(These are some notes from the Disciplined Agile FLEX alpha workshop under development)
When looking for cause and effect one must remember there may be multiple causes. Hence, if you fix one thing you may not get the result you want because other things may be going wrong. Consider building a bridge. It requires attending to compression strength (think concrete) and tensile strength (think support cables). Failure in either one will result in failure. Hence, doing one right thing doesn’t guarantee success, but doing one wrong thing often guarantees failure.
The trick is to look at things as a system, and improve something that either leads to improvement or leads to the discovery of something else required.
Root cause analysis is not to get to the root causes, it’s to learn what’s going on. If multiple causes are in play you can pick which one will most likely improve things or lead to learning which can lead to improvement. Or which may get improvement at low cost.
Also, consider which actions to take on how they affect others. In solution development actions upstream often have an effect on downstream work. MBIs can lead to less work hitting downstream teams which increases efficiency in and of itself. It also creates space for learning.
Attending to Cause and Effect in Complex Systems
Posted on: July 02, 2020 10:43 AM |
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Eduin Fernando Valdes Alvarado
Project Manager| F y F Fabricamos Futuro
Villavicencio, Meta, Colombia
Thanks for sharing
HI Al,
I agree but we have to take in consideration to types of cause and effects. But we can face real challenges when there are several variables in the complex system. So I like to divide the cause effects in two types following a mathematical process where we have:
Linear Effects- Where is visible that activity A impacts process B that influences C functionality and etc.
Non Linear Effects- Where the effects can spread on every or some directions and only manifest in upstream or downstream or side processes that are not necessarily contiguous and are dependents on the context and environment that surrounds them.
Look at the system as whole is fundamental to detect the effects, but depending of the dimension and complexity this job implies team work and reliable sources of information to make a good assessement.
Alexandre Costa
I agree but we have to take in consideration to types of cause and effects. But we can face real challenges when there are several variables in the complex system. So I like to divide the cause effects in two types following a mathematical process where we have:
Linear Effects- Where is visible that activity A impacts process B that influences C functionality and etc.
Non Linear Effects- Where the effects can spread on every or some directions and only manifest in upstream or downstream or side processes that are not necessarily contiguous and are dependents on the context and environment that surrounds them.
Look at the system as whole is fundamental to detect the effects, but depending of the dimension and complexity this job implies team work and reliable sources of information to make a good assessement.
Alexandre Costa
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