Supply chain management skills to sense and seize opportunities
Peter Tatham
Griffith Business School, Griffith University, Gold Coast, Australia
Yong Wu
Griffith Business School, Griffith University, Gold Coast, Australia
Gyöngyi Kovács
The HUMLOG Institute, Hanken School of Economics, Helsinki, Finland
Tim Butcher
Griffith Business School, Griffith University, Nathan, Australia
Corresponding Author: Peter Tatham: [email protected], Phone: +61 (0)7 555 28490
This is a so-called personal version (author's manuscript as accepted for publishing after the review
process but prior to final layout and copyediting) of the article: Tatham, P., Wu, Y., Kovac, G. & Butcher, T.
(2017) International Journal of Logistics Management 28(2), 266-356. doi: 10.1108/IJLM-04-2014-0066
This version is stored in the Institutional Repository of the Hanken School of Economics,
Dhanken. Readers are asked to use the official publication in references.
Abstract
Purpose
The aim of this study is to investigate the supply chain management skills that support the sensing
and seizing of opportunities in a changing business environment.
Design/methodology/approach
Based on previous literature on the T-shaped model of supply chain management skills, data was
collected through a mail survey among Australian business executives. The resultant skill sets are
grouped along factors that support the sensing vs. seizing of opportunities.
Findings
Interestingly from an SCM perspective, functional logistics-related skills are important to
maintain competitiveness but are not the ones contributing to a firm’s ability to sense
opportunities and threats, and to seize opportunities in a changing business environment. We
therefore support the notion that supply chain managers should be managers first. Factual SCM
knowledge is the solid basis, but otherwise only an entry requirement in this field.
Research limitations/implications
Problem-solving skills, along with forecasting and customer/supplier relationship management,
stand out as important components that support the ability of supply chain managers to sense and
shape opportunities and threats in a turbulent business environment. This focus would tend to
suggest the importance of supply chain integration and collaboration as management approaches.
Other SCM-skills from warehousing and inventory management to transportation and purchasing
are more prevalent for maintaining competitiveness.
Practical implications
The results of the survey, and the consequential analysis, indicate that the content of tertiary level
educational programmes should be significantly reviewed to deliver two distinct (but partially
overlapping) streams that focus on the generalist and functionalist managers who must work
together in the management of increasing global and complex supply chains.
Social implications
Functional skills often form the basis of training and education programmes for supply chain
managers. Whilst these form the solid foundation for their jobs, they are entry requirements at
best. In a changing business environment, other skills are needed for success. Given that
turbulence is becoming the norm rather than the exception, this finding necessitates rethinking in
training and education programmes, as well as in the recruitment of supply chain managers.
Originality/value
Testing the T-shaped model of supply chain management skills from a dynamic capabilities
perspective, the results of our factor analysis lead to a regrouping of skill sets in terms of sensing
and seizing opportunities in a turbulent business environment.
Keywords: Supply chain management skills, supply chain agility, dynamic capabilities, business
turbulence, business volatility, sense and respond
Article Classification: Research paper
Supply chain management skills to sense and seize opportunities
1.
Introduction
Although the management of supply chains has reached a high degree of sophistication in many
contexts and settings, there is an increasing perception that the basic structures may need revisiting in light of emerging changes in the global business environment. In particular, it has been
powerfully argued by academics and practitioners alike, that commerce and industry are faced
with an increasing and persisting level of business turbulence (Singh, 2009; Christopher and
Holweg, 2011; Shell, 2011; Doheny et al., 2012). In parallel, it is argued that whilst the skills
required of supply chains managers have received considerable attention since the field began to
emerge in the 1990s (e.g., Murphy and Poist, 1991 to Keller and Özment, 2009; Rossetti and
Dooley, 2010; Ellinger et al., 2011; Thomas et al., 2012), these also need to be re-visited in light
of the suggested increase in business turbulence.
Grounded in an Australian business environment and using the lens of the dynamic capabilities
model, this paper draws on the supply chain management (SCM) skills literature in order to
investigate the skills required for managing a supply chain in such turbulent times. The resultant
research question that the paper addresses is as follows:
RQ: Which (groups of) skills support supply chain managers in sensing opportunities
and seizing them vs. maintaining the competitiveness of their organisation?
Sensing and seizing opportunities is particularly important in turbulent times, and in a turbulent
business environment. To date, however, this perspective has not featured in the supply chain
skills literature which has traditionally focused on grouping skills in light of the “T-shaped”
model (Leonard-Barton, 1995) which distinguishes between functional supply chain (the vertical
arm of the “T”) versus overarching general management skills (the horizontal arm) (Mangan and
Christopher, 2005). However, taking this model as its basis, our study aims to further develop this
approach with a focus on the areas of emphasis that are relevant in supply chain management in
turbulent times. In this way, we will address a gap in the current supply chain skills literature
which has not yet specifically considered the skills required in this context.
It should be noted that, as will be demonstrated in the paper, the research was conducted during a
period of considerable business turbulence and, further, that this level of turbulence is continuing
and, to an extent, increasing. Thus, we were not able to conduct a comparison between the
perceived skills required in non-turbulent times vs. those required in turbulent times – rather, we
have identified those skills that are perceived to be important in the latter context, noting that this
appears, at least for the time being, to be ‘state normal’. It is accepted that if/when the business
world becomes less turbulent, it may well be that a similar skill set is also identified as being
important in such a benign business environment. For the time being, however, both recruiters
and educators need to be aware of the skills that are perceived to be important by business
executives and adjust their operations accordingly.
The next section of the paper will begin with a brief discussion of the SCM field and, in
particular, its breadth and the managerial implications. This will be followed by a focused review
of supply chain skills literature in general, and in relation to turbulence. The research is framed
by the dynamic capabilities model (DCM) (e.g., Teece and Pisano, 1994; Teece et al., 1997;
Teece, 2007), not least due to its emphasis on dynamic and, indeed, turbulent environments, and
the ways in which companies not only respond to these, but can organise their resources in ways
that lead to sustainable competitive advantage (Maskell, 2001).
In order to meet the aim of the paper, it is clearly important to establish the volatility of the
Australian business environment. To achieve this, we further develop, and then apply,
Christopher and Holweg’s (2011) Supply Chain Volatility Index (SCVI) to the Australian context.
Next we present results from a survey among Australian business executives that indicates the
skills that are considered important in terms of SC performance. These are then linked to the
DCM framework by means of a dendrogram and the associated analysis. In the final section of
the paper we draw out a number of conclusions and areas for further research.
2.
The scope of supply chain management
According to Bechtel and Jayaram (1997), there were more than 50 definitions of Supply Chain
Management at the time their paper was published and, unsurprisingly, the position has worsened
over the last 35 years – not least in light of the growth in articles that relate to the SCM field
which totalled some 3,000 by the end of 2008 (Stock and Boyer, 2009). Furthermore, there has
been an historic lack of clarity between the scope of ‘logistics’ vis-à-vis that of SCM when
viewed from the perspective of academics (Larson and Halldórsson, 2004) and practitioners
(Larson et al., 2007).
Thus, in order to ground this research, we have adopted what we perceive to be the increasingly
dominant view which, on the one hand, recognises the overlap between SCM and other
disciplines such as operations management (Mangan et al., 2012) and, on the other, distinguishes
between SCM and logistics. Under this approach logistics management is increasingly being seen
as reflecting the planning, implementing and controlling of the transportation and storage of
goods and services (CSCMP, 2014), whereas SCM is positioned at a more strategic level. Thus,
Stock and Boyer (2009, p. 706) offer a comprehensive view of the various perspectives and the
associated ambit of SCM leading to what they put forward as a consensus definition in which
SCM is seen as being “…the management of a network of relationships within a firm and
between interdependent organizations and business units consisting of material suppliers,
purchasing, production facilities, logistics, marketing, and related systems that facilitate the
forward and reverse flow of materials, services, finances and information from the original
producer to the final customer with the benefits of adding value, maximizing profitability through
efficiencies and achieving customer satisfaction.”
This definition has been used to underpin this research, and it will be seen that it reflects the
management of three components. The first of these is that of the two-directional flow of
materials, finances, services and information. This, in turn, implies the management of networks
of relationships within the focal firm and between the focal firm and the remaining entities within
the chain (or network). The second component reflects the outcomes of such managerial activity
which include added value and/or improved profitability and/or customer satisfaction. The final
component recognises the breadth of the organisational areas that SCM has to engage with, from
material suppliers through to marketing.
