Annotated Bibliography
Evans2020
Source1_GEN.pdf
The Department of Defense (DoD) and its organizationa l supply chain professiona ls recognize that DoD’s Supply Chain Management (SCM) system faces numerous cha llenges in need of ma nagement attention, especially excess inventory levels, inadequate controls, and cost overruns. Sustaining a ready, capable force through effective, joint logistics support for America’s warfighters is part of the DoD logistics mission, which includes SCM. Despite major investments in SCM systems, many organizations struggle to realize anticipated benefits, often times from the lack of valid methods to measure these benefits. Capturing key elements from historical efforts that others used to assess their SCM maturity levels, Crane Army Ammunition Activity developed the Supply Chain Management Maturity Model (SCM3) and used it to assess and improve its own maturity levels. Likewise, DoD organizations could use this model to improve operations in their supply chains and thereby improve the readiness of warfighters.
DOI: https://doi.org/10.22594/dau.16-772.24.04 Keywords: Supply Chain Management (SCM), Defense Industrial Base, Conventional Munitions Industrial Base (CMIB), Supply Chain Management Maturity Model (SCM3), Supply Chain Maturity
SUPPLY CHAIN MANAGEMENT Maturity Level Assessment
COL Scott S. Haraburda, USA (Ret.)
Image designed by Michael Krukowski
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Excess inventor y levels, inadequate controls, and cost overruns are initia l focus a rea s in the Depa r tment of Defense (DoD) Supply Cha in Management (SCM) system (Government Accountability Off ice [GAO], 2011, p. 1). Experiencing problems in these three areas for several decades, the DoD continues to lack outcome-focused performa nce measures for its SCM initiatives, ma king it diff icult to assess its capabilities in fore- casting, asset visibility, and materiel distribution (GAO, 2006, pp. 5–6, 9). Considering account safety stock and war reserves, the DoD possesses more than twice the amount of inventory needed to effectively sustain the war- fighters (Peltz & Robbins, 2012, p. 57). While reducing this inventory would lower operational expenses, the DoD has found it difficult to accomplish.
The DoD defines its logistics mission, including SCM, as “supporting the projection and sustainment of a ready, capable force through
globally responsive, operationally precise, and cost-effec- tive joint logistics support for America’s warfighters”
(GAO, 2011, p. 5). The DoD has identified a goa l to achieve a n effective a nd eff icient supply cha in
with improvement efforts aimed at each element in the log istics process. Increa sed govern-
ment-level SCM ef for t s to ach ieve t hese goa ls i ncrea se cost s a nd t h reaten
prof it s—t he pr i ma r y d r iver behind simila r improve-
ments in the commercial sector (Peltz & Robbins, 2012, p. 27). Instead of c on s i d e r i n g p r o f i t s , t he DoD shou ld iden- t i f y a n d p r i o r i t i z e improving those SCM processes that can aid in supporting the read- i n e s s of w a r f i g ht er s
within available costs.
Previous resea rch rein- f o r c e s t h e n o t i o n t h a t
effectively using a na lyzed business data improves organi-
zational decision making. However, despite major investments in SCM systems,
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many commercial and government organizations struggle to realize antic- ipated benefits, oftentimes from the lack of valid methods to measure them (Stadtler, 2005; Trkman, McCormack, de Oliveira, & Ladeira, 2010). What’s more, commercial companies recognize the importance of enhancing SCM, but often do not know what to implement to maximize their profits. Even worse, while many organizations have adequate systems in place to capture the required operationa l supply chain data, and since it often resides in dispersed functional domains, they lack suitable analytical tools and met- rics to assess the data to make process adjustment decisions (Song & van der Aalst, 2008). As such, they have problems in effectively achieving their supply chain-related goals.
Based upon a 2013 global supply chain survey of 209 companies, supply chain maturity is linked to operational performance (PricewaterhouseCoopers/ Massachusetts Institute of Technology, 2013). Since sustaining a mature supply cha in is critica l to a n orga nization’s performa nce, a structured diagnostic tool is needed to assess an organization’s current supply chain capability, defined as its maturity level, and identify target areas for perfor- mance improvement and cost reductions.
Background A s pa r t of DoD’s goa l to a ch ieve a n ef fective a nd ef f icient supply
cha in, the net work of munitions storage locations throughout the mil- ita r y shif ted empha sis from a compa ny- or a n insta l lation-on ly focus to a more adaptive supply cha in with integ rated comma nd a nd control throughout the entire Conventiona l Munitions Industria l Base (CMIB) of commercia l and government organizations. This meant that suppor t units now provide timely supply of the wa rf ighter’s munitions require- ments in response to sensing dema nd, whi le considering deliver y a nd production capabilities (Trip, A mouzega r, McGa r vey, Bereit, George, & Cornuet, 2006, p. 11).
