Project Management

Cause and Effect Does Exist in Complex Adaptive Systems

From the Manifesting Business Agility Blog
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An organization creating new products and services is a complex adaptive system. A CAS is a system in which a perfect understanding of the individual parts does not automatically convey a perfect understanding of the whole system's behavior. This means one can't be certain what change in one part of the system will have on another. But this doesn't mean that cause and effect doesn't exist for the system as a whole. Even in complex adaptive systems there is a cause and effect when one deals with the system as a whole. Here are some examples:

  • overloading teams with work will lead to ineffectiveness - "Operating a product development process near full utilization is an economic disaster." Don Reinertsen
  • a lack of visibility of what is being worked on will lead to extra work
  • large batch sizes will lead to delays in feedback and delivery of value while increasing unplanned work
  • the longer it takes to integrate across teams the more likely fixing the errors discovered will take more time
  • having people work in multiple value streams where they are not allowed to finish their tasks in one before going to another will increase multi-tasking and create waste
  • as code and product quality goes down, the amount of wasted effort goes up
  • micro-management is a disincentive and loses the value of understanding that people doing the work have

 

Posted on: December 11, 2019 10:18 AM | Permalink

Comments (6)

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Dear Al
Interesting this reflection
Thanks for sharing

We agree on the seven points mentioned.

Al,

Thank you for sharing your thoughts.

Most of your generic examples are accurate but we also need to be conscious of exceptions, unexplainable effects, and uncorrelated items.

Very interesting., thanks for sharing

Sreepathi
Totallly agree. I should have referenced Dealing with Complexity by Creating a Bias For Simplicity
https://www.projectmanagement.com/blog-post/58280/Dealing-with-Complexity-by-Creating-a-Bias-For-Simplicity

Where i talk about 'Why it's hard to make predictions about whether a change will be beneficial'. You always need feedback.

What would be interesting to test, Al, is whether causality is harder to prove with CAS's than with simple systems?

We're not trying to prove causality in the sense of this action here causes that reaction over there. We're talking about overall system improvement. You can prove it from your own experience.

Mythical manmonth is an example. Add people late to a project and it slows you down.

Allocate people to many projects instead of trying to get them on one thine and multi-tasking goes up and productivity goes down.

Do test-first and code quality will improve while wasted effort will go down.

Micro-manage people and their contribution will go down.

Do you see these statements being true from _your_ experience?

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