104 TOTAL REWARDS FOR TECHNICAL WORKERS

ASAC 2005,
Toronto, Canada
John W. Medcof
Steven Rumpel
McMaster University
TOTAL REWARDS FOR TECHNICAL WORKERS
Research on rewards for high technology workers is reviewed using the Total
Rewards framework and a theoretical analysis of Total Rewards performed.
Suggestions for more effective practice and further research follow.
Introduction
Firms in industries whose fundamental driver is the creation of value from science and
technology continue to face enormous challenges in environments marked by unrelenting
technical change and global competition (Boutellier, Gassmann and von Zedtwitz, 2000; Serapio
and Hayashi, 2004). Firms with the edge in attracting, retaining, motivating, and rewarding top
technical people have the edge in these technological races. But high technology workers present
unique challenges when it comes to rewards (Balkin, Markman and Gomez-Mejia, 2000) and
those challenges arise from the distinct nature of high technology firms and R&D workers. There
is a need for innovative practice, empirical research and conceptual development on issues related
to rewards for R&D workers. This paper will focus on such workers, their reward preferences,
and the reward arrangements that work best for them, using the Total Rewards framework.
Table 1 Four Categories for Total Rewards
PAY
1. Base salary
2. Variable pay
3. Stock
4. Recognition programs
LEARNING & DEVELOPMENT
1. Career development
2. Learning experiences
3. Performance management
4. Training
5. Coaching and mentoring.
After O’Neal (1998)
BENEFITS
1. Health care
2. Retirement
3. Savings
4. Time off
WORK ENVIRONMENT
1. Organization climate
2. Leadership
3. Performance support
4. Work/life balance
5. Challenge of the work
6. Reputation of the organization
7. Co-worker relationships
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Total Rewards is a promising approach to employee rewards that has recently emerged
from human resource management practice (Fischer, Gross and Friedman, 2003; Gross and
Friedman, 2004; Kantor and Kao, 2004; Lyons and Ben-Ora, 2002; O’Malley and Dolmat-
Connell, 2003; O’Neal, 1998; Petruniak and Saulnier, 2003; Pfau and Kay, 2002; Platt, 2000;
Poster and Scanella, 2001; Thanasse, 2003; Watson, 2003; Zingheim and Schuster, 2001). It is an
approach to rewards management which attempts a comprehensive inclusion of all the rewards
people receive in the workplace. It embraces the “complete employee value proposition”;
including financial rewards such as pay, stock options and benefits; and non-financial rewards
such as training opportunities, interesting work, and support for work/life integration. Total
Rewards has promise for the management of technical people as demonstrated by its application
at IBM (Platt, 2000), Ethicon (Thanasse, 2003) and AstraZeneca (AstraZeneca, 2004). However,
there has been no systematic consideration of Total Rewards in the R&D management literature.
Currently, most thinking about rewards confines itself to “compensation”, which focuses
almost entirely on pay and benefits as the principal rewards an organization can offer workers.
Total Rewards goes beyond that and considers a wide array of other positive results of working
(intrinsic and extrinsic) such as the social stimulation which people receive at work, the
satisfaction they receive from doing their jobs well and the opportunity for learning and
advancement at work. The assumption is that by thinking about rewards in this broader way we
will understand them all, and their relationships to each other, in a more effective way, and this
will lead to more effectively managed organizations. If the full spectrum of rewards and their
real value to employees can be identified, optimal mixes of rewards for those employees can be
designed and offered. For example, in some circumstances spending X dollars to increase
employees’ pay may not be as effective an alternative as investing the X dollars in a much more
effective career progression program that gives workers a strong sense that they are growing and
developing in the organization and that they have a bright future there. Under the Total Rewards
framework we thus can envision trading off pay against career growth opportunities. This tradeoff
might not have been thought of if pay were considered a reward and career growth a part of
training. Total Rewards thus promises to overcome some of the sticking points that are created
by the current set of silos used in human resource management practice.
