photo by freewine

Most managers, public or private, have a tendency to look for performance indicators that they can measure. This seems logical–you want to know how you are doing, so you look for acceptable ways to quantify your performance such as LEED building ratings, or how a supply chain is rated in terms of fair trade, or how much carbon you have as a footprint. Indicators gives a sense of security because you feel like they can tell you how much of a difference you’re making, or that they can predict, like an early warning system, when things might go wrong.

Unfortunately, most of the time this does not happen. Indicators are often so off-base that they can cause disaster for the company or the environment. That is because most managers reduce performance indicators to what they can measure easily and directly. It seems so obvious that we cannot even conceive of another way to do this.

This is likely very obvious to almost everyone in the recent recession as they watched their performance indicators collapse around them, feeling unable to do much of anything to stop the downslide. Federal Reserve Chairman Alan Greenspan testified that for years he felt that the indicators of inflation rates and growth in GDP told us what we needed to know to manage financial stability, and that no regulation was needed as long as these indicators are within “acceptable” bounds. Even he has now stated, “I was wrong.”

This lesson seems to need to be learned repeatedly. In 1918, a great compromise was reached between ecologists and wild life managers based on a formula for determining “maximum sustainable yield” (MSY)*. It was based on measuring factors that predicted the fish replacement rate of lakes using the nutrients in, rate of breeding, number of fish at the start and a few other variables you could calculate. Then if you got a surplus you could take out more, but you know how not to deplete the lake by over fishing. This formula seemed to give rules to follow. Except for one thing: it started to cause mass extinction in lakes and a collapse in many lakes of fish life. What is important to remember it is fooled not only the wild-life managers, but also the ecologists. What seemed obvious was wrong.

After years of study, the problem was found to be that the changes external to the lake were better predictors of lake health than the measurements taken from the lake itself. Keeping track of the things you could measure were worse than useless and led to people’s not paying attention to the things that really mattered. Lakes looked stable, a false assumption, but were really filled with deep and hidden complexity. What you could measure mattered less than what you could not measure. What mattered was outside the system. Factors that seem unrelated to the problem at hand mattered more. CS Holling, who studied and identified the need to account for external factors, found things such as attracting more fisherman to seemingly well-stocked stable lakes, more trash they left that blocked channels, which dislodged moss that feed other fish, which were the staple diet of the “target” fish being sustained, actually caused the problem that they were trying to avoid. The seduction of easy measures left people feeling they were doing something scientific and therefore reliably good and right. It all made sense on paper, but it fell apart in the deadly reality of practice.
We need to develop a different way of thinking that looks at systems nested in systems and to the systems dynamics that are constantly changing. And our current sustainability measures are not our answer.

*Source : The Age of the Unthinkable, by Joshua Ramo