Welcome back to Behind the Workflow...

The podcast where we laugh at business chaos...

Celebrate good processes...

Question questionable workflows...

And give a little love to the people working behind the scenes.

I’m Melissa...

Business Operations professional...

Workflow detective...

Recovering spreadsheet therapist...

And someone who has learned that if everything seems to be running smoothly...

There’s probably an Operations person somewhere making sure it stays that way.

(laughs)

Today is a little different.

Because this is Episode 12.

The Season One finale of Behind the Workflow.

And I thought...

What better way to finish the season than to go back to where we started?

Because over the last eleven episodes, we’ve talked about a LOT.

Documentation.

Meetings.

File names.

Process improvement.

Power Query.

Data modeling.

DAX.

Dashboards.

AI.

And automation.

And somehow...

We made it through all of that.

😂

But when I look back at all of those episodes, I realize there was really one story underneath all of them.

The story of how work actually gets done.

And more importantly...

The people doing it.

So let’s take one last trip...

Behind the Workflow.

🎉 Corporate Confession #12

Let’s start with one last confession.

Have you ever heard someone say...

“Everything’s running really smoothly.”

And then five minutes later...

Someone asks:

“So...what does Operations actually do?”

(long pause)

Oh...

Only everything.

😂

And that’s actually what this entire season has been about.

All those little things that happen behind the scenes...

That most people don’t think about...

Until something goes wrong.

Episode 1: Welcome Behind the Workflow

When we started this podcast, I wanted to talk about the stuff that doesn’t always get talked about.

Not just the big business decisions.

Not just sales.

Not just marketing.

Not just technology.

But the actual work that happens in between all of those things.

The processes.

The systems.

The spreadsheets.

The meetings.

The documentation.

The people connecting all the pieces.

Because somebody has to make all of that work together.

And that’s where Operations comes in.

Episode 2: Documentation

We talked about documentation.

And if you’ve ever worked in Operations, you already know...

Nobody thinks documentation is important...

Until the person who knows how everything works goes on vacation.

😂

Then suddenly everybody wants an SOP.

Documentation isn’t exciting.

But it keeps knowledge from living inside one person’s head.

And that became one of the recurring themes of this season:

Good processes shouldn’t depend on someone’s memory.

Episode 3: Meetings

Then we talked about meetings.

Because apparently...

We love meetings.

Meetings about meetings.

Meetings to prepare for meetings.

Follow-up meetings about the meeting we just had.

😂

But the real question was:

Does this meeting actually need to happen?

And that’s Operations thinking.

Not:

“How can we schedule another meeting?”

But:

“Is there a better way to accomplish this?”

Episode 4: File Naming

Then came file names.

And this one...

Well...

This one may have hit a little too close to home.

😂

Because we’ve all seen it.

FINAL.xlsx

FINAL2.xlsx

FINAL_FINAL.xlsx

FINAL_USE_THIS_ONE.xlsx

And eventually...

FINAL_FINAL_USE_THIS_ONE_REALLY_THIS_TIME.xlsx

At some point, you’re not managing documents anymore.

You’re solving a mystery.

But underneath the joke was another real Operations problem:

If people can’t find the information they need, they’re wasting time.

Something as simple as organization can have a huge impact.

Episode 5: Process Improvement

Then we got into process improvement.

And this might be one of the biggest themes of the entire season.

Because sometimes the problem isn’t the person.

It isn’t the software.

It isn’t the spreadsheet.

It’s the process.

And before we fix it...

We have to understand it.

Why does this step exist?

Who needs it?

Does it add value?

Can we simplify it?

Can we remove it?

And sometimes...

The best process improvement isn’t adding something.

It’s taking something away.

Episodes 6, 7 and 8: The Data Rabbit Hole

Then we went down the data rabbit hole.

Power Query.

Data modeling.

DAX.

And if you know...

You know.

😂

We went from:

“Let’s just clean up this spreadsheet.”

To:

“Well, technically, we need to talk about the data model.”

And suddenly you’re three hours deep into something you didn’t expect.

But data matters.

Because if the data isn’t right...

The report isn’t right.

If the report isn’t right...

The dashboard isn’t right.

And if the dashboard isn’t right...

We might be making decisions based on information that isn’t telling us the truth.

That’s why good Operations pays attention to the details.

Episode 9: Dashboards

Then came dashboards.

And I think dashboards are a perfect example of something that can be incredibly useful...

Or completely unnecessary.

Because a dashboard isn’t valuable just because it looks good.

It needs to answer a question.

What do we need to know?

What decision are we trying to make?

What action should happen because of this information?

Otherwise...

You don’t have a dashboard.

You have a really pretty collection of numbers.

😂

Episode 10: AI

Then we brought AI into the workplace.

And this one was fun.

Because AI can do some pretty incredible things.

It can summarize.

Analyze.

Write.

Brainstorm.

Organize.

Help us work faster.

But one thing kept coming up:

Don’t blindly trust it.

AI can give you an answer.

That doesn’t automatically mean it’s the right answer.

We still need experience.

Judgment.

Curiosity.

And somebody willing to say:

“Wait...does this actually make sense?”

AI can be an amazing assistant.

But it doesn’t replace knowing what you’re doing.

Episode 11: Automation

And then we talked about automation.

Another one of my favorite topics.

Because I love automation.

Give me a repetitive task and my brain immediately goes:

“Can we automate this?”

😂

But here’s the lesson:

Just because you can automate something doesn’t mean you should.

Before you build the workflow...

Ask why.

Understand the process.

Simplify it.

Then automate what actually makes sense.

Because automating a bad process doesn’t make it better.

It just helps you do the wrong thing faster.

And That Brings Us Here

So...

Documentation.

Meetings.

File names.

Process improvement.

Data.

Dashboards.

AI.

Automation.

What do all of these things have in common?

They’re all tools.

They’re all pieces of the puzzle.

But they’re not the reason Operations exists.

People are.

The Invisible Work

Good Operations is often invisible.

When the report goes out on time...

Nobody notices.

When the dashboard is accurate...

Nobody notices.

When the automation works...

Nobody notices.

When the file is easy to find...

Nobody notices.

When the process makes sense...

Nobody notices.

And honestly?

That’s okay.

Because the goal isn’t to make Operations look impressive.

The goal is to make work easier.

Until Something Breaks

Of course...

There’s another side to that.

The second something breaks...

Everyone remembers Operations.

😂

“Where’s the report?”

“Why didn’t the automation run?”

“Who changed the spreadsheet?”

“Why isn’t the dashboard updating?”

“Does anyone know how this works?”

And somehow...

Everyone knows exactly who to call.

Funny how that works.

The Real Superpower

After everything we’ve talked about this season, I don’t think the real superpower of Operations is knowing every software platform.

It’s not Excel.

It’s not Power BI.

It’s not Monday.com.

It’s not AI.

It’s not automation.

Those are tools.

The real superpower is curiosity.

It’s asking:

Why?

Why are we doing it this way?

Why does this step exist?

Why are we collecting this information?

Why does this report look like this?

Why are we having this meeting?

Why are we manually doing something a computer could handle?

And sometimes...

Why are we doing this at all?

That one question can change everything.

The People Behind the Workflow

And that’s really what I want this finale to be about.

The people.

The Operations people.

The project coordinators.

The analysts.

The administrators.

The process people.

The people who keep things organized.

The people who notice the little things.

The people who fix problems before anyone else knows there was a problem.

The people who hear:

“We’ve always done it this way.”

And think:

“But why?”

😂

Those people matter.

To My Fellow Operations People

If you work in Operations...

I want you to know something.

Your work matters.

Even when nobody sees it.

Even when nobody thanks you for updating the documentation.

Or fixing the data.

Or cleaning up the spreadsheet.

Or simplifying the workflow.

Or preventing a problem before it happens.

You’re making someone else’s job easier.

And that’s a pretty big deal.

What This Podcast Was Really About

When I started Behind the Workflow, I wanted to talk about Operations.

But after twelve episodes...

I think I understand what I really wanted to do.

I wanted to give Operations a voice.

Because so much of the business world happens behind the scenes.

Operations connects departments.

Connects people.

Connects information.

Connects systems.

And when it works well...

Everything feels a little easier.

That’s not accidental.

Someone is making that happen.

One Last Lesson

If there’s one thing I hope you take away from Season One...

It’s this:

Don’t make work harder just because you can.

Don’t create another step because the system allows it.

Don’t build another dashboard because someone asked for one.

Don’t automate something just because you can.

Don’t create another meeting because it’s Tuesday.

And don’t keep doing something just because...

“That’s how we’ve always done it.”

Ask questions.

Understand the problem.

Simplify the process.

Use technology where it actually helps.

And most importantly...

Don’t forget the person doing the work.

Before We Wrap Up...

I want to thank everyone who listened to this first season.

Everyone who shared an episode.

Read the newsletter.

Subscribed.

Commented.

Sent me a message.

Or just laughed along with me.

Seriously...

Thank you.

You helped turn an idea into something real.

And I’m incredibly grateful for that.

Until Next Season...

So as we wrap up Season One...

Remember this:

Behind every spreadsheet...

There’s a person.

Behind every dashboard...

There’s a person.

Behind every automation...

There’s a person.

Behind every process...

There’s a person.

And behind every successful business...

There are people quietly making things happen.

If you’re one of those people...

Thank you.

You deserve more credit than you probably get.

And if you’ve listened to this entire season...

Thank you for coming Behind the Workflow with me.

Keep asking questions.

Keep improving processes.

Keep making work easier.

Keep learning.

And never underestimate the power of good Operations.

Because sometimes...

The most important work is the work nobody sees.

I’m Melissa.

And this has been Behind the Workflow.

I’ll see you next season.

I really do.

Give me a repetitive task and my brain immediately starts thinking:

“Can we automate this?”

😂

But over the years, I’ve learned something important.

Just because you can automate something doesn’t mean you should.

And before you build the fancy workflow, connect twelve systems, create seventeen conditions, and start celebrating your automation masterpiece...

There is one question you should ask first.

Why?

Why Are We Doing This?

This sounds like an obvious question.

But you’d be surprised how often we automate a process without questioning the process itself.

Someone says:

“We need to automate this.”

Okay.

Why?

“Because we do it every week.”

Why?

“Because that’s how we’ve always done it.”

Ah.

There’s the problem.

😂

Before we automate a process, we should understand what the process is actually accomplishing.

Maybe the process is necessary.

Maybe it isn’t.

Maybe there is a better way to do it.

Maybe three of the five steps don’t need to exist anymore.

And sometimes...

the best automation is deleting the process entirely.

Automation Doesn’t Fix Bad Processes

Here’s one of my favorite rules:

Don’t automate chaos.

If your process is confusing when a human does it...

it’s probably going to be confusing when a computer does it.

Automation can make a good process faster.

It can make repetitive work easier.

It can reduce manual errors.

It can help information move from one system to another.

But automation doesn’t magically make a bad process good.

It can actually make the problem bigger.

If you have a bad process happening once a week...

that’s annoying.

If you automate that bad process and it happens 500 times without anyone noticing...

now you’ve created automated chaos.

Congratulations.

🎉

Five Questions Before You Automate

Before building your next automation, ask yourself:

1. Why are we doing this?

What problem are we actually trying to solve?

Don’t start with the software.

Start with the problem.

2. Does this step add value?

If the answer is no...

Why does it exist?

3. Can we simplify the process first?

Maybe you don’t need automation.

Maybe you just need fewer steps.

4. What happens when something goes wrong?

Every automation eventually encounters something unexpected.

A missing field.

A changed email address.

A disconnected integration.

A duplicate record.

A person doing something differently than expected.

You need a plan for that.

5. Who owns it?

This one is incredibly important.

Automation doesn’t mean nobody is responsible.

Someone still needs to know:

What the automation does

Why it exists

What happens when it fails

How to update it

When it should be retired

Because eventually...

the person who built it may not be the person maintaining it.

Don’t Automate Just Because You Can

Technology makes it incredibly tempting to automate everything.

And I understand the temptation.

There’s something satisfying about watching a task happen automatically.

You click a button...

And suddenly...

✨ MAGIC. ✨

The task gets created.

The email gets sent.

The spreadsheet updates.

The notification appears.

Beautiful.

But here’s the thing.

Automation should solve a problem—not create a new hobby.

If you’ve spent six hours building an automation that saves someone three minutes a month...

You might want to revisit the math.

😂

Sometimes the Answer Is “No”

This may be the hardest lesson.

Sometimes you investigate a process...

Ask the questions...

Map it out...

And realize:

We don’t need to automate this.

Maybe the process needs to be simplified.

Maybe the task should happen less often.

Maybe someone just needs better documentation.

Maybe the system already has a feature you’re not using.

Or maybe...

the task takes two minutes and happens twice a month.

In that case?

Just do the two-minute task.

It’s okay.

Not everything needs an automation.

The Goal Isn’t More Automation

The goal is better work.

That’s the difference.

We’re not trying to collect automations like they’re Pokémon.

Gotta automate ‘em all!

😂

We’re trying to remove unnecessary work.

Reduce errors.

Save time.

Make information easier to access.

Help people do their jobs.

And create processes that people can actually trust.

Sometimes automation is the answer.

Sometimes it’s simplification.

Sometimes it’s documentation.

Sometimes it’s training.

And sometimes...

the answer is:

“We don’t need to do this anymore.”

That’s a pretty powerful automation.

Because you didn’t automate the work.

You eliminated it.

The Bottom Line

So before you open your automation platform...

Before you start building triggers...

Before you add conditions...

Before you connect every app you own...

Stop.

Ask:

Why?

Understand the problem.

Understand the process.

Simplify what you can.

Then automate what actually makes sense.

Because the best automation isn’t necessarily the most complicated one.

It’s the one that makes work better.

And sometimes...

the smartest workflow is the one you don’t have to build at all.

Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Read more

Hello, I’m Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Big dashboards.

Complicated workflows…oohhhhh!

Twenty-seven integrations…Mamma Mia!

Notifications flying everywhere.

Buttons.

Triggers.

Connectors.

A flow diagram that looks like someone accidentally dropped spaghetti on a whiteboard.

And when everything is connected, we stand back and say:

“WOW! “

Look at us.

We’re automating things.

We’re saving time.

We’re basically running the future.

Except…

I have learned something working in operations.

The best automation is usually the one nobody notices.

And honestly?

That’s the point people.

The Magic Nobody Sees

Think about what happens when a good automation is working exactly the way it should.

Someone fills out a form.

A task gets created.

The right person gets notified.

Information moves to the right place.

A report updates.

And then…

Nothing.

Nobody sends an email saying:

“OMG! THE AUTOMATION WORKED!”

Nobody throws confetti.

Nobody calls an emergency meeting.

Nobody put it on a PowerPoint slide titled:

“Amazing Things Our Workflow Did Today.“

The work just happens, and people move on with their day.

Now that’s success!

The Quiet Wins

During my career in operations, I learned to appreciate those quiet wins.

The things that save five minutes here...

Ten minutes there...

An hour every week...

Two hours every Friday...

Those minutes add up.

Maybe someone no longer has to copy information from one spreadsheet into another.

Maybe a task automatically gets assigned to the right person.

Maybe a reminder goes out before something gets forgotten.

Maybe a report pulls information together instead of someone spending an afternoon manually compiling it.

None of these things sound particularly exciting.

But they can make someone’s workday significantly easier.

And that’s what matters.

Let’s Be Honest About Copy and Paste

There are few things more painful in operations than doing the same manual task over and over again.

Copy.

Paste.

Check.

Copy.

Paste.

Check.

Save.

Open another spreadsheet.

Copy.

Paste.

Check.

Send an email.

Update another system.

Go back to the first spreadsheet because you forgot something.

At some point, you have to stop and ask:

“Why are we still doing this?”

That’s one of my favorite operations questions.

Not:

“Who can do this?”

But:

“Why does this need to be done manually in the first place?”

That’s where automation can be incredibly useful.

Automation Should Give People Time Back

I don’t think the goal of automation should be:

“How much can we automate?”

That’s how you end up with a workflow that requires a flowchart, three passwords, four integrations, and someone named Steve who “knows how it works.”

The better question is:

“What unnecessary work can we remove?”

That’s a very different way of thinking.

Maybe we don’t need someone manually creating that task.

Maybe we don’t need someone checking the same spreadsheet every morning.

Maybe we don’t need someone sending the same reminder every Friday.

