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2 minutes reading time (489 words)

Leadership vs Management in Change and Crisis

Leadership-vs-management_A

There’s a fascinating emerging set of literature on true leadership (versus management) of crises. One of the signal books in this genre is Upstream: The Quest to Solve Problems Before They Happen by Dan Heath. The author explains that true leaders are people whose names you don’t know. Why is that? Because true leaders use tools such as Latent Effects Modeling to discover in time T1 (i.e., now) what they will need to be worried about in time T3 (i.e., years later, when the bad thing could actually occur).

True leaders confront the latent effect now and develop remedies now, often quietly and without fanfare so that in time T3 the problem has vanished or is a dud.

Managers, on the other hand, are celebrated. They are seen to “grip the problem” and show a can-do attitude about fixing the mess that’s been created. We need information! What’s the size of the problem? Bring the statisticians in quickly! Let’s have a task force to manage this crisis with discipline and resolve!

This is not to disparage titans of government, industry, and the military who gained fame for their management. It’s to remind us that we have grown comfortable with a leadership paradigm that allows the proverbial “poop” to hit the fan, then look around desperately for someone to rescue the matter.

Under this paradigm, all manner of predictions are demanded from data modelers after the bad news hits. But there’s really no voice amid the din to say, “the science of prediction could have been managed in a more humanity-serving way.”

Leadership Starts With Asking The Right Questions

True leaders could potentially ask astoundingly good questions about what they should be worrying about now if they have the will to do so and enlightenment to listen to the results. Here are just a few rough ideas:

  • Looking at demographic data in China, there’s a jaw-dropping shortage of women. (We won’t go into the reasons right now.) What latent effects are discoverable in those data? Could regime change be one of them? Are there other latent effects that could be detected?
  • Looking at US electoral data, more and more candidates for Congress are being elected from the extreme right and left, and fewer from the political center. What latent effects are discoverable in those data? Could we be moving toward a new form of government that’s hard to define right now? Are there other latent effects that could be detected?
  • Looking at workforce data, more and more workers’ tasks are being undertaken by robots or AI-driven programs. What latent effects are discoverable in those data? Is a new American aristocracy one of them? Is a proletarian rebellion one of them? Are there other latent effects that could be detected?
  • Any way you cut it, humanity is better served asking data scientists “what should we be worried about?” rather than it does to ask data scientists “how large is the problem?”
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