Making Sales Technology, Crm, And Sales Force Automation Effective

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“Making g Sales Technology gy Effective”

Gary K K. Hunter and William D. D Perreault, Perreault Jr Jr.

Journal of Marketing 71, 1 (January 2007), pp. 16-34. 16 34.

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Continuum C ti

Traditional Arm’s--Length Exchange Arm’s

Nature of IO interface (Anderson & Narus 1990):

Distribution of relationship outcomes (Clopton 1984):

Temporal outlook (Dwyer, Schurr, & Oh, 1987; Ganesan, 1994):

Contemporary Conditions

Competitive p

Cooperative p

Distributive

Integrative

Short-term Shortmaximizing

Long-term Longoptimizing

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Dimension Salesperson’s Role (M (Moon &A Armstrong, 1994)

Channel Power (Messinger & Narasimhan, 1995)

Seller’s Competitive Orientation (Achrol & Kotler, 1999)

Traditional C diti Conditions

Contemporary C diti Conditions

Gatekeeper / “Linking Pin”

Manage key account / functional experts

Manufacturer f

Retailer

Horizontal

Vertical (network economy)

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Introduction

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1) Generating 2) Improving

revenues

sales force effectiveness

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Salesperson-Independent Salesperson(e.g. Online reverse auctions, Jap 2003)

Replaces or reduces sales force’s strategic significance by changing its value value--added as a participant in firm’s gogo-to to--market strategy

Salesperson-Dependent Salesperson(this and other research)

Alter sales force strategy (People, skills, processes, tactics tactics, architecture, size, etc.)

The strategic importance of driving the top line (Rust, Moorman, and Dickson 2002) 7

refers to information technologies that can f f facilitate or enable the performance of sales tasks. tasks

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CRM

Sales Technology

CRM as technology, includes IT’s that bridge w/ sales functions but also some that do not. not

Sales-based CRM tools

SFA

Primarily efficiencyfocused sales technologies developed to automate sales tasks.

We consider W id ST tools t l as the th entire ti gamutt off information i f ti technologies t h l i that th t salespeople use to perform their roles—not just the subset designed as sales-CRM or SFA tools.

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p B2B salesperson’s different uses of information technologies to build better relationships with business buyers.

Example: p A P&G customer business development p rep using scanner data to make marketing mix recommendations to a major grocery chain’s centralized buying center center. Introduction

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Sales technology is complex, complex expensive, and its returns are ambiguous. Opportunities to build better relationships between organizations through sales technology are often unrealized. In sales organizations organizations, there’s there s a limited understanding concerning technology’s role towards improving relationship building efforts.

Introduction

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Propose, Propose measure, measure and test new sales tasks associated with forging buyer-seller relationships. p Investigate the role sales technology plays in f ili i or enabling facilitating bli salespeople l l to perform f those new tasks. Develop and test a behavioral process model using structural equation modeling. Introduction

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Ubiquitous relationship

yp Roach’s p productivity paradox ((circa 1980’s)) - Some support (cf. Powell & Dent Micallef, SMJ, 1997) - Others contradict (cf. Sharda, Barr, & McDonnell, MS, 1998) Spectrum of frameworks (Hitt & Brynjolfson, MISQ, 1996)

Innovative debate over appropriate dependent variable

Typically use accounting measures like ROE, ROI, etc. Alt Alternative ti example: l Torbin’s T bi ’ q (Bharadwaj, (Bh d j Bh Bharadwaj, d j Konsynski, K ki MS, 1999)

“Black box” approach pp

This stream of research usually employs traditional econometric modeling measuring relationship between firm spending and productivity (inputs/outputs)

Relevant literature

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Descriptive studies

Investigate aggregate usage of technologies (e.g., Widmier, Jackson, & McCabe, JPSSM, 2002)

Forward-looking studies that focus on new innovations

Helped prompt adoption by organizations (e (e.g., g Collins & colleague colleague, JPSSM)

