Sales Force Automation: a review of the research Francis Buttle, Lawrence Ang and Reiny Iriana Macquarie Graduate School of Management, Macquarie University. Abstract We review the published research into Sales Force Automation (SFA) in order to identify gaps in our knowledge that might be worthy of further investigation. We find that academics have tried to answer just 4 questions: Why do organizations adopt SFA? What are the organizational impacts of SFA? What accounts for the success or failure of SFA projects? What accounts for variance in salesperson adoption of SFA? Introduction Since their introduction in the 1980’s SFA systems have become widely adopted in businessto-business environments and are seen as a ‘competitive imperative’ (Morgan and Inks, 2001) that offers ‘competitive parity’ (Engle and Barnes, 2000). SFA is characterised by, and defined as, the application of information technology to support the sales function. The SFA eco-system comprises software, hardware and service providers. SFA software vendors can be classified in a number of ways. Some vendors are SFA specialists (e.g. Salesnet; Selltech). They compete against CRM suite vendors that offer SFA modules (e.g. Siebel; Pivotal) and Enterprise suite vendors that offer a full range of IT solutions to support business, including supply chain management , enterprise resource planning and customer relationship management (e.g. SAP; Epicor). Vendors and consultants claim a number of benefits from SFA implementation, including accelerated cash-flow, shorter sales cycles leading to faster inventory turnover, improved customer relations, improved salesperson productivity, accurate reporting, increased sales revenue, market share growth, higher win rates, reduced cost-of-sales, more closing opportunities and improved profitability. We review here the body of academic research that has been published on SFA, including some that challenge these assertions. A critique of this body of knowledge is available elsewhere (Buttle, 2005). Research review Since the early to mid-1980‘s (e.g. Klompmaker, 1980-81; Collins, 1984; Wedell & Hempeck, 1987a, 1987b) there has been small amount of research on the topic of SFA. Our analysis shows that the research output can be clustered into subsets that have attempted to answer just four research questions, as follows. 1. 2. 3. 4. Why do organizations adopt SFA? What are the organizational impacts of SFA? What accounts for the success or failure of SFA projects? What accounts for variance in salesperson adoption of SFA? Given the conflicting reports on the success rates of SFA implementations, it seems anomalous that so little academic research has been conducted. Siebel and Malone (1996), for example, report that economic returns from SFA are ‘immediate’, and that the business case for its implementation is ‘compelling’. Moriarty and Swartz (1989) claim that some SFA implementations have achieved return on investment in excess of 100%. However, a number of reports signal alarms about the outcomes of SFA implementations. Block et al (1996) found that 61% of all SFA implementations fail. Rivers and Dart (1999), Morgan and Inks (2001) and Schafer (1997) have also reported similar failure rates. Blodgett (1995-96) testifies to failure rates of 75% and Bush et al (2004) of up to 80%. In the analysis that follows we review the SFA literature in relation to the four research questions identified above. Why do organizations adopt SFA? Research data suggest that efficiency gains are a primary motivation for investing in SFA. Erffmeyer and Johnson (2001) interviewed informants at 40 US manufacturers and service firms to discover their motivations for implementing SFA. The primary motivation was improved efficiency. Harris and Pike (1996) asserted that greater operational flexibility, better sales management, enhanced customer support, higher sales-force productivity, superior customer account management and improved communications between headquarters and the field were expected outcomes from SFA implementations. Ingram, LaForge and Leigh (2002) agree that many companies are turning to SFA to help them manage their customer relationships more efficiently. However, Erffmeyer and Johnson (2001) also observe that only ‘a limited number of respondents were able to offer details regarding formalized goals and objectives for SFA’. Wright and Donaldson (2002) identified four ‘quite strategic’ objectives for sales information systems applications – increased customer retention (mean score of 6.1 on a 7-point importance scale), enhanced customer relationships (6.1), increase customer acquisition (5.7) and integration to contact management (5.5). On further investigation, they suggest that the application of these systems reflects a ‘mailing-list mentality’. Like Erffmeyer and Johnson (2001), they also found little evidence of the sample companies actually measuring outcomes in terms of these strategic objectives. What are the organizational impacts of SFA? Kraemer and Danziger (1990) report that SFA implementations have both task and non-task outcomes. Most of the research performed on this topic has studied task-related outcomes. In an early study, Cronin and