Article review
eryrcch
13_articles.pdf
Analysis of SCOR’s approach to supply chain risk management
Kristian Rotaru, Carla Wilkin and Andrzej Ceglowski Department of Accounting, Monash University, Melbourne, Australia
Abstract Purpose – SCOR 10.0, released in late 2010, is the second version of the supply chain operations reference model (SCOR) to incorporate risk management processes, metrics and best practices. Given the paucity of studies that have explored the coverage and integration of supply chain risk management (SCRM) within SCOR, the analysis and suggested improvements for SCRM are designed to enhance SCOR’s collaborative and coordinated management of supply chain (SC) risks. The paper aims to dicsuss these issues. Design/methodology/approach – Critical analysis was used to analyse the coverage and integration of SCRM within SCOR 10.0. Findings – Discrepancies were identified in how SCRM has been incorporated into SCOR, including issues with the hierarchical representation of SCRM processes, metrics, best practices and skills. These may potentially propagate into difficulties in embedding risk management processes within other SC processes, visualizing risk metrics in a SC’s value hierarchy and reconciling SCOR’s SCRM with organizational enterprise risk management. Research limitations/implications – This paper is limited to theoretical analysis of the coverage and integration of risk in SCOR 10.0. Once the issues identified are remedied, the subsequent suggested improvements require validation through empirical testing. Originality/value – Despite SCOR’s wide acceptance as a reference model in managing SC operations, there has been no investigation of its approach to SCRM. The analysis addresses this lack of prior investigation by analysing SCRM in the latest version, SCOR 10.0. The paper identifies deficiencies and suggests amendments regarding SCRM’s coverage and integration of SCRM. Keywords Supply chain management, Risk management, Conceptual framework, SCOR 10.0 Paper type Conceptual paper
1. Introduction Supply chain risk management (SCRM) concerns “the management of supply chain (SC) risks through coordination or collaboration among the SC partners so as to ensure profitability and continuity” (Tang, 2006a, p. 453). SCRM is of strategic concern for organizations. Toyota’s two billion dollar loss from a failure in brake pedal design that was magnified by SC lead time (Dittman et al., 2010); and Matsushita’s losses of LCD IT panels from its factory fire, with subsequent global supply implications (Smith and Associates, 2007), are examples of the ripple effects from manifestation of SC risk. Whilst CEOs are increasingly aware of the financial aspect of SC disruptions (Malone, 2006), 90 per cent of organizations are yet to effectively address the matter (Dittman et al., 2010). The supply chain operations reference model (SCOR) is a widely accepted industry reference model for SC operations that was introduced to assist organizations in mapping, developing and referencing SC operations, and assessing and monitoring levels of SC performance.
Despite being developed in 1996, there was no conceptualization of SCRM (or risk of any form) in SCOR until 2008 when SCRM was introduced in SCOR 9.0 through the addition of processes, attributes and metrics, and best practices (Supply chain council (SCC), 2008). This was later extended in SCOR 10.0 (Supply chain council (SCC), 2010) via the addition of performance attributes and metrics (in the enabling process) and a
International Journal of Operations & Production Management Vol. 34 No. 10, 2014 pp. 1246-1268 © Emerald Group Publishing Limited 0144-3577 DOI 10.1108/IJOPM-09-2012-0385
Received 21 September 2012 Revised 24 May 2013 23 July 2013 Accepted 23 July 2013
The current issue and full text archive of this journal is available at www.emeraldinsight.com/0144-3577.htm
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set of best practices. Our extensive literature review showed no evidence of appraisal of SCOR’s approach to SCRM[1], nor any practical application of its risk guidelines. Given the growing body of literature on SCOR as well as its predominance in industry, this is a serious research gap.
Our critical analysis of the wider body of literature shows a number of discrepancies regarding how SCRM is aligned within the components of SCOR. According to the general principles of hierarchical decomposition (Simon, 1996), which have been adopted in the field of SCRM (Neiger et al., 2009; Rotaru et al., 2011), if a process and associated process-related metrics are aligned at a higher level (i.e. Level 1), the relationship between subcomponents of the process and metric should be preserved when they are decomposed to lower levels (i.e. Levels 2 and 3). Further, lower level performance metrics should directly contribute to higher level metrics and subsequently to performance attributes directly associated with Level 1 metrics.
With this in mind the objective of our paper is to theoretically analyse the coverage and integration of SCRM within SCOR 10.0 and to suggest improvements that contribute to SCOR’s evolving relevance in proactively managing SC risks.
Our findings demonstrate significant concerns with the current coverage of SCRM in SCOR, in particular:
(1) the hierarchical misalignment between SC risk-related processes and metrics, which is contrary to the basic processes/metrics hierarchy principles espoused in SCOR;
(2) the ex post (reactive) nature of value at risk (VAR), the only risk measure suggested by SCOR, which severely limits the ability to proactively identify, assess and react to unprecedented (and potentially devastating) future events;
(3) issues with subadditivity/diversification of VAR, i.e., the sum of compart- mentalized (disaggregated VAR-Plan, VAR-Source, VAR-Make, etc.) measures of risk associated with distinct SC processes produce an unrealistic (often too optimistic) assessment of the risk exposures associated with the entire SC;
(4) the lack of hierarchical representation of SCRM best practices and the dated- ness of the SCRM tools recommended within the SCRM “best practices” com- ponent; and
(5) the shortage of prescribed SCRM skills in the “People” component of SCOR 10.0.
In reporting on our analysis and suggested improvements, the paper is structured as follows: First, we provide an overview of SCOR, followed by discussion of risk management and SCOR’s approach to it. We then provide a review of research related to SCOR before outlining our research method. Next, we provide an analysis that highlights problems with SCOR’s representation of SC risk in process and value hierarchies, and critically appraise the incorporation of SCRM processes, attributes and metrics, best practices and skills. A number of improvements are suggested in conjunction with our analysis. Finally, we conclude the paper and offer suggestions for future research.
2. Background and literature review 2.1 SCOR: concepts and context SCOR is a hierarchical cross-functional process reference model “that links business process [including over 200 process elements], [550] metrics, [500] best practices
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Analysis of SCOR’s approach
[including ones specifically targeting risk and environmental management] and technology features into a unified structure to support communication among [SC] partners and to improve the effectiveness of [SC] management and related [SC] improvement activities” (SCC, 2010, p. 1.1.1; Knolmayer et al., 2009). From a SC process perspective, SCOR is organized around five strategic SC process types, namely Plan, Source, Make, Deliver and Return (Figure 1). These link suppliers and customers to a company (denoted “your company”). At the strategic level SCOR represents each SC as interconnected sets of Source-Make-Deliver execution processes, which transform/transport materials and/or products. Planning allows management of cross-organizational customer-supplier links, while Return accounts for raw material returns and receipt of finished goods.
The process types portrayed in Figure 1 are decomposed into process categories, then sequentially into process elements, activities and workflows (see Figure 2). This decomposable SC process hierarchy assists with analysis of intra-/inter-organizational relationships (Wall et al., 2007; Theeranuphattana and Tang, 2007) and SC performance (Hwang et al., 2010; Trkman et al., 2010). It also assists with supply chain management’s (SCM’s) core objective: “to optimize the efficiency of the companies involved and harmonize the conflicting objectives” (Poluha, 2007, p. 26).
SCOR provides a standardized language to describe a SC’s performance attributes and metrics, configuration, activities, practices and workforce assets through four major components:
(1) Processes: standard descriptions of management processes and process relationships;
(2) Performance (attributes and metrics): attributes refer to characteristics that are used to describe a strategy, facilitate classification for metric purposes, and formulate strategic direction. Metrics refer to measurement standards that can be used to quantitatively express achievement of a company’s objectives associated with SC processes;
(3) Best practices: “current”, “structured” and “repeatable” practices with proven and positive impact on SC performance; and
(4) People (skills): assessment of skill needs and availability related to building the SC.
Your CompanySupplier Supplier’s Supplier
Customer Customer’s Customer
Source Make Deliver
Return Return
Plan
Source Make Deliver
Return Return
Plan
Source Make Deliver
Return Return
Plan
Return
Deliver
Return
Sourse
Internal or External Internal or External
Source: Supply chain council (SCC, 2011)
Figure 1. SCOR model with its five strategy-level processes
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Through integrating these components SCOR aims to increase visibility and enhance performance for all members of a SC network (SCC, 2010; Hwang et al., 2008; Huang et al., 2004). These four components are combined (see Figure 3) with four techniques (business process reengineering, benchmarking, best practices analysis and organizational design) to establish and subsequently achieve desirable targets. Each process comprises associated performance attribute(s) and metrics, as well as best practices and skills.
