Emerging procurement technology: data analytics and cognitive analytics

Abstract

Purpose The purpose of this paper is to elucidate the emerging landscape of procurement analytics. This paper focuses on the following questions: what are the current and future state of procurement analytics?; what changes in the procurement process will be required to enable integration of analytical solutions?; and what future areas of research arise when considering the future state of procurement analytics? Design/methodology/approach This paper employs a qualitative approach that relies on three sources of information: executive interviews, a review of current and emerging technology platforms and a small survey of subject matter experts in the field. Findings The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years. However, there currently exists a low usage of advanced procurement analytics, and data integrity and quality issues are preventing significant advances in analytics. This study identifies the need for organizations to establish a coherent approach to collection and storage of trusted organizational data that build on internal sources of spend analysis and contract databases. In addition, current ad hoc approaches to capturing unstructured data must be replaced by a systematic data governance strategy. An important element for organizations in this evolution is managing change and the need to nourish an analytic culture. Originality/value While the majority of forward-looking research and reports merely project broad technological impact of cognitive analytics and big data, much of it does not provide specific insights into functional impacts such as the impact on procurement. The analysis of this study provides us with a clear view of the potential for business analytics and cognitive analytics to be employed in procurement processes, and contributes to development of related research topics for future study. In addition, this study suggests detailed implementation strategies of emerging procurement technologies, contributing to the existing body of the literature and industry reports.

Structuring the phenomenon of procurement digitalisation: contexts, interventions and mechanisms

“…The nature of the phenomenon of interest presents an interesting challenge for this research. Much of procurement digitalisation has not yet been realised at scale, at least in its advanced forms, including predictive analytics, artificial intelligence and blockchains (Handfield et al, 2019;Gray and Prud'homme, 2019). Therefore, observing the actual states of the response variables is challenging.…”

Supply chain management and Industry 4.0: conducting research in the digital age

“…Stank et al (2019) used MRT to introduce a theoretically grounded DDP. Handfield et al (2019) used theoretical constructs in their interviews with company executives and developed a…”

The big data-business strategy interconnection: a grand challenge for knowledge management. A review and future perspectives

“…With reference to strategic sourcing activities, BDA enable the construction of cost prediction and risk assessment models. These models prove useful to analyse the spending profiles of current and potential suppliers, select new suppliers based on the best value proposals and monitor the activity of existing suppliers and supply market dynamics to avoid risks of interruptions within the production cycle (Handfield et al, 2019;Wang et al, 2016). With regard to the physical configuration of the SC, BDA can support decisions regarding the number, position and size of production plants and distribution centres, primarily through optimisation and what-if analysis techniques (Nguyen Dang Tuan et al, 2019).…”

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