Measures of Success is about improving results by improving the way we interpret data. Too many organizations react to noise, chase arbitrary targets, and mistake random variation for meaningful change—creating fear, waste, and poor decisions instead of learning.
These posts explore better ways to use metrics through Lean thinking, statistical thinking, and Process Behavior Charts. Drawing heavily from the ideas in my book Measures of Success: React Less, Lead Better, Improve More, this archive focuses on understanding variation, avoiding overreaction, and helping leaders ask better questions of their data—so improvement efforts are grounded in reality, not frustration.
Thanks to Eric Ries and the organizers for Lean Startup Week for allowing me to share video of my 15-minute talk from last year's event.
One reason for sharing this today is to celebrate yesterday's initial release of the in-progress version of my book Measures of Success. If you buy the book now, you'll get a PDF of the first three chapters, or about 40% of the book's expected content.
Today, I’m giving a keynote talk at the Lean & Six Sigma World Conference being held in Las Vegas. I don’t normally attend or speak at “Lean Sigma” events, but I had an opportunity to give a new talk that touches on two of my favorite themes in recent years – the need to apply statistics and psychology to our “Lean Management” practices or Six Sigma or whatever.
Measures matter. The proper analysis of data and performance metrics allow us to separate good changes from bad, progress from stagnation. The methods in my book, Measures of Success, help us determine if our performance is getting better, getting worse, or essentially remains unchanged. Having the right set of balanced scorecard metrics is important. But the role of leaders is important, too. How do leaders interpret measures? How do they respond to changes in metrics? How do they know if a change is worth reacting to?
