Pawel Brodzinski on Leadership in Technology

Whatever it takes to lead a team, build a product, and run a business

Tag: continuous improvement

Why We Fail to Change

I’d love to get a beer each time I hear a story about management imposing a change on teams and facing strong resistance. Literally every time I’d fancy one, I’d be like, “Hey, tell me your agile transformation story.”

One common excuse is that people don’t like the change. That is surprising given how adaptable humankind has proven to be. I’d rather subscribe to the idea that people don’t mind the change; they don’t like being changed.

Unfortunately, being changed part is the story of oh so many improvement initiatives. And Agile implementations, obviously, are among the most prominent examples of these change programs, of course.

So, how is it really with responding to changes?

First, it really helps to understand typical patterns of introducing change. The model I find very relevant in this context is Virginia Satir’s Change Model. Let me walk you through it.

We start with the existing status quo, which translates to a performance level. We then introduce a new concept, which we call a foreign element.

Then we observe an expected improvement, and they lived happily ever after and all. Well, not really. In fact, whenever I draw that part of the model and ask what happens next, people intuitively give pretty good answers.

After introducing a change, performance drops.

It is kind of obvious. We need time to learn how to handle a new tool, practice, or method. Eventually, we become increasingly proficient at whatever that is, and we start to see the results of the promised improvements. Finally, we internalize the change, and the cycle is finished.

Because of its shape, the curve is called a J-curve.

It is an idealized picture, though. In reality, it is never such a nice curve.

What we really see is something much bumpier. It isn’t a straight line to start with, when we maintain the old status quo. Then, it gets way more all over the place when we start messing with stuff. It’s not only that the rough average deteriorates, but also that the worst-case scenario gets worse, and by much more.

It’s pretty much chaos. In fact, that’s exactly how this phase is called in Virginia Satir’s original model.

An interesting observation we can make is that the phase called resistance is a short one that occurs just after introducing a foreign element. Does it mean that we should expect resistance against the change to be short-lived?

Yes and no. Yes, if we consider only the “I’m not even going to try that new crap” type of resistance. This kind of reaction is typically driven by a lack of understanding of why the whole change was proposed in the first place. There is, however, a whole range of behaviors that happen later in the process that we would commonly call resistance as well.

Some people aren’t ready to see even a temporary drop in performance. Once they face it, they suggest a retreat to the old status quo. When facing a stressful situation, many people instinctively go back to what they know best. Unsurprisingly, the old way of doing things is precisely what they know best.

There are also those who are impatient and not willing to give people enough time to learn the ropes. Curiously enough, the last group often includes managers who initially funded the change.

In either case, the result is the same in the end. More resistance.

Inevitably, we reach a pivotal moment. We’ve been through the bumpy ride for quite some time already, and yet we haven’t gotten better. In fact, we’ve gotten worse. Not only that. We’ve gotten worse and less predictable. The whole change doesn’t seem like such a good idea after all.

So what do we do?

Of course, we reverse the change and go back to the old status quo. Oh, and we fire or at least demote that bastard who tricked us into starting the whole thing.

One interesting caveat of the whole process is that a change is not always simply reversible. When we change specific behaviors and yet don’t get the expected outcomes, reverting to the old status quo may be difficult, if not impossible.

For the sake of the discussion, let’s assume we are lucky and the change can be reversed. We are back to old ways of doing things, and we simply wasted some time trying something new. Oh, and we built a stronger case for resisting the next change. We petrified the existing situation just a little bit more.

One reason changes are often reverted is the perceived risk associated with them.

A pretty good proxy for perceived risk is predictability. Typically, the more unpredictable a team or process is, the riskier it is considered. In this case, the important thing that comes along with a foreign factor is how much predictability changes. Not only does performance drop, but it also becomes much less predictable.

While the former alone might have been bearable, the combination of both factors contributes to the perception that the change was wrong in the first place.

There is another dimension that is particularly interesting here. It is the scale of change. How much we change the existing environment: team, process, practices, etc.

We can imagine a series of small improvements, each modifying the context only slightly. The entire series of them leads to a similar outcome as one big change rolled out at once.

We can describe one approach as evolutionary and the other as revolutionary. If we draw inspiration from Lean, we’d call them Kaizen and Kaikaku, respectively.

Fundamentally, the J-curve in both approaches would be shaped the same. The big difference is the scale. The revolutionary change means one big leap and rolling out all the new stuff simultaneously. This means a single big J-curve.

The evolutionary approach introduces a lot of tiny J-curves one after the other. In fact, it is possible to have a few changes run concurrently, but let’s not complicate the picture any more.

What are the implications?

Let’s go back to the scale of the risk we undertake. With Kaikaku, the unpredictability we introduce is much higher than what we’ve seen in the late status quo.

Kaizen, on the other hand, typically suggests changes that are small enough to avoid destabilizing the system nearly as much. It is pretty likely that unpredictability introduced by each of the small changes will be almost invisible, given that we don’t deal with a fully predictable process anyway.

The risks we take with an evolutionary approach are much more acceptable than those we face when rolling out a single, large change.

That’s not all, though.

Another consideration is the duration of the destabilization. In other words, the cycle time of change.

A big change, naturally, has a much longer cycle time, as it requires people to internalize many more new behaviors, practices, techniques, etc. It means that exposure to the risks is longer. Given that the risks are also more significant, it raises the odds that the change will be reverted before we see its positive results.

With small changes, cycle time is shorter and so is exposure to risks. Again, not only are the risks much smaller, but they are also mitigated much faster.