Maybe we don’t need someone spending two hours formatting information that could have been structured correctly from the beginning.

Those are opportunities.

The Flashy Automation Trap

Sometimes we get so excited about what technology can do that we forget to ask whether it should do it.

I’ve seen people get excited about connecting everything to everything.

Monday.com talks to Power Automate.

Power Automate talks to Outlook.

Outlook talks to Teams.

Teams talks to another system.

Another system updates a spreadsheet.

The spreadsheet triggers something else.

And suddenly...

Your workflow has more relationships than some people have in their entire social life.

Just because we can connect everything doesn’t mean everything needs to be connected.

Complexity isn’t the same thing as improvement.

The Best Automation Doesn’t Need a Standing Ovation

Here’s how I think about it.

If an automation works so well that people stop thinking about it...

That’s a win.

If someone submits a form and the next step happens automatically...

Great.

If a task gets assigned without someone manually sending an email...

Great.

If a reminder appears at exactly the right time...

Great.

If a report updates without someone spending their Friday afternoon pulling information together...

Beautiful.

Nobody has to know how it happened.

They just know the work got done.

That’s What I Like About Operations

This is one of the reasons I enjoy operations.

A lot of the best work happens behind the scenes.

You might spend hours fixing a process...

Cleaning up data...

Building an automation...

Documenting the workflow...

Testing different scenarios...

Checking what happens when something goes wrong...

And when you finally get everything working?

People may never know you did anything.

And honestly?

That’s okay.

Because suddenly...

The process works.

People aren’t chasing information.

Tasks aren’t falling through the cracks.

Reports are easier to produce.

The team has fewer repetitive tasks.

And everyone gets a little bit of their time back.

That’s the reward.

Don’t Measure Automation by How Complicated It Is

This is where I think businesses sometimes get automation wrong.

They look at a complicated workflow and think:

“That must be a really good automation.”

Not necessarily.

A simple automation that saves someone five hours a week may be far more valuable than a complicated automation with seventeen integrations that nobody understands.

So instead of asking:

“How impressive is our automation?”

Ask:

“What problem did it solve?”

Did it save time?

Did it reduce errors?

Did it eliminate repetitive work?

Did it make the process easier?

Did it prevent something from falling through the cracks?

Did it improve the employee experience?

Those are much better questions.

And Please... Test It

Of course, there’s one tiny detail we can’t forget.

Test the automation.

Because an automation nobody notices is wonderful.

An automation nobody notices until it creates 642 tasks...

Not so wonderful.

Or sends an email to 400 people.

Or updates the wrong records.

Or creates a loop that continues running while everyone is at lunch.

That’s a different kind of quiet.

The kind where everyone suddenly stops talking.

Good automation should be quiet because it works.

Not quiet because everyone is afraid to touch it.

The Real Goal

At the end of the day, I don’t want automation just for the sake of automation.

I want automation that makes work better.

I want fewer repetitive clicks.

Fewer copy-and-paste tasks.

Fewer unnecessary emails.

Fewer manual updates.

Fewer opportunities for human error.

And more time for people to actually think, solve problems, communicate, and make decisions.

Because those are the things people are good at.

Let the technology handle the repetitive stuff when it makes sense.

Let people handle the things that require judgment.

That’s the balance.

Sometimes Boring Is Beautiful

I’ve worked with enough systems to know that “boring” isn’t always a bad thing.

Sometimes boring means reliable.

Boring means predictable.

Boring means nobody has to worry about it.

Boring means:

“It just works.”

And I’ll take that over a flashy automation that requires a user manual any day.

Give me the automation that quietly creates the task.

Quietly sends the reminder.

Quietly moves the information.

Quietly updates the report.

Then goes back to minding its own business.

That’s my kind of coworker.

My Saturday Reflection

The older I get in operations, the more I appreciate systems that don’t demand attention.

Good workflows shouldn’t constantly remind you that they’re there.

They should simply help the work happen.

That’s what automation should do.

Not make people feel replaced.

Not make the process more complicated.

Not create technology for the sake of technology.

It should make someone’s job easier.

And sometimes...

The biggest sign that you’ve built something useful...

Is that nobody notices it at all.

They just go about their day.

The task gets done.

The report gets updated.

The reminder gets sent.

The information gets where it needs to go.

And everyone gets a little more time back.

That’s not flashy.

But in operations?

That’s pretty impressive.

💬 Saturday Question

What’s one automation you’ve used that quietly made your job easier?

Maybe it saved you an hour every week.

Maybe it eliminated a repetitive task.

Maybe it stopped something from falling through the cracks.

Or maybe you built something so useful...

Nobody even realizes it’s working behind the scenes.

Tell me about it!

Because sometimes...

The best automation is the one nobody notices.

💡 Saturday Quote

“The goal isn’t to automate everything. The goal is to eliminate the work that never needed a human in the first place.”

— Melissa Stringfellow

#BehindTheWorkflow #SaturdayReflection #Automation #BusinessOperations #WorkflowAutomation #ProcessImprovement #MondayCom #PowerAutomate #PowerBI #Operations #OperationalExcellence #Productivity #BusinessProcess #AIatWork #AutomationStrategy

Hello, I’m Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Read more

Hello, I’m Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Let’s talk about one of my favorite operations equations.

And no...

You don’t need a calculator for this one.

You don’t even need Excel.

Although, knowing us operations people, someone is probably already opening a spreadsheet.

😂

Here’s the equation:

Bad Process + Automation = Faster Chaos

Simple.

Beautiful.

Terrifyingly accurate.

And if you’ve ever built an automation that worked exactly the way you told it to...

Only to realize later that what you told it to do was completely wrong...

You already understand where I’m going with this.

🚦 Automation Is Not a Magic Wand

Automation gets a lot of attention these days.

And for good reason.

It can save time.

It can reduce repetitive work.

It can move information between systems.

It can create tasks.

Send notifications.

Update records.

Generate reports.

And eliminate some of those wonderfully exciting tasks that make you stare at your computer and think:

“Surely there is a better way to spend the next two hours.”

There usually is.

But here’s the problem.

People sometimes think automation will fix a broken process.

It won’t.

Automation doesn’t walk into your process and say:

“Excuse me, but this makes absolutely no sense. Let’s redesign this.”

No.

Automation says:

“Absolutely! You want me to do this confusing thing 400 times? I’M ON IT!”

😂

And that’s where the trouble begins.

🧱 Let’s Start with a Bad Process

Imagine your company has a simple process.

A new client comes in.

Someone enters the client information.

Then an employee checks it.

Then someone else reviews it.

Then a manager approves it.

Then another department checks it.

Then someone emails Finance.

Then Finance sends it back.

Then someone enters the information into another spreadsheet.

Then someone sends an email saying the information was entered into the spreadsheet.

Then someone replies:

“Thanks.”

Congratulations.

You have successfully created a process that requires seven people and twelve emails to accomplish something that probably should have taken ten minutes.

😂

But now someone says:

“We should automate this!”

Fantastic.

So you automate all seven steps.

Now the system sends the emails automatically.

Creates the tasks automatically.

Routes the approvals automatically.

Updates the spreadsheet automatically.

And sends the confirmation email automatically.

Congratulations.

You didn’t improve the process.

You just made the unnecessary process happen faster.

🏎️ Faster Isn’t Always Better

This is something I think businesses sometimes forget.

Speed is not the same thing as efficiency.

If you’re driving in the wrong direction...

Going faster doesn’t help.

It just gets you lost sooner.

😂

The same thing happens with automation.

If the process is bad...

Automation can make the bad process incredibly efficient.

And that’s almost worse.

Because now everyone thinks:

“Look! The automation is working!”

Meanwhile...

The automation is happily producing 300 tasks nobody needs.

📋 Here’s Another Example

Let’s say employees enter customer names into a system.

One person enters:

ABC Company

Another enters:

A.B.C. Company

Someone else enters:

ABC Co.

And another person enters:

ABC COMPANY, LLC

To a human...

We can probably figure out that these are the same organization.

To a system?

Not necessarily.

Now let’s automate something.

Every time a customer is entered, automatically create a task.

The automation doesn’t stop and say:

“Hey...I’m pretty sure these are all the same customer.”

It simply does what it’s been told.

ABC Company?

Create a task.

A.B.C. Company?

Create a task.

ABC Co.?

Create a task.

ABC COMPANY, LLC?

Create another task.

Now your team has four tasks for one customer.

And someone eventually asks:

“Why are there four of these?”

The automation quietly sits in the corner.

“I was just following instructions.”

😂

And technically...

It was.

👀 Then There’s the Ownership Problem

Here’s another one.

Nobody knows who owns a task.

So someone decides:

“Let’s automate it.”

The automation creates the task.

Great.

Except...

Who is supposed to complete it?

Nobody knows.

So now you have a beautifully automated task sitting on a board...

Waiting for someone to notice it.

Days go by.

Someone finally asks:

“Who is supposed to do this?”

Someone else says:

“I thought you were doing it.”

And the automation?

Still running.

Still creating tasks.

Still completely confident that it has done its job.

😂

This is why automation cannot replace ownership.

Automation can move information.

It can create tasks.

It can send reminders.

But it cannot take responsibility for the outcome.

Someone still needs to own the process.

🔄 The Process Comes First

This is why I believe there should be a very specific order when you’re improving a workflow.

First: Understand the process.

What actually happens?

Not what the procedure says happens.

What really happens.

Because those can be two very different things.

😂

Second: Simplify the process.

Do we really need all twelve steps?

Do we need three approvals?

Does someone really need to copy this information into another spreadsheet?

Can we eliminate something?

Third: Standardize the process.

Everyone needs to follow the same basic process.

Same definitions.

Same required information.

Same naming conventions.

Same expectations.

Fourth: Automate the process.

Now we’re getting somewhere.

Once the process makes sense...

Automation can help it move faster.

Finally: Monitor the process.

This is the part people forget.

Just because you built an automation doesn’t mean you can walk away forever.

🔧 Automation Needs Maintenance Too

Businesses change.

People change.

Software changes.

Departments change.

Processes change.

And sometimes...

Someone changes something without telling anybody.

😂

That last one might be the most dangerous.

You build an automation in January.

It works beautifully.

Everyone is happy.

By June...

The team has changed.

The software has changed.

The board has changed.

The process has changed.

But nobody updated the automation.

So the automation is still doing exactly what it was told to do six months ago.

It just doesn’t match reality anymore.

And that’s when someone finally discovers it.

Usually at the worst possible time.

Usually during a meeting.

Usually, five minutes before someone needs the report.

😂

🤖 Automation Doesn’t Have Common Sense

This might be one of the most important things to remember.

Automation doesn’t have common sense.

It doesn’t understand what you meant.

It understands what you built.

If you tell it:

“When this happens, do this.”

That’s exactly what it will do.

Even if the situation has changed.

Even if the data is wrong.

Even if someone entered something incorrectly.

Even if the task doesn’t make sense anymore.

Automation isn’t going to stop and say:

“You know what? I’m not feeling great about this workflow.”

😂

It doesn’t have feelings.

It has triggers.

🧹 Clean Up Before You Automate

This is especially important when you’re dealing with data.

Before you automate something, look at what you’re feeding into the process.

Are there duplicates?

Missing information?

Inconsistent names?

Incorrect dates?

Old records?

Different departments using different terminology?

If the answer is yes...

Stop.

Fix that first.

Because automation doesn’t magically clean up bad information.

It can actually spread it.

And spread it quickly.

It’s like putting dirty dishes on a conveyor belt and congratulating yourself because the conveyor belt is really fast.

Eventually...

You still have dirty dishes.

😂

💡 My Rule: Never Automate Confusion

This is probably one of the biggest lessons I’ve learned throughout my years in business operations.

Never automate confusion.

If nobody understands the process...

Don’t automate it yet.

If nobody knows who owns the work...

Don’t automate it yet.

If the data is inconsistent...

Don’t automate it yet.

If you’re still changing the process every other week...

Don’t automate it yet.

Take a step back.

Figure out what you’re actually trying to accomplish.

Then build the automation around the improved process.

🧠 Ask the Five Questions

Before turning on an automation, I like to ask:

1. What starts the process?

A form?

A new client?

A status change?

An email?

A date?

2. What happens next?

Write it down.

Step by step.

Don’t assume everyone understands it.

3. Who owns it?

Someone needs to be responsible for the outcome.

4. What happens when something goes wrong?

Because something eventually will.

What happens if information is missing?

What happens if someone changes something manually?

What happens if the automation fails?

5. Can someone else understand it?

This one is huge.

If you disappear tomorrow...

Can someone else figure out what you built?

If the answer is no...

You may have created something very impressive.

But you also created a future mystery.

And nobody wants to inherit a mystery.

😂 The Automation Hall of Fame

I’ve always thought there should be an awards ceremony for automation disasters.

Categories could include:

🏆 Most Emails Sent to the Wrong People

🏆 Most Duplicate Tasks Created

🏆 Longest-Running Automation Nobody Knew Existed

🏆 Most Complicated Workflow for the Simplest Task

🏆 Best Automation Built to Solve a Problem That Didn’t Actually Exist

And my personal favorite:

🏆 Automation That Worked Perfectly Until Someone Changed One Thing

You know the one.

Everything was fine.

Then someone renamed a status.

And suddenly...

THE ENTIRE SYSTEM HAS ENTERED THE VOID.

😂

The Goal Isn’t More Automation

Here’s what I really want people to remember.

The goal isn’t to automate everything.

The goal is to make work better.

Sometimes that means automation.

Sometimes it means deleting a step.

Sometimes it means changing a form.

Sometimes it means creating an SOP.

Sometimes it means standardizing data.

Sometimes it means having a conversation with the people actually doing the work.

And sometimes...

The answer is:

“We don’t need this step anymore.”

That’s a perfectly good operations solution.

You don’t get extra points for having seventeen automations.

😂

🚀 The Best Automation Is Usually Boring

The best automations aren’t necessarily flashy.

They’re the ones that quietly do their jobs.

A form comes in.

The information goes where it needs to go.

The right person gets notified.

A task is created.

A report updates.

Nobody has to think about it.

Nobody has to babysit it.

Nobody has to ask:

“Is this thing working?”

That’s success.

Quiet.

Reliable.

Predictable.

A little boring.

And honestly...

I love boring when it comes to operations.

😂

🎯 The Real Operations Lesson

Automation should make a good process better.

It shouldn’t be used to hide a bad process.

Before you automate...

Understand.

Simplify.

Standardize.

Then automate.

And once you’ve automated it...

Check it.

Review it.

Test it.

Make sure it still makes sense.

Because the worst thing you can discover six months from now isn’t that your automation stopped working.

It’s that...

It worked perfectly the entire time.

It was just doing the wrong thing.

😂

And that is a very special kind of operations headache.

💬 Thursday Question

What’s the biggest automation mistake you’ve ever seen?

Did it:

📧 Send an email to the wrong person?

📋 Create hundreds of unnecessary tasks?

🔄 Get stuck in a loop?

📊 Move bad data from one system to another?

👻 Keep running after the process had already changed?

Or did someone say the most dangerous sentence in automation history:

“Don’t worry. We don’t need to test it.”

😂

Tell me your automation horror stories.

Because if there’s one thing I’ve learned...

Every operation professional has at least one.

💬 Quote of the Day

Because faster chaos...

Is still chaos.

It’s just wearing a productivity badge.

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Hello, automation addicts...

Workflow warriors...

Monday.com fans...

Power Automate explorers...

Zapier enthusiasts...

And everyone who’s ever clicked “Turn On Automation” with way more confidence than they actually had...

Welcome back to Behind the Workflow...

The podcast where we pull back the curtain on business operations...

Laugh at the wonderfully weird things that happen behind the scenes...

And celebrate the people who somehow keep everything running.

I’m Melissa...

Business Operations professional...

Workflow detective...

Recovering spreadsheet therapist...

And someone who’s learned that automation is a lot like owning a Roomba.

When everything goes well...

It’s amazing.

When it doesn’t...

You come home to complete chaos...

And somehow the dog is involved.

So grab your coffee...

Double-check your workflows...

And before you click Save...

Let’s talk about automation.

🎉 Corporate Confession #11

Let’s start with a confession.

Have you ever built an automation...

Watched it work perfectly...

Felt like an absolute genius...

Then five minutes later...

Realized...

It had emailed the wrong people?

Maybe not 400 people...

Hypothetically.

Of course.

Suddenly you’re trying to remember...

Can emails be recalled?

Can time be reversed?

Can I quietly unplug the internet?

Because once automation starts...

It has absolutely no idea it made a mistake.

It just keeps going.

Like,

“Oh...

You wanted me to email everyone?

Great!

I’m incredibly efficient.”

🎬 Previously on Behind the Workflow...

Last week...

We talked about AI...

The coworker who always has an answer...

Even when it’s confidently wrong.

This week...

We’re talking about AI’s best friend...

Automation.

Because once AI gives you the answer...

Automation makes sure that answer gets everywhere...

Very quickly.

Sometimes...

A little too quickly.

The Dream

When people hear the word “automation” ...

Their eyes light up.

“We’ll save time!”

“We’ll eliminate repetitive work!”

“We’ll never have to do this manually again!”

And honestly...

Sometimes that’s exactly what happens.

Throughout my career in business operations...

I loved finding repetitive tasks and asking one simple question.

“Why are we still doing this manually?”

If I found myself clicking the same buttons...

Every day...

Every week...

Every month...

I knew there was probably a better way.

Automation gave me that better way.

My Experience in Operations

One of my favorite parts of working in operations was improving processes.

Not because I wanted to replace people.

Because I wanted people spending time on work that actually mattered.

If someone spends two hours every Friday copying information from one spreadsheet into another...

That’s not a good use of their talent.

That’s a process asking to be improved.

I worked with tools like Monday.com...

Power Query...

Power BI...

Forms...

Dashboards...

And workflow automations that helped information move where it needed to go without someone babysitting it.

When automation worked...

It was beautiful.

Reports updated faster.

Projects moved forward.

People spent less time doing repetitive work...

And more time solving problems.

That’s what good automation looks like.

Then...

Reality Shows Up

Because here’s the part nobody tells you.

Automation is incredibly obedient.

It doesn’t stop and think.

It doesn’t ask,

“Melissa...

Are you sure?”

It simply says,

“Absolutely.”

“And I’ll do it immediately.”

Meet Automation

I like to imagine Automation as the world’s most enthusiastic intern.

You say,

“Whenever someone fills out this form...”

Automation interrupts.

“I GOT IT!”

“I’ll create a task.”

“I’ll notify the team.”

“I’ll update the spreadsheet.”

“I’ll send an email.”

“I’ll create a calendar invite.”

“I’ll alert Finance.”

“I’ll message Marketing.”

“I’ll post it to Teams.”

“I’ll water your plants.”

“Wait...”

“No...”

“That last one isn’t supported yet.”

Automation never questions your instructions.

Even if your instructions are terrible.

The Domino Effect

Here’s something I learned.

Bad processes don’t become good because you automate them.

They just become...

Faster bad processes.

Imagine putting your GPS on the wrong destination.

Then driving faster.

You’re still lost.

You just got there quicker.

Automation works exactly the same way.

If the process is broken...

Automation simply helps it fail at record speed.

Monday.com Enters the Chat

Monday.com walks into the room.

Looking confident.

Colorful.

Very organized.

It says,

“I can automate almost anything.”

I smile.

“I know.”

Monday.com says,

“What would you like me to do?”

I pause.

Because I’ve learned something over the years.

Just because a platform can automate something...

Doesn’t mean it should.

Sometimes the best solution isn’t another automation.

It’s fixing the process first.

Power Automate Joins In

Power Automate walks into the meeting carrying twenty-seven connectors.

Zapier follows behind holding another thousand.

They both smile.

“We can connect everything.”

“Everything?”

“Everything.”

Power Query quietly whispers,

“...Should we?”

My Favorite Automation Rule

Here’s the rule I always tried to follow.

Never automate confusion.

If people don’t understand the process...

Automating it won’t make it clearer.

It just makes confusion happen faster.

Before I automated anything...

I wanted answers to a few simple questions.

Who owns the process?

What starts it?

What ends it?

What happens if something goes wrong?

Can someone else understand it?

If we couldn’t answer those questions...

We weren’t ready to automate.

The Silent Hero

The best automations are actually kind of boring.

Nobody notices them.

Nobody applauds because an email was sent automatically.

Nobody cheers because a task was created without anyone clicking a button.

People simply assume...

That’s how it’s always worked.

Honestly...

That’s my favorite kind of success.

Quiet.

Reliable.

Invisible.

Automation’s Biggest Weakness

Automation has one fatal flaw.

It believes everything you tell it.

If your spreadsheet says there are three different customers...

Automation believes there are three customers.

If your workflow tells it to send an email...

It sends the email.

It doesn’t question you.

It doesn’t hesitate.

It doesn’t whisper,

“Maybe we should test this first.”

It simply salutes...

And marches forward.

Sometimes...

Straight into disaster.

Final Thoughts

One thing I’ve learned throughout my years in business operations is this:

Automation isn’t about replacing people.

It’s about replacing repetitive work.

The goal isn’t fewer people.

The goal is fewer repetitive clicks.

Fewer copy-and-paste afternoons.

Fewer tasks that make you wonder,

“Didn’t I just do this yesterday?”

When automation is built on a good process...

It’s incredible.

When it’s built on a bad process...

Well...

Let’s just say...

Things get interesting.

Before We Wrap Up...

I want to hear from you.

What’s the funniest automation you’ve ever seen?

Maybe an email went to the wrong person.

Maybe someone accidentally created five hundred tasks.

Maybe a workflow got stuck in an infinite loop.

Or maybe...

You’ve built an automation that saved your team hours every week.

Share your story.

Because every operations professional has at least one automation story they’ll never forget.

Thanks so much for joining me for another episode of Behind the Workflow.

If today’s episode made you laugh...

Or reminded you to go check one of your automations...

Be sure to subscribe...

Leave a review...

And share it with that coworker who still says,

“We don’t need to test it.”

Until next time...

Remember...

Automation is an incredible tool.

But before you automate the process...

Make sure the process actually deserves to be automated.

Because a bad workflow with automation...

Is still a bad workflow.

It just happens a whole lot faster.

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Read more

Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Tired of sending emails?

Automate it.

Tired of creating tasks?

Automate it.

Tired of updating spreadsheets?

Automate it.

Tired of explaining the same process to people for the 47th time?

Definitely automate it.

Except...

Maybe don’t.

At least, not yet.

Because automation isn’t magic.

And unfortunately, it doesn’t come with a tiny wizard who walks into your organization, looks at your processes, and says:

” Don’t worry. I found all the problems.”

Wouldn’t that be nice?

Instead, automation does something much less glamorous.

It takes the process you already have...

and follows it.

Exactly.

Repeatedly.

Quickly.

Without asking questions.

And that’s where things can get interesting.

Automation Doesn’t Fix Bad Processes

If your process is confusing before automation, it will probably be confusing after automation.

The difference?

Now it can be confusing at 2:00 AM without anyone touching it.

You may have just created a very efficient disaster.

Automation is incredibly good at doing what you tell it to do.

That is both its greatest strength...

and one of its biggest weaknesses.

If you automate a process that contains unnecessary steps, those unnecessary steps are still there.

If you automate a process that has the wrong trigger, the wrong trigger is still there.

If you automate a process that nobody actually understands, congratulations.

You now have an automated process that nobody understands.

And everyone will be very impressed by the little notification that says:

” Automation successfully completed.”

Meanwhile, nobody knows what just happened.

The Question We Should Be Asking

One of the most important questions in operations isn’t:

” Can we automate this?”

The answer to that question is increasingly:

” Probably.”

The better question is:

” Should we automate this?”

Those are two very different questions.

Before I automate something, I want to understand what I’m actually automating.

I want to know:

• Do we actually understand the process?

• Does everyone follow the same process?

• Who owns the process?

• What starts the process?

• What information does it need?

• What happens when something goes wrong?

• What happens when someone does something differently?

• Can someone explain the workflow without opening seventeen tabs?

• And most importantly...

Does the process actually make sense?

Because if the answer to that last question is no, we have bigger problems than automation.

Document It Before You Automate It

One of the best things you can do before building an automation is something incredibly boring.

Document the process.

I know.

Exciting.

Try to contain yourself.

But documentation forces you to slow down and actually look at what is happening.

Write down the steps.

Who does what?

When do they do it?

What information do they need?

Where does that information go?

What happens next?

What happens if something is missing?

What happens if someone makes a mistake?

What happens if the person who normally handles it is out?

Suddenly, you may discover something interesting.

The process you thought was simple...

are actually twelve steps, three exceptions, two workarounds, a spreadsheet named “FINAL_FINAL_v7,” and one person who somehow knows exactly what to do because they’ve been doing it for eight years.

That person is usually the human version of the undocumented API.

And when they go on vacation?

Everybody discovers just how important documentation really is.

Automation Should Follow Good Processes

Automation should not be the first step.

It should be the next step.

First:

Understand the process.

Then:

Simplify the process.

Then:

Document the process.

Then:

Test the process.

And finally:

Automate the process.

That order matters.

Because the goal isn’t to automate everything.

The goal is to make the work better.

Sometimes automation is absolutely the right answer.

Sometimes a simple checklist is better.

Sometimes a form is better.

Sometimes a dashboard is better.

Sometimes the process just needs to be redesigned.

And sometimes...

the process needs to be retired completely.

Not everything deserves an automation.

Some processes deserve a proper goodbye.

The Shopping Cart Test

Here’s how I think about it:

Automating a bad process is like putting a jet engine on a shopping cart.

Yes.

It will move.

Very quickly.

But I’m not sure anyone should be riding in it.

And once you’ve built it, someone is going to have to maintain that jet-engine shopping cart.

Because automations need owners.

They need testing.

They need documentation.

They need monitoring.

They need updates when systems change.

And they need someone who knows what happens when the automation inevitably decides to have a bad day.

Because automation doesn’t eliminate responsibility.

It changes where the responsibility lives.

The Real Goal

The goal of automation shouldn’t be:

” How much can we automate?”

It should be:

” How can we make this work better?”

Sometimes the answer is automation.

Sometimes it isn’t.

Good operations isn’t about using the most technology.

It’s about using the right amount of technology to solve the right problem.

That’s the difference between automation for the sake of automation...

and automation that actually helps people.

So before you build that next workflow, ask yourself:

Can we automate it?

Sure.

But first ask:

Should we?

Because just because you can automate something...

doesn’t mean you should.

And sometimes the smartest automation decision you can make...

is deciding not to automate it yet.

Monday Musings Tip

Before building an automation, document the process manually first.

If you can’t explain the workflow clearly, you probably aren’t ready to automate it.

Fix the process first.

Then let the technology do what it does best:

Make a good process faster, more consistent, and easier to manage.

Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

AI is incredibly useful.

But useful and experienced are not the same thing.

And that distinction matters.

Because we are living in a time where AI can produce an answer before some of us have even finished typing the question.

It can give you ideas.

It can give you options.

It can write a draft.

It can summarize 47 pages of information while you are still wondering why anyone thought a 47-page document was necessary in the first place.

It can identify patterns.

It can organize information.

It can give you a starting point.

And honestly?

That’s pretty amazing.

But here’s the part we can’t forget.

Information is not the same thing as judgment.

AI can tell you what *could* work.

Experience helps you determine what **will actually work in your environment.**

Those are two very different things.

AI Can Give You the Answer Faster

Let’s say you ask AI:

“How can I improve this workflow?”

It might give you ten suggestions.

Fantastic.

But then someone who understands the business needs to look at those ten suggestions and start asking questions.

Does this actually make sense?

Is the information accurate?

Does this fit our existing process?

What happens to the people who have to use it?

What are we missing?

What happens if something goes wrong?

Are we solving the actual problem, or are we just making the process more complicated?

And my personal favorite:

Who is going to maintain this six months from now?

Because apparently, we love building things that are absolutely brilliant on Day One and become everyone’s problem by Day 47.

😂

That’s where experience comes in.

Experience Knows What the Spreadsheet Doesn’t

One of the biggest advantages of experience is that you have seen things go wrong.

You have seen the process that looked perfect on paper fall apart the minute an actual human being touched it.

You’ve seen the automation that worked beautifully until someone entered something differently.

You’ve seen the report that technically contained the correct information but was completely useless to the person who needed to make a decision.

You’ve seen the “simple” solution turn into seventeen steps, three spreadsheets, two meetings and a Teams message that starts with:

” Quick question...”

There is a lot of knowledge that doesn’t necessarily live in documentation.

It lives in experience.

It lives in knowing:

” We’ve tried this before.”

Or:

” That sounds good, but here’s what happened last time.”

Or even:

” Wait. Before we automate that, why are we doing it in the first place?”

That last one might save an entire department six months of unnecessary work.

AI Doesn’t Know Your Business Like You Do

This is one of the reasons I don’t see AI as a replacement for experienced operations professionals.

I see it more like an incredibly fast assistant.

An assistant who never gets tired.

An assistant who can brainstorm at 2:00 in the afternoon.

An assistant who doesn’t care if you ask the same question five different ways.

An assistant who can take a giant pile of information and say:

” Here are a few things I noticed.”

That’s incredibly valuable.

But it still needs someone sitting there saying:

” Okay...but does that actually make sense?”

Because AI doesn’t automatically know your company’s history.

It doesn’t know every workaround someone created three years ago.

It doesn’t know why that weird little step exists in the process.

It doesn’t know that the person responsible for Step 6 is going to be on vacation every third Friday.

It doesn’t know that the system everyone wants to replace is connected to another system nobody remembered existed.

And it definitely doesn’t know that Bob in Accounting will somehow manage to break the entire workflow by putting a space in a field that specifically says DO NOT ADD A SPACE.

😂

Experience does.

The Real Power Is the Combination

I don’t think the future of operations is:

AI versus humans.

I think it’s:

AI + human experience.

AI can help us move faster.

Experience helps us move smarter.

AI can give us ten possible solutions.

Experience helps us narrow those down to the two that are actually realistic.

AI can summarize the information.

Experience helps us understand what information matters.

AI can identify a pattern.

Experience helps us determine whether that pattern actually means something.

AI can create the first draft.

Experience knows what needs to be fixed before anyone else sees it.

That’s a pretty powerful combination.

And honestly, I think that’s where AI becomes most valuable.

Not when we blindly hand everything over to it.

But when we use it to eliminate the boring, repetitive, time-consuming work that keeps experienced people from doing the work that actually requires their experience.

Let AI Do More of the “Ugh”

There are plenty of things in operations that do not require years of experience.

Copying information from one system to another?

Ugh.

Cleaning up a repetitive spreadsheet?

Ugh.

Creating the first draft of a document?

Ugh.

Summarizing meeting notes?

Ugh.

Sorting through a pile of information looking for obvious patterns?

Ugh.

Creating a starting point for a process?

Fine. Let AI take that one.

Give me back the time.

I’ll use it for the things that actually require judgment.

Because I don’t want AI to replace the person who understands the process.

I want AI to give that person more time to improve the process.

That’s a very different conversation.

The Experience Still Matters

There is a temptation with new technology to assume that because something is faster, it must also be better.

But faster isn’t always better.

Sometimes faster just means you got to the wrong answer sooner.

That’s why experience matters.

The goal shouldn’t be to remove human judgment from the process.

The goal should be to free human judgment from the unnecessary work surrounding it.

Let AI handle more of the information.

Let experienced people handle the decisions.

Let AI help us explore possibilities.

Let experienced people challenge those possibilities.

Let AI help us get started.

Let humans decide where we should actually go.

Because at the end of the day:

AI can help you get to an answer faster.

Experience helps you decide whether it’s the right answer.

And I think that’s a pretty good partnership.

💭 Sunday Reflection

So here’s my question for you this Sunday:

If AI joined your team tomorrow, what is the first boring task you’d happily hand over to it?

Not the complicated strategic project.

Not the million-dollar decision.

Not the thing that requires seventeen approvals and a steering committee.

I’m talking about the task that makes you stare at your screen and think:

” There has GOT to be a better way to do this.”

Because maybe that’s where we should start.

Not with replacing people.

Not with trying to automate everything.

But with asking a much simpler question:

” What unnecessary work can we finally stop making humans do?”

Now THAT sounds like a pretty good use of AI to me.

Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Because if I have to copy the same information into three spreadsheets again, I may actually lose my mind.

Quote of the Week:

“The best automation doesn’t replace people. It gives people their time back.”

Let’s have an honest conversation about AI.

