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Journal of Relationship Marketing

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Strategic Operational and Analytical Customer Relationship Management

Reiny Irianaa; Francis ButtleaaMacquarie Graduate School of Management (MGSM), Macquarie University, Sydney, Australia

To cite this ArticleIriana, Reiny and Buttle, Francis(2007) 'Strategic, Operational, and Analytical Customer RelationshipManagement', Journal of Relationship Marketing, 5: 4, 23 42

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Strategic, Operational, and AnalyticalCustomer Relationship Management:

Attributes and Measures

Reiny Iriana

Macquarie University

Francis ButtleMacquarie University

ABSTRACT. Customer Relationship Management (CRM) means dif-ferent things to different people. For some, CRM is the term used to de-scribe a set of IT applications that automate customer-facing processes

in marketing, selling and service. For others, it is about an organizationaldesire to be more customer focused. Others associate CRM with the cap-

ture, analysis and exploitation of customer-related data. One distinctionthat has been made is between strategic, operational and analyticalCRM. This paper sets out to understand, conceptualize and operationalize

these terms. Our research generally supports the idea of a multi-dimen-sional conceptualization of CRM. We develop and present an instru-

ment, consisting of a thirteen-item scale, which can be used to assess anorganizations orientation towards one or more of these three forms ofCRM.doi:10.1300/J366v05n04_03 [Article copies available for a fee fromThe Haworth DocumentDelivery Service: 1-800-HAWORTH. E-mail address:

Reiny Iriana, MM, is a Doctoral Candidate and Francis Buttle, PhD, is Professor ofManagement and Chair of Marketing, both at Macquarie Graduate School of Manage-ment (MGSM), Macquarie University, North Ryde, Sydney, Australia.

Address correspondence to: Francis Buttle, Macquarie Graduate School of Man-agement (MGSM), Talavera Road, North Ryde, Sydney, NSW 2109, Australia (E-mail:[email protected]).

Journal of Relationship Marketing, Vol. 5(4) 2006Available online at http://jrm.haworthpress.com

2006 by The Haworth Press, Inc. All rights reserved.doi:10.1300/J366v05n04_03 23


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Website: 2006 by The Haworth Press, Inc. All rights reserved.]

KEYWORDS. Customer relationship management, CRM, strategic

CRM, operational CRM, analytical CRM, measurement scale

CRM DEFINITIONS AND PERSPECTIVES

Many definitions of Customer Relationship Management (CRM)have been developed and published. Academics and practitioners see

CRM as touching on issues of business strategy (Gummesson, 2002;CRMguru.com, quoted in Tan et al., 2002), customer life-cycle man-agement processes (Galbreath & Rogers, 1999; Nancarrow et al., 2003;Parvatiyar & Sheth, 2001), information technology (Gefen & Ridings,2002; Shoemaker, 2001), and communications strategy (Kay Mandati,quoted in McKim, 2002; Swift, 2001). CRM is also seen as multiple-variate construct, a combination between strategy and IT (Payne &Frow, 2005), between process and IT (Plakoyiannaki & Tzokas, 2002),between strategy, process and IT (Buttle, 2004; Rigby et al., 2002), andbetween process, strategy, philosophy, capability and IT (Zablah et al.,2004). These many definitions are evidence of the emergent and variednature of CRM. Some authorities have concluded that an agreement ona definition of CRM is needed before it can become a distinct manage-ment discipline (Paas & Kuijlen, 2001; Parvatiyar & Sheth, 2001;Plouffe et al., 2004).

Given the diversity of definitions and descriptions of CRMs scope itshould come as no surprise that there have been several attempts to pro-duce taxonomies that recognize different forms of CRM. One earlyeffort identified three different forms of CRM: Operational, Collabora-tive, and Analytical CRM (METAGroup, 2001, p. 5). They defined theseforms as follows:

Operational CRMcomprises the business processes and technol-ogies that can help improve the efficiency and accuracy of day-to-day customer-facing operations. This includes sales, marketing,and service automation.