One last thing worth mentioning here is that, so far, we optimistically assumed that all the proposed improvements have a positive outcome. That’s not true.

With the evolutionary approach, even if some of the changes don’t yield expected results, we still gain from introducing others. With a revolutionary approach, each part that doesn’t work simply increases the likelihood of reverting the whole thing altogether.

It is not to say that Kaizen is always superior to Kaikaku. Both evolutionary and revolutionary approaches have their place. We need Stuart Kauffman’s Fitness Landscape to explain that.

Imagine a landscape that roughly indicates how fit for purpose your organization is. It should simply translate to factors such as productivity, responsiveness to the changing business environment, etc. The higher you are, the better.

The simplest and safest way to climb up is to take small steps uphill.

While the approach works very well, eventually we reach a local peak. If we continue our small steps in any direction, it would result in lower fitness for purpose. Simply said, we wouldn’t perform as well as we did at the peak.

If we look only at the closest terrain, we might as well say that we’re already perfect and there’s no need to go further.

Obviously, that would be naive. Or stupid. Or both.

The solution becomes apparent when we take a broader view. If we moved to the slope of another hill, we could eventually reach even a better position.

That’s exactly when we need a big jump. It doesn’t have to automatically land us in a better situation than the one we were initially in. The opposite would often be the case. What is important, though, is that we land on the hill that is higher. That translates to bigger potential for improvement.

Once there, we can retreat back to the good old strategy of small steps that allow us to climb up. Eventually, we reach the peak that is higher than the previous one. Then we can repeat the cycle by looking for even a bigger hill.

Similarly, to the case of J-curves, the picture here is idealistic, suggesting that each change, whether small or large, is considered successful. In reality, it is more the result of experimentation. Some of the changes would work, while others would not.

As you might have guessed, small steps here represent the evolutionary approach or Kaizen. A big jump is equivalent to revolutionary change or Kaikaku. Depending on the context, one or the other will be more useful.

In fact, there are situations when one of the strategies will be basically useless. That’s why introducing change without understanding the current context is simply begging for failure.

One more implication of the picture is that, given the lack of any other guidance, the evolutionary approach is both less risky and more likely to succeed. That’s why I prefer to start with Kaizen when I’m unsure about the context within which I’m operating.

One last remark on Fitness Landscape. What you’ve seen here is a heavily oversimplified view. In reality fitness landscape wouldn’t be two-dimensional. Stuart Kauffman discussed it as a three-dimensional model, although I tend to think of it as a multi-dimensional one.

It means that each change can improve our situation in some dimensions and have an opposite result in others (think: we’ve improved quality, but we are slower). We will have different combinations of effects in different dimensions—some more desirable and some less.

If that wasn’t enough, the entire landscape is dynamic and continually changes over time. In other words, even after reaching a local optimum, we will need further continuous improvements simply to maintain our fitness for purpose. The peak will be moving over time.

I know the post got long by now (thanks for bearing with me that far, by the way). This, however, is only a starting point for discussing why introducing the change often triggers resistance.

I believe it provides a pretty good explanation of why so many improvement initiatives fail. This is also one of my answers to the question of why many Agile adoptions are doomed to fail from day one.

Attempting to significantly change an organization without understanding its underlying mechanisms is simply begging for frustration and failure.

Finally, understanding the change models will influence the choice of the methods and tools we’d use to drive our change programs.

And if you chose a journey of a change agent, good luck! It can be as challenging as it can be rewarding.

February 24, 2015
A Fool With a Tool Is Still a Fool

When I first discovered how Kanban in general, and Work In Progress limits specifically, worked as a catalyst for deep systemic improvements it was like an epiphany. Kanban, which at the beginning seemed like a neat and light-weight process management tool, proved to be far more than that. Not only was it helping to clean up the mess short term but also steered sustainable changes in the long run.

When Tools Fail

These were my early days with Kanban. Since then I’ve seen a lot of teams applying Kanban in all sort of ways. A thing that surprised me was that, even among the teams that achieved a certain level of maturity of the adoption, the results were mixed at best.

Some of these teams are doing great and the early results I’ve seen no longer stand as exceptional. Most of them though weren’t even close. Clearly the magic of WIP limits that induce slack time, which in turn results in a steady stream of sustainable improvements, is neither obvious nor granted. There has to be something else.

No curious person, and I tend to consider myself one, would pass on this observation without a second thought. No reasonable person, and I tend to consider myself one, would keep sharing the success stories ignoring all the counterexamples.

Of course, one obvious reaction would be that the teams that failed to achieve exceptional results got it wrong. In fact, if you want to look for such attitudes among our thought-leaders it is pretty common. The method works, only those unskilled folks mishandled it, they’d say. No wonder these teams still crawl in the misery, they’d add. Actually, they sort of deserved it by not doing the thing the way we preached, the thought-leaders would sum up.

Fortunately I’m not a consultant or an owner of a business that depends on popularity of a specific approach. I consciously chose to stay in practitioners’ camp. This leaves me with no neat and simple (and wrong) answer to the puzzle.

A nice thing is that, given enough experience, we will stumble upon such puzzles on and on. Gemba walk which seems to be mentioned in every other important management book from The Goal to Lean Startup was another such realization for me. Failed stories of applying Kaizen boards and holding Kaizen evens was one more. Organizations struggling with Improvement Katas is probably the most recent one but the list goes on.

