Posted in July 2012

The beer game

As you might have noticed (maybe not), the usual programming was suspended on Friday. The reason for this is simple, I was playing the Beer Game.

No, this was absolutely nothing like you thought right now. It was a sober educational foray into the wonderful world of supply chains and system dynamics. The idea is that the players are made to play roles in a rather poorly designed supply chain where they have to sell, stock and produce beer. None of the players knows anything about what their neighbors do and the input variable (i.e. demand) is unknown as well. Communication is not permitted, you just draw conclusions from what’s happening. And boy, is that interesting.

Let me recount the layers of awesomness encountered.

Firstly, professor Morrison and his manner of delivering the subject. And, no, this is not me sucking up, I passed the class last year. The jokes, the attention to detail. Cool.

Secondly, the way you can feel yourself slowly drift away from reason as you try to understand what the hell is going on. You attempting to react to what is happening makes others react to _your_ actions which makes the input to you even more erratic and so forth. It gets ugly pretty fast.

Thirdly, the sheer predictability of human behavior. MIT folks have played the game for 50 or so years and kept meticulous records. Apparently, the results do not depend on whether the players are 5 or 55 years old, from kindergarten or upper management. Both the behavior of the game variables and the people is very similar. Except kids apparently tend to have fun.

Then there is the astonishing speed at which reasonable people resort to the fundamental attribution error. It was pretty civilized for us but some of the stories the prof told…

The applicability of it all. In a nutshell, we were presented with a small-world model of what we see every day. Do we realize it or not, we are part of complex systems all the time. We have no idea what is actually going on, we try to react the best we can and resort to the tools we have been taught regardless of their applicability or usefulness. We play the beer game every day.

Finally there is the learning. I was in a team that either had played the game before or had read about it. So we were somewhat prepared. Well, no. We did poorly. The entire group did worse than the 50-year average and we were on a third place within that below-average group of four teams. Doh. As a reflection, in my case it was mainly because I went back to one particular learning from one particular assignment from last year and tried to apply that with considerable lack of success. The topic is complex, I need to look at my notes and lecture materials and read more. Otherwise I have no place blogging about this thing, right?

Anyway, I do intend to get back with some more system dynamics on Friday. Until then, enjoy System Dynamics in action as much as I have done!

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On traffic

Oh dear, some horrible things happened around here with the gunman in the movies. For a second there I thought hey, this is a simple feedback loop between guns in the hands of criminals and guns in the hands of citizens, let’s make a post. Then I realized the magnitude of wrongness of me doing that. I also realized that the system is actually not that simple at all. Thus, we will continue with our regular programming delayed by a technical glitch and come back to the guns thing at a later time if at all.

Today we talk about traffic. Not least because this week professor Jay Forrester gave his lecture to the System Dynamics class. He is, of course, the grand old man of urban studies and last year at the same class he said something really interesting (am quoting from memory) about the topic: “Whenever you decide to make something better, you are just pushing bottlenecks around. You need to decide, what you are willing to make _worse_ in order to achieve a lasting result”

I have lately made the mistake of following up on Estonian media and, based on the coverage, one of the most pressing issues there is that the city of Tallinn has overnight and without much warning halved the throughput of certain key streets.

While we speak, the Euro is falling, US is in the middle of a presidential debate, the Arab world is in flames, we are on a verge of a paradigm shift in science, Japan is making a huge change in their energy policy possibly triggering a global shift and all of this is surrounded by general climate change and running out of oil business.

Oh, well. We probably all deserve our parents, children, rulers and journalists.

Anyway, that piece of news seemed to match perfectly the words of Jay Forrester and thus todays topic.

What the quote above means is that tweaking system values will just prompt more tweaking. Making a road wider will encourage more people to drive on it necessitating expansion of source and sink roads which have source and sink roads of their own. Thus, what professor Forrester says is that in order for that cycle to stop, one must make a conscious decision _not_ to improve certain things. Yes, traffic is horrible but instead of adding more roads, what else can we do? How can we change the structure of the system rather than tweaking and re-tweaking certain values that will only result our target variable stabilize at a (hopefully more beneficial) level?

