What's Wrong With Data-Based Decision-Making?
Data Science Central, Wednesday, April 23rd, 2025
Whether launching a new product or changing an existing one, decision-makers are relying on data more heavily than ever. Today, we can track customer behavior, competitor prices, demand shifts, and even the performance of our products through countless metrics from complex data systems. But when does data-based decision-making go wrong? And what can we do about it?
In this article, I'll discuss some common gaps I've seen in data-driven decisions at large and medium-sized companies (like Google, EY, and others) and share a few ideas we've used to close those gaps.
Where things go south
Let's break down the process, from data gathering to making decisions, as errors can happen at every stage, including data import, data processing, interpretation, and the final application of the results. (The list below is by no means exhaustive and serves rather an illustrative purpose and as a warning signal against overconfidence when dealing with results.)