Early classification schemes for sales automation

Helped lay foundation for conceptualization (e.g., Wedell & Hempeck, JPSSM, 1987)

Causes of sales automation failures (e.g., Speier & Venkatesh, JM, 2002)

Motivating sales and information technology adoption (e.g., Venkatesh and Davis, Mgt. Sc, 2000)

Relevant literature

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How different uses of sales technology influence behaviors that may y help p reps p build stronger relationships with customers while simultaneously considering influences on administrative d i i i performance. f

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Relationship forging tasks activities that an individual in an Relationship-forging organization performs to help build relationships with external constituents. • In I a more generall sense, relationship-forging l ti hi f i tasks t k refer f to t activities ti iti conducted d t d by boundary spanners to forge or merge their organizational boundaries with an external organization’s boundaries.

Sales technology refers to information technologies that can facilitate or enable the performance of sales tasks. • Beyond sales automation (efficiency-focused (efficiency focused applications) • Related to CRM (IT product, but ST includes more than computer technologies) • Include new tasks enabled by technology (effectiveness-focused applications).

Introduction

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y to the user to g This research g goes directly get assessments on information technology’s value. Substantial research on factors that influence the level (and validity) of user evaluations and debate over the limitations of this approach. pp Goodhue’s task-technology fit theory and measurement is the most relevant to this research Goodhue (DS, 1995) strongest link between information systems and performance will be due to a correspondence between tasks needs and information system/ technology functionality.

This research Thi h diff differentiates ti t ttasks k ffrom th the ttechnology h l and d iincorporates t th the human factor (including voluntary use).

Relevant literature

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Draws from six research streams: ™relationship marketing,

Atuahene-Gima and Li 2002; Doney and Cannon 1997; Dwyer, Schurr, and Oh 1987; Ganesan 1994

™buyer-seller relationships, Cannon and Perreault, 1999

™information technology productivity

Hitt and Brynjolfson y j 1996;; Bharadwaj, j, Bharadwaj, j, and Konsynski y 1999

™organizational learning,

Huber 1991; Sinkula 1994; Day 1994

™cognitive selling

Sujan, Sujan, and Bettman 1988; Szymanski 1988

™negotiations egot at o s

Pruitt 1981; Clopton 1984; Jap 1999; 2003. 18

Behavioral modeling approach

y used to study y other aspects p Widely of sales roles in interorganizational markets (c.f. Behrman & Perreault, JM, 1984, JBR 1982; Behrman, Bigoness, & Perreault, MS, 1981; Sujan, Weitz, and Kumar, JM, 1994; Singh, JM, 1998).

Relies on primary data

which contrasts with the IT productivity literature that relies on secondary data

Portfolio of sales technologies

which contrasts with the IT applications literature

Sales technology effects on tasks are empirically estimated which contrasts with a user rating of the effect.

Relevant literature

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What key tasks does the salesperson perform that can be influenced by using i f information ti technology? t h l ?

What manageriallycontrollable factors motivate salespeople to use technology?

Conceptualization & Measurement

How much and how does the salesperson use technology?

Whatt accountt Wh objectives & key aspects of salesperson performance could be influenced by one’s use of information technology, both directly and indirectly through sales tasks? 20

What key tasks does the salesperson perform that can be influenced by using i f information i technology? h l ?

What manageriallycontrollable factors motivate salespeople to use technology?

Conceptualization & Measurement

How much and how does the salesperson use technology?

Whatt accountt Wh objectives & key aspects of salesperson performance could be influenced by one’s use of information technology, both directly and indirectly through sales tasks? 21

Extensive literature on salesperson performance (almost 100 years old)

• See Brown & Peterson (JMR, 1993) for meta-analysis meta analysis • Adapt measures form inventory proposed by Behrman & Perreault (JBR, 1982; JM, 1984) and widely used in the marketing and management literatures.

