In my training sessions, I often use sports metaphors for project schedule modeling – this, despite my utter lack of any sort of athletic ability and pathological indifference to most sporting events. The thing is, sports events are great examples of predictive models.
Take the World Cup for instance. If I were to ask you who would have taken the Cup way back at the beginning of this thing, you would have selected from 32 teams. At a basic level, we could say that each team has an equal chance of winning. Of course, we can make the model more complex. We can look at individual player performance, historical records, playing style, locations in which matches will be played….. When we throw all of those together, we can create a model of the top 5-10 favored teams.
What is this doing? It’s adding information to the model to predict the future – and providing a range of potential outcomes. Like any schedule, as I learn additional information, I include that in my model and refactor the results. From where I sit at the time of writing, we have now gotten down to the quarterfinals. Of the 32 teams that started, 8 are left. Clearly, I can remove 24 of the original candidates from the list of potential winners.
Simply by removing those 24 from the list, I have greatly increased my chances of being correct about who will win the championship. Can I tell exactly who will win? No, but I can apply my data modeling structure to the remaining teams and come up with a much better prediction than when the games started.
Extrapolate that forward, and as each game is played, the potential outcomes for the competition narrow even further. Eventually, we’re left with two teams – which greatly simplifies the modeling. Finally, at the end, we know who won.
Apply this model to a schedule. We forecast a range of potential outcomes, with a more probably outcome and a less probable outcome. As the project plays out, the range of potential outcomes diminishes. The most probably path becomes more and more apparent.
Another metaphor I commonly use is a toothpaste tube. If you assess the amount of risk, or uncertainty, associated with the schedule. As events increasingly transform from thepotential future to the recent past, the amount of uncertainty goes down. It’s the same as squeezing toothpaste from a tube. At the end of the day, there’s no uncertainty as the project is complete. All of the risk has been squeezed out of the tube.