The COVID-19 pandemic has revealed deep flaws in some widely used advanced analytics techniques.
One of the most widely used advanced analytics techniques, machine learning, relies on historical patterns of data to predict future behavior. Models which rely on machine learning have been thrown by the profound changes in the way we live, shop, work and spend our free time.
While analytics professionals clearly have an important role to play in stabilizing business critical models, leadership must recalibrate their business strategies in response to an ever-shifting landscape. Through using a framework to strengthen their company’s analytics strategy and prioritize their model risk strategy efforts, business leaders can more effectively evaluate and resolve the risks arising from the pandemic.
Regularly reevaluating and prioritizing the models in use, exploring new data sources, and making a firm commitment to agile processes will all be critical for leaders to ensure their organization’s resilience in this current crisis. As we move out of the crisis, leaders will also need to take steps to help their businesses respond more flexibly to what lies around the corner.
This article was originally published on McKinsey.com on September 1, 2020, and is reprinted here by permission.