Cargo Cult

A cargo cult is, in short, defined as mechanically following practices or rituals without understanding why they worked in the first place and expecting the same results as achieved originally. In case you wondered it doesn’t really do miracles. In fact, the only known successes are creating prophets of cargo cults.

A common observation, and a sad one, is that our efforts with applying different methods are surprisingly close to that definition. Even worse, such attitude is often encouraged. By the book applications of any tool means spreading the disease. It is like saying that we need to trust an enlightened prophet who guarantees two-, three- or fourfold productivity increase as long as we do exactly as they say.

Don’t get me wrong the other end of spectrum, which is NIH syndrome, is equally bad. If NIH syndrome was a good guidance it would mean that entire management knowledge is useless because no one in the world was exactly in the context such as ours.

In either case the missing bit is understanding the underlying principles behind the tools. One exercise I typically start my Kanban training with is asking a group about practices and principles. While they always know a few practices, sometimes most or even all of them, almost no one remembers any of the principles.

By the way, the same thing is true when it comes to Agile Manifesto. Everyone knows “this over that” part but most of the time that’s pretty much it. It seems like we haven’t understood what we read. Alternatively, we never read that thing at all but heard about it somewhere where they used only the marketing part of the manifesto on a slide.

It is kind of like knowing how but having no clue whatsoever why we’re doing something. And then we wonder why we fail so frequently.

Understanding

I know that belief in universal solutions has certain appeal. It doesn’t require us do to the hard work of trying to understand what is happening around. I don’t think there’s a shortcut here though. I mean one can get lucky, as I did during my early adventures with Kanban, but this experience can’t be easily translated to different contexts.

Now, certain techniques give us a promise of help in facilitating the understanding how we work. Visualization and Gemba walks come as obvious examples. However, before we rush to apply them we may want to ask ourselves a question do we understand how and why these techniques work. Seriously. Even something seemingly so straightforward as visualization may be a waste unless a team understands that one of its biggest powers is reflecting current condition and current process and not projecting an expected state, or that too much burden on keeping it up to date will render it irrelevant, or that that too many objects on a board makes it incomprehensible and, as such, pretty much useless.

I think the most common practice across all agile teams I know, no matter which method, if any, they follow, is a daily standup meeting. I believe I can safely assume that vast majority of agile teams have their daily standups. Now, how many of them asked themselves why they are doing that? Why are standups a part of a canon of Agile and Lean? Why were they introduced in the first place? And why, the hell, are they so prevalent?

It doesn’t seem to bug many people. That’s interesting because they may be just following a cargo cult and maybe they could have been doing something much more useful in their context.

Take pretty much any popular practice, technique or method. The same story again. We don’t understand why the tools we use work and simply blindly apply them. Doesn’t that fulfill a definition of a cargo cult?

By the way, I think that one of significant contributors to the situation we have here is pretty common perception that Shu-Ha-Ri model universally applies in our context. A basic assumption that when being on Shu (apprentice) level we should do as a master say because we are incapable of understanding what we are learning doesn’t seem to be an extremely optimistic view of our teams.

Call me lucky but most the time I worked with teams that are perfectly capable of better understanding how the work gets done and how specific tools contribute in that. The missing bit was either knowledge itself or curiosity to get that knowledge.

A side note: the higher up we go through hierarchy the less of that curiosity I see, but that’s a bit different story. Most of time talking about tools we are in the context of teams, not VPs and execs.

A Fool With a Tool is Still a Fool

Any time a discussion goes toward tools, any tools really, it’s a good idea to challenge the understanding of a tool itself and principles behind its successes. Without that shared success stories bear little value in other contexts, thus end result of applying the same tools will frequently result in yet another case of a cargo cult. While it may be good for training and consulting businesses (aka prophets) it won’t help to improve our organizations.

A fool with a tool will remain a fool, only more dangerous since now they’re armed.

Not to mention that I don’t think orthodoxy is anyhow helpful in this discussion.

By the way: as much as I didn’t want to engage the recent TDD versus anti-TDD discussion you may treat it as my take on it.

May 18, 2014
Why Your Change Program Will Fail

Most change initiatives fail. How many of them? Well, let’s see.

In 1995, John Kotter published research that revealed only 30 percent of change programs are successful. Fast forward to 2008. A recent McKinsey & Company survey of business executives indicates that the percent of change programs that are a success today is… still 30%

This is from a McKinsey report. How about different sources?

According to international management consultants Bain & Co, 70 to 90 per cent of organizational change initiatives fail.

Now, obviously these statistics receive some criticism. After all, what is a change initiative? What is a success? My point is that what we see is that in different context we suck big time at improving how we work.

What’s more we are not improving really. Over the course of past 15 years we’ve seen a huge rise of the methods and approaches that are specifically aimed toward driving the change management.

Agile proposed a neat value container quickly filled with specific methods that should change and improve the way we work. Lean offered a thinking pattern focused on continuous improvements. Both are more and more frequently considered table stakes than game changers. Why nothing is changing then?

First, let me make a bold observation: neither Agile nor Lean seem to be making a difference. In fact, that’s not only my observation. Daniel Mezick points that:

If current approaches actually worked well, then by now, thousands of organizations would have reached a state of self-sustaining, “freestanding” agility.

We have to be doing something wrong. Dave Nicolette offers some ideas what that might be. Anyway with such a wild popularity of Agile and Lean we should expect to do better than that. The problem is that most of the time we don’t even try to understand what made them work in the first place.

