Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

I’ve been thinking a lot lately about the purpose of public service and what public sector values really are. The public sector prioritizes something intangible: a duty to the public good.

There’s a lot of writing on exactly what this duty to the public good looks like, and last year I took my own stab at describing the purpose of the public sector (linked here if you’re interested).

I think I keep coming back to this question about values and what it means to be a public servant because there’s a growing sense that something in our public service culture may be slipping. I’ve heard very senior people go so far as to say it’s a driver of the increase in on-site presence to 4 days a week.

Recall that after John Hannaford took over as Clerk of the Privy Council in 2023, he stood up a Deputy Ministers’ Task Team on Values and Ethics. Its creation suggests that senior leaders felt there was a problem. The Task Team tied its mandate directly to the post-pandemic environment and the realities of hybrid work (Deputy Ministers’ Task Team on Values and Ethics, 2023).

The resulting report noted that there had been no systematic conversation about values and ethics since the Code was updated in 2012, and that almost 30 years had passed since John Tait’s landmark report, A Strong Foundation, which led to the first Code in 2003 (Task Force on Public Service Values and Ethics, 1996).

Now, the current Values and Ethics Code for the Public Sector (the Code) provides a formal, written expression of five core values: respect for democracy, respect for people, integrity, stewardship, and excellence. I wonder how many of us could name all five without looking them up.

The Code matters because it provides a shared language, establishes expectations, and describes how each of us, as public servants, should behave. But just reading the Code and memorizing it won’t teach you how to be a public servant. How do the words become part of someone’s judgment and behaviour?

Surely, things like knowing the Code and completing all the mandatory training are part of the process, but much of the more practical learning happens by watching other people: what is acceptable and what is not, how to handle difficult situations, and how to be that steward of the public good I alluded to earlier. It’s lived experiences that define what this abstract thing called public good means to each of us.

So, if values move through relationships and shared experiences, we should be asking what the conditions for these transmissions are and whether they are intact.

This week, we’ll look at organizational culture. We’ll explore how formal values translate into real behaviours, examine how recent changes in our environment might be weakening that process, and end with a call to action on what each of us can do to carry the culture we want forward to the next generation.

Grab your morning coffee, and let’s get started.

How values become lived practice

Let’s start with a reflection.

You likely got formal guidance from training that introduced you to basic principles and expectations. Through your daily work, you gave those ideas context. But, most importantly, you watched experienced colleagues.

This last part is key. Research on organizational culture shows that learning from others is an important way of passing down values.

Van Maanen and Schein (1979) call this process organizational socialization. It’s the process by which newcomers develop the social knowledge and skills (values, norms, and behaviours) in an organization. They propose six dimensions that shape how this happens.

One dimension is especially relevant to our discussion today: serial socialization. It’s about how experienced people guide newcomers. Van Maanen and Schein explain that these relationships are crucial because they teach not only the job's responsibilities but also how to work. These relationships pass on good things like sound judgment and shared norms, but also bad things like shortcuts, blind spots, and biases.

Lave and Wenger (1991) describe a process called legitimate peripheral participation. A newcomer starts at the edge of a community and, as they participate alongside experienced people, they move slowly inward toward fuller participation. They learn by being involved in the work and being a part of the community.

We can add a simple idea about tacit knowledge to this. Michael Polanyi (1966) argued that people know more than they can fully express. Things like judgment can be discussed, documented, and even taught, but some context is impossible to capture completely through rules or guidance.

Taken together, all of this suggests that formal guidance and social learning need to work together. So if we have the Code as a formal document that sets expectations, we also need to participate in, observe, coach, and receive feedback from the community to learn how to apply it.

Why the workplace matters

Okay, so that’s some of the theory, but what can we make of it?

It’s that the conditions surrounding how we learn about values and how we learn to be a public servant are critical. Newcomers need access to experienced colleagues, those who demonstrate the right values. And they need the opportunity to participate in meaningful work that demonstrates the right values.

Let’s bring in a related concept. Perry and Wise (1990) talk about public service motivation: the desire to contribute to the public interest through public institutions. They proposed motives that draw people towards public service. Importantly, their framework suggests that socialization is one way those motives may be developed.

Looking at public service motivation and public service values side by side, we see that they address interconnected questions. Motivation helps explain why someone wants to serve, and values guide how that service should be carried out.

But it goes both ways. Moynihan and Pandey (2007) looked at public service motivation among American state government managers. They found that elements of the professional environment affect public service motivation both positively and negatively, meaning that the workplace can help sustain or weaken a person’s duty to the public good. I think this finding will be intuitive to all of us.

Three conditions for value transmission

All of this together gives us a practical way to think about how values are transmitted in our organizations. I see three conditions:

1. Newcomers have consistent access to experienced people.

2. Teams are stable long enough to have shared norms

3. The overlap between newcomers and experienced colleagues is long enough for knowledge to be transmitted.

Has transmission eroded over time?

So, are these conditions that carry public service values still strong? Let’s look at a few recent factors that might be eroding them.

Hybrid work makes socialization a design responsibility

Hybrid work is an obvious place to start, and it’s the circumstance the Task Team itself flagged.

I’ll start by saying that the case for hybrid work is strong, and flexible work locations offer meaningful benefits to employees and organizations. But for today, I’m just going to focus on what hybrid means for the conditions for value transmission in our organizations.

Hybrid changes how newcomers engage with colleagues, observe, build relationships, and experience workplace culture. These changes make socialization something we need to design deliberately.

It’s worth highlighting that the Deputy Ministers’ Task Team reported concerns about things like virtual onboarding, reduced access to natural cues, and fewer conventional opportunities for dialogue. The report recommended improved training and dialogue, continued departmental conversations, senior-level governance, and support from the Canada School of Public Service.

Unfortunately, the report provides only broad direction on rebuilding these socialization mechanisms. It names who and what need to carry this forward, including deputy ministers, senior governance bodies, departments, and the Canada School of Public Service. However, it leaves the hard part about implementation unanswered: what effective socialization should look like in a hybrid environment, what minimum experiences newcomers should receive, and how progress should be measured.

I find this gap concerning. Taken one way, it could be seen as a coup de grâce against hybrid (hybrid is the culprit!). But, seen in a better light, the report should be taken as a call to action on how we do hybrid better, not just throwing the baby out with the bathwater.

My critique is supported by a 2025 meta-analysis by Bauer and colleagues, which examines what effective socialization requires. They reviewed 256 studies on the socialization process of newcomers into organizations (and included 183 in their analysis). They found that organizational socialization tactics, mentoring, and support from experienced people were consistently associated with social acceptance, role clarity, and task mastery. This is important because social acceptance was associated with outcomes like job satisfaction, commitment, performance, well-being, and reduced turnover (Bauer et al., 2025).

Specifically on virtual onboarding, the review found that research was limited and identified it as an open question for future research.

Going back to the conditions above, it’s important to ask how deliberately have we designed our hybrid workplaces to provide them?

Turnover shortens the window for transmission

A big contributor to turnover is the high internal mobility built into our system. Don’t get me wrong, internal mobility serves many useful purposes. It helps people grow, spreads knowledge and experience across the enterprise, and helps fill emerging or urgent needs. A key incentive is that movement is often the fastest and easiest way to advance.

There’s a downside. Frequent turnover means teams have less time to build shared norms and less experience to transmit. I don’t think this is a recent phenomenon, but it’s being accelerated, which is a concern.

The current wave of workforce reductions and incentives to depart is adding more pressure. Budget 2025 seeks to reduce the federal public service population from a peak of almost 368,000 in 2023–24 to roughly 330,000 by 2028–29, a reduction of about 40,000 positions. On top of this, the Early Retirement Incentive (ERI) creates another source of turnover. The program received 10,006 applications by the July 24, 2026, deadline. As of August 11, 2026, 8,161 applications had been approved, with only 42 denied. ERI participants are those experienced people whom newcomers need. They bring years of experience, relationships, stories, and institutional memory.

The accelerated rate of these departures presents a clear risk for value transmission. It effectively reduces overlap between experienced employees and those learning from them. This puts an even greater onus on how we introduce people to public service.

Onboarding creates the first shared experience

How we introduce people to the public service tells them what we believe is important. It’s a vital first impression that we only get once.

I remember that when I joined in 2010, I had to attend a mandatory 3-day introductory course on the public service in person in Halifax, where I lived and worked. I also remember older colleagues telling me that “back in their day,” all new public servants went to Ottawa for that course, which included tours of Parliament and the Senate, as well as meetings with politicians and senior bureaucrats. I know that version of onboarding only through their accounts of it, but it’s stuck with me all these years.

These experiences gave newcomers time and space to view their work within our democratic institutions. They also created opportunities to ask questions, build relationships, and develop a shared understanding of what public service requires.

I went and looked at the “mandatory” onboarding for new public servants in my department, and I wasn’t surprised to see it’s been watered down to a handful of click-through CSPS courses. Sure, there’s essential information in there, but is this experience starting people on the right foot? Is it building Perry and Wise’s public service motivation?

We may have saved a few bucks by scaling back on onboarding—but at what cost?

It’s nice that onboarding teaches people how to check their pay and submit a leave request. But it needs to go deeper to teach what really matters to helping newcomers become good public servants. It should ask:

• Does the newcomer understand the democratic purpose of the public service?

• Do they know how its values guide real decisions? Have they developed relationships with people they trust?

• Do they know where to turn when the right course of action feels uncertain?

When transmission weakens, the loss compounds

I’ll leave it to you to decide whether the way we transmit public service values is eroding and whether the conditions that support this transmission are thinning. I believe they are, and I’ll give a warning: the effects compound from one cohort to the next.

People can only pass on what they themselves have. Today’s newcomer is tomorrow’s transmitter. If a newcomer gets less to absorb, they pass on less. This is how the snowball grows. Each cycle shapes the next. Small gaps in things like onboarding, coaching, and shared experiences and norms accumulate, and the gap between the values the public service states and the behaviours people see around them grows.

The longer that process continues, the more difficult it is to stop and rebuild what’s been lost.

Each of us is part of the transmission

Hard to stop doesn’t mean impossible to stop. But a growing snowball gets harder and harder to stop, which makes taking action now even more important.

The solution starts with a recognition: public service values survive through people, and each of us is part of that transmission. Sure, the Code gives us shared words and commitments, but we carry them into day-to-day work through what we model, explain, reward, tolerate, and challenge.

This is the part I feel most strongly about. Don’t treat culture as something owned by others, by someone with more authority. There’s a deeper thing I’m trying to describe, call it pride, stewardship, or a commitment to doing good for people we may never meet, that belongs to all of us. It moves through each of our organizations in every direction, from anyone who lives it to anyone close enough to feel it.

So, the first step is to actually understand what these values mean beyond the words. The Code matters, and you should know it. But the sense of excellence that I’m talking about shows up in smaller things: flagging the error that no one would have caught, giving the advice the room doesn’t want to hear, reminding people what the real point of the work is, understanding why your contribution matters to Canada and Canadians, and treating every public dollar as something entrusted to us.

Then, take responsibility for passing it on. Coach the person coming up behind you. Explain the reasoning behind the steps. Bring junior colleagues into the room when values will be challenged or demonstrated, while the reasoning is still warm to the touch. These tacit things, like reasoning and judgment, are the very things that Polanyi says we can’t write down. We need to experience them to learn them. People need opportunities to observe them, discuss them, and practise them. Tell the stories of difficult decisions out loud so the lesson travels beyond the few people who were there.

Whatever your title, culture is your responsibility. Be deliberate about what others absorb from you.

Wrap up

The values we care about reached us through others. Whether on purpose or not, we learned by watching and by being in the culture. This culture, this sense of what the public service is and who we are, is critical. It shapes what it means to be a public servant. It gives us a shared sense of responsibility for democracy, for Canadians, and for one another. It also supports our legitimacy. Canadians need to trust their democratic institutions. They need to trust that the people in them will use sound judgment, protect the public interest, and live the values our institutions state.

The machinery that turns a newcomer into a steward of the public interest and a creator of public value keeps running only if we choose to keep it running.

Let me end on a request: Be someone worth watching, and make sure someone is watching.

Three questions to reflect on this week:

1. When you think back, who taught you what it actually means to be a public servant?

2. What do people around you learn about public service from watching how you work?

3. Who are you deliberately helping carry these values forward?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Bauer, T.N., Erdogan, B., Ellis, A.M., Truxillo, D.M., Brady, G.M. and Bodner, T. (2025) ‘New Horizons for Newcomer Organizational Socialization: A Review, Meta-Analysis, and Future Research Directions’, Journal of Management, 51(1), pp. 344-382.

Deputy Ministers’ Task Team on Values and Ethics (2023) Report to the Clerk of the Privy Council. Ottawa: Privy Council Office.

Lave, J. and Wenger, E. (1991) Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press.

Moynihan, D.P. and Pandey, S.K. (2007) ‘The Role of Organizations in Fostering Public Service Motivation’, Public Administration Review, 67(1), pp. 40-53.

Perry, J.L. and Wise, L.R. (1990) ‘The Motivational Bases of Public Service’, Public Administration Review, 50(3), pp. 367-373.

Polanyi, M. (1966) The Tacit Dimension. Garden City, NY: Doubleday.

Task Force on Public Service Values and Ethics (1996) A Strong Foundation: Report of the Task Force on Public Service Values and Ethics (J.C. Tait, Chair). Ottawa: Canadian Centre for Management Development.

Van Maanen, J. and Schein, E.H. (1979) ‘Toward a Theory of Organizational Socialization’, Research in Organizational Behavior, 1, pp. 209-264.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

A few issues ago, we looked at the Auditor General’s five spring reports side by side. We found a consistent theme: the visible parts of the work, the parts that were easy to count and show, got completed (mostly). The less visible parts, the ones that really determined whether the intended goals and outcomes were achieved, didn't.

In that issue, we touched on two concepts that might explain why this happens. Last time, we looked at Robert Merton’s goal displacement: the familiar way that a measure becomes the goal it was meant to represent.

Today, we’re looking at the second idea, which helps explain why organizations are vulnerable to that shift.

The idea is called legibility, and it’s central to James Scott’s 1998 book Seeing Like a State (Scott, 1998). It’s fairly intuitive and goes like this: government needs simplified versions of reality that it can record, compare, and act on. We see this every day in forms, surveys, categories, maps, dashboards and standard processes that reduce complex systems to something government can understand and manage.

This simplification is absolutely essential. First, a large public service could not function if it tried to understand every minute detail of a system; it’s just too complex. Second, it cannot tailor every benefit and service to every person’s exact circumstances, so it relies on shared categories and standards to provide comparable treatment across the country. Someone in Fredericton should be able to expect the same basic treatment from a federal program as someone in Victoria.

But, of course, there’s a risk to oversimplification. If we forget about the real world beneath it and mistake the simplified picture for reality, we lose all local knowledge and useful variation.

Scott begins with a real case about a forest oversimplified. A literal example of missing the forest for the trees. It’s an excellent illustration of the problem, so we’ll start there today.

Grab your morning coffee, and let’s get started.

How a forest became an administrative model

Scott starts with a story about German scientific forestry. It goes like this. From about 1765 to 1800, foresters in Prussia and Saxony developed methods to calculate the volume and revenue of timber in forests. To do this, they used a Normalbaum, or standard tree. Then, progressively throughout the nineteenth century, actual forest management increasingly made forests resemble the Normalbaum so they would more closely match the calculations. This meant fewer species, same-age stands, cleared underbrush, and perfectly straight rows.

From the state’s perspective, this worked quite well. Officials could count the trees, better predict the timber yield and issue standards that worked really well. All of this made harvesting easier and revenues more predictable. In essence, the forest on the ground began to match the forest in the books.

Although early results looked impressive, as time went on, officials began to see things the books had missed; things the simplifications smoothed out.

The thing is, the old forest depended on a number of key factors: nutrient cycles, decaying material, varied tree species, and symbiotic relationships among fungi, insects, plants, and animals. The standardization, which involved clearing and monoculture, completely disrupted all of this. The result was catastrophic. Growth declined, and the soil quality degraded. In addition, disease, pests and storms did more damage.

All of this did not go unnoticed by foresters. The effect was so prevalent that a new term was born to define it: Waldsterben, or forest death. There were significant efforts to reverse these effects, and another concept emerged: “forest hygiene.” This involved methods to reintroduce insects, birds, and other animals into the ecosystem.

Scott’s analysis here builds his entire thesis. The state has simplified its view to what it could measure, the Normalbaum, then reshaped the forest around that view. Everything outside that view was expendable until feedback from the forest revealed its true worth.

Scott opens with this forestry case as an illustration of legibility. He also puts this story inside a larger argument about high modernism: a deep belief in expert design, scientific progress, and the ability to order society from above. He goes on to look at cases of collectivization, Brasília, and Ujamaa villages. From these, he draws similarities and infers four conditions that must be present for these “planning disasters” to manifest: administrative simplification, high-modernist confidence, an authoritarian state willing to impose the plan, and a civil society unable to resist it.

Although contemporary public sector administration operates in a very different setting from 18th-century Germany, many of these factors persist today, and the main lesson remains valid: our “official” representation of a system or a group can begin reshaping the reality it was meant to describe.

Let’s pull on this a little more.

The knowledge that the system cannot fully record

Scott gives a name to what these simplifications miss. He calls it mētis and describes it this way. The practical skills and acquired intelligence gained through experience in changing circumstances. He notes that you can describe pieces of that knowledge, but its full value only appears in the moment someone uses it.

This reminds me of the contrast between a lesson identified and a lesson learned. It’s one thing to note something didn’t work and have an idea of how to improve, but it’s a whole other thing to try that idea and see the result.

Scott contrasts mētis with what he calls techne: the formal knowledge that can be stated as rules or principles, and verified and taught in standard form. Whereas mētis develops through experience in a particular setting, like repeated contact with a place, group, or process.

Most of our work in the public sector requires both. Formal knowledge (techne) provides consistency, transparency, and a basis for accountability. Practical knowledge (mētis) helps us apply those formal rules intelligently.

A good illustration of the difference between these two is the concept of work-to-rule. The French term grève du zèle, quite literally, “strike of zeal,” is much more colourful, especially when we consider the French definition of zeal: eagerness and dedication in serving someone or an idea; keen commitment to doing one’s work extremely well.

In work-to-rule, employees strictly follow written rules (techne) and withdraw things like judgment, adaptation, and cooperation (mētis). The effect is ironic: strictly following the rules as written is extremely detrimental. This tactic works because the “rulebook” doesn’t contain the whole job. It requires everything outside of it, too, to keep the work moving.

This directly connects to what we discussed last time about keeping rules and measures tied to purpose to mitigate goal displacement. When a rule handles a case poorly, people need the room to serve the purpose behind it. Mētis explains why this works because discretion is how practical knowledge reaches the formal system.

Of course, local knowledge also deserves scrutiny. Informal practices preserve bias, inconsistency and outdated ways of working. It’s the “we’ve always done it this way” monster rearing its ugly head. This is why we need both mētis and techne, with a meaningful connection between the two to enable them to correct each other: common rules protect rights and consistency, while feedback and discretion expose where those rules don’t work well.

A sharper picture can still be incomplete

I think Scott’s argument becomes more useful as government acquires better data. The collection and centralization of data through data lakes, real-time access and visualization, along with AI, can find patterns, process, analyze, and apply decisions at rates unthinkable to our 18th-century forester-administrators.

But they also make the official picture feel more complete than it actually is.

The OECD’s review of AI in government is a good place to see both sides. It looked at 200 real-world examples across 11 core government functions. It found that automation and modern tools support tailoring of services, better decision-making and forecasting, fraud and anomaly detection, and better job quality for public servants. However, they also create risks related to bias, transparency, explainability, and public accountability, especially when governments rely on poor data or weak human oversight (OECD, 2025).

In my view, the present-day extension of Scott’s argument is about confidence, not the technology itself. It’s the old saying from computer science: garbage in, garbage out. Bad data can be exposed with both mētis and techne. However, a polished dashboard built on bad data hides its blemishes and gives the impression that the data is good.

The dashboard is the Normalbaum. It’s a simplification that’s easier to manage than the underlying reality.

Uneasiness with this question should be the cue to step away from your screen to test the picture against the real world.

Keeping the picture open to correction

Back to Scott’s point about legibility: simplified versions of reality that can be recorded, compared, and acted on are necessary for effective governance. But discipline is important: we need to treat every simplification as a partial truth. When the feeling that it’s complete creeps in, this should act as a trigger to look deeper.

Three habits can help.

1. Name what is being left out

Start with the view that every simplification, standardization, or proxy leaves something out. Take time to think about what is being left out and the implications. For each, rate the impact and justify why leaving it out is acceptable.

Then use feedback to iterate and do this at effective intervals, such as right after key reporting milestones. Ask, “With my current simplifications, how good is my knowledge of what’s really going on, and is it still helping me to achieve the desired outcomes?”

Adapt and continue.

2. Build correction into the system

A simplification gets safer when the people with mētis can correct and improve it. Make sure the channel exists and assign someone to be accountable for it.

Test this by asking, “When was the last time someone on the frontline provided an improvement to our official picture?”

3. Go to the ground when the data looks perfect

This one follows from my philosophy on project dashboards. If it’s all green, it simply means you’re not looking hard enough for risks and issues; go back and look harder.

The more comprehensive the dashboard, the harder you should look at what it’s flattening and what you’re not seeing. It should prompt the question, “What are we missing?”

These habits are also well documented in the Government of Canada’s Digital Standards, which call for ongoing user research, frequent iteration, staff empowerment, and ethical service design. I encourage you to read them and put them into practice.

Wrap up

The techne gives government the common language it needs to be fair and accountable, by setting rules and standards. That common language and the simplifications it introduces will always describe a narrower world than the one people actually live in.

