Purpose – There is significant potential for adding value by involving customer in the design process and delivery of logistic services. In order to add value to the overall logistic system, the purpose of this paper is to apply an integrated systems approach for the design of forward and reverse logistics services in order to build a self-organising service that can maximise efficiencies and in particular reduce reverse logistics costs.
Design/methodology/approach – Two exploratory case studies were conducted in the logistics systems of housing repair and maintenance sector in the UK. Data were collected using semi-structured interviews, observations, and documented evidence.
Findings – The findings of the cross-case analysis suggests that systems approach expressed as the Vanguard Method (Seddon, 2008) has a direct impact on enhancing forward logistics performance and reducing reverse product flows by nourishing three dimensions for learning from demand-driven
analysis; capturing customer clean information, demand predictability and categorisation, and failure demand analysis.
Research limitations/implications – Findings from exploratory case studies cannot be easily generalised. Hence, further case studies are needed to enrich the findings, and to facilitate their industrial applications. Further, the paper explores the utilisation of the Vanguard Method only in the area of housing repairs and maintenance logistics services. It would be valuable for future studies to further investigate the utilisation of the Vanguard Method in other logistics services settings.
Originality/value – The paper demonstrates an important dynamics of how logistics services can incorporate customer demands into the logistics design process.
Keywords: UK, Demand management, Customer requirements, Information exchange, Supply chain management, Reverse logistics
Paper type: Research paper

Title

The International Journal of Logistics Management

Publisher

Emerald Group Publishing Limited

Publisher Country

United Kingdom

Indexing

Thomson Reuters

Impact Factor

1.776

Publication Type

Both (Printed and Online)

Volume

27

Year

2016

Pages

947-971