That’s a sad observation, but most of the time when I hear an Agile or Lean experience report it simply covers methods, practices and tools. The problem is that neither of these is pivotal in any change initiative. Basically, adopting practices and tools is simply a cargo cult. That’s not going to work unless there’s something more, the same way as it didn’t work for the Pacific tribes after the World War II.

In agile context we often mention values as the missing bit. I sort of agree with that. Sort of because the way Agile Manifesto is formulated it creates false dichotomies, yet it points us the right direction.

There’s a problem with values though. You don’t introduce values simply stating that you have them. You don’t incept them through mission statements and stuff. By the way, do any of you know value statement of your org by heart? Values are derivative of everyone’s behaviors and attitudes, thus they are a result of organizational culture.

There’s one more layer to that. Values can’t be inconsistent with the culture. Otherwise authenticity is gone and your claims about values have little to do with reality.

In other words a company can’t adopt Agile Manifesto simply by stating so. Not a surprise that change initiatives around Agile so frequently boil down to methods and tools. Not a surprise they fail at a high rate.

We see the same story with Lean as well. The bits that get traction are tools and techniques. It is so often when I see teams acting like limiting work in process, doing Gemba walks and having Kaizen boards was everything there was to improve continuously.

It’s not going to fly, sorry. We are back to organizational culture and everyone’s everyday behaviors. What do people do when they see an issue? Do they feel empowered to do whatever the hell they believe is the right thing to do to fix that issue? Do they even know what is the ultimate value they produce so they get good guidance on what is an issue in the first place?

These behaviors tell a lot about the culture. Unfortunately most of the time answers for the questions above suggest that there’s no freaking chance to make the tools work the way we intend them to. Typically we see over-constrained, siloed organizations where one neither knows what is the right thing to do nor has courage to go beyond the constraints.

I keep getting flak for bringing this up over and over again but I will do it once more.

It’s easier to ask forgiveness than it is to get permission.

Grace Hopper

Grace Hopper’s famous words are, in my opinion, the essence of the bit we are missing when introducing Lean or Agile to our organizations. That very bit is responsible for the appalling rate of success of change initiatives.

You can have all the hot tools and practices in place but when your people are driven by fear of consequences of their actions nothing will change. “Fear” may sound harsh but that’s what it is. It doesn’t mean that changing status quo by a tiny bit scares the crap out of me. It’s enough that I start thinking about potential consequences, what my bosses would think about that and whether they would even be happy. This is fear too.

When I think about the situation from a perspective of my experience as a manager I’m not surprised. I mean, really, promoting this whole “don’t ask permission” attitude is going to backfire on you on occasions. What’s more it means giving up control. Even worse, it assumes trust. It assumes trust to everyone, not only to few trusted people. Now, this is a huge leap of faith management has to take.

If you are thinking about continuous improvement or making your change initiatives work start with this leap of faith. If you can’t make it work don’t bother with all the tools, methods, practices and stuff. It’ll be just a waste of time. And the best part is that to make this work leaders have to start with themselves.

Only then you can dream of influencing culture so that it supports the everyday acts of leadership on all levels. If you got it right you may actually start thinking about all the helpful stuff you can introduce to keep the changes running. In fact, it’s pretty likely that you won’t need so much guidance as lots of them will emerge.

Oh, and if you wonder whether that change among leaders and managers is easy, well, it involves lots of pain and suffering. It is against of what we’ve been (wrongfully) taught for years. Sorry.

March 30, 2014
Why Kaizen Boards (Typically) Don’t Work

A Kaizen board is a neat concept. It’s a visual tool that keeps track of all the ideas for improvements gathered across a team and then helps to analyze the status of ongoing improvement experiments. What we get from using a Kaizen board is we encourage everyone to participate in improvement process, visualize ongoing and planned improvements and give ourselves some sort of a tracking mechanism.

That’s the theory.

In practice I haven’t seen such a board that would work well.

I don’t say it isn’t possible to make it work. I just say it’s unlikely.

To answer why I think so, I have to bring the old story repeated multiple times in the context of Lean. When Japanese started kicking Americans’ butts in automotive industry in the second part of twentieth century Americans sent their managers to see what’s so different in factories in Japan. Surprisingly enough Japanese were super-open and transparent with all the tools and practices they had in place. Americans meticulously noted all the novel stuff they learned and implemented the same tools and methods back home. Guess what. It didn’t work.

It didn’t work because all these practices weren’t really game changers. The real game changer was underlying mindset that actually made these tools and methods work. By the way, this was also a reason why sharing all the secrets about practices wasn’t a problem. They weren’t nearly enough to make a difference.

We pretty much recreate the same story when we try tools like Kaizen boards or when we create Kaizen teams. We introduce a tool and believe it will change the game. It won’t.

The magic behind thousands and thousands of improvements implemented in Toyota every year is not any of the tools. It is a culture that supports trying stuff out. It is mindset that enables that. All that continuous improvement is happening not because people submit improvement ideas to Kaizen boards but because people are actively experimenting. They do stuff.

If you tried using a Kaizen board this picture may be familiar. There was lots of stuff submitted to the board but very few, if any, real changes were observable in your working environment. Now ask yourself: what would it take for any team member to try something out. Would people need to get permission and a blessing before they changed the way they worked? And then, when the thing failed, would they need to explain or ask forgiveness? Would they feel that they were co-creating the system they were a part of?

In most organizations I know these answers would tell you why your Kaizen board or Kaizen team or Kaizen whatever doesn’t have a slightest chance to work. In fact, in such a situation a Kaizen board would just be a nice excuse. I’d had that awesome idea but it wasn’t accepted. I’d come up with that great improvement but there wasn’t time to implement it.

