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Strategic and organisational determinants of sophistication in deployed sales force automation systems within three industry sectors in the UK a

b

Bill Donaldson , Jong-Ho Lee & George Wright a

Robert Gordon University , UK

b

Korea University Business School , Korea

c

c

Warwick University , UK Published online: 11 Oct 2012.

To cite this article: Bill Donaldson , Jong-Ho Lee & George Wright (2012) Strategic and organisational determinants of sophistication in deployed sales force automation systems within three industry sectors in the UK, Journal of Marketing Management, 28:11-12, 1305-1330, DOI: 10.1080/0267257X.2012.691527 To link to this article: http://dx.doi.org/10.1080/0267257X.2012.691527

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Journal of Marketing Management Vol. 28, Nos. 11–12, October 2012, 1305–1330

Strategic and organisational determinants of sophistication in deployed sales force automation systems within three industry sectors in the UK


Bill Donaldson, Robert Gordon University, UK Jong-Ho Lee, Korea University Business School, Korea George Wright, Warwick University, UK Abstract This paper investigates strategic and organisational context determinants of the sophistication of adopted sales force automation (SFA) systems in three UK industries: financial services, pharmaceuticals, and building/construction. Sophistication of adopted systems is associated with the organisation placing greater emphasis on information orientation, which is itself driven by an increased integration of IT and sales coupled with increased organisational slack. Increased integration of IT and sales is itself driven by increased strategic importance of sales coupled with increased use of internal communication networks. Importantly, a firm’s marketing orientation, although also driven by the strategic importance of sales, has no impact on either information orientation or SFA sophistication. We discuss the implications of our findings to aid understanding of SFA implementation failure. Keywords sales force automation; sophistication of SFA systems; system implementation

Introduction Adoption of sales force automation (SFA) systems can be conceptualised to be a two-stage process. Initially, the organisation makes a decision to adopt a SFA system, followed by an implementation focus on encouraging the use of the SFA by individual salespeople (Parthasarathy & Sohi, 1997). Indeed, it has been confirmed that there are clear distinctions between organisational and salesperson perspectives on the goals, benefits, and obstacles associated with SFA (Honeycutt, Thelen, Thelen, & Hodge, 2005). Although many SFA projects have been classified as unsuccessful, Rivers and Dart (1999) have noted that the academic community ‘. . . remains silent in terms of reporting factors associated with SFA adoption and use’ (p. 60). In fact, the majority of research that has been conducted has focused at the level of the individual salesperson. Individual-level factors such as ISSN 0267-257X print/ISSN 1472-1376 online © 2012 Westburn Publishers Ltd. http://dx.doi.org/10.1080/0267257X.2012.691527 http://www.tandfonline.com


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perceived ease of use and perceived usefulness have been shown to be important in the initial acceptance of SFA technology by salespeople (Venkatesh, 2000). Venkatesh and Davis (2000) extended this latter investigation by using three points of measurement: pre-implementation, immediate post-implementation, and three months post-implementation. These authors found that social influence – whether an individual perceived that other individuals who were important to him/her were positive or not about the technology – was also important to salespeople’s acceptance of SFA, as were factors such as job relevance, perceived quality of the output of the technology, and perceived ease of use. Venkatesh and Davis found that these factors accounted for about 50% of the variance in usage intentions by members of the sales force. However, we note that the majority of the applications of the SFA technology were initiated by companies rather than by salespeople. This may be because, as Widmier, Jackson, and McCabe (2002) argued, the sales managers saw the SFA technology as a ‘. . . very useful tool in managing the sales force’ (p. 194). The extant studies indicate that adoption of SFA systems are driven by managerial imperatives – such as cost control and the wish to control and manage the sales force – and that, subsequently, usage of adopted systems may be resisted by the sales force. By contrast, with the focus on the role of the individual salesperson in SFA adoption, other, more general, studies of information systems adoption and customer relationship management (CRM) have focussed on organisational-level variables (e.g. Jones, Sundaram, & Chin, 2002; Ragowsky, Stern, & Adams, 2000) and have linked the sophistication of management information systems to organisational structure (Raymond, Pare, & Bergeron, 1995). Effective use and sophistication of CRM is achieved by matching organisational capabilities to market context – rather than by an uncritical adoption and development of systems (Ryals & Knox, 2001). Successful system implementation requires close integration with an organisation’s competitive strategy (Erffmeyer & Johnson, 2001). Studies on the unsuccessful adoption of SFA and CRM point to a failure by the organisation to align the technology with sales processes (Cooper, Gwin, & Wakefield, 2008) and with the needs and requirement of customers (Buttle, Ang, & Iriana, 2006). For this reason, the present study is focused at the level of the organisation, and investigates the effects of selected strategic and organisation variables on the sophistication of adopted SFA. Does the study of organisational-level variables aid our understanding of SFA sophistication, once adopted? We investigate the current usage and sophistication of SFA within three industries in the UK: financial services, pharmaceuticals, and building/construction. The logic for our selection of these three industries is detailed later.

Theoretical background In this paper, we make a case as to why firms adopt, invest, and deploy resources in SFA systems. Our perspective is in line with recent calls to consider sales as a strategic issue (Piercy & Lane, 2011), and while much research interest has focussed on adoption/non-adoption at the level of the individual salesperson, SFA deployment is a managerial issue which, we argue, is dependent on both strategic and organisational, including people, issues acting as predictors of SFA sophistication. Put simply, firms adopting and deploying sophisticated SFA systems will have different characteristics,

