Three Types of Performance Measure Relationships

November 4, 2009 by Stacey Barr

If you think about when organisations work well, it’s because all the parts are coordinated together and managed as an integrated whole. And that’s a very good reason why we ought to treat our performance measures the same.

By understanding how measures are related to one another, you increase their power to help you understand and diagnose performance, and thus how you can report those measures together to make performance understanding and diagnosis easier.


As the most commonly talked about relationship between measures or KPIs, the cause-effect relationship isn’t too hard to understand. It simply means that when one measure improves or deteriorates in performance, it causes another measure to improve or deteriorate in performance as a consequence.

For example, reducing rework can cause costs to reduce; improving recruitment of talent can cause workforce capability to improve; if employee engagement slides then it can cause customer satisfaction to slide too.


Measures have a companion relationship when they each tell a part of a complete story of performance. If you relied on just one of the measures, you wouldn’t have a full enough picture to take the best action.

For example, number of new prosects and prospect conversion rate are companions to track a marketing process; customer lifetime value and number of active customers are companions to understand drivers of profit.


Because you can’t have your cake and eat it too, you often can’t maximise the performance of any one measure. Other measures of performance can pay the price, and that’s where you get conflict relationships between measures.

For example, improving workplace safety can conflict with on-time delivery to customers; reducing call handling time (in a call centre) can conflict with first call resolution; improving product quality can conflict with cost reduction.

Look at one of your organisation’s performance reports, and the suite of measures or KPIs it includes. How are these measures related to one another? Does this appreciation of the relationships suggest any opportunities to improve the way your report the measures, so they are more useful?


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