Except then you shouldn’t call it a Kaizen board but an excuse board.

And the best part is: if you have right mindset and the right culture in place a Kaizen board isn’t needed at all. People just run their improvement experiments. Of course some of them last and some of them don’t. Then you obviously can use a Kaizen board as a tracking and visualization tool. Unless you get there though – don’t bother.

February 28, 2014
What Does Project Management Mean to Me

I was poked to answer the question on meaning of project management by Shim Marom. Since my work, and this blog, evolved away from covering what can be called traditional project management approach long ago I thought it may be a good occasion to restate the purpose of the blog as well.

Se here it is.

Getting the stuff done

The simplest answer, from the top of my head, is that project management is all about making it happen. Of course it’s not a single person’s effort. It’s more orchestration of all the stuff happening around but at end of the day the discussion always starts with what got delivered.

But wait…

“There is nothing so useless as doing efficiently that which should not be done at all.”

~Peter Drucker

Getting the right stuff done

The discussion on the right stuff is primarily product management / product ownership thing but most definitely it’s not beyond the scope of what I consider project management. After all, if you’re doing the wrong thing there’s no credit to anyone. A project manager isn’t an exception here.

So yes, it starts with grasping the business case, understanding how the project corresponds to it and actively working on that match.

When we are on the right thing though, it’s inevitable that doing right thing versus doing thing right argument will pop up…

Getting the right stuff done right

Getting the thing right is about the quality. If there’s no quality built-in it’s going to come back to you and bite you in the butt. Painfully. While I’m as far as possible from introducing oppression tools like quality procedures and such stuff, quality doesn’t automagically happen. One needs to create environment where high quality thrives and is encouraged.

What exactly the high quality means is obviously contextual but from my experience it’s not that difficult to describe the quality in any given context.

If nothing else you can always make the next project better than the last one.

Getting the right stuff done right and improving

This brings me to one of the areas I sunk into when I started flirting with Kanban – continuous improvement. There should be no pride in doing same stuff again and again. Unless you’re a freaking genius and know it all about project management, that is.

Personally, I couldn’t be farther from that. That’s why I have an ambition to improve. Improve the way I work but also improve the way everyone around works. It’s not that easy as it sounds though. The prerequisites are: understanding how the work gets done and learning like hell.

Without understanding work we are like children in the fog – clueless and lost. Learning means that we broaden our horizons and go beyond that carrot and stick method our first managers were using all the time.

Getting the right stuff done right, improving and building trust

This one is a classic last but not least. In fact, I believe that without trust you will struggle across the board. And I mean trust here in a very broad sense. One, it is about building trust within a team. Without that people wouldn’t become vulnerable, thus would restrain to become transparent. Without that a project manager would always have limited information of what’s happening in an endeavor they’re supposed to lead.

Second, and more importantly, it’s about building trust with a client. That’s where the real fun starts. It’s really rare when a client would take the first step and will start to be open, transparent and vulnerable. The good part is that they will likely do so once they see it on the other side. But this is fear that every project manager, and every team member, has to overcome by themselves.

The example, as usually, should go from leaders.

So this is it. I believe this definition works well for me right now and the stuff I deal with fits the picture neatly. It doesn’t matter whether I talk about Kanban, organizational culture or team management. It doesn’t matter whether I deal with a portfolio level, a project level or a task level. It’s all there.

Project management is about getting the right stuff done right, improving and building trust.

September 24, 2013
MVP Thinking

One of the most valuable goals achieved by Eric Ries’ Lean Startup is popularizing the term Minimal Viable Product (MVP). Of course the concept isn’t novel. We were using the Minimal Marketable Feature (MMF) idea back in the early days of Kanban and it was coined based on the same way of thinking. There are more of such concepts too.

The basic premise is that we should build the smallest possible thing or run the smallest possible experiment that is still reasonable and adds value. Depending on the context the value may be something that helps users, but may as well be just knowledge discovery or verification a hypothesis.

One thing I’ve realized recently is how widely I apply this thinking. Initially, it was simply the way of breaking the scope down. I wanted my teams to build possibly small, but still valuable, chunks of software so a client can verify them and feed us back with useful information. Then, after Lean Startup, it was about running a product. What we want to build something new that kicks butts. What is the smallest feature that can prove or disprove the hypothesis that it would work at all?

Somehow I now use the same way of thinking, MVP thinking if you will, to discuss marketing ideas, define actionable items during retrospectives, etc. Often it is difficult to define a product per se, but there always is some kind of an expected outcome and definable minimal effort allowing the get that outcome.

So how would I define MVP thinking?

1. Define the next smallest valuable goal you want to achieve.
2. Define minimal effort that allows you to achieve that goal.
3. Execute.
4. Analyze the outcomes and learn.
5. Repeat.

A potentially tricky part here is defining the goal because it is totally contextual. It is also something that really appeals to me as I don’t like recipes. In fact, if there is anything new here it is basically extremely broad application of the pattern as the idea itself is anything but new. I mean, we usually close our context to working with the scope of a project, driving a product, running a business, etc. Then, we absolutely coin a new term and if it works we make our careers as overpriced consultants.

That’s totally not my goal. I’m just trying to broaden an applicable context of ideas we already know as I’ve personally found it helpful.

So if my problem is a roof leaking near a roof window my next minimal goal may be verifying whether the leakage has anything to do with an external window blind. Such a goal is nice because minimal effort may mean simply waiting for the next rain with the blind either opened or closed. I definitely don’t rush to repair the roof.