As the focus of this research is on SCM skills, our further review has implemented this broad
definition in that it searched for related literature in mainstream SCM journals first, and then
snow-balled through key articles and their references to find other, similar articles in related
journals. It should be noted that the focus was on the skills of supply chain managers, and not on
operational employee skills (e.g., Pagell et al., 2000), nor on the discussion on deskilling in
general. Furthermore, rather than focusing on skill development and learning, the focus of our
study is on differences in skill requirements depending on the business environment of the firm,
and of an entire industry. Hence we see skills as essential parts of the dynamic capabilities of the
firm and its supply chain. This positioning requires a short review of the key elements of the
dynamic capabilities model in light of skills.
3.
Skills for SCM in turbulent environments
Business environments have changed dramatically in recent years to the point that ‘turbulence’ is
frequently referred as the new business normal. The research on the impact of such turbulence is,
however, not new. For example, Dawson studied the impacts of turbulence on retail industry in
Europe and proposed a number of strategies that firms could adopt to mitigate its effects
(Dawson, 1995 as cited in Kotzab et al., 2009; Dawson, 2001). However, as indicated by the
macro-analysis in Section 4, the current business environment is demonstrating an increasing
level of turbulence, not only in terms of its magnitude, but also in relation to its frequency of
occurrence. This, coupled with shorter product and technology lifecycles, more demanding
customers, and new ways of conducting business such as omni-channel retailing, creates
significant challenges for firms which at a strategic level are characterised by D’Aveni’s (1994)
concept of ‘hypercompetition’. In an attempt to address the increased rate of change, Fine
introduced the term ‘clockspeed’ to describe an industry’s evolutionary life cycle and argued that
the ultimate source of sustainable competitive advantage is a company’s ability to manage its
supply chain (Fine, 1998; 2000). In parallel, Lewin et al. (1998) used complexity theory to
examine the relationships within firms and between firms noting that globalisation and
outsourcing activities extend the management of supply chains far beyond the focal firm and,
hence, increase its complexity. Thus, against a background of increasing business environment
turbulence, more competitive markets, accelerating clockspeed, and more complex supply chains,
it is perceived that there is a compelling need to understand the skills needed by Supply Chain
managers as these challenges grow and expand.
Unsurprisingly, therefore, as the whole field of SCM has developed, so too have the many lines of
people-related research, with a number of key streams including those (a) tracking careers in
SCM (Dischinger et al., 2006; La Londe et al., 2010), and (b) developing curricula in this area
(Myers et al., 2004; Mangan and Christopher, 2005; Carter et al., 2006; Okongwu, 2007: Allen et
al., 2013). Another important area of skills research is the evaluation of differences in skill sets
required of supply chain managers vs. various subsets of the discipline (Murphy and Poist, 1993;
Gammelgaard and Larson, 2001; Gibson and Cook, 2001; Van Hoek et al., 2002; Rossetti and
Dooley, 2010; Kovács et al., 2012), in skills required for various job levels (Pagell et al., 2000;
Gabric and McFadden, 2001), and in respect of geographically different requirements (Mangan et
al., 2001; Sohal and D’Netto, 2004; Okongwu, 2007; Rahman et al., 2009; Sohal, 2013).
Unlike other resources, skills generally do not deplete or deteriorate, but rather improve over time
(Molloy et al., 2011), while they maintain the other important aspect of resources in that they are
heterogeneous and hard to replicate, if not inimitable (cf. Ramsay, 2011). The aspects of
heterogeneity and inimitability contribute to the strategic value of a resource (Azadegan et al.,
2008; Hunt and Davis, 2008). In this respect, therefore, the DCM pioneered by Teece and Pisano
(1994) was seen to have particular relevance as a theoretical baseline for the research. The DCM
is generally conceptualised as developing the Resource Based View (RBV) of a firm, but with a
particular focus on the mechanisms by which firms build competitive advantages in times of rapid
change. Teece et al. (1997, p. 515) suggest that “Winners in the global market place have been
firms that can demonstrate timely responsiveness and rapid and flexible product innovation
combined with the management capability to effectively coordinate and redeploy internal and
external competencies.” In order to achieve this, the DCM postulates that, in a turbulent business
environment, firms must (among other things) have the capacity and capability to (1) sense and
shape opportunities and threats; (2) seize these opportunities and (3) reconfigure the enterprise’s
assets as necessary to achieve the desired outcomes.
Skills contribute to the development of dynamic capabilities which, in turn, are important to a
firm’s competitiveness in a rapidly changing and hence, turbulent environment (Teece and
Pisano, 1994; Fawcett et al., 2011). “Logistics” has been described as such a dynamic capability
(Zhao et al., 2001; Autry et al., 2005; Esper et al., 2007), whilst “SCM” has been regarded a
relational capability (Grant, 2009), with the relational aspect capturing also the management of a
chain. The dynamism of these capabilities is obviously all the more important in turbulent
business environments or, as Eisenhardt and Martin (2000) put it, high-velocity markets.
Competitive advantage in such markets depends on the ability to sense and respond to turbulence
quickly and proficiently (Teece, 2000, 2007, 2010; Barreto, 2010), an ability for which specific
skills play an important role (Butcher et al., 2011).
From a DCM perspective, Grant (2009) sees skills as single-task-level capabilities which are then
aggregated into higher hierarchies; whilst Gammelgaard and Larson (2001) and Myers et al.
(2004) distinguish between skills, attributes, experience, competencies and knowledge on
different levels. Furthermore, whilst Grant (2009) consolidates skills into resource bundles,
Kovács et al. (2012) develop the idea of hierarchies of skills themselves. However, the more
common approach – which is the one we follow – is to merge these concepts together into a
number of skill sets. Thus, Dischinger et al. (2006) propose the sets of “functional skills” (i.e.
skills that relate to SCM functions), “technical (ICT) skills”, “leadership skills”, “global
management skills”, and “experience and credibility”; whereas Gibson and Cook (2001) offer
“general management skills”, “interpersonal capabilities”, “technical skills” and “specific [SCM]
capabilities”. Other researchers prefer three sets – for example, Murphy and Poist (1991, 2007)
refer to these as “logistics skills” which combine functional and technical skills; “business skills”
which relate to other business functions as well as to psychology and sociology; and
“management skills” that relate to planning and organising, and to personal attributes. Within
many, if not all, of these classifications there is a common theme of the need to ensure an
appropriate balance between business, technical and functional knowledge, and other “softer”
(Vereecke et al., 2008) skills.
The skill set approach has been developed further by a number of authors including, Gabric and
McFadden (2001), Van Hoek et al. (2002), Mangan and Christopher (2005), Vereecke et al.
(2008), and Kovács et al. (2012) all of whom argue for a “T-shaped” skills profile (see Appendix
A). This framework uses the analogy of the “T” to argue that practitioners need to have in-depth
functional skills (the vertical axis of the “T”) that are complemented by competences in a broader
range of, typically, “softer” skills (the horizontal axis). A similar approach has been found in
other fields including research and development (Iansiti, 1993), transport (EP, 2006), defence
engineering (Weiss, 2005), and IT (Harris, 2009), and this leads to a depth vs. breadth discussion
of skills that is reflected in the findings of Mangan and Christopher’s (2005, p.180) that “supply
chain managers” would regard themselves as “managers first and logisticians second”.
Separately, it is also argued by Butcher (2007) that a reason for the emphasis on general
management rather than functional skills may lie in the disparate nature of the SCM profession
which is fed by people whose initial work experiences have been in a very broad range of subdisciplines which include engineering, purchasing, transport, IT and warehousing to name but a
few. Thus, as such individuals ascend the management tree, they are likely to face the
requirement to make decisions that are well beyond their previous experience base. This
reinforces the need for the development of a broad range of business management, problem
solving and inter-personal skills – especially in view of the horizontal nature of SCM that
frequently is required to cut across vertical organisational silos (Christopher, 2011).
In light of the requirement for supply chains to be able to respond efficiently and effectively in an
increasingly turbulent environment, many authors (e.g., Christopher, 2011; Doheny et al., 2012)
argue that a more ‘agile’ approach should be adopted. Whilst there is a continuing debate over
the exact meaning of this concept (Gligor and Holcomb, 2012; Sweeney et al., 2015), a detailed
analysis of the concept is beyond the scope of this research. Rather, we have adopted the
approach of Sarkis (2001) who suggests that it reflects the ability to thrive in an environment of
continuous and often unanticipated change.
However, Butcher et al. (2011, p. 462) have considered the theoretical impact of a turbulent
business environment on the skills of SC managers and concluded that “there is no empirical link
between the SCM literature and agility theory”. One may, nevertheless, infer from the agility
concept that successful SC managers will demonstrate superior abilities in areas such as: decision
making, communication, people management, negotiation, leadership, change management,
customer and supplier relationship management. Importantly, all of these skills are present in
Mangan and Christopher’s (2005) skills model and this was, therefore, used as the framework
underpinning our study. It should also be noted that Mangan and Christopher see their 2005
research as merely a foundation to further investigation of the whole question of the development
of the supply chain manager of the future – and this paper is, in part, a response to their challenge.