Donaldson et al. Sophistication in sales force automation

Figure 1 Research model. H1

Strategic Importance of Sales

Marketing/customer Orientation

H2 H3

Organisational Slack

H4

H15 H13

H5 H6

Information Orientation

H7

H16

Sales campaign evaluation


H8 Organisational Control

H9

H14

H17

H10 Internal Network

H11 H12

Integration of IT and Sales

both strategically and at the organisational level, from those who do not have sophisticated systems. The research reported in this paper measures a number of organisational and strategic variables and relates them to SFA sophistication – evaluated as measures used in sales campaigns. Our focus is on understanding the way in which internal strategic and ‘people’ issues relate to SFA sophistication. See Figure 1. Strategic importance of sales Hunter and Perreault, (2007) have argued that ‘the strategic importance of the sales force to the organisation’s success may be at an all-time high’ (p. 16), noting that this change has been the result of a move from transaction to relationshipbased selling. This change has altered the activities that many salespeople perform (Marshall, Moncrief, & Lassk, 1999; Moncrief, Marshall, & Lassk, 2006) and changed the emphasis to sales as a value-added activity. Rackham and DeVincentis (1999) argue that there are three types of selling – transaction, consultative, and enterprise selling – which require different strategic perspectives and by implication different sales solutions. Together with the importance of key account management and customer orientation (Ingram, Laforge, Avila, Schwepker, & Williams, 2001; Ryals, 2008; Spiro & Weitz, 1990), sales has become of strategic importance to the firm. This strategic importance, to be effective, requires, inter alia, more relevant and timely information, increased knowledge about customers, recognition of the importance of key accounts, and adequate organisational response via people and technology. Thus we propose: H1: There is a positive relationship between perceived strategic importance of sales decisions and the level of marketing/customer orientation. H5: There is a positive relationship between perceived strategic importance of sales decisions and the level of information orientation.

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H9: There is a positive relationship between perceived strategic importance of sales decisions and the integration of IT and sales.


Integration of IT and sales The successful strategic application of IT requires not only a recognition of the strategic importance of certain functional decisions, but also the integration of business and IT strategy and a common understanding of aims, objectives, and needs from users and suppliers of the IT system (Venkatraman, 1994). Organisations with little integration of IS strategy with business strategy have a greater likelihood of implementation difficulties (Baets, 1992). Thus, for successful deployment of sophisticated SFA, functional areas should themselves be involved in the strategic planning process (Hammer & Mangurian, 1987; Venkatraman, 1994), and so, in the context of SFA applications, marketing and IT investment decisions should be linked and integrated (Le Meunier-Fitzhugh & Piercy, 2007). The integration of marketing and IT personnel into ‘strategic’ activities and decisions is thus likely to increase the probability that an IT-based sales strategy, such as SFA, is implemented in the form of sophisticated systems. Thus it is proposed that: H14: There is a positive relationship between integration of IT and sales and the level of information orientation. H17: There is a positive relationship between integration of IT and sales and the sophistication of SFA systems.

Information orientation The interaction of people, information, and technology establishes an orientation towards the use of information within a company, which in turn may affect business performance (Marchand, Kettinger, & Rollins, 2001). We link information orientation to the ease of use and capabilities of information-gathering systems. Similarly, Sinkula (1994) sees organisational learning as the acquisition, distribution, and interpretation of knowledge. Our own conceptualisation of information orientation has similarities with the concept of IT maturity and the ability of systems to provide relevant and sophisticated information. A high degree of information orientation thus represents the progress of the IT function into the strategic IT era (Sabherwal & Vijayasarathy, 1994) and as having the orientation necessary to support a strategic marketing application such as SFA. Adequate information capture, reciprocity, access, and use have been identified as important in an individual’s ability to use information for sales improvement (Jayachandran, Sharma, Kaufman, & Raman, 2005). In the sales-specific context, increasing emphasis on customerspecific knowledge and its use in influential key accounts has been recognised as a source of competitive advantage (Salojarvi, Sainio, & Tarkiainen, 2010). Hence, we assert that: H16: There is a positive relationship between the level of information orientation and the sophistication of SFA systems.



Marketing orientation Marketing orientation is understood as the degree to which the organisation has assimilated the marketing concept. The marketing concept represents a ‘cornerstone of marketing thought’ (Jaworski & Kohli, 1993) and the importance of a marketorientated business culture has been well reported in the literature (Baker, 1985; Day, 1990; Narver & Slater, 1990; Shapiro, 1988). Investigation into this has tended to focus on the concept of a market orientation (Jaworski & Kohli, 1993; Slater & Narver, 1995). The term ‘market orientation’ refers to the ‘the organisation wide generation of market intelligence, dissemination of intelligence across departments and organisation wide responsiveness to it’ (Jaworski & Kohli, 1993, p. 57). While this definition is useful, it is important to distinguish between market orientation and the term used in this study, marketing orientation (Sharp, 1991). Marketing orientation relates to a fuller interpretation of the marketing concept in that it is not solely a matter of market and customer responsiveness. It involves choosing markets and managing its productive capacities in order to achieve its goals, the essential matching element of the marketing concept. Furthermore, it involves commitment to strategic long-term thinking, and matching the company objectives and capabilities with customer demands. For SFA systems to operate in a sophisticated way, a customer relationship orientation is a key underpinning (Jayachandran et al., 2005). In this context, selling cannot be viewed as a stand-alone function but is an integrated part of the overall marketing mix, which defines the value proposition. This focus on customers’ needs and wants requires the organisation to identify those customer segments whose needs and wants it can satisfy better than competitors (Day, 2000). For salespeople, it means that sales territories are no longer based solely on geographical areas but on specific customer segments (Rackham & DeVincentis, 1999) and customer appraisal (Hunter & Perreault, 2007). Effective deployment of SFA utilises the intelligence of the system rather than simply on the talent of the sales force (Quinn, Anderson, & Finkelstein, 1996). We hypothesise that: H13: There is a positive relationship between the level of marketing/customer orientation and the level of information orientation. H15: There is a positive relationship between the level of marketing/customer orientation and the sophistication of SFA systems.

