A Sneak Preview
The Fewer Assumptions the Better.
The reality of business is inherently complex and, as a result, strategic choice is risky. We will never be able to know for sure how our choices will turn out. It follows that, to paraphrase Phil Rosenzweig, the primary task of strategic leadership becomes to gather information and consider it thoughtfully, then make choices that, while risky, provide the best chances for success in a competitive industry setting. The only way to lower that risk and limit uncertainty is by ensuring one makes as few assumptions as possible, both in terms of the outside (customers, rivals, technologies) and the inside (casual ambiguity relating to internal capabilities).
This is no revolutionary truth — Occam’s razor states that “when presented with competing hypotheses to solve a problem, one should select the solution with the fewest assumptions” — but it remains true nonetheless. The more assumptions made, the more potential points of failure and opportunities to be wrong. There is a significant difference between being 90% correct 90% of the time, and being 100% correct 10% of the time. Or to put it differently: assumptions may lead you to be largely correct, but also hugely wrong.
The key to removing assumptions is acknowledging our propensity towards them in the first place. No matter how certain of the contrary one may be, we all view the world subjectively through lenses that have evolved across millennia. Consequently, we are susceptible to narrative fallacies, confirmation biases, illusory superiority, clustering illusions and halo effects. While this affects how we interpret data, we can decrease the degree to which results are skewed: by valuing data over anecdotes, quantifiable experience over generic advice and critical thinking over alluring promises.
Every analysis will be biased, every model will have its assumptions, so it is imperative that we identify what they are, keep them to a minimum and practice our Bayesian thinking.
