Unexpected productivity discoveries
Konnichiwa. Welcome to the AI Automation Dojo, where we stare into the abyss of the modern workplace and the abyss stares back with a calendar full of back-to-back meetings. Today we’re asking a simple question: What if everything you thought about your company’s productivity was wrong? And now that you can see the truth, are you brave enough to look at it without flinching?
I’m your host, Andrzej Kinastowski, one of the founders of Office Samurai, but this episode will be led by Zuzanna Pamuła, our Process Transformation Manager, who will dive even deeper into the productivity mind. She will move us past the age of suggestion boxes and how-do-you-feel-about-your-workflow surveys into an era of cold, hard facts. So, whether you’re a manager wondering why your team is always busy but never done, or an employee who knows the real process involves three legacy systems, a personal spreadsheet and a prayer, hula buccia, you’re in the right place. Now, grab your favourite katana, or the courage to open your screen-timing pod, and let’s get to it.
Hi, konnichiwa. My name is Zuzanna Pamuła, and in Office Samurai I am responsible for process improvement and business analysis areas. Earlier, for 12 years, I have worked in shared services centres of big international organisations, where I was responsible for Continuous Improvement, programmes management, business analysis, and staff upskilling in Lean Six Sigma topics. Today, I would like to share with you part of my story. When I first began working as a process improvement specialist, I thought measurement was easy.
The illusion of simple data
You have enterprise systems and applications that can provide you with lots of data. Categories and volumes of requests, split by region, type of customer, requests cyclicity. Sometimes you could find there also quality data, like accuracy or customer satisfaction.
For a young analyst, it was like a new playground for my kindergarten kids. But very quickly I realised that this data was very limited, and insights you can derive from it will not show us the whole picture of the process being performed.
How much do people actually work? How they use their tools? What are the process variants and where are the bottlenecks? How much time do particular activities take? I didn’t have answers for those questions, and suddenly felt like the kid that realised the swing does not have a seat, there is a cat’s poop in the sandbox, and some mean kids are occupying the slide, not allowing anyone else to enjoy it.
The human factor and resistance to measurement
Luckily for me, same questions were appearing also in heads of my bosses. In practice, it meant we actually got the mandate to bother teams in order to gather more data. I was really looking into this kind of a lean project, and it also was supposed to be an interesting experience.
You observe the process, map it, collect the time-related data, can really dive into it, play with different analyses, where you identify things that can run faster or cheaper. For a fresh black belt, it is a dream task, right?. But very quickly I learned that measurement is never simple, because behind every process there are people with their fears and totally natural resistance. Behind every number there are behaviours and biases, and behind every assumption there are exceptions.
I vividly remember the first big project. We spent lots of hours planning the exercise. We interviewed team leaders, we held workshops where people had to fill in their daily tasks, we designed and distributed really smart Excel templates.
The result? A very polished report that looked great in PowerPoint. But when we tried to implement improvements, the results were not really satisfying. Why? Because the report was based on how people said they worked, not how they actually worked.
Those gaps were coming from people being uncertain how the results will be used and what are potential consequences for them. Those reservations were voiced or silently endured, both by operational people, but also by their managers. People had fears that exposing the truth about reality of their work would show some kind of incompetence.
And I strongly believe that when people work inefficiently, it is extremely rarely caused by their bad will. Come on, they really don’t want to sabotage the company. It’s because they have inefficient tools, badly designed processes, or have received poor knowledge transfer.
Traditional measurement struggles
I have been hearing this like a mantra, repeated by everyone for those 12 years: Business processes are not like a factory processes. You cannot measure them accurately, calculate averages or even medians, not to mention lead times, cycle times, stack times, because every case is unique.
But is it? Well, to be honest, when you think about standard, old-school measurement methods, this is maybe not impossible, but really tough. And back in the days, we used to perform measurements through shadowing sessions. I was literally sitting next to a person working on the process, with a notebook on my lap, pen in one hand, and stopwatch in the other.
I didn’t have a laptop yet. The clue was in good quality of notes and quickly transferring them into some digital format, so it doesn’t get mixed up with my thoughts from three other observations I had that day.
On another project, we decided to rely on the employees’ input. So we prepared a bulletproof Excel template for them to capture the data. Of course, we didn’t predict people’s creative invention and capability to ruin preset formulas and formatting. And these were soul-sucking hours, or maybe days, that I then needed to spend making sense of the data, the inputs, and normalizing it.
