Why "big data" is proving elusive in retail supply chains

About five years or so ago, "big data" became "the next big thing." Consultants, analysts, and researchers argued that there was a wealth of useful information in nontraditional data sources like social media posts, video images, and weather reports. The companies that could successfully amass, analyze, and act on that data would seize a significant competitive advantage, they said.

But realizing this vision has proved to be difficult, according to "Current State of Big Data Use in Retail Supply Chains," a new report published by CSCMP, in conjunction with the Food Marketing Institute. The report's authors—Mark Barratt of Marquette University, Anníbal Camara Sodero of University of Arkansas, and Yao (Henry) Jin of Miami University—found that while many companies think they have implemented big data projects, true applications of big data in the retail industry are rare.

The researchers define big data as "the nearest to real-time as possible gathering, storage, analysis, and decision making based on large sets of both quantitative and qualitative data in structured and unstructured formats." They found that, in practice, most companies were still relying on data from traditional sources, such as point-of-sale and on-hand inventory data, and had not yet delved into sources outside of structured database formats. Furthermore, data was still being created, analyzed, and utilized in batches instead of in real time.

The report details the main reasons why the use of big data has been so limited. These include being unaware of all of the sources of data, not knowing what questions to ask the data, a lack of standardization, and a lack of necessary skills. The benefits of overcoming these barriers are huge, according to the authors. The report suggests that only through big data analyses can companies achieve true omnichannel retailing and become demand-driven.

CSCMP members can download the report for free here. The cost for nonmembers is US $15.95.