About David Manheim

David Manheim is a decision theorist / mathematician who is interested in everything. He's currently pursuing a PhD at Pardee RAND. You can follow him on Twitter, @DavidManheim.

Prescientific Organizational Theory

Organizational Theory isn’t a science, though it would like to be. Unfortunately, building a scientific approach requires understanding from a number of fields that themselves are still only aspiring to be sciences. Because psychology, economics, and sociology are a mish-mash of rules of thumb and vague, non-predictive, and generally unfalsifiable “theories”, organizations are reduced to ad-hoc rules and guesswork: critical, but prescientific.

For now, to abuse the parable of the blind men and the elephant, organizational theorists are still groping at their respective elephants, unable to figure out that the trunk is next to the tusks, or even that they are part of the same animal. It’s not a science: if anything, it’s a field of engineering, albeit one without a grounding in physics or Asimovian psychohistory to draw from. Precisely because the field isn’t scientific, understanding the engineering rules of thumb that were developed over time is fantastically useful for a practitioner.

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The Future of Compromise

Whether it is in stopping quarrels between children or in deciding any of the thousand issues that come up in a large household, Anita can always make up her mind and keep things moving. A family such as ours must have a strong, capable leader.
(Strong, capable tyrant, I said under my breath.)
-Robert A. Heinlein, Friday

Getting things done involves a strong dose of leading with a vision, and ignoring those that disagree. When such leaders are given the reins, the forward progress can sometimes, post-hoc, justify trampling others. Of course, when men do this, it’s called leadership, but when women do it, even when they are doing the same things, the research shows that it’s likely to be referred to more negatively . On the other hand, once given the reins, a rising tide can lift all boats . Successful leaders ensure that enough of the progress is towards shared goals, so that the rising tide compensates the trampled masses. But it doesn’t always work out.

The key difference between leaders seen as heroes after the fact and those seen as villains is the post-hoc consensus that what they accomplished was good. (Gender stops mattering in retrospect.) The tension between disagreement now and perceptions in the future illuminates the essence of how democracies fail — but also how politics can promote wider success. I think this dynamic shows deep reasons that compromise can be reached, that decisions are not impossible, and that politics doesn’t need to destroy our ability to move forward.

Of course, the US may still be royally screwed.

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Overpowered Metrics Eat Underspecified Goals

“Alice: Would you tell me, please, which way I ought to go from here?

Cheshire Cat: That depends a good deal on where you want to get to.

Alice: I don’t much care where.

Cheshire Cat: Then it doesn’t much matter which way you go.

Alice: …So long as I get somewhere.

Cheshire Cat: Oh, you’re sure to do that, if only you walk long enough.”

Lewis CarrollAlice in Wonderland

Like Alice, most organizations, and most people, have goals that haven’t been articulated clearly enough. I call these rough ideas “underspecified goals” — we only sort-of know what we want. That’s normal for any complex process; when writing, my ideas coalesce only once they become more concrete. Novelists sometimes say that the story got away from them, when the characters behaviors don’t lead to the outcome the author had initially imagined. This can lead to slight narrative flexations, or a full out revolt of the characters.

This happens outside of writing as well, and specifically, in organizations. But it isn’t always a handicap. An explanation of why and how it happens is required to know when this underspecification is benign, or even useful, and when it’s harmful. And that understanding, in turn, will lead us to some conclusions about how, in the latter case, we can mitigate the problem or fix it completely.

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Goodhart’s Law and Why Measurement is Hard

The other day, I was failing to teach my 3-year-old son about measurement. He wanted to figure out if something would fit in an envelope, and I was “helping” by showing him how to measure the width of the envelope, then comparing it to the width of the paper he was trying to insert. It turns out that this is a trickier concept than I had assumed; the ability to understand even simple measurements requires a fair amount of cognitive maturity. 3-year-old kids can compare directly, but the concept of using a measure to compare indirectly is more difficult. I finally let him try to fit the paper in the envelope to see it wouldn’t fit.

As with many other cognitive skills, the fact that it’s a counter-intuitive learned skill for children means that adults don’t do it intuitively either. So why are measures used? There are lots of good reasons, and I think a useful heuristic for understanding where to use them is to look for the triad of intuition, trust, and complexity.

Measuring a Network

Measurement replaces intuition, which is often fallible. It replaces trust, which is often misplaced. It finesses complexity, which is frequently irreducible. So faulty intuition, untrusted partners, and complex systems can be understood via intuitive, trustworthy, simple metrics. If this seems reductive, it’s worth noting how successful the strategy has been, historically. Wherever and whenever metrics proliferated, overall, the world seems to have improved.

Despite these benefits, measuring obscures, disrupts, and distorts systems. I want to talk about the limitations of metrics before expanding on some problems that are created when they are used carelessly, and then show why the problem with metrics — and algorithms that rely on them — isn’t something that can be avoided.
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Go Corporate or Go Home

If you’re in Silicon Valley, you might have missed the trend, but the percentage of American workers working for big companies has been increasing, even as corporate bureaucracy is getting more stifling. Strangely, this has been happening even as the companies issue press releases about being more flexible and adaptive, to compete with startups, as Paul Graham argues in his recent controversial essay on Refragmentation. But flexible seems to mean layoffs and reorgs into ever more complex and, yes, fragmented corporate structures. They aren’t slimming down into flexible startups.

Worse, startups scale into big companies, and transform into bureaucracies when they do. Harvard Business Review just came out with some advice on how to stop being a startup. Even startups can’t stay startups. Github, the catalyst for distributed software companies everywhere, is itself restructuring. As the author of this post on Github’s restructuring puts it, “Out with flat org structure based purely on meritocracy, in with supervisors and middle managers.” But why?

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