Data-driven Decisions and Why they Work, Part 2

Last week, I introduced you to the flaws of gut instinct and the harsh realities (but necessary wake-up calls) that data can demonstrate as well as author and Nobel Prize winner Daniel Kahneman’s “prospect theory,” which describes how people choose between different options (or prospects) and how they estimate (with bias) the perceived likelihood of these options. Now, let’s talk about how to avoid mistakes that our biased minds are programmed to make.

Consider the data that comes from a Customer Relationship Management (CRM) system. It can house millions of transactions that include objective data such as a product number, sale price, date and time of sale, sales territory, and more. That can be far too much data for an individual, a team, or even an entire department to analyze and leverage within a reasonable time. But add data analytics and business intelligence software, and a computer is able to crunch these numbers within seconds. It can quickly provide insights such as trends, anomalies, and risks, saving us hours of sifting through raw data and enabling us to focus on what is most helpful to assess.

Let’s return to our friend Don Draper. Often, executives may find data-based results that are contradictory to their initial understanding or prediction. Perhaps they are emotionally invested in a new product; however, data showing a clear lack of customer interest may give Don, or rather, executives, the wake-up they need to focus on more profitable products. In a different scenario, maybe there is a high rate of customers buying a certain subscription that an executive interprets as a clear winner; however, data showing low renewals of that subscription after the first month will give them a bigger picture, and prompt them to investigate subscriber churn.

Those are just two examples of numerous scenarios. Systems are continuously generating all types of data: supply chain, manufacturing performance, marketing, social media data and so much more. And there is no need to put the burden of this on your employees; let the computers handle the number crunching.

I do not mean to downplay the expertise and experience of all executives. However, in a time where the ability to combine their experience with data-driven insights is becoming increasingly available, acting on gut instinct alone is no longer the best recipe for success.

Do you tend to rely on data to support your decision-making? Or do you mainly rely on gut instinct?