O.R. is the discipline of applying advanced analytical methods to help make better decisions. Also called Management Science or Decision Science, O.R. is the science of Decision-Making. Employing techniques from mathematical sciences, O.R. arrives at optimal or near-optimal solutions to complex decision-making problems. For example, to determine the maximum (e.g. profit, performance, or yield) or minimum (e.g. loss, risk, or cost).
OR/MS is not new as it started during World War II but it has been re-branded as Analytics recently. The techniques used in O.R. sit at the top half of Analytics Evolution diagram shown above. A brief screencast video introduction of where O.R. fits in the Analytics big picture.
There are 3 types of analytics: descriptive (what has happened), predictive (what will happen), and prescriptive (what should happen). Prescriptive Analytics or Optimization recommends one or more courses of action and showing the likely outcome of each decision so that the business decision-maker can take this information and act.
Here are the O.R. leading edge techniques:
- Simulation (predictive analytics)
- Giving you the ability to try out approaches and test ideas for improvement
- Optimization (prescriptive analytics)
- Narrowing your choices to the very best where there are virtually innumerable feasible options and comparing them is difficult
- Probability and statistics (predictive analytics)
- Helping you measure risk, mine data to find valuable connections and insights, test conclusions, and make reliable forecasts
Here are some useful links if you would like to learn more about O.R.:
My personal view about O.R. in Malaysia.