Davenport (1990) found a number of hard and soft outcomes were achieved. The harder outcomes were enhanced quality of customer communications, better time management, and improved knowledge management. Softer outcomes were classified as structural (rationalization of order processing, development of a ‘virtual office’ held on laptops), motivational (lower sales force attrition, improved image, better stress control) and cultural (the creation of an extended ‘invisible college’ of salespeople). Erffmeyer and Johnson (2001) identified improved access to information (60% of the sample), improved communication with customers (65%), a more efficient sales force (27%) and faster revenue generation (16%) as realized benefits from SFA. Wright and Donaldson (2002) found that the biggest impact of sales information systems was in developing mailing lists, producing sales reports, contact management and sales cycle tracking. Engle and Barnes’s (2000) investigation found a clear relationship between SFA adoption and salesperson performance. They computed that 16.4% of the variance in sales was explained by the use of SFA systems, but that the SFA project had a payback period at six to seven years. Ahearne and Schillewaert (2001) also found that use of SFA was associated with improvements in reps’ selling skills, knowledge and performance. Their research found positive correlations between SFA implementation and sales reps’ market knowledge, technical knowledge, targeting skills, adaptive selling and call productivity. Essentially sales reps with SFA support became more adaptable and productive. Sales reps’ use of SFA accounted for a small, yet significant portion (7%) of their sales performance. In a later study, Ahearne et al (2004) obtained objective measures of technology usage and performance. They found a curvilinear relationship between SFA usage, as measured by reps’ accessing of SFA screens over a three month period, and salesperson performance, as measured by sales against quota. The worst performing reps either had very little or a large amount of interaction with the SFA software. What accounts for the success or failure of SFA projects? Researchers have employed a number of different approaches to this question, using a variety of definitions of success, and have identified several variables or factors that are associated with SFA success or failure. Pullig et al (2002) found that five shared values were important correlates of SFA success: customer orientation, adaptive cultural norms, an information-sharing culture, entrepreneurial values and high levels of interpersonal trust. Wright and Donaldson’s (2002) self-report data indicated that technical barriers were much less important than strategic and organizational barriers. For example, a shortage of IT specialists and a lack of board-level backing were highlighted as more significant barriers than having access to highly fragmented market and sales data. Bush et al (2005) set out to understand SFA outcomes by investigating ‘factors beyond those typically included in technology acceptance studies’. From semi-structured qualitative interviews with managers in 3 companies, they identified three major influences upon SFA outcomes: the degree of process change (from incremental to disruptive), the extent of salesperson buy-in and the perception of technology enablement (from low to high). In their sample buy-in by salespeople ranged from 50% to 70%, suggesting a good deal of disinterest or resistance. Speier and Venkatesh (2002) investigated two different firms where SFA technologies had been withdrawn following implementation. The research revealed that although the salespeople had been ‘fairly positive’ about the implementation of SFA at the outset, they turned against the system demonstrating their dissatisfaction with increased absenteeism and voluntary turnover. Sales performance did not increase following SFA implementation, principally because of the perceived lack of ‘professional fit’ between the SFA tools and the sales force. The sales team’s expectations of relative advantage to be delivered by the SFA tools had been high, but their perceptions of its delivery were much lower. Six months after implementation, organizational job commitment, job satisfaction, perceptions of salespersonorganization fit, and perceptions of salesperson-job fit had also decreased significantly. What accounts for variance in salesperson adoption of SFA? It has been observed that SFA adoption is a two-stage process (Parthasarathy and Sohi, 1997). First the organization decides whether to adopt the technology; second, the sales-force decides whether to use the technology. A number of researchers have attempted to ‘forward understanding of sales force acceptance of SFA’ (Morgan and Inks, 2001). As noted by Ahearne et al (2004), much of the research on this particular question has focused on technology adoption, rather than technology usage. One of the earliest studies was conducted by Keillor et al (1997) who found that there was considerable variance amongst salespeople in their attitude towards the use of SFA technologies. They found that younger sales reps were more positively inclined towards technology