Your boss wants a commitment. You want to offer a prediction. Agile, you say, only allows you to estimate and predict – not to commit. ”Horse-hockey!” your boss exclaims, “I want one throat to choke, and it will be yours if you don’t make a commitment and meet it.” There’s a way to keep yourself off the corporate gallows – estimate, predict, and commit – using agile principles.
This is an article about agile product management and release planning.
Change and Uncertainty
In the dark ages before your team became agile, you would make estimates and commitments. You never exactly met your commitments, and no one really noticed. That was how the game was played. You made a commitment, everyone knew it would be wrong, but they expected it anyway. Maybe your boss handicapped your commitment, removing scope, lowering expectations, padding the schedule. Heck, that’s been the recipe for success since they planned the pyramids.
It makes sense.
- Your early estimates are wrong. When you add them up, the total will be wrong. If you do PERT estimation, the law of large numbers will help you in aggregate. But you’ll still be wrong.
- The outside demands on, and availability of, your people will change. Unplanned sick time, attrition, levels of commitment over time, lots of “people stuff” is really unknown.
- The needs of your customers will change. Markets evolve over time. You get smarter, your competitors get better, your customer’s expectations change.
Agile processes are designed to help you deliver what your customer actually needs, not what was originally asked for. Contrast the two worlds.
In the old world, you would commit to delivering a couple pyramids. After spending double your budget, with double the project duration, you would have delivered one pyramid. When you deliver it, you find out that sphinxes are all the rage. Oops.
Your team changed to agile, so that you could deliver the sphinx. But your Pharaoh still wants a commitment to deliver a couple pyramids (the smart ones will be expecting to get just one). You can stay true to agile, and still mollify your boss’ need to have a commitment, if you take advantage of the first-principles of why agile estimation works.
A commitment is a factual prediction of the future. ”This will take two weeks.” Nobody is prescient.
A factual prediction has to be nuanced. ”I expect* this will take no more than two weeks.”
*in reality, this is shorthand for a mathematical prediction, such as “I expect, with 95% confidence, that this will take no more than two weeks.”
Few non-scientist, non-engineers, non-mathematicians understand that 95% confidence has a precise meaning. People usually interpret it to mean “a 5% chance that it will take more than two weeks.” What it really means is that if this exact same task were performed twenty thousand times (in a hypothetical world, of course), then nineteen thousand of those times, it would be completed in under two weeks – do you feel lucky?
To make a statement like this, you actually have to create a PERT estimate – identifying the best-case, worst-case, and most-likely case for how long a task will take.
Unfortunately, we’re rarely asked to make a commitment about a single task – but rather a large collection of tasks – well-defined, ill-defined, and undefined.
You can combine PERT estimates for the individual tasks, resulting in an overall estimate of the collection of tasks.
The beauty of this approach is that the central limit theorem, and the law of large numbers, work to help you estimate a collection of tasks – you can actually provide better estimates of a group of tasks than a single task. This obviously helps with the well-defined tasks that you know about at the start of the project. This even helps with the ill-defined tasks. Rationalists will argue that the key, then, is to do more up-front research to discover the undefined tasks – and then we’re set. As Frederick Brooks (Mythical Man-Month) points out in The Design of Design, this debate has been going on since Descartes and Locke. It is not a new idea.
Big Up-Front Design and Requirements (BUFD & BUFR) hasn’t worked particularly well, so far.
Don’t throw out the baby with the bath-water, however. The math of estimation is still important and useful. Even if empiricism is not the silver bullet.