A comparative study of manufacturing and service sector supply chain integration via the uncertainty circle model

• Pages: 188-205
• Published date: 09 May 2016
• Date: 09 May 2016
• DOI: https://doi.org/10.1108/IJLM-03-2014-0047
• Author: James Aitken,Paul Childerhouse,Eric Deakins,Denis Towill
• Subject Matter: Management science & operations,Logistics

A comparative study of

manufacturing and service sector

supply chain integration via the

uncertainty circle model

James Aitken

University of Surrey, Guildford, UK

Paul Childerhouse

School of Engineering and Advanced Technology, Massey University,

Palmerston North, New Zealand

Eric Deakins

Department of Management Systems,

Waikato University, Hamilton, New Zealand, and

Denis Towill

Business School LSDG, Cardiff University, Cardiff, UK

Abstract

Purpose –The purpose of this paper is to investigate the differences and similarities between the

manufacturing and services sectors in order to develop a methodology that can provide

the opportunity for the transfer of best practice between the two sectors. This paper aims to

describe an audit methodology capable of yielding objective comparisons of supply chain integration

performance that can assist practitioners and academics to transfer learned solutions.

Design/methodology/approach –A robust, site-based, multi-method supply chain diagnostic for

detecting manufacturing supply chain system uncertainty was amended for the service sector in order to

yield objective comparisons of the (normalised) supply chain integration performances of 119 organisations.

Findings –The research confirms the value of using a lens enabled by the uncertainty circle model

(UCM) for generating meaningful comparative supply chain performances. The research found that

services do not always exhibit unique attributes which effectively bar manufacturing-based supply

chain best practice from being adopted within the service sector.

Originality/value –Combining the UCM and Quick Scan Audit Methodology approach has the

potential to assist the spread of proven good practice across both sectors. The framework provides

realistic andrepeatable performance vectors,capable of aligning estimatesof value stream health status

even when comparing supplychains with differing objectives, configurations, and performance goals.

Keywords Supply chain integration, Service, Manufacturing, Uncertainty circle

Paper type Research paper

Introduction

Some researchers describe service supply chains as being distinct from manufacturing

supply chains (Sampson and Spring, 2012) due to both structural and management

approaches that arise from the role of the customer in the supply chain. The underlying

difference between manufacturing, with its product-centric focus, and services with its

customer-derived activity focus, is the degree of customer involvement in the value

creation process (Maull et al., 2012). The duality of customers being providers of inputs,

as well as consumersof outputs, differentiates servicesupply chains from manufacturing

and is an aspect viewed as being most critical and challenging to traditional

The International Journal of

Logistics Management

Vol. 27 No. 1, 2016

pp. 188-205

©Emerald Group Publishing Limited

0957-4093

DOI 10.1108/IJLM-03-2014-0047

Received 18 March 2014

Revised 20 August 2014

18 November 2014

Accepted 20 March 2015

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/0957-4093.htm

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IJLM

27,1

supply chain thinking (Sampson, 2000). Consequently, some manufacturing-based

supply chain models that are applied to services have required adaptation to reflect the

indispensable contribution of the customer in supply chain service provision.

Ellram et al. (2007), in investigating the application of manufacturing supply chain

models to services, highlight several contradictory aspects of the models and concluded

their research with a call for studies that recognise how service supply chains are

challenging to quantify and measure.

Researching uncertainty in service supply chains is a step towards answering this

call, since a basic requirement of supply chains is to ensure stable operation against a

background of changing constraints and uncertainty (Parnaby and Towill, 2009). For

at least two decades, researchers have investigated the sources of uncertainty and the

management approaches used by organisations as they endeavour to manage the

ambiguity that exists internally and externally to their supply chains (Davis, 1993 ).

Here, the primary focus has been on manufacturing supply chains and their

uncertainty, through the use of such frameworks as the uncertainty circle model (UCM)

and on management approaches for reducing or coping with uncertainty via lean and

agility approaches (Simangunsong et al., 2012).

This paper moves the discussion forward by investigating uncertainty in service

supply chains through the application of the UCM. It begins by presenting literature

that contrasts manufacturing and service supply chains. The UCM is then expla ined

and a review of uncertainties across the two sectors given. Next, the Quick Scan Audit

Methodology (QSAM) is explained and a cross-case analysis provided. Finally the

discussion, contribution to knowledge and conclusions are presented.

A comparison of manufacturing and service supply chains

The possibility of adapting and transferring supply chain management (SCM) best

practice from manufacturing to the service sector has only recently begun to interest

academics, due to the increasing importance of services in mature economies (Goldhar

and Berg, 2010; Sengupta et al., 2006). For example, in the USA the service organisation

contribution to GDP recently exceeded 75 per cent (Samuel et al., 2010). Researchers

claim that five unique attributes of services “have implications”for those who seek to

transfer manufacturing-based SCM best practice frameworks into the service sector:

intangibility, perishability, heterogeneity, inseparability, and customer participation

(Akkermans and Vos, 2003; Sampson, 2000; Vargo and Lusch, 2004).

While the service attribute most commonly cited by academics is intangibility

(Sampson and Froehle, 2006), its legitimacy and uniqueness as a concept for services

has been challenged (Vargo and Lusch, 2004). The Oxford Dictionary (2012) defines

intangible as “unable to be touched; not having physical presence”, yet many service

processes can be viewed as tangible in terms of their outputs. For example, repair of

a crashed car is a service provided to owners that results in rectification of the

vehicle plus the tangible return of the car to its pre-crash status (Aitken and Murray,

2010). Similarly, original production of the vehicle in a car plant would be classed as

a tangible manufacturing output; however delivering the car to the customer

requires that intangible transport services be used (Bozarth and Handfield, 2006).

Thus, tangibility and intangibility coexist in manufacturing and service supply

chain settings.

Manufacturing supply chai ns utilise inventory to buffer against lead -time

variability and demand uncertainty (Spearman and Hopp, 1998). However, services

are deemed to be perishable due to their time-sensitive nature since in general they are

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Service sector

supply chain

integration