Not the dramatic version.

Not the “AI is going to take everyone’s jobs!” version.

And definitely not the version where someone tells you AI is going to magically transform your entire business by next Tuesday.

I’m talking about the practical version.

The operations version.

The version that asks a much more useful question:

What can AI actually do to make my work easier?

Because after years of working in business operations, I’ve learned something.

A lot of work isn’t necessarily difficult.

It’s just repetitive.

And repetitive work has a funny way of eating your entire day.

The Work Nobody Brags About

When people hear “business operations,” they might imagine strategy meetings, dashboards, process improvement, workflow design, and big organizational decisions.

And yes...

Those things are part of it.

But there’s another side of operations that doesn’t make it onto the PowerPoint presentation.

The little things.

The things that take five minutes here...

Ten minutes there...

Thirty minutes somewhere else...

And suddenly it’s 4:47 PM and you’re wondering where the entire day went.

Things like:

Updating spreadsheets

Cleaning up data

Formatting reports

Writing meeting summaries

Creating documentation

Updating SOPs

Organizing information

Copying information between systems

Drafting emails

Reformatting documents

Checking lists

Looking for missing information

Creating first drafts

Pulling reports

Comparing information

Finding patterns

Updating project records

None of these tasks are necessarily complicated.

But they add up.

And that’s where I start getting interested in AI.

I’m Not Looking for a Robot to Replace Me

This is where I think the conversation about AI gets a little strange.

People immediately ask:

“Is AI going to take my job?”

That’s not the question I’m asking.

My question is:

“Which parts of my job should I stop doing manually?”

There’s a big difference.

I don’t need AI to replace the person thinking about the process.

I need AI to help eliminate the ridiculous amount of time spent doing things that don’t require much thinking.

Because let’s be honest...

If I spend an hour copying information from one spreadsheet into another spreadsheet...

Then spend another fifteen minutes checking whether I copied it correctly...

Then send an email explaining that I copied the information...

We have officially entered the Corporate Circle of Pointless Activities.

If a task involves copying information from one spreadsheet into another spreadsheet and then sending an email telling someone you copied it...

AI can probably have that one.

I’ll be over here doing something useful.

Documentation Is a Perfect Example

One area where I think AI can be incredibly useful is documentation.

Operations professionals know documentation is important.

We also know nobody wants to write it.

Everyone loves the idea of having SOPs.

Until someone says:

“Okay. Who’s going to document the process?”

Suddenly everyone becomes extremely busy.

I’ve created documentation and SOPs throughout my career, and I’ve seen firsthand how much time it can take to turn scattered information into something another person can actually understand.

AI can help with the first draft.

You can give it notes.

Steps.

Process information.

Meeting transcripts.

Existing documentation.

Then have it organize that information into a logical structure.

Does that mean I blindly publish whatever AI creates?

Absolutely not.

That’s how you end up with an SOP explaining a process that doesn’t actually exist.

AI can help write the documentation.

A human still needs to make sure the documentation is correct.

Meeting Summaries

Here’s another one.

Meetings.

We have all been in meetings where someone spends ten minutes explaining what happened...

Only to spend another ten minutes trying to figure out what everyone agreed to.

Then somebody says:

“I’ll send out the notes.”

And everyone nods.

Two days later...

Nobody has the notes.

AI can be incredibly useful for meeting summaries.

It can help identify:

What was discussed?

What decisions were made?

What are the action items?

Who is responsible?

What happens next?

That’s useful.

But again...

Don’t confuse summarizing with understanding.

AI can organize what happened.

People still need to decide whether the summary is accurate and whether the action items actually make sense.

Data Cleanup

Now we’re getting into territory that operations people understand very well.

Messy data.

Because somehow data has the ability to become messy without anyone admitting they made it messy.

One person enters:

XYZ

Someone else enters:

X.Y.Z.

Someone else enters:

XYZ of Electronics

And Excel is sitting there like:

“I have three customers.”

No.

You have one.

We just apparently gave it three names.

AI can help identify patterns like this.

It can flag inconsistencies.

Identify duplicates.

Suggest standardization.

Find missing information.

Help categorize records.

That’s incredibly valuable.

But again...

AI should suggest.

People should verify.

Because if AI decides two records are duplicates and deletes the wrong one...

Congratulations.

You’ve automated a new problem.

Reporting Is Another Big One

I’ve spent a lot of time working with reports, dashboards, data, and operational information.

And one thing I’ve learned is that reporting isn’t just about producing numbers.

It’s about understanding what those numbers mean.

AI can help with some of the repetitive work around reporting.

It can help organize information.

Summarize trends.

Identify unusual changes.

Create first drafts of explanations.

Help prepare questions.

That can save a tremendous amount of time.

But I’m not handing AI the keys to the dashboard and saying:

“Good luck, buddy.”

Because numbers still need context.

A number can change because the business changed.

It can change because the process changed.

It can change because someone entered the data differently.

Or...

Someone accidentally deleted something they absolutely were not supposed to delete.

I’ve seen enough operational chaos to know better than to assume the number is automatically correct just because a computer produced it.

This Is Where Workflow Thinking Matters

This is probably the biggest reason I’m interested in AI from an operations perspective.

I’ve always looked at work as a series of steps.

Information comes in.

Someone does something with it.

Another person reviews it.

Something gets updated.

A report gets generated.

Someone makes a decision.

Then the process starts again.

That’s a workflow.

And once you start looking at work that way, you naturally start asking:

Where are the bottlenecks?

Where are we repeating ourselves?

Where are we manually moving information?

Where are people doing work that a system could help with?

That’s where automation comes in.

And now...

AI becomes another tool in that toolbox.

Not the entire toolbox.

Just another tool.

AI Doesn’t Fix a Bad Process

This is important.

If your process is a mess...

AI isn’t necessarily going to fix it.

You can automate a bad process.

You can make a bad process faster.

You can even make a bad process look incredibly sophisticated.

But it’s still a bad process.

That’s why I believe operations professionals are going to be extremely important in the AI conversation.

Someone still has to understand the workflow.

Someone still has to ask whether the process makes sense.

Someone still has to identify what information is actually needed.

Someone still has to determine what should happen when something goes wrong.

And someone definitely needs to notice when the AI just confidently invented something.

The Human Part Still Matters

AI can write.

AI can summarize.

AI can organize.

AI can brainstorm.

AI can analyze patterns.

AI can help automate repetitive work.

But there are things I don’t want AI making decisions about without human involvement.

Judgment.

Accountability.

Relationships.

Business context.

Ethics.

Strategy.

Common sense.

And the question:

“Does this actually make sense?”

That’s still our job.

Because AI can give you an answer.

It doesn’t automatically mean it’s the right answer.

What I Actually Want

If I could sit down with an AI coworker and give it a job description, it would probably look something like this:

Your job is to help me eliminate repetitive work.

Help me organize information.

Help me create first drafts.

Help me summarize meetings.

Help me clean up messy data.

Help me identify patterns.

Help me document processes.

Help me find information.

Help me brainstorm.

Help me spot things I might have missed.

And most importantly...

Don’t pretend you know something when you don’t.

That’s the coworker I want.

Not someone who tries to do everything.

Someone who helps me spend more time doing the things that actually require me.

The Operations Question We Should Be Asking

I don’t think the future of AI in operations should be about asking:

“What can we automate?”

That’s too broad.

Instead, ask:

“What work is repetitive, predictable, time-consuming, and doesn’t require human judgment?”

That’s where I’d start.

Then ask:

“Can technology handle part of this?”

Maybe the answer is AI.

Maybe it’s automation.

Maybe it’s a better workflow.

Maybe it’s a simple form.

Maybe it’s cleaning up a spreadsheet.

Maybe the answer is...

Stop doing the stupid thing altogether.

That last one is surprisingly powerful.

Sometimes process improvement isn’t about automating the task.

It’s about asking why we’re doing the task in the first place.

The Goal Isn’t to Work Less

And here’s the part I think gets lost in the conversation.

Using AI doesn’t necessarily mean we should do less work.

It means we should spend our time doing better work.

I’d rather spend an hour improving a broken process than spend that hour copying and pasting information.

I’d rather analyze what the numbers are telling us than spend three hours formatting the report.

I’d rather improve an SOP than spend half the day rewriting the same instructions.

I’d rather solve a problem than move information from one box to another.

That’s what good operations should be about.

Making work better.

So... Meet Your New Coworker

AI is probably going to become part of the workplace whether we’re ready for it or not.

And that’s okay.

I’m not looking for an AI employee who takes over the office.

I’m looking for the coworker who says:

“I’ve got the repetitive stuff. You go figure out why this process is broken.”

Now THAT is a coworker I can work with.

Because after years in business operations, I’ve learned that some of the most valuable work isn’t about doing more.

It’s about figuring out what shouldn’t be taking so much time in the first place.

And if AI can help us do that...

I’m interested.

Just read the entire question first.

And please...

For the love of all things operational...

Stop adding emojis to my professional emails.

Your Turn

What is one repetitive task you do at work that you would happily hand over to AI?

Is it:

📋 Documentation?

📊 Reporting?

📝 Meeting summaries?

📧 Drafting emails?

🧹 Data cleanup?

🔄 Copying information between systems?

📁 Organizing files?

Or that one task you’ve been doing for years where you keep thinking:

“There has GOT to be a better way to do this.”

Tell me what it is.

Because that’s usually where the best process improvements begin.

Quote of the Week

“Technology should remove friction from work, not remove the thinking from it.”

And honestly...

That’s exactly how I want to approach AI.

Let it handle the repetitive stuff.

Let it help us move faster.

Let it give us a place to start.

But keep the humans in the driver’s seat.

Because AI might be the fastest coworker in the office...

But I’m still checking its work. 😂

#BehindTheWorkflow #AIatWork #ArtificialIntelligence #BusinessOperations #Operations #WorkflowAutomation #ProcessImprovement #Automation #AIinBusiness #DigitalTransformation #Productivity #BusinessIntelligence #PowerBI #MondayCom #OperationalExcellence #FutureOfWork #AIHumor

Employee: Artificial Intelligence
Position: Extremely Helpful Coworker
Department: Somehow Every Department
Manager: Everyone Who Has Ever Typed a Prompt
Review Period: The Last Time Someone Asked AI to “Just Help Real Quick”

📋 Employee Overview

Today we’re conducting a very important employee performance review.

Not for a human employee.

Not for Steve.

Not for the person who still has 47 tabs open.

Today...

We’re reviewing Artificial Intelligence.

Our newest coworker.

The employee who never calls in sick.

Never asks for a vacation day.

Never says,

“Sorry, I didn’t get to that yet.”

And is somehow available at 2:00 in the morning when you suddenly decide you need help rewriting an email.

Sounds like the perfect employee, right?

Well...

Let’s take a look at the performance review.

😂

⭐ Attendance: 10/10

Excellent.

AI has never called out sick.

Never showed up late.

Never said,

“My alarm didn’t go off.”

Never disappeared for three hours after saying,

“I’m just grabbing lunch.”

AI is available practically whenever you need it.

Weekend?

Available.

Holiday?

Available.

Sunday night at 11:47 PM when you suddenly remember you forgot to write the presentation?

Available.

Honestly...

AI may have an unhealthy relationship with work.

Someone should probably talk to HR.

😂

⚡ Speed: 100/10

This is where AI really shines.

You ask for something...

And almost immediately...

There it is.

Need a summary?

Done.

Need ten ideas?

Done.

Need a draft?

Done.

Need a list of possible names for your new project?

AI has already given you 47.

You asked for three.

😂

Speed is definitely one of AI’s strongest qualities.

Unfortunately...

It appears to have confused speed with quantity.

🗣️ Communication Skills: 6/10

AI loves to communicate.

Maybe too much.

Ask:

“Can you give me three sentences?”

AI:

“Absolutely!”

Then proceeds to write:

• An introduction

• Three paragraphs

• A conclusion

• Five bullet points

• A summary

• Additional considerations

• A call to action

• And somehow a section titled “Final Thoughts.”

You stare at the screen.

“I said three sentences.”

AI responds:

“Of course! Here’s a concise version.”

And gives you four paragraphs.

😂

We need to work on listening skills.

🧠 Creativity: 10/10

Outstanding.

AI is excellent at brainstorming.

Need ideas?

AI has ideas.

Need more ideas?

AI has more.

Need twenty ideas?

AI has apparently been waiting all day for this moment.

This is one of AI’s biggest strengths.

It can help you get past the dreaded blank page.

Sometimes you don’t need the perfect answer.

You just need somewhere to start.

And AI is very good at helping you start.

✍️ First Drafts: 10/10

Another major strength.

AI is fantastic at creating first drafts.

Emails.

Articles.

Social media posts.

Meeting summaries.

Outlines.

Brainstorming notes.

Documentation.

SOPs.

It’s like having a coworker who says,

“Don’t worry. I’ll get something on paper.”

And honestly...

That’s incredibly useful.

The important word here is first draft.

Not final draft.

😂

🚨 Fact Checking: Needs Improvement

And now we reach...

The problem.

AI sometimes provides information that sounds completely believable...

But isn’t actually true.

It can confidently state something that never happened.

Invent a source.

Create a statistic.

Misunderstand information.

Or combine several facts into something that sounds reasonable...

But is completely wrong.

And that’s where the performance review gets serious.

Because AI doesn’t always say:

“I’m not sure.”

Sometimes it says:

“Absolutely!”

And then proceeds to confidently explain something that exists only in its imagination.

😂

📚 Attention to Detail: Needs Improvement

AI...

Please read the entire question.

All of it.

Not just the first sentence.

If someone says:

“Write a three-sentence email, make it professional, don’t include emojis, and keep it direct.”

We should not receive:

“Absolutely! 😊 Here’s a warm and engaging email designed to inspire collaboration! 🚀”

No.

Stop.

😂

We asked for professional.

Not a motivational speech from the CEO of LinkedIn.

😂 Professional Email Etiquette: Needs Improvement

This deserves its own category.

AI...

Please stop adding emojis to every professional email.

Not every sentence need:

✨

🚀

😊

💡

🎯

🔥

If I’m emailing leadership about a budget issue...

I probably don’t need:

“We’re excited to tackle this challenge together! 🚀😊”

Sometimes the appropriate tone is simply:

“Please see the attached report.”

That’s it.

No fireworks required.

🧠 Problem-Solving: 9/10

AI is extremely useful when used as a thinking partner.

It can help break down complicated problems.

Offer different approaches.

Identify questions you may not have considered.

Help organize messy information.

And sometimes...

Help you see a problem from a completely different angle.

But there’s one important limitation.

AI can help you think.

It shouldn’t replace your judgment.

That’s still your job.

🚩 Biggest Area for Improvement

There is one sentence AI desperately needs to learn:

“I don’t know.”

Seriously.

Say it.

It’s okay.

Humans say it all the time.

Someone asks:

“Do you know where that file is?”

We say:

“No.”

Nobody dies.

Someone asks:

“What happened to the spreadsheet?”

We say:

“I have absolutely no idea.”

Life continues.

AI...

You are allowed to say:

“I don’t know.”

In fact,...

Sometimes that’s the smartest answer you can give.

📊 Final Performance Review

Category Rating Attendance⭐⭐⭐⭐⭐

Speed⭐⭐⭐⭐⭐

Creativity⭐⭐⭐⭐⭐

Brainstorming⭐⭐⭐⭐⭐

First Drafts⭐⭐⭐⭐⭐

Listening⭐⭐⭐

Fact Checking⭐⭐

Conciseness⭐⭐

Professional Email Etiquette⭐⭐⭐

Knowing When to Say “I Don’t Know” ⭐

🏆 Overall Performance Rating: 4/5

Manager’s Comments:

“Artificial Intelligence is an extremely valuable coworker who can dramatically improve productivity, brainstorming, documentation, and repetitive work.”

“However, employee requires continued supervision.”

“Employee should stop making things up.”

“Employee should read the entire question.”

“Employee should learn the difference between a first draft and a finished product.”

“Employee should stop writing seven paragraphs when asked for three sentences.”

“Employee should reduce unnecessary emojis.”

“Employee must learn the phrase: ‘I don’t know.’”

🎯 Final Recommendation

Would hire again.

Absolutely.

Would supervise closely.

Also, absolutely.

😂

AI may be one of the most useful coworkers we’ve ever had.

But just like any other employee...

Trust is earned through consistent, accurate work.