Talking about marketing? Let’s set a general goal that, say, TechCrunch will cover us. What would be the smallest valuable experiment that can bring us closer to achieving this kind of a goal? I guess reaching out and networking may be a very reasonable first step. It doesn’t even require having an idea, let alone a product, that we want to have covered.

How about a product? Well, this one was covered virtually everywhere. Building minimal functionality, possibly even fake, that allows verifying that the idea for the product makes sense.

Retrospectives? What is a single, smallest possible, change that will have a positive impact on the team? Try it. Verify it. Repeat.

Heck, I even buy my sailing gear this way. What is the smallest possible set that allows reasonable survival? Then I use the outcome and iterate, e.g. next time I need new gloves, long johns and waterproof case for a phone.

When you think about that it is basically Kaizen – systematically running small improvement experiments everywhere. So yes, it’s nothing new. It’s just the specific idea of Minimal Viable Product that spoke to me personally and gave me a nice constraint that can be used in different areas of my life.

By the way, despite it very open definition I also find Kaizen usually applied in a very limited context. So no matter which idea works for you, just remember you can use it in broader context.

June 10, 2013
Pitfalls of Kanban Series: Stalled Board

One of signals that something may be wrong with a Kanban implementation is when the Kanban board’s design doesn’t change over time. Of course it is more likely that rapid changes of the board will be happening during early stages of the Kanban implementation, but even in mature teams a board that looks exactly like it did a year ago is sort of a warning light. For very fresh Kanban teams I would expect that board design would differ month-to-month.

Actually, a stalled board is more a symptom than a problem on its own. The root cause is likely the fact that the team stopped improving their process. On one hand, it is a common situation that at the beginning the potential for change is significantly higher and it diminishes over time. On the other, I’ve yet to see a perfect team that doesn’t need to improve their processes at all.

In such cases, what can one do to catalyze opportunities to discuss the board design?

One idea that comes in very handy is to watch for situations in which any team member takes an index card to update its status and, for whatever reasons, struggles to find the right place on the board to put the card. It may be so because there isn’t relevant stage in the value stream, or the work currently done isn’t in line with the rest of process, or a task is sort of specific, or what have you. This kind of situation is a great trigger to start a discussion on the board’s alignment to what the team really does and how the work is done.

Another idea is to dedicate a retrospective just to discuss the board. Such a constrained retro can be a natural opportunity to look for board-related issues or improvements in this area. I think about a class of issues that might not be painful enough to be brought as biggest problems to solve on regular basis, but, at the same time, we know that tiny changes in the board design or WIP limits can introduce tremendous changes in people’s behavior.

There is also a bigger gun – a significant board face-lift. Following the idea that Jim Benson shared during his ACE Conference keynote, teams find it easy to describe and define about 80% of processes they follow. The rest seems vague and that’s always a tricky part when you think about value stream mapping. This is, by the way, totally aligned with my experience with such exercises – I’ve yet to meet a team that can define the way they work instantly and without arguing.

Of course, introduction of visualization helps to sort this one out although it’s not that rare that we fall into a trap of idealizing our flow or just getting used to whatever is on the board.

Then you can always use the ultimate weapon and redesign your board from scratch. Probably people will have in mind the board you’ve just wiped out and will mimic it to some point. Anyway, odds are that if you start a discussion from the beginning – the moment when work items of different classes of services arrive to the team –some new insight will pop up, helping you to improve the board.

On a side note: it is also a good moment to discuss what you put on an index card exactly; I treat it as an integral part of board design, as you will need a different design for standard-sized work items and different for highly-variable projects on portfolio board.

Read the whole Kanban pitfalls series.

August 1, 2012
Pitfalls of Kanban Series: Wishful Thinking

I find it pretty common that teams who adopt Kanban try to draw the ideal process on their boards. Not exactly the one they really follow, but the one they’d like to. It is thinking taken from prescriptive methods – since we have this ideal process we want to implement let’s just draw it so we know where we are heading to.

Bad news is that Kanban in general, and Kanban board specifically, doesn’t work that way. You may draw pretty much any process on your Kanban board, a better or a worse one, too detailed or too generic, or just simply different. However in each case data you get from the board won’t reflect reality.

The end result is pretty simple as with the board that is not up to date people will be making their everyday project decisions basing on a lie.

What more, drawing the ideal process on the board instead of one that team really follows brings additional pains. People are confused when it comes to work with the board, e.g. I’m supposed to do code review but I haven’t and won’t do it but hey, I should put an index card here because our process on the board says so.

As a result it is way harder to show value of Kanban board, people lose interest in updating it and whole Kanban implementation quickly deteriorates.

The first step to deal with the problem is admitting your process is less-than-ideal. Pretty often it means admitting your process is simply crappy. As funny as it may sound teams find it really hard to go past this step. We wish we were better and this wishful thinking blinds us.

Then it’s time to adjust the board so it reflects the way team works. It may be painful. I saw teams throwing out code review stage. I saw those throwing out all the testing stages. That didn’t mean they didn’t want to review code or test. That meant they weren’t able to do it consequently for majority of features they built.

Note: at this stage a pressure from the top may appear. How come that you aren’t testing? That’s outrageous! That just cannot be! Well, it is, so better get used to it for a time being because drawing the ideal process on the Kanban board is almost as useful as drawing unicorns there. If such pressure appears, you definitely want to resist it.

