There are many approaches to building key performance indicators including the balanced scorecard, value imperative, and value code to name a few. We agree with many of the high level thrusts that can be gleaned from these approaches, although we also recognize that every organization is unique. Beyond the high level maxim that "You can't control what you don't measure", the definition of those specific key indicators whose implementation and use would bring the most measurable benefit to your organization can vary substantially from organization to organization.

At DSS lab we have extensive experience designing and implementing key performance indicators. Over the years we have dealt with such complexities as

• Defining rules for the inclusion/rejection of specific indicators
  
• Defining hierarchical indicators
  
• Creating composite indicators
  
• Merging indicators from multiple sources (for example, divisions or newly merged entities)
  
• Creating systems of indicators where lowest-level definitions or variables must vary from region to region or division to division
  
• Performing weightings-based sensitivity analysis
  
• Developing routines for checking data quality for raw level indicators
  
• Defining and implementing interpolation rules for working with missing indicator data

along with presentation interfaces for delivery in a variety of formats.

Indicators/metrics are an important piece of a larger puzzle: the analytical specification and information requirements.

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