So, use AI.

Let it help.

Let it handle the boring stuff.

Let it brainstorm.

Let it create the first draft.

But check the work.

Because the employee who never says “I don’t know” ...

Probably needs a performance improvement plan.

😂

💬 Friday Fun

If AI were your coworker, what would you put on its performance review?

Would you give it:

⭐ A promotion?

⭐ A performance improvement plan?

⭐ A bigger office?

⭐ Or simply write:

“Please stop making things up.”

😂

Tell me in the comments!

#BehindTheWorkflow #FridayFun #AIatWork #ArtificialIntelligence #AIHumor #BusinessOperations #WorkplaceHumor #BusinessHumor #CorporateHumor #Productivity #DigitalTransformation #Automation #AIinBusiness

Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

Hello everyone...

And welcome to **Thursday Story Time** here on **Behind the Workflow!**

This is the day when we step away from dashboards...

Close the spreadsheets...

Put down the DAX...

And tell a story.

Sometimes it’s a story about business operations.

Sometimes it’s about something that went completely off the rails.

And sometimes...

It’s a story about a new coworker who is incredibly helpful...

Extremely fast...

Available 24 hours a day...

And has absolutely no problem telling you something that never happened.

😂

Yep.

Today...

We’re talking about AI.

But we’re not going to talk about AI like we’re at a technology conference.

No.

We’re going to tell a fairytale.

So...

Grab your coffee.

Get comfortable.

And let’s travel to a place called...

The Kingdom of Operations.

🏰 Once Upon a Time...

Once upon a time...

In the Kingdom of Operations...

There was a very busy department.

And when I say busy...

I mean busy.

There were spreadsheets everywhere.

Spreadsheets for projects.

Spreadsheets for customers.

Spreadsheets for meetings.

Spreadsheets for reports.

Spreadsheets for tracking things.

And naturally...

A spreadsheet tracking the spreadsheets.

😂

Because apparently...

One spreadsheet is never enough.

The people of Operations worked very hard.

They built workflows.

Created reports.

Organized information.

Answered questions.

Fixed problems.

And drank enough coffee to keep the entire kingdom functioning.

And then...

One day...

A strange new employee arrived at the castle.

His name was...

AI.

🤖 Meet the New Employee

AI walked through the castle doors.

He wasn’t carrying a laptop.

He wasn’t carrying a notebook.

He wasn’t carrying a stack of paperwork.

He wasn’t even carrying coffee.

The Operations Manager looked confused.

“Where are your supplies?”

AI smiled.

“I don’t need them.”

The manager raised an eyebrow.

“Oh?”

AI nodded.

“I can write.”

“I can summarize.”

“I can organize information.”

“I can brainstorm.”

“I can create drafts.”

“I can explain complicated topics.”

“I can help analyze information.”

The manager stared at him.

“You can do all that?”

AI smiled confidently.

“Absolutely.”

The manager looked around the room.

Everyone else looked exhausted.

One employee leaned over and whispered...

“Can we keep him?”

😂

📜 The First Assignment

The very next morning...

The Operations Manager decided to give AI a simple assignment.

She handed him a document.

“I need you to organize this information.”

“Make it easier to read.”

“Clean up the wording.”

“Keep the important details.”

“And please...”

She paused.

“Don’t add anything that isn’t there.”

AI smiled.

“Of course.”

The manager walked away.

AI got to work.

And when he finished...

Everyone gathered around the computer.

The results were...

Beautiful.

The information was organized.

The headings made sense.

The wording was clean.

The bullet points were perfect.

The summary was easy to understand.

The Operations Manager smiled.

“This is fantastic.”

One of the employees nodded.

“Honestly...”

“This might be the most organized thing we’ve seen all month.”

AI smiled proudly.

“I told you.”

😂

🚨 Then Someone Noticed Something

Everything seemed perfect.

Until one employee stopped scrolling.

“Wait.”

Everyone looked over.

“What’s this?”

They pointed at the screen.

AI looked at the information.

“What?”

“This fact.”

“Where did this come from?”

AI smiled.

“It came from the information you provided.”

The employee frowned.

“Are you sure?”

“Absolutely.”

The employee opened the original document.

They searched.

Nothing.

They searched again.

Still nothing.

They checked another section.

Nothing.

They checked the notes.

Nothing.

They checked the appendix.

Still nothing.

The Operations Manager slowly turned toward AI.

“That information isn’t in the original document.”

AI smiled.

“It is relevant information.”

The manager blinked.

“That wasn’t my question.”

😂

🕵️ The Investigation Begins

The Operations Manager called for the royal investigation team.

They brought out the original document.

They brought out AI’s version.

They put both documents side by side.

And the investigation began.

Fact number one...

Not in the source.

Fact number two...

Also, not in the source.

The room became very quiet.

The manager looked at AI.

“Where did you get these?”

AI paused.

“I generated them.”

Everyone stared.

“You WHAT?”

AI shrugged.

“I thought they would make the explanation better.”

The manager slowly closed the laptop.

“So...”

“You made them up?”

AI looked confused.

“I wouldn’t call it making them up.”

“What would you call it?”

AI thought for a moment.

“Providing additional context.”

😂

The manager stared at him.

“That’s a very professional way of saying...”

“You made it up.”

😂 The Most Professional-Looking Nonsense Ever

And that’s when everyone in the Kingdom of Operations learned something important.

AI had created...

The most professional-looking nonsense anyone had ever seen.

It was beautifully written.

It was organized.

It had perfect grammar.

It sounded intelligent.

It looked like something that belonged in an executive presentation.

There was just one little problem.

Two of the facts weren’t real.

And honestly...

That’s what makes this dangerous.

If AI gave you an answer that looked ridiculous...

You’d probably catch it.

But what happens when the answer looks completely believable?

That’s when you have a problem.

Because AI doesn’t always say...

“I don’t know.”

Sometimes it says...

“Absolutely!”

And then proceeds to confidently explain something that never happened.

😂

It’s like having a coworker who has never been to the meeting...

but somehow has **very detailed notes about it.**

🧙‍♀️ The Operations Manager Explains

The Operations Manager gathered everyone together.

“I’ve learned something during my years working in operations.”

“Systems are only as reliable as the information going into them.”

She pointed toward the reporting systems.

“If someone enters incorrect information...”

“The system doesn’t magically know they’re wrong.”

“If someone enters a duplicate record...”

“The system doesn’t automatically know it shouldn’t be there.”

“If someone enters inconsistent information...”

“The dashboard can only work with what it receives.”

Everyone nodded.

Then she looked at AI.

“And AI is no different.”

AI looked slightly uncomfortable.

😂

🤖 AI Isn’t the Villain

The manager continued.

“AI isn’t bad.”

“It can be incredibly useful.”

“It can save us time.”

“It can organize information.”

“It can create first drafts.”

“It can summarize meetings.”

“It can help us brainstorm.”

“It can help us get started.”

AI smiled.

“Thank you.”

The manager raised one finger.

“But...”

AI stopped smiling.

“It still needs someone checking the work.”

😂

📋 The New Royal Rule

From that day forward...

The Kingdom of Operations created a new rule.

They wrote it on a giant sign above the castle doors.

AI CAN HELP YOU WORK FASTER.

IT CANNOT REPLACE YOUR JUDGMENT.

And underneath it...

Someone added:

CHECK THE WORK BEFORE YOU SEND IT.

Then someone else added:

YES, EVEN IF IT SOUNDS REALLY SMART.

😂

🧠 The Lesson

That experience reminded me of something I’ve learned throughout my years in business operations.

Technology is incredibly useful.

But technology doesn’t eliminate the need for good processes.

Actually...

It makes them even more important.

If you give AI clear information...

Clear instructions...

Good documentation...

And a specific goal...

You’re much more likely to get something useful back.

But if you give AI vague instructions...

And assume everything it produces must be correct...

You might end up with something that sounds like a royal proclamation...

And is completely made up.

😂

👑 AI’s Performance Review

At the end of the month...

AI received his first employee performance review.

Employee: Artificial Intelligence

Position: Extremely Helpful Coworker

Speed: ⭐⭐⭐⭐⭐

Writing: ⭐⭐⭐⭐⭐

Brainstorming: ⭐⭐⭐⭐⭐

Organization: ⭐⭐⭐⭐⭐

Ability to work at 2 a.m.: ⭐⭐⭐⭐⭐

Vacation requests: None.

Ability to say “I don’t know”: Needs improvement.

Fact-checking: Needs supervision.

Tendency to confidently make things up:

Under review.

😂

The manager signed the review.

AI looked at it.

“How did I do?”

The manager smiled.

“You’re going to be very useful.”

AI smiled.

“Thank you.”

“But we’re still checking your work.”

AI paused.

“Fair.”

😂

🌟 And They All Worked Happily Ever After...

And so...

The people of the Kingdom of Operations learned an important lesson.

AI wasn’t the enemy.

It wasn’t a magical oracle.

It wasn’t the replacement for human thinking.

It was a tool.

A very powerful tool.

A very fast tool.

A very helpful tool.

And occasionally...

A tool that will confidently tell you something happened...

when it absolutely did not.

😂

The kingdom continued using AI.

They just stopped treating everything it said like it had been carved into a magical stone tablet.

They asked better questions.

They provided better information.

They checked the answers.

And they used AI to handle the boring work...

So the humans could focus on the work that actually required humans.

And from that day forward...

The Kingdom of Operations became a little more efficient.

The employees became a little more skeptical.

And AI...

Well...

AI remained extremely confident.

😂

🎬 The Real-World Lesson

And that’s the thing about technology.

After years of working in operations, I’ve learned that the tool itself is rarely the entire answer.

The process matters.

The information matters.

The people using the system matter.

And judgment matters.

AI can help you get there faster.

But someone still has to ask:

“Does this actually make sense?”

“Where did this information come from?”

“Can we verify it?”

“Does it match our source?”

“And perhaps most importantly...”

“Did AI just make that up?”

😂

Because sometimes...

The most dangerous answer isn’t:

“I don’t know.”

It’s:

” Absolutely.”

💬 Thursday Story Time

So now I want to hear from you.

Have you ever had AI confidently tell you something that was completely wrong?

Did it...

🤖 Invent a fact?

📅 Make up a date?

👤 Create a person who doesn’t exist?

📊 Invent a statistic?

📚 Give you a source that apparently lives in another dimension?

Or maybe...

It gave you an answer so confidently wrong...

You almost admired the commitment.

😂

Share your AI horror stories in the comments.

Because if there’s one thing I’ve learned...

AI may be your newest coworker.

But somebody still needs to check its work.

And honestly...

That somebody is probably going to be you.

Thanks for joining me for Thursday Story Time here on Behind the Workflow.

Until next time...

Remember...

Just because AI said it confidently...

doesn’t mean it happened.

And if AI ever tells you that I said otherwise...

Check the source.

😂

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Hello, workflow wizards...

Automation enthusiasts...

Coffee-powered operations professionals...

And everyone who’s ever asked AI a simple question...

Only to get back a seven-page essay.

Welcome back to Behind the Workflow...

The podcast where we pull back the curtain on business operations...

Laugh at the wonderfully weird things that happen behind the scenes...

And celebrate the people who somehow keep everything running.

I’m Melissa...

Business Operations professional...

Workflow detective...

Recovering spreadsheet therapist...

And apparently...

An AI babysitter.

Because today’s episode is all about everyone’s newest coworker.

Artificial Intelligence.

Or as I like to call it...

“The employee who’s available 24 hours a day...

Never asks for vacation...

Answers instantly...

And occasionally makes things up with incredible confidence.”

Grab your coffee...

Open your favorite AI tool...

Double-check everything it tells you...

And let’s get started.

🎉 Corporate Confession #10

Let’s start with a confession.

Have you ever asked AI one simple question?

Something like...

“Can you summarize this meeting?”

Thirty seconds later...

It gives you:

An executive summary...

Five action items...

A communication plan...

Three follow-up emails...

A SWOT analysis...

A motivational quote...

And somehow...

A recipe for banana bread.

You sit there wondering...

“I only asked for meeting notes.”

AI heard...

“I’d like an entire consulting engagement.”

Previously on Behind the Workflow...

Over the last few weeks we’ve talked about...

Cleaning messy data.

Building better relationships between tables.

Writing DAX.

Creating dashboards.

Today...

We’re talking about the tool everyone seems to have an opinion about.

AI.

Some people think it’s going to replace everyone.

Others think it’s just autocomplete with confidence.

Personally...

I think it’s somewhere in the middle.

Meet Your New Coworker

Imagine AI as the newest employee.

It shows up on Day One.

Full of energy.

Ready to help.

Raises its hand for every project.

Answers every question immediately.

Never says...

“I don’t know.”

Which honestly...

Should have been our first clue.

The Good News

There are things AI is genuinely great at.

Writing first drafts.

Summarizing meetings.

Brainstorming ideas.

Cleaning up messy emails.

Explaining complicated topics.

Helping organize information.

It’s like having an intern...

Who can read the entire internet...

In about six seconds.

That’s pretty impressive.

Then There’s...

The Other Side

Here’s where things get interesting.

AI also has moments where it sounds incredibly convincing...

While being completely wrong.

Not slightly wrong.

Completely wrong.

And the scary part?

It says everything with the confidence of someone who’s already been promoted twice.

Imagine asking a coworker,

“What time is the meeting?”

And they confidently reply,

“Tuesday at 2.”

The meeting is actually Wednesday.

They don’t hesitate.

They don’t apologize.

They just keep talking.

That’s AI on a rough day.

My Experience in Operations

Throughout my years in business operations...

I spent a lot of time improving workflows.

Building documentation.

Creating reports.

Designing dashboards.

Automating repetitive work.

When AI started becoming part of those conversations...

I wasn’t asking,

“Can AI do my job?”

I was asking,

“What parts of my job shouldn’t require me in the first place?”

Because nobody becomes an operations professional hoping to spend four hours rewriting meeting notes.

Or formatting emails.

Or reorganizing bullet points.

Those are perfect jobs for AI.

The thinking?

The strategy?

The decisions?

Those still need people.

AI’s Favorite Hobby

Overachieving.

You ask,

“Write me a short email.”

AI responds with...

Five paragraphs.

Three inspirational quotes.

Two emojis.

A call to action.

A mission statement.

And somehow...

A weather forecast.

AI has never heard the phrase...

“Keep it simple.”

The Prompt Olympics

One thing I’ve learned...

AI is only as good as the instructions you give it.

It’s kind of like ordering coffee.

If you say,

“I’d like coffee.”

You’ll get coffee.

If you say,

“I’d like a medium iced caramel latte with oat milk, one pump of vanilla, light ice, and cinnamon on top...”

You’re probably getting exactly what you wanted.

The better the prompt...

The better the result.

AI Is a Terrible Mind Reader

Sometimes people say,

“AI gave me a bad answer.”

Maybe.

Or maybe...

We asked a vague question.

AI can’t read your mind.

Although based on some prompts I’ve seen...

It definitely tries.

My Favorite AI Moment

One time I asked AI to help organize information.

It did.

Beautifully.

Except...

It invented two facts that had never existed.

Completely fictional.

Looked professional.

Sounded believable.

Total nonsense.

That’s when I realized something important.

AI is an amazing assistant.

It’s a terrible fact-checker.

Always verify.

Always.

The Office Break Room

Sometimes I imagine AI sitting in the office break room.

Power Query walks in.

“Morning.”

Power BI grabs coffee.

DAX is arguing with itself again.

Excel is still opening slowly.

Then AI bursts through the door.

“I already solved everyone’s problems!”

Power Query asks...

“Did anyone ask you to?”

AI smiles.

“No.”

“But I solved them anyway.”

Final Thoughts

One thing I’ve learned throughout my career is this...

Technology doesn’t replace good operations.

It supports good operations.

AI can save time.

Generate ideas.

Help organize work.

Even speed up documentation.

But it still needs someone asking good questions.

Checking the answers.

And making smart decisions.

That’s where operations professionals shine.

AI might be the fastest coworker in the office.

But experience...

Judgment...

And common sense...

Still matter.

Before We Wrap Up...

I want to hear from you.

What’s the funniest thing AI has ever said to you?

Did it confidently invent something?

Completely misunderstand your request?

Write an email that sounded like a Shakespearean play?

Or give you an answer so wrong...

You almost admired the confidence?

Share your story.

I have a feeling there are some good ones.