Organisational slack and control Organisational slack is a term first coined by Cyert and March (1963) and can be defined as the degree to which uncommitted resources are available to an organisation. Slack helps individuals by influencing the perception of availability of knowledge, resources, and opportunities and hence encourages higher levels of sophistication in adoption. This situation can lead to excesses, however, resulting in the demand for more organisational control. In a control environment, financial and performance management systems are used to ensure that IS activities are effective and efficient. Whereas, in the slack environment, sophisticated controls are absent and more resources are available than are strictly necessary to get the job done. Nolan (1979) pointed out that the balance of these two variables is important in understanding the stage of organisational learning that the organisation has reached

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with regard to its IT development. Individuals’ perception of the balance of these two variables will be key variables in understanding personal intention and behaviour (Ajzen, 1991) and has been shown to be relevant in the acceptance of information systems (Mathieson, 1991; Taylor & Todd, 1995; Venkatesh, 2000). Several related hypotheses can be postulated. With regard to organisational slack: H2: There is a positive relationship between organisational slack and the level of marketing/customer orientation. H6: There is a positive relationship between organisational slack and the level of information orientation.


H10: There is a positive relationship between organisational slack and the integration of IT and sales.

With regard to organisational control: H3: There is a negative relationship between organisational control and the level of marketing/customer orientation. H7: There is a negative relationship between organisational control and the level of information orientation. H11: There is a negative relationship between organisational control and the integration of IT and sales.

Internal networks Knowledge-led organisations increasingly recognise the importance of personal or tacit knowledge, as well as explicit knowledge, which is more easily handled by software tools. The growth of internal networks expedites the flow of personal knowledge within and between organisations – which may facilitate the willingness to accept the transfer of explicit knowledge. In the context of SFA, where system relevance and applications cross industry boundaries, there is a greater likelihood of the organisational members utilising outside sources of information (Parthasarathy & Sohi, 1997). These social network structures are rarely examined in technology adoption studies, although Rogers (1983) specifically recommends such study. Individual usage of new technology is influenced not only on how many of the individuals peers use that technology, but also on the proximity of those peers (Krackhardt, 1994). Interconnectedness is positively associated with organisational innovativeness and is the degree to which the units in the organisation are linked by interpersonal networks, allowing new ideas to flow more easily and rapidly (Anderson, 2000). This is important for the sales function which requires crossfunctional collaboration to achieve its goals (Duncan & Moriarty, 1998; Hauser, Simester, & Wernerfeldt, 1996; Lukas & Maignan, 1996; Menon & Jaworski, 1997). Given the importance of intra-organisational and cross-functional team working to marketing success (Lukas & Maignan, 1996), this is an important element in the present study. The existence of formal and informal internal networks is likely to be positively related to the adoption of strategic IT interventions such as SFA. Thus we hypothesise that:


H4: There is a positive relationship between the presence of internal networks and the level of marketing/customer orientation. H8: There is a positive relationship between the presence of internal networks and the level of information orientation.


H12: There is a positive relationship between the presence of internal networks and the integration of IT and sales.

Our model, Figure 1, shows that the increasing strategic importance of sales and the increasing integration of IT and sales will both act to increase the information orientation of the firm. Additionally, increases in the strategic importance attached to sales decisions will also impact the integration of IT and sales and the market/customer orientation of the firm. Also, increases in organisational slack, decreases in organisational control, and the increased presence of internal networks will act to increase (i) the firm’s information orientation, (ii) the integration of IT and sales, and (iii) the market/customer orientation of the firm. Next, increases in the market/customer orientation of the firm will impact on the information orientation of the firm. Finally, the market/customer orientation of the firm, the information orientation of the firm, and the degree of integration of IT and sales will exert an additive impact on the level of sophistication of information held on customers – evaluated as the measures used to assess the results of sales campaigns. Industries studied To assess variability in SFA adoption and sophistication, we chose to survey in three separate industries: financial services, pharmaceuticals, and building/construction. The UK financial services industry has experienced unprecedented change through new entrants to the market, mergers and acquisitions, international competition, and new delivery channels – such as self-selection of tailored, financial products via the Internet. In this climate, the industry has come under increased scrutiny in terms of its sales and marketing practices, and much of the focus has been on the use of information technology to collect and use information about existing and prospective clients and their accounts. The banks in particular have traditionally been hostile to the marketing concept (Ryals, 2008), and thus, whilst the industry typically has a high level of computerisation, this has tended to be an aid in transaction processing (i.e. back-office application) rather than strategic or front office in application. More recently, there was evidence that this is changing as part of the overall industry drive to adopt e-commerce. The pharmaceutical industry has been, traditionally, sales driven and product led. Thus, while the industry typically has a high level of computerisation, this has tended to be an aid in transaction processing rather than strategic in application. More recently, there has been evidence that while pharmaceutical companies are becoming more market-oriented, they have not implemented the systems necessary to support such an orientation – investment in CRM and sales automation is a relatively new focus of investment in the pharmaceutical industry (George & Pearson, 2002). In the UK, despite a growing market driven by an ageing population, scientific developments, new treatments, and speedier drug discovery, there is intense competition – which has led to a decline in margins and more mergers and acquisitions. According to one source, Marketing cost is increasing as a percentage of

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sales, and pharmaceutical companies are now increasing their spend on advertising. In this climate, the costs to generate increased awareness and improve customerfocused service make it vital that resources, especially personal sales resources, are efficiently and effectively deployed both before a product reaches the market and in the early stages of product launch. The building and construction industry is an important part of the British economy, has long been a barometer for the UK’s economic well-being, and is highly susceptible to economic fluctuations. Traditionally, it is an industry characterised by ‘sales push’ rather than ‘demand pull’ – with emphasis on (i) personal selling to architects and specifiers and (ii) service selling to intermediaries such as builders’ merchants and contractors themselves.