Furthermore, as Christopher and Holweg (2011) note, turbulence is today the norm rather than the
exception and this aligns with the more recent view of Doheny et al. (2012, p. 2) who suggest that
the potential for catastrophic failure in a company’s supply chain has “... become more acute in
recent years as rising volatility, uncertainty, and business complexity have made reacting to – and
planning for – changing market conditions more difficult than ever.”
4.
Research Design
As the aim of this study is to investigate SCM skills in an Australian business environment, an
important first step was to ascertain whether the setting of the study could be accurately described
as turbulent. In earlier research Christopher and Holweg (2011) presented a Supply Chain
Volatility Index (SCVI), the development of which was a response to previously untested
assumptions that the globalisation of business, the demanding nature of customers, and market
uncertainty are increasing. Whilst these are all well-known assertions in SCM research (e.g.
Singh, 2009; Gattorna, 2010) the work of Christopher and Holweg (which was published in the
40th Anniversary Edition of the International Journal of Physical Distribution and Logistics
Management) is believed to be the first within the literature to demonstrate this empirically.
Christopher and Holweg’s (2011) SCVI displays both the absolute changes in a number of key
parameters as well as their rate of change. By plotting the coefficient of variance (CoV) of a
number of important economic indicators, they were able to demonstrate that the degree of
turbulence being experienced has expanded significantly since 2008. Thus, these authors argued
that the business environment has moved from a period of relative tranquillity since the early
1970s into one of considerable, and potentially lasting, fluctuations. This analysis resonates with
Shell’s contemporaneous development of long-term scenarios that envisage “an era of
revolutionary transitions and considerable turbulence” (Shell, 2008, p.10) and with the continuing
macroeconomic volatility noted in Shell (2011).
As shown in Table 1, the original SCVI was based on four groups of data relating to (a) currency
fluctuations, (b) raw materials, (c) stock markets and (d) shipping costs. We broadened this
approach to offer a more global perspective which included additional exchange rates and stock
market indicators which were designed to reflect the reality that supply chains are increasingly
global and, hence, it is the turbulence in the global business environment that impacts on SCM.
Specifically, we selected the exchange rates between the United States and its top five trade
partners as sources for financial data as these represent a more global perspective; we added iron
ore price index as an indicator for raw materials, not only because iron ore is a commonly used
raw material, but also because iron ore is one of Australia’s major exports; we also
‘internationalised’ the selection of stock market indices; and lastly we increased the number of oil
price sources from one to three.
Table 1 shows the resultant selection of sources, although it should be noted in particular that the
Baltic Dry Index (which was a component of Christopher and Holweg’s original research) has
been removed from revised calculations as it has been criticised as an economic indicator
(Simons, 2011). It has been replaced with the S&P 500 Air Freight & Couriers Price Index as a
means of capturing volatility on international transport.
Table 1. SCVI Data Sources
Type
Christopher & Holweg (2011, p.67) study*
Parameter
Financial
EUR/GBP (WMR&DS) exchange rate
USD/GBP (WMR&DS) exchange rate
UK clearing banks base rate – middle rate
Raw
materials
Gold Bullion LBM USD/troy ounce
LME-Copper, grade A three month GBP/MT
Stock
market
VIX – Chicago Board Options Exchange
Market Volatility Index
Oil Prices
Crude Oil-Brent FOM USD/BBL
Freight
Baltic Dry Index
Global SCVI (The Authors)**
Parameter
USD/CAD exchange rate
USD/EURO exchange rate
USD/CNY exchange rate
USD/JPY exchange rate
USD/MEX exchange rate
Gold Price
Copper Price
Iron Ore Price
NYSE
Tokyo SE
London SE
Frankfurt SE
Brent
TAPIS
OPEC
S&P 500 Air Freight & Couriers
Price Index
*All data sourced from Thomson Reuters Datastream over the period 1970-2010 except for the Brent Crude Oil price which was
from the Energy Information Administration, and VIX which was from the Chicago Board Options Exchange.
**All data sourced from Thomson Reuters Datastream for the period 1990-2015.
It is fully accepted that the introduction of additional parameters does not necessarily broaden the
scope of the index as some of the components may be interdependent and thus, potentially, result
in double-counting. We therefore conducted an exploratory factor analysis in order to find the
‘underlying’ factors and this use of exploratory factor analysis was supported by the Kaiser-
Meyer-Olkin measure of sampling adequacy (.840) and Bartlett’s test of sphericity. Using
Principle Component Analysis with the default settings in SPSS 22.0, this showed that four
factors could be extracted which explain about 91.9% of the overall variance. We subsequently
stored these four factors for further data analysis. By doing so, we were able to focus on the four
factors extracted instead of the original 16 data sources. As expected, not only do these factors
change quite dramatically over the years, but also their trends do not follow each other.
Next we determined how quickly the data changed. To achieve that, we first calculated the
overall data change range (R) for each factor using the difference of the maximum and minimum
values in the particular factor, e.g., for factor one (F1), R1 = max (F1) – min (F1). Subsequently,
we measured the relative change (C) for any two successive data points (in this case, the values
for two consecutive weekdays) in percentage terms over the factor range R. For instance,
C1d  abs( F1d  F1d 1 ) / R1
(1)
d
measured the relative change C1 of F1 at day d over the previous weekday d – 1. Once the
relative change for each factor on each day was calculated, we averaged the minimum, maximum
and average change for every day over 30 data points (consecutive weekdays) to smooth any
potential abrupt changes over a short time period. The results are plotted in Figure 1, along with
their associated trend lines from 01 January 1990 to 22 September 2015.
Figure 1: Turbulence in the business environment – the global SCVI
The important conclusion from this analysis is that, unsurprisingly, there has been a significant
spike in volatility during the period 2007-2009 (i.e. during the global financial crisis, GFC), but
even more importantly, the trend lines show that turbulence has been steadily increasing over the
years even though the GFC-caused peak has receded. In short, as observed by Rossi (2011, p.
300) in a major economic analysis: “...the key theme of this review is that volatility is the new
normal, and we must become accustomed to this.”
Our global SCVI extends the Christopher and Holweg (2011) dataset which ended in early 2010
in terms of both time and in the scope of parameters used. Our survey was conducted early 2011
in Australia, which was just after the peak of GFC, but not only was the discussion around the
GFC and its implications for business (and, hence, SCM) still highly topical, the overall
increasing trend of global turbulence has continued to underline the importance of the subject.
The use of a global SCVI is, therefore, entirely applicable to Australia since the country is a
global trading nation – indeed, a recent Strategic Review of the Australian Treasury has
emphasised the continuing international economic volatility facing the country (Australian
Government, 2011).
Furthermore, as will be seen from Figure 1, there has been a clear growth in the level of volatility
over the last 25 years. Thus, this research was, in part, designed to capture the impact of this
development.
5.
Survey design and sample
Given, therefore, this demonstration of continued and continuing business turbulence, we next
considered the question of the skills that are appropriate for supply chain managers in such an
environment. In the same way as for the T-shaped model in engineering, existing skills research
also lists numerous general vs. domain-specific skills that ‘good’ logisticians, as distinct from
supply chain managers, ought to have. Whilst there is no consensus in literature on either the lists
of skills or on their grouping into skill sets, there is a clear thread that functional or technical
‘logistics’ skills, though necessary, need in the case of supply chain managers to be
complemented with other, more general, softer skills (Murphy and Poist, 1991; Gibson and Cook,
2001; Van Hoek et al., 2002; Mangan and Christopher, 2005; Vereecke et al., 2008). We
therefore used a slightly modified version of the list of skills in the Mangan and Christopher
(2005) model that reflected the results of earlier research by Kovács and Tatham (2010). Such a
survey focuses on employees as the unit of analysis and, therefore, in particular sees such skills as
a core element of the resources and capabilities of the firm.
The sample of our survey consisted of Australian practitioners. As pointed out above, the timing
for administering the survey fits with the GFC, and also with Australia’s status as a global trading
nation, hence we expected turbulence to be of importance to these practitioners. The online
survey was administered through two key industry bodies, the Chartered Institute and Logistics
and Transport (Australia) (CILTA) and the Logistics Association of Australia (LAA). The
questions specified that the importance of the skills (on a 7-point Likert scale) should be
considered in terms of supply chain performance. A total of 216 valid responses were received,
but given our practitioner focus we discounted 6 from students and 12 from academics. Of the
remainder, 109 submissions had followed the link published by the LAA, and 89 emanated from
the membership of CILTA, with the respondents’ demographics shown in Table 2. The resulting
response rates of, in each case, around 8% of the organisation’s membership are low, but not
dissimilar to the typical response rate of 10% in electronic surveys as reported by Larson (2005).
Table 2. Survey demographics
Positions
LAA
N
CILTA
Years of
experience
LAA
N
CILTA
Manager of a Manager
18
16
4–6
5
11
Manager
66
49
7–10
21
10
Other
25
24
11–15
19
14
89
16–25
> 25
Not indicated
Sub-total
39
17
8
109
26
23
5
89
Sub-total
Total
109
198
198
Education level
Professional or
vocational
Bachelor
Graduate
Certificate
Master
Doctor
Other
Sub-total
LAA
N
CILTA
17
15
29
17
31
26
26
0
6
109
19
3
9
89
198
The effects of non-response bias were further estimated for both cohorts using the methodology
of Armstrong and Overton (1977). For each cohort, we compared the mean score for each skill
between the first and the fourth quartiles of responses, based on the time the surveys were
completed. Among the 32 skills, only two skills were ranked statistically differently (p = 0.05)
between the first quartile and the fourth quartile of responses for both cohorts, respectively. The
impact (if any) of the non-response bias was, based on this estimation, deemed to be acceptable.
The above results were also compared with a separate sample from a similar survey that was
administered to the membership of the Chartered Institute of Purchasing and Supply (Australia).
Unfortunately, only 36 responses were received from this survey and the sample size was,
therefore, deemed to be too small for formal analysis, but those results that were received fully
supported the fundamental thrust of the results as discussed below.
6.
Findings from the analysis
The first finding of the research is that the results from the two cohorts (CILTA and LAA) are,
notwithstanding the slightly different aims/objectives of these two organisations (see Appendix
B), remarkably similar with a Spearman’s rank correlation coefficient of ρ = 0.95. Agreements are
highest for top (9 of 10) and bottom (8) skills, with some variance in the 11th-24th ranks.
Generally, the LAA respondents placed slightly greater emphasis on the functional skills which,
arguably, reflects the organisation’s deeper practitioner roots. Nonetheless, the overall high
agreement, together with the Spearman’s rank correlation coefficient of 0.95, led to a subsequent
joint analysis of the two cohorts.
Considering the survey results (Table 3 and Figures 2 and 3), the first and most obvious
observation is the extent of the overall importance of the horizontal element of the T-shaped
model (i.e. the general management (GMS), problem solving (PSS) and interpersonal (IPS)
skills). Thus, for example, the highest scoring functional skill (FS) came in at number 13, whilst
4 out of the bottom 5 skills/attributes fell into this category. This outcome aligns with the
findings of Sohal’s (2013) survey where, also in an Australian context, the top three competencies
identified in his survey of supply chain professionals were an ‘Ability to work effectively with
individuals and groups/teams cross culturally, intra and interorganisationally’; ‘Ability to manage
relationships in diverse contexts – cross culturally, intra and interorganisationally’; and ‘Ability to
manage risks in [a] supply chain and associated issues’ (p. 436).
On the other hand, two areas were found to be surprising. The first is the low importance placed
on marketing (ranked last) whilst, at the same time, there is a high emphasis on customer
relationship management (CRM, ranked 9). On the one hand, the respondents may have been
reflecting a clear delineation between the fields of SCM and of marketing but, on the other hand,
it may be that CRM has become the process through which demand information is integrated into
SCM. The second unanticipated result is the relatively low level of importance placed on reverse
logistics. This is surprising given, for example, increases in internet shopping as well as broad
consumer pressure to be ‘greener’. Indeed, reverse logistics is generally perceived to be an area
in which successful management of the SC as a whole has the potential to achieve significant cost
savings (Rogers and Tibben-Lembke, 2001). Yet in this survey the area is not seen as being
particularly important and whilst this may simply reflect an Australian perspective, it is consistent
with Kovács and Tatham’s (2010) findings.
Table 3. Combined LAA/CILTA Skill Ranks (Source: The Authors)
LAA + CILTA
Rank
(N=198)
1
2
3
4
5=
5=
7
8
9=
9=
11
12
13=
13=
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Skill/Attribute
Leadership
Problem Solving
Supplier Relationship Management (SRM)
Negotiation
Personnel Management
Listening
Problem Identification
Problem Analysis
Customer Relationship Management (CRM)
Information Sharing
Oral Communication
Strategic Management
Forecasting
Inventory Management
Written Communication
Change Management
Information Gathering
Risk Management
Logistic Information Systems
Stress Management
Transport Management
Purchasing
Project Management
Warehousing
Information Technology (IT)
Financial Accounting
Meeting Facilitation
Reverse Logistics
Import/Export
Legal Specification
Port/Airport Management
Marketing
Category
IPS
PSS
GMS
IPS
IPS
IPS
PSS
PSS
GMS
PSS
IPS
GMS
FS
FS
GMS
IPS
PSS
GMS
FS
IPS
FS
FS
GMS
FS
GMS
GMS
IPS
FS
FS
FS
FS
GMS
LAA + CILTA
Mean Score
(N=198)
6.59
6.40
6.29
6.24
6.21
6.21
6.20
6.18
6.17
6.17
6.08
6.05
6.00
6.00
5.91
5.90
5.84
5.71
5.70
5.68
5.67
5.62
5.61
5.59
5.42
5.34
5.24
4.95
4.94
4.78
4.34
4.11
We conducted a number of group split analyses to evaluate the robustness of the study. A group
split in relation to educational levels did not result in any significant differences. Whilst at first
sight there is a slightly higher emphasis on general management skills and lower emphasis on
interpersonal skills that aligns with an increase in the respondent’s educational level, t-tests could
not support the significance of these shifts. The group split in terms of experience is also robust,
the only significant difference being that of less experienced respondents placing a slightly higher
emphasis on functional logistics skills. The same difference in emphasis based on experience is
also to be seen in the Allen et al. (2013) study.
In summary, functional skills can be seen as scoring lower when paired with increased education
as well as with increased experience, and it is suggested that this relates to the observation of
Butcher (2007) that SC managers may enter the profession with some other than logistics/SCM
background, impacting on their perception of the importance of functional skills. Overall, the
survey confirms the stability of Mangan and Christopher’s (2005) T-shaped model in both a nonEuropean context and also one that reflects the continuing growth of business turbulence.
7.
The dynamic capability of managing a supply chain in turbulence
More than just noting the ranks of individual skills and skill sets, it is important to understand
how they relate to dynamic capabilities and, hence, contribute to a firm’s success in a turbulent
business environment. Skills can be seen as single-task capabilities (Grant, 2009) which
contribute in their joint resource configuration to higher-level dynamic capabilities, and it is
highly relevant, therefore, to evaluate how they are synergised and transformed to dynamic
capabilities – with an emphasis on them being dynamic so that they are able to contribute to
competitiveness in a turbulent environment (cf. Fawcett et al., 2011).
Prior research has, indeed, linked skills to various capabilities although this is generally from the
perspective that some skills have been singled out as a capability – for example a purchasing
capability (Ramsay, 2001; Hunt and Davis, 2008), logistics information systems as a capability
(Autrey et al., 2005; Lai et al., 2008), or logistics as a capability (Zhao et al., 2001; Autry et al.,
2005; Esper et al., 2007). Logistics capability is also sometimes taken as a starting point and then
disintegrated into various elements including skills (e.g. Olavarrieta and Ellinger, 1997; Zhao et
al., 2001; Esper et al., 2007; Paulraj, 2011), although there is no consensus on the grouping of
skills into particular capabilities.
With this in mind, we plotted boxplots for each of the 32 skills and ranked them in decreasing
order according of their respective mean scores, with the result plotted in Figures 2 and 3. Given
that (a) there is a clear inflexion point at the mean score of 5.5 for the last 8 variables, and (b) the
medians of these variables are less than or equal to 5, we discounted these last 8 variables in the
subsequent analysis.
Figure 2: Ranking the 32 skills in decreasing Likert mean scores
Figure 3: Ranking the 32 skills (with boxplots) in decreasing Likert mean scores (solid dots)
To better understand how these 24 skills contribute to SCM in a turbulent business environment,
we grouped these skills using the ‘ClustOfVar’ package in R and the resultant cluster dendrogram
is depicted in Figure 4. The ‘ClustOfVar’ package is designed to be effective in grouping
variables that are strongly related to each other and is, therefore, an ideal candidate for dimension
reduction and variable selection (Chavent et al., 2012). Specifically, the function ‘hclustvar’ from
the package - which iteratively builds a set of nested partitions of variables (Chavent et al., 2012)
- was used to produce Figure 4.
Figure 4: Cluster dendrogram of the 24 skills from the ‘ClustOfVar’ package in R
Whilst this analysis did not fully position the 24 skills into the four groups within the “T-shaped”
model (general management skill (GMS); problem-solving skills (PSS); interpersonal skills (IPS);
functional logistic skills (FS)), the skills in each group are generally aligned to the same cluster.
That said, some skills are clustered across more than one group. For example, negotiation (IPS) is
grouped into the same cluster as forecasting (FS), LIS (FS) and purchasing (FS). This clearly
indicates that, while negotiation is classified as an interpersonal skill, it can also be treated as a
purchasing-related functional skill due to its paramount importance in procurement. A similar
trend can be observed for CRM and SRM.
Nevertheless, based on the aggregation levels from the dendrogram, three clusters of variables
were suggested and these were extracted using the ‘cutreevar’ function in the ‘ClustOfVar’
package. As will be seen from Table 4 below, whilst the alignment is not absolute, there would
appear to be a reasonable degree of linkage to the DCM through Teece’s sense and respond model
where he argues that dynamic capabilities can be: “…disaggregated into the capacity
(1)
to sense and shape opportunities and threats,
(2)
to seize opportunities, and
(3)
to maintain competitiveness through enhancing, combining, protecting, and,
where necessary, reconfiguring the business enterprise’s intangible and
tangible assets.” (Teece, 2007, p. 1319)
Table 4 shows the variables (with their category and mean score extracted from Table 3) mapped
to each cluster, the mean scores within the clusters, and cluster attributions to the sense and
respond model. Specifically, it can be seen that:

four (out of five) problem-solving skills can be seen as supporting the capability to
sense and shape opportunities and threats

the majority of the general management skills and almost all of the inter-personal
skills – which are vital for the achievement and maintenance of robust
communication and operational execution – are found to contribute to the
capability to seize opportunities;

the remaining variables, which are mostly functional skills, support the capability
to maintain competitiveness.
Table 4. Breakdown of the cluster analysis results
Skill/Attribute
Information gathering
Problem identification
Problem analysis
Problem solving
Project management
Change management
Risk management
Strategic management
Information sharing
Personnel management
Listening
Oral communication
Written
communication
Stress management
Leadership
CRM
SRM
Forecasting
Category Mean Score
Cluster
Mean
PSS
PSS
PSS
PSS
GMS
IPS
GMS
GMS
PSS
IPS
IPS
IPS
5.84
6.20
6.16
6.18
6.40
5.61
5.90
5.71
6.05
6.17
6.21
6.01
6.21
6.08
GMS
IPS
IPS
GMS
GMS
FS
5.91
5.68
6.59
6.17
6.29 5.92
6.00
DCM Mapping
to sense and shape
opportunities and threats
to seize opportunities
to maintain competitiveness
through enhancing,
combining, protecting, and,
Warehousing
Inventory management
Transport management
Purchasing
LIS
Negotiation
FS
FS
FS
FS
FS
IPS
5.59
6.00
5.67
5.62
5.70
6.24
where necessary,
reconfiguring the business
enterprise’s intangible and
tangible assets
Whilst it is fully acknowledged that this linkage to the DCM is exploratory, it will be noted that
the cluster analysis grouped functional skills such as warehousing, inventory management,
transportation management, purchasing and LIS together and, in doing so, largely supports the
functional vs. general management divide of the T-shaped model and of SCM skills models
overall. It should also be recognised that the grouping of the first cluster relates well to the
problem-solving-related hierarchy of skills as noted in Kovács et al. (2012).
On the other hand, when the categorisation in Table 3 was developed by the authors from the
existing literature, supplier relationship management (SRM), customer relationship management
(CRM) were seen to be general management skills, and negotiation an inter-personal skill – yet
they appeared in the functional cluster. It is perceived that, compared with other skills listed in
the other two clusters, these skills are more ‘intimate’ or closely related to functional skills and
this is, perhaps, an indication that these are key to ensuring the functionality of supply chains. It
should be noted that these three skills received higher scores than the rest skills in this cluster and
this aligns well with Mangan and Christopher’s (2005) model.
The factor groupings in the sense and respond model illustrate a number of important points.
First of all, skills in the group of “sense and shape opportunities and threats” have been much
emphasised by survey respondents, i.e., with a cluster mean score of 6.16 – which is to be
expected during turbulence. In other words, these skills gain in emphasis in a turbulent business
environment. Similarly, skills that help seizing opportunities are highly emphasised, with a
cluster mean score of 6.01. This may relate to the fact that the survey was conducted just after the
GFC and at a time when managers needed to implement the actions they had identified. The third
group of skills that is required to maintain competitiveness was the least emphasised but, again,
this corresponds well with the timing of the survey. In essence, the survey has captured times of
turbulence rather well, but what is more interesting, it supports Teece’s (2007) model and thus,
links SCM skills to DCM, and to agility overall.
8.
Discussion, Conclusions and Areas of Further Research
The aim of this paper was to investigate the skills required for managing a supply chain in an
Australian context and against the background of a turbulent business environment. Two core
findings are of particular note: the confirmation, in a non-European context, of the list and also
the grouping of SCM skills in the extant literature, and their ranking for managing supply chains.
The most interesting observation, however, concerns the paucity of functional logistics skills
among the list of significant skills during turbulent times. Instead, the focus shifts to relational
skills, and to the relational capability of SCM overall, alongside interpersonal skills, problemsolving, and other general management skills. Thus, in short, general problem-solving and
relational capabilities (mostly SRM that is ranked third) are more important for managing
turbulence than are functional skills such as inventory management, warehousing, transportation
management etc. This both confirms Mangan and Christopher’s (2005, p.180) view of supply
chain managers seeing themselves as “managers first and logisticians second” as well as the
importance of more strategic aspects of SCM for riding the high seas of turbulence.
In terms of the generalisability of the study, a number of observations are made. Firstly, as
indicated above, the empirical results from the survey described in this paper are broadly similar
to, and hence confirm, the earlier work of Mangan and Christopher (2005) and the more recent
work of Sohal (2013), which was also in an Australian context. A preliminary contribution of this
research is, thus, a much needed consolidation and extension of the SCM skills literature.
We suggest, therefore, that as a working hypothesis a similar level of importance would be found
were a comparative study to be undertaken in other developed, and possibly developing,
countries. This assertion is made by considering the core challenges of supply chain management
that are implicit in the Stock and Boyer (2009, p. 706) definition of SCM that underpins this
research. Core to this definition is the opening clause that “SCM is the management of a network
of relationships...”, a theme that is even more clearly laid out by the definition of SCM offered by
Christopher (2011, p.3) who suggests that it is “[t]he management of upstream and downstream
relationships with suppliers and customers to deliver superior customer value at less cost to the
supply chain as a whole.” Furthermore, Christopher goes on to suggest that “… equally the word
‘chain’ should be replaced by ‘network’ since there will normally be multiple suppliers and,
indeed, suppliers to suppliers, as well as multiple customers and customers’ customers to be
included in the total system.” (Christopher, 2011, p.3; emphasis in original).
Given that supply chains are now global concerns what we assert here is that the skills required by
a supply chain manager in the Australian context – to sense and respond to a change in supply or
demand – will be the same as those in a European context, and will also very likely be the same in
other parts of the world. By the same token, turbulent economic conditions are global phenomena
and few, if any, national contexts or supply chains will not feel the impact of events such as the
GFC. Given that turbulence is persistent and pervasive, it is argued that the skills required to
respond to it, in all its forms, will be very similar if not the same in all contexts. Nevertheless,
further research in other global regions should be undertaken in order to provide further
warrantability to these findings and test this assumption.
Thus, the management of supply chains (or networks) must be founded on relationships across
both internal and external networks. This is why our research strongly indicates that the skills
perceived to be most important by practitioners are centred on those activities that are essential to
such a role, namely: leadership; problem solving; SRM; negotiation; personnel management;
listening; problem identification; problem analysis; CRM; information sharing and oral
communication. The importance of such skills would also seem to touch on a point of
differentiation for SCM from other business disciplines, as SCM, almost by definition, cuts across
vertical fiefdoms within an organisation and across organisational and national boundaries. SCM
is conceptually both driven by, and a driver of, interdisciplinarity, boundary-spanning, and
globalisation. Thus, from the perspective of the survey respondents, there is clear advantage to be
gained from employing managers who can deliver the cross-cutting approach implicit in SCM and
who are able to challenge the siloed tendencies of those working in a particular organisational
division or national/cultural context.