O’Neal (1998) and Kantor and Kao (2004) divide Total Rewards into four categories as
shown in Table 1. For efficiency of presentation we will use this widely accepted four category
model in this paper. From this we can see the comprehensive nature of Total Rewards.
Proponents of Total Rewards emphasize its value for attracting and retaining workers. If
the full spectrum of rewards offered by an organization is presented to recruits in a structured
way, the organization will be more attractive than will firms which emphasize only pay and
benefits. If the current employees of a firm are kept apprised of the complete set of rewards they
are currently receiving, they will be less likely to find other firms to be attractive alternatives. It
is important to effectively communicate to employees all the rewards they receive from their
work as this cultivates the sense that this set of rewards is not available elsewhere and that this
firm is an “employer of choice”.
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Proponents of Total Rewards have paid less attention to the ways in which Total Rewards
could be used to influence organizational practices that directly impact work performance.
However, the potential is there to do just that. For example, Total Rewards encompasses the
intrinsic rewards employees receive from working. The framework thus has a conceptual link to
job design, which can be used to ensure that employees do get intrinsic rewards from their tasks.
Job design has long been considered to be an important mechanism for improving individual and
organizational performance. Total Rewards offers the prospect of using job design even more
effectively, by thinking of it as a reward delivery mechanism, in the same context as pay,
benefits, social rewards, and others.
There is no “one best way” to implement Total Rewards. Every firm is unique and,
although organizations can learn from each other, each should develop its own solution. In short,
Total Rewards is a strategy to meet the needs of both the organization and the employee in a way
that helps employees understand the full value proposition they work under.
Comparisons of Reward Categories
Our literature review of rewards for R&D staff found only one study which compared
rewards from all four Total Rewards categories. Three others compared more than one category
but not all four. These papers will now be reviewed.
Kochanski and Ledford (2001) studied the importance of various rewards in the turnover
decisions of 210 high technology workers using five reward types: work content, affiliation,
indirect financial, direct financial and career. Work content and affiliation were the most
important, with 75% and 72% of respondents, respectively, saying they are “very important” or
“extremely important” in the decision. Career development, indirect financial and direct financial
rewards were judged “very” or “extremely important” by 62%, 65% and 64%, respectively. The
rewards of Kochanski and Ledford can be aligned with O’Neal’s (1998) four types. Work
content and affiliation from Kochanski and Ledford fit under O’Neal’s Work Environment.
Indirect financial corresponds to Benefits. Direct financial with Pay. Career with Learning and
Development. The ranking is shown in Table 2.
Table 2 Ranking of Importance of Total Rewards in Various Studies
Research Studies
Rewards Rankings
Work
Environment
Benefits Pay Learning and
Development
Kochanski & Ledford (2001) 1 2 2 2
Kochanski, et al (2003) 1 - 3 2
Chen et al (1999) 1 - 2 -
Keller et al (1996) 1 - 2 -
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Kochanski, Mastropolo and Ledford (2003) were also concerned with retention issues in
their survey of 1999 R&D unit leaders. Respondents were asked which factors are most
important for attracting and retaining R&D workers. The work itself was ranked most important,
followed by long term career opportunities and a unique work culture. Cash compensation
followed distantly. Aligning these with the Total Rewards framework: work itself fits with Work
Environment; career opportunities with Learning and Development; unique work culture with
Work Environment; and cash compensation with Pay. No facets of Benefits were included in the
study. These results are also shown in Table 2.
Chen, Ford and Ferris (1999) did a questionnaire study of 1109 technical workers in
R&D units. Respondents were asked to rate the degree to which various reward types benefited
the organization. The ranking of their rewards was: intrinsic, individual fixed, socioemotional,
collective variable and individual variable. The correspondences with Total Rewards have
intrinsic and socioemotional fitting under Work Environment; while individual fixed, collective
variable and individual variable fit under Pay. Thus, their finding was that Work Environment
rewards have greater benefits for the organization than does Pay, as seen in Table 2.
