We are pleased to introduce this Editor’s Cut on Transforming Retail through Analytics. The topic of retail analytics is well worth systematic attention from researchers and practitioners for several reasons: (1) retail has always been a key point of customer contact; (2) digital information flow between all parties in all directions is burgeoning; (3) retailing is dynamic: there are new formats and platforms; and power is shifting between channel and supply chain participants; and (4) many new tools for data collection and analysis are being developed. This Editor’s Cut provides relevant materials to help us take stock of where this field is and where it is going.

As background, analytics has been defined as “the scientific process of transforming data into insight for making better decisions.” Analytics is an “end-to-end” process in the following sense. Analytics professionals engage in seven key domains of activity, according to an INFORMS Job Task Analysis. The analytics process covers these domains – starting from the business problem formation, then framing the problem as an analytics problem, collecting data, applying the right methodology, building the model with that methodology, and finally, deploying the model, and lifecycle modification and management of the model. One can distinguish between three types of analytics applications: descriptive (what happened or is happening), predictive (what is likely to happen in the future), and prescriptive (what is the best outcome).

To assemble the content in this Editor’s Cut, we first identified twelve topics in retailing. These are topics commonly applied by retail professionals and taught in classes on retailing. Not every one of these topics, however, has been covered extensively in academic research or in INFORMS journals, in particular. So we found it useful to group the topics into three broad areas: (1) strategic positioning (setting or choosing the value proposition, the store assortment, merchandising policies, store locations, store layout and design, and service and personnel guidelines), (2) tactical decision making (managing pricing, the supply chain, and profitable financials), and (3) communications management (effective selling, communications, and online retail points-of-contact). Concerning methodology/approach, the research on retailing, in general, can be grouped into four categories: (i) empirical analysis, (ii) analysis of policies, algorithms, and heuristics, (iii) analytical micro modeling, and (iv) practitioner applications and teaching materials.

We drew from INFORMS journals for the research papers in this Editor’s Cut on Transforming Retail through Analytics. We also make available a much longer extended list, drawn from a wider selection of sources. Lastly, we created our own video of interviews with selected leaders and managers in retailing in U.S., Canadian, and Australian companies. Some elaboration on the content selection is necessary.

First, most of the research papers concern the first five stages of the analytics process. These papers devote particular attention to methodology and model building, as well as relevant attention to the antecedent steps of business problem formulation, analytics problem framing, and data considerations. Perhaps more research attention could be devoted to stages 6 and 7, concerning deployment and model lifecycle management. The practitioner papers, industry reports, videos, and podcasts, however, do deal extensively with deployment and lifecycle management.

Second, concerning the types of analytic applications, most of the materials that we make available online here are descriptive and predictive. A smaller number of the materials are prescriptive applications of analytics. Third, concerning coverage of retail topics, half of the research papers are about tactical retail decisions, some deal with communications management, and the fewest deal with strategic retail positioning. This is perhaps because the fields of operations research and the management sciences often provide methods and procedures to improve upon a strategy that has already been selected.

Fourth, concerning methodology, one-third of the research papers fall in the category of “Analysis of Policies, Algorithms, and Heuristics.” These six papers appear in Management Science, MSOM, and Operations Research, and mostly deal with predictive analytics, and some prescriptive, applications. Two-thirds of the research papers fall in the category of “Empirical Analysis.” These 12 papers appear in Marketing Science, Management Science, Information Systems Research, Organization Science, and MSOM, and mostly deal with descriptive analytics, with some predictive applications.

Fifth, and very importantly, there is also a large body of work devoted to retailing issues that use analytical micro modeling, including modeling with game theory. This work is not formally part of the analytics process, so this work is not included in this volume of Editor’s Cut. But this work has improved our understanding of retail, supply chains, and channels of distribution in a number of ways and has added considerably to our conceptual and theoretical understanding. Therefore, we created an extended list that includes this large body of work.

Extensive changes in retailing call for continued assessment of the new environment. There has been a shift in power in channels of distributions and supply chains, with less power for some traditional brick-and-mortar retailers, emergence of online platforms, and growing power of consumers. This has led at least 17 retailers to close large numbers of brick-and-mortar stores in North America and at least one market analyst to eschew the retailing sector altogether. Retailers serve key functions in society, but they are not immune to competitive pressures or to the structural implications of new technology and accompanying societal changes. Indeed, retailers are at the heart it.

Analytics can help retailers adapt and thrive in this changing environment. Retailers need to understand how analytics can be leveraged for more efficient decision making, and many of the resources in this Editor’s Cut provide ideas and guidance. At the same time, there is a critical gap between advanced methods of data acquisition and analytics, on the one hand, and the usability of the information and techniques for managers when making practical decisions, on the other hand. This was particularly emphasized by Brett Halliday (President, North America, Michael Hill jewellers) in our interview video (starting at minute 4:00). The need for analytics to provide actionable intelligence is a challenge that must be continually addressed.

We close by emphasizing that the Editor’s Cut volume is a process, and this online resource on Transforming Retail through Analytics will be updated periodically. Please do not hesitate to send us your suggestions and comments.