Research methodology and sample characteristics Our study focuses on three industries – financial services, pharmaceuticals, and building/construction – and a particular sales application of IT, SFA. Our measures examine both the technology of SFA and the information that is contained within SFA systems to support the activities of the sales force. Our questionnaire items were pretested within qualitative interviews with consultants from IBM and Merial about the changing role of salespeople and the way in which salespeople add value in the new information age. Our study is based on a quantitative survey of a sample of named sales and marketing managers in: (i) all UK banks, building societies, and insurance companies; (ii) all UK-based pharmaceutical firms; and (iii) all UK-based building and construction firms. We used secondary sources to identify firms that did not have a field sales force. Five hundred companies were finally selected – based on our own judgement – that would have a sizeable sales force. Next, telephone contact was established to ensure that the companies had a sales force and to ensure the contact was current and relevant. After follow-up phone calls and one repeat mailing, 220 usable responses to our mailed questionnaire were received – 72 from financial services, 69 from pharmaceuticals, and 79 from building and construction. The sample response rate was compared to the industry structures and found to be representative of all three industries – whilst favouring larger firms with a substantial sales presence. We found no differences in the sales-force size profiles of early and late respondents. Table 1 gives a headcount summary of the nature of our obtained samples. Our information sophistication measure counted the number of types of results of sales campaigns that are measured by a firm. The exact questions used are given in Appendix 1. The list of types of information held on deployed SFA systems was generated on the basis of the Datamonitor (2001) report and analysis of SFA systems and their capabilities. SFA design objectives were to increase customer retention, cross-selling, targeting of sales and marketing activity, analyses of customer profitability, and servicing customers via multiple channels. Across these objectives, the major focus was found to be on the use of data to facilitate customer retention – as opposed to an alternative focus on customer acquisition. Our count of the number of types of results of sales campaigns that are measured by a firm thus distinguishes those with little data capture (e.g. record of a customer’s



Table 1 Nature of the firms within the three industries: mean (and median) headcounts.

Firm size

Outside sales people

Inside sales people

Total customer services and sales

Financial services N Valid Missing Mean Median Minimum Maximum

71 1 3263 500 12 70,000

63 9 243 25 .0 2000

63 9 299 20 .0 12,000

65 7 1265 170 3 25,000

Pharmaceuticals N Valid Missing Mean Median Minimum Maximum

68 1 3027 250 7 75,000

62 7 77 18 .0 900

65 4 29 4 .0 1150

67 2 103 20 .0 1000

Building/construction N Valid Missing Mean Median Minimum Maximum

79 0 1360 550 4 30,000

71 8 31 8 .0 500

76 3 24 6 .0 300

73 6 73 14 .0 700

name, address, number of sales achieved, etc.) from those with more extensive data analysis (e.g. effectiveness of different contact strategies, degree of relationship enhancement, etc.). Thus the count realistically separates high and low sophistication and reflects actual usage of installed SFA systems from intention to use – see Jones et al. (2002) for further discussion and evaluation of this issue. In our UK-based study, the American term ‘Sales Force Automation’ was replaced by the UK term ‘Sales Information System’, since pretesting revealed that the latter term was the common parlance for SFA in the UK. We evaluated adoption of SIS/SFA by asking the respondent two linked questions: 1. A Sales Information System has been defined as ‘the collection of information to assist the sales and customer management process’. Do you have a Sales Information System? Yes/No 2. Do you have an automated (computer-based) Sales Information System? Yes / No

Almost all of our 220 firms claimed to be using some form of automated sales information system. For those who indicated that they had an automated

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computer-based system, we asked the name of system and its vendor. These systems are now widely available and used by most companies. In our sample, 99% had some form of system and 98% claimed to have an automated SIS. The average time they had been using such systems was seven years. The level of perceived sophistication was however, found to be variable. Using the seven-point scale, ranging from 1 = ‘low level’, most perceived themselves as about 4 (M = 4.20, SD = 1.65). From our data, we matched responses to the known capabilities of the installed systems. We found no evidence of the use of very-low-level applications that would not support the strategic use of the information collected for sales analysis. Our subsequent analysis thus focuses on the total sample of 220 firms who, to differing degrees, measured the results of sales campaigns. Measurement of strategic and organisational variables The scale development methodology is detailed in Fletcher and Wright (1997). In that study, question development was focussed on issues to do with the uptake of database marketing (DBM). In the present study, we utilise the same scales but alter the wording of specific questions to address SFA – rather than DBM – contextual issues. Because of these slight changes, we present, in the current paper, in-sample reliability estimates for the altered scales. Appendix 2 details the individual questions that made up our seven measures. Cross-industry comparisons Two strategic variables and five organisational variables may be conceptually related. Therefore, we used MANOVA analysis for industry comparison with two strategic variables and five organisational variables. For dependent variable, we used ANOVA analysis. First, we ran MANOVA analysis using industry types as independent variables and two strategic variables (Strategic Importance of Sales, Integration of IT and Sales) as dependent variables. Wilks’ lambda (F = 8.284, p = .00) was statistically significant with Integration of IT and Sales. We also ran MANOVA to test the effect of industry type on five organisational variables (Information Orientation, Marketing Orientation, Organisational Slack, Organisational Control, Internal Network). Wilks’ lambda (F = 8.284, p = .416) was not statistically significant. Cross-industry comparisons of the obtained mean scores on our two strategic variables and our five organisational variables revealed only three significant differences out of 24 possible paired comparisons. Since between-industry comparisons would have reached significance by chance alone (at the 5% level of significance), we treat these findings with caution. See Table 2 for the descriptive summary statistics. The differences that we found were: • Pharmaceuticals evidenced more strategic construction (mean differences = 7.16, p = .00).

integration

than

building/

• Financial services evidenced more strategic integration than building/ construction (mean differences = 7.86, p = .00). • Financial services evidenced greater measurement of the results of sales campaigns than building/construction (mean differences = 2.44, p = 0.00).