Keller, Julian and Kedia (1996) studied the effect of a number rewards-related variables
on the performance of 658 industrial and 1033 academic R&D teams. Independent variables
included the degree of participation and cooperation in the team; the scientific and social
importance of the work being performed by the team; and the satisfaction of team members with
remuneration, opportunities for advancement, and supervision. The dependent variable was team
performance. Work importance had the strongest effect upon productivity, followed by
participation and cooperation. The three satisfaction variables had no consistent effect. Aligning
these results with Total Rewards: Work Environment (importance of the work,
participation/cooperation) clearly affects the productivity of R&D workers. There is minimal
support for an effect of pay satisfaction on productivity, as shown in Table 2.
Four papers comparing multiple rewards in the R&D context have now been reviewed
and the results summarized in Table 2. They show that all four rewards categories are important
to R&D workers and that Work Environment is the most important. A number of different
rewards under Work Environment are individually important to R&D workers. There is little
empirical work which bridges all four categories and more such research should be done. Now to
papers focussing on only one reward category, starting with Learning and Development.
Learning and Development
Cordero, DiTomaso and Farris (1994) studied job satisfaction, turnover and career
development opportunities in 3163 R&D professionals and found a positive relationship between
managerial development opportunities and job satisfaction, but no relationship between technical
development opportunities and job satisfaction. They also found that those with technical
development opportunities were more likely to leave the employer but less likely to leave R&D
for other areas of the firm. Those with managerial development opportunities were more likely to
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leave R&D for other parts of the firm, but less likely to leave the employer. This shows career
development opportunities have value for R&D workers but that assessing the benefits of
providing such opportunities is not straightforward. For example, is turnover in the R&D unit a
good measure of the effectiveness of reward practices? Providing managerial development
opportunities does contribute to job satisfaction but also leads to higher turnover in R&D units.
But at least some of that turnover results from technical people moving into management, which
may be desirable. Career development programs for R&D employees need to be matched to their
career development needs. Chen, Chang and Yeh (2003) argue that the career development
programs provided to R&D employees need to be matched to their career development needs and
at different career stages technical workers have different career development needs.
In summary, Learning and Development rewards are important to R&D workers and
should be included in Total Rewards programs for them. R&D workers have different career
development needs depending upon their ages and their career aspirations. The use of turnover as
a measure of the effectiveness of human resource practices has some subtleties which need to be
addressed when it is used for that purpose.
Work Environment
Kim and Oh (2002) quantified the value of the Work Environment in their study of the
economic and “intrinsic” compensation preferences of 1,214 scientists and engineers. Intrinsic
compensation included feelings of achievement, personal growth and social status, which fall into
the Work Environment category. Overall 37% of the sample said they received intrinsic rewards
from their work. Respondents who said they got intrinsic rewards were asked to give the
monetary value of those rewards as a percentage of their economic compensation. The average
was 26.8%. This low value is not consistent with the importance of Work Environment found in
the studies cited above. The difference may arise from Kim and Oh’s distinctive methodology for
measuring the importance of intrinsic rewards. James (2002) advocates more attention to work
environment variables based on some published data and his experience. His view is that the
work itself is a very strong motivator for technical people. He states that research scientists and
engineers have a deep-seated need for professional recognition and recommends a dual ladder
recognition system. Mannheim, Baruch and Tal (1997) studied work centrality in a sample 727
people employed by high technology firms in Israel. Although the sample included non-technical
people as well as technical, their results are relevant here because the sampled firms were selected
for their above average numbers of technical people. By Mannheim et al‘s definition, work
centrality is the degree to which an individual is cognitively and attitudinally involved in the
work role. They found work centrality significantly related to organizational commitment, career
planning and wages, and weakly but positively related to work performance. This is yet more
evidence of the importance of Work Environment. Harpaz and Meshoulam (2004) compared the
“work centrality” of 461 technical, professional and managerial workers in high technology firms
to that of 942 workers from traditional industries. Here again the “high technology” sample is not
pure. The high tech group saw work as more central and had a more expressive work orientation
than the other sample. The importance of interpersonal relationships did not differ significantly.
