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[return to "How I estimate work"]
1. notjus+xw[view] [source] 2026-01-24 15:32:54
>>mattjh+(OP)
After owning a product, I've developed a lot of sympathy for the people outside of engineering who have to put up with us. Engineers love to push back on estimates, believing that "when it's done" is somehow acceptable for the rest of the business to function. In a functioning org, there are lot of professionals depending on correct estimation to do their job.

For us, an accurate delivery date on a 6 month project was mandatory. CX needed it so they could start onboarding high priority customers. Marketing needed it so they could plan advertising collateral and make promises at conventions. Product needed it to understand what the Q3 roadmap should contain. Sales needed it to close deals. I was fortunate to work in a business where I respected the heads of these departments, which believe it or not, should be the norm.

The challenge wasn't estimation - it's quite doable to break a large project down into a series of sprints (basically a sprint / waterfall hybrid). Delays usually came from unexpected sources, like reacting to a must have interruption or critical bugs. Those you cannot estimate for, but you can collaborate on a solution. Trim features, push date, bring in extra help, or crunch. Whatever the decision, making sure to work with the other departments as colaborators was always beneficial.

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2. Curiou+XE[view] [source] 2026-01-24 16:30:30
>>notjus+xw
This is true, but the problem is that engineers are being asked to over-extrapolate given the evidence, and expected to own that extrapolation despite the paucity of evidence to make a good estimate.

I *HATE* estimating roadmaps, because it feels unfair. I'm happy to estimate a sprint.

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3. state_+cY[view] [source] 2026-01-24 18:26:57
>>Curiou+XE
In another life, I would do things like measure the cost in developer time of bugs making it into developer repos vs. the cost in time of running tests in CI to catch such bugs, so evidence based decision making. It was mostly ignored, and at first I was surprised. A multi million dollar organization of people making negative EV plays, which I chalked up to the political pressures being more important than the wastage. More on that later.

As far as estimates go, I've also struggled with the industries cult(ural) rituals. I tried to put forward a Gaussian based approach that took into account not only the estimate of time, but the expected uncertainty, which is still probably off the mark, but at least attempts to measure some of the variance. But again, the politics and the rigidity of the clergy that has built around software development blocked it.

On the bright side, all this has helped me in my own development and when I think about software development and estimating projects. I know that outcomes become more chaotic as the number of pieces and steps compound in a project (i.e. the projects normal curve widens). You may not even get the project at all as defined at the outset, so my normals approach is still not quite the right tool.

I think this kind of thinking can be helpful when working solo or in a small group who are exposed to market forces. But for solo and small groups, the challenge isn't so much about the estimates, it's about how you're going to fight a battalion of mercenaries hired by big VC money and Big Tech. They can often afford to be inefficient, dump in the market, because their strategy is built around market control. These aren't practices small players can afford, so you need to get creative, and try to avoid these market participant kill boxes. And this is why, coming back to my earlier point, that often times, inefficient practices and politics plays a big role. Their trying to marshal a large number of troops into position and can afford to lose a few battles in order to win the war. The big money plays by a different set of rules, so don't worry if their doing it wrong. Just recognize your in the army soldier!

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4. nradov+fb1[view] [source] 2026-01-24 19:42:59
>>state_+cY
It's sad how software organizations refuse to learn from history. The US Navy was using PERT to manage huge, risky projects back in the 1950s with pretty good results. It can give you a Gaussian distribution of project completion dates based on best / middle / worst case estimates for individual tasks with dependencies.

https://en.wikipedia.org/wiki/Program_evaluation_and_review_...

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