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Optimising supermarket promotions of fast moving consumer goods using disaggregated sales data: A case study of Tesco and their small and medium sized suppliers

Malik, Sheraz Alam (2015) Optimising supermarket promotions of fast moving consumer goods using disaggregated sales data: A case study of Tesco and their small and medium sized suppliers. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:53834)

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Abstract

The use of price promotions for fast moving consumer goods (FMCG’s) by supermarkets has increased substantially over the last decade, with significant implications for all stakeholders (suppliers, service providers & retailers) in terms of profitability and waste. The overall impact of price promotions depends on the complex interplay of demand and supply side factors, which has received limited attention in the academic literature. There is anecdotal evidence that in many cases, and particularly for products supplied by small and medium sized enterprises (SMEs), price promotions are implemented with limited understanding of these factors, resulting in missed opportunities for sales and the generation of avoidable promotional waste. This is particularly dangerous for SMEs who are often operating with tight margins and limited resources.

This thesis explores the scope for improving the planning and execution of supermarket promotions, in the specific context of products supplied by SME, through the use of dis-aggregated sales data to forecast promotional sales and allocate promotional stock. An innovative case study methodology is used combining qualitative research to explore the promotional processes used by SMEs supplying the UK’s largest supermarket, Tesco, and simulation modelling, using supermarket loyalty card data and store level sales data, to estimate short term promotional impacts under different scenarios and derive optimize stock allocations using mixed integer linear programming (MILP).

The results suggest that promotions are often designed, planned and executed with little formalised analysis or use of dis-aggregated sales data and with limited consideration of the interplay between supply and demand. The simulation modelling and MILP demonstrate the benefits of using supermarket loyalty card data and store level sales data to forecast demand and allocate stocks, through higher promotional uplifts and reduced levels of promotional waste

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Fearne, Andrew
Thesis advisor: O'Hanley, Jesse
Thesis advisor: Wu, Shaomin
Uncontrolled keywords: Sales promotions, simulation,optimisations
Subjects: H Social Sciences > HF Commerce
H Social Sciences > HF Commerce > HF5351 Business
Divisions: Faculties > Social Sciences > Kent Business School
Depositing User: Users 1 not found.
Date Deposited: 22 Jan 2016 16:00 UTC
Last Modified: 15 Feb 2020 04:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/53834 (The current URI for this page, for reference purposes)
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