Table 2 Between-industry comparisons on the questionnaire scales: MANOVA. Variables Strategic variables

Industry type Financial Pharmaceuticals Building/Construction Financial Pharmaceuticals Building/Construction Financial Pharmaceuticals Building/Construction Financial Pharmaceuticals Building/Construction

M (SD) 14.96 (3.32) 15.32 (2.84) 14.76 (2.86) 43.39 (8.67) 42.70 (8.41) 35.53 (10.32) 63.28 (17.36) 57.29 (18.14) 59.95 (16.35) 65.15 (12.46) 64.61 (12.38) 64.73 (12.50)

Financial Pharmaceuticals Building/Construction Financial Pharmaceuticals Building/Construction Financial Pharmaceuticals Building/Construction

8.03 (3.24) 7.96 (3.15) 8.52 (3.37) 6.86 (2.84) 6.84 (3.03) 7.71 (3.26) 11.07 (2.68) 10.68 (2.45) 10.56 (2.52)

Count of the Financial Results of Sales Pharmaceuticals Campaigns Building/Construction

8.39 (4.24) 7.19 (4.14) 5.95 (3.89)

Strategic Importance of Sales Integration of IT and Sales


Information Orientation Marketing Orientation Organisational variables

Organisational Slack Organisational Control Internal Network

Dependent variable

F

Sig.

.65

.53

16.92

.00

1.92

.15

.11

.89

.41

.67

1.65

.20

1.12

.33

6.71

.00

From this set of analyses, we conclude that there is little difference between our three industry samples to distinguish them in terms of our measurement scales. For this reason, we next aggregate the samples to investigate our research model. Note, also, that a group difference check is an integral part of our structural equation modelling (see later). Here, a multiple-group confirmatory factor analysis confirmed that the units of measurement are equivalent across the three industries studied in the full structural equation model.

Investigation of our research model Table 3 details the headcount summary of our combined sample and Table 4 sets out the mean, standard deviations, and reliabilities of our seven questionnaire measures. To determine whether samples from financial service, banking, and building could be combined for the subsequent assessment procedures, we tested whether metric invariance is supported for the multi-item constructs measured by reflective indicators (Steenkamp & Baumgartner, 1998). As recommended by Steenkamp and Baumgartner (1998), we used multiple-group confirmatory factor analysis to test for metric invariance, which implies that the units of measurement are equivalent across groups.

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Table 3 Nature of our aggregated sample. Mean 2,500 114 111 460

Total number of employees Number of outside sales force Number of inside sales force Total number in sales and service

Median 400 14 8 36


Table 4 Means, standard deviations, and reliability estimates obtained on the questionnaire measures for our aggregated sample.

Strategic Importance of Sales Decision Strategic Integration of IT and Sales Information Orientation Organisational Slack Organisation Control Marketing Orientation Internal Network Dependent measure: count of the number of types of results of campaigns that are measured

M 15.06 40.56 60.63 8.21 7.18 64.92 10.76 7.14

SD 2.99 9.74 17.23 3.24 3.06 12.45 2.55 4.19

Cronbach alpha .83 .84 .87 .89 .83 .84 .85 N/A

Goodness of fit of the research model In order to test for differences in the factor structure across the observed industries, we have to test for measurement invariance. We defined this invariance as equality of measurement weights. This metric invariance is mandatory for comparing the relationships between latent constructs across groups (Steenkamp & Baumgartner, 1998). To test the multi-group model, the unconstrained original model has to be compared to the more restrictive nested model assuming measurement invariance. In the first step, we analyse the measurement model by conducting an unconstrained multi group confirmatory factor analysis (MGCFA) to check for configural invariance. Configural invariance implies the same number of factors in each group and the same pattern of fixed and free parameters. It is a prerequisite for the other tests. Metric invariance implies equal factor loadings across industries. Equal factor loadings indicate that the groups calibrate their measures in the same way. According to Steinmetz, Schmidt, Tina-Booh, Wieczorek, and Schwartz (2009), metric invariance is necessary to infer that the construct has the same meaning because it provides evidence about the equality of validity coefficients. Invariance of the factor covariances refers to equality of the associations among the latent variables across industries. Covariances among constructs have implications for the constructs’ meaning or validity (Cronbach & Meehl, 1955). Hence, unequal covariances raise concerns about equality of construct meanings (Cole & Maxwell, 1985). As summarised in Tables 5 and 6, the hypothesised model holds up well when tested against the sample of 220 UK respondents (72 financial services, 69 pharmaceuticals, and 79 building/construction). Table 5 displays the fit indices


Table 5 Goodness of fit information. Model Configural invariance Full metric invariance Invariance of factor covariances

χ 2 (df) 2542.994 (1272) 2603.920 (1324) 2620.808 (1344)

χ 2 (df) − 59.926 (52) 76.814 (72)

RMSEA .053 .052 .052

CFI .952 .951 .952

CAIC 3160.994 3117.920 3094.808

TLI .944 .945 .946


Table 6 Research model fit indices. Degrees of freedom χ2 RMSEA NFI CFI IFI GFI

5 4.93 .0 .9788 1.000 1.000 .9944

for the models that tested measurement invariance. The initial model that assessed configural invariance resulted in an acceptable fit (χ 2 (1272) = 2,542.99, RMSEA = .053, CFI = .952, CAIC = 3160.99, TLI = .944). The second step, testing full metric invariance, also yielded an acceptable fit: the chi-square increase was not significant (χ 2 (52) = 59.926, p > .05). Constraining the factor covariances to be equal across the industries does not significantly increase the chi-square (χ 2 (72) = 76.814, p > .05). The result of this analysis indicated that metric invariance was supported, which enables us to combine data from financial services, pharmaceuticals, and building/construction. The chi-square value is not statistically significant with five degrees of freedom1 and the chi-square value (4.93) is close to the degrees of freedom (five), which suggests a good fit. The root mean squared error of approximation is .0, which suggests a good fit, since it is below the critical point .08, as suggested by Browne and Cudeck (1989). Further, the normed fit index, the comparative fit index, the incremental fit index, and the goodness of fit index are all between .9788 and 1, suggesting that the research model fits the observed data well (see Tables 7 and 8). Figure 2 gives our obtained model with the significant pathways emboldened. As can be seen, an increased count of the result of sales is driven by a firm’s increasing information orientation and an increased degree of integration of IT and sales. Increased information orientation is itself driven by an increased integration of IT and sales coupled with increased organisational slack. Increased integration of IT and sales is itself driven by increased strategic importance of sales coupled with increased internal networks. Interestingly, marketing orientation, although also driven by the strategic importance of sales, has no impact on either information orientation or that the null hypothesis in the χ 2 test is that there is no difference between the covariance matrix predicted by the model and the observed data, an insignificant result suggests a perfect fit.

