Planning and Entropic Forces

The Foundation series is a classic science fiction series by Isaac Asimov. In it Harry Seldon, a scientist of the fictional field of psychohistory, predicts the collapse of the galactic empire by modeling the future of humanity with entropic forces. Seldon devises a plan to ensure the best future for humanity after the collapse. He forecasts a thousand years of future, then sets up a series of actions in motion to ensure humanity is able to go down a highly unlikely specific path and end up at the desired future.

I think he got it wrong.

By focusing on one path, Seldon limits the potential good futures to one very unlikely path. Spoiler: guess how that worked out. Despite understanding how entropic forces made the end of the empire all-but-inevitable, he never turns this idea to humanity’s advantage. He should have taken actions that maximized the potential future paths with desirable states.

What does this mean?

The more ways a plan has of succeeding, the more robust it is. Robust plans don’t fail at the first unforeseen challenge. Consider an example from technology – database redundancy. If everything is stored in one database and the database goes down, the entire system stops working. However, if there are three copies of the database (far enough away that failures are independent) then the likelihood of the entire system going down are minuscule. As we increase system redundancy, the entropy of a state where all systems are failing approaches zero, and the entropy of states we want grows without bound.

(In this situation there are practical redundancy limits, and the best practice is usually to go for at least two more than the number of databases for the system to run under the heaviest expected load. It may be interesting to explore the math later …)

How do I use this in planning?

Have more than one path towards what you consider “success”. Suppose your goal is to work in position X at Company Y. Naively, your path forward is to apply for position X. You have some probability of getting the position, and you either get it or you don’t.

There are more paths than these.

What are other paths that accomplish your needs? Do you need the position right now or can it wait a year? Does it need to be that position at that company, or are there similar opportunities at the same (or at similar) companies? Is it acceptable to apply, fail and get feedback, then try again? Is there, perhaps, an intermediary stepping-stone job? A degree that might increase your chances? A meetup group where you might run into employees who could refer you?

The answers to all of these depends on your constraints – your requirements. If you want one specific future then you really only have one option and entropic forces will (statistically) work against you. If more than one future – or more than one path – is acceptable, then you can use them in your favor. In general the more paths and the more likely you make the success of the paths, the higher the entropy of desired futures is.

But what does that look like?

I recently switched jobs. I decided I wasn’t happy on my current team and I needed a change. There wasn’t anything urgently wrong, so I was fine with waiting up to a year. After thinking about the sorts of changes I wanted, I realized there were three main categories of futures I would consider a success:

  1. finding a team I would be more happy with at my current company,
  2. finding a new company I would be more happy at, or
  3. going back to school for a graduate degree.

I added constraints to each future. For example, there are companies with cultures I would never want to work at. I wanted to stay in the Bay Area, so that limited both schools and companies I could look into.

Then, I broke each general future into a general sequence of tasks required to make that future happen and ones that would make the future more likely. Required tasks generally fit into two groups: ones that cut off my ability to pursue other paths (e.g. accepting a job offer) and ones that moved the path along while changing (usually reducing) the likelihood of the others (e.g. doing an onsite interview). While the required tasks varied greatly, the optional tasks presented a lot of overlap in the futures: networking, studying, and understanding my desired team qualities were common to all three.

By doing the tasks that made all of the successful futures more likely, I increased the entropy of futures where I succeeded in my goal. My plans were robust in that there was no single point of failure that could topple them – there were more companies to apply to, many possible teams, and if those didn’t work out in a year then I also had applications for school in the works. Throughout it all, I would be gradually improving the likelihood of each subsequent attempt.

Briefly, these are the steps this approach suggests:

  1. What futures do you consider successful?
  2. What are your constraints on these futures?
  3. What increases the likelihood of each future?
  4. What are common actions that increase the likelihood of multiple futures?
  5. In general do as much towards the common actions as your constraints allow, and do specific actions as necessary.

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