There are probably more books on agile methods than successful projects with well-documented agile results. Writing a book on agility or project management, where the decision-making process is laid out in the abstract, is easy compared to managing a real project where you must steer through a minefield of uncertainties and the consequences of decisions under game conditions are very real. We should place increased emphasis on publishing measured improvement case studies. They are critical to accelerating the innovation delivered in software.
Posts Tagged ‘managing uncertainty’
Highly complex systems like societies, economies, and evolution are non-deterministic because they represent unpredictable life forms interacting with each other in chaotic ways. Weather forecasting and earthquake prediction are similarly complex and non-deterministic. These large-scale systems have emergent behaviors where we can create probabilistic models that predict the range of outcomes and likelihood of outcomes, but never the exact outcome. Why? Because there is uncertainty inherent in the interacting elements (i.e., humans with free will, random or unpredictable acts of nature, mutations, innovations, etc.). This does not mean that these predictive models are not useful. It simply means that we must reason about things differently and understand both the distribution of outcomes and the uncertainty inherent in that distribution to make better decisions.