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Overall, the empirical data on the Work Environment suggest that it is very important for
R&D workers and deserves more research attention than it has received to date. This suggests
that Total Rewards programs for R&D workers should give it more importance than it might have
in programs for others. There are many facets of Work Environment included in these studies
which suggests that Total Rewards programs for R&D workers might usefully divide it into
multiple categories that have equal status with Pay, Benefits and Learning and Development. The
work itself and the social milieu of work are good candidates to be additional principal categories.
Pay
Kim and Oh (2002) studied the compensation preferences of 1,214 scientists and
engineers in basic, applied and commercial R&D, asking them to state what percentage of their
compensation they would like to receive in each of three forms: fixed salary, individual
performance-based, and team performance-based. All three groups had the strongest preference
for fixed salary, with individual-based incentives a distant second, and team-based incentives a
close third. Those in basic R&D had a stronger preference for fixed salary and less for teambased
incentives than the other groups, which were not significantly different from each other.
Risher (2000) studied current and emergent pay practices for R&D workers in the R&D
organizations of 41 large companies well regarded for their R&D. He interviewed senior HR and
compensation executives and found new approaches to compensation emerging. Although these
new practices are still not widely adopted, Risher argues that they are well suited for R&D
workers. The unique nature of R&D and the people who practice it justify the adoption of these
practices, even if they are not used in the rest of the organization. The five “new” practices most
commonly adopted are: (1) Broad banding of compensation categories, (2) Competency based
pay emphasised over job based pay, (3) Market alignment of pay emphasized over internal equity,
(4) Cash incentives such as profit sharing, (5) Recognition/reward practices (e.g. Award prize and
ceremony). As Risher describes them, the compensation strategies of the firms he studied are
consistent with Total Rewards. They see compensation as a tool for achieving firm goals and
believe that compensation practices should be tailored to employees.
This brings us to a series of studies that look at the relationship between Pay practices and
organizational effectiveness in firms in which R&D workers are an important group of
employees. These are studies of high technology companies defined as those which expend a
high proportion of resources on R&D. Although technical people are not the only type of
employees in such organizations they are a key group and effective management of them is
critical to the success of the firm. In these studies the rewards preferences of R&D workers are
not directly studied. Instead, the pay practices at the firm level are examined to see if they affect
the performance of the firm. These studies provide a complementary perspective to those which
look only at the preferences of employees. Two studies taking this approach are those of Diaz
and Gomez-Mejia (1997) and of Tremblay and Chenevert (2004). Both papers argue that pay
practices should be different in high technology firms because of their distinctive nature. Across
the two papers, the practices that are predicted to be more prevalent and more effective in high
technology firms are as follow. Pay levels will be more influenced by the characteristics of the
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person rather than by the job. Pay includes elements of risk sharing (e.g. performance-based
bonuses). Pay levels are set with more emphasis upon external equity than internal equity.
Managers have significant discretion in setting their subordinates’ pay, as opposed to having a
centralized pay-setting. Aggregate incentives are used whereby team and organization
performance influences the individual’s pay. There is a long term orientation in pay policy. The
firm takes a leader strategy by offering the best compensation levels in its sector. Individual
incentives are offered. With somewhat different methodologies the two studies collected data
from both high technology and low technology firms. They performed statistical analyses to see
if there was any relationship between the prevalence of these pay practices and firm high/low
technology status. They also analysed the degree to which these practices were more effective for
high technology firms than for low. The results are summarized in Table 3.