1 Given

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Table 7 Correlation matrix of variables.


Variables 1 2 3 4 5 6 7 8 1. Marketing Orientation 1.000 2. Information Orientation .291 1.000 3. Integration of IT and Sales .125 .313 1.000 4. Sales Campaign Evaluation .131 .405 .335 1.000 5. Strategic Importance of Sales .324 .179 .203 .170 1.000 6. Organisational Slack .348 .437 .007 .121 .077 1.000 7. Organisational Control .046 .041 −.093 −.099 −.047 .111 1.000 8. Internal Network .170 .120 .211 .114 .235 .091 −.231 1.000

Table 8 Hypothesis tests for the research model.

Hypothesis 1 Hypothesis 2 Hypothesis 3 Hypothesis 4 Hypothesis 5 Hypothesis 6 Hypothesis 7 Hypothesis 8 Hypothesis 9 Hypothesis 10 Hypothesis 11 Hypothesis 12 Hypothesis 13 Hypothesis 14 Hypothesis 15 Hypothesis 16 Hypothesis 17

Estimates .277 .33 .04 .09 .07 .40 .04 .06 .13 −.004 −.07 .14 .09 .29 .02 .32 .22

T-value 4.522 5.414 .660 1.462 1.123 6.573 .700 .101 1.971 −.062 −1.022 2.043 1.491 5.104 .322 4.794 3.391

count of the results of sales. This result suggests that the SFA applications will not be orientated to accessing customer-focussed information to enhance customer relationship management. To investigate this possibility further, we turn next to analyse the type and amount of information collected on customers by the installed SFA systems. As would be anticipated from our obtained model, Table 9 shows that the installed SFA systems hold a paucity of information to enable the effective management of customer relationships. For example, although most measure the number of sales generated, the number of customers gained, revenue increases, and opportunities identified, relatively few measure more problematic areas such as individual customer value, share of customer business, effectiveness of different marketing mix elements, or efficiency of different


Figure 2 Obtained model of the determinants of SFA sophistication. 0.2773

Strategic Importance of Sales

Marketing/customer Orientation

0.3270 Organisational Slack

0.3979 Information Orientation

0.3182

Sales campaign evaluation

0.2941


0.1330

Internal Network

0.1426

0.2165 Integration of IT and Sales

Table 9 Count of the measures used to assess the effects of sales campaigns. If you measure results, please tick if you measure the following: Number of potential customers reached Opportunities identified Number of customer gained Sales by segments Number of sales generated Revenue per customer Share of customer business Cost per customer business Cost per sale generated Contribution to profits Level of customer satisfaction Individual customer value Effectiveness of different marketing mix elements Effectiveness of different contact strategies Relationship enhancement Overall marketing operations Other

% 53 69 74 69 81 66 38 43 47 79 62 36 38 38 39 42 8

customer conduct strategies. About 40% do not measure customer satisfaction at all. Costs per customer and costs per sale are also not measured by 50% of the sample. Even more surprising is the low level – less than 40% of the sample – who measure the degree of a relationship enhancement. As Table 10 reveals, sales and marketing managers generally feel they have adequate information and at least 50% of the sample do not see the need for any

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Table 10 Information held. What information is presently held or would you like to hold in the customer information file Name and address Postcode Telephone number Fax E-mail Names of all contacts Customer order history Purchasing profile Own products held Competitors’ products held Previous contact response details Credit rating

% Presently held 100 100 97 69 73 66 56 35 61 14 43 29

% Would like to hold 8 8 9 13 27 25 22 38 19 51 35 19

more. But both the quantity and quality of information held is at a low level of complexity. As expected, almost all hold name, address, and telephone number, but far fewer have fax, e-mail, or the names of different contacts with customers. Table 10 shows the extent to which different types of data are held. In terms of data that would really make a difference in the strategic use of SFA – such as purchasing profiles, competitor products, or services held and previous contact records – the data held by the organisations are relatively sparse. Respondents were next asked the degree to which they used SFA for aspects of sales planning on a scale from 1 = ‘not at all’ to 7 = ‘comprehensively’. Table 11 sets out the findings. As Table 11 reveals, SFA systems are being used extensively in sales planning for a variety of purposes but, as expected at this stage in the presentation of the results of our research, the major use is to develop mailing lists. Table 12 addresses the degree to which respondents utilised SFA for operational uses – using the same response scale as in Table 7. As Table 12 shows, the strongest use is made of SFA for contact management and sales reports but less use is made of SFA for ordering or billing. Remarkably, customer care is not a major use of the SFA in operational terms – scoring little more than half-way up the seven-point scale from ‘not at all’ to ‘comprehensively’. Table 11 Sales planning uses for SFA. Utilisation of: Mailing list Customer profiling Prospect bank Lead generation Segmentation Campaign effectiveness

Mean 4.90 4.18 3.74 4.07 4.34 3.70

Standard deviation 1.86 1.98 2.04 2.01 1.91 2.02


Table 12 Operational uses for SFA.


