In the service industry, success often favours those who deliver higher performance and value in the eyes of their partners and/or end-customers. The performance of the delivered service, however, may not always meet the expectations of the buyer, or the service quality may be evaluated differently by the supply chain partners, leading to a performance shortfall in both cases.
A perception gap refers to the differences in perception among the stakeholders regarding any aspect of the supply chain relationship. But how are such gaps associated with the performance of service supply chains and any resultant performance gaps? How can service supply chain partners identify, quantify, and eliminate the perception gaps?
Above research questions have recently been studied in an international and multi-institutional collaboration project conducted by LBS researcher Dr. Sean Asian, Dr. Dawei Lu (University of Warwick), Dr. Gurdal Ertek (Abu Dhabi University), and Mete Sevinç (Cognizant Technology Solutions Corporation, Netherlands). Their results have been published as a research paper, entitled “Mind the perception gap: An integrative performance management framework for service supply chains”, in the International Journal of Physical Distribution & Logistics Management (Impact factor 2017: 4.215).
Improving supply chain performance
In this multi-disciplinary project, the project team collaborated with a leading UK-based insurance company to improve their supply chain performance in three phases: First, they investigated the existence of perception and performance gaps along the supplier-buyer interface: Second, examined the association between the perception gaps and the performance: And, third, constructed an integrative framework that factors-in the perception gap into service supply chains and measures them through meta-KPIs.
The presented research confirmed that perception gaps do exist and can have significant association with the performance gaps along the service supply chain. The development of the presented analytical framework for quantifying the gaps extends the theoretical boundary of supply chain performance management and offers a new window to both researchers and practitioners.
Although the data tested and analysed in this research were sourced from the insurance service industry, the nature of the findings are general and can contribute to a more extensive body of knowledge from which new theories specific to supply chain management may be induced. For example, the presented methodology can be used as the computational engine behind the supply chain initiatives that aim at the identification and elimination of perception gaps. This ultimately can enable them to reduce the perceived gaps to an insignificant level through collaborative efforts, such as sharing key relevant information and synchronizing their perceptions.
Another possible implication is the analysis of data from diverse real-world cases and the observation of patterns across them. While big data is ubiquitously available and data science tools are becoming mainstream, the potential for similar research is practically unlimited. For example, unexplored primary data readily available in companies’ ERP systems (Enterprise Resource Planning), as well as additional secondary data, can be analysed through exploratory, descriptive, predictive, and prescriptive data science techniques to observe phenomena, propose hypotheses, and develop a plethora of general theory that is highly relevant, actionable, and applicable. This research can serve as an example, especially in the supply chain performance management literature, of how such a combined study can be conducted.
Dr. Sean (Sobhan) Asian is a management scientist and operations researcher, with special interests in exploring and solving complex Supply Chain Management, Logistics, and Transportation problems. To further discuss this research and explore any possible collaboration please directly contact Dr. Sean Asian (S.Asian@latrobe.edu.au).