The final stage is continuous evolutionary improvement. If you track down root causes of suboptimal process you will likely find that your flow is unbalanced. If you want to balance the flow slack time and WIP limits should be your best friends. Treat them seriously. Don’t violate limits; don’t get tempted to use slack time to build new features.

This change won’t be fast but at least odds are it will be successful. Drawing results of your wishful thinking on the Kanban board will fail for sure.

Read the whole Kanban Pitfalls series.

June 26, 2012
Kanban and Behavioral Change
One of my favorite and yet most surprising things I learned about Kanban over the years is how it steers change of behavior among mature teams. It shouldn’t be a surprise that at Kanban Leadership Retreat (#klrat) I ended up facilitating a session covering this area.

Those of you familiar with #klrat format would understand me when I say I didn’t have any specific expected outcome of the session. I wanted to start with exchanging stories and see how it goes. Maybe we would be able to observe some patterns of behavioral changes steered by Kanban and learn from that.

Fast forward to what we ended up with. For me it is still work in progress, so will see more on the subject soon. Anyway I pushed my thinking forward in terms of how we can stimulate our teams to improve.

One thing you instantly notice on the picture with the session summary (click to enlarge) is that there despite the fact we were gathering unrelated stories we started building a chain of dependencies. Another observation is how frequently visualization pops up in different examples.

What I believe we will be able to build is sort of a graph showing what kind of behavioral changes can be influenced or even incentivized with adopting specific practices. What more, I don’t want to keep it purely about Kanban. Although at #klrat Kanban context was set by design I’m pretty sure we can, and should, go beyond this context.

A few highlight from the session, basing on stories we’ve shared:
- Visualization combined with WIP limits and daily meetings around the board improve general team-wide knowledge about what’s happening. In short term this influence how people deal everyday tasks, encouraging them to get involved in work done by others, thus removing personal queues. As a result it pulls people toward generalization as they’re involved in many different tasks.
- Visualization and measuring flow improves understanding of work. It makes people to focus on pain points and incentivize them to improve problematic areas. As a result a team takes more responsibility for how the work is done.
- Rich visualization along with slack available to people results in better decisions and better use of slack time. It bases on a notion that rich visualization derives more meaningful data so whenever people decide what to do, especially when they aren’t constrained, e.g. when they’re using slack, improves the quality or potential outcome of these decisions. The final effect is building team’s collective intelligence both in terms of what they do and how they do it.
- Making visualization fun fuels viral adoption of the method. It bases on a fact that people like having fun with tools they use. More fun means more people trying to find out what this cool thing is and how to use it. Eventually you get more people willing to introduce the method and better attitude toward the adoption.
- Measuring flow (again) and understanding and visualizing (again) the nature of work can have impact in a multiple ways: creating incentive to change, building trust to a team and getting rid of 100% utilization. A simple fact that we were able to address so many effects to improved understanding how we work is a strong indicator that we do have problems with that. We might be onto something here.
- Avoiding 100% utilization and slack time, which is generated this way, may be a tool to build leadership among the team (people are free to make decisions on what’s being done) and at the same time can improve fun factor (people can choose to work on fun stuff). In both cases we strengthen our teams and develop people.
By the way: if you add a real story to each of these highlights you may imagine the experience we exposed ourselves to.

In retrospect, one thing that is definitely worth stressing is how little we seem to know about nature of our work. Actually if you think about it, Kanban deals with this issue in a very comprehensive way.

Visualization vastly improves information availability so we know better what is happening. Explicit policies force us to define, or agree on, the way we do work. Without explicit discussions on that we often believe we know how exactly how the work is done even when it’s clearly not true. Then we have flow management with a focus on measures that can change our perception of work highly. It’s a common situation when, being an outsider basing on a handful of simple measures, you can surprise a team showing them specifics of their work.

If that wasn’t enough we get WIP limits that steer changes in the nature of work and give us an important lesson about nature of work in general.

Anyway, leaving tools aside the lesson is to invest more effort to understanding how we work. It will pay off.
June 23, 2012
Slack Time

It often comes to me as a surprise that people misunderstand different concepts or definitions that we use in our writings or presentations. Actually, it shouldn’t. I have to remind myself over and over again that I do exactly the same thing – I start playing with different ideas and only eventually learn that I misused or misunderstood some definitions.

Anyway, the context that brought me to these thoughts is slack time. When talking about WIP (Work In Progress) limits we often mention slack time and usually even (vaguely) point what slack time is for. However, basing on different conversations I’m having, people rarely get what slack time is when they first hear about it.

How Slack Time Works

Let’s start with basics. Imagine a very simple development process: we have backlog which we draw features from, then development and testing and after that we are done. For my convenience I split development stage into two sub-columns: ongoing and done, so we know which task is still under development and which can be pulled to testing.

As you might notice we also have WIP limits that will trigger slack time in our process.

In ideal situation a quality engineer would pull tasks from development done sub-column as soon as anything pops there and even if it won’t happen immediately we have a buffer for one feature in development (two developers and WIP limit of 3 in the column). I have a surprise for you: we don’t live in ideal world and ideal situations happen pretty rarely.

There are two scenarios possible here. One is that developers won’t be able to feed quality engineer with features at rate high enough to keep him busy.

In this situation quality engineer is idle. He just face slack time. He can’t pull another task from queue because it is empty so he needs to find a different task. He may try to help developers with their work (if possible) but he may also learn something new using slack time to sharpen his saw. He can also use this time to automate some of his work (and believe me: vast majority apps I saw would benefit heavily from automating some tests) so that the whole process is more effective in future.

