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What AI Can Teach Us About Designing Better KPIs
Machine learning research offers four proven strategies to prevent people from gaming measures of organizational performance.
Listen to “What AI Can Teach Us About Designing Better KPIs” (23:09)
In 2016, Wells Fargo found itself embroiled in scandal when headlines revealed that its employees, under pressure to meet aggressive sales targets, had opened millions of unauthorized customer accounts. The root cause wasn’t just unethical behavior but a flawed approach to performance measurement. When Wells Fargo’s leadership incentivized employees to sell eight financial products per customer, they inadvertently encouraged gaming behaviors that harmed customers, employees, and ultimately the bank itself. The metric had become more important than its underlying business purpose.
Although Goodhart’s law in action only sometimes rises to the level of scandal, companies everywhere fall prey to it: “When a measure becomes a target, it ceases to be a good measure.” Despite decades of warnings against metric fixation, leaders continue to build incentives around narrow indicators, which results in gaming and ethical lapses and harms business performance.
Traditional solutions to overcoming Goodhart’s law, like balanced scorecards and KPIs, often fail because they remain vulnerable to narrow optimization and gaming behaviors in the absence of careful oversight. The persistence of metric fixation signals a need for a more sophisticated approach to address the problem.
https://sloanreview.mit.edu/article/what-ai-can-teach-us-about-designing-better-kpis/
