[CuriouslyC]

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.

[fallinditch]

Yes. I took over the project management of a job where the previous project manager had spent a year planning it out, but development had not yet started. The client was furious, understandably.

I abandoned the plans from the previous PM and discussed the job with the developer who ballpark estimated that the work would take 2 months. After a quick analysis I adjusted this to 14 weeks.

But the account manager thought this sounded too long and insisted that we plug everything in to a Gantt chart, define the shit out of everything, map the dependencies, etc, which showed that the development would only take 6 weeks.

The project ended up taking 14 weeks.

[SpicyLemonZest]

It's definitely unfair in a sense. But companies that make over-extrapolated roadmap estimates from not enough evidence systematically outcompete those who don't, because their customers greatly prefer companies who give a date and then try their best to hit it over companies who say they don't know when the product will be ready for X and you'll just have to wait and see.

[CuriouslyC]

I get that, and I don't mind giving guidance on roadmaps, it's just the ownership when stuff outside my control goes wrong that bothers me. I shouldn't be responsible for product going in circles on little details with the customer causing req churn, yet I have been held accountable for missing estimates under that exact circumstance.

[plagiarist]

You estimate your best and then during the project the people who keep changing the spec every two weeks ask why the deadline is slipping.

[state_less]

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!

[nradov]

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_...