On Explaining Operations Research to Others

I’ve decided to start writing posts on operations research.  This seems natural to me as (1) I recently created a blog, (2) I just started a sabbatical, (3) I’ve been in O.R. for over 30 years, and (4)  I think I have something to say that is worth saying.  By the way, I don’t distinguish between management science and operations research.

I’ll start with a fundamental question.  What is Operations Research?  If you go the INFORMS website, you will see the following definition. “Operations research is the application of advanced analytical methods to help make better decisions.”   When describing O.R. to others, I prefer the shorter definition “The science of decision making.”  It’s short enough to be memorable, and conveys useful information that points listeners in the right direction.

As an aside, I really dislike the INFORMS term “the science of better.”  I know that it was not intended as a definition of O.R., but it sounds like a definition, with the disadvantage that it is opaque.  I know it was intended to encourage outsiders to become engaged, but I think that it is actually off-putting.  

But regardless of the definition used, others will have little clue what operations research is after they hear the definition.  Moreover, they will forget the definition within a short period of time (even if they are your parents).  So, it helps to give an example or two of O.R. applications to give others a sense for what is involved.  Given my natural research inclination, I’ll give an algorithm expressed in high level pseudo-code on how to give useful examples.  This may sound like a joke; or at the very least, it sounds like I’m not being serious.  But I actually do use this algorithmic approach when I explain Operations Research to someone who asks about it.

Algorithm for describing operations research to a friend or colleague.

Step 1.   Find out a system about which the other person is both interested and knowledgeable.  (e.g, sports, entertainment, communication, travel, or anything relating to a person’s job.

Step 2.    Develop a plausible scenario based on the system in Step 1; e.g., scheduling sports teams, designing wireless phone systems to provide for the best possible reception, or designing queuing systems at Disneyworld. (I have found that it is very useful to give an example that addresses a problem at the other person’s work that he or she just told you was important.)

Step 3.    Explain how operations research can be used to find an excellent solution for the scenario in Step 2 or provide very useful information for the scenario in Step 2. 

It is OK to modify the definition of O.R. depending on the example given.  For example, if one illustrates O.R. by talking about queuing at Disneyworld, one can modify the definition of O.R. to “The science of designing efficient systems.”   This definition is perhaps less precise; however, an overly keen desire for precision should not get in the way of a good explanation.


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8 Responses to “On Explaining Operations Research to Others”

  1. Michael Trick’s Operations Research Blog : On “On Explaining Operations Research to Others” Says:

    […] wide-ranging than this one, including education and politics along with operations research. His first OR post is on a great topic:  what do you say when someone asks “So what is Operations […]

  2. rif Says:

    I find that I often like to use a more historical approach. Something along the lines of “In World War II, people really started to figure out that large-scale planning problems (How do I get my tanks and people to Europe as quickly as possible?). During this period and later, a wide variety of mathematics and algorithms were developed to solve problems of this type. Today, Operations Research is all those problems, plus all this mathematics, plus any other problems you can solve with the same math, which turns out to be nearly everything.”

    Obviously, it’s historically a gross simplifciation. But these days, OR is very broad. Many (though not all) people doing artificial intelligence or machine learning (where I ended up doing my PhD work) could be said to be doing OR. So could a bunch of people in computational biology. And even a field like physics simulations end up having a lot in common with OR at the level of technique — a lot of convex optimizations, or convex approximations to non-convex optimizations.

    By the way, welcome to the blogosphere! I look forward to reading your future posts.

  3. Larry Says:

    I love this blog post. I found in on Michael Trick’s blog. I even paraphrased it on my blog. You definition really sells and conveys the idea of Operations Research. I’m looking forward to hearing more about OR from your experiences.

  4. John Says:

    My experience as a consultant is that using the terms Operations Research or Management Science doesn’t give your client a clue on what you can achieve. I agree with Jim that it is better to use examples, preferable in terms of the business area your client is in. Many times OR is seen as a subject you can study at university but doesn’t help you in practice. Using terms like algorithm or optimisation to explain it doesn’t help to do away with that misunderstanding. We should therefore use non technical terms in explaining what OR is and how it can create added value, using appealing examples. The examples should come from your own experience or testimonials from your customers. These will help you to show what OR really is.

  5. Explaining what is Operations Research « www.GuidoDiepen.nl Says:

    […] Now there always was the problem that I have to explain to other people what exactly Operations Research is. The other day I found the perfect post about this on the blog of Michael Trick, who in turn got this from the first OR post on the blog of Jim Orlin. […]

  6. OR/MS Recession? * « Güzin Bayraksan’s OR Blog Says:

    […] me.  Our blogs aim to promote the word (e.g., see the subtitle of this blog).  Heck, we even have an algorithm to describe it.  Perhaps it is a function of the fact that we have yet to agree upon a unified term for […]

  7. jrears Says:

    Excellent idea. I have decided on doing this as well. I am just getting started. I will follow your developments here so as to not repeat your
    comments except maybe to refer others to your blog (assuming you give me permission to do so first). Thanks for this and the inspiration. I have been working in operations research for about 20 years now. Discovered I am a perfect fit for this profession late in life. I was a mathematician, a chemist, and other professions before this one. Thanks again.


  8. jrears Says:

    Correction on the above post should read 10 years and not 20.

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