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Performance Metrics Inventory Database
Over time, leaders can grow their performance measurement systems to include almost countless numbers of interrelated metrics. Ensuring these numerous metrics remain well aligned, their output quality and relationship integrity preserved, and their meaning well understood while continuing to be of value to executives, managers, and employees necessitates a method of inventorying the measures themselves and their underlying construction characteristics. In our experience, the optimal method for maintaining such an inventory is through the use of a centralized metrics inventory database.
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About the Author
Nathan Ives is a StrategyDriven Principal and Host of the StrategyDriven Podcast. For over twenty years, he has served as trusted advisor to executives and managers at dozens of Fortune 500 and smaller companies in the areas of management effectiveness, organizational development, and process improvement. To read Nathan’s complete biography, click here.
A performance measurement system’s complexity and organizational impact can bring with it many people, process, and technology challenges post implementation. For several months following a system go-live or significant upgrade, the organization adjusts its processes, procedures, and behaviors so to achieve the best possible reflected performance. This evolution is not without its costs or problems.
Organizational performance measurement systems are complex constructs that significantly impact leadership decisions, employee behaviors, and management processes and systems. Consequently, there are often many people, process, and technology challenges associated with the implementation or significant upgrade of such monitoring systems. By understanding these potential risks, leaders can put in place mitigating instruments to reduce the overall organizational impact and increase the likelihood that the new measurement system will be accepted and have the desired positive impact on performance.
When developing the picture of organizational performance, many leaders view their metrics in clusters aligned with the organization’s hierarchical structure. While logical, such groupings cannot capture the cross-functional nature of many business processes, systems, and applications. Consequently, the organization’s monitoring system may provide the appearance of healthy performance that is inconsistent with what managers know to exist. Regrouping organizational performance measures often reveals these known issues and brings to light other previously unseen improvement opportunities that can yield great value to the business.
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