Flow Metrics for Scrum Teams by Daniel Vacanti and Will Seele

Author:Daniel Vacanti and Will Seele [Daniel Vacanti and Will Seele]
Language: eng
Format: epub
Publisher: leanpub.com
Published: 2022-08-10T00:00:00+00:00

But What About Complexity?

Nowhere in the discussion of MCS so far have we mentioned estimating the relative complexity of the PBIs we are forecasting. That’s because with an MCS approach, estimation is not needed. It is unfortunate that the Agile community has been sold the snake oil that is story points, but the truth of the matter is that estimated relative complexity is an extremely poor predictor of capacity. The brilliance of the Monte Carlo Method is that if you choose your inputs properly, then most variables that could affect future outcomes will be encapsulated in your historical flow data and the need for any estimation goes away.

Think about it for a second. Your historical Throughput (not to mention the other Flow Metrics) will include data for PBIs that as you worked on them:

had a wide range of complexities

were similar to other PBIs you had worked on in the past

were not at all similar to other PBIs you had worked on in the past

were blocked due to internal dependencies

were blocked due to external dependencies

were interrupted by other work

were interrupted by holidays and vacations

and so on…

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