Measures of Success: A Book Summary for Leaders Tired of Chasing Metrics
How much time did your team spend explaining last month's numbers? And how much of that discussion helped you improve anything?
A metric turns red. Somebody has to explain it. Next month it turns green, and we move on. The meeting creates activity, but we still might not know whether the system has changed.
I wrote Measures of Success: React Less, Lead Better, Improve More to help leaders break that cycle. The book explains how to distinguish meaningful signals from routine variation, so we can spend less time chasing noise and more time improving the work.
The opportunity is to get more value from the attention you already give your metrics. You don't need another dashboard that generates more questions nobody can answer.
A short summary of Measures of Success
The central idea is straightforward: a change in a number does not necessarily mean the underlying system has changed. Process Behavior Charts help us make that distinction using data over time and rules for identifying signals.
That distinction changes how we lead. A signal calls for learning about what changed. A predictable system with disappointing results calls for systematic improvement. Demanding an explanation for every up and down can distract us from both.
“React less” does not mean ignoring customers, safety concerns, or poor performance. A stable process can still be consistently unacceptable. We need to improve it without inventing a separate explanation for every routine fluctuation.
One question to try in your next metrics meeting
Before asking, “Why did this number get worse?” try asking:
What evidence do we have that the system changed?
If all you have is this month's result and last month's result, put the measure in a longer time context. Two data points alone do not establish a trend.
That question won't replace learning the method. It can, however, interrupt the habit of demanding a story before we know whether there is a meaningful change to explain. For an introduction to the method, see my guide to Process Behavior Charts.
What the book adds beyond that question
Recognizing overreaction is a start. The harder work is knowing what to do instead, and helping other people see why a different response makes sense.
Chapters 1-3 build the foundation: how we manage metrics, how Process Behavior Charts work, and why familiar red/green reports can encourage unhelpful reactions.
Chapters 4-7 connect interpretation to improvement. They examine different responses to variation, Deming's Red Bead Game, misleading headlines, and the traps in apparently convincing trend lines.
Chapters 8-9 bring the ideas into workplace examples and the practical challenge of getting started. Appendix A provides the chart-building instructions for readers who need them.
The charts, worked examples, and explanations matter. A short list of principles can tell you to separate signal from noise; the book helps you practice doing it and decide how to respond.
A management book, even if you don't build the charts
I wrote this for managers, executives, business owners, analysts, and improvement professionals. You don't need a statistics degree or a Six Sigma belt. If you lead a metrics review, request explanations, or decide where improvement effort goes, these decisions are already part of your job.
The potential benefit extends beyond better charts. Consider the time your team could put toward improvement if it spent less time preparing explanations for routine fluctuations.
“We've saved time by not overanalyzing every up and down in our metrics — and that's valuable time we now put to better use.”
Dr. Greg Jacobson, CEO and co-founder of KaiNexus, in his endorsement of Measures of Success
See whether it fits the way you work
Read the preview with one recurring metrics discussion in mind. Does the problem sound familiar? Can you see an opportunity to change the conversation? Use the sample to decide whether the book would help you and your team.
Ready to go further? Explore editions and buying options. If you would like help applying the ideas to your own measures, learn about workshops or bring the discussion to your next leadership event.
Related reading
For examples of putting data in context, explore the Red Bead Game and comparisons of individual performance, variation in NCAA football attendance, and an analysis of the MLB pitch clock's effect on game length.
Stop reacting to every up and down in your metrics
In Measures of Success: React Less, Lead Better, Improve More, I show how Process Behavior Charts help leaders tell signals from routine variation, so they spend less time explaining noise and more time improving the work. The foreword is by Donald J. Wheeler.
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