In Table 3 we see that four practices were included in both studies but only two of these
were found in both to be more prevalent in high technology firms than in low; risk sharing and
external equity. All the mechanisms that were included in only one study (person emphasis, long
term orientation, leader strategy and individual incentives) were found to be more prevalent in
high technology firms than low. Although the general thrust of these data is that high technology
firms compensate differently from others, there is a need for more research in areas of ambiguity.
The data on the relative effectiveness of the pay strategies was also mixed. Of the four practices
included in both studies, only two (risk sharing and aggregate incentives) gave positive results in
both. In addition, external equity was found by both studies not to be more effective for high
technology firms. These data suggest that some compensation practices are more effective for
high technology firms than for low, but further research is needed. There are several other studies
whose findings are consistent with these two but which did not focus on high technology workers
closely enough to be presented here (Balkin and Bannister, 1993; Balkan and Gomez-Mejia,
1990; Balkin, Markman and Gomez-Mejia, 2000).
Table 3 The Prevalence and Effectiveness of Pay Practices in High Technology Firms
Pay Practices Prevalence Effectiveness
D&G T&C D&G T&C
1. Person, not job, emphasis yes - yes -
2. Risk sharing yes yes yes yes
3. External equity yes yes no no
4. Discretion yes no yes no
5. Aggregate incentives yes no yes no
6. Long term orientation yes - yes no
7. Leader strategy yes - no
8. Individual incentives - yes - no
This table compares the data of Diaz & Gomez-Mejia, 1997 (D&G) and Tremblay &
Chenevert, 2004 (T&C). Both examined the degree to which compensation practices were more
prevalent in high tech firms than in low (shown in columns labelled “Prevalence”). Both also
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examined the degree to which the practices were more effective in high tech firms than in low
(shown in columns labelled “Effectiveness”). In the columns, “yes” indicates that the study
found the practice more prevalent or more effective in high technology firms, “no” indicates no
significant difference, and “-“ indicates the practice was not included in the study.
These studies suggest several conclusions. R&D workers do not value pay as highly as
do other workers. R&D workers prefer most of their pay to be fixed, but believe that some
should be in the form of individual and team incentives. In firms for which R&D is of high
strategic importance, risk sharing and an emphasis upon personal capabilities are the two pay
practices most consistently found to be related to firm performance. Discretion for managers,
individual incentives and long term orientation also receive some support. These results support
the proposition that R&D workers should be compensated differently to achieve worker
satisfaction and firm performance.
Benefits
Only two papers have empirical data on the role of benefits. O’Neal (1998) reports that,
for workers in general, benefits rank just after pay in the order of reward importance. Kochanski
and Ledford (2001) found Benefits ranked behind Work Environment and tied with Pay and
Learning and Development in ratings of reward importance. This suggests that Benefits should
be receiving more empirical attention than has hitherto been the case.
Conclusions from the Literature Review
This review of the empirical research on reward importance and practices in R&D shows
the literature to be rather thin, but it does suggest a number of conclusions and directions for
future work. The following seem warranted.
1. All four rewards categories are important to R&D workers and should be
systematically included in rewards programs for them, and a Total rewards
framework is a promising approach to doing so.
This is shown in Table 2 which summarizes the studies which compared more than one
reward category. It is also seen in the studies looking at only one reward at a time. R&D workers
consistently rated all categories of rewards to be important. However, there is a paucity of
research that includes all four categories in the same study. Such research is necessary if the
rewards are to be systematically compared and the complete employee value proposition for
R&D workers is to be understood. The relationships of these different rewards to organizational
performance should be explored empirically, as has been done for pay.
2. Work environment is more important to R&D workers than it is for most other
workers and accordingly should be given more emphasis in rewards management
programs for them.
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In the comparative empirical studies summarized in Table 2 Work Environment is
consistently rated as the most important reward category for R&D workers. Although it can be
argued that this may not indicate that Work Environment is ultimately more important than
competitive Pay and Benefits, it surely indicates the high importance of Work Environment.