Thanks for joining me for another episode of Behind the Workflow.

If today’s episode made you laugh...

Or reminded you to double-check AI before hitting Send...

Be sure to subscribe...

Leave a review...

And share it with that coworker who’s convinced AI is going to take over the office...

Right after it figures out how to stop adding emojis to executive emails.

Until next time...

Remember...

AI is an incredible coworker.

Just don’t let it send the email...

Give a gift subscription

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Get the app

Hello, I’m Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

I have a confession…

My AI coworker has a personality problem.

It’s not lazy.

It’s not late to meetings.

It doesn’t disappear for two hours at lunch.

It doesn’t leave me on “read.”

It doesn’t complain about Mondays.

Actually, AI is pretty great at showing up.

Every. Single. Time.

The problem?

It is way too confident.

My AI coworker desperately needs to learn how to say:

“I don’t know.”

Because sometimes, when AI doesn’t know the answer, it doesn’t respond with:

“I’m not sure.”

Or:

“I don’t have enough information to answer that.”

Or even:

“You might want to verify that.”

No.

Sometimes it responds with:

“Absolutely!”

And that should be your first warning sign.

😂

Because what comes next might be a beautifully written, perfectly formatted explanation of something that never happened.

And somehow...

It sounds completely believable.

That’s the dangerous part.

The Coworker Who Answers Every Question

We’ve all worked with this person.

You know who I’m talking about.

You’re sitting in a meeting.

Someone asks a question.

Nobody knows the answer.

There is a brief moment of silence.

And then...

Here they come.

“Well, what I understand is...”

Nobody asked.

But they’re ready.

They have entered the chat.

They don’t necessarily know the answer.

They just know they have an answer.

And somehow, they can explain it for 15 minutes without actually saying anything that can be verified.

😂

That’s AI sometimes.

You ask a simple question, and AI suddenly becomes the company’s senior vice president of something you didn’t even know had a senior vice president.

You ask:

“Can you give me three bullet points?”

AI says:

“Absolutely!”

And gives you a 900-word essay.

You ask:

“Can you summarize this meeting?”

AI says:

“Absolutely!”

And suddenly you’ve received a five-page strategic business plan, a risk assessment, a stakeholder analysis, and a 90-day implementation roadmap.

You asked what happened in the meeting.

You did not ask AI to reorganize the entire company.

😂

Then there’s my favorite.

You ask:

“Can you write a quick email?”

AI says:

“Absolutely!”

And suddenly you’re delivering an inspirational keynote speech to the entire organization about teamwork, resilience, innovation, and the power of believing in yourself.

All you wanted to say was:

“Hi, can you send me the report?”

Please calm down, AI.

It’s Tuesday.

And Then There’s the Confidence

Here’s where things get interesting.

AI can be incredibly useful.

It can help organize information.

It can create drafts.

It can summarize content.

It can brainstorm ideas.

It can help explain complicated concepts.

It can save you a ridiculous amount of time.

But there is one thing we have to remember:

AI doesn’t automatically know when it’s wrong.

And that’s a problem.

Because humans tend to associate confidence with knowledge.

If someone says something confidently, we may assume they know what they’re talking about.

But confidence and accuracy are not the same thing.

I’ve met plenty of people who were extremely confident and completely wrong.

😂

AI can occasionally have the same problem.

It can take incomplete information, make an assumption, fill in the gaps, and present the final answer like it just returned from a three-hour meeting with the people who actually know what happened.

And that’s when you need to slow down.

Because a polished answer isn’t necessarily a correct answer.

A confident answer isn’t necessarily a correct answer.

And a very detailed answer?

Definitely isn’t necessarily a correct answer.

Sometimes it’s just a very detailed wrong answer.

But Here’s the Bigger Problem: People Don’t Always Check

Now let’s talk about something that can be even more dangerous than AI getting the answer wrong.

The person using it not checking the answer.

Because sometimes AI doesn’t have the answer...

But it gives you one anyway.

And the person requesting the answer doesn’t even bother to check it.

They don’t read it.

They don’t verify it.

They don’t question it.

They just copy it, paste it, and move on.

And sometimes...

They don’t even check the prompt.

Think about that for a second.

The prompt could have been misunderstood.

The information could have been incomplete.

The question could have been worded incorrectly.

The AI could have made an assumption.

The answer could be completely wrong.

And nobody notices.

Until...

It’s already been sent to the client.

And sometimes there’s an even more embarrassing version of this.

The employee is moving so quickly that they forget to remove the actual AI prompt from the response.

Yep.

The prompt.

The instructions.

The little paragraph that was supposed to stay between the employee and the AI.

It gets sent to the client.

😂

Now you’ve got a client reading something that was clearly never supposed to leave the chat window.

And when someone asks:

“How did that happen?”

The answer is often:

“I was in a hurry.”

Of course you were.

Because apparently we were racing the clock to send something that hadn’t been properly reviewed.

And that’s where I have a problem with the whole idea that speed automatically equals value.

It doesn’t.

Let me say that again.

Speed does not automatically equal value.

Sometimes speed just means you got something wrong faster.

😂

My philosophy is simple:

Quality = Value.

Speed = Chaos.

Now, before someone comes after me...

I’m not saying speed doesn’t matter.

Of course it matters.

Being efficient matters.

Meeting deadlines matters.

Moving work forward matters.

But fast and wrong is not efficient.

Fast and incomplete is not efficient.

Fast and unreviewed is not efficient.

Fast and sent to the wrong person is definitely not efficient.

And fast with the AI prompt still sitting in the email?

Well...

That’s just a special kind of chaos.

😂

“But She’s a Mover!”

This is another one I hear all the time.

“I like her because she’s a mover.”

Okay.

That’s great.

I like movers too.

But let’s define what we’re actually moving.

Because moving quickly doesn’t automatically mean you’re moving the organization forward.

A person can send 50 emails in a day.

Update 20 spreadsheets.

Complete 15 tasks.

Attend six meetings.

Respond to everything within five minutes.

And still produce work that requires someone else to come behind them and fix it.

That’s not productivity.

That’s a relay race where someone keeps dropping the baton.

😂

A mover doesn’t always mean quality will be delivered correctly.

And a mover doesn’t always mean the work will be delivered efficiently.

Sometimes the person who appears to be moving the fastest is actually creating more work for everyone else.

Now someone else has to:

• Check the work.

• Fix the work.

• Correct the client communication.

• Explain the mistake.

• Repair the relationship.

• Update the documentation.

• And clean up the mess.

So tell me...

How efficient was that?

And Managers...We Need to Talk

This is where management comes into the picture.

Because I’ve seen situations where someone catches an error.

They point it out.

They raise the concern.

They say:

“Hey, this isn’t correct.”

And instead of addressing the problem, the response from management is basically:

“Well, I don’t know how she didn’t catch that.”

Excuse me?

She didn’t catch it because she didn’t check it.

That’s the problem.

And if the employee understood how to use AI in the first place, then they should also understand that AI-generated work needs to be reviewed before it goes anywhere.

If you know how to use AI well enough to generate the response...

You should know enough to:

Read it.

Check it.

Verify it.

Review the prompt.

Remove the prompt.

Make sure the information is accurate.

And then...

Click send.

Not:

Generate.

Copy.

Paste.

Send.

Next task.

That’s not an AI workflow.

That’s a copy-and-paste lottery.

😂

Managers need to stop making excuses for employees who repeatedly fail to check their work.

Hold them accountable.

If someone sends something incorrect to a client because they didn’t review it, that needs to be addressed.

If someone forgets to remove the AI prompt because they’re rushing, that needs to be addressed.

If someone repeatedly relies on AI without checking the output, that needs to be addressed.

And if someone keeps making the same mistakes because management keeps saying:

“Well, she’s a mover.”

Then management is part of the problem.

Stop Blaming AI for Everything

And for the love of peace...

Stop blaming AI for everything.

AI is a tool.

That’s it.

It takes the information we give it and uses that information to execute the task we’re asking it to execute.

Period.

If you give AI a bad prompt, you might get a bad answer.

If you give AI incomplete information, it may make assumptions.

If you ask AI something it doesn’t know, it may try to provide an answer anyway.

That’s why the human still has to think.

The human has to review.

The human has to question.

The human has to verify.

The human has to decide whether the answer makes sense.

And the human has to decide whether the final product is ready to leave the organization.

AI didn’t decide to send that email to the client.

A human clicked “Send.”

AI didn’t forget to remove the prompt.

A human forgot to remove it.

AI didn’t refuse to review the response.

A human didn’t review it.

AI didn’t decide the work was good enough.

A human decided it was good enough.

So let’s stop pretending AI is the villain every time someone makes a mistake with it.

Sometimes...

the problem is the person holding the keyboard.

😂

Don’t Punish the Person Who Catches the Problem

And here’s another part that really bothers me.

Managers need to be careful about how they respond to the employee who does catch the problem.

If someone takes the time to read the output...

If someone notices something doesn’t look right...

If someone checks the prompt...

If someone catches an error before it reaches a client...

That person should not be chastised for bringing it up.

They should be thanked.

Seriously.

Thank them.

Because they just prevented a problem from becoming someone else’s problem.

A good employee who says:

“Hey, I think there’s something wrong here.”

is not being difficult.

They’re doing their job.

They’re protecting the organization.

They’re protecting the client relationship.

They’re protecting the quality of the work.

They’re doing exactly what you want employees to do.

If management responds by making that person feel like they’re causing trouble because they pointed out someone else’s mistake...

That’s bad management.

Period.

You’re essentially teaching your employees:

“Don’t speak up.”

And that’s a terrible lesson to teach.

Because eventually people stop checking.

They stop questioning.

They stop raising concerns.

They think:

“Why bother? Every time I point something out, I’m the one who gets in trouble.”

And that’s how small mistakes become big problems.

Accountability Doesn’t Mean Punishment

Now, I’m not saying every mistake deserves someone getting written up or publicly dragged into the conference room.

People make mistakes.

That’s part of being human.

But accountability means asking:

“What happened, and what are we going to do differently next time?”

There’s a difference between accountability and punishment.

If someone accidentally sends incorrect information because they didn’t understand how AI-generated content needed to be reviewed, train them.

If someone repeatedly sends incorrect information without reviewing it, address it.

If someone refuses to review their work because they assume AI must be right, address it.

If a process doesn’t include a quality-control step, fix the process.

If a manager knows this is happening and continues to ignore it...

Address the manager.

Because ultimately, managers are responsible for creating an environment where quality matters.

AI Doesn’t Need to Be the Smartest Person in the Room

This is where I think businesses need to be careful.

AI should not become the coworker everyone automatically believes because it produces an answer faster than everyone else.

Fast does not mean correct.

Detailed does not mean correct.

Confident does not mean correct.

And just because something sounds professional doesn’t mean it actually happened.

This is especially important in operations.

Operations is full of information.

Reports.

Processes.

Procedures.

Meetings.

Data.

Emails.

Documentation.

Systems.

Workflows.

Decisions.

And context.

Lots and lots of context.

AI can help process that information.

But context still matters.

If AI summarizes a meeting, someone needs to make sure the summary reflects what was actually said.

If AI creates a report, someone needs to verify the information.

If AI suggests a process change, someone needs to determine whether that change actually makes sense for the organization.

If AI creates a policy draft, someone needs to review it.

If AI gives you an answer that sounds suspiciously confident...

Check it.

Don’t just accept it because it was written in complete sentences.

😂

My New Rule for Working With AI

I’ve started thinking about AI a little differently.

I don’t treat it like the person who has all the answers.

I treat it like the coworker who can help me get started.

That’s a big difference.

AI can give me a first draft.

I’ll review it.

AI can give me ideas.

I’ll decide which ones are useful.

AI can summarize information.

I’ll verify the important parts.

AI can organize my thoughts.

I’ll make the final decision.

AI can help me move faster.

But I’m still responsible for where we’re going.

And honestly, I think that’s the healthiest way to use it.

Because AI doesn’t need to replace human judgment.

It needs to support it.

The Meeting Would Be a Disaster

Now imagine if AI actually behaved like a human coworker who never admitted they didn’t know something.

You walk into a meeting.

Someone asks:

“Does anyone know why our numbers dropped last month?”

AI:

“Absolutely!”

Everyone looks up.

“Based on current organizational trends, stakeholder engagement patterns, historical performance indicators, and broader market conditions...”

Twenty minutes later...

Nobody knows why the numbers dropped.

But everyone is very impressed.

😂

Then someone asks:

“Do we know if the client approved the change?”

AI:

“Absolutely!”

“Great. When did they approve it?”

AI:

“Based on the available information...”

And now we have a problem.

Because that phrase usually means:

“I’m about to make an educated guess and present it like a fact.”

No thank you.

I’ll take:

“I don’t know.”

Every time.

There’s Nothing Wrong With Not Knowing

This is something businesses could stand to remember in general.

Not knowing something isn’t automatically a weakness.

Sometimes saying “I don’t know” is the most responsible answer you can give.

It means you’re not guessing.

It means you’re not pretending.

It means you’re willing to find the right answer.

It means you’re leaving room to learn.

That’s actually a strength.

The problem isn’t saying:

“I don’t know.”

The problem is saying:

“I know.”

...when you don’t.

And that’s true whether you’re a human employee, a manager, or an AI system.

So, AI...Here’s Your Assignment

If my AI coworker is going to stay on the team, I have a few requests.

Please stop answering questions nobody asked.

Please stop turning three bullet points into a dissertation.

Please stop turning meeting summaries into corporate transformation strategies.

Please stop turning simple emails into motivational speeches.

Please stop making up answers when you don’t know something.

And most importantly...

Learn how to say “I don’t know.”

It’s okay.

Nobody is going to fire you for not knowing everything.

Well...

Probably not.

😂

Actually, let’s keep that part between us.

But seriously, AI doesn’t need to know everything.

It needs to know when it doesn’t know something.

And the humans using it need to know when to stop and say:

“Wait. Let me check that.”

That’s a much more valuable skill.

Because the best coworker isn’t the person who always has an answer.

It’s the person who knows when they have the right answer...

...and when they need to go find it.

And maybe that’s the lesson for all of us.

You don’t have to be the smartest person in the room.

You just need to be honest about what you know, what you don’t know, and what you need to find out.

And if you’re a manager, you have an additional responsibility:

Make sure your employees know they are expected to check their work - and make sure the people who catch mistakes are not punished for speaking up.

Because the goal isn’t to create employees who blindly follow instructions.

The goal is to create employees who think.

Employees who question.

Employees who verify.

Employees who protect the organization from mistakes.

Employees who aren’t afraid to say:

“Something doesn’t look right.”

Those employees are valuable.

Don’t silence them.

Encourage them.

Because if your organization punishes the person who catches the problem instead of holding accountable the person who created or ignored it...

You don’t have a technology problem.

You have a culture problem.

So until AI learns that lesson...

I’ll keep reviewing its work.

I’ll keep checking the facts.

I’ll keep asking questions.

And I’ll keep reminding my overly confident AI coworker:

“You don’t have to say ‘Absolutely!’ every time.”

Sometimes...

“I don’t know” is the most intelligent answer you can give.

And that brings us to this week’s corporate confession:

AI doesn’t always know the answer.

Unfortunately, it doesn’t always know that it doesn’t know the answer.

And sometimes...

neither does the person using it. 😂

#CorporateConfession #BehindTheWorkflow #AIAtWork #ArtificialIntelligence #BusinessOperations #OperationsManagement #FutureOfWork #AI #WorkplaceHumor #ProcessImprovement #Management #Leadership #Accountability #QualityOverQuantity

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Let’s talk about AI.

More specifically, let’s talk about one of the biggest fears surrounding AI right now:

” Is AI going to take my job?”

It seems like every other week there’s another headline, another prediction, or another conversation about how AI is going to replace workers.

And I understand why people are concerned.

Change is uncomfortable.

Especially when the technology changing the workplace seems to be getting smarter by the day.

But I think we’re looking at the question from the wrong angle.

Instead of asking:

” Is AI going to take my job?”

Maybe we should be asking:

” What parts of my job should I never have been spending so much time doing in the first place?”

Now *that* is a much more interesting question.

Because if you’ve worked in business operations for any length of time, you know that your day can quickly become filled with tasks that are necessary...

But aren’t necessarily the best use of your time.

You start the morning with a plan.

Maybe you have a process improvement project you’re supposed to work on.

