Industrial Engineering

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IJPPM 60,3

Industrial engineering priorities for improved demand chain performance D.R. Towill
Logistics Systems Dynamics Group, Cardiff University, Cardiff, UK, and

Received October 2009 Revised May 2010 Revised July 2010 Accepted August 2010

P. Childerhouse
Department of Management Systems, Waikato University, Hamilton, New Zealand Abstract
Purpose – The purpose of this paper is to exploit site-based research evidence from a range of value streams so as to prioritise the industrial engineering (IE) foci necessary to move towards the goal of a seamless demand chain. Design/methodology/approach – A sample of 40 real-world value streams have been audited to produce codified scores assessing the usage of 12 Simplicity Rules leading to streamlined material flow. The rules are partitioned into “local” (Internal) and “holistic” (External) actions. Exploratory statistics are used to explore the different uptake of these two groups. Research limitations/implications – The sample is neither random nor fully representative of all supply chain scenarios. This paper confirms, via site based research, the validity of first actioning the improvements necessary to enable “our process” to deliver efficiently and effectively, in response to internal demands. Practical implications – Expending effort into effective engineering of “our process(es)” as first priority offers a double advantage compared to starting at the systems level. Such a strategy generates both competence and confidence. Once this level is achieved the business is in a good position for upgrading the external interfaces. Originality/value – This paper shows that modern industrial engineering concepts transpose into two groups of Simplicity Rules, which can move a business forward towards the seamless demand chain goal. The rich field data confirm a logical industrial engineering sequence when enhancing demand chain performance. Keywords Supply and demand, Industrial engineering, Production processes, Best practice, Performance management Paper type Research paper

International Journal of Productivity and Performance Management Vol. 60 No. 3, 2011 pp. 202-221 q Emerald Group Publishing Limited 1741-0401 DOI 10.1108/17410401111111961

1. Introduction It may be argued that a realisation that some level of integration would improve demand chain performance dates back at least as far as Forrester (1958). On the basis of simulation experiments, he advanced specific recommendations for integration thereby reducing demand distortion (now popularly known as bullwhip, Lee et al. (1997). Subsequently, these recommendations were further investigated and ranked in The authors would like to thank the original Cardiff LSDG team that helped in developing the QSAM and the 25 plus multinational researchers who have since participated in the various Quick Scans over the past decade.

“value” of reduction in projected on-costs by Wikner et al. (1991). These Forrester ideas are; echelon elimination (because this action directly removes both distortion and delay), time compression (to make control more effective), information transparency throughout the chain (which also removes both distortion and delay) and robust decision support systems – DSS (in order to optimise order placement throughout the chain). Forrester’s work (and that of Parnaby, 1979, 1988, 1991, and 1995 which particularly emphasise interface management) have greatly influenced our approach to demand chain design (Towill, 1997), and subsequent value stream auditing (Naim et al., 2002a). However, our site-based research has also made much use of the supply chain integration model of Stevens (1989), shown in Figure 1. The latter concept has found much use elsewhere for example in Bhattacharya et al. (1995), Bagchi and Skoejtt-Larson (2003), Barratt (2004), van der Vaart and van Donk (2004), Power (2005)...
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