To tackle the age-old challenge of aligning operations with core business strategy, savvy business leaders are using artificial intelligence to help use and develop key performance indicators.
AI-enriched KPIs, known as smart KPIs, can better guide organizations toward key business goals. Smart KPIs paint a more detailed and accurate picture of what’s happening in the business: They provide predictive insights and situational awareness that can help organizations improve performance and foster better coordination among corporate functions.
A global survey of more than 3,000 managers conducted by MIT Sloan Management Review and Boston Consulting Group found that executives across industries are using AI to enhance how KPIs are prioritized, organized, and shared while also improving KPI accuracy and predictive capabilities.
Survey respondents who said their company had used AI to prioritize KPIs were 4.3 times more likely to have seen improved alignment between functions than those who had not used AI.
The research team identified three types of smart KPIs:
Smart descriptive KPIs synthesize historical and current data, serving up insights on past and current performance while providing context on critical gaps. The results are more effective KPIs and a better understanding of KPI relationships.
Smart predictive KPIs anticipate future performance and provide visibility into potential outcomes while highlighting preemptive actions that will mitigate risk or expand opportunities. For example, General Electric is using smart KPIs to analyze order pipelines to identify opportunities for increased future orders.
Smart prescriptive KPIs go beyond description and prediction to make AI-recommended suggestions for corrective measures. Sanofi, for example, employs smart KPIs to adjust sales metrics based on supply chain performance.
Shared and connected KPIs
Companies are also using AI to discover interdependencies among indicators, with the goal of creating KPI “ensembles” that bundle distinct KPIs for connected business activities. AI can help link KPIs, even if they span multiple functions and stakeholders, such as profit margins and market share. By breaking down silos and increasing collaboration, KPI ensembles can advance cross-functional performance.
AI can also enhance KPI information sharing and collaboration. According to the survey, companies that use AI to share KPIs are five times more likely to improve alignment between functions and three times more inclined to be agile and responsive compared with organizations that don’t.
Other leadership takeaways from the research:
Treat KPIs as assets. Just as organizations identify, cultivate, train, and develop talent, they should do the same for KPIs. Taking an intentional approach to determining which KPIs would benefit from AI enrichment or should become predictive and forward-looking will result in higher-quality actionable insights and recommendations.
Promote visibility and transparency. Making KPIs more visible clarifies accountability and creates a greater sense of shared purpose. The C-suite should commit to AI-related resources that improve the transparency of KPIs and democratize access to credible performance data in order to improve alignment.
Connect the dots between KPI relationships. Use AI to map, model, and manage performance drivers and KPI priorities so people in the enterprise can see how everything relates. Doing so helps identify which KPIs should be shared and establishes KPIs as more effective assets.