When it comes to collecting more data on development, or other processes, we start to think about using data analysis techniques in order to make predictions for the future. We may use this information to predict project costs, upcoming deadlines, or the necessary, required resources. In the past, businesses have used this approach for other functions, such as in finance to predict sales or budgets.
Sometimes we start to believe that it is possible to get exact predictions all the time. Unfortunately, this mindset leads us into a prediction trap because in real life, it is not as easy as we think to make accurate predictions and there are more cases of wrong predictions than right ones.
In his famous book “The Signal and the Noise: Why So Many Predictions Fail — But Some Don’t., Nate Silver advices us to think about predictions in a probabilistic way, meaning that although predictions may not fall to an exact number, many fall into a similar range, making it possible to achieve a level of understanding.
This probabilistic view is very similar to Agile in nature. Agile defines situations where you can’t forecast everything that will be required, but you can start with a vision of where you want to go and be prepared to shift and adjust it over time.
How often do you stick to one number as a goal and miss other opportunities only because they may be slightly off from your intended objective?