AN EXCERPT FROM “THE DARK SIDE OF BI” “THE ILLUSION OF ACCURACY” BY NAKEL NIKIEMA Numbers have a way of captivating us like nothing else in business and everyday life. When a salesperson announces a projection of 16.3% growth in quarterly revenue, we feel it’s truer than if he simply said, “We think sales will increase by around 15 or 20%.” 49 Millennium - Twentieth Edition BUSINESS, FINANCE AND ENTREPRENEURSHIP We see decimal points and assume that a rigorous process has been carried out: data has been collected, models have been run, and each step has been a meticulous progression that has led us to an indisputable truth. Precision, or at least its appearance, instantly creates a sense of authority. And because we generally respect authority, exact numbers can short-circuit our natural inclination to question and doubt. And why is that? Much of it stems from the way we’ve been taught to see math and science. From an early age, we learn that numbers represent solid, factual knowledge. The multiplication table never lies, and a geometry problem solved correctly will always represent an accurate answer. This sense of certainty becomes ingrained in our thought processes. In a world full of ambiguities, especially in business, politics, and social problems, numbers are like islands of stability. So, a pie chart detailing a 27.45% customer conversion rate will comfort us: “Finally something real,” we tell ourselves, “something measured, beyond debate.” This cultural training, which treats numbers as facts, sets the stage for what becomes a deeprooted trust, almost like a spell of accuracy. We assume that a specific decimal or percentage will be the last word and that everything behind it has been done correctly. Over time, this can foster a dangerous environment where decisions depend on a superficial appearance of statistical rigor and “evidence-based” rather than a genuine understanding of how the numbers were produced. It doesn’t help that, in many professional environments, questioning a meticulously formatted spreadsheet or a well-presented dashboard is socially awkward or, worse, careerlimiting. It’s normal to be afraid of questioning and, in the end, to appear unprepared and even anti-scientific. The norm is to nod in agreement, especially if the figures appear in official documents or come from someone considered an expert. As a result, even glaring inconsistencies or assumptions that skip too many steps can remain hidden in plain sight, overshadowed by the hypnotic power of decimals. On top of all this, our appetite for accurate-sounding data has intensified as organizations have become more “data-driven.” During strategy meetings and project presentations, being able to say, “We forecast a 3.62% reduction in operating costs,” can be far more persuasive than the best anecdotal evidence. Team members eagerly adopt analytical tools to stand out, producing metrics that look impressive but may be based on weak premises. The more elaborate the methodology, the harder it is to discover the flaws hidden in layers of code, logical statements, and statistical assumptions. Despite all this, precision is not an enemy per se, of course. We’re not here to fight against science and numbers but against the uncritical acceptance that leads to failure.
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