{"id":1454,"date":"2011-05-25T15:56:20","date_gmt":"2011-05-25T19:56:20","guid":{"rendered":"http:\/\/mat.tepper.cmu.edu\/blog\/?p=1454"},"modified":"2011-05-25T15:56:20","modified_gmt":"2011-05-25T19:56:20","slug":"business-analytics-and-operations-research-tomato-to-mah-toe-tractor","status":"publish","type":"post","link":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/2011\/05\/25\/business-analytics-and-operations-research-tomato-to-mah-toe-tractor\/","title":{"rendered":"Business Analytics and Operations Research: Tomato, To-mah-toe, Tractor!"},"content":{"rendered":"

There are few things in life more tedious than assigning boundaries to fundamentally ill-defined concepts.\u00a0 Either terms are used to divide things that cannot be divided (“No, no, that is reddish-purple and clearly not purplish-red!”) or are used to combine groups while ignoring any differences (Republicans?\u00a0 Democrats?\u00a0 just “Washington insiders”).\u00a0 Arguing over the terms is fundamentally unsatisfying:\u00a0 it rarely affects the underlying phenomena.<\/p>\n

So when INFORMS<\/a> (Institute of Operations Research and the Management Sciences), an organization of which I am proud to have been President and equally proud to be Fellow, embarks on its periodic nomenclature debate, ennui overwhelms.\u00a0 Not again!\u00a0 The initial debate between Operations Research and Management Science resulted in two societies (ORSA and TIMS) for forty years before they combined to form INFORMS in 1995.\u00a0 Decision Engineering, Management Engineering, Operations Engineering, Management Decision Making, Information Engineering, and countless other terms have been proposed at times, and some have even made toeholds in the form of academic department names or other usages.\u00a0 None of this has fundamentally changed our field, except perhaps in confusing possible collaborators and scaring off prospective members (“Wow, if they don’t even know who they are then maybe I should check out a more with-it field!”). I decided long ago to just stick with “operations research” and make faces of disgust whenever anyone wanted to engage the issue of the name of the field.<\/p>\n

\"\"<\/a>Then, three years ago (only! check the google trends graph<\/a>) the phrase “business analytics” came along, and it was a miracle!\u00a0 Here was the phrase that really described what we were doing:\u00a0 using past data to predict the future and make better business decisions based on those predictions.\u00a0 That’s us!\u00a0 And, due to books such as “Competing on Analytics”<\/a>, the wider world actually were interested in us!\u00a0 There were even popular books like “The Numerati”<\/a> about us.\u00a0 We were finally popular!<\/p>\n

Except it wasn’t really about “us” in operations research.\u00a0 We are part of the business analytics story, but we are not the whole story, and I don’t think we are a particularly big part of the story.\u00a0 A tremendous amount of what goes by the name “business analytics” are things like dashboards, business rules, text mining, predictive analytics,OLAP, and lots of other things that many “operations research” people don’t see as part of the field.\u00a0 IBM’s Watson<\/a> is a great analytics story, but it is not fundamentally an operations research story.\u00a0 People in these areas of business analytics don’t see themselves as doing operations research.\u00a0 Many of them don’t even identify with business analytics but rather with data mining, business intelligence, or other labels. \u00a0 All of this involves “using past data to help predict the future to make better decisions” but “operations research” doesn’t own that aspect of the world.\u00a0 There are lots of people out there who see this as their mandate but haven’t even heard of operations research, and really don’t care about that field.<\/p>\n

This is not surprising for those with an INFORMS-centric point of view.\u00a0 INFORMS does not (and near as I can tell, ever has) represent even all of “operations research”.\u00a0 According to the Bureau of Labor Statistics<\/a>, there are more than 65,000 people with the job “operations research analyst”.\u00a0 INFORMS membership of a bit more than 10,000\u00a0 is a small fraction of all those involved in operations research.\u00a0 INFORMS is not all of operations research:\u00a0 it certainly is a small amount of business analytics.\u00a0 How can INFORMS “own” business analytics when it doesn’t even own operations research?<\/p>\n

