Thursday, March 26, 2009
It's been a long time since I've posted. I guess going on vacation and getting back to the real world after vacation will do that to you.
That isn't actually a picture we took of the arch, but I'm at work right now (and having a "distracted child" day), and it's a close enough approximation to the pictures D got while we were on our riverboat cruise.
But this is not about that...
Today's topic is a book report of sorts. I just finished W. Edwards Deming's book The New Economics. Deming became well known for helping develop Japanese industry after WWII, and although the book was "about" quality control in an industrial setting, his main points are easily applied to fitness and weight loss as well.
The New Economics was largely focused on what's wrong with American industry (and schools, and management in general) and what should be done to fix it. The main problem, according to Deming, is that managers (or in other words, all of us) fail to recognize the difference between common causes of variation and specific causes of variation.
I think it's easiest to understand what these types of variation are and how they differ from each other using an example. Say I run the same route every day, and I time myself. Some days I'll run faster than others- that's variation.
Common causes of variation in run times are things that just happen- things I can't control. Examples would be how well I slept the night before, the temperature outside, how difficult a workout I did the day before.
Special causes are things that are way out of the ordinary. I fell and twisted my ankle. My watched stopped for 5min in the middle of the run, and I didn't notice. I'm truly getting faster or I'm truly getting slower.
So let's say I'm evaluating my running progress. I wake up, run, and find that I ran the same route 5 minutes slower than I did yesterday. Should I be upset with this? Am I getting slower?
This is the second of Deming's important points: Don't attribute meaning, especially qualitative (as in "bad" or "good"), to common cause variation.
That 5 minute difference was probably not measuring a change in my ability. More likely it was measuring my quality of sleep or hydration level or something else that was entirely unrelated to my running speed.
I ruined a whole spring and summer of running back in 2007 mistaking common cause variation for specific causes. How? I ran myself into the ground. I'd go out and do a hard workout, and the next day I'd be slow because I was tired. Did I stop and think about the reason I was slow and tired? No. I just believed I was getting slower and vowed to push harder. And I got slower. Nothing improved.
The same is true when you step on the scale every day. My weight can be up for a whole host of reasons (common causes) other than true weight gain: how salty my dinner was and how hard my workout was the day before both come to mind.
Special causes might include the holidays or Girl Scout Cookie season.
A great example of a violation of Deming's rule #2 is Google 15. Google 15 is a neat tool that gives you a 15-day moving average of your weight. That would be great on its own, but Google 15 tells you every day if 1.You are moving toward your goal or 2.You are moving away from your goal. It's attributing a special cause (actually gaining or losing weight) to a daily fluctuation. Kind of demoralizing when you've finished a hard workout and you're up half a pound.
So what to do? First we have to lose our fear of data. You can't change what you don't understand. You can't evaluate if you're getting faster if you don't know how fast you are. You can't evaluate if you're losing weight if you don't know what weight you are. Keep track- without judgment (and that's the hard part)- of how you fluctuate from day to day.
Only then can you work on shifting the mean lower (lower on the scale and lower on the stop watch). I had a band director say once , "You know you're a good musician when your worst performance is still really really good." You'll drive yourself crazy trying to limit everyday ups and downs, but you can trend everything down.
So that's my goal: To not be afraid of data and o embrace it as a tool for learning about myself without judgment.