re: post on prediction [link broken, so removed] on the Deming Electronic Network:
…that intelligence more or less boils down to updating a predictive model of the world. As far as I can see, this is the C.I. Lewis epistemology that Shewhart and Deming based their philosophy upon.
…but is there any kind of operational definition for ‘prediction’ that would explain what Deming means when he uses this word in various contexts?
I think your first point is correct, which I see as: learning by predicting, then looking at the result and then adjusting understanding to this new information is very powerful.
I believe Deming’s thoughts about prediction are most effectively put into action using the PDSA cycle. Specifically, you must predict the results in the planning phase (prior to piloting improvements). I find that this is rarely done. I don’t think the form of that prediction is critical (narrative with loose numerical guesses, precise numerical prediction…). The critical issue is making the prediction, then comparing the results to that prediction and then figuring out how your original understanding can be improved based on the new data.
Learning will not only be about the specific case being examined, but also, over time, learning about your tendencies in prediction. For example, do you: overestimate the size of the improvement, underestimate the time it will take to institute a new process improvement, underestimate the complexity of IT projects…? Basically, over time, learning from your prediction history the biases that affect your predictions (which are then tied to your model for viewing the world…). Then, that knowledge can be used to improve your ability to make better predictions in the future. Without actually predicting and then examining the results people often make the same errors in their belief about the potential outcomes of changes for not just years, but decades.
I believe the act of formally making a prediction is critical to improving the learning process. I think prediction and examination of results is rarely done. And I think it is a very powerful component to creating an organization that can improve rapidly.
The understanding Deming had of prediction was as a component of the Theory of Knowledge. The importance of prediction is due to the impact it has our our learning. Prediction, with subsequent evaluation of results and then adjust to the model used to make the original prediction is a process that improves a person’s ability to understand how they think. By going through this prediction cycle many times the person becomes better at using the knowledge the have. Even if they don’t learn about the theory of knowledge abstractly as a concept they learn about the theory of knowledge in practice. On page 101 of the New Economic and for several pages thereafter Deming addresses prediction.
Pingback: Curious Cat Management Improvement Blog » Blog Archive » Six Keys to Building New Markets by Unleashing Disruptive Innovation
Pingback: Curious Cat Management Improvement Blog » The Illusion of Understanding
Pingback: Knowledge Management - Management is Prediction
Pingback: CuriousCat: Predicting Improves Learning
Pingback: CuriousCat: How to Get Ahead
Great discussion. The prerequisite for a prediction is some theory in use. In using the PDSA cycle, is important to frame questions that help people explicitly state their theory, especially if a team in involved. Merely answering yes or no, or guessing, does not make the theory explicit. I have seen instances where people will predict “yes” or “no” for two different reasons. The act of making the prediction can change how we collect data or run a test. Richard Feynman commented, “Science begins and ends in questions.” So should the science of improvement. Questions lead to predictions (theory being explicit), this leads to a plan for data collection and a test. Built into the PDSA cycle is the logic of deductive and inductive learning; Plan to Do (deductive)Study to Act (inductive). This iterative learning process was explored in Statistics for Experimenters by Box,Hunter and Hunter.
Cliff Norman (API)
One should remember that Deming and Shewhart always refer implicitely to probability theory from which they created spc (statistical process control).
The one main idea of spc is that you cannot make prediction like you learn at school with normal law that 95% of datas will be between 2 standard deviations if your process is not under control.
To achieve this state control and so be able to make prediction, they derived another tool PDSA which is a layman term for induction / deduction scientific process inherited since at least Aristotle circle.
Pingback: From Lean Tools to Lean Management Â» Curious Cat Management Improvement Blog
Pingback: Deming Institute Conference: Tom Nolan » Curious Cat Management Improvement Blog
Pingback: Deming 101: Theory of Knowledge and the PDSA Improvement and Learning Cycle Â« The W. Edwards Deming Institute Blog