Our job is also to ensure that mētis, the practical knowledge techne leaves out, keeps the official picture open and honest.

Three questions to carry into your week:

1. For a simplification like a report or dashboard, what mētis is it failing to capture?

2. Where might a simplified picture be reshaping the work?

3. Who can tell you that the simplification is wrong, and who can correct it?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

OECD (2025) Governing with Artificial Intelligence: The State of Play and Way Forward in Core Government Functions. Paris: OECD Publishing. Available at: https://doi.org/10.1787/795de142-en.

Scott, J.C. (1998) Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. New Haven: Yale University Press.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Today, we’re following up on an idea from the sociologist Robert Merton that I leaned on in last time, in the article on the Auditor General’s five spring audit reports. He calls it “goal displacement.”

Goal displacement happens when a rule, process, or measure created to serve a purpose gradually becomes the purpose. Think of the rule everyone follows, but nobody can explain, the form completed because it has always been completed, or the metric a team works hard to report on, even when no one really understands why.

The means becomes the end.

Public services rely on rules and measures for good reasons. They support fairness, accountability, and consistent treatment, so a citizen in Fredericton can expect the same treatment as one in Victoria. That consistency helps large public institutions earn trust.

The arrangements that create consistency can also produce rigidity. Merton gave that problem a particularly influential bureaucratic account more than 80 years ago.

Today, we’ll start with Merton’s argument, follow how later researchers extended it from rules to targets and proxies, and close with four practices that can keep those means tied to their purpose and not some type of self-licking ice cream cone.

Grab your morning coffee (or ice cream!), and let’s get started.

Why reliability can produce rigidity

Merton began with Max Weber’s 1922 account of modern bureaucracy. Weber saw rules, hierarchy, expertise, and impersonal decision-making as major technical achievements. They let a large institution apply decisions consistently, preserve continuity as people change, and protect official work from personal favour (Weber, 1978).

Merton’s contribution was to examine the pressures created by that structure (Merton, 1940). Reliable behaviour requires discipline and a strong devotion to rules. Bureaucracies reinforce that devotion through training, defined authority, graded careers, promotion, pensions, and status. Together, these features reward methodical and cautious conformity.

Over time, that devotion can loosen from its original purpose. Merton described adherence to rules moving from an instrumental value, something useful for reaching a goal, into a terminal value, something treated as worthwhile in itself.

This is the displacement of goals.

Merton used a phrase from the economist Thorstein Veblen to explain part of the mechanism: “trained incapacity.” Under changed conditions, skills and habits that once worked well can become blind spots. A team that applies a policy flawlessly may struggle to recognize when the policy no longer fits the case at hand.

His most vivid figure is the “bureaucratic virtuoso,” the official who remembers every rule and becomes unable to assist many of the people the rules were created to serve. Many of us have encountered this pattern. Some days, we have embodied it ourselves.

How later work extended the idea

Merton focused on what happens when rules and routines acquire value of their own. Later researchers found related problems in measurement, incentives, and target systems.

In 1979, social scientist Donald Campbell described what became known as Campbell’s Law: the more heavily a quantitative indicator is used in decision-making, the more vulnerable it becomes to corruption pressure and the more likely it is to distort the process it monitors (Campbell, 1979).

Standardized testing was one of his examples. When test scores carry high stakes, teaching can narrow toward what the test rewards. The score still measures something real, while the pressure changes what people do to produce it.

Anyone who has prepared for a Second Language Evaluation may recognize the cause and effect here. Studying to pass the test over studying to achieve the desired outcomes of bilingualism.

A related idea became widely known as Goodhart’s Law. Anthropologist Marilyn Strathern gave it the form most people quote:

Campbell and Strathern sharpen Merton’s insight in an important way. A measure does more than describe behaviour; once it carries consequences, it shapes behaviour. People allocate attention, effort, and resources toward what the system recognizes and rewards. The indicator can improve even as its relationship to the larger purpose weakens.

What targets reveal and conceal

Gwyn Bevan and Christopher Hood examined this dynamic in the English National Health Service. The government had attached published ratings, reputational consequences, and management sanctions to national performance targets. Reported performance improved in several areas, including waiting times.

The same regime produced significant gaming, measurement gaps, and output distortions. Some providers changed booking practices or reported data in ways that helped them reach thresholds. The star ratings also had a weak relationship with some measures of clinical quality. These problems made the headline results harder to interpret (Bevan and Hood, 2006).

Bevan and Hood described a target as a synecdoche, one part standing in for a larger whole. Every target leaves something (many things) out. When the target carries enough weight, an organization can optimize the measured part while other dimensions receive less attention.

Their conclusion was measured. The evidence could not show how much gaming had undermined the reported improvements. They recommended stronger target design, better data audit, and monitoring capable of detecting predictable responses to pressure. Targets can focus attention and support improvement. Their design determines how much confidence we can place in the story they tell.

The most recent turn came in 2024, when Yohan John and colleagues gave the broader family of problems a name: proxy failure. When enough pressure is placed on an imperfect stand-in for a goal, the system begins optimizing the stand-in and its connection to the real goal weakens (John et al., 2024).

Goal displacement is one version of that problem. Rules, targets, and indicators make a messy reality manageable. Under enough pressure, the manageable part can become the part that receives the attention, funding, and care.

Keeping rules and measures tied to purpose

Careful thinking can reduce these persistent risks. In practice, we need to treat every rule and measure as a proxy borrowed from a purpose.

Here are four practices teams can use.

1. Name what the rule or measure serves

For any rule or indicator your team treats as important, finish the sentence: “We use this because…” If nobody can explain the connection to an outcome, the means may already be drifting.

Benefits management helps make that connection explicit by tracing outputs and new capabilities through outcomes to benefits. Leading indicators provide early evidence about whether a change is progressing. Lagging indicators show later effects. Both remain partial representations of the result, so use them together and check them against direct outcome measures and qualitative evidence.

Use early indicators to guide action. Continue measuring long enough to determine whether the intended benefit was realized.

2. Put the purpose on a schedule.

A measure can drift even as its value remains steady because the policy, service, or operating environment has changed. Build a purpose review into the same calendar as financial reviews and performance reporting.

Once a quarter, or at each major milestone, place the rule or measure beside its intended outcome and ask:

• Does this still tell us what we intended it to tell us?

• Has the purpose or operating context changed?

• Would we choose the same approach if we were starting today?

Give someone clear ownership of that review. A ten-minute check can identify a stale measure before it directs months of effort away from the intended outcome.

3. Pair high-stakes measures with balancing evidence.

When a measure carries consequences, ask how reasonable responses to pressure could improve the number while weakening the underlying outcome. Pair speed with quality, volume with usefulness or durability, and quantitative indicators with qualitative review or audit.

Benefits management also asks us to identify disbenefits, measurable negative effects that stakeholders may experience alongside the intended gains. Tracking them can reveal what a target is displacing and help teams choose useful balancing evidence.

More measures can create more proxies, so restraint matters. Choose the smallest set that reveals the main trade-offs, then test the story through cases, feedback, and professional judgement.

4. Protect discretion, and make it safe to use.

Rules protect fairness, rights, safety, and accountability, so discretion needs clear boundaries. Give staff criteria for recognizing exceptional cases, a documented route for seeking or using an exception, and leadership support when they exercise approved judgment.

Review recurring exceptions as evidence. If conscientious staff repeatedly need the same workaround, the rule or one of its assumptions may need to change. This creates a feedback loop between those applying the rule and those responsible for its continued fitness.

Wrap up

Merton’s insight remains useful because it names a recurring risk built into formal systems: rules and measures can drift from the purposes they serve. Later work shows how incentives and pressure can accelerate that drift. We can respond by making purpose explicit, reviewing measures, watching for displaced harm, and preserving bounded discretion.

Three questions to carry into your week:

1. Which rule or number does your team treat as fixed, and what purpose was it created to serve?

2. How might normal pressure make that number improve while the underlying result weakens, and what evidence would reveal it?

3. Where have we exercised discretion so tightly that staff struggle to adapt a rule while still meeting its public purpose?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Bevan, G. and Hood, C. (2006) ‘What’s measured is what matters: targets and gaming in the English public health care system’, Public Administration, 84(3), pp. 517–538.

Campbell, D.T. (1979) ‘Assessing the impact of planned social change’, Evaluation and Program Planning, 2(1), pp. 67–90.

John, Y.J., Caldwell, L., McCoy, D.E. and Braganza, O. (2024) ‘Dead rats, dopamine, performance metrics, and peacock tails: proxy failure is an inherent risk in goal-oriented systems’, Behavioral and Brain Sciences, 47.

Merton, R.K. (1940) ‘Bureaucratic structure and personality’, Social Forces, 18(4), pp. 560–568.

Strathern, M. (1997) ‘Improving ratings: audit in the British University system’, European Review, 5(3), pp. 305–321.

Weber, M. (1978) Economy and society: an outline of interpretive sociology. Edited by G. Roth and C. Wittich. 2 vols. Berkeley: University of California Press.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

This spring, the Auditor General tabled five performance audits: pay modernization, fiscal initiatives with First Nations, accessibility in the public service, RCMP recruitment, and reforms to the international student program. In looking at them together, there’s a common element: in each, the part that could be counted, funded, and pointed to was completed (the legible part); while the structural, slow, and hard-to-measure part was deferred (the illegible part). And in each report, the deferred part was the one that really tells us if the change or modernization actually worked (the outcomes we were trying to achieve).

Today we’ll unpack this. I want to start with pay modernization, since it is deeply familiar to all of us and clearly shows the pattern, especially in contrast to what was reported as the root cause of the whole Phoenix debacle. Then we’ll trace the same split, between what gets counted and what gets deferred, across the other four reports. And we’ll close on three things we can do differently when we scope the next reform, so the structural half stays on the table.

Grab your morning coffee, and let’s get started.

The pay file shows this pattern clearly

What did the Auditor General say in her report on modernizing the pay system? The audit (Office of the Auditor General of Canada, 2026a) found the project to replace Phoenix with Dayforce in its planning phase, with a first wave of three organizations, the Canadian Nuclear Safety Commission, Shared Services Canada, and Public Services and Procurement Canada, set to onboard in 2027, against a preliminary cost estimate above $4.2 billion.

Under the system's rules, the report found slow progress. After Phoenix, the government commissioned its own study, by Goss Gilroy, into what went wrong, and a central lesson was that pay rules should be simplified and standardized before a new system goes in, so the system does not need expensive custom shapes built around rules nobody streamlined. The AG found this lesson documented and understood. It also found the Treasury Board Secretariat had made slow progress in acting on it, because simplification depends on consensus with unions, and by the end of the audit period, the Secretariat had brought unions only one of the simplification areas it had identified, with no agreement reached.

The report then describes what the department did instead. Rather than wait for simplified rules, PSPC is having three custom applications, so-called “cloud extensions,” built so Dayforce can process the unsimplified rules as they stand, at an estimated cost of at least $4 million a year. The AG noted this is the kind of customization that Phoenix’s own lessons-learned had warned against.

The audit reported a similar pattern throughout the rest of the file. PSPC made progress clearing the pay backlog for first-wave departments, but the AG found it had not fully assessed how that prioritization affects departments onboarding later. The report also examined how timeliness is measured, and this one is worth pausing on, because anyone who has waited on a pay file will recognize it. The AG found PSPC uses a “stop-the-clock” approach, which counts only the time advisors actively work on a file and excludes the time the file spends waiting. Measured that way, reported timelines look considerably better than the wait an employee actually lives through. On top of that, PSPC compressed the schedule by three years after the audit period, and the AG found no indicators in place to confirm the new system would actually lower the cost of processing pay, one of the main reasons given for building it.

What gets counted gets done

Here’s the underlying theme that I found most interesting because I see it all of the time: the parts of the work that we can “see,” let’s call them the “legible” parts, are what get done. While the parts that are much harder to see, let’s call them the “illegible” parts, slip.

Two ideas explain why.

The first is about what large organizations are able to see. In Seeing Like a State, the political scientist James Scott describes how big bureaucracies act on the version of reality they can standardize, count, and map (Scott, 1998). The upshot is straightforward. What can be counted gets managed, and what resists counting, local knowledge, relationships, and informal practice, tends to be neglected, because the organization has no clean way to track or reward it.

Here is how that plays out in our large modernizations. A system going live, hardware installed, click counts, dollars spent, time spent, all of it is legible: it can sit in a status report under a named owner. Simplifying rules, co-developing a policy with partners, understanding why an indicator moved, none of it is. Under pressure to show progress, an organization does the legible work first because that is the work it can actually see itself doing.

The second idea is about what happens once the legible work is underway. The sociologist Robert Merton described the process now known as goal displacement, in which the measurable proxy for success slides into becoming the goal itself, so people end up serving the indicator rather than the objective it was meant to represent (Merton, 1940). In the pay file, the objective is to ensure accurate, timely pay for public servants; the proxy is a system delivered on schedule. The gap between those two is exactly where the cloud extensions and the unsimplified rules sit. Once the proxy becomes the target, hitting it can feel like success while the real objective drifts.

Put those two together: An organization does the part of the reform it can see, then treats that part as the whole. With that in hand, the other four audits start to look an awful lot the same.

The same pattern, four more times

The fiscal initiatives with First Nations

The audit (Office of the Auditor General of Canada, 2026b) found the 10-year grants delivered as designed, with more than $6.5 billion provided to recipients by the end of 2024-25. The other two commitments from 2017 were not met: the Default Prevention and Management Policy was not replaced with a capacity-building policy, with the AG noting the department cited insufficient funding, and a mutual accountability framework was not developed. The AG also found the department did not assess whether the grants were closing the socio-economic gaps they exist to address.

A set sum paid on a schedule is straightforward to confirm and report, and that is the commitment that was kept. Co-developing a replacement policy and building mutual accountability with partners are structural and slow, and those are the commitments that stalled. The money moved. Whether it advanced self-determination or closed any gap is the question the department left unanswered.

Accessibility in the public service

The accessibility audit (Office of the Auditor General of Canada, 2026c) found that all seven organizations examined reached the 7% disability representation goal. It also found their processes could not handle the volume of accommodation requests, that data on those requests was collected inconsistently, and that where organizations did not track resolution times, requests took, on average, hundreds of days to resolve.

Reaching 7% is real progress, and a representation percentage is also as legible as a number gets, easy to track and to show moving. The daily experience of an employee waiting on an accommodation is far harder to see, and harder still to put in a status report. The countable goal was met while the slower work of fixing accommodation processes was left undone.

RCMP recruitment

The RCMP recruitment audit (Office of the Auditor General of Canada, 2026d) found that the force’s Flexible Posting Plan, which let cadets choose their first posting, drew thousands more applications. It also found the RCMP had narrowed its workforce planning in 2023 to front-line policing, no longer knew how many officers it needed across the whole force, and saw chronic vacancies in hard-to-staff divisions get worse.

This is perhaps the clearest version of the pattern, because here the legible number did not just sit on top of a stalled prerequisite; it actively pulled against it. Application volume is a clean, easy-to-understand metric. The kind that signals momentum to anyone reading a dashboard. Knowing the true size of the force’s need is harder analytical work with no satisfying number at the end of it (a lose-lose most likely), and that is the work the RCMP set aside. The result is an organization that looked busier and better resourced on the easy-to-see metric, while the structural understanding that was supposed to guide all that recruiting thinned out underneath it. A transformation can be moving quickly and losing ground at the same time, and the legible number will not tell you which is happening.

International student reforms

The international student reforms audit (Office of the Auditor General of Canada, 2026e) found that IRCC reduced the number of new study permits well past its target. It also found that the department could not explain why its approval rates fell so far below projections, did not adequately monitor the heavier-than-expected impact on smaller provinces, and made limited progress on the more difficult integrity and diversity work the reforms also called for.

The permit count is the Globe and Mail number. Understanding why approvals collapsed, tracking where the cuts landed hardest, and following through on integrity enforcement are ongoing, investigative, and far less legible. The number came down on schedule, but the department’s grasp of what it was doing did not keep pace.

Naming the half that does not show up in a status report

If the pattern is this consistent, the response has to be structural, because nobody in these audits was failing to try. What needs to change is how a reform gets scoped in the first place.

Three changes are worth building in.

The first is to name the structural work out loud, at the very start. A system launch arrives with a champion, a budget line, and a project name. The prerequisite underneath it, the rule simplification, the policy co-development, the process redesign, usually arrives with none of those, and work that nobody names is work that gets deferred by default. When a reform is being scoped, one question belongs on the table before anything else: what outcomes are we actually trying to achieve, and how will these show up in a status report? Write it down next to the deliverable, so keeping it or dropping it becomes a deliberate decision rather than a hidden one.

The second, following the first, is to decide how you will measure the real outcome before the project starts. This echoes a recommendation the AG made directly in the pay file, that PSPC develop indicators to confirm whether processing costs actually fall under Dayforce. The discipline generalizes to any reform. If the only thing instrumented at the outset is the proxy, the proxy is what the organization will manage, and it can be years before anyone can say whether the actual goal was met. Building the measure of the real objective into the plan from the start keeps success something to be earned rather than declared.

The third is to sequence and fund the structural work ahead of the visible deliverable. The pay file is the cautionary case: rule simplification was the documented prerequisite, and it still lost to the system schedule, because the schedule had funding and a deadline, while the simplification had neither. The AG made a similar observation about the stalled replacement policy for First Nations default management, which the department attributed to insufficient funding. A prerequisite that runs on goodwill and spare capacity, while the deliverable runs on a budget and a deadline, loses every time. If the structural work genuinely has to come first, the funding and schedule have to reflect that.

Wrap up

Across five audits in five unrelated corners of government, the same thing happened. The visible and fundable half of each reform moved forward while the structural half, the half that decided whether it worked, lagged behind or stalled. The encouraging part is that this is a predictable result of how large organizations see, which means we own it as a design choice and can change it the next time we scope a piece of work.

Three questions to carry into the next big project you’re closest to:

1. What is the part of this change that will never appear in a status report, and what happens to the goal if it is skipped?

2. Is the prerequisite work funded and sequenced before the visible deliverable, or is it expected to keep pace with only goodwill?

3. Does anyone measure the actual outcome, or only the proxy that is easy to report?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Merton, R.K. (1940) ‘Bureaucratic structure and personality’, Social Forces, 18(4), pp. 560–568.

Office of the Auditor General of Canada (2026a) Modernizing the Pay System. Ottawa: Office of the Auditor General of Canada.

Office of the Auditor General of Canada (2026b) New Fiscal Initiatives With First Nations. Ottawa: Office of the Auditor General of Canada.

Office of the Auditor General of Canada (2026c) Accessibility in the Public Service. Ottawa: Office of the Auditor General of Canada.

Office of the Auditor General of Canada (2026d) Recruiting for the Royal Canadian Mounted Police. Ottawa: Office of the Auditor General of Canada.

Office of the Auditor General of Canada (2026e) International Student Program Reforms. Ottawa: Office of the Auditor General of Canada.

Scott, J.C. (1998) Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. New Haven: Yale University Press.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

It’s worth saying up front that running a major federal IT transformation is genuinely hard, and the people doing it are good at their jobs. Currently, several major transformations are underway. The systems behind Old Age Security (OAS), Employment Insurance (EI), and the Global Case Management System for immigration (GCMS), are knit into legislation and policy in ways that make every change consequential, and serve millions of Canadians who can’t afford a bad rollout… Not to mention the whole HR and Pay system debacle. Oversight machinery exists for real reasons. Treasury Board submissions are meant to induce disciplined thinking. Audits surface what would otherwise stay hidden. Cost authorities create accountability.

And yet, we have ESDC’s Benefits Delivery Modernization (BDM), IRCC’s Digital Platform Modernization (DPM), and PSPC’s post-Phoenix HR and pay work all running concurrently, and the same story keeps coming back. Original commitments slip, and re-baselining gets harder to explain each time. The Auditor General writes a report warning the next programme not to repeat the mistakes of the last one (e.g. Office of the Auditor General of Canada, 2023). Inside the programmes, leaders who clearly see the trade-offs of their decisions take them, but we rarely document the rationale or decision process in a way that makes them easy for others to find or fully understand.

While working on something else, I recently came across a framework that names the trade-offs we’re being asked to take and gives us a way to defend the responsible ones. From my time doing oversight at the Treasury Board Secretariat (TBS), I saw many of these projects up close. Even a couple of years on, I keep coming back to the question of why the same pattern keeps repeating, and this framework gave me an interesting way to look at it.

This week, we’ll start by walking through that framework, then look at why one of its four boxes is the one any serious transformation has to live inside, and finally, why our governance regime structurally has difficulty supporting this. Then we’ll talk about what to do about it (yes, with kindsight, and I fully acknowledge I’m playing Monday morning quarterback here).

Grab your morning coffee, and let’s get started.

The quadrant we need most

The framework I want to use comes from a metaphor that’s been kicking around software engineering since the early 1990s. Ward Cunningham (1992) introduced “technical debt” to describe what happens when a team ships a shortcut in software design. I’m sure many of you have heard this term before, but are we using it effectively? For Cunningham, he meant that the system works in the short run, but every future change has to push through the shortcut, as interest payments compound on a loan. The shortcut is the principal. The extra effort to work around it later is the interest. The metaphor caught on partly because it gave engineers a way to talk to executives in language executives understood.

The trouble is that it’s too easy to use loosely.

“Technical debt” gets used more and more as a euphemism for “we cut corners, and the system is now hard to work with,” or, more so in my experience, “the system is old and failing.” This is a bit of a soapbox of mine, and could fill its own post sometime. In my role at Shared Services Canada, I often hear IT executives use “technical debt” as if it’s always a bad thing, when what they really mean is “aging or legacy IT,” which carries a very different context. It’s a bit like calling all financial debt bad. We intuitively know that a frivolous high-interest credit card balance is a very different beast from a 25-year mortgage.