An unexpected, let’s say, discovery was that all those measurements were surprisingly round and always adding up to eight hours a day. Amazing, right?.
Then, on my third attempt of this kind of project, my manager came up with an idea to have an Excel tool with VBA macros that will allow people to select a task from the drop-down list, click Start, and then Stop buttons, and the record will be done automatically. No manual manipulation, no rounded numbers, times corresponding to the reality.
In theory, it sounded great. But there we had so-called human factor, meaning people forgetting to click one or the other button, which made the measurements, again, unreliable, and Process Excellence team a hidden factory to edit those faulty records in the database. Back then, I was nearly certain that uncovering the reality of the processes is incredibly difficult.
Every attempt will be flawed, and the measurements will give us only a vague idea on what is most time-consuming, where people waste their time, waiting or reworking, how is the workload distributed, and what are the best areas to identify improvement opportunities. We had lots of data, but those were never complete nor reliable. And during my corporate career, those measurement efforts were being repeated with some frequency, funnily correlating to new strategies and objectives announcements or some managerial courses.
The need for a new measurement strategy
Each time I heard this request coming, I wanted to cite the classic. I am sure you know this one. Albert Einstein supposedly said that insanity is doing the same thing over and over again and expecting different results. This sentence really gets to me. However, fun fact is, it is wrongly attributed to Einstein.
Therefore, let me cite another classical thinker, Harvey Specter, from the suits: Don’t be upset with the results you didn’t get from the work you didn’t do.
The question becomes, what do we really want to measure? And how to do that?. Do we want to know how much time is spent on emails? On customer interactions? And which customers and regions are the high need ones and which are low maintenance? How to quantify it?. Then, how much work is done within systems that are supposed to support us, but often slow us down? So we need to create workarounds. In Excel, of course.
Do we want to know how the workload is distributed? Who is drowning in tasks? And who has time to spare?. Or maybe we want to know which areas are the best candidates for improvement, where we will get the biggest return for the effort. Can we estimate it? For years, these were educated guesses. But then, new technologies arrived. And suddenly, we could move from guesses to facts. Think about process mining or task mining tools. In previous episodes, my colleagues told you about productivity intelligence tool, KYP AI.
What it gives us is essentially an X-ray of work. Instead of relying on people’s memory, on their perception of how they work, we can now see the reality. We can see the flow of activities across systems, across teams, across entire organizations.
This is where the magic and sometimes the discomfort happens. Because the data shows us things we didn’t expect. Or maybe we suspected them, but we didn’t want to admit it.
Unexpected findings and the illusion of productivity
That’s why I call them the unexpected findings. Now, let’s play a game. Imagine you had this technology running in your company.
Imagine you could see every click, every system interaction, every break, every task switch. What do you think you would discover?. Would you discover that people spent most of their time passively on the meetings? Or maybe would you see that during those meetings, half of them are secretly catching up on emails?. Would you notice how many hours are swallowed by discussions that really don’t move the needle?.
Where people are most productive? At home or in the office? Which setup supports better results? Do they really need to get back to the office for four days a week?. Or would you find something more personal? Like parents leaving early to take their child to the game or to the doctor? Employees blending work with personal life because flexibility is part of survival in today’s world. And then there is the bigger question.
How is each individual working? Are they genuinely engaged? Are they overworked? Or are they just trying to look busy? This leads us to one of the most uncomfortable findings: Illusions of productivity. Let’s be honest.
People have always tried to look busier than they are. In pre-COVID times, when most of us worked in the offices, the trick was to rush through the corridors and staircases, carrying your laptop or notebook, pretending to be heading to a meeting. Then, during home office era, you could just put some heavy object on your keyboard, open text editor, and simply prepare your lunch or do the laundry, appearing still green on your company communicator.
You could also give your computer mouse to the cat or place it in your hamster’s wheel. Or attach it to the running Roomba robot, swiping your house clean. That is technology-supported multitasking, right?. Now, computer technology has given new tools for that pretending.
The famous mouse jigglers that keep your computer awake. Auto-clickers that simulate activity. Now, here is the twist.
All those old-school and new hacks may be invisible to the managers. They may be even invisible to your IT. But they are not invisible to productivity intelligence tools.
Because the AI-powered systems see patterns. They know when clicks don’t lead to any outcomes. They know when motion doesn’t equal progress.
It’s uncomfortable, but it’s real. And if we don’t confront it, we can improve. Not all findings are about deception. Many are simply about being human. Take shopping, paying your bills, planning your next holiday. Even some entertainment, like social media or online games.
