One estimation trick that I've found effective is the following:
(1) determine the smallest number that your sure is larger than the true answer.
(2) determine the largest number that you are sure is smaller than the true answer.
(3) take the <i>geometric</i> average of the two. (i.e., sqrt(a * b))<p>The reason this does well, is that oftentimes, (1) overestimates the true answer by roughly the same <i>multiplicative</i> factor as (2) underestimates the true answer by. So the geometric mean cancels the over and under estimates in order to get an estimation that does pretty well.<p>I find that this works remarkably well for estimating the dimensions of buildings, trees, etc.
I think the biggest thing holding engineering estimates back is that the people asking for them are actually not interested in accurate estimates; instead they are looking for inputs to be used in various games of corporate politics.
My go-to heuristic is three point estimation, basically a weighted average of the best, worst, and average case [0].<p>(Best + Worst + 4 * Average) / 6<p>One nice property is that it imposes a distribution that adjusts for longer tailed risks.<p><a href="https://en.wikipedia.org/wiki/Three-point_estimation" rel="nofollow">https://en.wikipedia.org/wiki/Three-point_estimation</a>
Things, IMO, which are spoilers:<p>1. Starting with an End date and create a plan from there. Some top leads want to get promoted and want to achieve X by this quarter or next.<p>2. With so many people leaving, there is not enough time and resources to onboard new folks, who are accounted in deliveries<p>3. Too many parallel initiatives<p>4. Unstable production taking daily attention<p>5. Not able to priortise tech debts over business features<p>6. Decision makers at top don't have grass root visibility or don't want to have.
Interesting article.
Our PO often almost demands estimations from us. Usually I am already responding in a best/worst case fashion.
In the end PO only seems to remember the best case and takes it as commitment. Since I was fooled by this a few times, I am now collecting a paper trail and am quiet reluctant, when giving "just a ballpark figure".
My key takeaway was, that estimations mostly aren't about accuracy or getting a value, but rather managing people's expectations and navigating corporate politics.
When estimating a software project of any size, try to imagine the most optimistic number of hours needed for each activity you can think of.<p>Then multiply by 4.14.<p>This provides room for<p>Phase 1: First verions of the deliverable: x<i>pi/2<p>Phase 2: Trying to work around all the cases where the initial design was bad: x</i>pi/2<p>Phase 3: Re-factor from scratch (with the same team) : x1<p>Sum phase 1-3 : x(pi+1)<p>This is for facing the customers/stakeholders. When facing the team, only present them with Phase1, with the estimate of x<i>pi/2.<p>Otherwise, phase 1 alone will take x</i>(pi+1).
The best estimation tactic I've found in practice is ROPE, which works because it helps different kinds of stakeholders understand different kinds of estimates and ranges.<p>R = Realistic estimate. Based on work being typical, reasonable, plausible, and usual.<p>O = Optimistic estimate. Based on work turning out to be notably easy, or fast, or lucky.<p>P = Pessimistic estimate. Based on work turning out to be notably hard, or slow, or unlucky.<p>E = Equilibristic estimate. Based on 50% probability suitable for critical chains and simulations.<p><a href="https://github.com/sixarm/rope-estimate" rel="nofollow">https://github.com/sixarm/rope-estimate</a>
When I make an estimate, I just double what I think it is and this is usual pretty accurate. I keep underestimating, sometimes doubling down I wonder myself, will it really take this long? 99% of the time, in the end, the answer was yes. So this is my goto method. People still think I finish stuff quick, even if I think myself it's too long.