Technical debt has flavours too.

Martin Fowler’s 2009 essay was a response to this pattern. Fowler (2009) argued that the metaphor only does useful work when we distinguish between debts taken responsibly and debts taken carelessly, and between debts we knew about at the time and debts we only see in retrospect. He laid out a 2x2 matrix across those two dimensions, which Kruchten, Nord and Ozkaya (2012) later picked up and built on.

Here’s what the 4-quadrants look like:

Inadvertent-reckless debt is what you take when you don’t know what you don’t know. The team that didn’t realize it should design for layered architecture lives here.

Inadvertent-prudent debt is what good teams notice after the fact: “Now we know how we should have done it.”

Deliberate-reckless debt is the dangerous quadrant: “We don’t have time to think about design, just ship it.”

Deliberate-prudent debt is the most mature posture available to anyone running a serious build: “We have to ship in the next quarter, so we’ll defer the proper data model and put it on the roadmap, and here’s how we’ll live with the cost in the meantime.”

For any real transformation, the no-debt plan is fictional. BDM’s original 2017 plan, costed at $1.75B with a 2030 finish line and full transformation included (Office of the Auditor General of Canada, 2023), was as fictional as any transformation plan ever is. The question that’s actually in front of a senior leader is which debts to take with eyes open. Deliberate-prudent debt, the kind that gets named, justified, and managed, is the quadrant where ambitious transformations have to live.

ESDC’s choice to migrate OAS ahead of EI is recognizable as exactly this kind of decision. The OAS systems were the oldest and at highest risk of failure (OAG, 2023). Moving them first protected continuity, at the cost of delaying the transformation work originally scheduled for EI. That’s a sequencing trade taken on purpose, with a clear reason and a plan.

Textbook deliberate-prudent debt.

Why our governance can’t hear it

Here’s where things get a little uncomfortable. Things like Treasury Board submissions, gating reviews, and audit follow-ups share a structural feature: any acknowledged trade-off becomes a finding, a risk to manage, or a deficiency. There is no part of the template for “we’re taking this debt on purpose because the alternative is worse.” The AG’s critique of BDM’s “inflexible funding approach” (OAG, 2023) is exactly this dynamic. Gated tranches require the next tranche to be justified by the previous one’s claimed success, leaving no room to say “the prudent debt we took on phase one needs to be settled now, before we go further.”

Two theories help explain why this dysfunction is tough to crack. The first comes from Nils Brunsson, whose work on organizational hypocrisy (Brunsson, 2002) argues that when an organization faces incompatible external demands, the functional response is decoupling: talk, decision, and action are separated. Applying this to our context, the public service is asked to deliver an ambitious transformation while demonstrating no compromise, no risk, and no debt, all at the same time. Those demands cannot both be satisfied. So the formal record denies the trade-off (talk), the actual programme takes it (action), and the retrospective renames it (talk again). The institution is functioning as designed.

The second comes from Christopher Hood (2011), who argues that public-sector decision-making is strongly influenced by a blame-avoidance bias. The political asymmetry between blame and credit means most senior moves are shaped by “how do I avoid being blamed” before “how do I succeed.” Phoenix is the canonical example, of course. The 2018 OAG report found that the executives who briefed the Deputy Minister on Phoenix’s readiness emphasized adherence to budget and schedule and omitted critical concerns about testing and unresolved defects (Office of the Auditor General of Canada, 2018). These were people responding rationally to asymmetric incentives. Naming the debt openly was a free gift to future critics, with no offsetting upside if the bet paid off.

The two theories stack. Brunsson explains why the institution demands decoupling. Hood explains why individual leaders rationally provide it. The result is the pattern we see across BDM, DPM, and the post-Phoenix HR and pay work: debt taken and disguised, debt refused that should have been taken, debt buried with no documentation of why. The AG’s explicit warning to BDM that ongoing pressure could lead the programme to scale back transformation or take shortcuts the way Phoenix did (OAG, 2023) is the OAG telling the programme it can see the dynamic forming again.

The translation

Here’s the kindsight part: Treasury Board and the central agencies should change how they frame oversight so that prudent debt has somewhere to live in the formal record, or even stronger perhaps, obligies it be documented and followed.

I’d like to propose that a translation of language is needed, and I see three pieces to it.

1. Speak the language oversight already accepts

The substance of “we are taking this debt on purpose” maps cleanly onto vocabulary the system already understands. A deferred technical decision becomes a risk register entry with explicit trigger conditions for revisiting. A phasing choice becomes a sequencing decision tied to a specific future review gate. Partial scope becomes MVP or stabilize-before-transform, costed at the level of detail the system requires. This changes the vocabulary, but the underlying decision is identical to what the technical-debt literature would call deliberate-prudent debt. IRCC’s DPM did this when it named Phase 1 as a stabilization phase aimed at reducing accumulated technical debt in the legacy, and structured Phase 3 as iterative tranches that release capabilities as they’re ready.

Likewise, PSPC’s $135M Budget 2024 allocation, framed as “testing and design” (PSPC, 2024) and deliberately stopping short of a committed end-state build, does the same job at the front end of a programme: refusing to commit to a fixed end-state until learning has happened, in language oversight can receive.

2. Keep an internal record that survives the transition

This is the part that protects future leaders from inheriting decisions they cannot reconstruct. Inside the programme, maintain something like a debt register that lists each deferred item, the rationale at the time the decision was made, the conditions that would trigger revisiting it, and the cost of leaving it unresolved. Pair this with architecture decision records, which capture what alternatives were considered and why the chosen option was selected.

Go further and tag each entry to the specific TB submission paragraph or gate review it relates to, so the parallel record and the formal record can be read together. When mandates change or senior leaders rotate out, brief the incoming team on the debt register first, before the formal record.

In general: any decision-making system that requires public denial of trade-offs needs an internal record to keep the trade-offs survivable.

3. Hold the line between translation and cover

Translation works only if it stops short of “air cover.” Its purpose is to name the trade-off in a form that oversight can receive, and to leave a real record for the people who come next. A submission that translates “we will take three months of schedule debt to migrate the highest-risk legacy first” into “we are sequencing the highest-risk migration ahead of full transformation to protect benefit continuity” is doing translation. A submission that omits the trade-off entirely and describes only the nominal end-state is doing cover.

The first description is recognizable in how ESDC handled OAS sequencing, where the trade-off was named in the formal record. The second is closer to what the 2018 audit found PSPC had done with Phoenix, where critical readiness concerns were omitted from briefings to leadership.

Here’s an honesty test for any leader accountable for a TB submission: would a successor, reading both the formal record and the internal debt register five years from now, recognize the same trade-off in both? When the formal record and the internal record line up, that’s translation. When they diverge in substance, that’s cover.

Wrap up

I believe one reason why our largest transformations like BDM, DPM, and the post-Phoenix work, keep producing the same story arc is that the culture of oversight they’re given makes it difficult for prudent trade-offs to be documented honestly. They either get refused, disguised, or buried for the next person to discover. Changing the narrative might be a way to overcome this: speaking deliberate-prudent debt in language the system can receive, and building the parallel record that lets today’s prudent choice still look prudent to the people who inherit it.

Let’s end with some self-reflection:

1. In your current or most recent transformation, what debts did the formal plan claim were not being taken, that the actual delivery has had to take?

2. Who, if anyone, in your organization knows the real rationale for the trade-offs embedded in your major IT systems, and what happens to that knowledge when they leave or when the mandate changes?

3. What would change in your next Treasury Board submission if you committed to translating the prudent debt you intend to take in a form that leaves it visible to your successor?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Brunsson, N. (2002) The Organization of Hypocrisy: Talk, Decisions and Actions in Organizations. 2nd edn. Copenhagen: Copenhagen Business School Press.

Cunningham, W. (1992) ‘The WyCash Portfolio Management System’, ACM SIGPLAN OOPS Messenger, 4(2), pp. 29–30.

Fowler, M. (2009) ‘Technical Debt Quadrant’, martinfowler.com, 14 October. Available at: https://martinfowler.com/bliki/TechnicalDebtQuadrant.html.

Hood, C. (2011) The Blame Game: Spin, Bureaucracy, and Self-Preservation in Government. Princeton: Princeton University Press.

Immigration, Refugees and Citizenship Canada (2023) IRCC Minister Transition Binder 2023: Digital Platform Modernization and IT Upgrades. Ottawa: IRCC.

Kruchten, P., Nord, R.L. and Ozkaya, I. (2012) ‘Technical Debt: From Metaphor to Theory and Practice’, IEEE Software, 29(6), pp. 18–21.

Office of the Auditor General of Canada (2018) 2018 Spring Reports of the Auditor General of Canada, Report 1: Building and Implementing the Phoenix Pay System. Ottawa: OAG.

Office of the Auditor General of Canada (2023) 2023 Reports of the Auditor General of Canada, Report 8: The Benefits Delivery Modernization Programme. Ottawa: OAG.

Public Services and Procurement Canada (2024) The Government of Canada provides update on progress toward a new human resources and pay solution to replace the Phoenix pay system and its human resources systems. News release, 9 July. Ottawa: PSPC. Available at: https://www.canada.ca/en/public-services-procurement/news/2024/07/the-government-of-canada-provides-update-on-progress-toward-a-new-human-resources-and-pay-solution-to-replace-the-phoenix-pay-system-and-its-human-.html

Share Beyond the Status Quo: Leading Public Sector Transformation

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Many of us have read post-mortems, audits, or the “lessons-learned” compendium that follow initiatives, usually when things have gone wrong. The work behind those documents is real, and sometimes it’s excellent. Capturing what went wrong, identifying the contributing factors, and circulating the findings is a genuine attempt to ensure the next program does better.

But, then, why do we keep making the same mistakes?

It’s a question that Bent Flyvbjerg and colleagues try to answer in a new study, “'Do projects learn across space and time? Evidence from the Olympics'“ published in Public Management Review (Ansar, Flyvbjerg, and Budzier 2026).

(Yes, I have a Google Scholar alert set up for any new Flyvbjerg publication. Anyway...)

The study is nominally about the Olympic Games, which are interesting because they repeat every four years and remain mostly consistent in scope. But the authors are clear that what they’re studying is a public management problem: how large, dispersed, repeating initiatives learn, and why most of them don’t. What struck me reading their findings is how directly the diagnosis maps onto how we deliver complex work in the public sector.

Today, we’ll walk through what the authors found, why their diagnosis is broadly applicable to our work, the four strategies they offer for breaking the pattern, and the precondition these strategies depend on.

Grab your morning coffee, and let’s get started.

Sixty-four years, twenty-three Games, no improvement

Here’s a high-level overview of the paper's argument.

The Olympics are, on paper, an ideal setting for organizational learning. They happen every four years, the events are largely consistent, and the technical, logistical, and operational requirements repeat from one Games to the next. By any reasonable theory, costs should come down, schedules should tighten, and risks should shrink as host cities and the International Olympic Committee accumulate experience.

The data show none of this. Across all 23 Games from 1960 to 2024 with reliable cost figures, the authors find no sustained reduction in the magnitude, frequency, or variance of cost overruns over 64 years. The average overrun runs at about 159 percent in real terms. Across 23 major project types studied in Flyvbjerg’s broader research program, only nuclear waste storage performs worse in terms of cost.

Reform efforts haven’t moved the underlying numbers. The IOC’s Agenda 2020 was meant to bring discipline. Paris 2024 was sold as a “lean Olympics” with 95 percent of venues already in place, yet it still overran by 115 percent.

The authors are emphatic that the people delivering each Games are skilled, and that tactical learning is everywhere within individual Games. The puzzle is why none of it aggregates into something durable. That’s where their diagnosis gets interesting.

Why the Olympic structure is built to forget

The authors view the starting point as a classic concept in organizational theory: the myopia of learning (Levinthal and March 1993). Organizations are systematically shortsighted in three ways. Spatial myopia: they overweight nearby experience and underweight what they could learn from elsewhere. Temporal myopia: they overweight the recent and underweight longer historical patterns. Failure myopia: they overweight successes and under-record failures, building organizational histories that flatter the institution and erase the evidence it most needs.

The authors add that in some delivery models, these three myopias compound. They call the resulting condition spatiotemporality: geographic dispersion, multi-year gaps, and the temporary form of the delivery organization combine to make higher-level learning nearly impossible.

The Olympics are an extreme case. Each Games is staged in a different city, four years apart, by a host committee that assembles, delivers, and disbands. The authors describe this as a franchise model: the IOC is a permanent franchisor that sets the rules and coordinates knowledge transfer; each host committee is a temporary franchisee.

Here’s how it compounds. In a permanent organization, distance and time are challenges, but manageable ones: people from the last project are still there for the next, tacit knowledge sits in the same building, and institutional memory persists. In a temporary delivery organization, those compensating structures are absent by design. Knowledge has to be transferred across geography, across years, and across teams that have never met. The barriers stop being additive and become multiplicative.

The pattern shows up vividly in something one of the authors heard from the CEO of a large real-estate firm: despite his organization having built projects continuously since 1973, every new project felt as though they had never built anything before. Flyvbjerg and colleagues call this the eternal beginner syndrome (Flyvbjerg, Budzier, and Lunn 2021). Public delivery models with the three features, work spread across distance, multi-year gaps between iterations, and teams that come together for one program and then dissolve, are vulnerable to the same dynamic. Many of the biggest ones have all three.

When tactical learning gets mistaken for the strategic kind

A useful distinction from the organizational learning literature, first proposed by Fiol and Lyles (1985), separates lower-level from higher-level learning. Lower-level learning is the tactical kind: procedural improvements within existing routines, better checklists, sharper handoffs, smarter logistics. Higher-level learning involves shifts in the underlying assumptions, delivery models, and norms of the organization itself.

The Olympics show abundant lower-level learning. Successive Games have produced real improvements in crowd management, venue accessibility, anti-doping protocols, and security after the tragic events of Munich 1972 and Atlanta 1996. None of that shows up in the cost data over 64 years.

The authors are critical of this. They critique what they call “learning legacies”, the post-event summaries produced after Games like London 2012, as fragmented tactical learnings celebrated as if they were strategic. The risk, they argue, is that learning legacies become political rhetoric without substantial impact.

For me, this is the most uncomfortable part of the paper. Our gate reviews, audit reports, closeouts, and lessons-learned exercises are the same genre. Some are excellent on tactics. Many produce documents that the next program team reads, but then fail to change the underlying delivery model.

A question worth asking: when we point to a “lessons-learned” report as evidence we’ve learned, what specifically did the next initiative do differently because of it? Anyone I’ve worked with knows this is a point I make all the time: we can’t call something a lesson learned until we actually learn it. Maybe my hard line on this distinction comes from when I cut my teeth as a public servant at DND, which has a robust framework and makes the explicit distinction between a lesson identified (we noticed something) and a lesson learned (we changed how we operate). Most “lessons-learned” reports I’ve seen are doing the first while claiming the second, and celebrated at that.

Four strategies, three of them radical

The authors identify four archetypal strategies that permanent organizations have used to overcome spatiotemporal barriers, each illustrated with a company that has used it well. The four are worth carrying into our own work as a menu of structural choices.

The first is incremental (Ferrari, Holiday Inn, IKEA, McDonald’s): continuous improvement within a stable structure, with clear accountabilities, codified routines, and repeatable formats prior to full modularity. In the public sector, this is the world we live in: refreshed project management methodologies, gateway and stage-gate reviews, maturity models, central-agency guidance changes, mandatory training, and “stronger” governance bolted onto each new initiative. It’s the strategy many of our delivery systems have defaulted into. The IOC has been pursuing the same approach for years through guidelines, roving expert teams, and reform packages like Agenda 2020. The 64-year data show it has not produced higher-level learning at the Olympics.

The second is centralizing (Apple): consolidate delivery in one or a few permanent locations to accumulate expertise, infrastructure, and memory. For the Olympics, the authors mean a permanent host city. The public-sector parallel is standing up a permanent delivery agency for a class of work, a major IT modernization shop, an enduring infrastructure delivery body, and a permanent benefits transformation team that builds and retains capability across successive programs. We’ve seen recent examples of this here in Canada: Build Canada Homes and the Major Projects Office come to mind. What they have in common is continuity of staff, tooling, and method that persists across successive projects and accumulates real institutional memory and expertise. (A thought: why not a major IT/transformation equivalent?)

The third is decentralizing (Toyota): distribute work across specialized permanent nodes that each become world-class at one component, with deliberate knowledge transfer between them. The Olympic version would be permanent global homes for individual events. The public-sector version would be a network of specialized permanent delivery institutions, one for digital services, one for major procurement, one for benefits delivery, one for grants and contributions, each accountable for depth in its component and each feeding learning into the network. The capability lives in the institutions and persists across initiatives.

The fourth is real options (Merck, Netflix): build flexibility in through sequential, staged commitments that can be expanded, paused, or abandoned as evidence emerges, in place of locked-in big-bang plans. In the public sector, this means structuring a major programme as a sequence of authorized stages: a six-month proof of concept, then a twelve-month pilot, then a phased rollout, with each stage funded and approved only on the evidence produced by the one before it. What cabinet and central agencies approve at the outset is the staging discipline itself, with full data feeding go-or-stop decisions at each gate. This was the idea behind the Deputy Minister Committee on Core Services (DMCore). The implementation didn’t quite meet the intention.

The authors’ verdict travels well: incrementalism alone is the one option the 64-year evidence shows does not produce higher-level learning. The other three require structural reform, with different governance, funding, and accountability arrangements. None is automatically right for any given initiative. The point is that the choice should be deliberate, because drifting into incrementalism by default produces the outcomes documented by 64 years of evidence.

The harder part is letting ourselves see it

There’s a precondition for any of these strategies to work. Levinthal and March’s third form of myopia, the failure kind, is the one most relevant to public administration. We over-remember our successes and under-record our failures because political incentives push that way. Acknowledging that a delivery model has been producing predictable failures for a long time is professionally and politically costly.

The authors invoke Rayner’s (2012) concept of “uncomfortable knowledge” and call for what they describe as radical candour: a willingness to confront challenging evidence directly, including evidence about what our own delivery model is actually producing. Without that, the four strategies are unread papers on a shelf.

This is the part of the diagnosis that’s hardest to sit with. Structural reform is difficult. The willingness to name what our structures are producing, in language straightforward enough for the people who’d have to fund and authorize a different model, is harder still. The structures themselves are downstream of whether we’re willing to look at the data with clear eyes.

Wrap up

This study offers us three key takeaways: a structural diagnosis for why dispersed major programs keep failing in the same ways; the distinction between tactical post-mortems and the higher-level learning that actually changes the next program; and four options for strategic responses, three of which require more than tinkering. The pattern in our biggest delivery failures is structural. That’s the bad news, because tactical fixes won’t reach it. It’s also good news because the structure is ours, which means we can redesign it.

Three questions to sit with this week:

1. Does your delivery model have a “franchise structure”, a permanent overseer paired with a temporary delivery team that disbands at completion, and what does that team take with it when it goes?

2. The “lessons learned” or post-mortem report you are most proud of: what did it specifically change about how the next program was delivered? If you can’t name something concrete, what does that tell you?

3. If you were honest about which of the four strategies your current model is closest to, which one would it be? And is it the one you meant to pick?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Ansar, A., Flyvbjerg, B., and Budzier, A. (2026) ‘Do projects learn across space and time? Evidence from the Olympics’, Public Management Review. https://doi.org/10.1080/14719037.2026.2650426

Fiol, C. M. and Lyles, M. A. (1985) ‘Organizational learning’, Academy of Management Review, 10(4), pp. 803–813.

Flyvbjerg, B., Budzier, A., and Lunn, D. (2021) ‘Regression to the tail: why the Olympics blow up’, Environment and Planning A: Economy and Space, 53(2), pp. 233–260.

Levinthal, D. A. and March, J. G. (1993) ‘The myopia of learning’, Strategic Management Journal, 14(S2), pp. 95–112.

Rayner, S. (2012) ‘Uncomfortable knowledge: the social construction of ignorance in science and environmental policy discourses’, Economy and Society, 41(1), pp. 107–125.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

It’s the start of a new fiscal year, and it’s the first where departments are seeing their budgets reduced as part of the Comprehensive Expenditure Review, which is aiming for broad savings across the board over the next three years, reaching 15 percent by 2028-29.

If there are ways for us to deliver more efficiently and cost-effectively, we should do it, and the CER is forcing departments to rethink and challenge their spending.

But one interesting part of all of this is the human factors that come into play. Generally, in a department, every branch is asked to find its share. Label what’s critical, identify what can be cut, then work to generate savings.

But then there’s this interesting dance that happens. Branches think, “On the one hand, if we propose too many things and others don’t, there’s no taking it back, and our stuff will get the axe. On the other hand, if no one proposes enough, we’ll have to do another round, so I need to leave some things on the table that can be cut later.” We think to ourselves, “I don’t want to be punished for playing fairly if someone else doesn’t.”

We go around in circles, and inevitably, we complain that nobody is playing as one team.

In thinking about this, I see parallels to game theory and a famous thought experiment that tells us this is predictable behaviour: this defensive posture is the rational play when we design the exercise the way we have. And running cost-cutting exercises without changing that design is a choice to accept defensive behaviour as the operating mode and, ultimately, to achieve a less effective result.

We’ll explore this idea today and think about what we can do differently. We’ll start by looking at the famous prisoner’s dilemma paradox, then connect it to how cost-cutting exercises typically run, look at what gets hollowed out when this dynamic plays out over multiple rounds, and finish with ways we can actually change the equilibrium.

Grab your morning coffee, and let’s get started.

