Senior software developer at Amazon Web Services. I work on the AWS Serverless Application Repository and AWS SAM. I’m passionate about writing quality software and teaching others how to do the same.
Location
Seattle, WA
Education
BS Computer Engineering, Minors: CS and Math
Work
Sr. Software Development Engineer at Amazon Web Services
Thanks for the feedback and good points, John. You're right that impact and effort can be difficult to estimate and measure. I don't have a bullet-proof solution for that, however here are my thoughts:
Estimation of effort is hard, period. I generally like using Scrum, because it tries to mitigate this with frequent practice of estimation, measurement of actuals and retrospective to continuously improve. For longer-term planning, frequent checkpointing to see if you're on track, and if not, if you can make changes to help (reducing scope, adding resources, etc).
Measurement of impact can also be difficult to measure, however I think the more common pitfall is failing to define success metrics from the beginning. If you take the time to think about what you want to measure and instrument your solution, then you can draw meaningful conclusions from the data, even in an environment where you can't hold all other variables constant.
In any case, as I mentioned in the article, fast iterations with rapid feedback is key to taming the chaos. If the cycle time is too long, the amount of noise you'll have to sift through quickly becomes prohibitive.
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Thanks for the feedback and good points, John. You're right that impact and effort can be difficult to estimate and measure. I don't have a bullet-proof solution for that, however here are my thoughts: