Governance for Smarter KPIs

Without adaptation and refinement, static business metrics create two types of strategic risk. One is encouraging performance on the wrong measures. The 2008 global economic crisis, for example, was triggered in part by banks’ dependence on a then widely used metric: value at risk, which measures potential portfolio losses in normal market conditions at a single point in time. Financial institutions did not adjust this measure as riskier subprime mortgages and securitized default swaps became a larger part of their portfolios. Guided by a metric that severely underestimated potential losses — in some cases, by orders of magnitude — many financial institutions went bankrupt or suffered significant losses.

Opportunity costs represent another risk from static key performance metrics. Our research persuasively demonstrates that companies deliberately using artificial intelligence to design and create more dynamic KPIs enjoy greater situational awareness, stronger ties between operations and strategic outcomes, and improved results overall.1 These smart KPIs reflect deeper understandings of performance drivers and produce more reliable predictions about future outcomes than comparable KPIs not informed by AI. (See “Three Types of Smart KPIs.”) A “set them and forget them” approach to key metrics is neither desirable nor sustainable in volatile and fast-changing markets.