A defensive posture is the rational play

The prisoner’s dilemma is a paradox in game theory that reflects a common problem in real life: individually rational choices can lead to a worse outcome for everyone. Here’s how it works. Police have two suspects in custody and are questioning them separately. Each is offered the same deal. If both remain silent, each receives one year on a minor charge. If one testifies while the other remains silent, the one who testifies walks free, while the silent person receives three years. If both testify, they each receive two years. Since neither suspect can communicate with the other, each sees testifying as the safer choice, regardless of what the other person does. The result is that both are likely to testify, even though they would both be better off if they stayed silent. The dilemma shows how rational individual choices can create a poorer collective outcome (Axelrod, 1984).

The same structure appears in many cost-cutting exercises. The organization has a collective savings target, just as the two suspects share an interest in a lighter outcome. The consequences, however, land separately at the branch level. Each branch must decide what to offer without knowing what others are offering. A branch that volunteers real reductions risks permanently losing base funding, since reductions are difficult to reverse once implemented. A branch that protects its work may avoid deeper cuts if others come forward first. The system creates a shared interest in meeting the target, but gives each branch a strong individual reason to hold back.

Under those rules, the rational move for each branch is to defend as much as possible, frame most work as critical, and disclose only limited flexibility. A branch that plays in good faith can end up permanently weaker if others protect their funding. A branch that holds back may preserve room to manoeuvre, especially if the collective target is met through reductions offered elsewhere. That is the prisoner’s dilemma in administrative form: each branch is reading the incentives correctly, yet the combined result is weaker transparency, poorer prioritization, and a cost-cutting exercise that rewards defensive behaviour.

What gets hollowed out

Across multiple rounds, this pattern creates a predictable result. Branches that can defend their work through strong narratives are better positioned to protect their funding. Branches that disclose real flexibility early can end up carrying a larger share of the reductions. The exercise still produces a savings number, but it is based on uneven information.

The deeper cost shows up later. Call it cultural debt: the trust version of technical debt. Each cycle teaches leaders that honest disclosure can be punished. After two or three rounds, the organization starts to lose access to accurate information about its own capacity. Capacity conversations become negotiations rather than honest assessments. Leaders learn to protect their areas first, disclose less, and frame every activity as essential. The organization may achieve the short-term savings it needs, but it pays for them with weaker evidence, lower trust, and a reduced ability to make good strategic choices in the next round.

Rules shape the outcome

Two strands of research help explain why this matters.

The first is mechanism design, a branch of economics that studies how rules shape behaviour. The field earned Hurwicz, Maskin, and Myerson a joint 2007 Nobel Prize in Economic Sciences (Hurwicz, 1973; Myerson, 1979; Maskin, 1999). The main point is simple: people respond to the incentives built into a system. When the rules are well-designed, people can act in their own interests and still produce a good collective result. When the rules are poorly designed, appeals to good behaviour have a limited effect.

The second is Elinor Ostrom’s work on how groups manage shared resources, such as pastures, fisheries, and irrigation systems. Ostrom (1990) found that co-operation worked best when a few conditions were in place: clear rules, visible monitoring, fair consequences for people who broke the rules, and trusted ways to resolve disputes. These findings matter because they show that co-operation depends heavily on the system's design. It is rarely enough to ask people to “act better.”

Apply this lens to a typical reduction exercise. The definition of critical or non-discretionary is’ is often vague and left to each branch to decide for itself. Monitoring is uneven. Senior leaders may see the savings totals, yet have limited visibility into how each branch made its choices. A branch that holds back may face few, if any, consequences. A transparent branch may lose funding immediately. Disagreements often get resolved through persistence, pressure, and just waiting it out.

That is why a message like “we need everyone to think enterprise-first” has limited power when the financial rule says, “your base will be cut if you admit you can absorb the reduction.” Values matter, but incentives carry more weight. Better communication can help people understand the exercise. It cannot fix rules that reward defensive behaviour.

Changing the equilibrium

The equilibrium is not fixed. It comes from the rules, and the rules can be changed.

Here are four design features worth considering for any reduction exercise, or for any process where shared goals and individual incentives pull in different directions.

1. Define the decision categories before people act. When people are asked to classify their own work, funding, risk, or capacity, they need common definitions before decisions start. Without shared definitions, each area can interpret the categories in the way that best protects its own interests. Clear definitions make the exercise more comparable and reduce the advantage of self-certifying everything as too important to change.

2. Put reasonable limits on self-protection. Any process that relies on self-reporting needs boundaries. Without them, the rational move is to protect as much as possible and expose as little as possible. A clear limit forces areas to make real choices, and it makes those choices easier to compare across the organization.

3. Remove the penalty for honest disclosure. People will not share accurate information if they believe that transparency will be used against them. Any process that needs honest input must protect those who provide credible, evidence-backed information. Otherwise, each round teaches people to hold back more in the next one.

4. Record the consequences of each decision. Shared decisions need a clear record of the trade-offs being accepted. Without that record, the organization may remember the savings while forgetting the risks, service impacts, and operational pressures created by the decision. A visible record also improves future planning by connecting today’s choices to tomorrow’s consequences.

For people outside the design role, the most useful move is to ask for shared definitions on the record: “Can we agree on a working definition of ‘critical’ so I can classify my spending on the same basis as other branches?” It is a fair question, hard to refuse, and it quietly reduces the advantage held by the loudest defender in the room.

Wrap up

The defensive behaviour we see during cost-cutting is rational behaviour resulting from the rules we set. The good news is that that means we own it as a design choice and can change it. Running these exercises without understanding human behaviour is how we end up with defensive theatre.

Here are a few questions to reflect on:

1. In the last reduction exercise you were a part of, which of the four design features were present, and which were missing? What did the gap predict?

2. Can you tell, right now, which organizations in your department played transparently and which defended hardest? Are you treating those two groups differently, or are you about to punish honesty again?

3. If an auditor asked you to defend the rules of the last cost-cutting exercise (set the savings number aside for a moment), would you stand behind them, or would you discover you’d inherited them from a Finance template no one had revisited in years?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Leave a comment

References

Axelrod, R. (1984) The evolution of cooperation. New York: Basic Books.

Hurwicz, L. (1973) ‘The design of mechanisms for resource allocation’, American Economic Review, 63(2), pp. 1–30.

Maskin, E. (1999) ‘Nash equilibrium and welfare optimality’, The Review of Economic Studies, 66(1), pp. 23–38.

Myerson, R.B. (1979) ‘Incentive compatibility and the bargaining problem’, Econometrica, 47(1), pp. 61–73.

Ostrom, E. (1990) Governing the commons: The evolution of institutions for collective action. Cambridge: Cambridge University Press.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

We’ve all sat in those meetings where a senior leader laments the lack of “entrepreneurial spirit” in the public sector. The narrative is familiar: public servants are framed as risk-averse, complacent, or unwilling to innovate. The proposed solutions usually follow the same script: soft-skills training, empowerment workshops, or vague exhortations to “fail fast.”

But what if the problem isn’t culture at all?
What if the problem is psychological?

The reality is that public servants aren’t cowardly. They’re rational. They operate within a system of deeply asymmetric payoffs, where the penalty for failure is career-limiting, while the reward for success is marginal at best. When we examine these incentives through the lens of behavioural economics, stagnation stops looking like a bug in the system. It’s the predictable output of the equation we’ve built.

Today, we’ll unpack the “asymmetric payoff” model that governs public sector decision-making. We’ll look at why doing nothing is often the only psychologically sound career move, and we’ll finish with a practical playbook for leaders who want to flip the equation and make innovation a rational choice.

Grab your morning coffee, and let’s get started.

Why Inaction Feels Safe

To understand why government organizations struggle to modernize, we need to start with Prospect Theory, developed by Daniel Kahneman and Amos Tversky (1979). Their core finding was loss aversion: the psychological impact of a loss is significantly stronger than the impact of an equivalent gain. In plain terms, losing $100 hurts far more than gaining $100 feels good.

Their later work refined this insight. By 1992, Kahneman and Tversky estimated that losses are experienced at roughly 2.25 times the intensity of gains. This isn’t an abstract concept. It’s a deeply embedded cognitive bias that shapes how humans assess risk in real-world decisions.

In the private sector, this bias is often counterbalanced by substantial rewards, including bonuses, equity, promotions, or a strong reputation. In government, those offsets barely exist. The result is what I’ll call rational stagnation.

The Asymmetric Payoff Model

Let’s map the decision matrix faced by a senior leader considering a digital transformation project.

Option A: Innovation
You attempt to replace a legacy manual process with a new automated system.

• Success scenario: The project saves $2 million annually and reduces citizen wait times.
  Reward: A Deputy Minister award, a mention in the internal newsletter, and perhaps a “Succeeded+” on your PMA. Let’s generously assign this a value of +1.

• Failure scenario: The pilot overruns its budget by $50,000 or fails outright.
  Penalty: ATIP requests, difficult questions from Treasury Board analysts, potential committee scrutiny, and reputational damage that quietly stalls your career. Let’s assign this a value of –2.

Option B: Inaction
You keep the legacy process running.

• Outcome: You meet your operational targets. No audits are triggered. No headlines are written.
  Value: 0.

From a behavioural economics perspective, this isn’t a close call. Innovation offers a modest upside, but comes with a disproportionately severe downside. Inaction reliably delivers neutrality.

The Calculus Everyone Understands (Even If They Don’t Say It)

This is about the psychology of expected value rather than the boldness of courage

Choosing innovation means gambling a potential +1 against a potential –2. The expected value is negative. Choosing inaction all but guarantees a zero.

In this environment, the rational actor will always choose inaction. Not because they lack ambition or imagination, but because the system punishes deviation more than it rewards improvement. In fact, choosing to innovate under these conditions is, psychologically speaking, irrational.

Visibility Bias: Why Audits Target Action, Not Inaction

This asymmetry is reinforced by the machinery of government oversight.

Our accountability systems are highly effective at detecting commission errors: mistakes made while trying to do something. Failed pilots, overspending, or implementation issues are visible, documentable, and politically salient.

But the system is largely blind to omission errors: the value destroyed by not acting. If a department continues to waste $2 million a year on inefficient manual processes, there’s no audit for “missed opportunity.” The loss is real, but invisible.

As a result, the system optimizes for avoiding headlines rather than avoiding obsolescence. The cost of action is immediate and personal. The cost of inaction is diffuse and abstract. Over time, that bias quietly calcifies organizations.

What This Means for Leaders With Authority

If you’re a DG, ADM, or DM, your role isn’t to lecture your organization about courage but rather to change the payoff structure.

Lower the Cost of Loss
Create explicit sandboxes or controlled environments where experimentation is expected and bounded. Define clear guardrails. If a project fails within those parameters, protect the team. Better yet, normalize it.

Reward the attempt, not just the outcome
If loss aversion is a feature of human psychology, you need to counterbalance it deliberately. Recognize teams that ran disciplined experiments, even when the results weren’t favourable. Make it clear that a smart attempt carries value in its own right.

When leaders do this consistently, they change how risk is perceived. Innovation stops feeling like a career gamble and starts feeling like a managed responsibility.

What This Means If You Don’t Have Authority

If you’re a manager or director, or simply working in this environment, you can’t eliminate the penalty for failure. But you can change how risk is framed.

Loss aversion tells us that gains are weak motivators. Losses, real or perceived, drive behaviour. So stop leading with the promised benefits of the future and start making the risks of the present visible.

Instead of saying, “This migration will save money,” say, “If we don’t migrate, there’s a high likelihood this legacy system will fail during the next election writ period, with predictable operational and reputational consequences.”

The goal is to move the fear. Make the status quo feel like the risky choice. When inaction becomes psychologically unsafe, momentum shifts.

Wrap up

Public sector stagnation isn’t a failure of culture or character. It’s the predictable outcome of incentive structures that punish experimentation and reward stability. Until leaders address the asymmetric payoffs that make doing nothing the safest option, no amount of agile training will change behaviour. We need to stop asking public servants to be brave and start making it rational for them to be bold.

Let’s reflect on these questions together:

1. Where in your organization is the “safe” option of inaction quietly costing more than the risk of trying something new?

2. When was the last time you visibly recognized a thoughtful attempt that didn’t succeed?

3. Are you framing your proposals around future gains, or present risks?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

References

• Flyvbjerg, B. (2006). From Nobel Prize to Project Management: Getting Risks Right. Project Management Journal.

• Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica.

• Tversky, A., & Kahneman, D. (1992). Advances in Prospect Theory: Cumulative Representation of Uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

What if a big reason major public projects go off the rails isn’t technical complexity, but subtle deceit in the opening business case?

This week, we’re looking at something Bent Flyvbjerg calls strategic misrepresentation: when people deliberately lowball the true cost, inflate expected benefits, and downplay risk to get a project approved. In blunt terms, it’s lying on paper to unlock funding and authority.

Flyvbjerg’s research across large public projects shows how common this pattern is: over budget, behind schedule, and weaker results than promised (Flyvbjerg, Holm and Buhl 2002; Flyvbjerg 2009). Nine out of ten “megaprojects” don’t deliver on time, on budget or the results they promised (Flyvbjerg 2014).

This matters because the first “story” we hear about the project (usually in something like a business case) becomes the official truth. It becomes the baseline in your Treasury Board submission, the briefing note your deputy reads, the commitment to Canadians, and the line audit and evaluation will eventually come back to. Once you’ve said, “We can do it for $120M in 18 months,” you own that number, even if everyone in the room knew it wasn’t real.

Today, we’ll look at what this behaviour actually is, why people keep doing it even when they know better, and what good practice looks like, whether you hold the pen or you’re trying to influence the person who does.

Grab your morning coffee, and let’s get started.

Strategic misrepresentation is selling, not forecasting

Strategic misrepresentation is deliberate distortion. You make the project look safer, cheaper, faster, and more beneficial than it really is because you know that’s what will get it approved. Flyvbjerg describes it as political rather than technical. You’re not forecasting, you’re selling (Flyvbjerg, Holm and Buhl 2002; Flyvbjerg 2009).

There’s also a quiet arms race built into the system. If you believe other teams are sweetening their story to win scarce funding, you feel pressure to do the same or lose out. You’ve seen the pattern:

• A department promises to rebuild a critical legacy system “within 18 months,” even though the last attempt at the same class of work took four years and still isn’t fully adopted.

• A capital plan says a new facility can be delivered for $140 million, when internal costing puts it closer to $190 million once you include contingency, bilingual service requirements, and long-term maintenance.

• A transformation project claims “significant efficiency gains” in year one. There is no baseline for the current effort, no method to track the savings, and no signed agreement on who will actually release headcount.

And we often hear things like:

• The assumptions will be refined in delivery.

• Schedule risk is manageable.

• It’s a realistic stretch target.

The goal here isn’t to understand the work. The goal is to get a yes, lock in authority, and secure the funding. Once that “yes” is recorded, the numbers become the baseline everyone defends, even if we didn’t truly believe them in the first place.

The system rewards this behaviour

This keeps happening, even in organizations full of capable and well-intentioned people, because the system rewards it.

Scarce money and internal competition

Large public projects compete for limited capital, constrained headcount, and hard-to-find skillsets, especially now. When branches or departments are fighting over a fixed pot, they’re rewarded for promising more benefit for less cost, sooner. Flyvbjerg calls this “jockeying for position” (Flyvbjerg 2009). The most attractive story often wins, not the most accurate forecast.

Political and executive clocks

Leaders are under real pressure to show motion. A deputy minister wants visible progress before year-end. A minister wants an announcement this quarter. A CIO wants proof of early value before the next funding gate. None of this is unreasonable. It is, however, perfectly designed to produce promises that ignore the realities of delivery.

Hope, confidence, and willpower

Not all of this is bad faith. Some of it is optimism bias.

Optimism bias is the tendency to believe our plan will go well and that we’re different from the average person. We underestimate cost, effort, and risk. Lovallo and Kahneman show how leaders routinely overestimate benefits, underestimate timelines, and penalize people who surface bad news (Lovallo and Kahneman 2003). Flyvbjerg distinguishes optimism bias, which is self-deception, from strategic misrepresentation, which is intentional deception (Flyvbjerg 2009). Both lead to bad numbers. The difference is motive.

“We can do it for less because this team is exceptional.” That’s optimism bias.

“Do not include the contingency estimate in the deck. It will scare off Finance.” That’s strategic misrepresentation.

Governance rarely stops it

We tell ourselves governance will catch this. After all, committees exist to challenge assumptions and protect the institution. In practice, most governance bodies don’t interrogate estimates. They ratify spend, confirm alignment to mandate, and record that “a challenge took place.”

The sequence is familiar:

• The material arrives the night before the meeting.

• We flip to a cost table. We skim for the delivery date highlighted in green.

• If we’re lucky, there’s a benefits slide and a risk map.

• The question put to the table is, “Are we comfortable approving this so work can start?”

The question is rarely, “Is this number grounded in anything we’ve actually delivered before?”

Flyvbjerg has a phrase for this: “the survival of the un-fittest.” The projects that should lose often win because their promises are the most unrealistic. The honest proposal, the one that says, “This will take three years and 20 FTEs,” loses to the fantasy that claims it can be done in 12 months with contractors and minimal operational impact (Flyvbjerg 2009).

Most of us have watched a table nod through a delivery date that no delivery lead in the room believed.

The debt created by selling a fantasy

Strategic misrepresentation creates two kinds of “debt.”

Delivery debt

Delivery teams inherit an impossible baseline. They start under-resourced, already behind, and boxed in by a promise that was never real. From day one, the work is framed as “recovery.”

Overruns get labelled “emerging issues,” even though nothing is surprising. Studies of hundreds of public works projects show average cost overruns of roughly 20 percent for roads, about a third for bridges and tunnels, and close to half for rail, with multi-year schedule delays to match (Flyvbjerg, Holm and Buhl 2002). This pattern is consistent across megaprojects of all kinds (Flyvbjerg 2014).

Reputational debt

Sponsors inherit reputational debt. Variance after variance has to be explained to senior leadership, central agencies, and sometimes Parliament and the public. Time goes into recovery plans instead of delivery. Audit takes an interest. The file becomes known as “troubled,” and people with career risk quietly step back.

Once you’re carrying both kinds of debt, you’ll be told to recover without increasing cost, scope, or schedule. That’s impossible arithmetic. The predictable response is quiet scope trimming, phased timelines that slip a few weeks at a time, and a final outcome that’s smaller and later than promised.

What good looks like in practice

There’s no silver bullet, but there are habits that make strategic misrepresentation harder to sustain.

Use reference class forecasting

Flyvbjerg advocates for reference class forecasting (Flyvbjerg 2007). In plain language, stop estimating from scratch. Base your numbers on real outcomes from comparable projects, not internal optimism.

Ask: “For work like this, done in organizations like ours, what did it actually cost? How long did it take? When did benefits show up?” This approach was adopted in the UK for major transport projects precisely because traditional estimating kept failing (Flyvbjerg 2007).

Reference class forecasting frustrates people who want fast approval. That friction is a feature, not a flaw.

Define “done” in public, early

You can’t manage cost, schedule, or benefits until “done” is explicit.

“Done” is not “the vendor deployed version one.” It’s “the promised outcome is live in operations, people are using it, and someone is measuring the benefit.”

Forcing that definition early exposes weak benefit claims and surfaces real accountability. It also makes it harder to declare victory halfway through to satisfy a political milestone.

What to do, depending on your role

If you’re the leader

Set an honest baseline in writing before approval. Ask for the reference-class view. Ask Finance, Procurement, HR, and the delivery lead what this kind of work actually cost last time once contingency, vendor management, backfill, bilingual rollout, testing, training, privacy, records management, and security accreditation are included. Do not accept, “This time will be cleaner.”

Ask for evidence.

Put the definition of “done” into the approval package. Spell out what will exist in production, what service or process will change, which indicators will be tracked, who owns them, and when. Attach this to the decision record.

Surface real risk while it’s still cheap. Build a formal gate where delivery, cost, and schedule risk are disclosed to your CFO and audit partners before contracts are locked in. That’s institutional protection, not delay.

Reward accuracy, not theatre. Make it safe to tell you uncomfortable truths in private and unacceptable to sell fantasy in public.

If you’re influencing up

Your job is to move the conversation toward honesty without being labelled “negative.”

Protect your credibility first. You don’t accuse the plan of dishonesty. You say, “I want to make sure we can defend these assumptions if audit or the Deputy asks.”

Use reference questions rather than direct challenge. “Have we ever delivered something of this scope in 12 months here? If so, I’d like to see that file so I can model resourcing.”

Get “done” on paper. Ask when the initiative will be considered delivered, then capture that in meeting notes and circulate them. You’ve just created a baseline.

Frame timeline risk as reputational protection. “If we publish this date and miss it, we’ll need to brief the Deputy and prepare committee notes. Would you like me to propose a milestone with more buffer?”

A simple thought experiment

Your department’s investment committee receives two proposals.

Proposal A promises $120M, delivery in 18 months, immediate efficiency savings, zero procurement risk, and bilingual rollout on day one.

Proposal B proposes $170M over 36 months, phased delivery, benefits starting in year three after process change and training, with clear risks and mitigation.

Which one reads better on the surface? Which one is more likely to survive contact with reality?

Flyvbjerg’s warning is straightforward. Institutions keep choosing Proposal A. That feels bold in the short term, but it funds fiction. This is the survival of the un-fittest (Flyvbjerg 2009; Flyvbjerg 2014).

Wrap up

Strategic misrepresentation has become a survival tactic. We understate cost, overstate speed, and exaggerate benefits to get approval, then spend years paying off delivery and reputational debt. Flyvbjerg’s work shows that our governance systems often select against honesty.

There is a way to push back. Build estimates from real history. Define “done” before approval. Surface risk early, while it’s still cheap.

Make accuracy safe.

Ask yourself:

1. Who owns the truth about cost, schedule, and benefits on my file, and is it captured anywhere I could table in governance tomorrow?

