A business model for uncertainty management

Purpose – To present the application of a business model for holistic uncertainty management for twenty‐first century manufacturing enterprises. Design/methodology/approach – A questionnaire survey is carried out to UK manufacturing enterprises to collect relevant data, and analysis of variance (ANOVA), correlation analysis and cluster analysis are performed to infer the results. Findings – It can be concluded that different manufacturing environments suffer different effects of underlying causes of uncertainty on product tardy delivery. The product tardy delivery performance in make‐to‐order (MTO) manufacturing environment is found significantly affected by a wide range of underlying causes of uncertainty. It is interesting to find that mixed‐mode (MM) manufacturing environment has an opposite outcome. Correlation results provide significant evidence that underlying causes of uncertainty do not have linear association with product tardy delivery. This finding reinforces the proposition that the effects of uncertainty are difficult to quantify due to the compound effect. The cluster analyses of the business environmental factors of the manufacturing enterprises in MM, make‐to‐stock (MTS) and MTO environments found that size of enterprise, product variety, product complexity, number of parts, ratio of buy vs make parts, the use of rough‐cut capacity planning, and the use of buffering or dampening techniques in production, influence the effects of underlying causes of uncertainty on product tardy delivery. Research limitations/implications – Only UK manufacturing enterprises are investigated. The results will be relevant to MTO, MM and MTS manufacturing environments. Practical implications – The application of the business model has provided useful knowledge to MM, MTS and MTO manufacturing enterprises on which underlying causes of uncertainty are significantly affecting their product tardy delivery performance. Originality/value – A holistic approach such as the business model has given a solid foundation for the enterprises to evaluate their performance. Using the knowledge of significant underlying causes of uncertainty, the enterprises could then prioritise the effort and devise suitable buffering or dampening techniques.