Speaking of Tacit Knowledge, have you heard of Blink Estimation? Take a medium sized group of people with significant tacit knowledge in a domain. Explain a problem/opportunity and give them some time to ask questions and explore the shape of the problem. Then, ask them for a rough order of magnitude of the level of effort required to implement the solution. If your group comes up with similar answers then you’ve got your estimate. If they don’t, work with the outliers to understand why their answers were so different. At least one group missed something, possibly both.
It’s surprising how often this works. There are lots of caveats and biases to watch out for, but if you can manage those you can get a good answer. The biggest of those caveats is that tacit knowledge can be incredibly domain specific. Which means the folks you ask need to be well versed in something close enough to what you’re asking them about.
And not just on the surface. All software development is not the same. Asking someone with deep tacit knowledge about IOS apps for an estimate on distributed parallel processing is unlikely to give you a good answer. Both problems involve computers, but they're not the same. Consider bicycles and unicycles. In the US somewhere around 6% of people say they don’t know how to ride a bike. Unicycles are half the complexity (1 wheel vs 2), so even fewer people don’t know how to ride a unicycle, right? Of course not. On the surface they’re the same, but in reality they’re mostly unrelated.
Then there are the cognitive biases. Not surprisingly, if the experts have been working on the project and know it was supposed to take a year and they’re 6 months in, that fact will color their answer. So will how long it took them to finish the last task they worked on. Just mentioning an expected duration will bias the results. Even a bad commute into the office that morning can bias the results.
And it won’t work if the problem space is new. We can estimate how long it will take to build a single family ranch house in the suburbs because we’ve got thousands (millions) of examples to look at and get that tacit knowledge from. Building the first habitat on Mars, from local material, will not be nearly as predictable.
How can such a shallow evaluation be better than a deeper one? Of course having the right tacit knowledge is key. But there’s more to it than that. Here’s a question for you. How long is the coast of England? It depends on how small you break the problem down. I suppose if you get down to plank units there’s a limit, but the closer you look the longer the coastline gets. Software can be like that too. The deeper you design, the more work you find. And of course, no task takes less than a day, so the estimate blooms the harder you look. Which seems counterintuitive, but is reality.
We’re doing lots of new things, so it may not be very applicable, but just for grins, next time you start a project, get a few folks together, think deeply about the size and shape of the problem, (but not too deeply) and make an estimate. Then see how close you come. Do it a few times. Keep track of the results. Regardless of the outcome it will likely make you blink.