2. Do we have a written definition of “done” that reflects real outcomes, not just deployment?

3. Am I rewarding accuracy and candour, or confidence and story?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

References

Flyvbjerg, B. (2007) ‘Curbing Optimism Bias and Strategic Misrepresentation in Planning: Reference Class Forecasting in Practice’, European Planning Studies, 16(1), pp. 3–21. doi: 10.1080/09654310701747936.

Flyvbjerg, B. (2009) ‘Survival of the unfittest: Why the worst infrastructure gets built – and what we can do about it’, Oxford Review of Economic Policy, 25(3), pp. 344–367. https://doi.org/10.1093/oxrep/grp024

Flyvbjerg, B. (2014) ‘What you should know about megaprojects and why: An overview’, Project Management Journal, 45(2), pp. 6–19. doi:10.1002/pmj.21409.

Flyvbjerg, B., Holm, M.K.S. and Buhl, S. (2002) ‘Underestimating costs in public works projects: Error or lie?’, Journal of the American Planning Association, 68(3), pp. 279–295. doi:10.1080/01944360208976269.

Lovallo, D. and Kahneman, D. (2003) ‘Delusions of success: How optimism undermines executives’ decisions’, Harvard Business Review, 81(7), pp. 56–63. https://hbr.org/2003/07/delusions-of-success-how-optimism-undermines-executives-decisions

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

As 2025 draws to a close, I’ve been reflecting on what we’ve explored together this year. I wrote 15 posts in total. I tended to write in spurts, banging out four or five posts in a sprint whenever I got inspired by a particular topic.

Looking back, you can see that four overarching themes stand out:

1. Value and outcomes (the anchor)

2. Stewardship and spending (the pressure test)

3. Delivery realism (the place we usually get hurt)

4. Leadership and culture (the part with no template fixes)

Through all of that, I noticed a quiet but persistent thread: the danger of mistaking activity for value. It is a mistake we continue to pay for in money, time, and, most painfully, in trust.

This isn’t about effort or lack of it.

Our public sector is powered by capable and caring people giving their best every day. But as we’ve discussed time and again this year, “hard work” does not guarantee “public value.” Turning effort into impact requires a rigorous discipline around outcomes, evidence, and governance.

As we wrap up the year, let’s take a moment to look back on these recurring themes and glean a few lessons to carry with us into 2026.

Grab your morning coffee (perhaps with a little Baileys in it for that extra festive punch), and let’s get started.

The 2025 theme in one line

Transitioning from delivery theatre to a value discipline.

That means getting sharper about what we are trying to change for citizens, being honest about risk, and using governance that protects outcomes rather than protecting comfort. You can see that arc clearly across this year’s posts on public value and outcome management, on business cases as living decision tools, and on delivery approaches that resist the “rush to start” pressure.

The posts, grouped by what they were really about

Here’s a macro look at this year’s posts, grouped by the core problem each one set out to tackle.

1) Value and outcomes (the anchor)

• Maximizing Public Value: Value is not abstract. It is how we justify trade-offs and stewardship, and how we track whether investments improve lives.

• The Power of Outcome Management: A mindset shift from deliverables to impact, with discipline around logic models and course correction.

• Beyond the Checkbox: Rethinking Business Cases: Treat the business case as a living decision record, not a one-time gate artifact.

The Broken Cog: These posts all pointed to the same issue: we approve work because it is “doable” or “urgent,” then we lose sight of what success means. Outcome discipline is about avoiding building a strong machine that produces the wrong results.

2) Stewardship and spending (the pressure test)

• Transforming Public Spending: Reframing spending conversations around value, not just reductions or compliance.

• How the Social Value Model is Reshaping Public Procurement: Procurement choices can explicitly weight social outcomes, instead of treating them as side benefits.

• Strategic IT Budget Optimization: Budget decisions should protect outcomes and reduce structural waste, instead of salami-slicing.

• What the UK’s Office for Value for Money Can Teach Us: “Value for money” can be institutionalized as a capability, not a slogan.

The Reality Check: This cluster is where public administration gets real. When money is tight, the system defaults to blunt tools. The year’s argument was that blunt tools are avoidable if you have a clear value frame and a credible method for choosing what to stop, what to scale, and what to fix.

3) Delivery realism (the place we usually get hurt)

• Think Slow, Act Fast: Planning is not procrastination. It is risk reduction, scope control, and decision readiness.

• Start with Why: Right-to-left thinking keeps delivery anchored in outcomes and evidence, then works backward to scope and milestones.

• Why Your Project Isn’t Unique: Uniqueness stories are comforting, and they are expensive. Use the outside view and reference classes.

• When IT Projects Go Wild: IT has a special risk profile. Once it goes bad, it can go catastrophically bad.

The Hard Truth: This is the part of the year I keep coming back to. We still treat large IT initiatives like they are “normal projects, but with more Jira tickets.” The research summary on IT “wild risk” makes the point sharply: once IT projects cross a certain overrun threshold, the average overrun becomes extreme. If you are a senior leader, this should change how you approve, budget, stage, and govern.

4) Leadership and culture (the part with no template fixes)

• What Plato’s Cave Teaches Us About Leadership: The hardest part of change is not the plan. It is helping people see past the familiar shadows.

• Every Role Matters: Building a Value Culture: Value culture is built through everyday line-of-sight and shared responsibility, not speeches.

• A Common Sense Revolution: Simplicity is a choice, and it often takes courage to protect it against the system’s natural drift.

• Rediscovering the Purpose in Public Service: Purpose is a management tool. It helps teams stay oriented when constraints and noise pile up.

The Lesson: This cluster is the counterweight to the technical posts. You can have excellent governance on paper and still fail because leaders cannot challenge assumptions, cannot tell uncomfortable truths early, or cannot build trust across roles.

Five lessons I am carrying into 2026

1) Treat outcomes like first-class work products

If we cannot describe the intended change in plain language, we are not ready to fund the work. Outcome management is not a checkbox exercise. It is the discipline that keeps delivery anchored to real-world impact, ensuring that every action taken moves us closer to the outcomes we promised.

A simple test: Can someone outside government understand the outcome statement without a detailed explanation? IIf not, the initiative isn’t ready for approval. It needs clearer language and sharper intent before it can move forward.

2) Make the business case a living tool, or stop pretending

A business case that is never updated is not a decision-making tool. It is a historical artifact. The year’s point on business cases was simple yet uncomfortable: if you do not revisit assumptions and measure against expectations after delivery, you cannot learn.

If you want fewer repeat failures, start with fewer “one-and-done” approvals.

3) When money gets tight, value clarity becomes the whole game

If leaders cannot articulate what value they are protecting, they will protect what is loudest, newest, or most politically visible. The posts on public value and value-for-money capability were a push to make stewardship more concrete.

That is where tools like social value models and structured value discussions in procurement can help. And we should not reserve this kind of value thinking only for times of austerity or fiscal pressure. AND: it should be part of the everyday culture of how we plan, decide, and deliver.

4) Stop celebrating fast starts; celebrate controlled starts

The “think slow, act fast” theme keeps showing up because government is addicted to motion. We equate urgency with competence, even when urgency is driving bad sequencing.

The healthier pattern is: slow down early to reduce uncertainty, then move quickly once you have credible scope, governance, and kill criteria.

5) Assume your project is not unique, unless you can prove it is

The uniqueness story is seductive because it protects optimism. It also blocks learning from comparable work. Pair that with what we learned about IT “wild risk,” and the implication is blunt: major IT initiatives should be staged, modularized, and governed as if extreme outcomes are plausible.

When governance structures can’t absorb or act on bad news early, that information doesn’t disappear; it compounds. By the time it surfaces, the damage is greater, the options are fewer, and the cost is far higher.

Wrap up

If you take only three things from this year’s writing, make them these:

• Value work is governance work. We must apply the same discipline to outcomes and trade-offs that we currently apply to delivery schedules.

• Paperwork doesn’t manage risk; decisions do. When business cases become static paperwork instead of active decision records, failure becomes predictable.

• Respect the “Fat Tail.” Large IT initiatives are not standard projects. They demand a defensive risk mindset because the outliers can—and will—dominate your results.

As we head into the new year, let’s reflect on three questions:

1. What decision on your desk would look different if you had to justify it in terms a citizen could understand?

2. Where are you mistaking “speed” for progress, when it might actually be a way to avoid uncertainty?

3. What familiar “shadow” in your organization is being accepted as truth simply because it’s comfortable?

Rest up, reflect, and enjoy the break. We ride at dawn (in January).

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Today, we continue our look at the central ideas from How Big Things Get Done by Bent Flyvbjerg and Dan Gardner, focusing on two in particular: the myth of uniqueness and the power of modularity.

“This project is different. It can’t be compared to anything else.”

Whether it is migrating to the cloud, building a new hospital, launching a digital service, or rolling out a major infrastructure project, the phrase is familiar.

It is a comforting belief.

It allows us to rationalize why schedules slip, budgets balloon, and risks go unacknowledged. But as Bent Flyvbjerg and Dan Gardner remind us in How Big Things Get Done, this assumption is dangerous. Most projects are not as unique as their sponsors claim. And success, counterintuitively, often comes not from reinventing but from repeating, what they call " finding your Lego.”

Today, we'll explore these two concepts and what they mean for transformation in government.

Grab your morning coffee, and let’s get started.

So You Think Your Project Is Unique

When a new initiative begins, many times we hear (or believe) it has never been done before. A government department implementing a new benefits system? That’s different from a corporate HR system. A public transit extension? That’s not the same as the one across the country. A military IT modernization? Totally unlike civilian digital transformation.

Except it isn’t.

Every project may have unique features like its context, stakeholders, or policies, but the patterns of success and failure are remarkably consistent. Budgets are underestimated. Risks are downplayed. Benefits are exaggerated. Timelines are optimistic.

When we think our project is too special to compare, we shut the door on learning from thousands of others that have gone before.

This is where reference class forecasting comes in. Instead of assuming uniqueness, we should place our project within a class of similar projects and draw lessons from the data:

• What were the average costs?

• How long did it usually take?

• What risks commonly materialized?

By anchoring in the reality of history rather than the optimism of ambition, we can build more realistic plans.

We've seen this played out time and time again. Many IT projects are often described as singularly complex. Yet the same challenges, like underestimating application dependencies, overpromising timelines, and struggling with partner engagement, emerge every time. Treating each as a unique blind decision-maker to avoid the predictable traps.

The lesson in How Big Things Get Done is pretty clear: stop insisting your project is unprecedented. Start looking for patterns that have played out elsewhere. That is how you build realistic expectations and avoid the trap of overconfidence.

What’s Your Lego?

If rejecting uniqueness is about perspective, then finding your Lego is about smart design.

The metaphor is simple: big projects succeed when they are broken down into modular, repeatable units (like Lego bricks) that can be assembled predictably. The smaller and more standardized the block, the less risk and uncertainty in putting it together.

Take Apple stores, an example highlighted in How Big Things Get Done. The first few took time to design. But once the blueprint was perfected, the company replicated it worldwide. Each store was not designed from scratch. It was assembled from tested, reliable components. Offshore wind farms follow the same logic, reusing foundations, turbines, and processes across sites. Pixar, too, treats movies as modular: the characters and plots change, but the creative pipeline and production process are standardized.

The same principle applies in government. The UK’s Government Digital Service (GDS) created common service design standards so that new digital services didn’t reinvent the wheel. In Canada, the Government’s Digital Standards (while admittedly a lot less prescriptive and more principle-based) provide a flexible framework for modular, repeatable elements in digital service design. Even infrastructure projects are discovering modularity: hospitals built with prefabricated units, classrooms delivered through standard designs.

Here again, the lesson is clear: What is the repeatable unit in this project? Identify it, refine it for your context, and use it again. That discipline, reusing proven blocks rather than starting fresh, is what reduces risk, speeds delivery, and strengthens results. This is your Lego.

From Unique to Repeatable: How the Concepts Work Together

Those two concepts work nicely together:

• Recognizing your project is not unique opens the door to learning from history. It helps teams draw on evidence, use data effectively, and better anticipate risks. The result is more realistic commitments and stronger delivery.

• Finding your Lego encourages reuse and grounds you in repeatable practice. It is about seeing that successful delivery often comes from assembling proven blocks rather than creating everything new. That discipline builds confidence, reduces risk, and accelerates delivery.

Together, they shape how we approach transformation. Rather than overemphasizing novelty, they encourage anchoring in evidence. Rather than starting from scratch, they point us toward standardization and scale. When predictable patterns are recognized and modular solutions are applied, we can concentrate our energy on the parts of the project that genuinely demand adaptation and creativity.

But let's be clear: This is not about ignoring context. Every project will need tailoring. But the baseline is not a blank sheet of paper. It is a set of lessons learned and blocks already built. That mindset shift is what separates fragile ambition from durable delivery—start from there and build outward.

Applications for the Public Sector

Let’s explore some areas where these ideas can transform how we deliver our initiatives.

1. Digital Service Delivery

Too often, new services are designed from scratch. Departments argue that their program is unique, so existing design standards do not apply. The result: inconsistent experiences for citizens, higher costs, and avoidable risks.

The non-unique approach: recognize that most digital services share common features. Apply lessons from previous projects and use data from existing platforms to set realistic timelines, costs, and risks.

The Lego approach: adopt and adapt service design standards. Treat things like authentication, payments, and notifications as blocks. Build once, reuse many times. Citizens benefit from consistency, and government benefits from efficiency.

2. Policy Implementation

Many policy rollouts fall into the uniqueness trap. Leaders argue their reform is unlike any before. But the challenges like stakeholder engagement, communication, and resourcing follow predictable patterns.

The non-unique approach: treat new reforms as part of a reference class. Look at what worked and what failed in past policy changes, and anticipate the same recurring risks and opportunities.

The Lego approach: identify the standard policy tools and engagement strategies that consistently work. Treat them as blocks, then adapt only where context requires.

3. Program Administration

Often, new programs are pitched as one-of-a-kind to give them that shiny new look. But they almost always share recurring administrative needs. Things like application intake, eligibility checks, payment systems, and reporting.

The non-unique approach: acknowledge these commonalities and ground planning in the lessons of earlier program launches.

The Lego approach: treat program administration components like intake forms, eligibility engines, and reporting dashboards as reusable blocks that can be applied across multiple programs.

Leadership Lessons

These concepts carry important lessons as they remind us to let go of the myth of uniqueness, to embrace the evidence of history, and to lean on repeatable building blocks that make delivery more reliable.

1. Check Your Ego at the Door

The belief that “our project is different” often reflects pride more than fact. Humility is a leadership strength. Recognize that others have faced similar challenges, and their lessons apply to you.

2. Anchor in Evidence

Reference class forecasting is more than a technique; it is a mindset. Insist on comparing your project to a class of similar efforts. Use data to ground your expectations. Optimism may inspire, but realism delivers.

3. Find and Build Your Lego

Ask early: What is the modular, repeatable unit in this project? Invest in designing it well. Once built, use it again. Each repetition increases confidence and reduces risk.

4. Balance Standardization with Context

Not everything can or should be standardized. Leadership lies in knowing where to reuse blocks and where to adapt. The art is in balancing efficiency with flexibility.

5. Focus on Value, Not Novelty

Too many projects chase uniqueness for its own sake. The public does not care if a service is novel. They care if it works, if it is reliable, and if it delivers value.

Wrap up

Many projects are often framed as special, unprecedented undertakings. This mindset is costly. It fuels overconfidence, blinds us to evidence, and leads to reinvention. The truth is that while every project has unique aspects, the patterns of success and failure are consistent.

Those who succeed are those who embrace comparability and repeatability. They reject the uniqueness trap, learn from the reference class, and find their Lego. They understand that transformation is less about novelty and more about disciplined execution.

Here are three questions to reflect on:

• Where have I assumed my project was unique, and how did that shape my decisions?

• What repeatable building blocks could I identify and reuse in my current work?

• How can I balance adapting to context with applying lessons from past projects?

The next time you hear someone insist their project is unique, ask them: What’s your Lego?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Last time, we explored think slow, act fast and how deliberate preparation followed by disciplined execution improves results (Flyvbjerg and Gardner, 2023; Kahneman, 2011).

This week, we return to another central theme from How Big Things Get Done: think right to left, or begin with why. In Flyvbjerg and Gardner’s terms, this means deciding on the end outcomes that matter most for citizens and then reasoning backwards to identify the outputs, activities, resources, and milestones that will make them real. The authors stress that large, successful projects are rarely the result of diving straight into delivery. Instead, they begin with clarity about the destination.

Simon Sinek’s (2009) work Start With Why reinforces this point: leaders who clearly articulate the underlying purpose of their work inspire stronger commitment and alignment. For Sinek, starting with why builds trust and fosters intrinsic motivation, making it easier for teams to persist through challenges and adapt when circumstances change.

Grab your morning coffee, and let’s get started.

Why Starting with Why Works

Flyvbjerg and Gardner note that projects often derail when teams rush to solutions before clearly defining the desired impact. Activity takes centre stage, outputs multiply, yet outcomes stay vague or contested. The public sector is particularly susceptible to this, given the nature of political cycles and the pressure for visible progress.

Right‑to‑left thinking corrects this by:

1. Anchoring decisions in public value: Outcomes, not tasks or outputs, guide choices. This aligns with Rumelt’s (2011) argument that good strategy identifies a clear challenge, sets guiding policies, and defines coherent actions. Sinek (2009) adds that this clarity of purpose is what rallies people behind a common cause, enabling consistent decision-making even under pressure. He argues that when leaders communicate a clear "why," it taps into the limbic part of the brain responsible for decision-making and behaviour, making the purpose resonate on both an emotional and rational level.

2. Guarding against premature action: Kahneman’s (2011) work demonstrates that humans tend to lean toward quick, intuitive actions. A deliberate focus on outcomes forces a System 2 pause to check assumptions. Sinek reinforces this by suggesting that when the "why" is front and centre, it slows the impulse to act for the sake of activity and instead encourages actions that stay true to the underlying purpose.

3. Clarifying trade‑offs: When objectives conflict, leaders can compare options by their contribution to the end goals, echoing Robinson’s (1990) concept of backcasting to resolve competing pathways. Sinek’s framing supports this, noting that a clearly articulated "why" serves as a filter for choices, making trade‑offs more transparent and aligned with the ultimate mission.

Holmberg and Robèrt (2000) expand this by demonstrating that beginning with a clearly defined sustainable end state provides a stable reference point for decision‑making. In practice, this means identifying the environmental, social, and economic conditions that must be met for the project to be considered sustainable, and then working backwards to determine the policies, technologies, and processes needed. This approach helps teams avoid committing too early to solutions that may later prove incompatible with long‑term goals, ensuring that every step taken aligns with the overarching vision for sustainability.

Example: the Guggenheim Museum Bilbao

In How Big Things Get Done, Flyvbjerg and Gardner highlight the Guggenheim Museum in Bilbao as a case where right‑to‑left thinking shaped both design and execution. The aim was never simply to construct a museum. When architect Frank Gehry probed the underlying why, he discovered that the city’s leaders wanted more than an art space; they wanted a landmark capable of putting Bilbao on the global stage and sparking a cultural and economic renaissance. This meant first defining specific desired outcomes (increased tourism, job creation, and international recognition) before moving to design choices, material selection, or delivery methods. By anchoring decisions in these end goals, Gehry ensured that the building’s striking design served the city’s broader ambitions.

Example: Building a Bridge

Consider a simpler example: building a bridge. In many cases, the bridge is not the ultimate objective; the goal is to improve the movement of people and goods and potentially stimulate economic growth.

However, when the underlying "why" is examined, a bridge may not be the best solution. Improvements to ferry service, public transportation, or logistics infrastructure may deliver the same or better outcomes at a lower cost and with less environmental impact.

Defining the intended benefits at the outset allows planners to work backwards to identify the most effective option. If a bridge is chosen, this clarity helps set the right specifications, construction methods, and sequencing. The focus shifts from delivering a predetermined structure to achieving measurable outcomes that serve the public interest.

The Four Right‑to‑Left Questions

Flyvbjerg and Gardner’s framing can be broken into four sequential questions, which act as a structured decision-making pathway from purpose to execution:

• Why: What measurable outcomes for citizens and the state are we pursuing?

• What: What products, services, or policy changes are essential to reach those outcomes?

• How: What activities, delivery models, and capabilities will create and sustain the "what"?

• Who/When/How Much: Who owns each part, by when will it be done, and at what cost and risk?

The authors emphasize answering these in order, revisiting them regularly, and ensuring they shape business cases, plans, and governance decisions.

Applying Right‑to‑Left Thinking

Drawing on the principles in How Big Things Get Done and reinforcing them with insights from wider literature and practice, a practical step-by-step process could be structured as follows:

1. Write the Outcome Statement: Define a goal that is citizen-centred, measurable, and time-bound, making it clear enough that anyone outside the project team can understand what success looks like.

2. Backcast from the Target Date: Starting from the end goal, identify the essential preconditions and milestones in reverse order to ensure each step logically leads to the next.

3. Define Benefits and Measures: Choose only indicators that clearly reflect public value, assign accountable owners, and identify reliable data sources to track them.

4. Translate Outcomes to Outputs: Determine which tangible deliverables will directly influence the agreed‑upon indicators, avoiding unnecessary work that does not move the needle.

5. Choose Options and Minimum Viable Scope: Compare different approaches based on outcome-impact per unit of cost and risk, and opt for the smallest scope that achieves the desired results.

6. Build a Theory of Change: Explicitly map how activities will lead to outcomes and test the riskiest assumptions early to reduce the chance of costly missteps.

7. Design Governance Around Outcomes: Structure oversight so that funding and approvals are tied directly to evidence showing movement toward the desired outcomes.