Utilisation of Ordering systems Billing system Customer care/service system Contact management Sales cycle tracking Sales reports Corporate data warehouse

Mean 3.5 3.85 3.87 4.6 4.04 5.18 3.68

Standard deviation 2.41 2.42 2.04 1.89 2.14 1.82 1.94

Discussion The findings offer only limited support for our initial conceptualisation, as outlined in Figure 1, but this research contributes to both academic and practical understanding of the benefits and drawbacks of using technology to support sales and marketing activities. As noted, previous studies, while adding to the knowledge base of SFA, have focussed on individual salesperson’s responses to SFA deployment. However, as Landry, Arnold, and Arndt (2005) observe, ‘the meagre number of published works with direct relevance to sales management along with the practicality of the topic suggests that additional research, both conceptual and empirical, would be beneficial’ (p. 231). First, we find that markets and customers are not at the heart of SFA and do not drive the level of sophistication of these systems. Instead, they are driven by an information orientation. Alike with the conclusions from Raman, Wittman, and Rauseo’s (2006) study on CRM, we suggested that firms will attempt to differentiate themselves by using their skills and knowledge to improve their organisational processes and systems in seeking competitive advantage. One way this can be achieved is the strategic use of information to improve sales operations – and by implication to increase the firm’s access to customers. Marketing orientation has been linked to performance outcomes in many studies outside the SFA context. It follows that strategic use of information – driven by a marketing focus – can improve the firm’s customer orientation and so allow the firm to differentiate itself in an increasingly competitive environment, but we found that the links between marketing orientation and information orientation and between marketing orientation and the sophistication of SFA systems to be absent. The lack of a link between a firm’s marketing orientation and the sophistication of the adopted SFA is confirmed by our findings of the paucity of information actually held on deployed systems. Our findings strongly suggest that sales-force resistance is a reaction to this over-riding information orientation in SFA deployment. As such, our work supports the importance of earlier research on individual-level factors in SFA acceptance (Cooper et al., 2008). At the same time, the direct effect of integration of IT and sales on SFA sophistication emphasises the importance of the organisational focus on utilising IT systems for information gathering. Second, we found little difference across industries. In the three industries chosen – financial services, pharmaceuticals, and building/construction – although quite different in the type of selling, the modus operandi of sales operations, and

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in their requirements for market and customer information, firms in these industries showed a remarkable consistency. Our findings show that, across the three industries we studied, a firm’s marketing orientation does not drive sophistication in salesrelevant information acquisition and utilisation. It was expected, a priori, that firms within industries will differ in their orientation towards the use and deployment of information management and also that there will be differences across industries. As Ahearne, Srinivasan, and Weinstein (2004) observe, ‘It is natural that there would be heterogeneity in technology usage across employees’ (p. 299). We would contend that heterogeneity would apply also to managers and organisations across firms and industries in their decisions to use/not use, over or under invest in new technology and in particular SFA systems. Through the cross-industry comparisons, we found that there is little difference in terms of strategic context and organisational context variables across the three industries. As such, industry-type appears not to influence the sophistication of adopted SFA systems. We then assessed if these motives varied across industries by comparing the results in three major industry sectors in the UK. This enabled us, by industry, to compare and contrast the individual and organisational issues that motivate adoption and investment in automated systems and follow-up on some of the problems identified by major firms that responded to our survey. We sought to clarify the reasons for adoption of automated systems, their use, satisfaction, and deployment with SFA systems across these three different industry sectors. Surprisingly, little difference was found and did not account for varying levels of sophistication. Only in 3 out of 24 variables were differences found between industries and these results suggest overall differences between industries to be marginal. Third, the expectation that managers were motivated to invest in SFA to control and possibly manipulate salespeople proved without foundation. While there is ample evidence that, throughout their operations, many organisations have invested heavily in technology to achieve the twin goals of improved customer service whilst reducing, or at least controlling, escalating costs, and nowhere is the objective of improved efficiency and increased effectiveness more clearly in focus than with sales operations (Hunter & Perreault, 2007), we found the link between organisational control and SFA sophistication absent. Nevertheless, the high cost of a field sales force has led many organisations to seek radical solutions by developing or changing routes to market via the Internet. To recap, our paper has contributed to the knowledge base on technology in sales in several ways. First, we reported on managerial research questions on the benefits and problems with SFA and elicit reasons for differences in the level of sophistication and deployment of such systems by assessing the individual and organisational issues involved deciding to invest in sales automation. This has been referred to as a ‘black box’ (Hunter & Perreault, 2007), and we attempt to get inside this box for clarification and explanation. What we found is that information orientation to be the main driver. Our current study’s identification of ‘information orientation’ and ‘integration of IT and sales’ as the direct drivers of SFA ‘sophistication’ suggests strongly that a managerial imperative to gather information underpin SFA deployment within the UK financial services, pharmaceuticals, and building/construction industries. More and more, in order to compete and survive, organisations need to provide a differentiated offering by adding value and perceived quality to a



core, physical product through the provision of services or change offerings so that they solve individual customer’s problems better. To do this requires information from and about their customers, which in part accounts for the growing importance of customer relationship management (Raman et al., 2006). Our study suggests that this focus is not coming from sales managers but through increasing sophistication of administered systems and managerial competence in the form of reduced organisational slack. What really drives these systems and their increasing sophistication is a pure information orientation. Information orientation and integration of IT and sales were identified as the direct predictors of SFA sophistication. Information orientation mediates the effects of (i) organisational slack and (ii) integration of IT and sales. Integration of IT and sales also mediates the effects of (i) strategic importance of sales and (ii) internal networks. The findings put forward in this paper suggest that research on SFA sophistication needs to focus further on these organisational-level variables. But increasingly, in order to compete and survive, organisations need to provide either (i) a differentiated offering by adding value and perceived quality to a core, physical product through the provision of services, or (ii) change their offerings so that they satisfy individual customer’s needs. To achieve either goal requires gaining insights about customers, but, importantly, such a marketing-orientated focus was not part of our findings.

