Why Are All the Softies in Europe? A Discussion of the Lack of Penetration of Soft OR in the US

Soft Operations Research (OR) methods are used for a variety of real-world problems due to their focus on qualitative or interpretative problem formulation and analysis. Analysts use Soft Systems Methodology for problem structuring, drama theory for understanding conflicts, and morphological analysis for decision support. These techniques have an advantage over their quantitative counterparts because they can be used to tame wicked problems. So why is the use of soft OR not widespread in the US? In this paper, we discuss the systems and forces in place that limit soft OR within the US' higher education system and, by extension, the US' OR labour market. We discuss the failed attempts to buck this trend and the consequences of continuing with the hard OR-focused status quo. 1.0 INTRODUCTION “Problem solvers have been approaching complex problems using a predominantly technical perspective to address complex problems since the advent of large-scale systems in the fledgling radio, television, and telephone industries in the United States during the 1930s” [1] but, as World War II erupted, both the US and UK military used a large number of these problem-solving scientists and engineers to help solve complex logistics problems to support their country’s war efforts. This effort contributed to the philosophy and techniques of the field known as Operations Research (OR). Unfortunately, while the problems faced by OR practitioners and academics alike have continued to evolve over the last seventy years, many antiquated techniques for addressing these problems remain. To address modern complex problems, the authors argue that increased adoption of a class of techniques known as soft OR is necessary to complement traditional OR techniques. We begin our discussion with an introduction to soft OR. We then discuss why soft OR is failing to gain a foothold, especially in the United States, and we provide a historical perspective on how this situation came about. We then address what the consequences of this omission means, and what may be done to correct course and adopt a more inclusive set of techniques in wrestling with truly complex problems. It is the hope of the authors that the reader will join the fight after reading this paper and take up intellectual arms in an effort to broaden the use of soft OR in the US and abroad. 2.0 WHAT IS SOFT OR? Before soft OR can be defined, OR must first be defined. There is much confusion around the definition of OR, starting with the name itself, as different terms are used to describe the same discipline; for example, in ~ NATO ~ OTAN Why Are All the Softies in Europe? A Discussion of the Lack of Penetration of Soft OR in the US 9 2 STO-MP-SAS-OCS-ORA PUBLIC RELEASE PUBLIC RELEASE the military domain, it is called Operations Analysis, Operational Analysis, or Operational Research. Since this paper focuses on general (i.e., non-military) OR in the US, we will use the term preferred in the US, Operations Research. Like its many names, OR has many definitions. We define OR as “giving analytical support to the decision-maker” [2] or “the discipline of applying advanced analytical methods to help make better decisions” (http://www.scienceofbetter.org/what/). However, these are not the only definitions of OR; for example, the Office Professional's Guide defines OR as “the application of scientific principles to business management, providing a quantitative basis for complex decisions” [3] and some have just equated OR to mathematical optimization. Thus, there is an unconscious debate within the OR community as to whether OR is purely quantitative (even simply optimization) or it encompasses all analytical techniques, including those that are both quantitative and qualitative in nature. For those that work with wicked problems [4], or problems in complex adaptive systems [5] or systems of systems [6], the notion that someone could generate an “optimal” solution to their problems might be amusing. In fact, as it pertains to these wicked problems, it has been proposed that optimal solutions are not only unattainable, but they are unnecessary [7]. So-called wicked problems are problems which are hard to solve because they lack complete information, their feasible solutions are not testable, they are unique, and how we understand the problem is based in part on how we want to solve it [8]. Further, there are likely multiple, possibly divergent perspectives on the problem and its resolution [9]. Wicked problems such as climate change, global conflict, and world hunger exist, and decision-makers need to decide how to handle them. But, if we accept the premise that OR is only optimization, then what academic discipline supports decision-makers faced with these wicked problems? We cannot think of a discipline and we believe that operations researchers