2.2 Risk management principles and SCOR’s approach to risk management Given the inter-operational nature of SCs, organizations involved in them are exposed to risk that is beyond what arises within their own operation. Thus, from a SC perspective, risk is customarily viewed as “the probability of an incident associated with inbound supply from individual supplier failures or the supply market occurring, in which its outcomes result in the inability of the purchasing firm to meet customer demand or cause threats to customer life and safety” (Zsidisin, 2003, p. 222). Herein, the objective of SCRM is to minimize the negative impact of such adverse events on the performance of distinct SC partners as well as the entire SCs (SCC, 2010; Tang, 2006a).
SCOR Level Overview Description
1. Scope
2. Configuration
4. Implementation (outside SCOR 10.0 scope)
3. Decomposed Process Categories
The five strategic SC process types (i.e. Plan etc.) decompose into process categories, which facilitate companies in scoping their SC strategy, objectives and content. Herein companies differentiate themselves through defining strategic objectives (such as pre- eminence in custom manufacturing processes) and associated metrics (such as “Perfect Order Fulfillment (RL.1.1)”).
The company configures its SC, with each Level 1 category decomposing into elements:
Planning: alignment of expected resources to meet expected demand requirements; Execution: triggered by planned or actual demand, it changes the stage of material goods; and Enable: prepares, maintains or manages information or relationships upon which planning and execution rely.
For example, The custom manufacturing strategy process entails a “make-to-order” process category, and the “Perfect Order Fulfillment” metric may decompose into Level 2 metrics like “% of Orders Delivered in Full (RL.2.1)”.
Organisational activities are detailed by linking metrics and best practices to Process Elements. This describes the sequenced activities needed to achieve Level 2 Process Categories. Continuing the example above, The sequence of Level 3 Process elements (plan,source materials, make products, deliver goods and handle returns) would support the “make to order” SC category, and decomposed Metrics For”% of Orders Delivered in Full” would include “Item Accuracy (RL.3.33)”.
Whilst Levels 1-3 provide a template, implementation is outside SCOR’s scope, but every company needs to tailor activities to their specific industry, product, location and technology.
P ro
ce ss
T yp
e s
P ro
ce ss
C a
te g
o ri
e s
P ro
ce ss
E le
m e
n ts
W o
rk flo
w s
Source: adapted from SCC (2010, 2011)
Figure 2. Overview: SCOR’s
four levels
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Analysis of SCOR’s approach
SCRM has been the subject of recent journal special issues (e.g. Narasimhan and Talluri, 2009; Wu and Olson, 2009; Flynn, 2009) and review articles (e.g. Tang, 2006b; Peck, 2006; Khan and Burnes, 2007; Rao and Goldsby, 2009; Tang and Musa, 2011; Sodhi et al., 2012). Authors have emphasized that given the positive factors brought about by new SCM trends and strategies (such as a reduction of supply base, reduction of inventory and lead time, shorter product life cycles, globalization of SCs), new socio- technical and other sources of SC risk have appeared, making modern SCs more vulnerable (e.g. Svensson, 2000; Christopher and Lee, 2004; Jüttner, 2005). As a result, the number of routine logistic failures like the two examples outlined in the Introduction have increased, as has the probability for disruption of the logistic network operations (Khan and Burnes, 2007; Rao and Goldsby, 2009). In view of this trend, SCRM is increasingly viewed as one of the critical strategic processes/functions of modern SCs (Tang and Musa, 2011) and, together with performance improvement, as a core SC value generating mechanism (Tang, 2006b; Hallikas et al., 2004; Hallikas and Varis, 2008; Ritchie and Brindley, 2007a, b; Neiger et al., 2009).
Within SCOR, SCRM has been reflected at Level 3 as a set of “Enable” type process elements i.e., Manage SC Plan Risk (sEP.9), Manage SC Make Risk (sEM.9), Manage Supply Source Risk (sES.9), Manage SC Deliver Risk (sED.9) and Manage SC Return Risk (sER.9). However, SCOR’s Process component does not reflect decomposition of risk management processes into sub-processes (i.e. risk identification, risk analysis, etc.) as commonly recommended in risk management standards and frameworks (e.g. ISO 31000:2009; COSO, 2004).
SCOR performance objectives are organized in a hierarchical manner with higher level metrics decomposing into lower level ones. Gaps or improvements in Level 1 metrics can be explained by looking at the performance of Level 2 metrics (called metric decomposition or root-cause analysis). Similarly Level 3 metrics serve as diagnostics for Level 2 metrics. The performance of SCRM-related processes is reflected in SCOR 10.0 through a single aggregated metric, VAR. VAR originated from analyses of financial risk where it is used to measure expected portfolio losses over a given time period at a certain confidence level (Jorion, 2006). In adapting VAR to the context of SCRM, SCOR inherits the portfolio-based approach, conceptualizing VAR as the sum of the probabilities of risk events times the monetary impact of the events for all the SC functions (Plan, Source, Make, Deliver and Return) (SCC, 2010). Figure 4 depicts this aggregation.
Organizational Design
Capture the “as-is” state of a process and derive the desired ‘to-be” future state
Quantify the operational performance of similar companies and establish internal targets
Business Process Reengineering
Benchmarking Best Practices
Analysis
Identify the practices and software solutions that result in significantly better performance
Process Reference Framework
Processes Performance
(attributes and metrics) Best Practices
People (skills)
Assess skills and performance needs and align staff and staffing needs to internal targets
Source: adapted from (SCC, 2010, 2011)
Figure 3. The relationship between SCOR’s techniques and components
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The internal logic driving the risk management process is reflected within SCOR’s best practices, rather than as sub-processes integral to SCOR (which are depicted in Figure 2).
The People section of SCOR 10.0 is new. It describes the SC specific skills required to perform tasks and manage processes, including those related to SCRM.
2.3 Review of research related to SCOR Since SCOR’s inception, adaptations have often been stimulated by comments in the research literature. Table I below summarizes conceptual, analytical and empirical research in relation to SCOR[2]. Findings show some lack of currency in the reported literature (i.e. eight papers post 2009 refer to outdated SCOR models), and no consideration of SCRM.
Table I above demonstrates that to date research has principally focused on describing (i.e. Stewart, 1997), comparing (i.e. Ellram et al., 2004), applying and/or adapting SCOR (i.e. Huang et al., 2005) by integrating it with analytical approaches and methodologies that address specific company needs (i.e. Huang et al., 2004; Kirchmer, 2004; Li et al., 2011; Persson, 2011). Importantly few researchers (Poluha, 2007; Millet et al., 2009; Trkman et al., 2010) have critically analysed SCOR’s internal consistency and/or alignment of its components or provided direction for further improvement. Consequently in the literature SCOR has largely been adopted/adapted in an “as is” manner, without its internal consistency being rigorously challenged.
The misalignment between publication dates and the scrutinized SCOR model is striking. For example, Persson (2011) studied SCOR 7.0 (released in 2005), while Gumus et al. (2010) used SCOR 2.0 (released in 1997). The research gap, identified by Gumus et al. (2010), related to the Return process type in SCOR 2.0, has been addressed since 2000 in SCOR 4.0. Similarly: Zangoueinezhad et al. (2011) used SCOR 3.0; Wang et al. (2010) used SCOR 7.0; Cai et al. (2009) used SCOR 3.0 and SCOR 4.0; and Millet et al. (2009) referred to either SCOR 5.0 or 7.0 (see Table I, note a).
The only refereed journal paper we identified (Faisal et al., 2007) that investigated the method and potential implications of SC risk modelling within SCOR was published prior to the introduction of SCRM into model[3]. This lack of analysis of SCOR’s
Hierarchical Metric Structure
AG.1.4 Value At Risk (VAR $) = VAR $ (Plan) + VAR $ (Source) + VAR $ (Make) + VAR $ (Deliver) + VAR $ (Return)
Level 1
Level 2 Value At Risk (VAR $) (Plan)
Value At Risk (VAR $) (Source)
Value At Risk (VAR $) (Make)
Value At Risk (VAR $) (Deliver)
Value At Risk (VAR $) (Return)
Source: adapted from SCC (2010, p. 2.3.8)
Figure 4. Hierarchical
decomposition of the VAR (AG.1.4) metric
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Analysis of SCOR’s approach
SC O R
ve rs io n
R es ea rc he r
T op ic an d fi nd
in gs
1. 0
St ew
ar t (1 99 7)
C la ss if ie d an d de fi ne d SC
O R 1. 0’ s m ai n co m po ne nt s
2. 0
G um
us et al .( 20 10 )
B as ed
on ne ur al
ne tw
or k si m ul at io n of
a SC
,d ev el op ed
a SC
m od el th at :
(1 ) de m on st ra te d m or e re al is ti c re su lt s re ga rd in g de m an d an d le ad
ti m e;
(2 ) w as
ge ne ra liz ed
fo r N -e ch el on s an d a tr ee -s tr uc tu re d SC
;a nd
(3 ) al lo w ed
ex pe di ti on
of or de rs
ar ri vi ng
ou t of
ph as e
3. 0
H ua ng
et al .( 20 04 )
C on si de re d SC
O R ’s po te nt ia l fo r st ra te gi c de ci si on
su pp
or t by
in cl ud
in g ch an ge
m an ag em
en t as
an el em
en t w it hi n
SC O R ’s P la n pr oc es se s
Z an go ue in ez ha d et al .