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Appendix 1. Measure of SIS sophistication If you do measure results, please tick if you measure any of the following: No. of potential customers reached __________ Opportunities identified __________ No. of customers gained __________ Sales by segments __________ No. of sales generated __________ Revenue per customer __________ Share of customer business __________ Cost per customer business __________ Cost per sale generated __________ Contribution to profits __________ Level of customer satisfaction __________ Individual customer value __________ Effectiveness of different marketing mix elements __________ Effectiveness of different contact strategies __________ Relationship enhancement __________ Overall sales operations __________ Other [please state] __________

Appendix 2 Strategic context Strategic importance of sales decisions 1. How important are sales decisions to the strategic decisions that your organisation takes? Not at all important 1234567 Crucially important 2. How serious would it be for our organisation if the sales decision was wrong? Not at all important 1234567 Crucially important 3. How involved are sales personnel in strategic planning? Not at all important 1234567 Totally

Strategic integration of IT and sales 1. How important are IT decisions to the sales decisions your firm makes? Not at all important 1234567 Crucially important 2. How serious would it be to the sales function if the IT decision is wrong? Not at all important 1234567 Crucially important 3. How interlinked are sales strategy and IT strategy investment decisions? Not at all 1234567 Totally


4. In your organisation, how dependent are sales on IT for the performance of everyday routines? Very dependent 7654321 Not at all dependent 5. In your organisation, how dependent are sales on IT applications in achieving marketing performance objectives? Very dependent 7654321 Not at all dependent 6. For your organisation, to what degree do you think it likely that IT developments in sales will create competitive advantage in the future? Very likely 7654321 Not likely at all


7. For your organisation, to what degree do you think it likely that IT applications will contribute to achieving future sales goals? Very likely 7654321 Not likely at all 8. To your mind, what is the current rate of use of IT to support sales by companies in your industry? Very little 1234567 A great deal 9. How much do you think this will increase in the next 5 years? Very little 1234567 A great deal

Organisational context Information orientation Below are a number of statements which could be used to describe a sales information system. To what extent to you agree or disagree with the statements, as they apply to your organisation’s provision of sales information?

1. Our system is almost totally manual agree 1234567 disagree 2. Sales personnel can easily obtain all the marketing data they need from our system agree 7654321 disagree 3. Our system has many interfaces with external commercial databases agree 7654321 disagree 4. Computerisation of systems creates more problems than solutions agree 1234567 disagree 5. Our system holds customer information files which are directly accessible by sales personnel agree 7654321 disagree 6. Customer information files cannot be justified on cost grounds agree 1234567 disagree 7. Our system allows product cross-holdings by customer to be easily identified agree 7654321 disagree 8. Our system records and stores responses to all sales campaigns in the customer information file agree 7654321 disagree 9. Sales personnel always use customer information to direct mailings and/or other promotional activities agree 7654321 disagree

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10. Our system has statistical capabilities to analyse all sales and/or customer data agree 7654321 disagree 11. Our system is not very user friendly for sales purposes agree 7654321 disagree 12. The sales department has access to software for direct marketing purposes on our system agree 7654321 disagree 13. Our IS is extremely sophisticated agree 7654321 disagree 14. Our IS is built around up-to-date technology agree 7654321 disagree


15. Our IT people can design and install all software suitable for sales purposes agree 7654321 disagree

Marketing/customer orientation Below are a number of statements which people have made when talking about marketing and business. To what extent does your organisation’s philosophy agree or disagree with the statements?

1. There is an emphasis on short-term profits at the expense of long-term success in the market place Strongly agree 1234567 Strongly disagree 2. The business is committed to a long-term strategic point of view, supported by thorough market planning Strongly agree 7654321 Strongly disagree 3. We focus primarily on the bottom line and productivity, and only then on the customer and the market place Strongly agree 1234567 Strongly disagree 4. We base the price of our products on cost only, worked out by the accountants, who dictate pricing strategy almost regardless of the market place Strongly agree 1234567 Strongly disagree 5. We believe that selling volume comes first. Profits then generally follow Strongly agree 1234567 Strongly disagree 6. We believe in the principle of managing the market place, by expecting and managing change Strongly agree 7654321 Strongly disagree 7. We tend to fit our forecasts to the profits that we know are expected of us; then we plan how to achieve the forecast Strongly agree 1234567 Strongly disagree 8. We don’t pay a lot of attention to market research Strongly agree 1234567 Strongly disagree 9. If customers aren’t happy with our products, we tend to go looking for new customers rather than new products Strongly agree 1234567 Strongly disagree


10. We tend to be more concerned with return-on-investment in the short-term, than with customer-satisfaction in the long term Strongly agree 1234567 Strongly disagree 11. Our focus is on the market place: identifying customer needs and meeting those needs – profitably Strongly agree 7654321 Strongly disagree 12. The product is the concern of our technical with little input from the marketing people Strongly agree 1234567 Strongly disagree


13. We use feedback of information from the market place, to measure and guide our activities Strongly agree 7654321 Strongly disagree

Organisation slack 1. To what extent are resources available if sales wished to make greater use of computing facilities? easily available 7654321 available with difficulty 2. To what extent are resources available if sales wished to increase the amount of customer information they gathered and stored? easily available 7654321 available with difficulty

Organisational control 1. What level of control would be placed on sales’ use of computing facilities and resources? low control 1234567 high control 2. What level of control would be placed on sales’ need to gather and store information? low control 1234567 high control

Internal networks 1. How often do you have formal meetings with specialists from other functional areas within your own organisation never 1234567 very frequently 2. How often do you have formal meetings with specialists from other functional areas within your own organisation? never 1234567 very frequently

About the authors Bill Donaldson is professor of marketing at Aberdeen Business School, The Robert Gordon University, UK. He is author of Sales Management: Principles, Process and Practice (3rd ed.), Palgrave, 2007; Strategic Market Relationships, (2nd ed.) (with Tom O’Toole) Wiley, 2007; and

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The Busy Manager’s Guide to Marketing, Goodfellow, 2009. His research interests continue in the area of sales management and relationship marketing. E

[email protected]

Jong-Ho Lee is associate professor of marketing at Korea University in Seoul, Korea. His research interests focus on understanding performance of innovation especially in high-tech companies. E

[email protected]

George Wright is professor of decision science at Warwick Business School, UK. He has published in Management Science, Strategic Management Journal, and Organizational Behavior and Human Decision Processes. He edits the Journal of Behavioral Decision Making.


Corresponding author: George Wright, Warwick Business School, Coventry, CV4 7AL, UK T E

+44 24 7652 4275 [email protected]