4 problems with traditional performance analysis

There are four main problems associated with traditional approaches that we need to overcome if we are to make the process of understanding and communicating performance fit for the modern world:

1. They’re too static 

Performance is continuous but conventional approaches present us with a series of snapshots separated in time. As a result, trend information is blurred, and patterns of cause and effect are hard to detect.

2. Failure to distinguish between signals and noise 

Data carries signals but is also unavoidably infected with noise. Conventional approaches do not enable us to distinguish between the two. Because we do not recognize the existence of noise, we falsely assume that any difference between the two numbers is meaningful. 

And by acting on corrupted information, we often amplify the noise, hence making it even more difficult to distinguish fact from fiction. 

3. Confusing variance with performance 

Comparing ‘point’ targets to actual outcomes is an unreliable guide to real performance because of the existence of noise and because targets are usually set without any sense of context many months in advance, often by an arbitrary or politically-driven process. 

4. Not taking account of the brain’s processing limitations and strengths 

Our capacity to collect data is unlimited but the bandwidth of our brains is fixed and subject to ever-increasing demands. Conventional approaches to analysing and communicating performance, using numbers alone, are difficult for brains to process. This is inefficient and increases the risk of confusion and misinterpretation.

This is an extract from Steve Morlidge’s latest book, Present Sense. Steve spoke at a recent GenCFO event.

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