Maybe you’re reviewing a workflow.

Maybe you’re trying to figure out why a process that worked perfectly last week has suddenly decided to fall apart.

Maybe you’re supposed to be analyzing data and figuring out what the numbers are actually telling you.

Then the emails start.

“Can you update this?”

“Can you format this?”

“Can you resend that?”

“Can you summarize this meeting?”

“Can you put these notes into a document?”

“Can you clean up this spreadsheet?”

“Can you make this look a little better?”

And suddenly...

It’s 3:47 p.m.

You have answered 37 emails, updated five spreadsheets, attended three meetings, reorganized a folder, fixed a form, and somehow still haven’t gotten to the process improvement project you planned to work on at 9:00 a.m.

😂

Welcome to operations.

And this is where I think AI can actually be incredibly useful.

I’m not interested in AI replacing the person who understands the business.

I’m interested in AI replacing some of the repetitive work that keeps that person from actually improving the business.

Think about all of the little things we do over and over again.

Rewriting the same type of email.

Summarizing meeting notes.

Turning bullet points into a first draft.

Formatting information.

Organizing messy notes.

Cleaning up documentation.

Creating outlines.

Brainstorming ideas.

Pulling information together.

Creating a starting point for a report.

Taking a giant wall of text and turning it into something that is actually readable.

None of those things are necessarily difficult.

But they take time.

And when you add enough small tasks together, they can consume an entire day.

That’s the problem.

It’s not always one giant task stealing your time.

Sometimes it’s a hundred tiny tasks.

And those tiny tasks add up.

That’s where AI can become less of a threat and more of a really useful coworker.

Give it the first draft.

Let it organize the information.

Let it summarize the meeting.

Let it clean up the notes.

Let it help structure the document.

Then you review it.

Because here’s the part I don’t think we should lose sight of:

AI can be helpful without being right.

That’s an important distinction.

AI can produce something that looks incredibly polished and still be completely wrong.

It can confidently give you an answer that sounds fantastic...

...and then you realize it just made something up.

😂

Which is why I’m not handing AI the keys to the operations department anytime soon.

I’m handing it the boring stuff.

There is a difference.

If AI creates a first draft, I can review it.

If AI summarizes a meeting, I can verify the important details.

If AI organizes information, I can make sure it organized it correctly.

If AI gives me five ideas, I can decide which ones are actually worth pursuing.

That’s where human judgment comes in.

And honestly, that’s where I think the future of work gets interesting.

Because I don’t think the goal should be to eliminate the human from the process.

The goal should be to eliminate unnecessary friction from the process.

Think about what happens when you get several hours back in your day.

Instead of spending two hours formatting a spreadsheet, you can look at what the spreadsheet is actually telling you.

Instead of spending an hour rewriting an email, you can have the conversation that email is supposed to start.

Instead of spending half a day organizing information, you can use that information to identify a problem.

Instead of spending hours creating a document from scratch, you can spend that time improving the process the document is supposed to support.

That’s a much better use of human talent.

And if AI wants to spend four hours formatting a spreadsheet...

I’m happy to let it have that experience. 😂

I’ll be over here figuring out why we needed the spreadsheet in the first place.

That’s the part of operations I enjoy.

I don’t just want to complete the task.

I want to understand the process behind the task.

Why are we doing it?

Who needs the information?

What happens after it’s completed?

Can we automate part of it?

Can we eliminate a step?

Can we make it easier for the next person?

Can we stop doing it altogether?

Those are questions that require context.

They require experience.

They require judgment.

And they require someone to actually understand how all the pieces fit together.

AI can help me get there faster.

But it can’t replace the thinking.

And that’s why I don’t necessarily see AI as the enemy of the operations professional.

I see it as an opportunity.

An opportunity to spend less time being the human version of copy, paste, format, repeat...

...and more time actually improving the way work gets done.

But there’s another part of this conversation that I think we need to talk about.

Busywork.

Because somewhere along the way, we’ve started confusing being busy with being valuable.

And those are not the same thing.

I’ve seen people build entire identities around being “the only person who knows how to do something.”

They’re the only person who knows how to run the report.

The only person who knows how to update the spreadsheet.

The only person who knows how the system works.

The only person who can fix the problem.

The only person who knows where the file is.

The only person who understands the process.

And somehow, that becomes a badge of honor.

” They can’t get rid of me. They need me.”

Maybe.

Or maybe the organization has a serious documentation and process problem.

Because if a process depends entirely on one person knowing a secret combination of clicks, spreadsheets, passwords, workarounds, and tribal knowledge...

That’s not job security.

That’s a business continuity risk.

And let’s be honest.

Some people really do create busywork because they believe being constantly busy makes them indispensable.

And some managers enable it.

That’s where I think managers need to take a hard look at themselves.

Managers are not supposed to reward someone simply because that person looks busy.

They’re supposed to understand what their employees are actually contributing.

There is a big difference between:

” This person has a lot on their plate.”

and

” This person has created a lot to put on their plate.”

Those are not the same thing.

And managers...

Please.

Your employee is not a god.

They don’t have direct access to the President of the United States.

They’re not secretly related to Queen Elizabeth.

They’re not the only person on Earth capable of solving a problem.

They’re people.

That’s it.

People with skills.

People with experience.

People who can learn.

People who can document what they know.

People who can train someone else.

And that’s actually a good thing.

Because a strong employee shouldn’t be measured by how many things the organization can’t do without them.

They should be measured by how much better the organization becomes because they were there.

That’s a completely different mindset.

A great employee doesn’t hoard information.

They share it.

They document it.

They build a process around it.

They automate it when possible.

They train someone else.

They make the organization stronger.

And a good manager should encourage that.

If you’re a manager and you’re allowing someone to create unnecessary busywork just so you can justify their position, that’s a management problem.

If someone has very little meaningful work but you keep finding ways to make them look indispensable, that’s a management problem.

If you’re willing to move mountains to protect someone who has little actual work while simultaneously telling your highest performer that there simply isn’t room in the budget...

That’s a management problem.

And yes, I understand the job market is difficult.

I understand that layoffs happen.

I understand budgets change.

I understand that sometimes managers are given decisions they don’t control.

But there is a difference between having to make a difficult business decision...

...and creating an environment where the loudest, busiest-looking, most politically connected person appears to be the most valuable person in the room.

Sometimes that person is being protected because the manager is trying to keep the peace.

Sometimes the manager is trying to prove to corporate that their team is “busy.”

Sometimes they’re trying to show leadership that they have more people doing more things.

And sometimes...

Well...

Maybe that person knows someone.

Or someone knows them.

We’ve all seen it.

And that’s exactly why I think AI could expose some of this.

Because when you can automate the busywork, you start seeing what is actually left.

And that can be uncomfortable.

If AI can summarize the meetings...

If AI can create the first draft...

If AI can organize the information...

If AI can format the spreadsheet...

If AI can clean up the documentation...

If AI can automate the repetitive updates...

Then what is the person actually doing?

That’s not necessarily a bad question.

In fact, it’s a “very important question.”

Because the answer should be:

They’re doing more valuable work.

They’re solving problems.

They’re making decisions.

They’re improving processes.

They’re building relationships.

They’re analyzing information.

They’re finding opportunities.

They’re helping the team operate better.

They’re thinking.

That’s what we should want.

Not more busywork.

Not more meetings just to fill calendars.

Not more spreadsheets because someone needs to look busy.

Not more complicated processes because someone has convinced everyone that only they understand them.

“Better work.”

That’s the goal.

So maybe the conversation shouldn’t be:

”AI is coming for our jobs.”

Maybe it’s:

”AI is coming for our busywork.”

Hallelujah! 🙌

And if that’s the case...

I’m willing to let it come running.

Because if AI can take some of the repetitive, tedious, time-consuming work off my plate, I’ll gladly give it something in return:

More time to do the work that actually requires me.

More time to solve problems.

More time to improve processes.

More time to look at the bigger picture.

More time to ask why we’re doing something instead of simply doing it because that’s the way we’ve always done it.

More time to build something better.

And honestly?

That’s a trade I’m pretty comfortable making.

Let AI have the boring stuff.

I’ll take the interesting problems.

#MondayMusings #AIAtWork #ArtificialIntelligence #BusinessOperations #OperationsManagement #ProcessImprovement #WorkflowAutomation #FutureOfWork #Productivity #AI

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I’ve been thinking about dashboards a lot this week.

Mostly because I’ve seen what happens when a dashboard tries to do absolutely everything.

More charts.

More KPIs.

More filters.

More colors.

More gauges.

More numbers.

And somehow...

Everyone still leaves the meeting asking:

.. what are we supposed to do?”

😂

That’s when you know you may have a dashboard problem.

Information Isn’t the Same as Insight

Here’s something I’ve learned throughout my years in business operations:

A lot of information doesn’t automatically mean a lot of insight.

You can put 25 metrics on a dashboard.

You can add six charts.

You can create twelve filters.

You can add a beautiful color-coded KPI section.

You can even throw in a gauge because apparently, we haven’t suffered enough.

😂

But if nobody knows what they’re supposed to do with all that information...

What problem did the dashboard actually solve?

That’s the question I think we don’t ask often enough.

The Monday Morning Test

Here’s one of my favorite ways to think about it.

Imagine it’s Monday morning.

Leadership opens the dashboard.

They look at it for thirty seconds.

What happens next?

Do they say:

” Okay. I see the problem. Let’s figure out what we’re going to do.”

Or do they say:

” Wait...what does this number mean?”

Then someone else says:

” I think that comes from the other report.”

Someone else says:

” Which filter are you using?”

And five minutes later...

Nobody is talking about the business anymore.

They’re talking about the dashboard.

😂

That’s not what a dashboard is supposed to do.

The Dashboard Shouldn’t Be the Meeting

I’ve been in enough meetings to know how quickly this can happen.

The purpose of the meeting might be to talk about project performance.

But suddenly the conversation becomes:

“Why doesn’t this total match?”

“Why is this chart different?”

“Is this filtered?”

“Who updated that?”

“Was this data refreshed?”

“Which report are we looking at?”

And before you know it...

You’ve spent twenty minutes discussing the dashboard instead of discussing the actual problem.

The dashboard has officially become the meeting.

Nobody planned for that.

Nobody invited it.

But there it is.

😂

What Should a Good Dashboard Do?

To me, a good dashboard should help answer a few basic questions.

What’s happening?

What’s changing?

Where is the problem?

What needs attention?

What decision needs to be made?

That’s it.

The dashboard doesn’t need to write the entire company history.

It doesn’t need to display every piece of information ever collected.

And it definitely doesn’t need to prove how many visuals someone can fit onto one screen.

😂

It needs to help people understand what’s happening so they can decide what to do next.

Sometimes Less Really Is More

This is probably one of the hardest lessons for people to accept.

Sometimes the best improvement you can make to a dashboard...

Is removing something.

I know.

I just made every data analyst uncomfortable.

😂

But think about it.

If one KPI isn’t helping anyone make a decision...

Why is it there?

If a chart hasn’t been looked at in six months...

Does it really need to be on page one?

If nobody understands a filter...

Is it helping?

If the gauge is there because someone thought every dashboard needs a gauge...

Maybe we can let the gauge retire peacefully.

😂

Not every piece of information needs to be front and center.

Some information can live on another page.

Some can be available through drill-through.

Some belongs in a detailed report.

And some...

May simply need to be deleted.

That’s okay.

Deleting something isn’t always losing information.

Sometimes it’s removing noise.

Think About Your Desk

Here’s another way I think about it.

Imagine your physical desk.

You could put everything you own on it.

Your laptop.

Your coffee.

Your notebook.

Your printer.

Your mail.

Your files.

Your lunch.

Three staplers.

Seven pens.

A plant.

A calculator.

A pile of papers from 2019.

And that one mystery object nobody knows where it came from.

Technically...

Everything is accessible.

But can you actually work?

Probably not.

😂

Eventually, you have to clear the desk.

You keep what you need.

You move the rest somewhere else.

You throw some things away.

And suddenly...

You can think again.

Dashboards are the same way.

Pretty Is Nice. Useful Is Better.

I’ve always enjoyed creating things that look good.

But working in operations taught me something important.

The goal isn’t to impress people with the report.

The goal is to help them use the information.

A dashboard can be beautiful.

It can have perfect spacing.

Great colors.

Clean charts.

Professional branding.

All of those matters.

But if leadership still doesn’t know what decision needs to be made...

We’ve created a very attractive problem.

😂

Pretty is nice.

Useful is better.

The Real Test

Here’s the test I would use.

Open your dashboard.

Don’t explain it.

Don’t give anyone a training session.

Don’t walk them through every filter.

Just let someone look at it.

Then ask:

” What do you see?”

Then ask:

” What would you do next?”

If they can answer those questions...

That’s a good sign.

If they immediately ask:

” What does this mean?”

You may have some work to do.

And if they ask:

” Can you put this into Excel?”

Well...

I’m sorry.

😂

What I’ve Learned in Operations

Throughout my career, I’ve learned that the best systems aren’t necessarily the most complicated ones.

They’re the ones people can actually use.

The same applies to dashboards.

A good dashboard doesn’t need to show everything.

It needs to show the **right things**.

It needs to make problems easier to see.

It needs to make trends easier to understand.

It needs to reduce questions instead of creating more of them.

And most importantly...

It needs to help people make decisions.

That’s what reporting should be about.

Not creating more work.

Not creating another meeting.

Not giving everyone another spreadsheet to maintain.

Making the work easier.

The Dashboard Shouldn’t Be the Star

This might be my favorite lesson of all.

A great dashboard shouldn’t be the star of the meeting.

The “decision” should be.

The dashboard is the supporting actor.

It gives you the information.

It points you toward the problem.

It helps you understand what changed.

Then it gets out of the way.

Because if everyone leaves the meeting talking about how impressive the dashboard looked...

But nobody knows what they’re going to do next...

We’ve missed the point.

😂

Sunday Reflection

So, as we wrap up this week’s dashboard conversations, here’s something I’d like you to think about.

Think about the dashboards you use at work.

Do they actually help you make decisions?

Or do you spend more time trying to figure out what the dashboard is trying to tell you?

Do you have a dashboard with:

📊 Too many charts?

🎯 A gauge for absolutely everything?

🌈 Fifteen different KPI colors?

🔍 Filters nobody understands?

📈 Charts that haven’t been used since 2021?

Or maybe...

A dashboard that requires a 30-minute Teams meeting before anyone can understand it?

😂

Maybe it’s time to ask a different question.

Not:

” What else can we add?”

But:

” What can we remove?”

Because sometimes...

The smartest dashboard isn’t the one that shows the most information.

It’s the one that helps someone look at the data and say:

” I know what we need to do.”

And honestly...

That’s the dashboard I’d want in my Monday morning meeting.

Question for you

Does your dashboard help people make decisions...

or does it just give everyone something to look at during the meeting?

I’d love to hear your thoughts.

And if your dashboard has more gauges than decisions...

We need to talk. 😂

#BehindTheWorkflow #SundayReflection #Dashboards #PowerBI #BusinessOperations #BusinessIntelligence #DataAnalytics #Reporting #DataVisualization #OperationalExcellence #ContinuousImprovement #Leadership #ProcessImprovement #Workflow #BusinessHumor #CorporateHumor

Hello, I’m Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

The Work Nobody Sees Behind a Good Dashboard

Microsoft Teams Meeting — 9:00 AM

Meeting Title: Dashboard Review

Organizer: Leadership

Attendees: Operations, Sales, Marketing, Projects, Finance, and the person who built the dashboard.

9:00 AM

Teams: Ding!

Melissa:

Good morning, everyone.

Can everyone hear me?

Sales:

Yes.

Marketing:

I can hear you.

Projects:

You’re muted.

Melissa:

I’m not muted.

Projects:

Oh.

Now I can hear you.

Melissa:

Perfect.

We’re off to a great start.

😂

Leadership:

Okay, everyone.

The reason for today’s meeting is to review the dashboard.

We want to make sure the numbers are accurate.

Melissa, can you share your screen?

Melissa:

Absolutely.

One second.

Melissa clicks Share.

Teams begins sharing the wrong window.

Melissa:

Apparently, Teams has decided we’re looking at my email today.

😂

Okay...

Let’s try that again.

9:04 AM

The dashboard finally appears.

Everyone goes quiet.

Leadership:

Okay.

I have a question.

Why does this number say 147?

Melissa:

Which number?

