Leadership’s role in fixing the analytics models that COVID-19 broke

COVID-19 has upended life as we knew it, and our new behaviors are wreaking similar havoc on some analytics models that rely on historical data. How can leaders enable teams to get analytics back on track?

 
The COVID-19 crisis has put a spotlight on the power and potential of analytics and artificial intelligence. We have heard from leaders across industries and geographies about the many ways analytics have enabled them to more effectively handle the challenges presented by these unprecedented times, from supporting and protecting workers to engaging increasingly digital customers and managing fragile supply chains.

But the crisis has also revealed the technology’s Achilles’ heel. One of the most widely used advanced-analytics techniques—machine learning—relies on the principle that patterns and behaviors from the past will likely repeat in the future. Algorithmic models expose these patterns in data and draw on them to predict what will happen (such as whether a particular customer will cancel a service) and even recommend what the business should do (for example, identifying which offer will most likely change a customer’s mind). This was effective until the pandemic transformed the way we live and work. Lockdowns, travel bans, physical distancing, and widespread furloughs have altered how we shop, where we perform our jobs, how—and if—we travel, and more. Even as communities reopen, we’re a far cry from business as usual.

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Πηγή: mckinsey