This brings us back to Tallinn. From one hand it might seem that the change is in the right direction: somebody has decided to make the lives of drivers worse in order to stop pushing the bottlenecks around.


Or maybe not. You see, what Jay Forrester definitely did not mean was that _any_ action resulting in somebody being worse off is beneficial for the system. Only careful analysis can reveal what change can overcome the policy resistance of a given system.

The following is based on public statements about the future of public transport in Tallinn as reflected by media. It would certainly be better to base them on some strategy or vision document but alas, there is none. At least to my knowledge and not in public domain. There was a draft available on the internet for comments last summer but that’s it.


Let’s see, then. When driving restrictions are applied, two things happen. Firstly, amount of people driving will go down simply because it is inconvenient but also, the _desire_ to go downtown will diminish after a while. I’ll go to the local shop instead of driving. Let’s lease our new office space somewhere with good access rather than downtown. That sort of thing. When willingness to drive downtown diminishes, amount of people driving certainly goes down but so will the number of people taking the bus: if the need and desire are gone, there is no point in standing in the bus stop, is there?

It has been publicly stated that the money acquired from making the lives of drivers harder (this includes high parking fees, among other things) will be used to fund adding capacity to public transport. Therefore, the less people drive, the less money there is to maintain some headroom in terms of capacity. The less headroom we have the higher the chance that the person taking the bus does not want to repeat the experience and prefers not to the next time. And, of course, investment in the road network drives up the amount of people who actually drive.

Simple, isn’t it? Before I forget, many of these causal relationships have delays. Offices do not get moved and shops built overnight, investments take time to show results. It takes time for people to realize they don’t actually want to spend 2 hours each day in traffic.

Here’s a diagram of the system I described.

Now, tell me, what changes in what variables and when will result in sudden and rapid increase in driving restrictions that occur simultaneously to a massive investment to road infrastructure at city boundary?

Nope, I have no idea either. From the structural standpoint, the system is a reinforcing loop surrounded by numerous balancing loops. Since several of them involve delays, it is very hard to tell whether the system would stabilize and when. It seems though that in any case, a reinforcing loop driving down the willingness of people to go downtown gets triggered. The danger with these things is, of course, that when they _don’t_ stabilize or stabilize at a lower level than desired, downtown will be deserted and left only to tourists (if any) as the need to go there diminishes. The citizens not being in downtown kind of defies the point of making that downtown a more pleasurable place, doesn’t it?

Surprisingly, the city of Tallinn has actually done some things to break the loops described. For example, the public transport system has operated on non-economic principles for years and years. The city just pays for any losses and there is no incentive to make a profit. This makes the system simpler and removes a couple of fast-moving economic feedback loops. For this particular campaign, however, taxation on drivers was specifically announced as a funding source for public transportation without much further explanation.

The system is an interesting one and had I some numbers to go on, would be fun to simulate. But I think I have made my point here. Urban transportation is a problem of high dynamic complexity. When the system described above was to be cast into differential equations, there would unlikely to be an analytical solution. How many of you can more or less correctly guess a solution to a Nth order system of partial differential equation? Without actually having the equations in front of you? Do it numerically? Right.

It is thus imperative that decisions that could easily result in rather severe consequences to the city are based on some science or are at least synchronized amongst each other (did I mention it? There is a multi hundred million euro development project underway to radically increase the capacity of a certain traffic hotspot in Tallinn) using some sort of common roadmap.

I hope this excursion into local municipal politics still provided some thoughts on system dynamics in general and hope you’ll enjoy some of it in action over a safe weekend!

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Sustainable quality improvement

Today we are going to talk about quality assurance. I’m going to typical processes of a software house as an example but the principle should be applicable in a wider context.