adoption. Ko and Dennis (2004) also suggest that SFA systems tend to store formal knowledge about products, customers, markets and competitors, and are therefore more likely to be of value to newer sales reps. Robinson, Marshall and Stamps (2005) combined the Technology Acceptance Model (TAM) (Davis 1986; Davis 1989) with the Theory of Reasoned Action (TRA) (Ajzen and Fishbein, 1980) to identify the relationship between perceived usefulness, perceived ease of use, attitude towards using technology, and intention to use the technology. In addition, they tested the relationship between technology acceptance, adaptive selling practice, and job performance of field sales people. Analysis indicated that the attitude towards using technology is positively related to perceived usefulness and perceived ease of use, and the more positive the attitude toward using technology, the higher the intention to use the technology. They also found that although intention to use SFA tools is not directly related to better job performance, it is positively related to the adoption of adaptive selling practices by sales people, which, in turn, leads to better job performance. Jones et al’s (2002) longitudinal study examined actual usage of SFA technology also employed TAM and TRA. They found that 3 variables explained salesperson intention to use the technology – perceived usefulness of the new system, attitude towards the technology and its perceived compatibility with the current system. However, actual use of the technology was shown to be strongly associated with the personal innovativeness of the sales person, attitude towards the technology and facilitating conditions. Schillewaert et al’s (2005) results reinforce the importance of perceived usefulness and ease of use as the main drivers of technology adoption in the sales force setting. Avlonitis and Panagopoulos (2005) deployed TAM in conjunction with the DeLone and McLean Information System Success Model (DMISSM) (DeLone & McLean, 2004) to explain the acceptance of CRM technology by sales people. Accurate expectations regarding system usage is the prime organizational factor positively associated with perceived ease of use, and sales people participation in system design and implementation is positively related to perceived usefulness of the technology. They also measure the impact of CRM technology on sales force performance and conclude that the higher the positive perceived usefulness of CRM technology, the better the sales performance. Other researchers have offered different explanations for variance is sales person adoption of SFA. Buehrer et al (2005) found that reps adopted SFA not only because of its promised ‘efficiency’ but also because they ‘had to’. Reps also reported that they would be more likely to use SFA if there was continuous or on-demand training. Erffmeyer and Johnson (2001) and Gohmann et al (2005) both identify improved productivity as a reason for SFA adoption by reps. Other researchers, however, have pointed out the negative outcomes for salespeople of adopting SFA. Rangarajan et al (2004) find that salespeople adopting SFA experience strong and stressful feelings of role ambiguity and role conflict. Speier and Venkatesh (2002) found that if the fit between SFA tools and reps’ roles is poor, the tools may fall into disuse. Conclusion Researchers have tried to answer just four questions in this body of research into SFA. Why do organizations adopt SFA? What are the organizational impacts of SFA? What accounts for the success or failure of SFA projects? What accounts for variance in salesperson adoption of SFA? Given that there are an estimated 45 million salespeople worldwide (Siebel and Malone, 1996) and that US demand for SFA applications, estimated to be half the world’s spending on this technology is forecast to grow from US$534 million in 2003 to US608 million in 2008 (eMarketer, 2005), this amount of research is rather meager. Our review leads us to suggest that there are a number of SFA research questions that merit further investigation. 1. What objectives are executives and managers pursuing when they adopt SFA, and how do these vary, if at all, across context? 2. How do definitions or claims of SFA success (or failure) vary contextually? Much of the extant research has failed to adequately define measures of success for SFA implementation, and has erringly considered acceptance by reps as a proxy for use and effectiveness (Ahearne et al, 2004). 3. What counts as SFA success (or failure) from the perspective of the various internal (sales person, sales manager, senior manager, IT manager), and external (vendor and customer) stakeholders? 4. What impacts does SFA have on customers, and on supplier-customer relationships? 5. What are the organizational and environmental conditions that are associated with the achievement of desired SFA outcomes? 6. Does the implementation model – hosted, installed or blended – make any difference to SFA outcomes? 7. Which technology, people and process factors are important components of SFA implementations and what impact do they have on SFA outcomes? 8. Does SFA deliver competitive advantage? 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