Thoughts about thinking about business

“When a colleague admonishes us to ‘quit complicating the issue,' it’s not just an impatient reminder to get on with the damn job—it’s also a plea to keep the complexity at a comfortable level.”
--Roger Martin


One of the first things I found odd about working in business, or at least the odd part of the business I was in (advertising), was how hard it was to define the thinking we were supposed to do.

Everyone was pretty clear that, as a planner, I had the luxury to “think” about my clients’ business, but they were less clear describing how I should go about it. Looking around for examples, it seemed that thinking could mean a whole bunch of things but none of them bore much resemblance to what I thought thinking was in my old life as a perpetual graduate student, studying Literature and Economic history.

So I was pleased to see that an intriguingly titled article “How Successful Leaders Think” in the June issue of The Harvard Business Review by Roger Martin, Dean of the School of Management at the University of Toronto.

http://harvardbusinessonline.hbsp.harvard.edu/hbsp/hbr/articles/article.jsp?ml_action=get-article&articleID=R0706C&ml_page=1&ml_subscriber=true

I liked a lot about it, not least a refreshing critique of the relentless push for forced simplicity quoted above and which nicely supports my general mission here.

Also refreshing was the diplomatic acknowledgment that most business leaders, even successful ones, are not very self-aware about their own decision-making processes, using the heralded bio of Jack Welch as a paradigmatic example. However much we might think (or remember) that we simply used our guts or searing, prophetic insight to make a decision, the truth is that most of us do try to evaluate the costs and benefits of high-stakes decisions. We think about it first, though not necessarily in an empirical, or research-driven way.

Martin describes a cognitive process called “integrative thinking” which he opposes to a more linear cost-benefit analysis of two existing options, which generally leads to unpleasant trade-offs. Successful leaders, he claims, don’t settle for an “either-or” scenario, but look for synthetic or innovative solutions by taking a wider and more holistic view of the challenge. Using Fitzgerald’s old chestnut about high intelligence being defined by the ability to “hold two opposing ideas in the mind” to define the foundational cognitive act, he maps out a three-stage process:

1) Determining Salience: identifying the relevant factors even if they aren’t obvious
2) Analyzing causality: searching for surprising relationships between these factors
3) Envisioning a decision architecture: this is Martin's weakest category and means, roughly, don’t lose track of the best solution by delegating various parts of the analysis to different people who will miss the forest for the trees

This strikes me as fine and good, but less because it’s so ground-breaking then because it’s a clear description of what I’d call old-fashioned conceptual thinking, as I used to do it and attempt to teach it in graduate school when I was studying the humanities and social sciences. Though my steps were a little different and more evaluative than prescriptive (they were designed to help students write papers after all) they amount to another version of the same thing:

1) Determine the factors/categories/experiences that are really important in the data set
1a) Pay as much attention to what’s surprisingly missing (e.g. a book about a relationship without any mention of desire) and irrelevant as what is included and emphasized.
2) Determine relative value/influence of these various factors in terms of how they interact and impact the data set as a whole.
2a) What factors are validated and what are under-valued? Are the factors dynamic or static?
3) Develop a hypothesis/story to explain the data set which has captured your attention or seems particularly important
4) Then test the hypothesis/story up against contradictory data. Can you come up with a story that explains the contradictory data? 5) If you can’t make it work, evolve the hypothesis or start over with a new data set.

Business doesn’t take conceptual thinking too seriously as a real discipline, probably because it sounds too soft, too theoretical, at least compared to the catch-all category of Quant or statistical analysis which is the most convincing form of evidence for most business people. (Martin also mentions the reliance on regression analysis as the favorite tool of simplicity seekers). Or maybe it’s because business education relies so heavily on a case study model which facilitates the impulse to “search and reapply” which I’ve witnessed among so many M.B.A.-trained colleagues.

It’s weird because business—with it’s complex systems, susceptibility to social-cultural factors, radically dynamic relationships and need for overarching explanatory stories—seems more suited to conceptual thinking than quantitative analysis which is a better tool for analyzing existing data sets or studying phenomena in controlled environments.

But as Martin rightly points out, complexity makes most of anxious, even if the ability to analyze more factors generally leads to more innovative solutions.

Maybe I’m missing something obvious (the vice of the complexity-embracer), but for the time being, I’m going to continue defending old-fashioned thinking (whatever you call it: integrative, conceptual, critical) as the first tool of choice for solving business problems.