Collaborative CRMcomprises the components and processesthat allow an enterprise to interact and collaborate with theircustomers. This includes voice technologies, Web store-fronts,e-mail, conferencing and face-to-face interactions.

24 JOURNAL OF RELATIONSHIP MARKETING


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Analytical CRMprovides analysis of customer data and behav-ioral patterns to improve business decisions. This includes theunderlying data warehouse architecture, customer profiling/seg-mentation systems, reporting, and analysis.

Building on the META Groups representation of a tripartite CRMecosystem, Payne and Frow (2005) proposed a strategic framework forCRM consisting of five interrelated cross-functional processes: thestrategy development process, value creation process, multi-channel in-tegration process, information management process, and performance

assessment process. Four of these five processes are subsumed withinthree forms of CRMStrategic, Operational, and Analyticalas shownin Figure 1.

Strategic CRM encompasses the strategy development process andthe value creation process, and therefore answers questions such aswhat business are we in?, which customers do we serve?, and howdo we create and deliver value to these customers? Operational CRMis focused on the management of the virtual and physical channelsthrough which customers and organization communicate and transact.Analytical CRM is focused on the development and exploitation of cus-tomer data. Figure 1 also illustrates how these three forms of CRM are

interrelated. Analytical CRM, for example, supports Operational CRMby feeding the right information at the right time to agents and channelsinteracting with customers (Payne, 2006; Payne & Frow, 2005).

Reiny Iriana and Francis Buttle 25

STRATEGIC CRM OPERATIONAL CRM

StrategyDevelopment

Process Value Creation Process

Multi-ChannelIntegration Process

Physical& VirtualChannels

Information Management Process

IntegratedChannel

Management

PerformanceAssessment

Process

ShareholderResults

PerformanceMonitoring

ANALYTICAL CRM

BusinessStrategy

ValueOrganization

Receives

ValueCustomerReceives

CustomerSegmentLifetimeValue

AnalysisCustomerStrategy

FIGURE 1. Strategic, Operational, and Analytical CRM


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CRM initiatives can also be classified according to their implementa-tion objectives. Organizations implement CRM to achieve certain busi-ness outcomes, which are reflected in their expectations of CRM. Xuand Walton (2005) provide examples of CRM objectives, including thefollowing: to improve customer satisfaction levels, to retain customers,to improve customer lifetime value, to deliver better strategic informa-tion to relevant departments, to attract new customers and to cut cost.An organization implementing an Analytical CRM project would aimto have better marketing and sales programs by collecting customer dataand analyzing relevant data into actionable information, resulting cus-tomers being offered an appropriate product, in suitable channels at the

right time. A company implementing an Operational CRM project mightbe keen to reduce cost-to-serve and improve transactional accuracy. Acompany implementing Strategic CRM project might be aiming to trans-form the business into a customer-centric organization with the goal ofincreasing customer profitability (Chye & Gerry, 2002; Hughes, 2002).

STRATEGIC, OPERATIONAL,AND ANALYTICAL CRM

We now explore in greater detail the three forms of CRM identifiedby Payne and Frow (2005)Strategic, Operational, and Analytical (SOA)CRM.

Strategic CRM. Buttle (2004) defined Strategic CRM as a top downperspective on CRM, which views CRM as a core customer centricbusiness strategy that aims at winning and keeping profitable custom-ers (p. 3). Plakoyiannaki and Tzokas (2002) explained that when CRMserves as a basic business strategy, it reflects a long-term vision of striv-ing to create and deliver value to customers. Lin and Su (2003) addedthat Strategic CRM gives the opportunity to leverage customer knowl-edge and create value for customers and, in the end, helps organizations

to understand and fulfill current and potential customers needs.Payne and Frow (2005) noted that an important goal in Strategic

CRM is to align the broader business strategy with customer strategy.They suggest that an understanding of business strategy issues, such ascorporate vision and industry and competitor profiles, can help an orga-nization develop Strategic CRM that is consistent vis--vis its own con-text. Customer strategy is concerned with aligning customer segmentsto relationship management strategies. The managerial discipline ofcustomer portfolio analysis (Turnbull & Zolkiewski, 1997) enables



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companies to carve up their current and potential customer base intosegments that can then be treated to specific relationship managementstrategies. Buttle (2004) identifies seven basic relationship strategiesfor identified segments: start a relationship, re-engineer the relation-ship, enhance the relationship, protect the relationship, harvest the rela-tionship, win-back the relationship, and end the relationship.

