We Must Measure, Because Our World Is Neither Predictable Nor Unpredictableby Stacey Barr |
Forget all the cliches about why we measure performance. ‘You can’t manage what you don’t measure.’ ‘What you measure is what you get.’ Why we measure performance is much more profound and fundamental.
“If we lived on a planet where nothing ever changed, there would be little to do. There would be nothing to figure out. There would be no impetus for science. And if we lived in an unpredictable world, where things changed in random or very complex ways, we would not be able to figure things out. Again, there would be no such thing as science. But we live in an in-between universe, where things change, but according to patterns, rules, or, as we call them, laws of nature…” — Carl Sagan, Cosmos
I find this quote from Carl Sagan one of the most inspiring motivations for measurement.
If the world was completely predictable, where nothing ever changed, organisations would be like perfect machines. Every output or outcome they intended to produce would be produced precisely as intended. Control is 100%.
At this extreme, there is no use for measuring performance, because performance is always perfect, with no variation. Our world isn’t like this. And that’s why performance targets of perfection – like 0 injuries or 100% on-time performance – make no sense, no matter how idealist or ‘right’ they might seem. Our organisations are not deterministic machines.
If the world was completely unpredictable, with no order at all, organisations wouldn’t exist, because the concept of organising would be impossible. Control is 0%.
At this extreme, there is no use for measuring performance, because performance varies so randomly that we could not observe patterns of causation, and therefore not learn how to exercise any degree of control over performance. Our world isn’t like this either. And there is no excuse for making decisions purely driven by gut feel or hearsay or tradition or whim. Our organisations are not putty in the hands of an individual.
Our world is in between these extremes of perfect predictability and perfect unpredictability. There is variation, but it’s not the product of complete randomness. It’s the product of complexity, and there is order in this complexity.
So in our in-between world, we have a use for measuring performance, because it helps us quantify the variation and observe patterns of causation. It helps us learn how we can influence performance by reducing variation, and by using or changing these patterns.
Performance measurement is an application of science to deepen our understanding of the complexity in our organisations, and speed up our identification of the patterns within that complexity, so we might get better and better, but never perfect, at creating the results we want.
Do you see in your organisation any evidence that suggests people believe the organisation is more predictable than it really is, or more unpredictable than it really is?
Great post! If we were capable if seeing all cause and effect relationships, we would have a perfectly predictable world. The issue is that with our human senses, we are limited by time and space and must use tools to help us see further. In order to become better we must draw a larger circle around what we manage and understand. I believe that is what all performance improvement systems including TQM, Six Sigma, Theory of Constraints, Learning Organization / System Thinking, Reengineering, Lean, and your excellent measurement methodology, allow us to do.
As one who hangs in the balance between not knowing everything and knowing something, I must take the pains to discipline my approach and the risk to move forward to learn more. Learning has to be intentional.
My experience leads me to the following conclusions about your question: Most people see their system as mostly predictable, don’t understand why it goes out of predictability, and inject more unpredictability into it trying to fix it. Again, my experience is that a person who understands variance and attempts to understand it as part of a system risks being branded as unresponsive, uncaring, or theoretical. A person who does not have a grasp of managing a system will suffer from the ‘post hoc ergo proctor hoc’ fallacy (associating unrelated events that occur closely together.) They take credit when their guesses are correct, invent another solution and possibly blame when they are wrong. I know because I spent a portion of my career behaving like this and have observed the behavior as common.
I try to spend a lot of my time helping people see the system. THanks again!
This is definitely a great starting point for those conversations we have with management teams about the “why” before moving on to the “what”.
I’d not seen the quote from Carl Sagan previously. It does set the stage quite well for this discussion. I might need to drop that into my own toolbox for reference.
Your point about “making decisions purely driven by gut feel” is also a common theme that I’ve observed with many managers. I find this strange given that, from an individual perspective, we tend to be more comfortable with structure and organisation in our lives. In my experience, those “gut feel” decisions seem to be more prominent in organisations where there is a bigger gap between management and workers. But that also varies based on the organisation’s size and maturity.
It would be interesting to understand how much of an impact accountability has on decisions based on “gut feel” alone.
What a great quote to think about and to share with my peers during our next get-together! I agree with Tom G: “Most people see their system as mostly predictable, don’t understand why it goes out of predictability, and inject more unpredictability into it trying to fix it.”
I would like to add to the discussion that in my experience selecting the data points we want to measure and sticking with them over a period of time is one of the biggest challenges. We are not very patient so our tendency to try something new to “fix it” faster will take our attention away from following through on a planned approach to make positive change resulting in just more unpredictability.
Speak with data..many people will collect data before measure and analysis. Once we got Data is always past condition and for the future condition we can’t predict 100%. So, for leading success in the future, should develop people, not the data because people make changes for improving the data. And we must focus in the present condition with the data for carrying prediction of improvement at time to time..
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