Project Forecasting and Uncertainty
Yesterday, I posted about the need to focus on time remaining, using a driving analogy. The premise was that, if we were traveling from Philadelphia to New York and we were at the New Jersey Turnpike entrance (and assuming arriving on time is a critical success factor), the best predictor of success would be to determine how much time remains on our trip.
But what if arriving on time were not the most pressing need? And what if we increased the uncertainty factor? Is "time remaining" still something we can and should monitor?
Let's take IT research projects, for example, which tend to carry great uncertainty. Using an agile approach, the team builds prototypes, and the deliverables get ever closer to "the truth" as the project progresses. If we used a fixed set of iterations, and/or fixed-time iterations, we still benefit from focusing on time remaining, possibly even more so. The only difference is, we're operating in increments.
And even if time is not the ultimate concern, any customer will still want to know "How long will it take before I see something of value?", and usually, "How much will it cost me?" These are the basic fundamentals of good customer service. We still need objectives and scope statements, even on agile projects. It's just that we recognize uncertainty more.
And speaking of uncertainty, proper preliminary research and planning can often help reduce it, and contingencies or buffers can help prepare for the unexpected. Piecemeal deliverables (iterations) can also help, as learnings can be applied to the next phase.
Labels: agile, project-plan, Success, success-measures




