If you need a tool to break down complex scenarios, this approach, a tool using decision forests, might be right for you. By the end of this post, you’ll be able to use the gentler, forward, variant of dancing in a decision forest.
This is a post is intended for a curious audience.
You’re an extraordinary assembly of chemical gradients. At any given moment you have the opportunity to make millions of decisions.
The crudest segmentation, the roughest way I can impose order on all of this complexity is divide them up in two types of decisions: to act, or to not act.
Further, when you decide to act, there are two broad types of actions: explore and exploit. You can choose to learn more, or you can choose to exploit a decision opportunity.
Colin Powell 40/70 Rule
Colin Powell came up with the 40/70 rule. At least, that’s who we’ve credited it to. Put simply, if you make a decision with only 40% of the information in place, you’re calling it too early. If you want for more than 70% of the information, you’re calling it too late. The sweet-spot is between 40% and 70%.
Both exploring and exploiting are equally important decisions.
Starting Point For This Tool
The starting point for this tool is that you’ve decided that it’s time to exploit. It’s time to get cooking. You’re going to start your mise en place. Start with answering the question: what choices do I really have?
- Start with a forest short trees;
- Sequence the trees in order;
- Stack the trees;
- Eliminate absurdities;
- Score the leafs;
- Select the outcome you want;
- Eliminate the branches that don’t take you to where you want to;
Start with a forest of short trees
So let’s say you explored and you explored, and really, you can only think of three actions you can take. I’ll label them A, B, and C. That opens the door to three decisions you can make. notA or A, notB or B, and notC and C. Those are three decision trees. Three trees is hardly a forest, now is it?
The management science strongly suggests that fluffing the forest floor for more options generally creates better outcomes in the end. I think that only works up to a point. Remember the Powell 40/70 rule. You want a whole bunch of choices to choose from so long as you’re still able to make sense of the world. Using this tool will help you manage a lot more complexity, and help you make better judgements.
Another way to fluff the forest floor is by using Hall’s Order of Change model. Hall noticed that you have small routine changes to settings on a tool (First Order), bigger changes where you’re changing the tool entirely (Second Order), and huge changes, like changing entire goals or stances (Third Order). You can generate a huge number of leafs just by considering different changes to the tools you have.
For instance, the decision between increasing A to 20, and not(A to 20), represents a choice. Increasing A to 100, and not(A to 100) is another. You can generate a huge number of leafs this way. And if that sounds familiar, it’s a big part of the magic that is the random forest algorithm.
Tool decisions are not as common as setting decisions, but they can be found. Big changes in stances and goals (paradigms) are even more rare, and take a lot of creativity and a considerable amount of work to discover.
The more trees you can discover, and this is where having a huge variety of people to help you out, (up to a point!) the better your outcome is going to be.
Sequence The Trees In Order
Sometimes, often, sequence matters. Sometimes choosing A means that you can’t choose C. Sometimes the only way you get the opportunity to do B is by choosing notA.
Hall’s Orders of Change gives us a good hint of how sequencing really matters. A decision to change the goals usually comes before tools are changed, and before the decisions of how to set the settings. Often, when groups of people are not behaving as though they are stepping through a decision tree, dozens to thousands of small changes come before the big paradigm shift. If you were to plot them…it would almost look like an earthquake.
Arrange your trees in a logical order from left to right. Do a rough order for your first pass. Then refine it on your second pass. As you’re doing your second pass, note the ones that are hard, and mark the ones where the order isn’t as important.
Putting the trees in your forest in order will make the next step a lot easier.
Stack the Trees
Next, you’ll wan to create your first tall tree. Starting from the left, stack the trees in order, branching downwards. Your trees are about to become branches in your new tree.
Don’t be too hard on yourself with the first attempt. You may notice that some of the complexity may start to gallup. Note to yourself when it’s starting to happen. When it starts to feel very weird, just stop, and do another one.
At this stage, it’s okay to create a nice forest taller trees. Some trees will be lopsided. Some strange. Some neat.
Pick the tree that’s right for you.
Stand back and look at the tree. Are there any absurdities? Do the decisions flow logically from top to bottom? Prune any branches that don’t make sense.
Score the Leafs
You create the future by making choices. Each journey down the tree, along the branches, from to bottom, creates a future. Even following a path like not(A), not(B), and not(C) generates a future. What’s great is that you get to travel to that future, and think about it.
There are all sorts of ways to score a future. You can look at it from your own perspective – what you personally lose or gain. You can look at it from somebody elses’ perspective. You can stack several perspectives together. Sometimes you’re in a situation where you have actively trade off one outcome for another.