People make mistakes. Sometimes it is due to the way they work (the light switch and the drain-nuclear-reactor-coolant-system switch are identical and placed an inch appart) and sometimes is because they are just not well enough trained for the job. Sometimes they make mistakes because they are human but in any case, if the average quality of processes or people goes down, the number of defects in the product goes up. When the defects go up, the market is not going to like it and it will end up, in some way, driving down the revenue (Note: it might also be that the customer support costs or returns or whatever drive up the cost but the result is the same). This in turn drives down profit. When profit goes down, managers will be eager to find the culprit and might be inclined towards increasing investment in the QA. Effort spent on finding the defects before they reach the market goes up and the number of defects goes down again. This is what we’d call a balancing loop. Because it, well, balances itself.

What also happens as QA expense goes up, is that the average cost base of the company goes up which drives down profit which might lead to the same sort of managerial anger that caused QA expenditure to go up in the first place. Also, the more you spend on a unit the more powerful they get in the organization. The person commanding 200 people has more say in budget decisions than the person commanding 2. And of course they are going to as for more money. The entire picture looks like so:

There might be some process improvement going on but I think most QA folks agree that their primary job is catching bugs and finding better ways to do that. There is also a direct link between revenues and quality of people/processes as pointed out earlier but let’s ignore that added complexity for now.

I have two questions for you. With the forces at play, where do you think the quality level of the product stabilizes (if it indeed does stabilize)? And what do you think it takes in terms of money and effort to actually raise it to the next level?

You don’t know? Me neither. That’s the bloody thing: its a convoluted complex system where cause and effect go and dance tango leaving you to scratch your head in puzzlement. Oh, and did you notice? the thing that started at all does not feature in our primary feedback system at all. Nobody does anything to it and thus, whatever caused it to go down in the first place (loss of training budget due to missing of revenue targets?) is going to happen again and the entire system will tango to the sunset in search of a new equilibrium.

Let’s now say that instead of just kicking the arse of the head of QA (or increasing his budget), the management would go “Why?”. Why do our products have bugs? Why do we have more bugs today than we had yesterday? And increase the effort spent on process quality and people.

This picture is slightly better. The dance is still happening but at least the root causes are addressed and the entire system is likely to behave in a stable fashion after a while (even if this means oscillations).

Finally, let us take a long leap of faith and assume there is no managerial anger. That the leadership of the company has gone “Why the bloody hell are we constantly talking about quality? Why don’t we make it so that we don’t have to step in and manually govern the process? Let’s just make it simple and assign a fixed percentage of the revenue to process improvement”.

In this new reality, when the number of defects is pushed down (via a conscious push from QA, for example), the revenues go up, effort spent on process quality and training/hiring top people goes up which will, surprise, reduce the defects. What will also happen, is that the costs are actually going down. Smarter people working more smartly is a surefire way of reducing your development time and thus cost.

Whoa, hang on a minute. This thing does not stabilize! This thing is going to drive the defect rate down to a what exponentially approches zero!

Through a simple act of not caring the management has turned a balancing loop into a reinforcing loop. A loop that, once started, will drive down the defect rate to as close as zero as practically possible.

And this ladies and gentlemen, is why Toyota has become the worlds larges auto maker. This is why they have surpassed the Big Three in both quality and volume having started from the position of a clear underdog in both in just 40 years. Such learning-based feedback loops are a routine part of their production processes.

If this sounds similar then rejoice: agile software methods are to a large extent (to my surprise) rooted in the Toyota Production System. They preach the same concepts of fast reflection, constant improvement and built-in tests than Toyota does.

With this unexpected foray into the car industry, its time to end. Thank you for reading, have a good weekend and enjoy System Dynamics in action!

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On mice and success

So this is it. After years of hard work, there is finally some success to speak of. That’s a good thing, right? Well, yes. And no.