8. Communicate the Why: Share the purpose in outcome‑first narratives, ensuring that internal and public updates reinforce the link between actions and the original purpose.

9. Connect to Think Slow, Act Fast: Right‑to‑left defines the destination; think slow designs the route; act fast executes, creating a clear and coherent chain from intent to impact.

I’ve written about specific tools and techniques that I’ve used to achieve this before. You might want to have a look at these previous posts:

Pitfalls to Avoid

Flyvbjerg and Gardner caution against the following common traps that can derail right‑to‑left thinking in practice:

• Vague or conflicting outcomes: When end goals are unclear or contradictory, teams struggle to prioritize actions, resulting in wasted effort and a diluted impact. Clear, agreed‑upon outcomes keep all stakeholders aligned.

• Proxy metrics that drive the wrong behaviours: Relying on indirect indicators can encourage activity that appears to be progress but fails to deliver public value. For example, counting kilometres of road built without measuring travel time reductions may reward quantity over actual benefit.

• Over-engineering the scope beyond what affects outcomes: Adding features, specifications, or deliverables that do not improve the agreed-upon results wastes resources and increases risk. Keeping the scope to the minimum needed to achieve outcomes improves focus and efficiency.

• Treating the plan as fixed rather than updating as evidence changes: Rigidly following an initial plan can lock teams into ineffective paths. Regularly reviewing and adjusting plans based on new data ensures delivery remains on track toward the intended outcomes.

Sinek would add that a poorly communicated or weakly defined "why" can undermine even the best technical plan, as stakeholders disengage without a clear reason to care.

Leader’s Checklist: Making Right-to-Left Thinking Work in Government

Set the Why

• Draft outcome statements in clear, citizen-friendly language, including target dates and measurable results.

• Select 3–5 outcome indicators with named accountable owners.

Work Backwards

• Use backcasting to identify milestones and dependencies from the end goal to the present.

• Map key assumptions and design tests to address the riskiest early.

Design for Value

• Compare delivery options based on their impact on outcomes (economy, efficiency, effectiveness, and equity) per dollar spent.

• Choose the minimum viable scope that delivers outcomes; expand only with supporting evidence.

Govern What Matters

• Make approvals contingent on evidence of movement toward outcomes.

• Require change requests to show a clear and quantified impact on agreed-upon outcomes.

Communicate the Why

• Centre all updates around outcome-first narratives that connect actions to purpose.

• Explicitly link individual roles, team responsibilities, and funding to outcome accountability.

Wrap up

Flyvbjerg and Gardner’s think right-to-left approach offers a disciplined way to keep strategy anchored in public value: define the why, work backwards, and let evidence steer delivery. Combined with think slow, act fast, it creates a resilient link from intent to impact.

Here are some self‑reflection questions to help you consider how well you are applying right‑to‑left thinking in your own context

• Do my current initiatives have outcome statements that a citizen, like my neighbour, would understand?

• Do dashboards lead with outcomes, not activity counts?

• At the next gate, what evidence will show that we are moving indicators in the right direction?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

References

Flyvbjerg, B. and Gardner, D. (2023) How Big Things Get Done. London: Penguin Press.

Holmberg, J. and Robèrt, K.-H. (2000) ‘Backcasting from non-overlapping sustainability principles’, International Journal of Sustainable Development and World Ecology, 7(4), pp. 291–308. doi:10.1080/13504500009470049.

Kahneman, D. (2011) Thinking, Fast and Slow. Toronto: Doubleday Canada.

Robinson, J. (1990) ‘Futures under glass: a recipe for people who hate to predict’, Futures, 22(8), pp. 820–842. doi:10.1016/0016-3287(90)90018-D.

Rumelt, R. (2011) Good Strategy/Bad Strategy: The Difference and Why It Matters. New York: Crown Business.

Sinek, S. (2009) Start With Why: How Great Leaders Inspire Everyone to Take Action. New York: Portfolio.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

In government, urgency is constant. Political leaders face electoral cycles. Citizens expect timely services. Scrutiny from the public and the media pushes departments to show quick progress. The reflex is to “get started” immediately: launch the program, break ground, cut the ribbon.

Side note: This tendency to focus on visibly doing new things is one of the central humorous themes of the excellent Australian Broadcasting Corporation series Utopia, which follows a fictional government agency. The show captures, with sharp wit, many of the frustrations and ironies familiar to public servants. If you work in the public sector, you may find it both entertaining and uncomfortably relatable.

Yet decades of global research on large-scale projects show this instinct often backfires. Bent Flyvbjerg, the Oxford University professor behind the world’s largest database of megaprojects, calls it the Iron Law of Megaprojects: over budget, over time, under benefits—over and over again (Flyvbjerg, 2023). Whether it is a digital transformation, infrastructure build, or policy overhaul, the pattern is consistent.

In his book How Big Things Get Done (with Dan Gardner), Flyvbjerg offers a simple countermeasure: think slow, act fast. This principle, grounded in data and behavioural science, is especially relevant for public sector leaders managing high-stakes, politically sensitive initiatives.

It also reflects Daniel Kahneman’s Nobel-winning insights into decision-making. Kahneman’s research shows that we are overconfident, underestimate risks, and rarely use the “outside view” when planning (Kahneman, 2011). The “think slow, act fast” approach operationalizes these findings.

Today, we explore what “think slow, act fast” means in the context of the public sector, why it works, and how project teams and senior leaders alike can apply it in practice to achieve stronger, more reliable outcomes. We will draw on the work of Flyvbjerg and Kahneman to translate research insights into practical steps for government decision-makers.

Grab your morning coffee, and let’s get started.

Why Public Projects Start Wrong

Before getting into the method, it’s worth asking: why do projects fail? While there are many factors, Flyvbjerg keeps hammering on three recurring issues seen across projects worldwide that deserve closer attention. These are exactly the issues the think slow, act fast approach is designed to help address.

1. The Planning Fallacy
Coined by Kahneman and Amos Tversky, this describes our tendency to underestimate costs, timelines, and risks, even when past experience suggests otherwise (Kahneman and Tversky, 1979). Political optimism amplifies it: the belief that with enough determination, constraints can be bent to fit promises.

2. Strategic Misrepresentation
In some cases, proponents deliberately understate costs or overstate benefits to get approval, knowing the estimates are unrealistic (Flyvbjerg, 2009). The calculation is political: if you present the truth, the project might not be funded. This often reflects short-term incentives to secure political or financial backing at the expense of long-term viability. It can erode trust, distort priorities, and set the stage for chronic overruns or underperformance once delivery begins.

3. Premature Start
Flyvbjerg (2017) warns against launching projects before designs, governance structures, and procurement strategies are ready. Starting too early often leads to reactive firefighting: scope changes multiply, bottlenecks emerge, procurement slows, and costs rise. This premature start undermines delivery speed and budget discipline, especially compared to projects that invest more time upfront in thorough planning.

These problems are not inevitable. They are predictable and preventable when leaders change the sequencing of effort.

The Core Idea: Think Slow, Act Fast

This approach reverses the common rhythm of public projects. Instead of a rushed start followed by slow delivery, it calls for deliberate preparation followed by fast, disciplined execution (Flyvbjerg, 2023).

Thinking slow means:

• Understanding the problem, desired outcomes, and constraints in detail.

• Using data from past projects to produce realistic estimates.

• Identifying and mitigating risks before they stall delivery.

• Designing governance, procurement, and sequencing before signing contracts.

Acting fast means:

• Delivering in parallel work streams rather than one long sequence.

• Freezing scope and controlling changes tightly once work starts.

• Empowering teams to make quick, informed decisions within clear boundaries.

• Monitoring progress closely and correcting course immediately when needed.

The Behavioural Science Behind It

Kahneman’s System 1 / System 2 model explains the value of this approach. System 1 is fast, intuitive, and prone to bias. System 2 is slow, deliberate, and analytical (Kahneman, 2011). Most large public projects begin in System 1, a fast rush to action driven by optimism and political momentum.

Complex, unfamiliar projects require System 2. The “think slow” phase forces this shift, countering bias and preventing commitment to flawed plans.

Once the project is well understood and execution is designed, leaders can return to faster decision-making, with System 1 operating within a stable, predictable environment.

Thinking Slow in Practice

Thinking slow is active preparation, not delay. In the public sector, it involves:

1. Define “Done” in Measurable Terms
   Broad aspirations must be translated into specific, testable outcomes, such as service times, cost savings, or satisfaction scores (Flyvbjerg, 2023). In practice, this means agreeing on a short list of clear performance indicators at the outset, ensuring that all stakeholders share the same definition of success and that progress can be tracked objectively over time.

2. Use the Outside View
   Reference-class forecasting is a method for predicting outcomes by looking at a broad set of similar past projects and using their actual results as a benchmark (Kahneman and Tversky, 1979). Put simply, it means comparing your project to a "reference class" of completed projects to see what really happened, instead of relying only on your own assumptions. In practice, this involves gathering reliable data on the cost, schedule, and benefits of comparable cases and using these to set a realistic starting estimate. For example, if a similar project elsewhere took 36 months and cost $200 million, that becomes your baseline, which you then adjust for your own local context.

3. Pilot and Prototype
   Small-scale tests expose hidden risks before major commitments (Flyvbjerg, 2023). In practice, this could involve trialling a single service channel, building a minimum viable product, or testing a new procurement method with a limited set of suppliers, allowing you to uncover issues and refine your approach before scaling up.

4. Map the Delivery System
   Define governance, decision rights, procurement strategy, and sequencing before launch. In practice, this means creating a clear delivery roadmap, assigning accountable owners for each decision point, agreeing on escalation paths for resolving issues, and sequencing activities to avoid bottlenecks. Ambiguity here is a major source of execution failure.

5. Run a Pre-Mortem
   Imagine the project has failed, then identify why and address those risks now (Klein, 2007). A pre-mortem is essentially a structured "failure rehearsal" that helps teams think ahead about what could go wrong. In practice, this exercise should bring together the full delivery team and key stakeholders to brainstorm plausible failure scenarios, explore the chain of events that could lead to them, and record preventive actions. This technique often reveals vulnerabilities that traditional planning overlooks and encourages candid discussion of risks that might otherwise remain unspoken.

Acting Fast in Practice

When planning is complete, execution becomes focused acceleration.

1. Break Down the Work
   Structure the project into independent modules that can be delivered in parallel. In practice, this might mean dividing a large project into smaller, self-contained components with clear interfaces, so that if one part hits a problem, others can still move ahead. This reduces interdependencies and makes progress more resilient.

2. Freeze Scope, Manage Change
   Avoid adding features or requirements mid-stream. Every change is a risk to cost and schedule. In practice, this means having a formal change control process where all requests are logged, assessed for their impact, and approved only if they add significant value.

3. Push Decisions to the Front Line
   Allow delivery teams to handle day-to-day choices without escalation. In practical terms, this involves giving clear decision rights, authority, and accountability to those closest to the work, while reserving senior decision-making for major shifts in scope, cost, or policy.

4. Maintain Real-Time Insight
   Track progress against the baseline forecast using timely, reliable data. In practice, this could mean dashboards updated weekly, key performance indicators tied to milestones, and rapid escalation protocols when metrics show signs of slippage.

5. Protect the Critical Path
   Identify the most time-sensitive tasks that dictate the project’s overall schedule. In practice, this means prioritizing resources, attention, and problem-solving on these activities, ensuring they are unblocked quickly to keep delivery on track.

Common Pitfalls

Even with the right sequencing, traps remain:

• Analysis Paralysis: Thinking slow must be purposeful and time-boxed with clear decision gates. In practice, this means setting defined periods for planning, with milestones where decisions must be made, and resisting the urge to endlessly gather more data or options before moving forward.

• Political Impatience: Manage expectations by explaining why early preparation leads to better outcomes. This involves transparent communication with political sponsors and stakeholders about the risks of rushing, supported by examples from past projects where planning paid off.

• Scope Creep: Guard the execution phase from politically motivated or opportunistic additions. In practical terms, this means enforcing scope controls, having a clear process for assessing change requests, and being willing to say no when additions threaten delivery.

• Weak Kill Criteria: Define the conditions for stopping or pivoting in advance. This includes setting measurable thresholds for cost, schedule, and benefits, agreeing on who has the authority to halt work, and ensuring these criteria are understood and accepted by all key decision-makers before execution begins.

Leader’s Checklist: Making “Think Slow, Act Fast” Work in Government

Here’s a practical summary you can apply directly in your work.

During the “Think Slow” Phase

• Define Success Clearly: Translate political or strategic goals into measurable outcomes.

• Adopt the Outside View: Use data from past projects to set realistic targets.

• Identify Kill Criteria: Set thresholds for pausing, pivoting, or cancelling.

• Pilot Before You Commit: Test on a small scale to uncover risks.

• Design the Delivery System: Establish governance, escalation paths, procurement, and sequencing.

• Run a Pre-Mortem: Identify and address possible causes of failure in advance.

During the “Act Fast” Phase

• Break the Work into Modules: Deliver smaller increments to reduce risk and speed results.

• Freeze Scope and Control Changes: Review all scope changes formally.

• Push Decision-Making Down: Let teams handle operational calls without delay.

• Monitor in Real Time: Track progress against plan and act on early warnings.

• Protect the Critical Path: Keep the most time-sensitive work moving.

• Report Transparently: Keep stakeholders informed with clear, honest updates.

Wrap up

Speed without preparation is recklessness; preparation without speed is stagnation. The challenge is balance.

For senior leaders, this means resisting the urge to launch too soon while avoiding bureaucratic drift. It means investing in the discipline of thinking slow: defining “done,” forecasting realistically, and stress-testing plans, before unleashing the urgency of acting fast.

When you feel the pressure to “just get started,” remember: a project that starts slowly and finishes quickly is far more valuable than one that starts quickly and drags on for years.

Take a moment to consider how the principles discussed apply to your own work and projects. These prompts will help encourage honest evaluation and highlight where the think slow, act fast approach could strengthen your results:

1. In my current or upcoming initiatives, have I taken enough time to reduce uncertainty before moving into execution?

2. Am I using evidence from similar projects or relying mainly on internal assumptions to set expectations for cost, schedule, and benefits?

3. Do I have clear, agreed-upon criteria for when to stop, pivot, or accelerate a project?

Until next time, stay curious, and I’ll see you Beyond the Status Quo.

References

Flyvbjerg, B. (2009) Survival of the unfittest: why the worst infrastructure gets built—and what we can do about it. Oxford Review of Economic Policy, 25(3), pp. 344–367.

Flyvbjerg, B. (Ed.). (2017). The Oxford Handbook of Megaproject Management. Oxford University Press.

Flyvbjerg, B. and Gardner, D. (2023) How Big Things Get Done. London: Penguin Press.

Kahneman, D. (2011) Thinking, Fast and Slow. London: Penguin.

Kahneman, D. and Tversky, A. (1979) ‘Intuitive prediction: Biases and corrective procedures’, Management Science, 12(3), pp. 313–327.

Klein, G. (2007) ‘Performing a project premortem’, Harvard Business Review, September, pp. 18–19.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Today, we explore this question: Why do so many government IT projects spiral out of control?

A new paper by Bent Flyvbjerg and colleagues takes a close look at cost risk across 23 different project types, and the results are striking and offer a lot of insight. Their study shows that IT stands apart: unpredictable, with risk patterns so uneven that traditional forecasting cannot be trusted. The research compares IT with fields like nuclear power, transport, and energy, and still finds IT uniquely risky, which is an unsettling conclusion for those responsible for large IT transformations.

Today, IT investments are ingrained in every service we deliver. When costs spiral, budgets suffer, but worse: so does public trust and service reliability. The evidence suggests that IT is not just another category of capital project. Rather, it's a special risk class that demands a different mindset and different tools. This raises important questions about how leaders approach planning, oversight, and delivery.

Today, we'll start with a summary of this research, then look at what it means for us by extracting some lessons based on Flyvbjerg's findings. Finally, we'll share some prompts to spark reflection on how this connects to your own work.

The full article is here:

Flyvbjerg, B., Budzier, A., Aaen, J., Keil, M., & Zottoli, M. (2025). The Uniqueness of IT Cost Risk: A Cross-Group Comparison of 23 Project Types. Project Management Journal, 0(0). https://doi.org/10.1177/87569728251340590

Grab your morning coffee, and let’s get started.

What the Research Found

The study analyzed 11,011 projects across 23 categories, ranging from IT and nuclear power to roads and wind farms. The focus was on cost risk, measured as the ratio of actual to estimated costs at the point of final investment decision. I've put the data I'm about to discuss at the end of this section so you can have a look and follow along.

IT projects stood out as uniquely risky.

At first glance, the picture for IT looks surprisingly good. Out of the 5,360 IT projects in the dataset, only about 41% went over budget. That actually places IT among the best performers. For contrast, every Olympic Games project studied has gone over budget, and 97% of nuclear power projects did too.

Even when looking at projects that ran more than 50% over budget, IT still sits near the middle of the pack at 18%. On these basic measures, IT does not appear to be the problem child many expect.

The trouble emerges when looking at what happens once IT projects cross the 50% overrun threshold. For these projects, the average cost overrun is an astonishing 453%. This is worse than any other project type and, aside from nuclear storage, far worse than the rest.

Put simply: when IT projects go over budget, they go dramatically over.

The trouble continues...

The researchers also show that cost overruns follow a power‑law curve. For those interested in the technical details, they use a Pareto Type I distribution, defined by a “tail shape” parameter (alpha). IT projects have an unusually heavy tail: their alpha is 0.92, making them the only project type below 1. This matters because a value under 1 means averages and variances do not converge (they can't be calculated). In practice, there is no stable “typical” outcome. Instead, rare but extreme blowouts dominate the results and overwhelm the overall picture.

It's what they call “wild risk.”

This makes IT projects fundamentally different from bridges, roads, or even nuclear plants, where averages can provide some guidance. The research tells us that for IT projects, traditional forecasting breaks down, and leaders must plan for the possibility that these extreme events will bend the cost curve far out of shape.

The paper also explores why this might be the case, suggesting four familiar explanations for IT risk:

• Immaturity: IT is a relatively young field compared to engineering disciplines like construction, with weaker standards, less professionalization, and fewer established practices.

• Intangibility: Software has no physical presence, making progress harder to see, communication more difficult, and scope creep easier to accept.

• Unclear goals: Objectives in IT projects often shift or are poorly defined, leading to volatility, drift, and escalation.

• Stakeholder resistance: IT alters established ways of working and power dynamics, creating pushback that adds complexity and delay.

While these remain plausible explanations, the data point to added drivers: a heavy reliance on bespoke builds instead of modular components, and decision-making that is rushed, leaving projects underprepared.

Implications

The lesson is clear: large IT initiatives need to be treated as their own category of risk because extreme events drive the overall budget picture. Average-based forecasting and thin risk registers do not capture reality. A better approach is to use high-percentile budgeting and to set limits on exposure at the portfolio level.

Decision-making and Optimism Bias

Business cases built on averages are misleading. Approvals should be based on percentile forecasts that account for extreme outcomes. This is where reference-class forecasting and the outside view become essential. By comparing proposed projects with a broad dataset of similar initiatives, leaders can ground expectations in real-world outcomes rather than optimistic assumptions.

This connects directly to optimism bias: the tendency for leaders and teams to assume things will go better than they actually do. In IT, this often means underestimating costs, overestimating delivery speed, or ignoring early signs of trouble. Optimism bias is especially dangerous when combined with fat-tailed risk: even small misjudgments can leave organizations exposed to rare but extreme overruns.

Business cases, budgets, and schedules must therefore be stress-tested against outside evidence. Embedding reference-class forecasting and the outside view into gating and oversight processes reduces the gap between what leaders hope will happen and what actually unfolds. Where possible, we should also favour configurable off-the-shelf products or platform components rather than bespoke builds, aligning with the Treasury Board’s Policy on Service and Digital and departmental gating practices for major projects.

Service delivery

Systems should be designed to degrade gracefully and delivered in modular stages. The research highlights a barbell effect: many IT projects meet their budget, but a significant minority collapse with extreme overruns. Leaders cannot assume a single failure will be rare or containable. By staging releases, using feature flags, and designing for modularity, we can reduce the risk of a total shutdown when one part goes wrong. This ensures that even if a module slips, core services remain available and public trust is protected.

Budgeting

Reserves need to be ready at the portfolio level, not only at the project level. For projects that start moving into the extreme tail, pre‑defined kill‑switches and pivot options should be in place. Metrics such as change‑request velocity, the number of integration dependencies, and the share of bespoke code can serve as early warnings for governance. Budgets and stage‑gates should be built around P80–P95 cost forecasts. Tracking and reporting exposure at the portfolio level makes it possible to see the bigger picture and prepare for rare but damaging overruns.

Reducing bespoke design

Departments should favour platforms, commercial off‑the‑shelf products, and APIs to reduce the complexity that drives extreme outcomes. Measuring the share of configurable versus bespoke scope as a key performance indicator provides leaders with a clear picture of where their exposure lies.

Flyvbjerg’s broader work, including How Big Things Get Done, reinforces the same point. He argues that the best way to reduce risk is to treat projects like building with Lego: using repeatable, modular blocks that can be assembled in reliable ways. When organizations insist on unique, one‑off designs, they expose themselves to greater uncertainty, slower delivery, and larger cost blowouts. The goal should not be to chase uniqueness, but to build on proven, standardized components wherever possible. This mindset makes IT projects more predictable and keeps them within manageable levels of risk.

Monitoring and governance

Early‑warning metrics such as change‑request velocity, dependency counts, defect discovery rates, and interface churn should be monitored closely to detect risks before they escalate. Kill‑switches and de‑scope paths should be pre-authorized so that projects can pivot quickly if warning signs mount. Independent “think‑slow” reviews provide an additional check on momentum that can otherwise carry troubled projects too far.