Another situation, and the one that is more interesting, would happen when the quality engineer is a bottleneck. It means that he can’t deal with features built by developers at the same rate they are flowing through development.

In this case one of developers who just finished working on a feature has slack time. It is possible that another will soon finish his feature as well and both will be in the same situation. And again, they can use slack time, e.g. to do some refactoring or learn something new or help quality engineer doing his work. However, probably most valuable and at the same moment most desirable thing to do would be finding a way to improve the part of the process that is bottlenecked; here: testing.

The effect might be some kind of automated test suite that reduces effort needed to test any single feature or maybe improvements in code quality policies that result in fewer bugs, thus less rework for each feature.

What Slack Time Is

By this point you should already understand when slack time happens and what it is roughly. Let’s try to pack it into some kind of definition then. Slack time happens when any team member for whatever reasons restrains to do the task they would typically do, e.g. a developer doesn’t develop new features. It is used to do other tasks, that usually result in improvements of all sorts.

That’s a bit simplified definition of course. You may ask what if a developer has a learning task every once in a while put into their queue. Well, I would dare to say that it is just planning for learning and not introducing slack time, but we don’t deal here with strict definitions so I could totally agree if others interpret it differently.

Note: we went through two different root causes for slack time emergence. One is when there aren’t enough tasks to feed one of roles. This is something that happens pretty naturally in many teams. If one of roles further downstream is able to process more tasks than roles upstream (in other words: bottleneck is somewhere upstream) they will naturally have moments of slack time.

Some people may argue that this is not slack time and again I can perfectly accept such point of view. However, for me it suits the definition.

Another root cause is when we intentionally limit throughput upstream to protect bottleneck that is somewhere downstream. This case is way more interesting for a couple of reasons. First, it doesn’t happen naturally so conscious action is required to introduce such slack time. Second, for many people introducing slack time there is counterintuitive, thus they resist to do it.

A result of not limiting throughput before a bottleneck is a huge queue of work waiting for availability of bottleneck role, which makes the whole thing only worse. The team has to juggle more tasks at the same time introducing a lot of context switching and crippling own productivity.

Nature of Slack Time

One of specific properties of slack time is its emergent nature. We don’t carefully plan slack time as we don’t exactly know when exactly it’s going to happen. It appears whenever our flow becomes unbalanced, which sometimes means all the time.

You can say that slack time is some sort of flow self-balancing mechanism. Whenever team members happen to have this time while they don’t do regular work they are encouraged to do something that improves the flow in future, usually balancing it better. At the same time the more unbalanced the team and the flow are the more slack time there will be.

Remember though that in software development business our flow won’t be stable. Even when you reach equilibrium in one moment it will likely be ruined a moment later when you’re dealing with a special case, be it a non-standard feature, a team member taking a few days off or whatever else.

It means that even in environment which is almost perfectly balanced slack time will be happening. Even better, such state means that you don’t have a fixed bottleneck – it will be flowing between two or more roles, meaning that every role in the team would have slack time on occasions.

Another specific of slack time is that usually we aren’t told what exactly we should do in it. It doesn’t have to be that way in each and every case, however since slack time itself isn’t planned we can hardly plan to complete something during slack time in a reasonable manner. On the other hand there may be some guidance which activities are more desirable.

It means that slack time seems to be a tool for teams that trust each other and are trusted by their leaders. It is true as slack time, thanks to its emergent nature, can’t be managed in command and control manner.

However, for those of you who are control freaks, considering you have sensible WIP limits even if your people do nothing during slack time (and I mean virtually nothing) it should still have positive impact on team’s productivity. This is because 100% utilization is a myth. Note that in this case you lose self-balancing property of slack time – you don’t improve your flow. You just keep your efficiency on a bit higher level than you would otherwise.

What Slack Time Is For

I’ve already mentioned a few ideas what to use slack time for. Let’s try to generalize a bit here. Slack time, by definition, isn’t dedicated to do regular stuff, whatever “regular stuff” might mean in your case. If you think about examples I used and try to find a common part these all are important things: learning, improving team’s toolbox, balancing the flow or improving quality.

At the same time none of them seems to be urgent. It is usually more urgent to complete a project on time (or as soon as possible) than to tweak tools team uses or introduce new quality policies.

In short, slack time is for important and not urgent stuff. If something is urgent it likely is in the plan anyway and if something isn’t important what’s the point of doing it.

If you’re interested in more elaborate version of that please read the post: what slack time is for.

Other Flavors of Slack Time

When talking about slack time it is easy to notice that there is some ambiguity around this concept. Why unplanned slack time is OK and planned time slots dedicated to the very same tasks are not?

Personally I’m far from being orthodox over definitions. For me the key is understanding why and how slack time works and why it is valuable, so you can achieve similar effects using adjusted or completely different methods.

Considering that a general goal of slack time is improvement you can introduce dedicated time slots for that or include improvement features in your backlog. The effect might be pretty similar and you may feel that you have more control over a process.

What more, you may want to plan for improvement activities not leaving it to the random nature of slack time. Again, that’s fine for me even though personally I wouldn’t call that slack time.

We may argue over naming, whether something already can be called slack time or not, but I’m not going to die for that really. Especially if we agree on purpose of these activities.

I hope this helps to understand the concept of slack time – what it is, how it works and why it is valuable. Should you have any ideas what is missing or wrong here please leave a comment below. I’ll update the post.

May 10, 2012