Revisiting the value of data sharing in retail supply chain demand planning

Purpose

This study focuses on the value of data sharing in retail supply chains in terms of its impact on manufacturers’ demand planning. It investigates how manufacturers’ access to retail data influences their forecast accuracy and enhances the alignment between retailers’ and manufacturers’ demand planning.

Design/methodology/approach

Based on a mixed methods approach, we first observed four consumer packaged goods manufacturers, which integrated Point of Sales data into their forecasting algorithms, and measured the resulting improvements in the forecast accuracy. Second, we conducted semi-structured interviews with two manufacturers, three retail chains and industry experts from a solution-provider company to explore the mechanisms through which retail data sharing aligns demand planning at tactical and operational levels.

Findings

The quantitative study’s results indicate that retail data integration generally does not yield significant improvements in forecast accuracy. However, qualitative exploration reveals that continued investment in data sharing is driven by its use in demand planning alignment, where it can deliver substantial tactical and operational benefits. Retail data, in the form of replenishment forecasts, enable improved planning alignment by facilitating automated routine processes, proactive exception management and enhanced synchronization of production volumes and delivery schedules.

Originality/value

This study contributes to the supply chain information-sharing literature by reframing the value of retail data sharing as a driver of planning alignment rather than forecast accuracy improvement. Moreover, it proposes the regular sharing of replenishment forecasts as a scalable alternative to expert-based collaborative demand planning, suitable for adoption across an extensive supplier base without requiring intensive resource commitments.