In 2007, and to support this shift, senior DoD logistics leaders focused their attention upon two a reas impacting their supply cha in: orga nizationa l config uration and performance measures (Fletcher, 2011). Their initia l effort to improve the SCM included the development of a Joint Supply Chain Architecture (JSCA) based upon the Supply Chain Operations Reference (SCOR) model—a model widely used throughout the commercia l sector (Siegl, 2008). To implement this architecture within the acquisition com- munity, JSCA was added to the 2011 Product Support Manager Guidebook (DoD, 2011). Linking the SCOR model to JSCA required a heightened focus
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on the following performance metrics: Perfect Order Fulfillment for reli- ability, Customer Wait Time for speed, and Total Supply Chain Management Cost for efficiency. Perhaps because this JSCA was too prescriptive and did not capture the entire supply chain system, it disappeared from the DoD with no mention of JSCA in the 2016 Product Support Manager Guidebook. Yet, the SCOR model remained (DoD, 2016, p. 46).
Two other commercia l practices applied to the DoD included Sense and Respond Log istics (S&R L) a nd Performa nce Based A g reements (PBA) (Griffin, 2008). Fusing operations, intelligence, and logistics, the S&R L framework used highly adaptive, self-synchronizing functional processes to drive shor ter decision cycles a nd faster responses to the wa rf ighter. The PBA attempted to improve accountability, improve performance, and reduce costs for weapon systems with specific outcome-based performance metrics. Unlike the JSCA, these two efforts still exist.
Current DoD Direction In 2012, President Barack Obama issued a supply chain security strat-
egy that promoted the efficient and secure movement of goods and fostered a resilient supply chain (Obama, 2012, p. 1). To secure the flow of supplies, Obama required the alignment of federal logistics activities to the goals of this supply chain strategy (p. 5). Although this strategy focused primarily upon mitigating supply chain risks such as counterfeiting, terrorism, and cyberattacks, it lacked g uidance towards the logistica l and operationa l aspects of SCM. Yet, it was a n impor ta nt step towa rds improving SCM within the government.
Two yea rs later, the DoD issued updates to its SCM procedures, which required use of the SCOR model for the entire DoD supply chain (DoD, 2014a, Vol. 1, pp. 5–6). In an effort to address the supply chain security issues, these DoD procedures employed risk management strategies to identify and assess potential supply chain disruptions, such as unreliable suppli- ers, machine break-downs, natural disasters, and labor strikes. Further, these procedures promoted collaboration with suppliers and customers. Adoption a nd adaptation of best commercia l business practices were required to increase supply chain performance and reduce total life-cycle systems cost. These procedures required DoD organizations to continually monitor emerging business practices and a lign organizationa l decision authority in collaboration with stakeholders (pp. 7–8). Instead of requiring specific metrics, these procedures provided DoD the flexibility to tailor effective metrics, but still required metrics to be balanced throughout the supply chain system and to be compared to industrial benchmarks (pp. 6–7)
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The 2016 Product Support Manager Guidebook requires acquisition manag- ers to continuously reduce and streamline the logistics footprint by using existing supply chains instead of creating new ones (DoD, 2014b, Vol. 10, p. 25). During the materiel solution analysis phase, the PSM should apply the SCOR model to ensure all aspects of the supply chain are considered (p. 46). Further, acquisition managers should ensure processes exist that facilitate efficient public/private partnerships for data sharing (p. 54).
Research Framework In this research, I assessed the SCM maturity level of the Crane Army
Ammunition Activity (CAAA), a key organization within the CMIB. Located in centra l India na , this ma nufacturing a nd stora ge activit y ma nufac- tures, stores, and provides conventional munitions to warfighters. As an Army Working Capital Fund (AWCF) organization, it operates more like a commercial manufacturer focused upon winning customers versus a gov- ernment organization focused upon winning Congressional appropriations for its workload (Haraburda, 2016). In a rapidly changing environment, CA A A bega n a dra matic tra nsformation in the way it does business by adopting the more robust, flexible approaches of SCM to improve its opera- tional logistics processes. CA A A leadership recognized that using effective SCM was a viable way to achieve a competitive advantage within the CMIB and improve organizational performance (Li, Ragu-Nathan, Ragu-Nathan, & Rao, 2006).
To monitor its transformation efforts, CAAA wanted to revise existing com- mercial methods to assess the SCM maturity level. CA A A desired a higher level of this maturity, which led to improved operationa l performa nce, increased accuracy in forecasting, and higher effectiveness in reaching CA A A business goals (Lahti, Shamsuzzoho, & Helo, 2009).
The following three key topics were addressed in my research effort.
1. The mea ns to mea sure t he breadt h a nd dept h of a n AWCF organization that goes beyond simple operational capacities of procurement, storage, manufacturing, and transportation.
2. The assessment of long-term, exclusive (noncompetitive) sup- ply cha in relationships with commercia l vendors that would improve supplier efficiencies and flexibilities.
3. The incorporation of commercia l sector methods, such as the Capability Maturity Model (CMM), to assess SCM processes.
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Supply Chain Maturity Assessment Development Since 1996, orga nizations have used t he SCOR fra mework to lin k
business processes into a unif ied, integ rated str ucture that improves supply chain performance (Supply Chain Council, 2012, p. i.1). The Supply Cha i n Counci l, a g loba l nonprof it consor tium, developed t h is model. The model recog nizes six major processes: pla n, source, ma ke, deliver, ret ur n, a nd enable ( pp. 2.0.1–2.0. 2). O verlapping t hese processes a re 19 categories that include activities such as management of distribution, inventory, forecasting, production, training, risk, warehousing, and trans- portation (p. 3.0.2). Considered in this research, the following five supply chain maturity assessment models employ some concepts from the SCOR framework model. As shown in Table 1, each of these models contains five organizational maturity levels.
TABLE 1. SUPPLY CHAIN MATURITY MODELS
Model Author(s) Year
Organizational Maturity Levels I II III IV V
SCM- BPO
McCormick & Johnson
2002 Ad Hoc Defined Linked Integrated Extended
SCM2 Poirier & Quinn
2004 Enterprise Integration
Corporate Excellence
Partner Collaboration
Value Chain Collaboration
Full Network Connectivity
LME Reay, Colaianni, Harleston, Maletic, & Marcus
2006 Initial Managed Logistics
Tailored Logistics
Quantitatively Managed
Optimized Integration
S(CM)2 Garcia 2008 Undefined Defined Manageable Collaborative Leading
SCPM3 de Oliveira, Ladeira, & McCormack
2011 Foundation Structure Vision Integration Dynamics
Note. LME = Logistics Maturity Evaluator; SCM2 = Supply Chain Maturity Model; S(CM)2 = Supply Chain Capability Maturity Model; SCM-BPO = Supply Chain Management-Business Process Orientation; SCPM3 = Supply Chain Process Management Maturity Model.
Several key members of CAAA reviewed the initial survey instrument and provided valuable feedback regarding content and ease of use.
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1. Supply Chain Management-Business Process Orientation— SCM-BPO. Each of the five organizational maturity levels in this model contains characteristics associated with predictability, capability, control, effectiveness, and efficiency (McCormack & Johnson, 2002, pp. 50–52). The lowest level (Ad Hoc) ha s unstructured and ill-defined supply chain processes. The next level (Defined) has defined processes that are separate from one another. The third level (Linked) has processes that are con- nected to one another. The next level (Integrated) has all of its organizational processes connected to one another with a unified goal. Cooperation with external organizations such as suppliers and customers begins in this fourth maturity level. Finally, the highest level (Extended) is represented with a multiorganiza- tional, integrated supply chain.
2. S uppl y C h a i n M at u r it y Mo del— S C M 2 . T h i s mo de l i s based upon an enterprise view, with the first level (Enterprise Integration) involving functional integration (Poirier & Quinn, 2004). The second level (Corporate Excellence) has its internal organizational processes optimized to meet its goals, which is similar to the fourth level in the SCM-BPO model. External col- laboration begins in the third level (Partner Collaboration), a level difficult to achieve. The next level (Value Chain Collaboration) involves supply chain optimization with frequent discussions with suppliers and customers. The highest level (Full-Network Connectivity) involves full-communications integration with externa l organizations. This model is based upon the concept that clearly defined, managed, measured, and controlled supply chains improve performance.
3. Log istics Maturity Eva luator—LME . This supply cha in model applies a quantitative assessment to the CMM develop- ment model (Reay et a l., 2006, p. 2-1). The first level (Initia l) represents unstructured supply chain processes. The next level (Managed Logistics) has repeatable processes. The third level (Ta i lored Log istics) ha s well-def ined processes throughout the organization. The next level (Quantitatively Managed) has effective metrics to ma nage its processes. The highest level (Optimized Integration) has integrated processes that focus upon optima l performa nce. In addition to a n overa ll orga ni- zationa l assessment, this model assesses these f ive maturity levels in six functional areas: organization/workforce, logistics
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processes, performance, resources, technolog y enablers, and vision/strategy (p. 4-1). It also incorporates a structured, high- level sur vey of 173 questions, sepa rated into 26 f unctiona l components, to assess both the organizational and component maturity levels.
4. S up p l y C h a i n C a p a b i l it y M a t u r it y M o d e l— S (C M ) 2 . This is a maturity model that assesses the integration level of an organization’s supply chain processes, from suppliers through the organization to the customers (Garcia, 2008, pp. 32, 74–75). Simi la r to the other models, the f irst level (Undef ined) ha s unstructured and ill-defined supply chain processes. The next level (Def ined) has def ined processes that a re sepa rate from one a nother. The third level (Manageable) applies metrics to managing its processes. The next level (Collaborative) involves frequent discussions with suppliers and customers. The highest level (Leading) applies continuous improvement to its processes in pursuit of applying benchmark processes that other organiza- tions want to emulate.
5. Supply Cha in Process Ma na gement Maturity Model— SCPM3. This is a model based upon an assessment of nearly 800 companies throughout the world. It def ines the different levels of maturities based upon related supply chain processes of companies with similar performance (de Oliveira, Ladeira, & McCormack, 2011). The first level (Foundation) represents the early stages when processes are being developed. The next level (Structure) has defined processes where performance is starting to be measured. The third level (Vision) has processes that drive future improvements. The nex t level (Integration) has integrated processes with suppliers a nd customers. The highest level (Dynamics) has processes using key performance indicators that enable responsiveness to environmental changes.
CAAA Research Model: Supply Chain Management Maturity Model (SCM3)
The maturit y model applied in this resea rch effor t wa s the SCM3, which was heavily based upon the LME model. Ta ilored specif ica lly to the supply chain processes at CA A A, the new proposed assessment model is a hybrid. Using the same organizational maturity levels from the LME model, SCM3 replaced its logistics focus with that of SCM, while blending effectiveness from the other four models. Furthermore, using CMM, the
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SCM3 includes maturity levels for components and functional areas. The lowest maturity level (Initial) for these additional sections is an undefined component or area (Table 2). The next level (Managed SCM) has predictable performances. The third level (Tailored SCM) has defined processes. The next level (Quantitavely Managed SCM) applies metrics and controls. The highest level (Optimized SCM Integration) is focused upon continua lly improving performance throughout the component or area.
TABLE 2. PROPOSED SUPPLY CHAIN MANAGEMENT MATURITY MODEL
Organizational Maturity Levels (Functional Areas and Components)
Model I II III IV V
SCM3 Initial Managed SCM Tailored SCM Quantitatively
Managed SCM Optimized SCM Integration
SCM3 used many of the LME survey questions, which were each revised to more accurately assess the SCM of an AWCF organization. This new assess- ment model also evaluated the same six functional areas, with a focus on SCM processes. As for the functional components, this new model eliminated three and revised several others from the LME model, resulting in only 23 compo- nents in the SCM3 as depicted in the pyramid in Figure 1. Although assessed separately, these functional components were grouped into the organizational maturity levels where they were most likely to be used (Appendix).
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Research Methodology In my research to determine the supply chain maturity at CAAA, I sent
the SCM3 assessment survey to organizational supply chain professionals and supervisors. Participants received an Excel-based spreadsheet survey instrument of 163 multiple choice questions. These questions were grouped into 23 functiona l components a nd six functiona l a reas. In addition to assessing the overall maturity level of the organization, they were designed to assess the levels for each of these components and areas. If participants did not understand the organizational performance in any of the questions assessed, they were encouraged to select the fifth c hoice, ‘ E’. T hese fi fth choice selections were identif ied as ‘I do not know ’ (IDNK) selections. To ensure the integrity of the findings, I r emoved t hese r esponses during maturity-level analyses.
Each participant spent between 30–60 minutes to complete the sur vey. To ensure anonymity, individuals submitted responses by clicking a macro button in the file, which saved the data into a network server folder. A few organizational questions were added to indicate participant’s organization and supervisory status. Fina lly, the spreadsheet survey was designed to prevent partial submissions containing unanswered questions and multiple submissions by the same participant.
Data Collection Prior to issuing the survey to participants, I conducted a small pilot study
to check the mechanics of the spreadsheet and clarify text within the ques- tions. Several key members of CAAA reviewed the initial survey instrument and provided valuable feedback regarding content and ease of use. Based upon this feedback, I clarified the questions and redesigned the spreadsheet. I issued the survey with written instructions to participants, along with a document containing generic SCM background information. They were given 4 weeks to complete and submit the survey. On a weekly basis, I pro- vided completion status metrics to senior CA A A leaders, who used this to encourage their employees’ participation.
Only 40 percent of the survey population responded. Many participants provided comments indicating the survey was too long and too complicated, suggesting that too many questions on complex topics with which the partici- pants had no familiarity was a key reason for the high nonparticipation level.
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Participants I sent the sur vey instrument to pa r ticipa nts whose functions were
directly related to supply chain processes within CA A A. To minimize any risk of skewing the data with my preconceived ideas, I chose not to partici- pate in the survey. Participants came from supply chain positions, such as manufacturing schedulers, procurement specialists, inventory specialists, and transportation controllers. Slightly more than half were supervisors (51.7 percent), with the others classified as professionals. They were also segregated into four groups: command, logistics (DO for depot operations), manufacturing (ME for manufacturing and engineering), and support staff, with percentages of each depicted in Figure 2. The command group included the commander, his deputy, and the chief of staff; the staff, however, were support professionals external to the directorates.
FIGURE 2. SURVEY PARTICIPANTS
PARTICIPANTS 1
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51.7%
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Supervisors
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10.3%
17.2%
31.0%
41.4%
Command
Depot Operations
Manufacturing and Engineering
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0% 20% 40%
PARTICIPANTS 2
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Data Analyses Each of the 163 questions in the survey was tied to a unique functional
area and a unique functional component. Scoring of each question was based upon assigning a va lue to selected responses as shown in Table 3. From the assessment, I screened questions with “E” selected for the responses, indicating an answer of IDNK.
TABLE 3. SURVEY QUESTION SCORING VALUES
Answer Value
A 5.00 B 3.67
C 2.33
D 1.00
E screened from calculations
A f ter the sur veys were completed, I ca lculated the maturity level (ML) and standard deviation (σ) for each area and element using the following equations:
ML = 5.00n A + 3.67nB + 2.33nC + 1.00nD (1)n A + nB + nC + nD
ni = number of questions with answer i
σ = n A(5.00 – ML)
2 + nB (3.67 – ML) 2 + nC (2.33 – ML)
2 + nD (1.00 – ML) 2
(2)n A + nB + nC + nD – 1
Results and Recommendations Organizational Maturity Levels
The overa ll SCM orga nizationa l maturity level for CA A A was 3.04 (Table 4). With more knowledgeable selections, indicated with the lowest IDNK percentage (20.4 percent), the logistics group assessed the highest maturity level for CA A A (3.42); whereas manufacturing, with the highest IDNK percentage (47.4 percent), assessed the lowest maturity level (2.73). As for variances in the results, standard deviations within each of the four groups were about 1.3 within each of them. However, when combining all groups together, the variance more than tripled, indicating that each group had similar opinions, but differed significantly from other groups.
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TABLE 4. SURVEY PARTICIPANT RESPONSES
Group ML σ IDNK % Command 3.31 1.13 34.2% Logistics 3.42 1.38 20.4%
Manufacturing 2.73 1.31 47.4% Staff 2.95 1.35 42.8%
Overall 3.04 4.71 39.5%
Note. ML = Maturity Level; IDNK = I do not know.
Functional Area Maturity Levels The SCM a rea w it h t he highest maturit y level wa s Per forma nce/
Metrics with a value of 3.15. This might be the highest because the most recent SCM improvements at CA A A involved implementation of a new performance-based dashboard with industrial benchmarks just prior to this survey (O’Neall & Haraburda, 2017). The lowest area was Vision/Strategy, with a maturity level of 2.95. As shown in Figure 3, supervisors rated the levels about 0.2 lower than professionals, perhaps because professionals spent more time performing the SCM functions than their super visors. Another interesting obser vation was that the trends between these two groups were similar for five of the six areas. The Resources area was the sole exception with a 0.5 difference, perhaps because the supervisors held a more cautious perception than the professionals in believing the organization provided resources needed to complete the work.
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FIGURE 3. FUNCTIONAL AREA ASSESSMENT RESULTS
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Functional Component Maturity Levels The SCM component with the highest maturit y level was Materiel
Disposition, with a value of 3.53 (Table 5), which was a strong core compe- tency with the logistics group. The lowest component was strategic sourcing with a maturity level of 2.40. Again, variances in each group for each of the
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functiona l components were much sma ller than the overa ll CA A A vari- ance. Further, when both were sorted in decreasing order of overall levels, the logistics group scored higher maturity levels in each of the functional components—much higher than in the manufacturing group (Figure 4).
TABLE 5. FUNCTIONAL COMPONENT LEVELS AND STANDARD DEVIATIONS
Command DO ME Staff OVERALL
Component ML σ ML σ ML σ ML σ ML σ
Materiel Disposition 3.58 1.24 3.50 1.20 3.52 1.06 3.55 1.27 3.53 4.93
Balanced Scorecard/ Benchmark
3.67 1.33 3.78 1.37 2.65 1.39 3.47 1.40 3.38 4.78
Asset Visibility 4.00 1.24 3.77 1.35 3.08 1.12 3.11 1.51 3.36 5.42
Asset Management 3.75 1.14 3.56 1.49 3.06 1.42 3.33 1.31 3.36 4.95
Item Identification 3.42 1.31 3.97 1.09 3.13 1.38 3.10 1.56 3.31 4.39
Distribution and Transportation
3.08 1.09 3.82 1.21 3.03 1.33 3.19 1.23 3.25 4.51
Performance Based Logistics
5.00 0.00 3.53 1.40 2.33 0.89 2.91 1.13 3.23 4.83
Enterprise Integration 3.13 1.69 3.53 1.43 2.83 1.37 3.04 1.73 3.14 5.27
Systems Modernization 3.38 1.58 3.67 1.30 2.61 1.31 3.13 1.38 3.12 5.95
Supply Chain Integration 3.67 0.84 3.83 1.13 2.33 1.45 2.96 1.44 3.12 3.77
Metrics Analysis 3.45 0.96 3.35 1.40 2.94 1.25 2.96 1.44 3.09 3.55
Continuous Improvement 3.80 1.00 3.31 1.25 2.68 1.23 2.99 1.48 3.06 6.94
SCM Skills Development 3.00 1.36 3.45 1.34 2.94 1.50 2.83 1.28 3.03 5.07
Requirements Determination
3.36 1.11 3.33 1.32 2.71 1.47 3.02 1.28 3.02 4.27
Inventory Optimization 3.67 0.50 3.45 1.42 2.70 1.23 2.74 1.29 3.00 3.78
Functional Integration 3.21 1.25 3.55 1.48 2.57 1.48 2.85 1.37 2.99 7.46
Strategic Planning & Execution
3.10 1.25 3.13 1.59 2.47 1.17 3.06 1.36 2.97 5.04
Materiel Acquisition 3.13 1.29 2.92 1.46 2.84 1.35 3.00 1.28 2.95 4.25
Operational Excellence 3.33 1.01 3.02 1.41 2.87 1.33 2.46 1.23 2.79 3.68
Customer Relationship Mgmt
2.63 1.30 3.20 1.63 2.64 1.42 2.73 1.17 2.79 3.88
Supplier Relationship Mgmt 2.18 1.04 3.00 1.38 2.52 1.37 2.67 1.21 2.65 3.16
Maintenance 2.51 1.11 3.09 1.38 2.27 1.33 2.36 1.32 2.47 4.44
Strategic Sourcing 2.04 1.30 2.93 1.78 2.19 1.20 2.33 1.33 2.40 3.90
Note. Components are listed in decreasing order of overall maturity level (ML). DO = Depot Operations; ME = Manufacturing and Engineering.
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FIGURE 4. FUNCTIONAL COMPONENT ASSESSMENT RESULTS
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Command Logistics Manufacturing Sta�
Recommendations I n t he c om ment s se c t ion of t he s u r vey, pa r t icipa nt s ident i f ie d
Asset Ma nagement, SCM Skills Development, Inventor y Optimization, Requirements Deter mination, a nd Strateg ic Pla nning a s t he top f ive f unctiona l components that CA A A shou ld prioritize for supply cha in improvement efforts. When considering maturity level assessments with these identified components, the top five priorities for CA A A were revised to the following recommendations for improvement:
1. Asset Management. Hire consulta nts to assess gaps in the organization’s practices and recommend improvements based upon ISO-55000 sta nda rds (Internationa l Orga nization for Standardization, 2014).
2. SCM Skills Development. Establish a Community of Practice for SCM as an informal venue for exchange of knowledge relative to SCM principles and practices, with a strong focus on fulfilling
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the business goals of the organization (Wegner & Snyder, 2000). Next, align these skills throughout the organization and begin the journey to organizational performance excellence through the Baldrige National Quality Award program.
3. Strategic Sourcing. Increase knowledge in this component by encourag ing SCM professiona ls to complete two Defense Acquisition University continuous learning modules: Strategic Sourcing Over view (CLC 108) and Spend Ana lysis Strategies (CLC 110). Next, develop strategic sourcing processes based upon the DoD-wide Strategic Sourcing program and its framework (DoD, 2013).
4. Maintenance. Complete continuous improvement projects to improve management of organizational maintenance of facilities and equipment, such as implementing predictive maintenance programs for critical systems.
5. Supplier Relationship Management. Complete continuous improvement projects to improve relationships with governmen- tal and commercial suppliers.
Research Reflections Limitations
A limitation of this study rested upon a common understa nding of the SCM terms used in the survey, meaning that some of the respondents’ answers may have been hunches or more appropriately identified with the IDNK selections. Based upon participant comments, many of these IDNK selections and a low submission rate were impacted by information blind- ness (Eppler & Mengis, 2004). Less tha n 40 percent pa r ticipated, even after being given more time and supervisory encouragement. As such, the prioritized recommendations for improvement suggestions were based upon a minority of the CA A A supply chain population.
Implications T h is su r vey showed it wa s possible to a ssess t he SCM mat u r it y
levels within an organization. Based upon feedback that participants pro- vided, some questions could have been answered with more than one of the responses provided, leaving it to the participant to determine which
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response better represented the organization. Yet, this study provided valid recommendations to move this organization towards better understanding and application of SCM processes (DoD, 2013).
Conclusions Performance within an organization’s supply chain network can affect
a n orga nization’s mission, ma king it critica l to develop a nd susta in a mature supply chain. The SCM3 survey is a structured, high-level diag- nostic tool that could be used to assess the organization’s current supply chain capability and identify target areas for performance improvement a nd cost-reduction projects. Results of this sur vey could help improve operationa l decision ma king for orga nizationa l log istics effor ts, focus supply-related management emphasis, and align organizational resources within the organizational supply chain. Additionally, these results could provide an enterprise view of how the organization’s SCM processes com- pare to those of industry’s best performers. Although this research focused upon the CMIB, similar SCM3 assessments conducted in other Defense Industrial Base organizations should yield similar results.
CA A A will implement its prioritized recommendations to improve its supply chain network with valuable information obtained from this sur- vey. Implementing these few improvements will have noticeable results in CA A A advancing its business processes commensurate with those of other industrial leaders, and maintaining its relevance to the warfighters. Fur thermore, CA A A will reduce the complexit y of the orig ina l survey to just a handful of relevant questions gleaned from the prioritized five functional compo- nents. After improvements have been made, CA A A will then submit the revised survey to the sa me sur vey pa r ticipa nts. Using t he orig ina l sur vey resu lts a s a n ini- tial baseline, results of the winnowed q ue s t ion s w i l l y ie ld do c u m ent e d evidence of maturity level changes resulting from these improvements. Fina lly, through the continuous improvement cycle, CA A A will t hen i dent i f y a not her s e t of f unctiona l components in t he SCM3 model for its next round of improvements.
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References de Oliveira, M. P. V., Ladeira, M. B., & McCormack, K. P. (2011). The Supply Chain
Process Management Maturity Model – SCPM3. In D. Onkal (Ed.), Supply Chain Management - Pathways for Research and Practice (pp. 201–218). Retrieved from http://cdn.intechopen.com/pdfs-wm/17153.pdf
Department of Defense. (2011). Product support manager guidebook. Retrieved from https://ld.hq.nasa.gov/docs/PSM_Guidebook_April-2011.pdf
Department of Defense. (2013). DoD-wide strategic sourcing program: Concept of operations. Retrieved from http://www.acq.osd.mil/dpap/ss/docs/DWSS- CONOPS.pdf
Department of Defense. (2014a). DoD supply chain materiel management procedures: Operational requirements (Vol. 1, DoDM 4140.01). Retrieved from http://www.esd. whs.mil/DD/
Department of Defense. (2014b). DoD supply chain materiel management procedures: Metrics and inventory stratification reporting (Vol. 10, DoDM 4140.01). Retrieved from http://www.esd.whs.mil/DD/
Department of Defense. (2016). Product support manager guidebook. Retrieved from https://www.dau.mil/tools/t/Product-Support-Manager-(PSM)-Guidebook
Eppler, M., & Mengis, J. (2004). The concept of information overload. The Information Society – an International Journal, 20(5), 1–20.
Fletcher, M. P. (2011). Joint supply chain architecture. Army Sustainment, 43(2), 20–24. Retrieved from http://www.alu.army.mil/alog/issues/MarApr11/joint_supply_ chain.html
Garcia, H. (2008). A capability maturity model to assess supply chain performance (Doctoral dissertation). Florida International University, Miami. Retrieved from http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=1244&context=etd
Government Accountability Office. (2006). Challenges remain to achieving and demonstrating progress in supply chain management (Report No. GAO-06- 983T). Retrieved from http://www.gao.gov/assets/120/114512.pdf
Government Accountability Office. (2011). DOD needs to take additional actions to address challenges in supply chain management (Report No. GAO-11-569). Retrieved from http://www.gao.gov/assets/330/322061.pdf
Griffin, W. (2008). The future of integrated supply chain management utilizing performance based logistics. Defense Acquisition Review Journal, 15(1), 2–17. Retrieved from http://www.dau.mil/pubscats/PubsCats/ARJ47_Griffin.pdf
Haraburda, S. S. (2016). Transforming military support processes from logistics to supply chain management. Army Sustainment, 48(2), 12–15. Retrieved from http://www.alu.army.mil/alog/2016/MarApr16/PDF/162197.pdf
International Organization for Standardization. (2014). Asset management – overview, principles and terminology (ISO-55000:2014[E]). Genève, Switzerland: Author.
Lahti, M., Shamsuzzoho, A. H. M., & Helo, P. (2009). Developing a maturity model for supply chain management. International Journal of Logistics Systems and Management, 5(6), 654–678.
Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., & Rao, S. S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega: The International Journal of Management Science, 34(2), 107–124.
677Defense ARJ, October 2017, Vol. 24 No. 4 : 656-681
October 2017
McCormack, K. P., & Johnson, W. C. (2002). Supply chain networks and business process orientations: Advanced strategies and best practices. Boca Raton, FL: The St. Lucie Press/APICS Series on Resource Management.
Obama, B. (2012). National strategy for global supply chain security. Retrieved from https://obamawhitehouse.archives.gov/sites/default/files/national_strategy_for_ global_supply_chain_security.pdf
O’Neall, C. E., & Haraburda, S. S. (2017). Balanced scorecards for supply chain management. Defense AT&L, 46(4), 2-6. Retrieved from https://www.dau.mil/ library/defense-atl/blog/Balanced-Scorecards-for-Supply-Chain-Management
Peltz, E., & Robbins, M. (2012). Integrating the Department of Defense supply chain (RAND Technical Report 1274-OSD). Retrieved from http://www.rand.org/ content/dam/rand/pubs/technical_reports/2012/RAND_TR1274.pdf
Poirier, C. C., & Quinn, F. J. (2004). How are we doing? A survey of supply chain progress. Supply Chain Management Review, 8(8), 24–31.
PricewaterhouseCoopers/Massachusetts Institute of Technology. (2013). MIT forum for supply chain innovation: Making the right risk decisions to strengthen operations performance. Retrieved from https://www.pwc.com/gx/en/ operations-consulting-services/pdf/pwc-and-the-mit-forum-for-supply- chain-innovation_making-the-right-risk-decisions-to-strengthen-operations- performance_st-13-0060.pdf
Reay, J. H., Colaianni, A. J., Harleston, E. F., Maletic, A., & Marcus, J. G. (2006). Logistics maturity evaluator (Report No. IR509R1). LMI Research Institute. Retrieved from http://www.dtic.mil/dtic/tr/fulltext/u2/a457193.pdf
Siegl, M. B. (2008). Understanding the Supply Chain Operations Reference Model. Army Logistician, 40(3), 18–21. Retrieved from http://www.alu.army.mil/alog/ issues/MayJun08/ref_model_supplychain.html
Song, M., & van der Aalst, W. M. P. (2008). Towards comprehensive support for organizational mining. Decision Support Systems, 46(1), 300–317.
Stadtler, H. (2005). Supply chain management and advanced planning—Basics, overview, and challenges. European Journal of Operational Research, 163(3), 575–588.
Supply Chain Council (2012). Supply chain operations reference model (Revision 11.0). Chicago, IL: American Production and Inventory Control Society.
Trip, R. S., Amouzegar, M. A., McGarvey, R. G., Bereit, R., George, D., & Cornuet, J. (2006). Sense and respond logistics: Integrating prediction, responsiveness, and control capabilities (RAND Monograph 488-AF). Retrieved from http://www. rand.org/content/dam/rand/pubs/monographs/2006/RAND_MG488.pdf
Trkman, P., McCormack, K., de Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318–27.
Wenger, E. C., & Snyder, W. M. (2000). Communities of practice: The organizational frontier. Harvard Business Review, 78(1), 139–145. Retrieved from https://hbr. org/2000/01/communities-of-practice-the-organizational-frontier
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Appendix Supply Chain Management Maturity Model Components
Organizational Maturity Level I—Initial 1. Item Identification. The system of marking, va luing, and tracking
items delivered to an organization that enhances logistics, contracting, and financial business transactions.
2. Asset Management. The effectiveness of an organization in managing assets to support demand satisfaction. This includes the management of all assets: fixed and working capital.
3. Distribution and Transportation. The movement of items through- out the supply chain pipeline using services (i.e., trucking, rail, air, and marine) and facilities (i.e., warehouses and distribution centers).
4. Materiel Disposition. The sales, transfer, lease, loan, demilitarization, or disposal of materiel.
5. Materiel Acquisition. The processes to obtain materiel to satisfy an operational need, such as production, storage, disposal, and distribution tasks.
6. R equirements Deter mination . T he met hods to deter m i ne t he requirements of the orga nization through a va riet y of techniques (i.e., interviews, observations, designs, and customer dictates) while determining the most effective, timely, and cost-efficient way to obtain those requirements.
7. Maintenance. The processes involved to ensure equipment and facil- ities work when needed in an efficient and effective manner, applying reactive, preventative, and predictive methods.
Organizational Maturity Level II—Managed SCM 8. Functiona l Integ ration. The collaboration, communication, a nd
coordination between functiona l activities in an organization, such as finance, production, procurement, and logistics. This includes the efficient and effective deployment and allocation of the organization’s resources, which includes finances, inventory, labor, equipment, facili- ties, and information.
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9. Inventory Optimization. The processes for balancing the amount of working capital, such as warehouse buildings tied up in inventory with service-level goals across the organization.
10. Systems Modernization. The incremental cost-effective evolution of business processes that incorporates modern architectures and tech- nologies to improve operational performance.
11. Metrics Analysis. The iterative process for identif ying issues and problems derived out of data collected from organizational activities.
12. SCM Skills Development. The training and development of the orga- nization’s workforce to perform tasks needed for its SCM.
13. Asset Visibility. The capability to provide users with timely and accu- rate information on the location, movement, status, a nd identity of personnel, equipment, and materiel.
14. Continuous Improvement Program. An ongoing effort to improve products, services, or processes. This includes the process of finding and removing unwarranted expenses from the organization to increase profits without having a negative impact on the quality of its products.
Organizational Maturity Level III—Tailored SCM 15. Supplier Relationship Management. The comprehensive approach
to managing the organization’s interactions with vendors that supply the goods and services it uses.
16. Balanced Scorecard and Benchmarking. The strategic management system that aligns activities with an organization’s vision and strategy to improve decision making and communications by monitoring perfor- mance metrics along with comparing them to Defense Industrial Base best practices.
17. Customer Relationship Management. The processes used to under- sta nd customer needs by bui lding customer relationships leading towards providing better required products and ser vices, when and where needed.
18. Supply Chain Integration. The collaboration, communication, and coordination between a ll g roups involved in the supply cha in from suppliers through the organization to its customers.
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19. Strategic Sourcing. The collaborative and structured process of criti- cally analyzing the organization’s procurement expenses and using this information to make better and more cost-effective business decisions in the effective, efficient procurement of materials and services.
20. Performance Based Logistics. The processes used to optimize prod- uct availability while minimizing costs with the best use of public- and private-sector capabilities through partnering initiatives.
Organizational Maturity Level IV—Tailored SCM 21. E nt er pr ise Int eg ration . T he t i mely a nd a ccu rat e excha n ge of
consistent information between business functions throughout the organization to support strategic and tactical goals in a manner that appears to be seamless.
22. Strategic Planning and Execution. The processes for defining the long-term goals of an organization, making decisions on allocating its resources in pursuit of those goals, and continually tracking its progress towards them.
Organizational Maturity Level V—Optimized SCM Integration 23. Operational Excellence. The integrated approach to organizational
performa nce that results in the deliver y of ever-improving va lue to its customers and sta keholders while contributing to organizationa l sustainability.
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Author Biography
COL Scott S. Haraburda, USA (Ret.), is cur- rent ly t he strateg ic pla nner for Cra ne A r my Ammunition Activity. Throughout his 29-year military career, he primarily commanded chem- ical units, including the 464th Chemical Brigade. COL Haraburda graduated from the U.S. Army Wa r C ol le ge a n d hold s a Ph D i n C hem ic a l Engineering from Michigan State University. He is a registered Professional Engineer in Indiana, a Project Management Professional, and is Defense A c q u i s i t i o n Wo r k f o r c e I m p r o v e m e n t A c t ( D AW I A ) L e v e l I I I c e r t i f i e d i n P r o g r a m Management and Engineering.
(E-mail address: [email protected])
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