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Researching in Operations Management: Practice and Collaboration

By Pedro Amorim*

Operations Management is a broad research field that has organizations as its main stakeholder. We may define it as the discipline that deals with the design and management of supply chains by considering its products, services and processes. Such a broad discipline yields a considerable amount of complexity that translates into multiple perspectives of the same research stream. Typically, research in the field of Operations Management is performed using one of the four methods: analytical modeling, behavioral, case study and empirical.

Consider for example the problem of defining the ship-pack of a retailer from its warehouses to its stores. Using analytical modeling (coming more from the operations research community) we could jump into defining a mixed-integer model that aims at finding the ‘optimal’ ship-pack given constraints, such as the storage space. With behavioral methods (borrowing ideas from psychology) we could infer the impact of different ship-packs on the consumer purchasing patterns of final clients. Using case studies (generally based in social sciences) we could try to infer good policies for setting ship-packs by studying detailed observations of real-word cases. Finally, using empirical methods (also generally based in social sciences) it would be possible to have a more data-driven approach and look into previous decisions of ship-pack changes to analyze how they correlate with cost and sales figures.

Instead of trying to find what method suits more a given Operations Management problem, we should acknowledge that relevant research in this field needs to follow a stage process in which these different methods will fit unevenly. To tackle a research stream with rigor, we should undertake the following four stages: (1) Find and describe the problem using the available (or made) tools such as taxonomies and using case study methods for example; (2) Question the research gaps and their pertinence and access the suitability of the modelling techniques to be used; (3) Model the problem at hands using probably either behavior methods or analytical modelling; (4) Validate the results obtained through the models to show their relevance and improve their content.

Going back to the ship-pack definition example, in stage (1) one could look into different retailers to understand the key concerns related with its definition. Then, in stage (2), we should probably look into research questions such as what is the relationship between shelf-life and the ship-pack size. To answer this question and others we could use an analytical cost model in stage (3) and, finally, in stage (4) we could implement our model in a retailer and control key indicators to assess its validity.

By dragging away the focus on the methods and positioning the Operations Management research stages at the center of the researchers’ concerns, it is evident the importance of practice, particularly to connect and perform the first and fourth research stages. In the first stage, practice is critical to find the right motivation and describe problems that are important to organizations, and in the fourth stage, practice is the only way to understand the limitations and the value of the research efforts in a real-world setting.

Last but not least, this discussion leads to another important conclusion, which is the need for collaborative efforts in order to explore with rigor Operations Management research streams. Hence, researchers should continue to specialize in a given method, but have a clear idea of their positioning in the research stream that should be steered and integrated by other (more senior) researchers.

INESC TEC with its close positioning to decision makers and the complementarity of its researchers in Operations Management is in a privileged position to excel in this field!

*Centre for Industrial Engineering and Management (CEGI)