The Corn Maze Strategy

October 10, 2016


Today was our annual family visit to the pumpkin patch. We go to a local farm that is a sort of pumpkin theme park. In addition to the fields of U-pick pumpkins, they have a petting zoo, pumpkin launchers, halloween themed play structures, hay rides, and a corn maze. It was a beautiful early October afternoon, and the kids roamed through all the usual activities. Finally we got around to the corn maze.

Now you should know that as these things go, this corn maze is pretty decent. I have no idea how large it really is, but my fitbit tells me that it’s at least a few thousand steps or so. I would guess it’s a walk of a mile or two to get through it. You should also understand that it’s relatively robustly built. You really can’t see any nearby landmarks, and the paths are kept far enough apart that you can’t see other adventurers in the maze. So it’s really quite easy to get good and lost.

So I followed the family in and tagged along behind as we made our way through the maze. I was tired, so I was perfectly happy to let the kids make all the decisions and accept the consequences. The pattern usually went something like this: We would come to an intersection and pause. We would look for clues on the ground. Was one path better travelled than another? Did the curve of the path look like it might actually form a loop? Did the path head in a direction that we thought might be the correct destination? We would ponder these questions and consult as a family before moving onward. So some sort of consensus was arrived at as we reached each intersection.

As I stumbled through the maze following my family, lost in my own thoughts, I started to observe how we were making decisions as a team. At each intersection there was usually some sort of debate. Arguments were made for and against different options. The group would informally arrive at a decision. We had the advantage of multiple brains rather than just one, so you would expect some sort of multiplier effect from using those additional noggins. But it really didn’t feel that way.

Instead we were bouncing around the maze, wandering into loops and blind alleys, and as far as I could perceive, we were not much more successful than someone walking the maze and flipping a coin to decide which direction to go. It was quickly becoming apparent that our success rate was hard to discern from a completely random performance. In fact, at some point I joked that we should be using a 20 sided dice to determine our next move. Geek family.

As we came around a bend I saw another family just standing at an intersection expectantly looking down the path like they were waiting for something. The father came running into view from further down the path and I heard him say rather breathlessly, “There’s nothing down that way guys.” We moved on and I couldn’t help but wonder about that approach. That family was using an interesting strategy. They were obviously making an effort to collect some information about the maze before moving on. That seemed to be one level of effectiveness beyond what we were doing. They were trying to look ahead and gather some intelligence that they could use to help make a better decision about the direction to go in the maze.

We continued to ramble about, but it was soon apparent that the kids were starting to get tired. My wife indicated that it was time for us to bring the adventure to a close before we had a riot on our hands. Dad, stop being such a slacker, it’s time for you to make a few decisions! So that’s when I had an idea.

At the next intersection, I sent a child down each avenue with the instruction to continue until they come to another split in the path and then to report back to me. Off they went. I figured I had two children, so I could afford to lose one with this experiment and still call myself a parent.

At the first junction, the kids came back and one reported a dead end, and the other reported yet another junction. Well that made the decision easy, so off we went. At the next junction however, both kids reported the same thing – there was another junction, but no indication beyond that. So it appears that my look ahead strategy had it’s limitations. There was only so far we could see ahead in the maze using my one intersection strategy. So we flipped a coin and moved on.

At the next intersection, we had a choice between an intersection and an obvious milestone, so we continued toward the milestone. A few more choices like that and we found the end of the maze.

As we celebrated and headed back to the car, it occurred to me that wandering through a corn maze is not all that different from the way that we work on projects as teams.
A project has a lot in common with a corn maze. In principle we all know how they work, but the path from start to finish isn’t all that clear when you start (oh you may THINK it is clear, but let’s face it, there are a lot of unknowns). So you kick off your project and get started and before too long you have to make some decisions. All too often when we make decisions as teams, we do it on the spur of the moment, using only the information that is immediately in front of us. Just like me and the family in the corn maze. We are only using the information that is immediately at hand. Decisions are made quickly with a minimum of information. It’s little better than a coin toss. But there is an alternative.

We can be gathering information to help us make better decisions. There are various names for this kind of look ahead strategy, personally I’m thinking of “set based decision making.“ In set based decision making you explore multiple alternatives. You look down multiple paths, but you don’t go too far. You are gathering just enough information to help you make a good decision now before you proceed onward. Just like with the kids running forward reconnaissance in the maze. This is how you improve the information you use for decision making, and this is how you give yourself a chance to make better decisions.

You see, projects have many important decisions to be made. You bump into them daily. Go the right direction and you are increasing your project’s likelihood of success, go the wrong direction and the project is that much closer to failure. These are high stakes decisions with lots of money on the line. So using the corn maze escape strategy is a good one. A small qualification is probably in order here: The look ahead doesn’t give you a crystal ball or a guarantee of success.

The point is that we all might benefit from using a conscious strategy to acquire knowledge that can inform our decisions. It doesn’t have to be very much additional information in order for there to be a substantial benefit. So the next time you find yourself on a complex project where you have to make tough decisions, remember the corn maze. The strategy you choose can make your journey a whole lot easier.

What is “Swarming?”

December 3, 2007

The term is derived from the behavior of insects in nature. The classic example of this behavior is a beehive when it reaches a critical mass. The workers will grow a new queen, and then the hive will split and a swarm will form that will leave the hive and seek out a location for a new hive. Perhaps the most astonishing thing is the fact that there is no one individual controlling the actions of the hive. There is no controller, no authority, no coordinating influence. Sounds kind of Agile.

These characteristics of “swarming” in the insect world are very similar to the kind of behavior that we are trying to foster within Agile teams. We want the entire team to focus on one and only one story at a time.

We want to use simple rules. We want to allow the team to self organize.

However, swarming is a relatively new pattern to emerge in the software world, and there has been a lot of misunderstanding and resistance to the notion of swarming. The idea of having the entire team focused exclusively on the same story is very hard for some people to swallow. The key is to create the right environment to support swarming activity.

If you are going to practice the swarming you need to make sure the following conditions hold true for your team:

  1. There is a definition of done that enables the involvement of the entire team
  2. The scope of the story is non-trivial
  3. A Set based decision making model is used

Often the argument that I hear is that a given story simply doesn’t require the involvement of everyone on the team. However, the more I thought about it, the more I realized that this probably isn’t really true very often. If we look at the definition of done for a team, we fine that there are activities from virtually every team specialization that are required to get a story into “potentially shippable” form. There needs to be a definition of done that enables the involvement of the entire team. Think about it – what activities need to be done for each story? Can we leave out QA? Documentation? Analysis? Design?

Someone once argued that it doesn’t make any sense to build a car 1 tire at a time. I have to agree, but I must also maintain that the challenge must be equal to the resources of the team. We should scale the stories to the appropriate size. The scope of the story must be non-trivial. Instead of building one wheel at at time, perhaps we should change the story to implementing the braking system? Perhaps the team should be implementing the suspension? The drive train? The story has to be scoped large enough that it allows the participation of more than one team member.

We also have to realize that swarming opens up some opportunities that we might not have using more conventional team organizational patterns. A Set based decision making model can be used. If the entire team is focused on the same problem, then we can also have them explore multiple solutions to the problem. This can lead to enhanced learning by the team, and allows them to explore alternatives more fully before making a commitment to an implementation or technology.

So, if you want to explore your busy inner bee, you need to create the right environmental conditions to support the swarming behavior:

  1. There is a definition of done that enables the involvement of the entire team
  2. The scope of the story is non-trivial
  3. A Set based decision making model is used

Given these conditions, the swarming pattern represents an exciting opportunity for us to explore a new way of understanding how we collaborate within our teams.