Workforce and procurement

Contracts should be built around modularity and standard interfaces. Vendors should be incentivized to reduce integration complexity. Avoid monolithic statements of work that lock in bespoke design. Integration architects, platform engineers, and commercial specialists are all needed to enforce modular procurement and reduce complexity. Investing in these capabilities strengthens the foundation for managing IT as a distinct risk class.

What To Do

Asking the right questions is one of the most practical tools we have to spot risks early and decide how to respond. Here are five areas to probe to help reduce exposure and improve outcomes.

Where do we see “bespoke by default,” and how could we modularise without losing mission fit?

Leaders should ask whether solutions are being custom-built when existing platforms or components might work. Explore how modularisation can preserve mission needs while cutting down on unnecessary complexity and risk.

What tail-specific indicators should we adopt to trigger gatekeepers early?

Metrics like change‑request velocity, the number of integration dependencies, and the share of bespoke code can warn when projects are drifting into the extreme tail. These signals should trigger earlier reviews before overruns take hold.

How should we rebalance contingencies between project and portfolio levels for fat-tailed IT risk?

Reserves may be more effective at the portfolio level, where extreme risks can be absorbed across projects. Leaders should consider whether current contingency practices reflect the reality of fat-tailed risk.

Which procurement levers best reduce integration interdependencies and scope volatility?

Breaking contracts into smaller, modular packages, building in incentives for simpler integration, and avoiding monolithic statements of work are practical ways to reduce volatility and complexity.

When should we pivot from build to buy to reduce exposure to extreme risk?

Consider thresholds where bespoke development becomes too risky, and where configurable off-the-shelf or platform solutions can achieve the same outcomes with less exposure.

Wrap up

Flyvbjerg’s research shows why IT projects stand apart and why we need a different toolkit to manage them. The main ideas are straightforward: recognize IT as its own risk class, use the outside view to check optimism bias, and rely on modular, proven components instead of chasing uniqueness.

As you think this through, here are three questions to reflect on:

1. Are we managing IT initiatives as if they are uniquely risky, or as if they are just like other major projects?

2. What would it take to embed tail-aware budgeting and governance practices into our institutions?

3. How can we shift from bespoke builds toward modular approaches that better manage risk?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Governments everywhere are feeling the squeeze: rising expectations, shrinking budgets and workforces, and complex delivery challenges.

In response, the United Kingdom established the Office for Value for Money (OVfM) within HM Treasury in late 2023 to support a Spending Review and improve the way government spending is planned, assessed, and delivered.

Today we explore why the UK created this office, how it’s structured to deliver impact, and what lessons we can apply to our own organisations, even at a much smaller scale.

So grab your morning coffee, and let’s get started.

Why the UK Created the OVfM

The OVfM emerged from recognizing that good intentions and policy ambition are not enough. Public spending can drift without a clear focus on outcomes, resulting in duplication, waste, or missed opportunities. The UK needed a way to challenge this pattern and make value for money a foundational principle, not an afterthought.

The unit was set up with a clear objective: to improve how the UK government assesses, delivers, and evaluates public spending.

In particular, it focuses on high-risk areas, where multiple departments contribute to complex delivery chains. These are exactly the situations where accountability can blur, and inefficiencies creep in.

Rather than relying solely on traditional oversight tools like audit and evaluation, the UK Treasury wanted something more proactive and embedded. The OVfM is designed to operate in real-time, supporting investment decisions before the money is spent and helping departments plan and deliver more strategically.

The UK’s Approach: Practical, Focused, and Collaborative

The OVfM is intentionally lean. It is a time-limited unit, designed to make a big impact in a short window, with a mandate to advise the Treasury during the current spending review period. Rather than creating a large, permanent body, the UK Treasury opted for a focused and nimble team that could operate with urgency and flexibility, providing high-value insight when it is most needed.

The OVfM applies a structured, repeatable approach grounded in analysis, challenge, and partnership. It is not an auditing body, nor a performance measurement unit. It works alongside departments to:

• Study high-risk policy areas (where multiple players and unclear accountability can derail outcomes)

• Assess investment proposals using clear, repeatable criteria

• Support strategic delivery by building capability and improving

To deliver on this purpose, the OVfM uses three key mechanisms that reinforce each other: value-for-money studies, investment appraisal criteria, and continuous evaluation and learning.

Value-for-Money Studies

These are in-depth, cross-cutting assessments of high-risk policy areas, particularly where responsibilities span multiple departments or involve complex delivery chains. The OVfM leads these studies to explore whether programs are achieving their intended outcomes and whether they represent a worthwhile use of public funds.

Importantly, the goal is not to assign blame.

Instead, the focus is on collaborative learning: identifying inefficiencies, overlaps, or delivery risks and using evidence to generate practical options for reform. Departments are involved throughout the process, ensuring findings are relevant, feasible, and actionable.

Investment Appraisal Criteria

To inform spending review decisions, the OVfM developed a consistent framework for assessing the quality of investment proposals. These criteria focus on several key questions, like:

• Does the proposal clearly define its objectives?

• Is it aligned with cross-government priorities?

• Does the delivery team have the capability and track record to execute it

• Have lessons from previous, similar investments been incorporated?

• Is the financial and delivery plan realistic?

This structure helps cut through optimism bias and makes it easier to challenge assumptions. You can find more great questions to ask on the OVfM Investment appraisal criteria page.

Evaluation and Learning

The OVfM also commits to learning from its own work. Through a light-touch evaluation plan, it collects feedback on the impact of its studies and appraisals, the usefulness of its recommendations, and the quality of engagement with departments.

This self-evaluation is used to improve internal processes, identify gaps in capability, and inform decisions about the future of the model itself. Rather than defending past decisions, the emphasis is on continuous improvement. This ensures that the office remains relevant, responsive, and effective over time.

Lessons We Can Apply at Home

We may not have a national treasury behind us. Still, the OVfM model offers practical ideas that can be scaled to fit our organizations on a smaller scale.

Here’s how I see it.

1. Make Value a Shared Responsibility

The OVfM model demonstrates that value should be a shared responsibility across program, policy, delivery, and finance functions. Building this culture requires intentional steps:

• Define value metrics early, before initiatives are launched, and ensure they reflect both efficiency and outcomes.

• Embed a "challenge function" in planning processes to ask tough questions and test assumptions without being adversarial.

• Host joint planning or review sessions where multiple functions come together to explore if an initiative is on track to deliver its intended value.

Creating shared ownership of value reinforces accountability and breaks down the silos that often undermine delivery.

2. Focus on High-Risk, Cross-Cutting Issues

The OVfM targets areas where spending is significant, risk is high, and multiple players are involved. These are often the areas where nobody owns the full picture.

In your organization:

• Identify priority areas where multiple business lines or teams contribute to a shared goal, but coordination is weak.

• Map decision points and data gaps to understand where risks are emerging.

• Set up temporary task teams to focus specifically on these thorny issues, with a mandate to recommend actionable changes.

Don’t try to boil the ocean. Focus your efforts where confusion or duplication is costing you the most.

3. Build a Simple Review Framework

One of the OVfM’s most practical contributions is a checklist of criteria for assessing proposals. This doesn’t require a new system or software. You just need a commitment to asking the right questions.

You can build your own framework by:

• Drafting five to ten core review questions to apply at intake, mid-point, or during project planning (take inspiration from the OVfM’s questions linked above).

• Focusing on clarity of objectives, delivery readiness, past lessons, alignment with strategic goals, and financial realism.

• Making the review process transparent and repeatable so that staff understand how proposals are assessed and improved.

This approach improves quality without adding red tape.

4. Use Time-Limited Units to Accelerate Change

Permanent structures often struggle to do new things quickly. The OVfM’s short-term, focused nature gives it the space to challenge, learn, and recommend without the constraints of long-term bureaucratic roles.

To replicate this:

• Set up small, fixed-term teams with a clear mandate and access to leadership.

• Use them to explore a specific challenge, review a portfolio of work, or pilot a new approach.

• Ensure they have independence and visibility—and disband or evolve them once their task is complete.

These "pop-up" models offer a practical way to break through inertia and make focused progress on complex issues.

The UK model is designed for impact over permanence. Sometimes, creating a dedicated (but temporary) team focused on solving a specific strategic issue is more effective than reworking permanent structures. A pop-up review team or task force can be stood up quickly with the right people. And, if it is given the right authority, can unlock real improvements.

Wrap up

The UK’s Office for Value for Money is an excellent blueprint for smarter spending, and I think it’s very adaptable on a smaller scale. It reminds us that discipline doesn’t have to mean delay. That being critical can still be collaborative. And that small teams, with the right mandate, can create big shifts.

Reflective questions to take away:

• What are your organization's high-risk, cross-cutting issues, and who’s responsible for their success?

• How might you embed a "challenge function" into your planning processes without creating gridlock?

• What would it take to build a culture where identifying delivery risks and questioning assumptions is seen as a shared responsibility, not an exception?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Today, we continue looking into how the UK is transforming how it thinks about procurement: the Social Value Model. This builds on our previous discussion about the Public Services (Social Value) Act 2012, which laid the foundation for embedding social value into procurement decisions. While the Act required public authorities to consider the social impact, the Social Value Model takes it further—moving from consideration to action by making social value an explicit evaluation criterion in procurement.

Traditionally, procurement focused on cost, efficiency, and service delivery. But what if contracts could also drive social change, support economic equality, and help communities thrive? That’s exactly what the Social Value Model aims to achieve.

Grab your morning coffee and let’s get started.

What is the Social Value Model?

Public procurement is a powerful tool. With billions spent on contracts yearly, what if that money could do more than buy goods and services? What if it could tackle unemployment, reduce inequalities, and even combat climate change?

That’s the thinking behind the Social Value Model, introduced in December 2020 as part of the UK government’s drive to embed social value in procurement. It builds on the Public Services (Social Value) Act 2012, which required public authorities to consider how procurement could improve social, economic, and environmental well-being.

The Social Value Model goes further, requiring all major contracts to explicitly evaluate social value as part of the decision-making process. In short, it’s no longer just about what’s being procured—it’s about the impact that procurement creates.

The Five Pillars of Social Value

The model defines five key themes that should be considered in procurement decisions:

1. COVID-19 Recovery – Supporting local communities in bouncing back, including job retraining, mental health initiatives, and workplace adaptations.

2. Tackling Economic Inequality – Encouraging new businesses, fair wages, and opportunities for underrepresented groups.

3. Fighting Climate Change – Promoting carbon reduction, green supply chains, and sustainable resource use.

4. Equal Opportunity – Ensuring fairness in hiring, career progression, and supplier diversity.

5. Well-being & Resilience – Improving health and mental well-being and fostering strong, connected communities.

Each procurement process must consider how contracts align with these themes, ensuring tangible social impact alongside service delivery.

Why Does This Matter for Public Sector Transformation?

The Social Value Model is more than just a policy—it represents a fundamental shift in how governments and organizations approach procurement. Here’s why it matters:

🔹 Moves from compliance to impact – Instead of treating procurement as a checkbox exercise, it ensures contracts deliver measurable social benefits.

🔹 Encourages innovation – Suppliers are now competing based on creative solutions to social challenges, not just price.

🔹 Shifts accountability – Contractors must measure and report on their social value contributions, ensuring transparency.

🔹 Aligns with global goals – The model supports multiple United Nations Sustainable Development Goals (SDGs), linking local actions to global impact.

Challenges and Opportunities

Challenges:

• Defining and measuring social impact in procurement decisions can be complex, as it requires clear metrics, tracking systems, and methodologies that go beyond traditional financial indicators.

• Balancing cost-efficiency with ambitious social value targets is a persistent issue. Organizations must weigh the financial bottom line against the long-term benefits of socially responsible procurement.

• Avoiding “social value washing” is critical, where organizations claim to deliver social value but fail to provide verifiable results. Ensuring proper reporting mechanisms and accountability structures is necessary to prevent superficial commitments.

Opportunities:

• Embedding equity, sustainability, and resilience into public contracts fosters long-term social progress and ensures procurement becomes a tool for systemic change.

• Leveraging procurement as a strategic tool for transformation allows governments to drive broad societal improvements while securing necessary goods and services.

• Encouraging public-private partnerships to co-create solutions creates opportunities for innovative collaborations, where businesses and government agencies work together to design and implement impactful programs that deliver measurable social outcomes.

What Can We Learn from This?

The Social Value Model forces organizations to rethink procurement from a value-driven perspective. Some key takeaways:

• Measurement is key – Data-driven decision-making will separate genuine impact from empty commitments.

• Procurement teams need new capabilities – Expertise in social policy, sustainability, and community engagement is becoming essential.

• Public-private collaboration is vital – Governments and suppliers must work together to define and achieve meaningful outcomes.

Wrap up

Public procurement is not just about acquiring services but about shaping the future. The Social Value Model is a bold attempt to make public spending work for everyone. But it’s not a plug-and-play solution; it requires rethinking priorities, processes, and partnerships.

Over to you:

1. How can procurement teams better define and measure social value?

2. What role should private sector partners play in delivering social impact?

3. What’s stopping public organizations from making social value a core procurement metric?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Let’s begin with a thought experiment that’s more than two thousand years old, but one that’s been hitting close to home for me lately as I try to lead change: Imagine trying to explain the need for change to people who are absolutely certain they already see things clearly.

Sound familiar?

This is the heart of Plato’s famous allegory of the cave. It’s a story about what happens when people mistake partial truths for the whole picture, and why it’s so hard to help them see beyond it. For those of us leading from the top or trying to influence from below, it offers a powerful perspective for understanding one of the toughest challenges in our work: helping people see what they cannot, or choose not to.

This week, we’ll explore how Plato’s Cave can guide us in leading cultural change inside organizations that are, in many ways, still chained to status quo. We’ll start with a quick look at the original allegory and what it tells us about perception, belief, and resistance to new ideas. Then, we’ll connect the story to the lived experience of leading transformation in the public sector, both from positions of authority and from the middle of the hierarchy.

Whether you’re a senior leader trying to influence from above or a quiet catalyst working from below, we’ll close with practical advice on how to help others shift their thinking without triggering defensiveness or resistance.

Grab your morning coffee, and let’s get started.

The Allegory of the Cave

In Plato’s Republic (Book VII), Socrates introduces a story to explain how people come to understand the world around them. He asks a fellow character, Glaucon, to imagine a group of people who have spent their entire lives chained inside a dark cave, unable to move or turn their heads. (N.b. Glaucon, Plato’s real-life brother, often appears as Socrates’ dialogue partner in the Republic.) They are fixed in place, able to see only the cave wall before them. Behind them, a fire burns, and between the fire and the prisoners is a walkway. Other people pass along this walkway carrying various objects and statues, which cast moving shadows on the wall. The prisoners, having never seen anything else, mistake these shadows for the entirety of reality.

Plato uses this scene to show how human beings often take appearances or partial truths to be the whole, simply because they lack access to a broader context. What we call knowledge may in fact be habituated belief, reinforced by collective repetition and unchallenged assumptions.

The cave becomes a closed system of perception and belief, maintained by shared language and social norms. It represents a condition in which people are imprisoned not by force, but by the structure of their experience. The prisoners' error lies in treating what is available to them as the only possible reality. An error that often occurs in cultures or institutions resistant to change.

Eventually, one prisoner is freed. At first, he is overwhelmed and confused. Turning to see the fire (the source of the shadows) hurts his eyes. He initially wants to return to what he knows. But he is guided out of the cave and gradually begins to adjust to the brightness of the outside world. He first sees shadows, then reflections, then objects, and eventually the sun itself. Plato explains that the sun represents the “Form of the Good,” the highest and most important idea in his philosophy. Just as the sun makes physical things visible and provides life, the Form of the Good allows us to understand everything else. It gives meaning, structure, and purpose to what we know.

The allegory continues.

The freed prisoner returns to the cave, motivated by a sense of duty to those still in chains. However, upon re-entry, he struggles to see in the darkness. The others, seeing his disorientation, assume his journey has weakened him. To them, his inability to navigate the shadows is a sign of diminished capacity. As Plato points out, they would reject his insights, and if they could, might even kill anyone who tried to free them.

This final piece is critical: It suggests that the pursuit of truth is not only difficult but politically and socially dangerous.

Scholars have emphasized that Plato's cave is a commentary on education as liberation and the hostile reaction that often follows efforts to challenge settled worldviews.

The Modern Cave: Leading in a Culture Stuck in the Status Quo

The allegory struck me as a commentary on transformation, and on the courage required to see clearly, speak openly, and help others do the same.

This allegory maps strikingly well onto the experience of leadership in systems resistant to change.

In many organizations, I’ve experienced teams and leaders who operate with deeply embedded ways of thinking. These beliefs are the shadows on the wall. They may have once served a purpose, but they often persist long after their value has faded. Leaders who question them or propose alternatives risk being seen as naïve, unrealistic, or disruptive.

In cultures perpetuating these ideals, rules and routines often carry the weight of tradition. New ideas, even those grounded in evidence, can be dismissed if they challenge long-standing narratives. Legacy thinking and incentive structures may push teams to prioritize short-term outputs at the expense of long-term value. In both cases, people operate in the cave not out of ignorance, but because the system rewards familiarity and punishes deviation.

Those who begin to see differently, whether through reflection, education, time spent in other organizations, or exposure to new ideas and perspectives, often develop a broader view of what is possible. These experiences help them step outside the cave (or come from outside the cave), and see that the shadows are not the full story. The ability to see differently often comes from a combination of learning, lived experience, and critical distance. And when people have this shift in awareness, they often feel a duty to return and help others see.

That is leadership.

But it is rarely welcomed without resistance. The reaction of those who remain in the cave, immediately dismissing the possibility that they might be wrong and assuming that the returning prisoner is damaged by the experience, reveals something deeper. It reflects a mindset that resists reflection and growth. People who respond this way lack the openness, humility, and curiosity that effective leadership demands.

True leadership requires more than holding tightly to what is known. It calls for the courage to step into the unfamiliar, to ask questions, and to explore what might lie beyond the limits of current understanding.

Advice for Leaders Trying to Lead Others Out of the Cave

What can leaders do when they see a better way forward, but the culture resists?

The guidance that follows offers advice for two common situations: when you are in a position of leadership trying to help others shift their thinking, and when you are not in charge but those above you remain stuck in outdated assumptions. These are very different challenges:

• Leading change from the top allows for greater influence but requires empathy and clarity.

• Leading change from below demands diplomacy, persistence, and a careful understanding of power dynamics.

In my experience, many of us find ourselves in the second situation more often than the first.

Here are five principles that reflect what we can learn from Plato’s allegory and the everyday reality of trying to move a system forward.

1. Respect the Shadows

Dismissing current practices as illusions rarely works. People do not cling to the status quo because they enjoy stagnation. They do it because the known feels safer than the unknown.

If you are in a leadership role, begin with empathy. Acknowledge the reasons people believe what they believe. Ask questions to understand what needs are being met by current practices. This builds trust and makes space for evolution, not confrontation.

If the people in the cave are above you, show respect for their experience while carefully introducing alternative perspectives. Avoid framing your insights as corrections. Instead, position them as extensions or refinements that build on existing knowledge.

2. Start with Light, Not Fire

People cannot go from darkness to full sunlight in one step. Instead of confronting deeply held beliefs head-on, help others experience small shifts in perspective. Share stories. Surface overlooked data. Encourage experimentation. Let them see cracks in the wall for themselves. Insight grows through experience, not instruction.

If you are leading others, break change into manageable steps. Give people a chance to test new ways of thinking before fully committing to them. Create safe environments for curiosity.

If your challenge is to influence those above you, your leverage may lie in framing. Highlight incremental improvements. Use pilot projects and lessons learned to introduce change gradually without provoking defensiveness.

3. Model What You’ve Seen

The freed prisoner does not simply talk about the sun; he returns changed. Likewise, leaders must embody the change they advocate. If you want to shift from control to trust, show what trust looks like. If you want more creativity, create space for it. When your behaviour reflects your message, people are more likely to listen.

When you are leading others, your actions carry weight. Let people see the benefits of new thinking in how you work and interact. Demonstrate the mindset and behaviours you hope to inspire.

When influencing upward, credibility matters. Be consistent. Let your calm, clarity, and results show that your perspective is grounded and reliable. Show that your vision is not a personal agenda, but a constructive path forward.

4. Build Coalitions, Not Just Cases

You are not the only one who senses the limits of the system. Find others who are already turning around. Support them. Learn from them. Change accelerates when people move together. Focus less on winning the argument and more on building shared momentum.

If you lead a team, create space for collaboration across roles and functions. Encourage others who “get it” to share their insights. Normalizing new thinking can have more impact than top-down direction alone.

If you are lower in the hierarchy, look for informal networks. Influence rarely travels in a straight line. It often spreads through trust, consistency, and quiet alignment among people who share a concern or aspiration.

5. Prepare for Resistance, and Stay the Course

Returning to the cave is hard. Plato’s allegory ends with the freed prisoner being rejected. Real change is rarely met with immediate applause. That does not make it wrong. As a leader, your role is not only to see the truth. It is to persist. Keep inviting others toward the light, even when they hesitate.

If you are in a leadership role, accept that resistance is part of the process. Don’t take it personally. Stay clear on your purpose, and create regular opportunities for learning, reflection, and dialogue.

If you are influencing from below, resistance can feel more personal and harder to navigate. Keep your expectations realistic. Be consistent. Small acts of clarity, kindness, and courage can have outsized impact over time, even if they are not immediately recognized as leadership.

Wrap up

Plato’s cave makes us think about how change about more than structures or strategies. We need to focus on people, mindsets, and the very human challenge of seeing beyond what we’ve always known.

