Some days I feel like estimates and plans are worthless. Other days I find myself idly speculating that if only we were better at planning and estimating, everything would be beautiful.
In an engineering organization, we want realistic plans. Realistic plans and roadmaps will hypothetically help us utilize our capacity effectively and avoid overcommitting. And our plans are usually built on estimates; that’s why we believe that “correct” estimates are more likely to generate a realistic plan. Therefore, we believe that correct estimates are useful for planning.
On the other hand, if you’ve ever worked with engineers, you also believe that estimates are never correct. Something always gets in the way, or we pad the estimate out to avoid being held responsible for missing a deadline, or (occasionally) the task ends up being much simpler than we expected. The time we estimate is never the time it actually takes to do the job.
These two statements seem to be in contradiction, but they are not. There is a key to holding both these beliefs in your head at once. And I believe that if an entire engineering org were to grasp this key together, it would unlock enormous potential.
The key is to treat uncertainty as a first-class citizen.
Why This Is Hard
Developing organizational intuition in about estimates is really hard. It is in fact so hard that I’m not aware of any organization that has done it. I see two big reasons for this:
- We don’t have good awareness of the amount of uncertainty in our estimates.
- We pay lip service to the idea that estimates aren’t perfect, but we plan as if they are.
1. Uncalibrated estimates
When we give estimates, those estimates aren’t calibrated to a particular uncertainty level. Everybody has different levels of confidence in their estimates, and those levels are neither discussed nor adjusted. As a result, engineers and project managers find it impossible to turn estimates into meaningful plans.
2. Planning with incorrect use of uncertainty
You’ve surely noticed uncertainty being ignored. It usually goes something like this:
PM: How soon do you think you can have the power converters re-triangulated?
ENG: I’m not sure. It could take a day, or it could take five.
PM: I understand. What do you think is most likely? Can we say three days?
ENG: Sure, three or four.
PM: Okay. I’ll put it down for four days, just to be safe.
Both sides acknowledge that there is a great deal of uncertainty in this estimate. But a number needs to get written down, so they write down 4. In this step, information about uncertainty is lost. So it shouldn’t be a surprise later when re-triangulating the power converters takes 7 days and the whole plan gets thrown off.
Suppose 5 teams are working independently on different parts of a project. Each team has said they’re 80% confident that their part will be done by the end of the year. The project manager will want to know how likely is it that all five parts will be done by the end of the year?
When we answer questions like this, we don’t usually think in terms of probability. And even if we do think in terms of probability, it’s easy to get it wrong. If you ask non-mathy people this question (and most project managers I’ve worked with are not mathy), their intuition will be: 80%.
But that intuition is extremely misleading. What we’re dealing with is a set of 5 independent events, each with 80% probability. Imagine rolling five 5-sided dice. Or, since 5-sided dice are not really a thing, imagine spinning five 5-sided dreidels (which are also not really a thing, but are at least geometrically possible). You spin your five dreidels and if any of them comes up ש, the project fails to meet its end-of-year deadline. The probability of success, then, is:
(80%)⁵ = 80% ⋅ 80% ⋅ 80% ⋅ 80% ⋅ 80% = 32.8%
Awareness of the probabilistic nature of estimates makes it obvious that a bunch of high-confidence estimates do not add up to a high-confidence estimate.
To make matters even worse, most organizations don’t even talk about how confident they are. In real life, we wouldn’t even know the uncertainties associated with our teams’ estimates (this is problem 1: uncalibrated estimates). Nobody would even be talking about probabilities. They’d be saying “All five teams said they’re pretty sure they can be done by the end of the year, so we can be pretty sure we’ll hit an end-of-year target for the project.” But they’d be dead wrong.
Why This Is Worth Fixing
I believe that poor handling of uncertainty is a major antagonist not just of technical collaboration, but of social cohesion at large. When uncertainty is not understood:
- Project managers feel let down. Day in and day out they ask for reasonable estimates, and they’re left explaining to management why the estimates were all incorrect and the project is going to be late.
- Engineers feel held to unreasonable expectations. They have to commit to a single number, and when that number is too low they have to work extra hard to hit it anyway. It feels like being punished for something that’s no one’s fault.
- Managers feel responsible for failures. Managers are supposed to help their teams collaborate and plan, but planning without respect for uncertainty leads to failure every time. And what’s worse, if you don’t understand the role of uncertainty, you can’t learn from the failure.
- Leadership makes bad investments. Plans may look certain when they’re not at all. Return on an investment often degrades quickly with delays, making what looked like a good investment on paper turn out to be a dud.
Fostering an intuition for uncertainty in an organization could help fix all these problems. I think it would be crazy not to at least try.
How To Fix It
Okay, here’s the part where I admit that I don’t quite know what to do about this problem. But I’ve got a couple ideas.
1. Uncalibrated estimates
To solve the problem of uncalibrated estimates (estimates whose uncertainty is wrong or never acknowledged), what’s needed is practice. Teams need to make 80%-confidence estimates for everything – big and small – and record those estimates somewhere. Then when the work is actually done, they can review their estimates and compare to the real-world completion time. If they didn’t get about 80% of their estimates correct, they can learn to adjust their confidence.
Estimating with a certain level of confidence is a skill that can be learned through practice. But practice, as always, takes a while and it needs to be consistent. I’m not sure how one would get an organization to put in the work, but I do believe it would pay off if they did.
2. Planning with incorrect use of uncertainty
Managers and project managers should get some training in how to manipulate estimates with uncertainty values attached.
Things get tricky when tasks need to be done one after the other instead of in parallel. But I like to think we’re not adding complexity to the process of planning; rather we’re just revealing the ways in which the current process is broken. And recognizing the limits of our knowledge is a great way to keep our batch sizes small and our planning horizons close.
I think we need to get used to calibrating estimates before we can see our way clear to address the planning challenges.
Can It Be Fixed?
It strikes me as super hard to fix the problems I’ve outlined here in a company that already has its old habits. Perhaps a company needs to be built from the ground up with a culture of uncertainty awareness. But I hope not.
If there is a way to make uncertainty a first-class citizen, I truly believe that engineering teams will benefit hugely from it.