should not shy away from such problems because they do not fit the optimization paradigm. So, what is soft OR? Using our first definition of OR, soft OR is simply OR techniques that use qualitative or interpretative analytical techniques to support a decision-maker, whereas hard OR is mathematical or quantitative analytical techniques. Examples of soft OR techniques include Soft Systems Methodology [10], cognitive mapping [11], and Strategic Options Development and Analysis (SODA) [12]. These techniques will not be explicitly described here but an overview of them can be found in Hester et al. [13]. Other emerging techniques include Morphological analysis [14] and Drama Theory [15]. Any qualitative technique, e.g., ethnographical analysis, could be used as soft OR approach depending on the problem. Soft OR techniques, of which problem structuring is a part, should be thought of as working in concert with hard OR techniques and not against them. Generally, “soft OR methods are those that structure a problem, as opposed to hard OR that seeks to solve it” [16]. It can be difficult for a decision-maker to determine what the problem actually is (the focus of problem structuring) and this difficultly is the motivation for the development of a great deal of soft OR approaches [2]. This problem of actually defining problems has led to much discussion in the academic literature, for example, messy problems [17], wicked problems [4], and Complex Adaptive Systems [18]. Beyond problem structuring, qualitative issues can be important to decision-makers and should be considered in any analysis of the related problem. For example, the Coca-Cola Company had to reverse its introduction of “New Coke” because of a resultant loss in revenue, which was due to consumers’ purchasing habits changing because they felt a sense of bereavement from the loss of the old product [19]. This phenomenon, found by Coca-Cola, is a qualitative issue and no quantitative technique would have uncovered the underlying issue. 1 “Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. ” (https://www.informs.org/About-INFORMS/What-is-Operations-Research). Why Are All the Softies in Europe? A Discussion of the Lack of Penetration of Soft OR in the US STO-MP-SAS-OCS-ORA 9 3 PUBLIC RELEASE PUBLIC RELEASE Though useful to the decision-makers, the use of qualitative techniques seems to be very limited within the Operations Research literature, especially in the US. The following sections discuss how this lack of use occurred. 3.0 WHAT IS THE PROBLEM? In recent years, it has been commented that academic research, in the OR domain, is not used by practitioners. Tang said that the “returns on Operations Management [a field related to OR] research effort appears to be low” [20]. Pfeffer and Fong argued “that there is little evidence that business school research is influential on management practice” [21]. The authors continually meet practitioners that used to read the OR journals but have given up due to a perceived lack of benefit. Unlike other academic domains, which can be studied for their own sake, OR is a practical subject that should be used. The authors would, therefore, argue that academic OR is there to support the practitioner OR community, but this does not appear to be happening. There is a disconnect between the theory being produced in academia, and the need experienced by practitioners. The theories and methodologies being produced in academic OR literature are impressive feats of technical and intellectual prowess. However, these tools and methods are not the ones required by the practitioners. The academic OR community is guilty of committing Type III errors [22] in that they are “building the wrong models” and thus solving the wrong problems. In an effort to demonstrate their new quantitative methodologies, academic operations researchers make limiting assumptions to the underlying problems they are trying to solve. These limiting assumptions reduce the efficacy of solutions for those actually trying to solve the problem. Examples of these limiting assumptions include assuming zero delivery time in manufacturing models, or assuming that humans are expected utility optimizers (even thought this has been shown incorrect through Allais’ paradox [23] and the Ellsberg paradox [24]). As Tang put it, “results are not insights unless they lead to some real implications about a real [OR] problem. ” Not every problem can be solved with a mathematical model and it is not obvious what every problem actually is, as highlighted by Heyer: “In the 1970s, 80s and 90s, it had become obvious that some [organizational] problems could not be solved by pure logic, employing hard OR. Indeed problems have continued to become more complex and increasingly difficult to model mathematically” [16]. Soft OR can help provide both problemstructuring and qualitative information, e.g., survey data collection, to an operations resear