Recognizing this divide does not mean erecting a wall between the areas (see the first paragraph on the mendacity of labels).\u00a0 I think the “business analytics” world has a tremendous amount to learn from the “operations research” world and vice versa.\u00a0 Here are few things the two groups should know (and are clearly known by some on both sides, though not to an ideal extent);\u00a0 I welcome your additions to these lists:<\/p>\n

What Business Analytics People should Learn from Operations Research<\/em><\/p>\n

    \n
  1. Getting data and “understanding” it is not enough.<\/li>\n
  2. Predicting the future does not imply making better decisions.<\/li>\n
  3. Lots of decisions are interlinked in complicated ways.\u00a0 Simple rules are often not enough to reconcile those linkages.<\/li>\n
  4. Handling risk is more than knowing about the risk or even modeling the risk.\u00a0 See “stochastic optimization”.<\/li>\n
  5. Organizations have been competing on and changed by analytics for a long, long time now. \u00a0 See the Edelman competition<\/a> to start.<\/li>\n
  6. Operations research is not exactly an obscure field.\u00a0 Check the google trends of “operations research” versus “business analytics”<\/a> (with OR in blue and BA in red).\"\"<\/a><\/li>\n<\/ol>\n

    What Operations Research People should Learn from Business Analytics<\/em><\/p>\n

      \n
    1. It is not just the volume of data that is important:\u00a0 it is the velocity.\u00a0 There is new data every day\/hour\/minute\/second, making the traditional OR approach of “get data, model, implement” hopelessly old-fashioned.\u00a0 Adapting in a sophisticated way to changing data is part of the implementation.<\/li>\n
    2. Not everything is complicated.\u00a0 Sometimes just getting great data and doing predictions followed by a simple decision model is enough to make better decisions.\u00a0 Not everything requires an integer program, let alone a stochastic mixed integer nonlinear optimization.<\/li>\n
    3. Models of data can involve more than means and variances, and even more than regression.<\/li>\n
    4. One project that really changes a company is worth a dozen papers (or perhaps 100) in the professional literature.<\/li>\n
    5. It is worthwhile for people to write about what is done in a way that real people can read it.<\/li>\n<\/ol>\n

      I believe strongly in both operations research and business analytics.\u00a0 I have spent my career advancing “operations research” and have never shied from that name.\u00a0 And I just led an effort to start an MBA-level track in business analytics track at the Tepper School.\u00a0 This track includes operations research courses, but includes much more, including courses in data mining, probabilistic marketing models, information systems, and much more.<\/p>\n

      The lines between operations research and business analytics are undoubtedly blurred and further blurring is an admirable goal.\u00a0 The more the two worlds understand each other, the more we can learn from each other.\u00a0 INFORMS plays a tremendously important role in helping to blur the boundaries both by sharing the successes of the “operations research world” with the “business analytics” world, and by providing a conduit for information going the other way.\u00a0 And this, more than “owning” business analytics, is what INFORMS and its members should be doing.<\/p>\n

      Ironically, this is part of the INFORMS Blog Challenge<\/a>.<\/em><\/p>\n

       <\/p>\n

       <\/p>\n","protected":false},"excerpt":{"rendered":"

      There are few things in life more tedious than assigning boundaries to fundamentally ill-defined concepts.\u00a0 Either terms are used to divide things that cannot be divided (“No, no, that is reddish-purple and clearly not purplish-red!”) or are used to combine groups while ignoring any differences (Republicans?\u00a0 Democrats?\u00a0 just “Washington insiders”).\u00a0 Arguing over the terms is … Continue reading “Business Analytics and Operations Research: Tomato, To-mah-toe, Tractor!”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8,28],"tags":[],"class_list":["post-1454","post","type-post","status-publish","format-standard","hentry","category-business-analytics","category-informs"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1454","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=1454"}],"version-history":[{"count":0,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1454\/revisions"}],"wp:attachment":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1454"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1454"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1454"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}