All of this happens during working hours. But maybe it is a short distraction after long focus time or binge-solving client tickets. Evenings spent watching Netflix series.
If it happens after hours, this is fine, right?. But what are your corporate rules about using computer? Some might say it’s wrong. Others might say it’s just balance. But the point is, it’s real.
Productivity intelligence is not about monitoring those activities and punishing people. It should be set up in a way the so-called private applications are invisible to it and no such data is being gathered. It is about understanding how much time it takes to do the job.
Common enterprise productivity viruses
There are patterns that I have observed in every big enterprise I worked for earlier or work with now. I think those won’t be a big surprise for you. But the question is, are they productive and adding value in the process?. Because those patterns, in a big scale, are like viruses. Like diseases that consume an organism preventing it from performing at its optimum.
First one is meetinguria. The endless stream of meetings that makes you wonder when am I actually supposed to do my job?. Some of those meetings could have been an email.
Some will make sense with only half of the audience. And the rest was anyway checking emails or unpacking dishwasher. Waking up only when hearing their name being called.
Some of those meetings just lacked a proper facilitation, agenda or follow-ups. But this is also an opportunity.
Then we have inboxitis. Overload of emails. Including 15 people in the email thread, just in case. Endless chains of communication that actually could have been a status meeting or a phone call. But also the compulsive need to refresh the inbox. The dopamine hit of a new message, even if it’s irrelevant.
Lastly, tool fragmentation disorder. Using so many different tools and systems that switching between them and reconciling becomes its own full-time job. Individually, each of these may seem small. But together they create the lived reality of work. They shape how much we achieve or fail to achieve every day.
This is what I love about data from the tools like KYP. It gives us diagnostics.
Seeing the truth and driving change
Not the sanitized version of the process. Not the official flowchart on the wall. But the actual truth. The messy, unfiltered, sometimes shocking truth of how work gets done. And when you see that, you can’t unsee it. Suddenly, you realize that the biggest barrier to productivity isn’t laziness. It’s the structures we have built. The meetings we’ve normalized. The tools we have scattered across the digital workplace.
The culture that makes people stay late or use the mouse jigglers. Not because they have to, but because they want to be seen as committed.
And once you have this knowledge, the question becomes, what are your priorities?. Do you start by reducing meetings? Do you consolidate tools? Apply bots as a patch? Do you work on cultural change? Giving people permission to rest, not to finish the report on the weekend? To not measure their worth by the number of hours they are online. These are real choices that leaders have to make.
For process specialists like me, for black belts, this is a revolution. Because it means we no longer have to rely on theory. We don’t have to say, this is how the process should work. We can now say, this is how the process actually works. We don’t have time to argue with opinions.
We can put the data straight on the table. We can show where value is created and where time is wasted. We can prove which changes will make a difference and which ones are just window dressing. That’s the real power of these unexpected findings. They may make you uncomfortable. They may make you laugh. They may even make you defensive. But once you have seen them, you can’t go back. So let me leave you with this thought.
Every organization has a story. It tells itself about how it works. A story of dedicated employees, efficient processes and clear priorities. But the data often tells a different story. One of multitasking, distractions and illusions of productivity. One of time wasted in the meetings, on emails, on unreliable tools.
One of people doing their best but fighting against systems that don’t always support them. The question is, which story are you willing to believe?. And what will you do once you see the truth?. Because in the end, the unexpected findings are not just about measurement. They are about change. They are about making work not only more productive but also more human. And if we use the tools wisely, we can do exactly that. Thank you.
And that’s a wrap on this particular therapy session for the modern web news. It’s official. We are all living in a productivity illusion. We did this episode in cooperation with KYPAI, our first choice for productivity mining. Huge thanks to our guest, Zuzanna Pamuła, for being our guide and showing us that data, like a good friend, will tell you the uncomfortable truths you need to hear. And a huge thank you to Anna Cubal, our producer, who keeps the chaos of this podcast confined to a carefully crafted plan. Recorded in the hallowed halls of Wodzu Beats Studio, our own little sandbox environment. If you liked what you heard, tell your friends. And if you hated it, tell that one colleague who schedules meetings for 4.30 p.m. on a Friday. Your thoughts, a desperate plea for us to explain how to escape your own inboxitis, drop us a line. We love hearing from you. Until next time, remember that every company has a story about how it works. The question is, are you ready to read the chapter your data just wrote? Mata ne!
