Data Is Not the Problem. Good Decisions Are the Problem.
When you collect data, you’ve simply added cost. You need to add decisions to add value. However, adding decisions about operational situations is challenging. Knowing, at any time point, the location of every truck, the pressure value at every valve, or the status of every vibration sensor does not mean that we know how to act. Data-rich systems sometimes result in poorer decisions.
Decision support systems are usually focused on finding ways of collecting, transmitting, mining, and visualizing data. The last critical piece, decision-making, is left to the user. Frequently, organizations try to overcome this barrier to effective decision making by using various operations analytics tools, including data mining and statistical pattern recognition. However, these approaches provide only a part of the solution. Making decisions, for humans or computers, is far from straightforward. Usually, we have many constraints, competing objectives, and ad hoc knowledge, and often the problems themselves get exponentially more difficult to solve when the number of components increases.
Recent developments in scheduling, planning and optimization have opened new opportunities for improved operations in the resource industry. This presentation will discuss some of these developments and give examples.