Was reading an article about Chrysler decreasing their decision time drastically and that led me to thinking about metrics that could be used to measure decision making. Couldn't think of any besides the obious of length of decision process. Brief googling didn't make me much smarter either. Please provide links if I have been blind and overlooked something.
I would think it would be good to start with question if measuring decision making is even necessary? I think so, if for nothing else then atleast to provide company leadership a tool to improve their work. I don't mean looking for some ratio for correct decision divided by total decicions. Correct decisions are somewhat subjective and more often than not made with not enough information. So decision might've been correct given the information available at the time but incorrecet when looking back with better information.
I'm thinking more in line with measuring speed of decision making or reaction speed or something. A way to tell if company is adaptable and agile.
Supply Chain Councils SCOR model has pretty long list of different metrics so decided to check them out. There were few almost-but-not-quite metrics, mainly ones that measure different timeframes.
Average Release Cycle of ChangesHigh amount of changes lowers this metric this but high amount of changes is not good in itself.
Cycle time for implementing change notices divided by total number of changes.
Manufacturing Cycle TimeThis includes several cycle times with different start and end points. These measures really don't tell anything about other operations inside company besides manufacturing. Important metric but not what I am looking for in here.
Total time from order to delivery
Cumulative Source/Make Cycle TimeThis could actually describe companys ability to respond to sudden changes in product mix.
The cumulative external and internal lead-time to build shippable product (if you start with no inventory on hand, no parts on-order, and no prior forecasts existing with suppliers), in calendar days.
ECO (Engineering Change Order) Cycle TimeQuite good measure of ability to change.
The total time required from request for change from customer, engineering, production or quality control to revise a blueprint or design released by engineering, and implement the change within the Make operation.
Management Decision Timeframe RatioI think that this is one of the best SCOR has to offer. Could be also expanded by including cost of one cycle time so we could calculate price of decision.
The ratio of the time needed to make a decision about a particular process divided by the cycle time of that process. (This generates a number that is better if it is lower). For example, if an operation can be performed in 2 hours, and it takes 4 hours to make a decision about that operation, the ratio would be 200%. The timeframe would be affected by the time it takes to collect data, process information, develop knowledge and evaluate the situation, and implement the decision.
Upside Production FlexibilityThis could be useful as well. But why 20%?
The number of days required to achiece an unplanned sustainable 20% increase in production.
My googling did reveal this paper by Katsuya Takii in which he provides following measure for adaptability:
The difference between actual and predicted input (the residual) can be considered as the firm's reaction to changes. If the correlation between the changes and the residual is large, we can infer that the firm's ability to appropriately adapt to change is high.Paper concentrates on effect of prediction ability on projected profits. Even though he presents subject matter in convincing way I am inclined to disagree with his starting point. I can believe that better forecasting would lead to better profits but my ideal company can respond so fast to changing conditions that it makes predicting obsolete.
Thoughts, comments?
5 comments:
I think predicting is one crucial part of fast reaction. You might not know exactly what is coming but you can have a hunch of the nature of the change and prepare accordingly. One aspect of orientation (as in OODA-loop) is understanding what you see and realizing its consequences. When things start to change completely unpredictably you are usually the one who is behind in the loop.
Is is really? What if everyone else is focused on predicting and you are focused on acting faster? Who wins when prediction goes wrong?
In my opinion action is infinitely better than prediction. Trying to predict better just justifies not touching your sub-bar processes, which deliver the value.
It probably depends a lot of the nature of the problem. It should also be considered that action might be wrong and what would that mean. If your wrong action derails you badly, you might not have enough time to recover until it's too late. Sometimes your wrong action is not that big deal and trying out is the fastest and most efficient way to find a solution. Adapting through action is solving problems by trial and error without understanding. Sometimes it works, sometimes not. The important thing is to understand the situation.
In my opinion people use trial and error approach too much. They fight the same problems all the time without finding a way out because they don't care to seek understanding. Then again, that might be the best way to deal with everyday problems because it's so common. I don't know. I prefer understanding, propably because of my personality.
I think that people who lead nations and big corporations shouldn't just do something and see what happens but know what they are doing or at least try. What we are doing right here is seeking understanding which is a way to predict future on a small scale.
you need some writing lessons
That might be so. One purpose of this blog, at least for me as a non-native English speaker is to give venue where I can write in English, in order to improve my writing skills.
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