Relationship-building Relationship building performance with customers (external focus)

• refers to the extent to which the salesperson performs activities that cultivate a relationship that mutually benefits the selling and buying firms. • Ex: …relative to the average salesperson in similar selling situations… “working with buyers to develop a partnership that’s profitable to both firms.” 7-point Likert,, SDA to SA • These can be viewed as new “working smart” tasks.

Administrative performance (internal focus)

• refers to the salesperson’s ability to complete required, non-selling related activities in a timely t e y manner. a e • Ex: …relative to the average salesperson in similar selling situations… “Addressing my administrative responsibilities in a timely manner.” 7-point Likert, SDA to SA

Covariates that predict performance (for completeness) • Work experience • Work effort (“working harder”)

Conceptualization & Measurement

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What key tasks does the salesperson perform that can be influenced by using i f information i technology? h l ?

What manageriallycontrollable factors motivate salespeople to use technology?

Conceptualization & Measurement

How much and how does the salesperson use technology?

Whatt accountt Wh objectives & key aspects of salesperson performance could be influenced by one’s use of information technology, both directly and indirectly through sales tasks? 23

Share information across boundaries Sh i f ti b d i •

Hansen (ASQ, 1999): importance of sharing knowledge across organizational subunits

•

Eisnenhard & Tabarizi (ASQ, 1995): NPD knowledge sharing

Focus on integrative solutions •

Clopton (JMR, 1984): critical need in interorganizational relationships to adopt a winwin (integrative) attitude instead of zero-sum (distributive) ( ) game. g

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Jap (JMR, 1999): Pie-expansion

Conceptualization & Measurement

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g market knowledge g Sharing

• refers to the extent to which individuals (salespeople) develop relevant market expertise and share their knowledge with others (their customers). • Ex: “I keep my buyers aware of market changes.” 7-point Likert, SDA to SA

Proposing integrative solutions

• refers to the extent to which an individual (salesperson) applies information and knowledge to construct and propose recommendations that are mutually beneficial to the involved parties (the selling and buying firm) firm). • Ex: “I’m good at finding opportunities that benefit both my firm and my customer’s (firm).” 7-point 7 point Likert, SDA to SA

Conceptualization & Measurement

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What key tasks does the salesperson perform that can be influenced by using i f information i technology? h l ?

What manageriallycontrollable factors motivate salespeople to use technology?

Conceptualization & Measurement

How much and how does the salesperson use technology?

Whatt accountt Wh objectives & key aspects of salesperson performance could be influenced by one’s use of information technology, both directly and indirectly through sales tasks? 26

Considered multidimensional instead of uni-dimensional construct (based on learning from previous study: JPSSM 2006) Conceptualizing dimensions

Information technology is often conceptualized as the • collection, • analysis, • dissemination, and • storage of information.

Sinkula (JM, 1994) proposed four stages of market information processing: i acquisition, i ii iinterpretation, i di distribution, ib i and d storage. Using sales technology to store information (expands memory) should have temporal effects and would be better addressed through timeseries design design.

Thus, we propose and tested three dimensions: • accessing (acquisitioning), • analyzing (interpreting), (interpreting) and • communicating (distributing).

27 Conceptualization & Measurement

Access

Using technology for accessing information refers to the extent to which salespeople to information relevant l l use technology t h l t retrieve t i i f ti l t to t the th performance of their sales jobs.

Analyze y

Using technology to analyze information refers to the extent to which salespeople use technology to better understand the implications of information relevant to the performance of their sales jobs.

Communicate

Using technology to communicate information refers to the extent to which salespeople use technology to transfer information both to individuals within and outside their sales organization in the f h l jobs. b performance off their sales

Semantic differential (bi-polar adjectives) scales Routine, frequency, emphasis, and confidence.

Conceptualization & Measurement

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What key tasks does the salesperson perform that can be influenced by using i f information i technology? h l ?

What manageriallycontrollable factors motivate salespeople to use technology?

Conceptualization & Measurement

How much and how does the salesperson use technology?