Engineering projects often already encompass this whole philosophy by building estimates that roll up to a P10 and a P90 outcome.<p>P10 = 10% chance of occuring, P90 = 90% chance of occuring.<p>How it's typically done is standard scheduling packages, like Prima Vera, allow you to specify a band or range of duration/effort for individual tasks/activities.<p>This, when combined with task dependency information (which you must give it in the form of a Pert chart or similar, it takes a few different formats of data) means it can calculate the critical path across the whole range of activities for an overall outcome and yield the project P10/P90.<p>Then, you can run sensitivity analysis and identify key pivot points, look at assigning more resources to certain efforts etc etc and optimise the schedule, plus track actual progress as you go and make forecasts.<p>But this is all based on the premise of doing the kind of engineering where you have some reasonable idea of what your actual goals and methods are before you start, so if you are running under agile you are probably screwed because even if you tried this planning, your planner/s could probably never keep up with actual.<p>To understand the difference between an engineered project and an agile one see my comment <a href="https://news.ycombinator.com/item?id=31299834#31301616" rel="nofollow">https://news.ycombinator.com/item?id=31299834#31301616</a>
Using Steve McConnell's terms, I think of things playing out as Plan, then Estimate, then discuss the Target, and then cut features before Committment.<p>Having multiple people independently estimate a given problem is a more robust way to estimate, in general. Other than as a lead and a dev each sizing something up, I don't think I've seen that in practice. It feels a little weird for developers to be estimating each other's work. I think it's interesting if and only if Committment is truly separated from estimation.
I feel like "Note the Precision" is one that I most see missed.<p>Partially, this is on engineers. They'll say "That'll take 36 days" and not realize that they're implying a higher level of specificity than they intend.<p>Partially, this is on consumers of estimates (managers, etc). They'll hear "It'll be about 36 days, but that's just a super rough estimate, we haven't planned it out yet, it could be way more..." but they stopped listening and wrote down "estimate: 36 days."<p>My current eng team has fixated on two distinct levels of eng estimates. The first is super high level: "minutes to hours", "hours to days," "days to weeks", "weeks to months," or "months to quarters." The second is a number of hours<i>. We give out the high-level estimates freely - they're super helpful for project planning. We give out the second number only when we have a pretty solid plan with estimated tickets.<p>It's worked pretty well because engineers can always be clear on which estimation type is called for. It's also helpful because non-engineers can get used to hearing the high-level estimates pretty quickly and know to treat them as super vague.<p>* We actually deliver all hour estimates as 30/60/90 estimates: "we're 30% sure it'll be done in 36 hours, 60% sure it'll be done in 50 hours, and 90% sure it'll be done in 80 hours". There's still a tendency of people to just use the 60% estimate as "The Estimate," but it's better than nothing.</i>
I really like "3 point estimates". Rather than a single estimate you give three - one that's your expected timing, one for the best case if everything goes perfectly, and one absolutely worst case scenario time. The difference between "best case and expected", and "worst case and expected", indicate the risk factor. If best case and expected are similar then it's a low risk feature - you understand the complexity and there are few unknowns. If the worst case and expected are similar then it's a high risk feature that you don't expect to go to plan.<p>I've never been in a position to actually use this approach well, but I like the idea of it a lot.
Always keep in mind that estimate errors follow a long-tailed distribution. That means that if you estimate enough things, your total error will be defined by one or two tasks, it doesn't matter how you did for 95% of them.<p>Thus, if your goal is to lie to management stating that "we met 98% of our estimations last year" implying that because of this, there is not problem, then yes, go work on improving your estimates.<p>If your goal is to get things done so you can get some real progress, go set realistic targets on time or ROI and learn to throw away tasks that failed it.<p>And if your goal is to never get an estimation wrong, because they are commitments that you can never get free after you made them, go practice your interview skills and move to a better environment.
There are no hacks. Making estimates is difficult, the more information you can add into your equation as early as possible the better prediction you will get.
I usually go for the scale like hours, days or weeks. It comunicates the accuracy of the estimates. If something more accurate is required I like thrashtester's method of the 4.14x
some things can be estimated, others not so much<p>often folks don’t know if what is being estimated is actually knowable.<p>building something new pre product market fit is a crapshoot until it’s not.