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? Put another way, do competitors with SFA
achieve better outcomes than their counterparts without, and, if so, is the advantage
sustainable?
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