A framework for diagnosing the delivery reliability performance of make-to-order companies

• Published in: International journal of production research Vol. 50; no. 19; pp. 5491 - 5507
• Main Authors: Soepenberg, G.D., Land, M.J., Gaalman, G.J.C.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 01.10.2012; Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; Decision making models; Decisions; delivery reliability; Diagnosis; Exact sciences and technology; Firm modelling; Foundations; Inventory control, production control. Distribution; Logistics; make-to-order (MTO); Operational research and scientific management; Operational research. Management science; Production planning; production planning and control (PPC); Reliability; Reliability theory. Replacement problems; Software packages; Studies; Trees; Triangulation; Dispatching problem; Triangulation; Tree structured method; Make to order; Environment knowledge; make-to-order (MTO); Competitiveness; Software package; diagnosis; Tree structure; Integrated management; Standards; production planning and control (PPC); Scientific literature; Production management; Production planning; delivery reliability; Problem solving; Firm management; Reliability; Resource management; Fault diagnostic; Quantitative analysis; Firm
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2011.643251

Improving performance in terms of delivery reliability is increasingly important for make-to-order (MTO) companies. Detecting improvement opportunities requires a structured diagnosis of the current performance. General problem-solving literature provides structures for diagnosis processes in general, but - depending on the performance problem to be diagnosed - a theoretical framework based on domain-specific scientific knowledge is required. This paper presents a framework for diagnosing delivery reliability performance in MTO companies. The framework consists of a diagnosis tree that structures the diagnosis process, enabling one to navigate from the achieved performance to the underlying causes related to production planning and control (PPC). A theoretical foundation, enabling the possible causes of unreliable deliveries to be structured, is based on recent scientific developments in PPC literature. Three case studies exemplify the use of the framework. The developed framework shows its particular strengths in (1) selecting the right problem areas, (2) providing the right diagnosis instruments, and (3) detecting causes related to PPC decisions. It also supports diagnosis from quantitative data available in standard ERP software packages and enables diagnosis triangulation using qualitative data from the underlying decision processes.