There’s a better approach to getting the most out of key performance indicators. John Rodgers and Vinod Prashad outline strategies for organizations to measure meaningful metrics and unlock the potential of their KPIs in this Financial Executives International article. Read a preview of the article below.

Key Performance Indicators (KPIs) are present at nearly every level of the leading U.S. corporations—from their HR departments, to finance, to marketing, to sales. On paper, KPIs serve a very useful function: they quantify performance over a period of time, giving teams targets to hit, establishing milestones in a company’s journey toward its goals, and providing leaders with insights that can steer the ship toward greater efficiency and profitability.

However, in the age of advanced analytics, where organizations rush to incorporate the latest in analytics into aging infrastructures, companies keep building up their list of KPIs while losing sight of the big picture. Ironically, many companies that try to incorporate more data just end up with more reports that aren’t used and the data itself becomes less useful. Imagine someone intending to knit a sweater but instead starts tunnel visioning on making more and more loops, without connecting them back to the already-woven fabric. The loops become an end in themselves. This is what organizations are doing by over-indexing on KPIs—making the means the focus, not the end. Companies need to think beyond the “loops” to connect with the fabric of the bigger picture.

While there isn’t a magic number of KPIs that is correct for everyone, each company does need a well-organized set of metrics. Without a bold strategic vision that prompts action—one step in a larger culture shift toward decision making—KPIs quickly lose their standalone value. KPI measurements must be cohesive, each one building off the next link in a cascading chain to guide the organization forward. Companies are often enticed by the emergence of new data sources and lower data collection costs, misleading them into creating a glut of data. This unnecessary data, or data not tied to a specific purpose, takes time and resources to sift through, eating into the added value that these systems initially promised.

Read the full article HERE