Key performance indicators (KPIs) have long been seen as imperfect, yet they’re the closest we can get to understanding how one’s actions are impacting business performance. Did updating our CRM system increase the number of new customers signed per month? Did going with the cloud ERP increase net profit margins? Did the new IT service management system decrease the volume of IT trouble tickets?
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For technology teams, pumping up these metrics has always been the holy grail of project success. Yet, these metrics can be flawed and often only provide a one-dimensional picture of how something performed.
Another use case for artificial intelligence arises: 3D key performance indicators. AI is seen as a way to help smooth out the inherent flaws of KPIs, and thus, provide a much more accurate and holistic picture of how businesses are really performing.
More than a third of organizations, 34%, are now doing just that: They’re leveraging AI to create the next generation of these key performance metrics, according to a survey of 3,043 executives by MIT Sloan Management Review and Boston Consulting Group’s BCG Henderson Institute.
For example, AI can surface and analyze interdependencies between KPIs that formerly were seen as unrelated to business results. “Forward-looking organizations are benefiting from using AI to generate KPIs that are more intelligent, adaptive, accurate, and predictive than legacy performance indicators.”
More than half of the participating executives acknowledge they need more impactful KPIs. “They fall short in tracking progress, aligning people and processes, prioritizing resources, and advancing accountability,” the study’s authors point out. “Companies that use the same old KPIs to measure success are missing out on opportunities to better align people and processes, prioritize resources, and generate value.”
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How is AI doing in unwrapping such metrics and providing a more holistic picture of how the business is performing? So far, so good. Organizations using AI-enabled KPIs are five times more likely to “effectively align incentive structures with objectives compared to those that rely on legacy KPIs,” the MIT-BCG authors conclude.
They cite the example of Wayfair, the online furniture retailer, which employed AI to redesign its lost-sales KPI. “We used to think that if you lost the sale on a particular product, like a sofa, it was a loss to the company,” Fiona Tan, CTO of Wayfair, is quoted. “But we started looking at the data and realized that 50% to 60% of the time, when we lost a sale, it was because the customer bought something else in the same product category.”
With the help of AI-generated insights, Wayfair reengineered its lost-sales KPI from simply “calculating item-based lost sales in response to price changes to also calculating category-based retention of sales in response to price changes,” the report states.
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Nine out of 10 executives with AI-enhanced KPIs have seen a similar wider reach in their KPIs. Overall, they have seen a four-fold increase in collaboration between employees. They are also three times more effective at predicting future performance, three times more likely to see greater financial benefit, and twice more likely to see greater efficiency.
Three forms of 3D metrics can be designed with AI, the MIT-BCG authors suggest:
- Smart descriptive KPIs “synthesize historical and current data to deliver insights into what happened or what is happening.”
- Smart predictive KPIs identify patterns and “anticipate future performance, producing reliable leading indicators and providing visibility into potential outcomes.”
- Smart prescriptive KPIs “use AI to recommend actions that optimize performance.”
The time has come to re-examine the assumptions behind many traditional KPIs, the report’s co-authors urge. AI is opening up new ways to explode the legacy, one-dimensional KPIs that have dominated business thinking.