(2 01 1)
D em
on st ra te d th at
th e co m pe ti ti ve ne ss
po si ti on in g in de xe s of
SC O R :
(1 ) sh ou ld
be ta ilo re d to
th e or ga ni za ti on ’s ov er al l go al s+
ob je ct iv es
of ea ch
in di vi du
al un
it ;a nd
(2 ) m ay
no t be
m ut ua lly
in de pe nd
en t.
3. 0 an d
4. 0a
C ai
et al .( 20 09 )
B as ed
on SC
O R ,p
ro po se d a fr am
ew or k to
be tt er
ac co m pl is h it er at iv e ke y pe rf or m an ce
in di ca to rs
(K P Is ) in
SC s by
: (1 ) qu
an ti ta ti ve
an al ys is of
in te rd ep en de nt
re la ti on sh ip s am
on g K P Is ;a nd
(2 )i de nt if ic at io n of cr uc ia lK
P Ia cc om
pl is hm
en tc os ts ,a nd
pr op os it io n of pe rf or m an ce
im pr ov em
en ts tr at eg ie s fo r SC
de ci si on -m
ak er s.
4. 0
L oc ka m y an d
M cC or m ac k (2 00 4)
E xp lo re d th e re la tio ns hi p be tw ee n SC
pl an ni ng
pr ac tic es
an d th e P la n/ So ur ce /M
ak e/ D el iv er
ar ea s of
SC pe rf or m an ce
So ff er
an d W an d (2 00 5)
Sh ow
ed th at
a so ft -g oa l in
SC O R is as so ci at ed :
(1 ) w it h on ly
so m e re le va nt
pr oc es se s; an d
(2 ) on ly
w it h th e pr oc es s w he re in
it is m ea su re d.
4. 0 &
5. 0a
F ai sa l et al .( 20 07 )
A pp
lie d SC
O R in
de ve lo pi ng
an A N P -b as ed
fr am
ew or k fo r ri sk
m it ig at io n in
SC s th at
ac co un
te d fo r in di re ct
re la ti on sh ip s an d co m pl ex
in te ra ct io ns
am on g SC
ri sk
va ri ab le s. N O T E :t hi s pr ec ed ed
th e in tr od uc ti on
of SC
R M
5. 0
B ur ge ss
an d Si ng
h (2 00 6)
Sh ow
ed re la ti on sh ip s be tw
ee n re le va nt
va ri ab le s fr om
di ff er en t di sc ip lin
es (i. e. co rp or at e go ve rn an ce ,i nf ra st ru ct ur e,
op er at io ns
kn ow
le dg
e, so ci al
cl im
at e an d in no va ti on ) an d th ei r im
pa ct
on SC
pe rf or m an ce
E llr am
et al .( 20 04 )
C om
pa re d SC
O R ,t he
G lo ba l SC
F or um
F ra m ew
or k an d H ew
le tt -P ac ka rd ’s SC
M M od el fo r SC
m an ag em
en t.
H ig hl ig ht ed
ch al le ng
es fo r pr oc ur em
en t pr of es si on al s in
m an ag in g pu
rc ha se s in
a se rv ic es
SC H ua ng
et al .( 20 05 )
B ui lt a co m pu
te ri ze d so lu ti on
ba se d on
SC O R .C
on cl ud
ed th at
in su ff ic ie nt
cu st om
iz at io n to ol s co nt ri bu
te d to
SC O R ’s
sl ow
ac ce pt an ce
(c o n ti n u ed
)
Table I. Past research concerning application and analysis of SCOR
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IJOPM 34,10
SC O R
ve rs io n
R es ea rc he r
T op ic an d fi nd
in gs
K ir ch m er
(2 00 4)
B ui lt an d im
pl em
en te d a “b us in es s pr oc es s w ar eh ou se ”, na m el y a si ng
le re po si to ry
of SC
O R m od el s, st an da rd
e- bu
si ne ss
sc en ar io s, an d R os et ta N et
P ar tn er
In te rf ac e P ro ce ss
in fo rm
at io n th at
su pp
or ts
va lu e ch ai n im
pr ov em
en t
th ro ug
h in cr ea se d pe rf or m an ce
of re su lt in g bu
si ne ss
pr oc es se s. T he
su gg
es te d m et ho do lo gy
su pp
or ts
fu tu re
va lu e
ch ai n pr oj ec ts
th at
de al
w it h in te r- en te rp ri ze
sc en ar io s
R od er
an d T ib ke n (2 00 6)
E xt en de d SC
O R by
de ve lo pi ng
a SC
O R -b as ed
de ci si on
su pp
or t sy st em
fo r in tr a- in te r- or ga ni za ti on al pr oc es se s, w hi ch
pe rm
it s in te r- co m pa ny
us e of
in te gr at ed
pr od uc ts
an d ev al ua ti on
of pr oc es s do cu m en ta ti on
ba se d on
di ff er en t
co nf ig ur at io ns
of pr oc es s ch ai ns
w it h di ff er en t se ts
of pa ra m et er s
5. 0 an d 6. 0
L am
be rt et al .( 20 05 )
D em
on st ra te d th at
SC O R ad dr es se d SC
M fr om
a ta ct ic s- or ie nt ed
pe rs pe ct iv e, w hi le th e G lo ba l SC
F or um
fr am
ew or k
w as
m or e st ra te gi c
6. 0
Si nh
a et al .( 20 04 )
B as ed
on th e in te gr at ed
de fi ni ti on
m et ho d,
de ve lo pe d a ge ne ri c m et ho do lo gy
fo r m it ig at in g ri sk s in
ae ro sp ac e SC
s. R is k w as
no t ex pl ic it ly
in te gr at ed
in to
th e re su lt in g SC
O R m od el
W al l et al .( 20 07 )
B y in ve st ig at in g P or te r’ s V al ue
C ha in
m od el th ey
su gg
es te d an
ex te ns io n to
SC O R re ga rd in g cu rr en t e- B us in es s
ap pl ic at io ns
7. 0
H w an g et al .( 20 08 )
T hr ou gh
st ep w is e re gr es si on ,e xp
lo re d sc or in g pr oc es se s at
SC O R ’s L ev el 2 an d re la te d cr it ic al pe rf or m an ce
m et ri cs .
L is te d L ev el 3’ s st at is ti ca lly
si gn
if ic an t m et ri cs
an d id en ti fi ed
ba si c st ep s of
in st it ut io na liz at io n ac ro ss
ba si c ph
as es
of pr oj ec t in te gr at io n in
SC O R
H w an g et al .( 20 10 )
In ve st ig at ed
th e re la ti on sh ip
be tw
ee n th e pl an -d o- st ud
y- ac t (P D SA
) cy cl e of
gr ee n pu
rc ha si ng
an d th e SC
O R
pu rc ha si ng
/s ou rc in g pr oc es s+
co rr es po nd
in g m et ri cs .F
ou nd
st at is ti ca lly
si gn
if ic an t re la ti on sh ip s be tw
ee n th em
M ill et
et al .( 20 09 )b
A na ly se d al ig nm
en t of
bu si ne ss
pr oc es se s an d ex te nd
ed SC
O R by
: (1 ) as su ri ng
m or e co m pl et e re pr es en ta ti on
of SC
O R pr oc es se s;
(2 ) be tt er
vi su al iz at io n of
ph ys ic al
an d in fo rm
at io na l de pe nd
en ci es
be tw
ee n pr oc es se s; an d
(3 ) fa ci lit at in g m or e pr ec is e al ig nm
en t of
E R P (E nt er pr iz e R es ou rc e P la nn
in g)
sy st em
s w it h SC
O R pr oc es se s.
P er ss on
an d A ra ld i (2 00 9)
In ve st ig at ed
ho w to
pr ov id e a co m pu
te ri ze d si m ul at io n so lu ti on
th at
re fl ec ts th e dy
na m ic ch an ge s in
SC pe rf or m an ce .
P ro du
ce d a te m pl at e ba se d on
te n “m
od ul es ” th at
re fe r to
L ev el 2 SC
O R pr oc es se s
P er ss on
(2 01 1)
T hi s se co nd
re vi se d te m pl at e ov er ca m e ea rl ie r lim
it at io ns
(s ee
P er ss on
an d A ra ld i, 20 09 ). T es ti ng
sh ow
ed it s re le va nc e
as a de ci si on
su pp
or t to ol
in th e al lo ca ti on
of pr od uc ti on
re so ur ce s ta sk s
W an g et al .( 20 10 )
T hi s st ud
y of
co ns ti tu en ts
fo r bu
si ne ss
pr oc es s tr an si ti on ,w
hi ch
w as
ba se d on
fo ur
de ci si on
ar ea s (K P I an al ys is ,
pr ob le m
an d gr ou pi ng
an al ys is ,e xp
ec ta ti on
of ow
ne rs hi p,
an d ex pe rt op in io ns ) id en ti fi ed
a nu
m be r of
SC O R ’s
lim it at io ns
(c o n ti n u ed
)
Table I.
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Analysis of SCOR’s approach
SC O R
ve rs io n
R es ea rc he r
T op ic an d fi nd
in gs
8. 0
P ol uh
a (2 00 7)
Id en ti fi ed /s ta ti st ic al ly
pr ov ed
th e ne ed
to in cl ud
e m ar ke ti ng
/s al es
pr oc es se s; m at er ia l/i nf or m at io n fl ow
s be tw
ee n
cu st om
er s an d su pp
lie rs ;a nd
el ec tr on ic pu
rc ha si ng
pr oc es se s w it hi n th e pe rf or m an ce -r el at ed
te rm
s of
SC O R 8. 0
T he er an up
ha tt an a an d
T an g (2 00 7)
D em
on st ra te d th e co m pl em
en ta ry
na tu re
of m od el s of
SC O R an d th e C ha n an d Q im
od el th at
pr ov id ed
a us er -f ri en dl y
en ha nc ed
pe rf or m an ce
m ea su re m en t m od el
9. 0
L i et al .( 20 11 )
E xt en de d SC
O R ’s fi ve
de ci si on
ar ea s by
in te gr at in g qu
al it y as su ra nc e m ea su re s. Sh
ow ed
th at
ea ch
de ci si on
ar ea
po si ti ve ly
im pa ct ed
cu st om
er -f ac in g SC
qu al it y pe rf or m an ce
an d in te rn al -f ac in g fi rm
le ve l bu
si ne ss
pe rf or m an ce
Sa kk
a et al .( 20 11 )
H ig hl ig ht ed
th e im
po rt an ce
of kn
ow le dg
e fo rm
al iz at io n in
ac hi ev in g st ra te gi c al ig nm
en t an d su gg
es te d an
on to lo gi ca l
re pr es en ta ti on
of th e SC
O R m od el
T rk m an
et al .( 20 10 )
D em
on st ra te d a st at is ti ca lly
si gn
if ic an t re la ti on sh ip
be tw
ee n an al yt ic al
ca pa bi lit ie s an d pe rf or m an ce
by us in g
in fo rm
at io n sy st em
su pp
or t an d bu
si ne ss
pr oc es s or ie nt at io n as
m od er at or s
X ia o et al .( 20 09 )
D es ig ne d an
op ti m iz at io n ap pr oa ch
to a cy cl e qu
al it y ch ai n op er at io ns
re fe re nc e m od el th at
w as
ba se d on
an im
pr ov ed
SC O R m od el th at
re al iz ed
cy cl e op er at io n th ro ug
h re ve rs e m an uf ac tu ri ng
10 .0
Z ho u et al .( 20 11 )
U si ng
su rv ey
da ta
fr om
12 5 N or th
A m er ic an
m an uf ac tu ri ng
fi rm
s, em
pi ri ca lly
va lid
at ed
in te gr at io n be tw
ee n th e P la n,
So ur ce ,M
ak e an d D el iv er
hi gh
le ve l pr oc es s ty pe s in
SC O R
M ed in i an d B ou re y (2 01 2)
P ro po se d a m et ho do lo gy
ba se d on
SC O R th at ca n be
us ed
to gu
id e bo th
st ra te gi c an d op er at io na ll ev el de ci si on
m ak in g
in en te rp ri ze
ar ch it ec tu re
pr oj ec ts
(? )c
A rn s et al .( 20 02 )
P ro po se d a m od el -b as ed
an al ys is of
SC s vi a qu
eu in g ne tw
or ks
an d P et ri ne t an al ys is to
es ti m at e SC
pe rf or m an ce
m ea su re s
B ol st or ff (2 00 2)
D em
on st ra te d th e va lu e of
in te gr at in g SC
O R w it h Si x Si gm
a’ s D ef in e, M ea su re ,A
na ly se ,I m pr ov e, C on tr ol
m et ho do lo gy
B ol st or ff (2 00 5)
C on si de re d ho w SC
O R -e na bl ed
va lu e ch ai ns
ar e re pr es en te d. Id en ti fi ed
re se ar ch
ga ps
in SC
O R i.e ., la ck
of co ve ra ge
of Sa le s, M ar ke ti ng
an d so m e as pe ct s of
Se rv ic e pr oc es se s
R ei ch ar dt
an d N ic ho ls
(2 00 3)
C on si de re d ho w
SC O R ca n as si st
in tr an sl at in g th e IS O re qu
ir em
en ts
in to
pr ac ti ca l re co m m en da ti on s
N o te s:
a C om
m en t up
on th e op in io ns
of ot he r re se ar ch er s ra th er
th an
pr ov id e di re ct re fe re nc es
to SC
O R .b W hi ls t th e au th or s re fe r to
SC O R 7. 0, th ey
re fe re nc e
SC C (2 00 1) ,w
hi ch
re la te s to
SC O R 5. 0 no t 7. 0.
c T he se
pa pe rs
di sc us s SC
O R bu
t do
no t in cl ud
e re fe re nc e to
a pa rt ic ul ar
ve rs io n
Table I.
1254
IJOPM 34,10
approach to SCRM gives urgency to our analysis of SCOR’s SCRM process, performance (attributes and metrics), best practices and people (skills) issues.
3. Research approach Using critical analysis and a two-phased approach, we analysed the coverage and integration of SCRM practices and corresponding risk related metrics in SCOR 10.0. Phase 1 was positivist and entailed document analysis of SCOR 10.0 wherein we sought to determine restrictions, oppositions or contradictions (Myers, 1997). This facilitated our ontological view of SCRM in SCOR. In Phase 2, we adopted an interpretivist perspective (Walsham, 2006) wherein inductive reasoning allowed critical reflection. This led to the suggestion of amendments.
Throughout this analysis we were conscious of the potential for bias (Yin, 2008). In the positivist component, each author independently mapped SCRM in SCOR. This independence was important in addressing concerns about bias (Pare, 2004; Trochim, 2006) as we derived our summative position about the status of SCRM in SCOR 10.0. Acknowledging the inherent risk of subjectivity in the interpretivist inductive reasoning phase (Walsham, 2006), we again independently documented understandings. Here our use of underlying theoretical/modelling constructs and our prior literature review supported both the understanding gleaned and internal validity in our findings (Eisenhardt, 1989). Finally we triangulated our findings by comparing results, exploring any inferences and the extent to which we could substantiate our conclusions before discussing their implications. Table II below summarizes our analysis.
4. Analysis of SCRM in SCOR 10.0 and suggested improvements For conciseness purposes our analysis of SCRM in SCOR 10.0 is presented below in tabular format (see Table II). In column 1, the component, we break our analysis into four blocks, which represent SCOR’s four components (processes, performance (attributes and metrics), best practices and people (skills)). Given we often have several concerns with the current operationalization of each component, the points within each are indexed. For example P-1 relates to the first point concerning processes, P-2 to the second point, and so on.
Our analysis of each point (indexed item) is broken into three parts: Status, Issue(s) and supporting evidence. Status refers to the way in which SCOR deals with the point at hand. It serves as a context for the problem(s) discussed under the heading “Issue(s)”. Issues principally arise because of inconsistencies between the way SCOR deals with the point and the way in which it should be correctly decomposed. We link our discussion here to the general principles of process modelling and best practice, which we clarify through the use of “supporting evidence”.
In the fourth column, we detail our suggested improvements for each of the indexed points. These improvements relate to the actions that are necessary to achieve internal consistency or to conform to good practice in the realm of SCRM. In Figure 5 (which is presented immediately following Table II), using the general principles of hierarchical decomposition espoused by Simon (1996, which are outlined in the Introduction), we enact these points to bring the SCRM component of SCOR 10.0 into line with this. To assist with clarity we cross-reference Figure 5 to the indexes detailed in Table II.
5. Discussion Some issues with the conceptualization of risk and risk management in SCOR relate to their definitions. ISO 31000:2009 is strategic in defining risk “in terms of the effect of
1255
Analysis of SCOR’s approach
C om
po ne nt
In de x
A na ly si s an d di sc us si on
of SC
O R 10 .0 ’s co ve ra ge
an d in te gr at io n of
SC R M
Su gg
es te d im
pr ov em
en t
P ro ce ss es
P -1
S ta tu s: T he
co nc ep t of
ri sk
is fe at ur ed
at L ev el 1 of
SC O R un
iq ue ly
th ro ug
h th e
in tr od uc ti on
of th e V A R ri sk
m et ri c co de d as
A G 1. 4 (s ee
F ig ur e 4) .I n th e m od el ,
ri sk
is co nc ep tu al iz ed
as a di sc re te ev en t, ch ar ac te ri ze d ac co rd in g to
pr ob ab ili ty
an d im
pa ct .B
y la rg el y ad op ti ng
th e tr ad it io na lr is k m an ag em
en t lif ec yc le ,S C O R
in co rp or at es
el em
en ts
of th e re du
nd an t A us tr al ia n/ N ew
Z ea la nd
St an da rd
A S/
N Z S 43 60 :2 00 4a
C on si st en t w it h th e pr in ci pl es
of E nt er pr iz e R is k M an
ag em
en t (E R M )
sa nc ti on ed
by S C O R an
d th e IS O pe rs pe ct iv es
of ri sk
(I S O 31
00 0: 20
09 ),
S C R M
sh ou ld be
re po si ti on ed
to L ev el 1 (t he
st ra te gi c or ie nt ed
le ve l) un
de r
th e pr oc es s ty pe
“ M an
ag e [S C ] R is k”
(s ee
F ig ur e 5) .S
im ila r to
th e
P la nn
in g pr oc es s ty pe , w e su gg es t th at
th e re po si ti on ed
S C R M
pr oc es s
ty pe
be al ig ne d at
th e st ra te gi c le ve lw
it h th e ot he r fi ve
ty pe s of
S C O R
pr oc es se s. T hi s w ou ld
as su re
vi si bi lit y of
ri sk
so ur ce s ac ro ss
th e w ho le
S C O R pr oc es s hi er ar ch y an
d lin k ap pr op ri at e S C re so ur ce s th at
ar e
ne ce ss ar y to
m it ig at e th es e ri sk s. M or eo ve r, re po si ti on in g S C R M
to th e
st ra te gi c le ve lw
ill al lo w lo w er
le ve ls to
en co m pa ss
pr oc es s el em
en ts
cu rr en tly
po si ti on ed
at L ev el 3 (s ee
M -2 )
Is su es :( 1) SC
R M
is in tr od uc ed
at L ev el 3 as
a se qu
en ce
of di st in ct “E
na bl e”
ty pe
pr oc es s el em
en ts ,s o it is un
cl ea r ho w
ri sk
re la te s to
th e ob je ct iv es
(m et ri cs )
dr iv in g SC
O R pr oc es se s. (2 ) SC
O R is no t al ig ne d w it h th e ne w
IS O 31 00 0: 20 09
(s ee
th e D is cu ss io n se ct io n be lo w )
S up po rt in g ev id en ce : G iv en
re pe at ed
op er at io na l lo ss es
re su lt in g fr om
fa ilu
re in
in te rn al
SC s (F re de nd
al l et al ., 20 09 ), la ck
of un
de rs ta nd
in g ab ou t al ig nm
en t
be tw
ee n th e co rp or at e ri sk
pr of ile
(in cl ud
in g SC
ri sk s) an d co rp or at e ob je ct iv es
(C O SO
,2 00 4) m ay
le ad
to m aj or
di sr up
ti on s in th e ev en to fS
C cr iz es
(N ei ge r et al .,
20 09 )
P -2
S ta tu s: C om
pa re d to
SC O R ’s no n SC
R M
pr oc es s el em
en ts ,t he
cu rr en t L ev el 3
ri sk
re la te d pr oc es s el em
en ts (i. e. “M
an ag e [S C ] P la n R is k sE P .9 ”) ar e m or e ak in
to L ev el 2 pr oc es s ca te go ri es
(c f. F ig ur e 2)
R ep os it io n th e hi er ar ch y of
S C O R ’s S C ri sk
m an
ag em
en t pr oc es s ty pe s,
ca te go ri es
an d el em
en ts i.e ., m ov e L ev el 3 pr oc es s el em
en ts to
L ev el 2 as
pr oc es s ca te go ri es
(s ee
F ig ur e 5)
Is su e: A t L ev el 3 SC
O R so le ly
di ff er en ti at es
ri sk s ac co rd in g to
th e fi ve
pr oc es s
de fi ni ti on s (P la n/ So ur ce /M
ak e/ D el iv er /R et ur n) .T
hi s fa ils
to pr ov id e gu
id an ce
on th e ri sk
m an ag em
en t ac ti vi ti es
th at
ef fe ct iv el y ad dr es s th e ri sk s as so ci at ed
w it h
co re
pr oc es s ty pe s
S up po rt in g ev id en ce :L
ew is (2 00 3)
sh ow
ed th at
ri sk
co nt ro ls sh ou ld
co m bi ne
pr ev en ti on ,m
it ig at io n an d re co ve ry
el em
en ts
P -3
S ta tu s: SC
O R pr ov id es
de ta ile d st ep s re ga rd in g th e ri sk
m an ag em
en t lif ec yc le ,
bu t th es e ap pe ar
in th e B es t P ra ct ic es
co m po ne nt
ra th er
th an
in L ev el 3 pr oc es s
el em
en t de fi ni ti on s
R ep os it io n de ta ile d st ep s re la te d to th e ri sk
m an
ag em
en t lif ec yc le fr om
th e
B es t P ra ct ic es
co m po ne nt
to L ev el 3 pr oc es s el em
en t de fi ni ti on s (s ee
F ig ur e 5) .T
hi s ch an
ge w ou ld as si st w it h pr oc es s re pr es en ta ti on
an d be tt er
un de rs ta nd
in g of
th e ri sk
pr op ag at io n m ec ha ni sm
s in
S C s. P ro ce du
ra lly
th is su gg es te d en ha nc em
en t en ab le s in ve st ig at io n of
S C ri sk
ro ot ca us es
– a co re
re qu
ir em
en t of
S C O R pr oj ec ts (S C C , 20
10 )
Is su e: Im
pl ic at io ns
ar is e ab ou t cl ar it y re ga rd in g lo gi ca l as so ci at io ns
be tw
ee n
ac ti vi ti es
in vo lv ed
in th e ri sk
m an ag em
en t pr oc es s an d th e ca us es
an d
co ns eq ue nc es
of ri sk
S up po rt in g ev id en ce :I n IS O 31 00 0: 20 09 ,C O SO
(2 00 4) an d th e SC
R M
lit er at ur e (i. e.
R it ch ie an d B ri nd
le y,
20 07 a, b;
M ul la i, 20 08 ), pr oc es se s ar e de co m po se d
ac co rd in g to
th e ri sk
m an ag em
en t lif ec yc le st ep s su ch
as “i de nt if y [S C ] pl an
ni ng
ri sk ” an d “a na
ly ze
[S C ] pl an
ni ng
ri sk ”. A ls o, L ew
is (2 00 3)
re fl ec ts
th e ne ed
to ex pl ic it ly
re pr es en t op er at io na l ri sk
ca us es ,c on se qu
en ce s an d co nt ro ls
(c o n ti n u ed
)
Table II. Analysis of SCOR 10.0’s coverage and integration of SCRM and suggested improvements
1256
IJOPM 34,10
Table II.
C om
po ne nt
In de x
A na ly si s an d di sc us si on
of SC
O R 10 .0 ’s co ve ra ge
an d in te gr at io n of
SC R M
Su gg
es te d im
pr ov em
en t
P er fo rm
an ce
(a tt ri bu
te s an d
m et ri cs )
M -1
S ta tu s: SC
ri sk
(s ee
P -1 ) is re pr es en te d at
SC O R ’s st ra te gi c le ve l vi a a si ng
le m et ri c O ve ra ll V A R (A G .1 .4 )b (s ee
F ig ur e 4) .V
A R is ch ar ac te ri ze d in
th e m et ri cs
co m po ne nt
as “t he
pr ob ab ili ty
of no n- ad he re nc e to m et ri cs
va lu e (e xp
ec te d va lu e)
ba se d on
hi st or ic al
da ta ” (S C C ,2 01 0, p.
2. 3. 7)
i.e ., a re tr os pe ct iv e vi ew
of ri sk
G iv en
ra pi d gl ob al iz at io n an
d te ch no lo gi ca lc ha ng e, so le re lia nc e on
pa st
kn ow
le dg e is a th re at .C
on se qu
en tly
S C O R re qu
ir es
ad di ti on al ri sk
m et ri cs
th at
al lo w en vi si on in g of
un pr ec ed en te d fu tu re
ev en ts – th at
is V A R sh ou ld be
su pp le m en te d w it h ad di ti on al ri sk
re la te d m et ri cs in
or de r
to ac hi ev e m or e co m pr eh en si ve
un de rs ta nd
in g of
S C ri sk
ex po su re s to
su pp ly an
d/ or
de m an
d ri sk .T
he se
su pp le m en ta ry
m ea su re s in cl ud
e: E xp ec te d S ho rt fa ll (A ce rb i an
d T as ch e, 20
02 ;Y
am ai
an d Y os hi ba ,
20 05
), S pe ct ra lR
is k m ea su re s (A ce rb i, 20 02 ), D is to rt io n R is k m ea su re s
(A ce rb i, 20
02 ), an
d th e L ef t- ta il m ea su re
(W u an
d X ia o, 20
02 ). A no th er
so lu ti on
is in cl us io n of
co nt ex t- re la te d m ea su re s of
ri sk
th at
ar e cl os el y
as so ci at ed
w it h th e ac ti vi ty -b as ed
ob je ct iv es
of S C pr oc es se s (N ei ge r et al .,
20 09
;R ot ar u et al ., 20
11 )
Is su es :( 1)
T hi s re pr es en ta ti on
is in co ns is te nt
w it h th e re co m m en de d us e of
m ul ti pl e pr oa ct iv e m et ri cs
(G au de nz i an d B or gh
es i, 20 06 ;R
it ch ie an d B ri nd
le y,
20 07 a, b) .( 2)
P ro bl em
s w it h V A R ar is e w it h ch an ge s in
op er at io na l sy st em
s be ca us e hi st or ic al
ri sk
ev en t da ta
ea si ly
be co m es
ou td at ed
(D av ie s et al ., 20 06 ;
H ol m es ,2 00 3; Sc an di zz o, 20 05 ). T hu
s, th e te m po ra l ha nd
lin g of
ri sk
ac ro ss
SC O R ’s pr oc es se s, m et ri cs
an d be st
pr ac ti ce s re qu
ir es
im pr ov em
en t. (3 )
Su ba dd
it iv it y/ di ve rs if ic at io n of
V A R is re po rt ed
to be
pr ob le m at ic (G ou ri er
et al .,
20 09 ), w hi ch
im pl ie s th at
th e ag gr eg at io n of
co m pa rt m en ta liz ed
(i. e.
di sa gg
re ga te d V A R -P la n, V A R -S ou rc e, V A R -M
ak e et c. – se e F ig ur e 4) m ea su re s
of ri sk
as so ci at ed
w it h di st in ct
SC pr oc es se s pr od uc es
an un
re al is ti c (o ft en ,t oo
op ti m is ti c) as se ss m en t of
th e ri sk
ex po su re s as so ci at ed
w it h th e en ti re
SC .I n th e
SC R M
lit er at ur e th e pr ob le m
of re co nc ili at io n of
ri sk
m et ri cs
w as
ra is ed
in R it ch ie an d B ri nd
le y (2 00 7b ), w hi le P fo hl
et al .( 20 11 )p
ro vi de d a m et ho do lo gi ca l
ap pr oa ch
to ad dr es s th e is su e of
in te rd ep en de nc y am
on g ri sk s an d th er ef or e
lim it ed
su ba dd
it iv it y/ di ve rs if ic at io n of
ri sk s
S up po rt in g ev id en ce :( 1)
V A R is ca lc ul at ed
us in g a la rg e da ta ba se
of hi st or ic al
ev en ts ,w
hi ch
ca n po te nt ia lly
le ad
to un
de rs ta te m en t of
fu tu re
ri sk
(if th e da ta
re fl ec ts
a st ab le en vi ro nm
en t) or
ov er st at em
en t (if
th e da ta
re fl ec ts
vo la ti lit y)
(S ki nt zi et al ., 20 05 ). (2 ) D if fe re nt
as su m pt io ns
ab ou t re tu rn
di st ri bu
ti on s an d
di ff er en t hi st or ic al
ti m e pe ri od s ca n yi el d ve ry
di ff er en t va lu es
fo r V A R (B ed er ,
19 95 ). (3 ) R is k ne ed s co ns id er at io n as
an in tr in si c va ri ab le in
th e ex is ti ng
pe rf or m an ce
m et ri cs
(C ai
et al ., 20 09 ) as so ci at ed
w it h or ga ni za ti on al
bu si ne ss
pr oc es se s (N ei ge r et al ., 20 09 ;R
ot ar u et al ., 20 11 ;S
ca nd
iz zo ,2 00 5; D av ie s et al .,
20 06 ) to
en su re
th at
th e re su lt in g m et ri cs
re al is ti ca lly
re fl ec t a fi rm
or a SC
’s ex po su re
to ri sk
M -2
S ta tu s: V A R (A G .1 .4 ) la ck s di re ct
as so ci at io n w it h an y L ev el 1 P ro ce ss
T yp
e (c f. F ig ur e 2)
S C R M ’s re po si ti on in g to
L ev el 1 (s ee
P -1
an d (F ig ur e 5) .p
er m it s a
br oa de r ra ng
e of
ri sk
re la te d m et ri cs
to be
de fi ne d th at
m ay
su bs eq ue nt ly
be de co m po se d to
pr oc es s ty pe s
Is su e: T he
ty pi ca ls yn
ch ro no us
de co m po si ti on
of ri sk
m et ri cs
to pr oc es se s, w hi ch
ap pl ie s to
no n- ri sk
SC m et ri cs
(S C C ,2 01 0) ,i s no t po ss ib le fo r V A R .T
hi s
un de rm
in es
SC O R ’s hi er ar ch ic al
re pr es en ta ti on
of st ru ct ur al
el em
en ts ,w
hi ch
is it s fu nd
am en ta l st re ng
th
(c o n ti n u ed
)
1257
Analysis of SCOR’s approach
Table II.
C om
po ne nt
In de x
A na ly si s an d di sc us si on
of SC
O R 10 .0 ’s co ve ra ge
an d in te gr at io n of
SC R M
Su gg
es te d im
pr ov em
en t
S up po rt in g ev id en ce :( 1)
B ro ad en in g ho w
ri sk
is ca pt ur ed
at L ev el 1 m ea ns
th at
ri sk
ca n be
be tt er
pr ed ic te d us in g a br oa de r ra ng
e of
m et ri cs ,t he
im pa ct
ca re fu lly
ev al ua te d,
an d in pu
t fr om
a w id er
gr ou p of
st ak eh ol de rs
co ns id er ed
(G au de nz i an d B or gh
es i, 20 06 ;R
it ch ie an d B ri nd
le y,
20 07 a, b) .( 2)
In co rp or at io n
of a br oa de r ra ng
e of
ri sk
m et ri cs
w ill en ha nc e ri sk
vi si bi lit y w it hi n an d ac ro ss
SC pr oc es se s (J üt tn er ,2 00 5; H al lik as
an d V ir ol ai ne n, 20 04 ;C
hr is to ph
er an d L ee ,2 00 4)
M -3
S ta tu s: B y re la ti ng
th e on ly L ev el 1 ri sk
m et ri c (V A R A G .1 .4 .) to
th e pe rf or m an ce
at tr ib ut e “[ SC
] A gi lit y” ,t he
SC C om
it s re fe re nc es
to at tr ib ut es
lik e R el ia bi lit y,
R es po ns iv en es s, C os t an d A ss et s
In st it ut e L ev el 1 ri sk
re la te d m et ri cs
lin ke d to
th e at tr ib ut es
R el ia bi lit y,
R es po ns iv en es s, C os t an
d A ss et M an
ag em
en t
Is su e: A
w id er
vi ew
of th e po te nt ia l ef fe ct s of
ri sk
ex po su re s is re qu
ir ed .
S up po rt in g ev id en ce : P ri or
re se ar ch
su pp
or ts
a w id er
pe rs pe ct iv e re ga rd in g ri sk
ex po su re s (e .g .G
au de nz i an d B or gh
es i, 20 06 ;N
ag ur ne y et al ., 20 05 ;R
ao an d
G ol ds by
,2 00 9; P ec k,
20 06 )
M -4
S ta tu s: T he
SC C (2 01 0)
su gg
es ts
a be st
pr ac ti ce ,R
is k M an ag em
en t P ro gr am
s C oo rd in at io n w it h P ar tn er s, bu
t is si le nt
ab ou t m et ri cs
th at
w ou ld
ta ng
ib ly
as se ss
SC pa rt ne rs ’ ef fo rt s to
co lla bo ra ti ve ly
m an ag e ri sk
ex po su re s
In tr od uc e, in
A gi lit y an
d ot he r pe rf or m an
ce at tr ib ut es , ne w in te rn al an
d ex te rn al S C in te gr at io n m et ri cs
to su pp le m en t V A R so
th at
co lla bo ra ti ve
ri sk
m an
ag em
en t m ay
be as se ss ed
Is su e: A dd
it io na l ri sk
re la te d m et ri cs
re ga rd in g th e de gr ee
of in te rn al
an d
ex te rn al
SC in te gr at io n ar e re qu
ir ed
w it hi n A gi lit y an d ot he r pe rf or m an ce
at tr ib ut es
S up po rt in g ev id en ce :S
C A gi lit y,
as w el l as
ot he r pe rf or m an ce
at tr ib ut es ,c an
be im
pa ct ed
by in te rn al
in te gr at io n,
ex te rn al
in te gr at io n w it h ke y su pp
lie rs
an d
cu st om
er s, an d ex te rn al fl ex ib ili ty
(B ra un
sc he id el an d Su
re sh ,2 00 9; H al lik
as an d
V ir ol ai ne n,
20 04 )
M -5
S ta tu s: T he
lin ki ng
of L ev el 2 ri sk
m et ri cs
w it h L ev el 3 pr oc es s el em
en ts do es
no t
co rr es po nd
to th e pr oc es s/ m et ri cs
hi er ar ch ic al
de co m po si ti on
in SC
O R
R em
ov e “ cr os s- lin ks ” be tw ee n L ev el 2 m et ri cs
an d L ev el 3 pr oc es s
el em
en ts .O
ne op ti on
is to in co rp or at e be st pr ac ti ce s as
a se qu
en ce of
L ev el
3 pr oc es s el em
en ts (s ee
P -2
ab ov e) .T
hi s fa ci lit at es
cl ar if ic at io n an
d/ or
re de si gn
of L ev el 2 ri sk
m et ri cs so
th ey
re la te to L ev el 2 pr oc es s ca te go ri es ,
an d ad dr es se s al ig nm
en t of
L ev el 3 m et ri cs
w it h L ev el 3 S C R M
pr oc es s
el em
en ts
Is su e: F or
ex am
pl e, L ev el 2 m et ri cs
su ch
as “V
al ue
at R is k (P la n)
(A G .2 .1 5) ” ar e
lin ke d to
L ev el 3 pr oc es s el em
en ts
lik e “M
an ag e [S C ] P la n R is k (s E P .9 )” ,r at he r
th an
to L ev el 2 pr oc es s ca te go ri es .T
hi s ra is es
qu es ti on s ab ou t SC
O R ’s co re
st re ng
th in cl ud
in g w he th er
“p ro ce ss
pr ob le m
di sc ov er y ” ca n “d et er m in e w he re
ro ot
ca us es
[o f ri sk ] ar e”
(S C C ,2 01 0, p.
1. 2. 8)
S up po rt in g ev id en ce :S
uc h m is al ig nm
en t is co nt ra ry
to B ol st or ff an d
R os en ba um
’s (2 00 7)
fi nd
in g re ga rd in g th e ba si c pr oc es se s/ m et ri cs
hi er ar ch y in
SC O R
B es t pr ac ti ce s
B P -1
S ta tu s: SC
R M
is an
um br el la
be st
pr ac ti ce
in SC
O R th at
co nt ai ns
th re e ph
as es :
SC R is k Id en ti fi ca ti on ,S
C R is k A ss es sm
en t an d SC
R is k M it ig at io n (S C C ,2 01 0,
p. 4. 3. 1)
B y re po si ti on in g S C R M
to L ev el 1 (s ee
P -1 ), cu rr en t S C R M
pr oc es se s ca n
be po si ti on ed
to L ev el 2 (i ns te ad
of L ev el 3) .A
s sh ow
n in
F ig ur e 5,
th e
re m ai ni ng
S C R M
be st pr ac ti ce s th en
be co m e L ev el 3 pr oc es s el em
en ts
(c o n ti n u ed
)
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IJOPM 34,10
Table II.
C om
po ne nt
In de x
A na ly si s an d di sc us si on
of SC
O R 10 .0 ’s co ve ra ge
an d in te gr at io n of
SC R M
Su gg
es te d im
pr ov em
en t
Is su e: T he se
ca n be
de du
ce d as
be in g su bo rd in at e to
SC R M ,b
ut no
ex pl ic it
hi er ar ch y is pr ov id ed .A
lt ho ug
h SC
O R is ex pl ic it ab ou t no t co di fy in g be st
pr ac ti ce s (S C C ,2 01 0, p. 1. 2. 7) ,t he
ab se nc e of
a pr oc es s hi er ar ch y fo r SC
R M
be st
pr ac ti ce s cr ea te s di ff ic ul ti es
w he n in te rp re ti ng
th e or de r of
co rr es po nd
en ce
re ga rd in g be st
pr ac ti ce s an d th e un
de rl yi ng
SC R M
pr oc es s. T hi s co nf lic ts
w it h
th e “r ef er en ce
m od el ” na tu re
of SC
O R an d as se ss m en t of
th e su cc es s of
a ch os en
st ra te gy
S up po rt in g ev id en ce : P ri or
re se ar ch
de m on st ra te s be ne fi ts
fr om
be tt er
in te gr at io n of
th e SC
R M
pr oc es s (M
ul la i, 20 08 ;S
in ha
et al ., 20 04 ;R
it ch ie an d
B ri nd
le y,
20 07 a, b)
B P -2
S ta tu s: SC
O R ch ar ac te ri ze s SC
R M
be st pr ac ti ce s as
“c ur re nt ” (S C C ,2 01 0, p. 4. i.1 ).
S C O R ’s be st pr ac ti ce s sh ou ld
be up da te d to
re fle ct cu rr en t ri sk
m an
ag em
en t pr ac ti ce
i.e ., th ro ug h in te gr at io n of
th e co re
pr in ci pl es
of E R M
Is su e: SC
O R do es
do no t re fl ec t cu rr en t ad va nc es
in ri sk
m an ag em
en t an d m or e
sp ec if ic al ly
SC R M .F
ur th er
it s sp ec if ic at io n of
ob je ct iv es
(s tr at eg ic an d
op er at io na l) co nc er ni ng
pr oa ct iv e ri sk
id en ti fi ca ti on
an d as se ss m en t is w ea k
S up po rt in g ev id en ce : D es pi te
cl ai m in g th at
SC R M
“s ho ul d be
in te gr at ed
in an
en te rp ri ze
ri sk
m an ag em
en t fr am
ew or k ” (S C C ,2 01 0, p. 4. 3. 2) ,t he
co re
pr in ci pl es
of E R M
(C O SO
,2 00 4)
ar e no t in co rp or at ed
P eo pl e (s ki lls )
P P L -
1 S ta tu s: SC
O R as so ci at es
fi ve
sk ill s w it h SC
ri sk
m an ag em
en t (R is k an d
E xc ep ti on
M an ag em
en t (H S. 01 24 ); R is k A ss es sm
en t (H S. 01 25 ); R is k
Id en ti fi ca ti on
(H S. 01 26 ); R is k M it ig at io n (H S. 01 27 ); an d R is k R es po ns e P la nn
in g
(H S. 01 28 )).
So m e sk ill s (R is k A ss es sm
en t an d Id en ti fi ca ti on ,f or
in st an ce s)
co rr es po nd
to SC
R M
be st
pr ac ti ce s w hi ch ,a s pr ev io us ly
di sc us se d,
sh ou ld
be tr an sf or m ed
in to
L ev el 3 pr oc es s el em
en ts
(w it h as so ci at ed
sk ill s)
S C O R ’s ri sk
re la te d sk ill s ne ed
to m or e ex te ns iv el y ad dr es s so ci al
di m en si on s an
d al la sp ec ts of
th e S C R M
pr oc es s hi er ar ch y
Is su e: T he se
sk ill s do
no t ye t co ve r al l as pe ct s of
th e ri sk
m an ag em
en t pr oc es s.
F or
ex am
pl e, as pe ct s lik
e ri sk
co m m un
ic at io n (“ C ri si s C om
m un
ic at io ns
P la nn
in g” ,“ R is k M an
ag em
en t P ro gr am
s C oo rd in at io n w it h P ar tn er s” ) ar e no t
co ve re d
S up po rt in g ev id en ce : SC
ri sk s ar is e fr om
bo th
te ch ni ca l an d so ci al
di m en si on s
(R ao
an d G ol ds by
,2 00 9; T an g,
20 06 b;
K ha n an d B ur ne s, 20 07 )
N o te s:
a T hi s st an da rd
ha s al re ad y be en
su pe rs ed ed
by IS O 31 00 0: 20 09 .b T hi s m et ri c w as
re pr es en te d at
L ev el 2 in SC
O R 9. 0, bu
t w as
ch an ge d in SC
O R 10 .0 to
L ev el 1, w hi ch
de m on st ra te s a po si ti ve
at te m pt
to co ns id er
ri sk
at th e st ra te gi c le ve l of
th e va lu e hi er ar ch y.
H ow
ev er ,c on si st en cy
w as
no t m ai nt ai ne d as
th e
ti tl es
“V al ue
at R is k”
(s ee
T ab le II ) an d “O
ve ra ll V al ue -A t- R is k ” w er e co m bi ne d.
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Analysis of SCOR’s approach
uncertainties on objectives”. Similarly the ERM perspective advocated by COSO (2004) emphasizes the strategic nature of the risk management process. In contrast, SCOR takes a transactional approach to conceptualizing risk in SC processes, defining risk management as “[i]mproving (mitigating) the risks of an undesired event taking place, limiting the impact of such an event and improving the ability to recover from the
C u st
o m
e rs
Your CompanySupplier Supplier’s Supplier
Customer Customer’s Customer
Source Make Deliver
Return Return
Plan
Source Make Deliver
Return Return
Plan
Source Make Deliver
Return Return
Plan
Return
Deliver
Return
Sourse
S u p p lie
rs
Plan process categories
Level 1
Level 2
(Process Types)
(Process Categories)
H ie
ra rc
h ic
a l D
e co
m p o si
tio n F
lo w
Manage SC risk
Manage SC Risk
Manage SC Risk
Manage SC Risk process categories
Manage SC Source Risk
Manage SC Plan Risk
Manage SC Deliver Risk
Manage SC Make Risk
Manage SC Return Risk
Return process categories
Make process categories Deliver
process categories
Level 3 (Process Elements)
Plan Return
Enable SC Risk Management
Manage SC Source Risk:
Issue P-1
Issue P-1
Issue P-1
Issue P-3
Issue P-2
Identify SC Source Risk
Assess SC Source Risk
Mitigate SC Source Risk
M o n ito
r S
C S
o u rc
e R
is k
C o m
m u n ic
a te
S C
S o u rc
e R
is k
C o o rd
in a te
S C
S o u rc
e
R is
k M
a n a g e m
e n t
P ro
g ra
m s
w ith
P
a rt
n e
rs
Issue BP-1
Make Deliver
Internal or External Internal or External
Figure 5. Suggested hierarchical decomposition of SCOR’s Manage SC Risk process (with cross-references to the indexes contained in Table II)
1260
IJOPM 34,10
event” (SCC, 2010, p. 1.2.7). This representation of SCRM as a transactional (Level 3) rather than strategic (Level 1) process creates integrity issues, including inconsistencies in the hierarchical representation of risk-related attributes and metrics, best practices and skills (see Table II).
Given advances in the field of ERM we suggest that the hierarchy of SCOR’s “Manage SC Risk” process category and related elements be repositioned in order to reflect the nature of SCRM as “a process, effected by an entity’s board of directors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risks to be within its risk appetite” (COSO, 2004, p. 2). This vision is reflected in the decomposed SCOR “Manage SC Risk” process presented in Figure 5.
Such hierarchical repositioning of SC risk would address a number of significant issues. For example, alignment of the SCRM process type at Level 1 with the other five process types would improve visibility of SC risk sources across all levels of the SCOR process hierarchy thereby facilitating a “supply chain-wide” risk management perspective in SC processes. Moving the process elements currently positioned at Level 3 to Level 2 (see issues P-2 and P-3) would provide improved guidance on the SCRM activities that address SC risks linked to core process types. Furthermore it would facilitate better visualization of the logically related SCRM process steps as Level 3 process elements (see Figure 5), rather than discretely defining them in the Best Practices component of SCOR without considering the implicit risk management process logic.
Furthermore, analysis of issue M-1 (see Table II) shows SCOR’s overreliance on a single risk measure (VAR) with its reactive, not proactive, view of risk. SCOR acknowledges that VAR relates to the probability of non-adherence to expected value and is calculated using available historical data. Herein the use of VAR with its retrospective assessment of risk as the sole metric means that SCOR only allows evaluation of known potential adverse events within business processes. Such reliance on historical loss data assumes that future events are determinable based on past data, but the examples of SC disruptions cited in our introductory section negate this.
In the Finance industry VAR has been criticized for not being a coherent risk measure, i.e. it lacks an axiomatic foundation that includes the criterion of subadditivity/ diversification raised earlier. Herein regulatory bodies have reviewed the monopoly that VAR measurements have had in calculating the regulatory capital necessary to cover potential exposures to risk (Basel Committee on Banking Supervision (BCBS), 2011). As a result the use of more coherent and sophisticated measures of risk (see Table II, Issue M-1, Column 4) have been advocated since the early 2000s. Thus, it is concerning that SCOR, whilst eclectic in borrowing best practices for SCRM from different research domains, including Engineering and Finance, promotes adoption of VAR as the only SC risk metric.
Thus, without solving problems with the hierarchical representation of processes (Table II, indexes P-1 to P-3), the problems with the hierarchical decomposition of metrics (see Table II, indexes M-1 to M-5) cannot be solved. The suggested hierarchical repositioning of SCOR SCRM process elements and metrics will enable systematic investigation of the root causes of SC risks (see Table II, index M-2) and will confer benefits including:
(1) alignment of the hierarchical nature of risk metrics and corresponding processes (i.e. Neiger et al., 2009; Scandizzo, 2005; Anders and Sandstedt, 2003);
(2) decomposition/aggregation of SC risks according to the hierarchal SC processes. This will enhance SC risk visibility and consequently improve the effectiveness of the SCRM process (i.e. Neiger et al., 2009);
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Analysis of SCOR’s approach
(3) clearer categorization of risk causes, adverse events and consequences (Scandizzo, 2005) thereby allowing better understanding of the risk propaga- tion mechanisms in SCs (i.e. Lewis, 2003);
(4) more realistic design of risk scenarios when scenario-based risk analysis approaches are adopted (Olson and Wu, 2011; Scandizzo, 2006); and
(5) the ability to devise a database of potential risk events and a tight “cause(s)- effect(s)-consequence(s)” view of operational risk (Basel Committee on Banking Supervision (BCBS), 2004).
The suggested hierarchical repositioning would ensure consistency in the SCRM best practices (see Figure 5, issue BP-1) that correspond to the “Manage SC Risk” process elements, and facilitate better integration of SCRM Best Practices (i.e. those SCOR SCRM best practices that directly correspond to the core steps of the risk management process in the SC environment) into the SCOR process framework.
6. Conclusion Our study has analysed the coverage and integration of SCRM within SCOR 10.0. Given the pervasiveness of operational risk, SCRM’s inclusion into SCOR 9.0 and 10.0 was timely, as is related feedback on its effectiveness. Our critical analysis of SCOR 10.0 establishes the reference model’s coverage and degree of integration of process- based thinking towards risk, with findings showing a number of significant inconsistencies. If remedied these should usefully enhance future releases.
As shown in Table II, our analysis demonstrates the need to enhance the conceptualization and management of SCRM, particularly in SCOR’s Process component, which lacks guidance regarding the arrangement of SC risks associated with lower level processes. Related capability to devise a database of potential risk events would also facilitate appreciation of risk propagation mechanisms. Regarding Performance, SCOR’s narrow three-phased view of SCRM processes is inconsistent with other studies into SC risk management. In fact the misalignment of metrics and associated processes is contrary to the basic processes/metrics hierarchy principles espoused in SCOR’s design (Bolstorff and Rosenbaum, 2007). This has implications regarding a core strength of SCOR, namely its ability to identify root causes through the process of problem discovery (SCC, 2010, p. 1.2.8). Best Practices similarly require enhancement to address identification of SC risks at all levels of process decomposition. Moreover, although decomposition is implicitly situated in SCOR’s three-phased approach to managing SC risk within Best Practices, a prescribed approach to SCRM process decomposition at the level of risk management activities is still lacking. Further weaknesses concern the lack of avenue by which to assess the success of implemented best practices and reliance upon retrospective metrics, including outdated historical risk event data. This issue similarly applies across SCOR’s SCRM processes, performance (attributes and metrics) and best practices. Equally the new People component lacks a more diversified taxonomy of risks, including a lack of identified corresponding skill requirements. We argue that given the significance of the issues identified (see Table II), there is an urgent need to reconsider the way SCRM components are integrated in SCOR. Hence, suggested repositioning of the SCRM process alone (see Figure 5), allows some of the most pressing issues reported in Table II to be addressed.
Given SCOR’s pre-eminence as a framework to guide practice, its incomplete conceptualization of SCRM makes it less comprehensively effective than is desirable.
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As acknowledged in SCOR, risk is a growing concern for modern organizations and SCs. Thus, our analysis usefully progresses the evolutionary relevance of SCOR.
Notes 1. Whilst one paper explored a methodological approach to SC risk modelling with SCOR based
on the Analytic Network Process approach (Faisal et al., 2007), it was published before the release of SCOR 9.0. Thus, it can be regarded as a call to introduce risk into SCOR rather an analysis of risk-oriented SCOR model.
2. Databases like Business Source Complete, Emerald, Inderscience, IngentaConnect, Informit and Proquest were searched looking for a combination of “Risk” and “SCOR” in the title, abstract and keywords.
3. The SC risk modeling approach suggested is quite different from the one supplied in SCOR 9.0 and 10.0.
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Corresponding author Dr Kristian Rotaru can be contacted at: [email protected]
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- Outline placeholder
- 1.Introduction
- 2.Background and literature review
- 2.1SCOR: concepts and context
- 2.2Risk management principles and SCOR’s approach to risk management
- 2.3Review of research related to SCOR
- tb1Table IPast research concerning application and analysis of SCOR
- 3.Research approach
- 4.Analysis of SCRM in SCOR 10.0 and suggested improvements
- 5.Discussion
- tb2Table IIAnalysis of SCOR 10.0’s coverage and integration of SCRM and suggested improvements
- 6.Conclusion
- References
