Leveraging Human Solutions in Operations Research

People maintain control in spite of our new machine overlords.

Operations Research (O.R.) projects often focus on trying to take control of the entire problem, and therefore fail when the engineer or manager with the ultimate control cannot validate, verify, or sometimes even follow the solution recommended by the software. So we add graphics and simple ways of explaining the results, hoping the person with power gets comfortable and follows the recommendation.  But when that person doesn’t have a Ph.D. in O.R., they still don’t completely trust the solution. Why is that?

  • Sometimes it is because they know something the software doesn’t.
  • Maybe it is because there are requirements or constraints they just can’t articulate.
  • Perhaps it is because there are unpredictable events that the user believes could happen, and would cause the software to do very bad things.

All these possible reasons, and more, make it difficult to trust the software. Even when a person, even an expert, can’t possibly do a better job at finding the right solution, the user doesn’t trust. So the solution is again ignored.  I’ve seen this time and time again.

It seems time to try an alternate approach: use our O.R. skills to convert the problem to one the engineer or manager has a fighting chance to solve, and make sense of the results. Use our applied mathematics skills to clarify the problem, not just optimize. When O.R. works, I contend you will find that the real work does exactly that, converts the problem to help the person solve it, not try to take the reins from the person.

After much time trusting and validating, maybe they will ask for the decision to be automated. But not right away, not all the time, and not without an option to take back the reins.

About Rupe

Dr. Jason Rupe wants to make the world more reliable, even though he likes to break things. He received his BS (1989), and MS (1991) degrees in Industrial Engineering from Iowa State University; and his Ph.D. (1995) from Texas A&M University. He worked on research contracts at Iowa State University for CECOM on the Command & Control Communication and Information Network Analysis Tool, and conducted research on large scale systems and network modeling for Reliability, Availability, Maintainability, and Survivability (RAMS) at Texas A&M University. He has taught quality and reliability at these universities, published several papers in respected technical journals, reviewed books, and refereed publications and conference proceedings. He is a Senior Member of IEEE and of IIE. He has served as Associate Editor for IEEE Transactions on Reliability, and currently works as its Managing Editor. He has served as Vice-Chair'n for RAMS, on the program committee for DRCN, and on the committees of several other reliability conferences because free labor is always welcome. He has also served on the advisory board for IIE Solutions magazine, as an officer for IIE Quality and Reliability division, and various local chapter positions for IEEE and IIE. Jason has worked at USWEST Advanced Technologies, and has held various titles at Qwest Communications Intl., Inc, most recently as Director of the Technology Modeling Team, Qwest's Network Modeling and Operations Research group for the CTO. He has always been those companies' reliability lead. Occasionally, he can be found teaching as an Adjunct Professor at Metro State College of Denver. Jason is the Director of Operational Modeling (DOM) at Polar Star Consulting where he helps government and private industry to plan and build highly performing and reliable networks and services. He holds two patents. If you read this far, congratulations for making it to the end!
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