Whatt accountt Wh objectives & key aspects of salesperson performance could be influenced by one’s use of information technology, both directly and indirectly through sales tasks? 29

g sales technology gy usage g Factors affecting

ƒ Personal innovativeness, attitude toward the new ST, and facilitating conditions influence ST infusion (Jones, Sundaram, and Chin (2002) ƒ Alternative Alt ti fframeworks k ffor adoption d ti off iinnovations ti exist i t ƒ Parsimony dictated constraints on model specification ƒ Social influence theory (Thibaut & Kelley, 1959)

A social influence (e (e.g. g another person or group norm) can positively or negatively influence ones behaviors (e.g. sales technology use)

Two key antecedents:

ƒ Customer’s (buying firm) IT expectations, and ƒ Sales technology training effectiveness

Conceptualization & Measurement

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FIGURE 1

Fundamental management inputs

• Customer’s IT expectations • ST training effectiveness

Conceptual Model of Antecedents and Consequences of Sales Technology Uses and Relationship Relationship-Forging Forging Tasks

Type of ST uses

Relationship-forging tasks

Key aspects of performance

• Communicating • Analyzing

• Sharing market knowledge • Proposing integrative solutions

• Relationship-building performance

• Accessing Individual performance factor covariates

•Administrative performance

• Work experience • Eff Effortt

Conceptualization & Measurement

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See DeVellis (1991) Desired host firm characteristics (population generalizations): 1. salespeople conducted typical internal and external B2B sales tasks (e.g. they did not sell to final consumers) 2. ST implementation was under way, 3. variance in salesperson ST use (voluntary use) and skills, 4. management would encourage participation in responses that would be kept confidential to researchers, 5. the h sales l force f was large l enough h to support statistical i i l tests of the hypothesized relationships. Selected host firm was a well known consumer goods company well-known (not P&G, my former employer, and not the same firm used in my previous sales technology study publishing in JPSSM 2006) Administration

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•

Administration

Evaluated preliminary questionnaire with host firm managers for clarity and completeness. •

Fi l responses rate Final t was 79% .

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We dropped 3 observations for missing data yielded an effective rate of 77% and sample size of 151.

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• 66% male •Average age was 42 (ranging from 23 to 63) • Annual salaries from $24,000 to $139,000 not including bonus pay which ranged g from $400 $ to $$25,000 , p per yyear •Average years of sales experience was 18--new hire to 38 yr veteran • Average work week: 47 hours • 17 were spent doing administrative work, • 16 interacting with customers, • 7 doing data analyses, and h activities i ii • 7 on other • The average salespeople interacting with 34 people monthly outside the selling organization and 15 people within the selling organization Administration

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Used SEM modeling approach See Anderson & Gerbing (1988): 1. 2. 3.

Fit separate CFA’s for each of the proposed scales to assess reliability and convergent validity Fit separate (one vs. two dimensional) CFA’s for scales that were most susceptible to cross loadings (e.g. two aspects of performance) Tested fit of overall structural model and size of hypothesized yp effects

Relied on following fit statistics: Jöreskog and Sörbom’s (1986) goodness of fit index (GFI) and (AGFI) Bentler’s (1980) Comparative Fit Index (CFI) χ2 statistic with its associated degrees of freedom (and ratios) Browne and Cudeck’s (1993) root mean square error of approximation (RMSEA).

Methods

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• Construct reliability estimates • Fornell and Larcker (1981) computations • Bagozzi over .6 desirable B i and d Yi (1988) criterion: i i 6 iis d i bl • All of the constructs here exceed .71 • Worst fitting g CFA fit had GFI = .94;; AGFI = .90;; CFI =.90. • Item reliability estimates • Item reliabilities greater than .15–.20 15– 20 (or, (or equivalently, equivalently squared multiple correlation coefficients greater than .38– .45) indicate internally consistency with other items comprising i i a scale l • 36 items for composite measures: • 33 have item reliabilities ≥ .30, and • all items are greater than .20 (lowest is R-scored). Results

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• Followed conventional approach for large item surveys • Scale scores for constructs • Incorporates effect of measurement errors through model constraints • Set error construct effects to the square root of the reliability estimate • Set the error variances to the products of the scale variance and (1 – scale reliability)

•

Block-recursive model required algebraic identification (Bollen, 1989; Bekker & Pollock, JE, 1986)

• Overall fit statistics indicate an excellent fit (χ2= 37.1 (p = .17), df = 30; CFI= .98, CFI 98 RMSEA =.04, 04 GFI = .96, 96 AGFI = .91). 91) Results

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• Variance explained for endogenous constructs

• 13 Results

Technology Uses Communicating: Analyzing: Accessing:

24% 20% 15%

Relationship-forging tasks Sharing market knowledge: Proposing integrative solutions:

30% 21%

Aspects of salesperson performance f Relationship-building performance: Administrative performance:

% 57% 12%

outt 15 h hypothesized th i d paths th are significant i ifi t att p. <.05 < 05 38

FIGURE 2

Results

Managerial inputs .20 20 (p.< (p < .05) 05) Customer IT expectations

Types of Sales Technology Uses

Communicating SMC = .23

Relationship-Forging RelationshipTasks

.28 28 (p.< (p < .01) 01)

Sharing market knowledge SMC = .26

Rel.-building performance SMC = .50

.33 (p.< .001) Analyzing and better understanding SMC = .21 .23 (p.< .01)

Training effectiveness

.18 (p.< .05)

Performance Aspects

Proposing integrative solutions SMC = .21

-.04 (p.= .56) Experience

Effort

-.08 (p = 34) (p.=.34)

.22 (p.< .01)

a

Accessing SMC = .15

.30 (p.< .05)

Administrative performance SMC = .12

Standardized maximum likelihood parameter estimates. P-values for one-tailed significant tests of path coefficients. Solid lines indicate significant effects. c Model was specified as a block-recursive which produced correlations estimates of .34 between buyer IT expectations and training effectiveness, .31 between communicating and analyzing, .37 between communicating and accessing, .68 between analyzing and accessing, .71 between the relationship-forging tasks, and .48 between the two aspects of performance. 39 * Overall model fit statistics indicate an excellent fit: (χ2 = 37.1 (p = .17), df = 30, CFI= .98 RMSEA =.04, GFI = .96, AGFI = .91). b

• Specification alternatives and discriminant validity • Comparisons between: • proposed block-recursive model and one-dimensional alternatives (non-nested model comparisons via CFI and AIC), • proposed block-recursive model and higher-order constructs (nested models comparisons via χ2 difference test) • proposed block-recursive model and unrelated constructs (nested models d l comparisons i via i χ2 2 difference diff ttest) t) All tests supported block (see paper Appendix Table A1) • Item to scale composite and other scale comparisons • One double double-loading loading ((.52 52 and .55) 55) >> kept for content validity • Common

method bias test

• Harmon Harmon’ss one one-factor factor • Same source bias test with equivalent effect constraint Results

• No evidence of bias in estimates.

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RFTs represents an important new theoretical perspective for research f future f t h in i interorganizational i t i ti l contexts t t

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RFTs as new “smart-selling” behaviors in a relational context

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Salespeople can be viewed as value-creators in implementing a sales-service differentiation strategy.

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Different uses of technology have differential effects on different aspects of performance.

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Sales managers may increase sales technology costs yet decrease potential returns.

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Training and buyer encouragement represent relevant social influences on technology use that may be in conflict with each other.

Discussion/Conclusion

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• •

•

•

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Standard concerns with self-reports Potential for common method bias despite absence of statistical evidence Behavioral performance measures where ideal would be truly “objective” measures (if such measures exist) Seller’s views on relationship-building performance would benefit from supplements from buyers’ perspectives Consumer packaged goods industry versus other contexts

Discussion/Conclusion

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