The Job Characteristics Model (Hackman and Oldham, 1980) focuses upon the work
itself, one important component of the Work Environment. That model proposes that workers
with high growth need strength respond better to enriched jobs than do workers with low growth
need strength. Hackman and Oldham’s data show that “Professional or Technical” workers have
a very high growth need strength compared to most of the other job categories they studied. This
is consistent with the studies reviewed above showing that intrinsic rewards from the job itself are
very important to R&D workers, more important than they are to most other categories of
workers.
3. Work Environment should not be treated as a single reward category for R&D
workers but should be divided into several rewards which are treated separately in
Total Rewards programs.
For example, quality and importance of the work itself, quality of relationships with coworkers
and recognition of work accomplishments have been found to be separately important to
R&D workers. Given the overall importance of the Work environment category and the
empirically demonstrated importance of these sub-categories, their individual importance should
be acknowledged, included in Total Rewards plans, and articulated to R&D workers.
4. Pay is an important category of rewards for R&D workers and should be
prominently included in Total Rewards programs for them.
Despite the results shown in Table 2, Pay practices have an important effect upon
organizational performance, as shown in Table 3. However, overestimation of the importance of
Pay is a temptation to be avoided. Research shows that Pay practices for R&D workers are, and
should be, different from those for others. Risk sharing, person emphasis, aggregate incentives,
discretion, individual incentives and long term orientation are practices that work in R&D.
Evidence on others is mixed and more research is needed.
5. Organizational circumstances can have a significant effect upon the effectiveness of
Total Rewards programs.
There is a number of situational variables that can affect Total Rewards and the growth
and evolution of high technology firms provides a good example. When Microsoft was young the
value of its stock rose at a phenomenal rate over a number of years. During that period the lure of
company stock and the huge amount of money it could bring could easily overshadow the effect
that any other rewards might have upon employees. Now that Microsoft is large and has a more
stable stock value the monetary gains available through stock options are no longer as spectacular
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and the role of other rewards has become more prominent. This completes the review of the
empirical work on rewards for R&D workers. We now turn to a consideration of its theoretical
basis.
A Theoretical Basis for Total Rewards
To date, a sound, broadly accepted, theoretical base for the Total Rewards has not been
presented, but some beginnings have been suggested. For example, O’Malley and Dolmat-
Connell (2003) argue that three facets of commitment (organizational, occupational and
beneficial) can form the basis of a “total relationship strategy” with employees. They
demonstrate how the concept of commitment can underlie various management strategies that
have to do with rewards. In another example, Kantor and Kao (2004) suggest that Total
Rewards’ attention to a spectrum of rewards is consistent with long traditions of psychological
and organizational theorizing going back through Lawler, Drucker and Maslow. The rewards
included in Total Rewards run the gamut from personal and career growth (Maslow’s selfactualization
need), through recognition and promotion (esteem needs), to benefits (security
needs) and salary (to satisfy physiological and other needs). These approaches have some
promise as avenues for providing a stronger conceptual basis for Total Rewards.
However, Expectancy Theory (Vroom, 1964), given its good empirical support (Van
Eerde and Thierry, 1996), can probably provide a more solid theoretical base. Expectancy theory
proposes that workers will be motivated to exert a high level of effort in their work if they
perceive that their efforts will lead to good performance (expectancy), that that performance is
instrumental in obtaining the rewards offered by the organization (instrumentality), and that those
rewards have significant positive valence (value) to the worker. These constructs can encompass
Total Rewards concepts.
Total Rewards proposes that organizations should offer their employees a number of
rewards (not just pay and benefits) and should ascertain the relative values of those rewards to
their workers so they can offer the most cost effective mix. In expectancy theory the value of
rewards is called valence. The ascertaining of the value of rewards would, then, involve
measuring the valences of the rewards which the organization might offer to workers. This could
be done using the measuring techniques developed for the study of Expectancy Theory.