Payne and Frow (2005) explained that in the value creation process,business and customer strategy decisions are translated into implementa-tion programs that generate value for customers and organization alike.The main perspectives of the value creation process are the value thecustomer receives and thevalue theorganizationreceives. The value thecustomer receives is delivered by the value proposition of the organiza-tion. Organizations generally strive to develop offers that they believewill meet the needs and expectations of customers more effectively orefficiently than competing offers. The value the organization receives isthe return on investments in the value creation process. Customer Life-timeValue (CLV) is a metric that can be used to measure the customerspotential profit over a defined lifetime of transactions.

Operational CRM. Buttle (2004) defined Operational CRM as aperspective on CRM which focuses on major automation projects with-in the front-office functions of selling, marketing and service. Opera-

tional CRM automates the business processes underpinning the day-to-day tasks of sales, marketing, and service functions across a range ofcustomer touch points and channels. Sales force automation appliestechnology to the management of selling activities to optimize salesproductivity by improving the speed and quality of information flowto improve internal communications between the sales force and man-agement (Speier & Venkatesh, 2002; Tan et al., 2002). Tan et al. (2002)observe that marketing automation applies technology to marketingprocesses to help organizations manage their marketing programs. Sim-ilarly, service automation allowsorganizations to automate their service

operations, often with the objective of increased customer satisfactionby accelerating the inquiry and feedback processes across multiplecommunication channels. The general objective of Operational CRMis to improve the efficiency and effectiveness of customer manage-ment processes, by personalizing the relationship with customers, byimproving organizational response to customers needs (Xu & Walton,2005) and by increasing the speed and quality of information flows inthe organization, and between the organization and its external employ-ees and partners (Speier & Venkatesh, 2002).



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Payne and Frow (2005) point out that channel integration is animportant motivation for many Operational CRM system implementa-tions. This multi-channel integration process attempts to ensure consis-tency and high quality in the customers experience across differentcommunications and transaction channels.

Chan (2005) explained that Operational CRM data consists of trans-actional data from front-line customer touch points, such as sales,surveys, customer inquiries, and other customer interactions. Xu andWalton (2005) noted that Operational CRM data also exist in contact cen-tres and derive from contact management activities. Fayerman (2002)argued that data from back office functions, such as from human re-

sources and finance, might be needed for Operational CRM to functioneffectively.

Analytical CRM.Buttle (2004) defined Analytical CRM as a bot-tom-up perspective, which focuses on the intelligent mining of cus-tomer data for strategic or tactical purposes. Payne and Frow (2005)suggest that Analytical CRM refers to the information managementprocesses that rotate around the collection, accumulation, and analysisof customer information from customer interfaces. Knox, Maklan,Payne, Peppard, and Ryals (2003) explained that this informationmanagement process supports the strategy development process by

providing information about market characteristics that can be used todevelop customer strategy, as well as assist in the value creation pro-cess, determine customer lifetime value and develop new products andservices.

Analytical CRM uses technology to accumulate, store, organize,interpret, distribute, and exploit customer data. Customer informationmay be analyzed to develop customer profiles and opportunities thatwill be delivered to the touch points and channels for better OperationalCRM applications (Payne, 2006). Customer informationhelps the orga-nization to understand customer behavior better, to conduct the righttransaction at the right time, and to be able to segment its market effec-

tively (Plakoyiannaki & Tzokas, 2002; Xu & Walton, 2005).Herschel (2002) identified several applications within Analytical

CRM, including customer segmentation analysis, customer profitabil-ity analysis, what if analysis, real-time event monitoring and trigger-ing, campaign management, and personalization. Doyle (2002) alsosuggested other analytical tools such as, analysis of the characteristicsand behavior of customers, modeling to predict customer behavior,communications management with customers, personalized communi-cations with customers, interactive management and optimization to



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determine the best combination of customers, products, and communica-tions channels. Gebert, Geib, Kolbe, and Brenner (2003) claim that datawarehousing and data mining solutions are standard technology appli-cations in Analytical CRM.

Analytical CRM systems can increase revenue in many ways, such asthrough cross-sell and up-sell campaigns, predicting which customersare most likely to buy, identifying high value customers, increasingbrand awareness, and promoting customer satisfaction, loyalty and re-ferrals (SAS, 2002). Key success factors for Analytical CRM systemimplementation have been identified as the empowerment of manage-

ment through the sharing of customer information (Xu & Walton, 2005)andstrongteamworkbetween marketing andcustomer service (Herschel,2002). The lack of an integrated view of customers, insufficient cus-tomer intelligence, inability to act on customer intelligence quickly(SAS, 2002), and the lack of the awareness of the potential benefit ofAnalytical CRM (Xu & Walton, 2005) were identified as reasons forfailures to implement Analytical CRM systems effectively.

RESEARCH OBJECTIVES

Our research aims to develop an instrument that can be used to assess acompanys orientation towards Strategic, Operational or AnalyticalCRM (collectively SOA CRM). Our research process establishes whetherthese three forms of CRM are conceptually and operationally different.

Research Methodology and Analysis. Our method for creating thescale is broadly based on the recommendations of Churchill (1979) forthe development of better marketing constructs.

The Generation of Scale Items

Our literature review on CRM definitions and perspectives, which issummarized above, generated an exhaustive set of attributes that hadbeen used to describe and discriminate between different types of CRMinitiative. Appendix 1 contains the 32 items which appeared in our orig-inal pool of CRM descriptors, identifies which items were initially asso-ciated with each type of CRM and the position in which the itemsappeared in the questionnaire that we developed for the first stage of thescale refinement process.



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Scale Refinement

First Study

For the first study, a questionnaire was developed, piloted, refinedand distributed to a convenience sample of Executive Master of Busi-ness Administration (MBA) students who had taken one of three pre-sentations of an elective CRM course. The average age of the studentswas 32 years and the average length of business experience was 9 years.In total, 115 questionnaires were distributed and 48 responses or 41.7%were returned for analysis. Participants were asked to reflect on cus-

tomer management practices in their own organizations and to expressthe degree to which they agreed or disagreed that the 32 scale itemsdescribed the customer management practices of their own companies.Participants were advised that even though their organization may nothave developed a formal CRM strategy, it would have a de factoCRMstrategy with people, process, and technology used for the managementof customer relationships. A 7-point, Likert type response format wasused in which 1indicated that the respondent strongly disagreed with theitem statement and 7 indicated that the respondent strongly agreed withthe item statement.

The initial stage of scale reduction (purification) was performed usingtwo statistical processes: exploratory factor analysis as recommended byChurchill (1979) and item-total correlations (Nunnally, 1978).

Factor analysis is used to identify the underlying dimensions, or fac-tors, that explain correlations among variables (Malhotra et al., 2002).This process aims to discover whether a smaller number of factors canaccount for the variance within the data set. The Kaiser-Meyer-Olkin(KMO) measure was used to determine whether the data set was suitedto factor analysis. The KMO measure of sampling adequacy for ourdata is 0.811, a high value and close to 1, the perfect adequacy level(Malhotra et al., 2002). This supports the application of factor analysis

to the data. Bartletts test of sphericity also confirmed that the data weresuited to factor analysis.

The data set was factor analyzed using principal component analysisfollowed by varimax rotation. This generated a 7-factor solution, witheach factor having an eigenvalue exceeding 1. The 7-factor solutionaccounted for 77.85% of the variance. The results of the EFA are inAppendix 2.

Items with loadings of 0.40 or greater on more than one of the factorswere removed. This resulted in the removal of seven items that had been



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developed initially as Strategic CRM items (S7, S14, S20, S22, S26,S29, and S30), five items from the Operational CRM battery (O4, O6,O9, O10, and O11), and two items from the Analytical CRM battery(A12 and A13). The remaining 18 items were again factor analyzed, us-ingprincipal component analysis followed by varimax rotation. Based onthe SOA conceptualization of CRM, we made an a priorideterminationthat three factors would be retained (Hair Jr. et al., 1998). The KMO mea-sure of sampling adequacy was 0.846 and the Bartletts test of sphericitysignificance level was less than 0.05, both indicators again suggestingthat the data were suitable for factor analysis. The resulting 3-factor solu-

tion, as indicated in Appendix 3, accounted for 66.04% of the variance.To achieve a more parsimonious scale, the nine items loading on fac-tor 1 were analyzed using item-total correlations. Item-total correlationmeasures the correlation between a single scale item and the overallcomposite factor score. Items having low correlationsare candidates forelimination from the scale. This resulted in the removal of a further fouritems. At the end of the scale refinement process, 14 items remained,clustered, interpreted, and named as follows:

Factor 1: Strategic CRM. This factor comprises five items in total,made up of three items from the Strategic CRM inventory (S19, S21, andS28), and two items with the highest corrected item-total correlations,both initially associated with the Analytical CRM set (A31 and A32).

Factor 2: Analytical CRM. This factor comprises five items in total,made up of four items from the Analytical CRM inventory (A1, A2, A3,and A5), and one item initially associated with the Operational CRMset (O15).

Factor 3: Operational CRM. This factor comprises four items intotal, made up entirely of items initially associated with the OperationalCRM inventory (O16, O23, O24, and O25).

These factors are closely, but not perfectly, aligned with the a prioriclassification of Strategic, Operational, and Analytical CRM.

The reliability of each component or factor (Strategic, Operational,and Analytical CRM) and the overall (combined) scale were assessed bycomputing Cronbach alpha (Gerbing & Anderson, 1988). Reliabilities ofthe component scales are in the range of 0.751 to 0.891, with the overallCronbach alpha for the SOA scale being 0.904. These levels of reliabil-ity are satisfactory. In addition, according to a Monte Carlo study byGuadagnoli and Velicer (as cited in Stevens, 2002), constructs with fouror more loadings above 0.60 in absolute value are reliable, regardless ofsample size.



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Table 2 shows the model fit results for Strategic CRM after modifica-tion.

As shown in Table 2, Strategic CRM has a non-significant CMIN, and,with GFI and CFI both above 0.90, this is a strong indication that themodel fits the data well. Table 3 shows the final measurement instrumentconsisting of 13 items. This scale can be used to assess an organizationsorientation towards one or more of these three forms of CRM.

Reliability and Validity. The Strategic, Operational, and AnalyticalCRM scales have good reliabilities (above 0.60). However, reliabilitydoes not ensure validity (Hair Jr. et al., 1998). Satisfactory fit indices fora one-factor congeneric measurement model is evidence of good con-struct validity (Holmes-Smith et al., 2004). As shown in Tables 2 and 3,satisfactory model fit indices were achieved.

A more stringent test of validity is to determine the discriminant va-lidity of a construct. Discriminant validity among variables of a con-struct is achieved if the correlations between variables are significantlydifferent from 1. Large correlations above 0.80 or 0.90 suggest a lack ofdiscriminant validity (Holmes-Smith et al., 2004). The correlation coeffi-cients between Strategic, Operational and Analytical CRM variables

range from 0.296 to 0.582, which indicates good levels of discriminantvalidity (see Table 4).

CONCLUSION

The existing literature on CRM has identified three different but re-lated forms or types of CRMStrategic, Operational, and Analytical.We set out to determine whether it was possible to develop a scale that


TABLE 1. Model Fit Summary

Construct Items Reliability CMIN DF GFI CFI

Strategic 5 0.808 28.483* 5 0.901 0.856

Operational 4 0.746 5.383** 2 0.973 0.963

Analytical 5 0.833 14.064*** 5 0.948 0.953

*Significant at the 0.05 level.

**Not significant at the 0.05 level.

***Not significant at the 0.01 level.


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could discriminate between these forms of CRM. From a review of theliterature, we developed a set of items that appeared to have face valid-ity for describing these different types of CRM. In our first study, ex-

ploratory factor analysis and itemtotal correlations were performed ondata collected from 48 participants. This produced item loadings thatwere unexpected. Items did not load on the factors to which they wereconceptually related. Our interpretation of the forced three-factor solu-tion supported the idea that Operational and Analytical CRM were reli-able and useful constructs. The Strategic CRM inventory, however,needed further work.

In our second study, data were collected from 101 new participantsand we were able to modify the Strategic CRM item inventory. Theone-factor congeneric model results encourage us to suggest that the

Strategic, Operational, and Analytical CRM classification is a validconceptual model, and that it is possible to measure an organizationsorientation towards these three types of CRM. The final instrument con-sists of a 13-item scale that can be deployed in further CRM research.This is the first time that such a scale has been developed and published.

LIMITATIONS AND FURTHER STUDY

The major limitation of this research relates to the sample. Althoughthe sample size in our second study is within the desired level for reli-

ability and validity testing, the sample size of 101 limits the ability touse more sophisticated statistical analysis to provide additional supportfor the validity of the measures, for example, the use of ConfirmatoryFactor Analysis for the three forms of CRM in a single structural model.

This model will be used in future CRM-related research. We proposeto test whether CRM system implementation outcomes vary accordingto the type of CRM initiative. For example, we want to find out whichof the three types of CRM yield the fastest outcomes, the best lon-ger-term returns, is the easiest to implement, and has most significant


TABLE 2. Strategic CRM Model Fit SummaryAfter Modification

Construct Items Reliability CMIN DF GFI CFI

Strategic CRM 4 0.790 4.420* 2 0.979 0.979

*Not significant at the 0.05 level.


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TABLE 3. Refined Scale and Factor Loadings

Scale Items Loadings

Strategic Analytical Operational

Our CRM strategy aims to win and keep

carefully chosen customers or customer

segments

0.60

Our company is using CRM to ensure that all our

people understand which customers we want to

serve

0.74

Our company uses CRM to help us identifyhigh-value customers 0.71

Our company uses customer information to

construct customer profiles which are used to

improve the consistency of the customers

experience

0.76

An important objective of our CRM program is to

create a comprehensive customer-related database

0.67


deliver customer data to our people at the right time

so that they can cross-sell and up-sell customers

0.58


deliver customer data to our front-line staff so that

they can sell, market and service our customers

more effectively

0.57

An important objective of our CRM program

is to enable us to conduct intelligent analyses

of customer data to guide our marketing and

sales efforts

0.77


improve the productivity of our sales people

0.82

An important objective of our CRM program

is to reduce the cost of our customer-interface

operations

0.42

Our company uses CRM to automate customer

service processes to make them more efficient

and effective

0.71

Our company uses CRM to automate marketing

processes to make them more efficient and

effective

0.59

Our company uses CRM to automate selling

processes to make them more efficient and

effective

0.84


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APPENDIX 1

The Initial Pool of Scale Items

Strategic CRM

S7. An important objective of our CRM program is to enhancethe lifetime value of our customers

S14. An important objective of our CRM program is to improveour understanding of customer needs, expectations, and preferences

S19. An important objective of our CRM program is to lift customer

satisfaction and retention levelsS20. CRM provides the basis for our competitive advantage

S21. Our CRM strategy aims to win and keep carefully chosencustomers or customer segments

S22. Our CRM strategy creates mutual benefits for bothcustomers and company

S26. Our company uses CRM to create a customer-focusedbusiness culture

S28. Our company uses CRM to ensure that all our peopleunderstand which customers we want to serve

S29. Our company uses CRM to help us be more customerfocused than our competitors

S30. Our company uses CRM to find better ways of offeringcustomers more value

Operational CRM

O4. An important objective of our CRM program is to enableus to adapt our offers to suit different customers requirements

O6. An important objective of our CRM program is to enable usto select the most appropriate communication channels

for interaction with customersO9. An important objective of our CRM program is to help

our marketing people run more effective and efficient campaigns

O10. An important objective of our CRM program is to help our salespeople to have more effective and efficient interactions with customers

O11. An important objective of our CRM program is to improvecollaboration with our customers and channel partners

O15. An important objective of our CRM program is to improvethe productivity of our sales people


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APPENDIX 2

Factor Loadings for the Initial 7-Factor Solution

Component or Factor

1 2 3 4 5 6 7

A31 0.785 0.225 0.318 0.144 0.191 0.084 0.041

S28 0.774 0.205 0.121 0.144 0.080 0.033 0.057

A32 0.706 0.129 0.290 0.288 0.209 0.222 0.143

A27 0.702 0.392 0.284 0.158 0.213 0.091 0.057

S30 0.656 0.270 0.454 0.346 0.070 0.158

0.045

O10 0.595 0.535 0.162 0.043 0.108 0.196 0.232

S14 0.576 0.153 0.435 0.222 0.346 0.144 0.286

S29 0.571 0.328 0.494 0.114 0.046 0.224 0.108

S26 0.544 0.305 0.300 0.290 0.401 0.118 0.094

O15 0.152 0.852 0.097 0.025 0.044 0.273 0.094

A2 0.209 0.750 0.242 0.209 0.083 0.052 0.005

A3 0.361 0.742 0.179 0.019 0.116 0.186 0.167

A5 0.196 0.673 0.271 0.326 0.087 0.007 0.007

A1 0.159 0.640 0.266 0.245 0.188 0.013 0.134

S21 0.292 0.306 0.805 0.074 0.029 0.045 0.159

S20 0.404 0.218 0.706 0.136 0.196 0.238 0.037

S22 0.458 0.116 0.635 0.133 0.061 0.183 0.111

O4 0.157 0.406 0.611 0.391 0.237 0.033 0.058

S19 0.339 0.121 0.603 0.353 0.122 0.122 0.356

A8 0.388 0.360 0.077 0.706 0.173 0.119 0.116

S7 0.098 0.188 0.549 0.685 0.068 0.088 0.024

O6 0.200 0.120 0.341 0.599 0.407 0.096 0.180

O9 0.501 0.262 0.012 0.588 0.024 0.202 0.267

O18 0.242 0.029 0.383 0.489 0.332 0.215 0.306

A13 0.083 0.195 0.518 0.100 0.691 0.065

0.004

O11 0.420 0.054 0.016 0.293 0.642 0.211 0.264

A12 0.311 0.572 0.147 0.056 0.576 0.133 0.088

A17 0.252 0.340 0.386 0.341 0.455 0.146 0.252

O25 0.005 0.385 0.013 0.132 0.104 0.817 0.008

O23 0.173 0.051 0.151 0.106 0.240 0.792 0.207

O24 0.253 0.069 0.376 0.251 0.249 0.645 0.178

O16 0.050 0.150 0.091 0.058 0.075 0.201 0.854


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APPENDIX 3

Factor Loadings for Forced 3-Factor Solution

Component or Factor

1 2 3

A32 0.836 0.186 0.221

A31 0.831 0.297 0.046

A27 0.727 0.492 0.004

S19 0.722 0.161 0.323

O18 0.700 0.030 0.391

A17 0.669 0.326 0.356

S28 0.625 0.304 0.069

S21 0.615 0.330 0.222

A8 0.568 0.465 0.017

O15 0.062 0.871 0.272

A3 0.319 0.781 0.226

A2 0.317 0.776 0.078

A5 0.401 0.686 0.055

A1 0.381 0.660 0.105

O23 0.203 0.081 0.795

O24 0.502 0.150 0.679

O25 0.068 0.434 0.672

O16 0.094 0.040 0.640

Strategic Operational Anlytical CRM JRM

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