It is also relevant to note that the results of the above research broadly mirror more recent work
by Wong et al (2014) who analysed job advertisements for Logistics and Supply Chain
Management (LSCM) staff. Their research “…demonstrates that the job market needs graduates
with more general business and management knowledge and leaderships skills, over LSCM
subject knowledge.” (pp. 547-548). Whilst this work was not specifically positioned in relation to
a turbulent business environment, Christopher and Holweg (2012)’s SCVI was based in a UK
context and demonstrated the turbulent nature of the business environment in that country and the
timing of their research mirrors that of Wong et al (2014) whose data gathering was undertaken in
2011-2012. To that extent, therefore, the two independent sets of research (that of Wong et al.,
2014, and that described and analysed in this paper) are clearly offering a broadly similar
perspective and conclusions.
Grouping the resultant skills from the survey in line with Teece’s (2007) sense and respond model
helped us to establish a link between SCM skills and agility. Sensing and responding to turbulent
economic conditions – the first two groups of skills – are clearly aligned with more general
management skills, whereas functional skills are used to maintain competitive advantage. We
therefore conclude that supply chain managers are in need of those broader, generalist skills in
order for them to be able to lead their supply chains through turbulent times. This does not,
however, take away from the importance of functional skills and those who possess them as, selfevidently, generalist managers must work closely with their functionalist colleagues. Rather, we
conclude that there is a shift in emphasis between those skills required during turbulent times (and
for which agility is key) to the functional skills that may best contribute to efficiency and leanness
in less turbulent times. Hence, in relation to the T-shaped model, we propose that the generalists
and functionalists require distinctly different managerial skill sets – put simply, it would be rare to
find an individual with the breadth and depth of skills required to singlehandedly run a global
supply chain. Both cohorts are needed and both must work closely together in the long run,
although we would argue that, in light of the increasing impact of turbulence and the associated
requirement for supply chain agility, the skills of the former will be of increasing importance in
the future. Thus, our primary contribution is to distinguish between the generalist and
functionalist relative to the business conditions faced.
In making this distinction and highlighting the importance of the generalist SCM skills set, our
research uncovers the criticality of individuals who can sense and respond to changing business
conditions. Liaising regularly with other generalists across the global supply network and with
functionalists within their organisation, they can monitor trend and forecast data to sense change
and lead effective decisions to respond before a significant impact is felt. What is equally
interesting is the spatiality, temporality and economic impact of their control, which our research
implies. Spatially, the span of a generalist supply chain manager’s responsibilities frequently
crosses conventional organisational boundaries – for example, one minute they might be in a local
team meeting to resolve a conveyor belt fault; the next, they are on the phone to a colleague at the
other end of the network to reconcile a shipping delay (c.f. Butcher, 2007). Temporally,
situations such as this require quick response; the timeliness of their decisions is the key. Whilst
economically, the quality of their (quick) decisions is paramount – the cost of an ineffective
decision, and the value of an effective one can affect the bottom line of not only their own
organisation, but also those of their supply chain partners. Generalist supply chain managers are,
thus, critical to overall supply chain effectiveness and efficiency.
A further clear implication of this research, together with that of Mangan and Christopher’s
(2005), Christopher (2013), Sohal (2013), and Wong et al. (2014), relates to the design of tertiary
and executive education programmes. It is argued that, in addition to the need for functionalist
educational programmes in sub-disciplines of SCM such as procurement and logistics, there is a
need for generalist, MBA-type programmes that prepare SC managers for the spatial, temporal
and economic challenges they will inevitably, and as would argue, increasingly face. Hence our
proposition is that there is a need for two streams of higher education to emerge from the current
undergraduate, postgraduate and executive programmes that are available. The first of these
would focus on educating the functionalists in the specialist skills of their chosen sub-discipline,
whilst the second would focus on equipping the generalists with the skills needed to work with
their functionalist colleagues across conventional boundaries and yet have the capability to, in
quick time, take the lead in key decisions when the unexpected happens.
In addition, our findings support Fabbes-Costes and Jahre’s (2008) call for further research on the
elusive link between SC integration and effectiveness. Interestingly, Sinkovics and Roath (2004)
were able to assert a relationship between supply chain collaboration and market performance, but
not between supply chain collaboration and supply chain performance. Establishing which skills
are needed for SCM in times of turbulence is, therefore, but a first step towards a potential
improvement in performance. As with all prior studies of the skills and capabilities required in
supply chain, logistics and procurement management, our emphasis has been on the development
of individual human capital. Yet with our identification of an increasing emphasis on relational
capabilities, we can infer that groups and teams, rather than individuals, manage contemporary
supply chain issues. Hence we suggest that one focus of further research be extended to the
identification and enhancement of SCM social capital. Where human capital is derived from an
individual’s investment in themselves to increase their worth, social capital is an individual or
group investment in social relations to gain returns (Lin, 2001). In this respect, our research
would appear to suggest that the ability of a supply chain manager to connect with others who can
quickly and accurately help him/her address a given issue should therefore be of significant value
to their supply chain, particularly in turbulent business conditions.
More broadly, the results of this research offer a number of additional areas that would appear to
merit further consideration. The first is that of firm size. Following on from the earlier
discussion of the cross-cutting nature of SCM and, hence, the challenge of achieving goalorientated pan-network management, it follows that larger organisations would face a larger
challenge and, hence, value the inter-personal and problem solving skills to an even greater
extent. By the same token, there may well be a differentiation that can be observed between
industries that reflects the complexity of their supply networks. For example, in an Australian
context, some of the extractive industries (coal, iron ore, gas) whilst operating on an extremely
large scale actually lead to a supply network that is not overly complex. On the other hand,
manufacturing industries that rely on multiple components and have multiple outlets exhibit
greater complexity. It would follow, therefore, that a comparative survey that spans a range of
industries should also demonstrate differential levels of importance for the skills sets described
above.
It is clear from our findings that the role of the contemporary supply chain manager is vast and
complex and thus, besides the practical implications of our proposition that SCM education
should be tailored to meet the differential needs of the functionalist and generalist streams, our
research has a final core research implication: do we really know what generalist supply chain
managers do day-to-day? All of the literature would support the perspective of Butcher (2007)
which positions such managers as the linchpins of an organisation that, perforce, operates in a
global supply chain which is, at the same time, becoming ever more challenging to manage
successfully. Yet, whilst there are ethnographic studies of various other work roles and
organisational contexts, there is none of the contemporary supply chain manager. Such studies
have uncovered cultural and sociological aspects of work previously not known or acknowledged,
or at least taken for granted. They have also opened up new lines of enquiry and new research
directions. Hence we propose ethnographic research to understand the culture and sociology of
supply chain management – the everyday life of the supply chain manager. In so doing, this will
begin to uncover the sorts of work they do, the implications of their work, and the relationships
they must foster to do so. In turn, such in-depth research can inform new research directions in
SCM, and lead to new educational and training needs.
References
Allen, A.M., Kovács, G., Masini, A., Vaillancourt, A., and van Wassenhove, L.N. (2013),
“Exploring the link between the humanitarian logistician and training needs”, Journal of
Humanitarian Logistics and Supply Chain Management, Vol.3 No.2, pp. 129-148
Armstrong, J.S., Overton, T.S. (1977), “Estimating nonresponse bias in mail surveys”, Journal of
Marketing Research, Vol. 14 No. 3, pp. 396-402.
Australian Government (2011), “Strategic review of the Treasury”, available at:
http://www.treasury.gov.au/contentitem.asp?NavId=&ContentID=2283 (accessed 2 January
2012).
Autry, C.W., Griffis, S.E., Goldsby, T.J., and Bobbitt, L.M. (2005), “Warehouse management
systems: Resource commitment, capabilities, and organizational performance”, Journal of
Business Logistics, Vol. 26 No. 2, pp. 165-183.
Azadegan, A., Dooley, K.J., Carter, P.L., and Carter, J.R. (2008), “Supplier innovativeness and
the role of interorganizational learning in enhancing manufacturing capabilities”, Journal of
Supply Chain Management, Vol. 44 No. 4, pp. 14-35.
Barreto, I. (2010), “Dynamic capabilities: A review of past research and an agenda for the future”,
Journal of Management, Vol. 36 No. 1, pp. 256-280.
Bechtel, C., and Jayaram, J. (1997), “Supply chain management: A strategic perspective”,
International Journal of Logistics Management, Vol. 8 No. 1, pp. 15-34.
Butcher, T. (2007), “Supply chain knowledge work: Should we restructure the workforce for
improved agility?”, International Journal of Agile Systems and Management, Vol. 2 No. 4, pp.
376-392.
Butcher, T., Christopher, M.G., and Mangan, D.J. (2011), “Skills and capabilities for agility: Do
we really know our supply chain managers?” Proceedings of the 9th ANZAM Operations, Supply
Chain and Services Management Symposium, Deakin University, 16-17 June 2011.
Carter, J., Closs, D.J., Dischinger, J.S., Grenoble, W.L., and Maxon, V.L. (2006), “Executive
education’s role in our supply chain future”, Supply Chain Management Review, Vol. 10 No. 6,
pp. 34-41.
Chavent, M., Kuentz-Simonet, V., Liquet, B., and Saracco, J. (2012), “ClustOfVar: An R package
for the clustering of variables”, Journal of Statistical Software, Vol. 50 No. 13, pp. 1-16.
Christopher, M.G. (2011), Logistics and Supply Chain Management (4th Ed), Financial Times
Prentice Hall, Harlow, UK.
Christopher, M.G., and Holweg, M. (2011), “ ‘Supply chain 2.0’: Managing supply chains in the
era of turbulence”, International Journal of Physical Distribution and Logistics Management, Vol
41 Iss. 1, pp. 63-82.
Christopher, M.G. (2013), “Managing supply chain complexity: Identifying the requisite skills”,
Supply Chain Forum: An International Journal, Vol. 13 No. 2.
CSCMP [Council of Supply Chain Management Professionals] (2014), “CSCMP’s definition of
logistics management”, CSCMP, available at: http://cscmp.org/about-us/supply-chainmanagement-definitions (accessed 26 February 2014).
D’Aveni, R. (1994), Hypercompetition: managing the dynamics of strategic maneuvering, The
Free Press, New York.
Dawson, J. (1995), “Strategies for retailers in Europe by 2000”, in Johnson, M. et al., (eds),
Facing up to the challenges of retailing, ESOMAR, Amsterdam, pp. 191-204.
Dawson, J. (2001), “Strategy and opportunism in European retail internationalization”, British
Journal of Management, Vol. 12, pp. 253–266.
Dischinger, J., Closs, D.J., McCulloch, E., Speier, C., Grenoble, W., and Marshal, L.D. (2006),
“The emerging supply chain management profession”, Supply Chain Management Review, Vol.
10 No 1, pp. 62-68.
Doheny, M., Nagali, V., and Weig, F. (2012), “Agile operations for volatile times.” McKinsey
Quarterly, May, 1-7.
Eisenhardt, K.M., and Martin, J.A. (2000), “Dynamic capabilities: What are they?” Strategic
Management Journal, Vol. 21 Iss. 10-11, pp. 1105/1121.
Ellinger, A.E., Natarajarathinam, M., Adam, F.G., Gray, J.B., Hofman, D., and O’Marah, K.
(2011), “Supply chain management competency and firm financial success”, Journal of Business
Logistics, Vol. 32 No. 3, pp. 214-226.
Esper, T.L., Fugate, B.S., and Davis-Stramek, B. (2007), “Logistics learning capability:
Sustaining the competitive advantage gained through logistics leverage”, Journal of Business
Logistics, Vol. 28 No. 2, pp. 57-81.
Fabbe-Costes, N., and Jahre, M. (2008), “Supply chain integration and performance – a review of
the evidence”, International Journal of Logistics Management, Vol. 19 No. 2, pp. 130-154.
Fawcett, S.E., Wallin, C., Allred, C., Fawcett, A.M., and Mangan, G.M. (2011), “Information
technology as an enabler of supply chain collaboration: A dynamic-capabilities perspective”,
Journal of Supply Chain Management, Vol. 47 No. 1, pp. 38-59.
Fine, C.H. (1998), Clockspeed: winning control in the age of temporary advantage, Perseus
Books, Reading.
Fine, C.H. (2000), Clockspeed-based strategies for supply chain design, Production and
Operations Management, Vol. 9 No. 3, pp. 213–221.
Gabric, D., and McFadden, K.L. (2001), “Student and employer perceptions of desirable entrylevel operations management skills”, American Journal of Business, Vol.16 No.1, pp.5-60.
Gammelgaard, B., and Larson, P.D. (2001), “Logistics skills and competencies for supply chain
management”, Journal of Business Logistics, Vol. 22 No. 2, pp 27-50.
Gattorna, J. (2010), Dynamic Supply Chains (2nd ed), Financial Times Prentice Hall, Harlow, UK.
Gibson, B.J., and Cook, R.L. (2001), “Hiring practices in US third party logistics firms”,
International Journal of Physical Distribution and Logistics Management, Vol. 31 Iss. 10, pp.
714-732.
Gibson. B.J., Hanna, J.B., and Menachof, D.A. (2004), “Periodical Usefulness: An International
Perspective”, International Journal of Logistics: Research and Applications, Vol. 7 No. 3, pp.
297-311.
Gligor, D.M., and Holcomb, M.C. (2012), “Understanding the Role of Logistics Capabilities in
Achieving Supply Chain Agility: A Systematic Literature Review,” Supply Chain Management:
An International Journal, Vol. 17 Iss. 4, pp. 438-453.
Grant, R.M. (2009), Contemporary Strategy Analysis (7th ed), John Wiley & Sons Inc., Hoboken,
NJ.
Harris, P. (2009), “Help wanted: "T-shaped" skills to meet 21st century needs”, T+D, Vol. 63 No.
9, pp. 42-47.
Hunt, S.D., and Davis, D.F. (2008), “Grounding supply chain management in resource-advantage
theory”, Journal of Supply Chain Management, Vol. 44 No. 1, pp. 10-21.
Iansiti, M. (1993), “Real-world R&D: Jumping the product generation gap”, Harvard Business
Review, Vol. 7 No. 3, pp. 138-147.
Keller, S.B., and Özment, J. (2009), “Research on personnel issues published in leading logistics
journals: What we know and don’t know”, International Journal of Logistics Management, Vol.
20 No. 3, pp. 378-407.
Kotzab, H., Grant, D.B., Teller, C., and Halldórsson, Á. (2009), “Supply chain management and
hypercompetition”, Logistics Research, Vol. 1, pp. 5–13.
Kovács, G., and Tatham, P.H. (2010), “What is special about a humanitarian logistician? A
survey of logistics skills and performance”, Supply Chain Forum: An International Journal, Vol.
11 No. 3, pp. 32-41.
Kovács, G., Tatham, P.H., and Larson, P.D. (2012), “What skills are needed to be a humanitarian
logistician?” Journal of Business Logistics, Vol. 33 No. 3, pp. 245-258.
La Londe, B.J., Ginter, J.J., Zinn, W., and Widdifield, D. (2010), “The Ohio State University
2010 Survey of Career Patterns in Logistics”, available at: http://cscmp.org/career/careerpatterns.asp (accessed 29 August 2011).
Lai, F., Li, D., Wang, Q., and Zhao, X. (2008), “The information technology capability of thirdparty logistics providers: A resource-based view and empirical evidence from China”, Journal of
Supply Chain Management, Vol. 44 No. 3, pp. 22-38.
Larson, P.D. (2005), “A note on mail surveys and response rates in logistics research”, Journal of
Business Logistics, Vol. 26 No. 2, pp. 211-222.
Larson, P.D., and Halldórsson Á. (2004), “Logistics versus supply chain management: An
international survey”, International Journal of Logistics: Research and Applications, Vol. 7 No.
1, pp. 17-31.
Larson, P.D., Poist, R.F., and Halldórsson, Á. (2007), “Perspectives on logistics vs. supply chain
management: A survey of SCM professionals”, Journal of Business Logistics Vol. 28 No. 1, pp.
1-24.
Leonard-Barton, D. (1995), Wellsprings of Knowledge: Building and Sustaining the Sources of
Knowledge, Harvard Business School Press, Boston, MA.
Lewin, R., Parker, T., and Regine, B. (1998), “Complexity theory and the organization: Beyond
the metaphor”, Complexity, Vol. 3 No. 4, pp. 36–40.
Lin, N. (2001), Social capital: a theory of social structure and action, Cambridge University
Press, Cambridge, UK.
Mangan, D.J., Gregory, O., and Lalwani, C. (2001), “Education, training and the role of logistics
managers in Ireland”, International Journal Logistics: Research and Applications, Vol. 4 No. 3,
pp. 313-327.
Mangan, D.J, and Christopher, M.G. (2005), “Management development and the supply chain
manager of the future”, International Journal of Logistics Management, Vol. 16 No. 2, pp. 178191.
Mangan, D.J., Lalwani, C., Butcher, T., and Javadpour, R. (2012), Global Logistics and Supply
Chain Management, John Wiley and Sons Ltd., Chichester, UK.
Maskell, B. (2001), “The age of agile manufacturing”, Supply Chain Management, Vol. 6 No. 1,
pp. 5-11.
Menachof, D.A., Gibson, B.J., Hanna, J.B., and Whiteing, A.E. (2009), “An analysis of the value
of supply chain management”, International Journal of Physical Distribution and Logistics
Management, Vol. 39 No. 1, pp. 145-166.