Expectancy Theory is flexible in this consideration for it does not pre-specify any particular
number or type of rewards but does specify that the more rewards there are of positive valence
(assuming expectancy and instrumentality), the more motivated will be the workers. Expectancy
Theory proposes the inclusion of as many rewards, and as many types of rewards, as the
organization may wish to include, as does Total Rewards.
Expectancy Theory, however, leads us beyond this prescription from the proponents of
Total Rewards. Those proponents suggest that the value of rewards be measured and that the
most valued rewards be offered (subject to a cost effectiveness consideration). They do not
consider some of the subtleties suggested by Expectancy Theory. Expectancy Theory states that
for motivation to occur employees must perceive expectancy and instrumentality while Total
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Rewards does not mention these considerations. The implication is that, for Total Rewards to
work, the organization must make it clear to employees what rewards are offered and also how
employees can access those rewards. The organization must also ensure that mechanisms are in
place to ensure that employees who work hard and well actually get the rewards. Expectancy
Theory shows that there is more to deploying Total Rewards than telling employees about the
rewards available. For its part, Total Rewards introduces the idea of the cost effective rewards
mix. Expectancy Theory provides no place in its framework for this consideration.
This conceptual link between Expectancy Theory and Total Rewards suggests a
broadening of the scope of both models. Expectancy theory has largely been applied to the
question of how to motivate workers to work harder on their jobs. By linking it to total Rewards
we open up the possibility of applying it to the question of how to motivate workers to choose
one firm over another when seeking a job, and choosing to stay with a firm rather than moving to
another. Since Expectancy theory is a theory about choice, it easily encompasses this particular
set of choices. In choosing an organization, the worker, implicitly or explicitly, considers the
valences of the rewards available from each, the expectancies and instrumentalities attached to
each, and, therefore, the likelihood that those rewards will actually be attained. On the other
hand, attaching Total Rewards to Expectancy Theory opens up the possibility of applying Total
Rewards to questions of individual worker motivation to work hard. The conceptual route is now
opened to consider how to add expectancies and instrumentalities to the Total Rewards package
so that workers will do more than just join organizations, and stay with them, they will work hard
at their jobs to continue to get their rewards.
This discussion shows that although Total Rewards was conceived by practitioners who
were primarily concerned with recruiting and retention issues, it can be given a sound theoretical
basis in Expectancy Theory and shows promise for an extension into work motivation challenges.
Implicit in these considerations is the need for further research on these possibilities.
Conclusions
The literature review in this paper suggests that a Total Rewards strategy should have
business value in R&D. Most firms already offer rewards in all four categories, but most do not
manage them optimally. This is of particular concern in R&D settings where data clearly indicate
that career, personal development and the work itself are more important to R&D workers than to
most others. R&D rewards strategy should give serious consideration to all four quadrants. A
Total Rewards strategy has great potential to help improve the high turnover among technical
workers that has been signalled by a number of authors (e.g. Cordero, DiTomasso and Farris,
1994; Kochanski and Ledford, 2001; Kochanski et al, 2003). A number of suggestions for the
implementation of Total Rewards, based upon the literature review, have been provided.
The linking of Total Rewards to Expectancy Theory introduced several considerations.
Attention to expectancy and instrumentality in the implementation of total rewards was suggested
as well as the application of Total Rewards to issues of individual work motivation.
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However, the literature review found no studies that rigorously evaluated the efficacy of
any implemented Total Rewards program in R&D or elsewhere, although there is a report that
IBM’s program is working well (Platt, 2000) and that Ethicon is pleased with its program
(Thanasse, 2003). It is to be hoped that, if Total Rewards strategies are now being implemented,
rigorous evaluations of their efficacy will soon appear in the literature.
Total Rewards is an approach that makes pragmatic good sense. The empirical literature
suggests that it is a viable strategy for R&D workers. The idea of articulating the complete
employee value proposition holds much promise as a way to approach human resources issues.
Total Rewards has the potential to guide research programs and to aid human resource managers
in developing effective programs that support and fuel the strategic initiatives of organizations.
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