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Logistics 2017, 1(2), 12; https://doi.org/10.3390/logistics1020012

An Exploration of Big Data Practices in Retail Sector

1
Cranfield School of Management, Cranfield University, College Road, Cranfield MK43 0AL, UK
2
Apple Computer Trading (Shanghai), No. 391 Yuanshen Road, Pudong, Shanghai 200135, China
*
Author to whom correspondence should be addressed.
Received: 29 September 2017 / Revised: 1 December 2017 / Accepted: 6 December 2017 / Published: 12 December 2017
(This article belongs to the Special Issue Digital Logistics)
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Abstract

Connected devices, sensors, and mobile apps make the retail sector a relevant testbed for big data tools and applications. We investigate how big data is, and can be used in retail operations. Based on our state-of-the-art literature review, we identify four themes for big data applications in retail logistics: availability, assortment, pricing, and layout planning. Our semi-structured interviews with retailers and academics suggest that historical sales data and loyalty schemes can be used to obtain customer insights for operational planning, but granular sales data can also benefit availability and assortment decisions. External data such as competitors’ prices and weather conditions can be used for demand forecasting and pricing. However, the path to exploiting big data is not a bed of roses. Challenges include shortages of people with the right set of skills, the lack of support from suppliers, issues in IT integration, managerial concerns including information sharing and process integration, and physical capability of the supply chain to respond to real-time changes captured by big data. We propose a data maturity profile for retail businesses and highlight future research directions. View Full-Text
Keywords: big data; retail operations; maturity; availability; assortment; replenishment; pricing; layout; logistics big data; retail operations; maturity; availability; assortment; replenishment; pricing; layout; logistics
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Aktas, E.; Meng, Y. An Exploration of Big Data Practices in Retail Sector. Logistics 2017, 1, 12.

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