Molloy, J.C., Chadwick, C., Ployhart, R.E, and Golden, S.J. (2011), “Making intangibles
‘tangible’ in tests of resource-based theory: A multidisciplinary construct validation approach”,
Journal of Management, Vol. 37 No. 5, pp. 1496-1518.
Murphy, P.R., and Poist, R.F. (1991), “Skill requirements of senior-level logistics executives: An
empirical assessment”, Journal of Business Logistics, Vol.12 No. 2, pp. 73-94.
Murphy, P.R., and Poist, R.F. (1993), “In search of warehousing excellence: A multivariate
analysis of HRM practices”, Journal of Business Logistics, Vol. 14 No. 2, pp. 145-164.
Murphy, P.R., and Poist, R.F. (2007), “Skill requirements of senior-level logisticians: A
longitudinal research assessment”, Supply Chain Management: An International Journal, Vol. 12
No. 6, pp. 423-431.
Myers, M.B., Griffith, D.A., Daugherty, P.J., and Lusch, R.F. (2004), “Maximizing the human
capital equation in logistics: Education, experience, and skills”, Journal of Business Logistics,
Vol. 25 No. 1, pp. 211-232.
Nunnally, J.C. and Bernstein, I.H. (1994), Psychometric Theory (3rd Ed), McGraw Hill, New
York, USA.
Okongwu, U. (2007), “An innovative supply chain management programme structure:
Broadening the SCM skill set”, International Journal of Learning and Change, Vol. 2 No. 2, pp.
192-210.
Olavarrieta, S., and Ellinger, A.E. (1997), “Resource-based theory and strategic logistics
research”, International Journal of Physical Distribution and Logistics Management, Vol. 29 Iss.
9/10, pp. 559-587.
Pagell, M., Handfield, R.B., and Barber, A.E. (2000), “Effects of operational employee skills on
advanced manufacturing technology practice”, Production and Operations Management, Vol. 9
No. 3, pp. 222-238.
Paulraj, A. (2011), “Understanding the relationships between internal resources and capabilities,
sustainable supply management and organizational sustainability”, Journal of Supply Chain
Management, Vol. 47 No. 1, pp. 19-37.
Rahman, S., Butcher, T., and Yang, L. (2009), Logistics manager skill requirements: Comparing
international practices, Proceedings of the ANZAM Operations, Supply Chain and Services
Management Symposium, Adelaide, 8-10 Jun.
Ramsay, J. (2001), “The resource based perspective, rents, and purchasing’s contribution to
sustainable competitive advantage”, Journal of Supply Chain Management, Vol. 37 No. 3, pp. 3847.
Rogers, D.S., and Tibben-Lembke, R. (2001), “An examination of reverse logistic practices”,
Journal of Business Logistics, Vol. 22 No. 2, pp. 129-148.
Rossetti, C.L., and Dooley, K.J. (2010), “Job types in the supply chain management profession”
Journal of Supply Chain Management, Vol. 46 No. 3, pp. 40-56.
Rossi, V. (2011), “Is the global economy on the brink of recession?”, Intereconomics, Vol. 46 No.
6, pp. 300-326.
Sarkis, J. (2001), “Benchmarking for agility”, Benchmarking: An International Journal, Vol. 8
No. 2, pp. 88-107.
Shell (2008), “Shell energy scenarios to 2050”, available at: http://s01.staticshell.com/content/dam/shell/static/future-energy/downloads/shell-scenarios/shell-scenarios2050signalssignposts.pdf (accessed 22 Sep 2015).
Shell (2011), “Shell energy scenarios to 2050, signals and signposts”, available at:
http://s01.static-shell.com/content/dam/shell/static/future-energy/downloads/shell-scenarios/shellscenarios-2050signalssignposts.pdf (accessed 22 Sep 2015).
Simons, H. (2011), “Baltic Dry Freight Index no longer a valid economic indicator”, Minyanville
Business News, March 14, 2011, available at:
http://www.minyanville.com/businessmarkets/articles/baltic-index-economic-indicator-oceanfreight/3/14/2011/id/33292 (accessed 28 May 2012).
Singh, M. (2009), “In times of uncertainty, focus on the future”, Supply Chain Management
Review, Vol. 13 No. 3, pp. 20-26.
Sinkovics, R.R., and Roath, A.S. (2004), “Strategic orientation, capabilities, and performance in
manufacturer-3PL relationships”, Journal of Business Logistics, Vol. 25 No. 2, pp. 43-64.
Sohal, A.S., and D’Netto, B. (2004), “Incumbent perceptions of the logistics profession”,
International Journal of Logistics Systems and Management, Vol. 1 No. 1, pp. 5-25.
Sohal, A.S. (2013), “Developing competencies of supply chain professionals in Australia:
Collaboration between businesses, universities and industry association”, Supply Chain
Management: An International Journal, Vol. 18 Iss. 4, pp. 429–439.
Stank, T.P., Dittman, J.P., and Autry, C.W. (2011), “The new supply chain agenda: A synopsis
and directions for future research”, International Journal of Physical Distribution and Logistics
Management, Vol. 41 Iss. 10, pp. 940-955.
Stock, J.R., and Boyer, S.L. (2009), “Developing a consensus definition of supply chain
management: A qualitative study”, International Journal of Physical Distribution and Logistics
Management, Vol. 39 Iss. 8, pp. 690-711.
Sweeney, E., Grant, D.B., and Mangan, D.J. (2015), “The implementation of supply chain
management theory in practice: An empirical investigation”, Supply Chain Management: An
International Journal, Vol. 20 Iss. 1, pp. 56-70.
Teece, D.J., and Pisano, G. (1994), “The dynamic capabilities of firms: An introduction”,
Industrial and Corporate Change, Vol. 3 No. 3, pp. 537-556.
Teece, D.J., Pisano, G., and Shuen, A. (1997), “Dynamic capabilities and strategic management”,
Strategic Management Journal, Vol. 18 No. 7, pp. 509-533.
Teece, D.J. (2000), “Strategies for managing knowledge assets: The role of firm structure and
industrial context”, Long Range Planning, Vol. 33, pp. 35-54.
Teece, D.J. (2007), “Explicating dynamic capabilities: The nature and microfoundations of
(sustainable) enterprise performance”, Strategic Management Journal, Vol. 28, pp. 1319-1350.
Teece, D.J. (2010), “Business models, business strategy and innovation”, Long Range Planning
Vol. 43, pp. 172-194.
Thomas, R.J., Bellin, J.B., Jules, C., and Lynton, N. (2012), “Does your global leadership team
have what it takes?” Outlook, Vol. 1, pp. 1-7, available at:
http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Outlook-Does-your-globalleadership-team-have-what-it-takes.pdf (accessed 12 Jun 2013).
Van Hoek, R., Chatham, R., and Wilding, R. (2002), “Managers in supply chain management, the
critical dimension”, Supply Chain Management: An International Journal, Vol. 7 No. 3, pp. 119125.
Vereecke, A., Boute, R. Dierdonck, R., and Seernels, S. (2008), “Supply chain managers – who
needs them? Insights from a European survey on the profile and the role of the supply chain
manager”, White Paper, Vlerick Leuven Gent Management School, November 2008.
Weiss, A. (ed.) (2005), Conquering Complexity: Lessons for defence systems acquisition. The
Stationery Office, London, UK.
Wong, C.H., Grant, D.B., Allan, B., and Jasiuvian, I. (2014), “Logistics and supply chain
education and jobs: A study of UK markets”, The International Journal of Logistics Management,
Vol. 25 No. 3, pp. 537-552.
Zhao, M., Dröge, C., and Stank, T.P. (2001), “The effects of logistics capabilities on firm
performance: Customer-focused vs. information-focused capabilities”, Journal of Business
Logistics, Vol. 22 No. 2, pp. 91-107.
APPENDIX A
Skills and skill sets in the survey – (modified from the ‘T-shaped skill set’ originally introduced by Mangan and Christopher, 2005, p.181 and
subsequently developed by Kovács and Tatham, 2010, p. 35.
APPENDIX B
The aims and objectives of The Chartered Institute of Logistics and Transport, Australia (CILTA) and the Logistics Association of
Australia (LAA)
1.
The principle objective of CILTA is to Promote and Encourage the Art and Science of Logistics and Transport. It provides leadership in
research, policy and professional development and support continuous improvement in the industry. (Source:
http://www.cilta.com.au/index.cfm?MenuID=39)
2.
The mission of the LAA is to provide a voice for every logistics professional, practitioner and student throughout Australia. Its vision is
to serve the logistics and supply chain profession by facilitating the exchange of knowledge and experience. (Source:
http://www.laa.asn.au/vision.htm)