Decision Intelligence, Optimization, and Operations Research might seem synonymous at first glance as they all involve formulating solutions to complex problems, but they each bring distinct nuances.

Operations Research (OR) is well-known for its focus on developing and applying mathematical models and analytical methods to solve complex decision-making problems. A key aspect of OR is its use of Optimization Techniques, like Integer or Mixed-Integer Linear Programming, which play a crucial role in finding the most efficient or optimal solution from a set of available alternatives. This optimization is instrumental in streamlining operations, making better resource allocation decisions, and enhancing overall organizational decision-making processes. Classic optimization problems include finding the shortest delivery routes, optimally packing objects into boxes, or finding the best staffing schedule.

Decision Intelligence is a powerful evolution of Operations Research. It harnesses the potential of data-driven models to give businesses more control over their decision impacts and empowers them to make better and more efficient decisions.

Need an example? With machine learning, we can model and predict a shop floor’s capacity, utilization, and other factors. With Decision Intelligence methods, we can elevate that model and optimize the shop floor configuration for a desired outcome, like fewer staff overtime hours, higher throughput, or better quality.