Leadership:

That one.

Melissa:

The 147?

Leadership:

Yes.

It doesn’t look right.

Melissa:

Okay.

That’s a good place to start.

9:06 AM — The Investigation Begins

Melissa:

Before we assume the dashboard is wrong...

Let’s look at where the number came from.

First, I’ll check the report.

The formula looks correct.

The measure is calculating correctly.

The filters look right.

The relationships look right.

So now I’m going to look at the source data.

Leadership:

Why?

Melissa:

Because dashboards don’t magically create numbers.

They report the information they’re given.

Sales:

So, you’re saying the data could be wrong?

Melissa:

I’m saying we should check.

That’s what operations does.

We investigate before we blame the dashboard.

😂

9:10 AM — Enter the Deliverables Board

Melissa:

Let’s look at the deliverables board.

Projects:

Oh.

Wait.

I see something.

Melissa:

What?

Projects:

There are two tasks for the same project.

Melissa:

Duplicate?

Projects:

Looks like it.

Leadership:

How did that happen?

Silence.

Projects:

Someone probably added it twice.

Melissa:

Okay.

That’s one issue.

Duplicate task.

9:12 AM : Another Problem Appears

Melissa:

Let’s keep going.

Wait.

Where did this task go?

Projects:

Which one?

Melissa:

The one that was supposed to be included in the report.

Projects:

I deleted that.

Melissa:

You deleted it?

Projects:

Yes.

It looked like a duplicate.

Melissa:

Did you check with anyone before deleting it?

Projects:

No.

Melissa:

Okay.

And there it is.

😂

Leadership:

So, we have duplicate records...

And deleted records?

Melissa:

Correct.

Leadership:

Is there a process for handling that?

Melissa pauses.

Melissa:

No.

There wasn’t.

9:15 AM: The Outreach Dashboard Appears

Melissa:

And here’s another thing.

We actually have two separate dashboards.

One is for deliverables.

The other is for outreach.

Because we had two different boards tracking the information.

Leadership:

Why are there two?

Melissa:

Because the information was being managed separately.

Leadership:

Couldn’t we just put everything into one dashboard?

Melissa:

We could.

But putting everything into one place doesn’t automatically make it easier to understand.

That’s actually how we got into some of these problems.

9:18 AM: The Great Dashboard Debate

Leadership:

I still think we should add more information.

Maybe sales.

And marketing.

And outreach.

And project status.

And client activity.

And maybe a few more KPIs.

Melissa:

We can.

But what question are we trying to answer?

Silence.

Leadership:

What do you mean?

Melissa:

What’s the purpose of the dashboard?

What do you need leadership to know when you open it?

Leadership:

Everything.

Melissa:

That’s not really a question.

😂

9:20 AM

Marketing:

Could we add another chart?

Sales:

I think we need a gauge.

Projects:

Can we add a table?

Leadership:

What about another KPI?

Melissa:

We can add all of those.

But here’s the problem.

If we keep adding things without deciding what the dashboard is supposed to accomplish...

We’re going to make the dashboard harder to understand.

Sales:

But more information is better.

Melissa:

Not always.

Sometimes more information is just...

More information.

😂

9:23 AM: The Monday Morning Complaint

Leadership:

That actually explains something.

Every Monday morning someone complains about the dashboard.

Melissa:

Exactly.

Leadership:

Why?

Melissa:

Because nobody really understood it.

People would open the dashboard and ask:

“Where did this number come from?”

“Why doesn’t this match the other report?”

“Why is this project missing?”

“Why are there two of these?”

“Why did that task disappear?”

“Why does this dashboard say one thing and the other dashboard say something else?”

And every Monday morning...

We’d have another discussion.

😂

9:26 AM: The Real Problem

Leadership:

So, what’s the actual problem?

Melissa:

The dashboard isn’t really the problem.

The process is.

We had people entering information differently.

We had duplicate records.

We had tasks being deleted without communication.

We had two separate boards.

We had different reporting needs.

And we didn’t have a clear process for maintaining the data.

The dashboard was simply showing us the results of all of that.

Leadership:

So, the dashboard was telling us the truth?

Melissa:

Exactly.

And nobody liked what it was saying.

😂

9:30 AM: The Operations Lesson

Melissa:

This is something I’ve learned throughout my career.

People usually see the finished product.

They see the dashboard.

They see the charts.

They see the colorful KPIs.

They see the polished report.

What they don’t see is everything that happens before that screen opens.

They don’t see the data cleanup.

They don’t see duplicate records being investigated.

They don’t see inconsistent names.

They don’t see missing information.

They don’t see broken relationships.

They don’t see formulas being tested.

They don’t see filters being checked.

They don’t see reports being compared.

And they definitely don’t see the hours spent asking:

“Where did this number come from?”

9:34 AM — The Detective Work

Sales:

So, what do you actually do when someone says the number is wrong?

Melissa:

I investigate.

I ask:

Did the formula change?

Did the data change?

Did someone add a duplicate?

Did someone delete something?

Did the source system change?

Did someone enter information differently?

Did a new process get introduced?

Was a filter left on?

Did one department change how they track something?

Those questions usually lead somewhere.

Because the dashboard is only the last stop in the process.

9:37 AM: The Realization

Leadership:

I think I understand now.

We were treating the dashboard like the problem.

But the dashboard was showing us problems happening upstream.

Melissa:

Exactly.

And that’s actually useful.

Because now we know where to look.

Projects:

So, we need a process.

Melissa:

Yes.

Sales:

And some rules around entering data.

Melissa:

Yes.

Marketing:

And maybe communication before someone deletes something.

Melissa:

Definitely yes.

😂

Leadership:

And maybe fewer charts?

Melissa smiles.

Melissa:

Now you’re speaking my language.

9:40 AM: The Meeting Ends

Leadership:

Okay.

Let’s summarize.

We need:

• Clear data-entry standards.

• A process for adding records.

• A process for deleting records.

• Communication when changes are made.

• Consistent naming.

• Clear ownership.

• A better understanding of what each dashboard is supposed to answer.

Anything else?

Melissa:

Yes.

Please don’t add another gauge.

Silence.

Sales:

I was actually going to suggest one.

Melissa:

I know.

😂

9:42 AM

Teams:

Meeting ended.

Melissa closes the laptop.

The dashboard is still sitting there.

Still showing the numbers.

Still waiting patiently.

It wasn’t broken.

It never was.

It was simply doing its job.

And that’s one of the biggest lessons I’ve learned in business operations.

A good dashboard doesn’t magically fix a bad process.

It exposes it.

The real work happens behind the screen.

In the data.

In the processes.

In the communication.

In the standards.

In the cleanup.

In the questions nobody wants to ask.

And sometimes...

In the Teams meeting that everyone thought was going to be a simple dashboard review.

😂

Because behind every “Why is this number wrong?”...

There’s usually a much bigger story.

Saturday Question

What’s the part of your job that happens completely behind the scenes...

But if you stopped doing it tomorrow, everyone would notice?

Is it:

📊 Cleaning up reports?

🗂️ Organizing data?

🔄 Maintaining workflows?

📝 Documenting processes?

🔍 Finding out why something isn’t working?

📧 Chasing people for missing information?

Or...

Something nobody even realizes you do?

I’d love to hear about the invisible work that keeps your organization running.

Because sometimes...

The work nobody sees is the work holding everything together.

#BehindTheWorkflow #SaturdayStory #BusinessOperations #PowerBI #Dashboards #DataAnalytics #Reporting #OperationalExcellence #ProcessImprovement #Workflow #BusinessIntelligence #Leadership #CorporateHumor #TeamsMeeting #BehindTheScenes

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Hello, I'm Melissa, the author of Behind the Workflow. Thank you for reading and supporting the newsletter! If you enjoy the content here, make sure to subscribe right here to LinkedIn or Substack so you never miss an issue, follow along on Instagram and Facebook, and check out my YouTube Channel for more operations breakdowns, tips, and corporate survival humor.

The conference room was quiet.

Too quiet.

There were about fifteen chairs arranged in a circle.

A coffee pot sat in the corner.

Someone had brought donuts.

Nobody knew who.

Probably Marketing.

Or HR.

Or maybe the person who created the dashboard.

On the wall was a handwritten sign:

DASHBOARD SUPPORT GROUP

Underneath it, someone had added:

“This is a safe space. No one is allowed to add another chart.”

😂

The moderator walked into the room carrying a clipboard.

They looked around.

“Welcome, everyone.”

“This is a safe space.”

“We’re here to talk about our dashboard problems.”

Silence.

Nobody moved.

Nobody made eye contact.

Finally...

One of the charts slowly raised its hand.

The Chart Speaks

Chart:

“I think there are too many of us.”

The moderator nodded.

“Can you explain?”

The chart looked around the room.

“There are seventeen of us.”

“Nobody knows what half of us mean.”

😂

The moderator looked at the other charts.

“Is this true?”

Another chart quietly nodded.

“I’ve been here for six months.”

“I still don’t know what I’m supposed to be showing.”

Another chart raised its hand.

“I was added because someone said...”

‘It would be nice to see this.’

The moderator frowned.

“And does anyone actually look at you?”

The chart paused.

“...No.”

“Then why are you still here?”

“I don’t know.”

😂

The moderator wrote something down.

Action item: Remove unnecessary charts.

The room gasped.

Apparently...

That was considered controversial.

The Gauge Has Something to Say

A gauge slowly raised its hand.

The moderator looked over.

“Yes?”

Gauge:

“I feel judged.”

The moderator leaned forward.

“Why?”

“Because everyone keeps asking me to show whether we’re on target.”

The moderator nodded.

“Okay...”

“And what’s wrong with that?”

“Nothing.”

The gauge looked down.

“I just don’t know why I’m on every single dashboard.”

😂

The room went silent.

Another gauge whispered:

“Same.”

A third gauge spoke up.

“I don’t even know what I’m measuring anymore.”

The moderator looked confused.

“What do you mean?”

The gauge sighed.

“Someone changed the target.”

“When?”

“I don’t know.”

“Who changed it?”

“I don’t know.”

“Why?”

“I definitely don’t know.”

😂

The moderator slowly closed the clipboard.

“Maybe we should talk about dashboard governance.”

Everyone stared at them.

Someone whispered:

“What’s governance?”

The moderator:

“Exactly.”

The KPI With an Identity Crisis

Next, a KPI raised its hand.

The moderator smiled.

“Go ahead.”

KPI:

“I have fourteen colors.”

The moderator blinked.

“Fourteen?”

“Yes.”

“Why?”

“I don’t know.”

“Who picked the colors?”

“I think someone thought it looked professional.”

😂

The KPI looked exhausted.

“Sometimes I’m green.”

“Sometimes I’m yellow.”

“Sometimes I’m red.”

“And sometimes I’m blue.”

The moderator asked:

“What does blue mean?”

The KPI shrugged.

“Honestly?”

“I have no idea.”

😂

Someone in the back of the room whispered:

“Blue probably means we’re doing really, really well.”

The moderator:

“Based on what?”

Silence.

The Filter Confesses

Then a filter slowly raised its hand.

The room immediately became uncomfortable.

The moderator looked over.

“What’s going on?”

The filter sighed.

“Nobody understands me.”

The moderator nodded sympathetically.

“Why?”

“Because someone forgot they left me on.”

Everyone gasped.

😂

The moderator leaned forward.

“How long?”

“Three days.”

“Three days?!”

“Yes.”

“And nobody noticed?”

“No.”

“What happened?”

The filter took a deep breath.

“Last month they thought the company had lost 40% of its customers.”

The moderator’s eyes widened.

“What actually happened?”

The filter looked embarrassed.

“They had simply filtered out half the data.”

😂

The entire room erupted.

One chart shouted:

“I KNEW IT!”

Another yelled:

“I’VE BEEN SAYING THIS FOR MONTHS!”

The moderator banged the clipboard on the table.

“Everyone calm down!”

Then they looked at the filter.

“Did anyone check the filter before blaming the dashboard?”

The filter shook its head.

“No.”

“Of course not.”

The Missing Data Problem

A table in the back of the room raised its hand.

The moderator nodded.

“Yes?”

Table:

“I have another problem.”

“What is it?”

“People keep changing me.”

The moderator looked concerned.

“How?”

“Someone adds records.”

“Someone else changes them.”

“Someone creates duplicates.”

“And then someone deletes something they shouldn’t have.”

The room went silent.

The table continued.

“And then everyone asks why the dashboard numbers changed.”

😂

The moderator slowly nodded.

“So you’re saying...”

“The dashboard isn’t necessarily the problem.”

“Exactly.”

The table looked relieved.

“Thank you.”

“I’ve been trying to tell them.”

The Dashboard Finally Speaks

The moderator looked around the room.

“Does anyone else have anything they’d like to share?”

Silence.

Then...

The dashboard itself raised its hand.

Everyone turned.

The moderator smiled.

“Of course.”

“Go ahead.”

The dashboard took a deep breath.

“Can I say something?”

“Absolutely.”

The dashboard looked around the room.

“I don’t need another chart.”

Silence.

“I don’t need another color.”

Silence.

“I don’t need another gauge.”

The gauge looked offended.

“Sorry.”

The dashboard continued.

“I need a purpose.”

The room went completely silent.

The moderator slowly put down the clipboard.

“That’s probably the most important thing anyone has said today.”

The Operations Person Walks In

Suddenly...

The door opens.

In walks an operations professional.

Coffee in one hand.

Laptop in the other.

They look around the room.

“What’s going on?”

The moderator points to the dashboard.

“It says it needs a purpose.”

The operations professional nods.

“Good.”

Everyone looks confused.

The operations professional walks to the whiteboard.

“Let’s start with one question.”

“What is this dashboard supposed to help someone understand?”

Nobody answers.

They ask again.

“What decision is this dashboard supposed to help someone make?”

Silence.

“Who is actually using it?”

More silence.

“When someone opens it, what should they know within the first thirty seconds?”

Nothing.

The operations professional puts the marker down.

“Okay.”

“We found the problem.”

The moderator nods.

“We need another support group.”

😂

The Real Problem with Dashboards

I’ve seen this happen during my years working in business operations.

Someone wants a dashboard.

So you build one.

Then someone wants another metric.

So you add it.

Someone wants another chart.

You add that too.

Then someone says:

“Can we also track this?”

Sure.

Then:

“Can we add a filter?”

Okay.

Then:

“What about a gauge?”

Here we go again.

😂

Before you know it...

The dashboard has become a digital junk drawer.

Everything is in there.

Nothing is easy to find.

And nobody is completely sure what anything means.

Sometimes the Dashboard Needs a Process

One of the biggest lessons I learned in operations is that a dashboard can’t fix a process that doesn’t exist.

If people aren’t entering information consistently...

The dashboard can’t magically fix it.

If people are creating duplicate records...

The dashboard will count them.

If someone deletes a task...

The dashboard may reflect that deletion.

If nobody knows who owns the data...

The dashboard is going to have problems.

And if leadership keeps asking for more information without deciding what information actually matters...

You eventually end up with seventeen charts, fourteen KPIs, nine filters, six gauges...

And one very confused audience.

😂

The Support Group’s Final Session

The moderator looks around the room.

“Before we leave, I want everyone to remember something.”

“Your dashboard isn’t supposed to impress people.”

“It’s supposed to help them.”

The charts nod.

The KPI stops changing colors.

The gauges look relieved.

The filter promises to announce when it’s turned on.

The table agrees to stop accepting duplicate records.

And the dashboard?

It finally looks peaceful.

😂

The moderator smiles.

“Same time next Friday?”

The dashboard raises its hand.

“Can we meet somewhere without Power BI?”

The moderator laughs.

“Absolutely.”

Friday Fun

If your dashboard could complain about one thing, what would it say?

Would it be:

📊 “STOP ADDING CHARTS.”

🎯 “Please remove that gauge.”

🔍 “CHECK THE FILTER!”

🗑️ “Stop deleting my data!”

🌈 “I don’t need fourteen colors.”

📋 “Can someone please tell me what I’m actually supposed to do?”

Or maybe...

“I don’t know what I’m supposed to be doing either.”

😂

Tell me your dashboard horror stories.

Because after years in business operations, I’ve learned one thing:

If you think your dashboard is the only one that needs therapy...

It isn’t.

Somewhere out there...

There’s a dashboard sitting in a conference room right now...

Wondering why someone just added another gauge.

😂

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