How to overcome "Cartesian anxiety"

A few months ago, James Pomeroy of the Arup consultancy group published an article in LinkedIn on what he called "Cartesian anxiety"—the fear that, without proper planning and metrics, we are all lost. And yet, Pomeroy continues, planning and metrics can never prepare us for every eventuality.

Pomeroy's argument should sound familiar to regular readers of this blog. He begins by describing a mindset that he finds to be common among professionals in Quality, safety, and environmental management. He calls this "a PDCA mindset," and describes its fundamental tenets as follows:

• Planning is Paramount
• Variance is to be Controlled
• Measurement is Everything
• Causality is King
• Hindsight Bias

We've discussed many of these topics before. (See the embedded links for some relevant posts.)

But then Pomeroy goes on to point out just how fragile these assumptions are. In normal operations, of course they are fine; in fact, in normal operations these principles more or less define how to function best. But "in situations of significant uncertainty, high levels of complexity or a continually emerging environment, deterministic methods such as PDCA become problematic." These methods break down because they rely on certain preconditions to operate.

• In order to plan, you have to know what the default future will look like (before you act), so that you can assess what to do. 
• In order to measure, you have to know what to measure and you need a way to observe it without disturbing it. 
• In order to form any kind of cause-and-effect analysis, you need enough data to understand what interacts with what, and you need a clear understanding of how they interact—an understanding, so to speak, of which direction the causal arrows point. 

And under conditions of serious uncertainty, high complexity, or rapid change, none of those preconditions obtain.

Does that mean that when things get crazy, then all is lost? Not at all, says Pomeroy. But at that point the organization has to rely on other tools besides planning and measuring. He tells the famous story of the Hungarian soldiers lost in the Alps, who were saved by following the wrong map.* And he argues that in times of crisis it is better for the organization to do something, see the outcome, and react promptly—"feeling" its way through the tumult—rather than to wait for things to settle down far enough that the planning process can engage. He concludes that "by embracing [this kind of] agility ... we can use trial and error to 'feel' our way through complex situations and navigate uncertainty. This is the focus on doing over planning, trialling things and seeing what works, and adapting to an ever-changing situation."

It's a reasonable argument, and in fact we have seen something like it before. Nearly four years ago, I wrote a series of posts** drawing on a talk by Jeff Griffiths about "People Before Process." Over the course of these posts, I talked about the difference between organizations that have a process focus and those that have a competence focus. Of course in real life, any organization needs both. But I concluded that while in many ways leaning into a process focus scales and replicates faster than leaning into a competence focus, it is also more fragile. A competence focus, by contrast, is more resilient when things go wrong. (See especially the long discussion in Part 3.) The reason is precisely the one Pomeroy highlights: in a crisis, you don't have enough time or data to use the conventional tools of the process focus. You have to be nimble and improvise. And the higher the overall competence of your people, the more capably and creatively you can improvise.

In fairness, I have to make one other point. Pomeroy is not arguing that any organization in crisis should throw its rational tools out the window to navigate purely on vibes. If you look at it, the approach he promotes is topologically identical to the PDCA cycle: decide to do something, do it, see what happens, and react. The difference is in the time-scale. Organizations in crisis don't have time for lengthy data collection or analysis, and often may not even know which data are relevant. So the selection, the analysis, and the decision all have to be done by informal methods. But those informal methods themselves rely on the competence, expertise, and intelligence of the executives making the decisions. Nobody's going to suggest leaving the decisions to the toss of a coin or to ChatGPT.

It's a good article—by all means go read it—and it supports the basic point I always try to make here. All of the Quality principles are sound, as principles. But the point is to get results, not to follow the rules. That's pragmatic.     

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* This story derives from a poem by Miroslav Holub, recounting a story told by Albert Szent-Györgyi about a scouting troop of Hungarian soldiers in World War One. You can find the poem here. Briefly, the troops got lost in the snow and expected to die. Then one soldier found he was carrying a map of the mountains. After the troop used the map to return to base, they realized it was not a map of the area where they had been! 

** Here are the links: Part 1, Part 2, Part 3.