Let me elaborate. When you are successful, two things happen. The first is money. The more successful you are the more money there is. Actually, to be more generic, you get more “resources”. For an artist this might mean more freedom to do whatever they want, for a scientist this might mean recognition from peers and for a businessman this usually means money. The second thing that will happen that, all of a sudden, you are sure of your direction. Or more sure in any case. A startup is just a bunch of people with a crazy idea until the idea actually attracts users in the real marketplace. There is no way to be sure an idea will work until it has, well, actually worked.

You’ve got money, you’ve got a confirmation that your initial idea was good, what do you do? Let me tell you, based on personal experience, very few people go “Right, that’s that, then. I did this thing and it was good but now I’m going to take a risk by doing something completely different”. People will retire, oh yes, but majority of organizations and individuals tend to invest into the idea that brought them success. It makes sense, right? You’ve found a goose that lays golden eggs. Take the money from some of them eggs, hire a bunch of guys and go catch a herd of the suckers! You’ve got the recipe of a dish everybody likes, of course you are going to use their cheering as motivation to cook it again!

A well-funded and well-motivated individual focusing on doing something great they have already succeeded at once? Even if they were just lucky the first time around, chances of failure are slim under the circumstances. More success is unavoidable.

The entire model looks like so:

Success leads to money and confirmation which in turn drive down the likelihood of deviating from the set course which brings about focus and more success.

Brilliant, right? Kodak did this for 70+ years. Microsoft has been on this cycle for ages. IBM. GE.

No, not really. What this means is that the flexibility of an organization goes down. In the beginning, yes, its just the desire to choose a different path that goes away but soon the ability gets removed as well. After posting record profits for 10 consecutive quarters, your shareholders will not look kindly upon a CEO that proposes a radical change in direction. At some point an organization becomes so committed and invested in that one direction, even deliberation of change becomes hard. When everyone around is a chemist (or a software engineer, for that matter), who is there to experiment with hardware? Amazingly, Kodak actually managed to launch a digital imaging product as early as 1991 but the spectacular lack of success in the later years confirms the conclusion. The more successful you are the less likely you are to consider a change of direction.

Loss of flexibility is not a bad thing. Just like flying is not a bad thing. Its the hitting the earth part that gets you. When markets change and you don’t, things are not looking up.

Then there is the loss of variety.

Let’s think of Darwin, for a moment. He stipulated survival of the fittest. But what if everyone is equally fit? If you have a herd of mice, only the ones most successful in the given environment will survive and produce offspring. Should the conditions change, the definition of success changes, a different set of traits becomes desirable and the population survives. Given a bunch of genetically identical mice, however (let’s assume no random mutations), all the mice and their offspring are equal. If the environment is favorable, they’ll proliferate. But when the conditions change, they are doomed as there is no alternative set of traits to take over. There is none fitter to survive. The same goes with companies:

Single-mindedness in direction drives down variety in product portfolio (the “+”, as always, does not denote a positive influence but the fact that the variables move in the same direction). That reduces the intensity of evolutionary processes (our mice become more similar). This in turn reduces adaptability and eventually reduces chances of success.

What can we learn from this? Firstly, I think, it is not realistic to expect companies not to follow the cycle described earlier. People are not built that way. They will inevitably continue doing more of what makes them successful. Secondly, it seems that balancing the two cycles each other is a viable option. If the balancing loop kicks in when the success has already worn thin because of management failures or market issues, the company is done for. But if you manage to make sure both loops happen more or less simultaneously, survival is possible. Think of IBM. It was hit hard by changes in how computers are made but still had enough resources left to kick the cycle going backwards (lack of success reduces confirmation of direction which diversifies the portfolio) and to re-invent themselves. Few enough companies have pulled this off to call it a miracle of management.

Sidenote: there is interesting research on the topic of business survival. It seems that the pace of change is accelerating and companies die faster as they are no longer capable of adaptability the environment assumes. There is a good book about the topic as well.

Will your company be the next IBM or Kodak? Think about it while you enjoy System Dynamics in action!

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