Following on from Part 1, another of the legacy habits that can sneak surreptitiously into our XmR charts and make them incapable of highlighting the real signals in our performance measures, is focusing on the wrong performance measure!

Some legacy habits with how we analyse our data often sneak surreptitiously into our XmR charts, and these habits make our XmR charts incapable of highlighting the real signals in our performance measures.

You won’t find true signals of changes in performance by looking at month-to-month comparisons, or trendlines, or moving averages. The signals you really need to know about, the only signals that you ought to respond to, are revealed through one particular graph only.

This checklist of 5 basic KPI formulas, with examples for each one, will help you decide the best way to calculate your KPIs. (more…)

When it comes to cause analysis for performance measures, many people put the cart before the horse. They rush too quickly to analyse their data without first establishing a clear purpose. (more…)...

One of the ways that people like to classify their KPIs and performance measures is by whether they are quantitative or qualitative. Should we do it? And if we do, are we doing it right? (more…)

5 Stars -- My go-to resource for performance report design Okay, I'll admit that I haven't read "Show Me The Numbers" from cover to cover, even though I've owned a copy (a signed copy!) for a few years. But it's not the kind of book that requires this to get the value from it.

5 Stars -- Save millions of dollars by reading this book first... Over my many years as a performance measurement specialist, I've worked with quite a few organisations who built performance dashboards that cost them many hundreds of thousands of dollars to design, tailor, populate and launch, and got very little value from the investment.

4 Stars -- Interpreting data is about the patterns, not the points This is not a book for people looking for the technical detail of data analysis or statistical process control. The pearl in this book is the message that interpreting your data (such as KPIs or performance measures) is about looking at patterns, not at individual points. It's a book that can...

Data quality worries most users of performance measures. There is an obscene number of reported measures that only generate dialogue about how unreliable the underlying data is, rather than how performance can be improved.