Helping others step out of the shadows takes conviction. Perhaps moreso, it takes patience, empathy, and a deep understanding of how change actually happens. Whether you're leading from the front or nudging from below, the work matters. And it starts with seeing clearly yourself.

Before you go, here are a few questions to reflect on this week:

• What “shadows” are you noticing in your organization: beliefs or routines that are mistaken for truth?

• Have you ever returned to the cave with a new perspective? How was it received?

• What’s one small thing you can do this week to help someone else see a little differently?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

Let’s start today with a simple thought experiment:

Imagine walking your organization’s (virtual) halls and casually asking people this simple question, “What do you do?”

How would they respond?

Stop reading for a minute and really think about this question (don’t cheat)!

Did your people answer by

1. describing their daily tasks, or

2. how their work matters and helps your mission?

Why is this important?

How employees see and describe their roles says a lot about your organization’s values and how well they align with the mission. A value-centric culture can motivate every member of an organization to see their work as part of a larger mission. While this concept is often highlighted in the private sector, it is equally, if not more, important for public sector organizations. Fostering a sense of purpose among employees in the public sector, where missions usually revolve around service and societal improvement, can significantly enhance effectiveness and impact. In fact, it’s a major part of Heintzman and Marson’s Public Sector Value Chain model, which I’ve written about in many articles (see this list).

That’s the premise of today’s article. We’ll start with a well-known anecdote involving a famous US President and a janitor at NASA and use this to explore the importance of value-centric cultures in the public sector. A clear and inspiring mission can unify diverse roles, outline the steps to establish and maintain such a culture and discuss the crucial role of leadership in this process.

Grab your morning coffee, and let’s get started.

The NASA Janitor Story

The story of the NASA janitor is a nice illustration of how every role within an organization, no matter how seemingly insignificant, contributes to its larger mission.

To put it into historical context, President John F. Kennedy delivered his famous “We Choose to Go to the Moon” speech in September of 1962, where he set the ambitious goal of putting an American on the moon and returning them safely to Earth before 1970. At this point in history, the US was well behind the USSR in the Space Race. Kennedy’s proclamation was a big surprise and a huge push. It’s, in fact, where the term “Moon-Shot” was born. His speech galvanized the nation, providing a clear, compelling vision that united and motivated the country.

As the story goes, during a subsequent visit to the NASA Space Center, Kennedy met a janitor carrying a broom down the hallway. The President casually asked the janitor what he did for NASA, and the janitor replied,

“I’m helping put a man on the moon.”

Stop for a moment and think about that and how you visualized your people’s response.

(While the exact historical accuracy of the story is sometimes debated, let’s not let facts get in the way of a good story!)

It is a powerful anecdote about how the janitor saw beyond his daily tasks and understood how his work contributed to NASA’s ambitious goal of landing a man on the moon. The janitor’s response encapsulated a deep sense of purpose and connection to this broader goal, embodying the idea that every role is vital to achieving the organization’s objectives.

It highlights a crucial aspect of successful organizations: the ability to instill a shared mission that resonates with every employee. This sense of purpose can transform mundane tasks into meaningful contributions, fostering a culture where everyone feels connected to the larger objective. In NASA’s case, this unified vision was critical in achieving one of humanity’s most significant milestones.

The story also serves as a reminder of the power of leadership in communicating and reinforcing a vision.

What Does a Value-Centric Culture Look Like?

A value-centric culture is one where employees understand the why behind their work. It goes beyond job descriptions and tasks. People in these environments understand their roles in terms of outcomes, not inputs. They talk about who they help, what problems they solve, and why their work matters.

In these cultures, purpose is embedded in the everyday. Meetings, updates, performance reviews, and even informal conversations reference the organization’s mission and the value being delivered. Employees feel proud of their contributions and know how their work fits into the broader picture.

Most importantly, value-centric cultures aren’t accidental: they are built and maintained intentionally through stories, systems, and leadership that reinforce a shared sense of purpose.

Why This Matters in the Public Sector

Public servants serve the public good, steward public funds, and address complex societal challenges. Yet the connection between daily work and public outcomes can sometimes feel distant, especially for those who don’t work on the front lines.

This is where a value-centric culture becomes especially important. When public servants see how their work improves lives, directly or indirectly, they are more likely to feel motivated, engaged, and committed to excellence. It humanizes the bureaucracy, making work feel personal and purposeful.

A payroll clerk, ensuring that benefit payments are accurate and timely, is helping families meet their basic needs. A procurement officer navigating a complex contract enables critical digital service delivery. A project manager streamlining internal processes frees up capacity to better serve Canadians.

These connections need to be made visible and reinforced.

Building the Culture: Five Practical Steps

Creating a value-centric culture is a continuous practice built on intention, trust, and visibility. Here are five steps public sector leaders can take to bring this culture to life:

• Tell meaningful stories: Share real examples of how the work makes a difference. Stories make purpose tangible.

• Encourage reflection: Help people think about how their role contributes to the mission. Ask, “Who benefits from your work?”

• Recognize contributions: Celebrate achievements at all levels, especially those that align with mission impact.

• Integrate purpose into routines: Make space in meetings, reviews, and onboarding to discuss value and outcomes.

• Model the mindset: Leaders should consistently frame their public value, not just tasks or outputs.

The Role of Leadership

Leaders set the tone for the culture.

They shape the conversations, highlight what matters, and reinforce how success is defined. If leaders talk only about deadlines and deliverables, that’s what people will prioritize. However, that mindset will take root when they speak about public good, service, and mission.

Leadership in a value-centric culture means:

• Framing work in terms of its impact on people.

• Listening to and amplifying employee stories that reflect the mission.

• Holding space for conversations about purpose, not just performance.

• Reinforcing that every role, no matter how small, contributes to the whole.

This doesn’t require charisma or perfection. It requires consistency, authenticity, and an unwavering focus on the people we serve.

Wrap Up

So, next time someone asks, “What do you do?” how will YOU answer? Would you list your duties or describe your role in delivering value to others?

When employees at all levels see their roles through the lens of purpose, the organization becomes stronger, more resilient, and more capable of serving the public good.

That’s the heart of a value-centric culture.

Now go ask folks around you: “What do you do for XXXX (department, branch, division, etc…)?” And see what they say.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

This week’s post is a bit more personal. I hope you’ll take the time to read it because I feel like this is one of the most important pieces I’ve written.

After an unexpected pause from work, I found myself stepping back from the pace and pressure of the office. Without the usual flood of deadlines, fires to put out, and an inbox that never seems to rest, I had space to reflect. Without the daily noise, one question kept repeating itself in my head:

Not why am I here, or why are you here in a particular role or department, but why we, as public servants, exist. What is our collective purpose?

It’s a question we don’t ask ourselves often enough. And yet, without a shared answer, how can we know if we’re truly making a difference?

It reminds me of something someone told me very early in my public service career (like the first few weeks) that has stuck with me all these years. I was fresh out of graduate school, still wet behind the ears, and someone (I can't remember who) said, “At the end of every day, as you walk to your car, ask yourself: did Canadians get their money’s worth today?”

But how can we answer that question if we haven’t taken the time to reconnect with our true mission: something deeper than project outputs or departmental mandates, something rooted in the public good?

As a bit of a personal exercise, I decided to reflect on our purpose. I wrote down what felt meaningful to me, something that captured what I believe we’re really here to contribute.

Today, I want to share it with you and unpack why I framed it the way I did.

Grab your morning coffee, and let’s get started.

Our Purpose in Public Service

Here’s what I’ve come up with. You may not agree with every word, and that’s okay. This statement is shaped by my own experiences, informed by the work of others, and refined through countless conversations with thoughtful people over the years. I found it really healthy and meaningful to try to put all these feelings and experiences into the following words:

The role of our government is to promote the prosperity and well-being of the country and its people, both now and for future generations. Prosperity can mean many things: a good quality of life, public health, safety and security, access to opportunity, a sustainable environment, economic growth, and a society grounded in equity and fairness. These are just some of the elements that make a country stronger and enhance the lives of those who call it home. In short, it’s about building a stronger country and improving people’s lives.

Our public service plays a key role in making this vision a reality. It is expected to be professional, merit-based, and non-partisan, serving the government of the day with integrity and competence. Public servants contribute by delivering programs and services, offering evidence-informed advice, supporting implementation, and managing public resources responsibly.

As they carry out these responsibilities, they are expected to respect democratic institutions and the rule of law, and to uphold the trust placed in them by Canadians. High-quality, fair, and consistent service helps build and sustain public trust and confidence in government, which is reinforced by clear lines of accountability: public servants support and report through their deputy ministers to elected ministers, who are accountable to Parliament, and in turn, to Canadians.

The ultimate goal of the public service is to serve Canadians by helping government work better for everyone.

Why Each Part of This Purpose Matters to Me

I want to walk you through how I arrived at each part of this purpose statement. I’ll break it down piece by piece and explain my thinking behind it: why I included each element; how it reflects what I’ve seen and learned in public service; and why I believe it matters for all of us who are trying to make government work better.

Let’s take a closer look.

1. The Role of Government: Promoting Prosperity and Well-Being

I started with the role of government because it provides a clear and shared foundation for public service. We need to remind ourselves that government isn’t some abstract idea, that it exists for a reason. I believe that the reason is to improve the country and the lives of its people. That belief gives us a compass, a North Star, to help guide the work we do in service of government and its citizens.

It’s worth emphasizing that disagreement is expected in a democracy, and it’s essential. As citizens and participants in a democratic society, we won’t always agree with the politics or policies of the day. That’s both natural and healthy. But what matters most is that we maintain a foundational belief: that our government and opposing voices alike are acting in good faith, striving to do what they believe is best for the country. Even if we disagree on the specifics, we need to trust that others are motivated by a sincere commitment to the public good. Without that shared belief, it becomes much harder to uphold the idea that government exists to serve everyone.

Still, we live in a time when many people feel disconnected or disillusioned, and that makes this core purpose harder to see and harder to believe. Cynicism takes root. Trust erodes, and when trust goes, our institutions lose their legitimacy. That’s why our responsibility as public servants is to show up with a mindset grounded in service: to believe that while people will always differ on how to achieve prosperity, they all deserve a system that is genuinely trying to make life better. Without a shared understanding of what prosperity and well-being mean, how can we measure progress? How can we agree on what progress looks like?

What this means for how we act as public servants: This part of the purpose reminds us to stay focused on outcomes that genuinely improve people’s lives. It means asking: How does what I’m doing contribute to the public good? Who benefits? Who might be left out? Living up to our mission requires us to be outcome-driven, citizen-centred, and future-focused in everything we do.

2. The Role of the Public Service: Being the machine that turns this vision into reality

The government cannot fulfill its role without a capable and trusted public service. We bring that role to life in many ways: by delivering services, offering sound advice, implementing decisions, and acting as stewards of public resources. But how we do this work matters just as much as what we do. Our work must be grounded in core public service values: non-partisanship, professionalism, ethics, and a sincere desire to serve the public good. These values must shape how we show up. We should be seen as people who genuinely care about making this country better, with the heart of the country on our sleeves.

This means we are more than task-doers, decision-makers, or advice-givers. We are enablers of the government’s mission. When we see ourselves that way, our work takes on deeper meaning. It creates alignment between our values and our actions. That alignment fuels motivation, pride, and professionalism. And yes, people notice. Citizens notice. That’s when public confidence grows. That’s the pot of gold at the end of the public-sector value chain: not just outputs, but trust—credibility.

What this means for how we act as public servants: It means seeing ourselves as more than implementers. We are the stewards of the public good. We must approach each task, big or small, with care, with competence, and with integrity. We must stay anchored in facts, committed to evidence, and guided by fairness. We must speak truth to power with respect, ensuring that our services and advice reflect much more than personal interest or political convenience. It must reflect a genuine commitment to serving the public good.

3. Accountability: Serving Canadians, Not Just Systems

For the final part, I chose to focus on accountability. Trust is built when there is clarity about who is responsible for decisions and outcomes. While individual public servants are not always in the public eye, that doesn’t mean we are anonymous or unaccountable. We are part of a democratic chain of accountability: our work flows upward through organizational hierarchies, with deputy heads accountable to democratically elected ministers, who are themselves accountable to Parliament, and through Parliament, to the Canadian public.

This chain of accountability matters. Policy decisions are made by ministers and the cabinet, but it’s up to us, as public servants, to make the most of those decisions. We’re responsible for providing the best possible advice and for implementing those decisions with care and competence. Ultimately, it’s the public who will decide through elections and democratic engagement whether those decisions were right or wrong. That’s how democracy works.

Our role is to uphold the legitimacy of that process, which means acting with integrity, ensuring our work serves the public interest, and recognizing that our authority doesn’t come from titles or organizational charts. It comes from the democratically elected people we support and the trust Canadians place in our institutions. When we remember that we’re ultimately accountable to Canadians, it helps us focus on what matters. We choose service over self-interest, honesty over convenience, and long-term impact over short-term gains. That kind of accountability is vital to the health of our democracy.

What this means for how we act as public servants: It means accountability is about earning and maintaining public trust in every action we take. It means making decisions transparently, acting consistently, and staying mindful of how our work affects people’s lives. It also means respecting the democratic system we are part of, including the elected officials we support and the institutions that represent the will of the people. We should be able to look at anything we’ve done and answer, with confidence: "If a Canadian asked why I did this, would they see it as fair, honest, and worthy of their trust?"

Why This Matters Now

Trust in public institutions is at an all-time low. We’re navigating increasingly polarized environments, and as public servants, we’ve always worked under a high level of public scrutiny. In many cases, that scrutiny is warranted. Canadians are right to expect more from their institutions, especially when systems or individuals fall short of the extremely high standards the public deserves.

That’s exactly why reconnecting with our core purpose matters. Purpose helps us respond with humility, professionalism, and a renewed commitment to serving the public with integrity. It reminds us who we’re here for, and why the work matters.

We should regularly ask ourselves, “Why are we here?” Each of us might answer that question a little differently, and that’s okay. What matters is that we reflect on our answer and ensure it aligns with the values that define great public service: service, respect for democracy, integrity, stewardship, and excellence.

When individuals or systems fall short of these values, each and every one of us has a responsibility to act. Speak up. Raise concerns. Advocate for what’s right. Purpose doesn’t live in mission statements; it lives in choices. It takes courage to uphold it, but that’s what Canadians deserve from their public service.

What can we do?

Let’s start by setting titles aside. It doesn’t matter whether you’re a deputy head, a chief audit executive, an operational director, a policy manager, a service desk lead, an administrative assistant, or doing clerical support. Regardless of where you sit in the organization, you have the power and the responsibility to live the purpose. Here’s what you can do:

• Start with the why. Don’t just focus on the task at hand. Take time to connect your work to its impact. How is it helping real people? How is it making government work better?

• Make values visible. Let professionalism, integrity, non-partisanship, and service guide how you show up, whether in your tone, your decisions, or your day-to-day actions.

• Build accountability through meaning. Don’t just track activity. Take time to understand and explain how your efforts contribute to outcomes and trust.

• Protect time to reflect. Reflection is essential. Take a moment regularly to reconnect with why your work matters. And if you can, create space for your team or colleagues to do the same.

• Challenge what’s missing. When you see people or systems falling short of our shared purpose and values, don’t stay silent. Ask questions. Raise concerns. Offer alternatives. Speaking up is service. Purpose requires accountability, and accountability starts with us.

Wrap up

If we want to rebuild trust, deliver real impact, and serve Canadians in ways that matter, we need to do more than talk about purpose. We need to live it. We live it through our actions, we live it through our decisions, we live it through our courage, and we live it through our commitment to public service at its best.

So let’s leave off with a few questions to reflect on:

• How would you personally frame the purpose of public service?

• Does your current role or daily work reflect that purpose, or has something been lost in translation?

• What conversations could you start with your team to bring clarity, alignment, or renewed energy around that shared mission?

Until next time, stay curious and I’ll see you Beyond the Status Quo.

Happy Tuesday, Transformation Friends. Another week, another opportunity to go Beyond the Status Quo.

What if public procurement decisions weren’t just about cost, but about maximizing broader social, economic, and environmental value?

The UK asked this question over 10 years ago and set out to create the Public Services (Social Value) Act that challenges traditional procurement by shifting the focus from cost savings to long-term impact.

Since then, the Act has reshaped government procurement, ensuring that public spending contributes to economic growth, social well-being, and environmental sustainability. Instead of prioritizing cost alone, this law mandates that government contracts actively generate wider benefits for society.

Today, we’ll explore the purpose of the Act, its goals, and how it works in practice. We’ll also examine real-world case studies showcasing its impact.

Grab your morning coffee, and let’s get started.

What is the Social Value Act?

The Public Services (Social Value) Act 2012 requires public sector organizations in the UK to consider how their procurement decisions can create broader social value. This means that commissioners must also assess how services can contribute to local communities and economies instead of awarding contracts based solely on price.

The Act came into force on 31 January 2013, applying to all service contracts above the Official Journal of the European Union (OJEU) procurement threshold. However, many organizations have extended their principles to lower-value contracts and goods procurement.

In 2018, the UK government strengthened the Act by requiring major government contracts to explicitly evaluate social value as part of the procurement process. This change meant that departments could no longer just consider social value—they had to score and measure it when awarding contracts.

To help implement this shift, the Cabinet Office and the Department for Digital, Culture, Media and Sport (DCMS) developed the Social Value Model, introduced in 2021. This model provides a structured framework for government departments to assess social value across key themes, such as economic inequality, climate change, and equal opportunity. The model ensures consistency across procurement processes, making it easier for bidders to understand expectations and integrate social value into their proposals effectively.

Goals of the Social Value Act

The Act aims to shift procurement from a purely cost-based model to one that maximizes public benefit. Its key objectives include:

1. Improving Public Services

• Ensuring that public spending delivers long-term benefits for society.

• Encouraging innovation in service delivery by considering wider community impacts.

2. Boosting Local Economies

• Supporting small and medium-sized enterprises (SMEs), voluntary organizations, and social enterprises in securing public contracts.

• Encouraging job creation, apprenticeships, and skills development.

3. Enhancing Environmental Sustainability

• Prioritizing carbon reduction, waste management, and energy efficiency in procurement decisions.

• Encouraging businesses to adopt environmentally friendly practices.

4. Reducing Inequality and Promoting Social Inclusion

• Ensuring procurement benefits disadvantaged groups, such as the long-term unemployed or disabled individuals.

• Strengthening community resilience by supporting local projects and charities.

How Does the Social Value Act Work?

The Act requires public bodies to consider social value in procurement through three key stages:

1. Before Procurement

• Identify potential social value opportunities in upcoming contracts.

• Engage local businesses and organizations to shape procurement decisions.

2. During Procurement

• Include specific social value requirements in contracts.

• Evaluate bidders based on their ability to deliver social, economic, or environmental benefits.

3. After Awarding Contracts

• Monitor whether social value commitments are being met.

• Require suppliers to report on their social impact, such as job creation or carbon savings.

Case Studies: Social Value in Action

The UK conducted a review of the Act in 2014 (Lord Young’s review of the Social Value Act) and a positive effect where it is being taken up. Below are a few of the case studies:

Circle Housing – Value for Money and Apprenticeships

Circle Housing, a social housing provider, aimed to integrate social value into its procurement for maintenance and repairs.

How the Act Was Used:

• Required one apprenticeship for every £0.5 million worth of contract value.

• Used monetary values from HM Treasury Green Book to calculate social return on investment (SROI).

Results:

• Estimated £80 million cost savings over 10 years.

• Calculated an SROI of £5.40 for every £1 invested.

Start in Salford (Salford CCG) – Mental Health Through Creative Arts

Start in Salford offers creative arts programs to support mental health recovery and social inclusion.

How the Act Was Used:

• Salford Clinical Commissioning Group (CCG) incorporated mental health support initiatives into healthcare procurement.

• Contracts required providers to demonstrate social value impact, particularly in community well-being.

Results:

• Provided therapy through arts programs, improving mental health outcomes.

• Achieved a Social Return on Investment (SROI) of £6–£10 per £1 invested.

• Enhanced social inclusion, offering structured pathways into education, volunteering, and employment.

Durham County Council – Social Value in Banking Contracts

Durham County Council sought to maximize community benefits from its banking services contracts.

How the Act Was Used:

• Engaged potential providers before procurement to explore social value offerings.

• Included clauses requiring support for local financial education and credit unions.

Results:

• Financial education programs established for local communities.

• Local credit unions supported, improving access to fair lending.

Lambeth Council – Supporting Local SMEs

Lambeth Council focused on increasing procurement opportunities for small and medium-sized enterprises (SMEs).

How the Act Was Used:

• Embedded social value requirements into procurement policies.

• Identified SME-friendly contracts and simplified bidding processes.

Results:

• Increased local SME spending from £159 million to £180 million.

• Fostered economic growth in the local business community.

Cleanstart – Reducing Crime and Creating Employment

Cleanstart, a social enterprise, helps ex-offenders reintegrate into society through employment in property maintenance.

How the Act Was Used:

• Trafford Housing Trust embedded employment-focused social value requirements into contracts.

• Cleanstart was awarded contracts based on its ability to provide jobs and reduce reoffending rates.

Results:

• 40+ ex-offenders employed, with many moving into permanent jobs.

• Estimated cost savings of £442,000 for Greater Manchester Police due to reduced crime rates.

Wrap up

The UK Social Value Act reshapes public procurement by ensuring taxpayer money delivers wider benefits beyond cost savings. The Act is driving innovation in public service delivery.

Reflecting on these case studies, ask yourself:

1. How can social value principles be integrated into other public sector initiatives?

2. What challenges might arise in measuring and monitoring social impact?

3. How can private sector organizations align with social value objectives to secure government contracts?

Until next time, stay curious and I’ll see you Beyond the Status Quo.