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DigitalCommons@ILR
CAHRS Working Paper Series Center for Advanced Human Resource Studies
(CAHRS)
11-1-1998
Measuring Organizational Performance in
Strategic Human Resource Management: Looking
Beyond the Lamppost
Edward W. Rogers
Cornell University
Patrick M. Wright
Cornell University
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Rogers, Edward W. and Wright, Patrick M., "Measuring Organizational Performance in Strategic Human Resource Management:
Looking Beyond the Lamppost" (1998). CAHRS Working Paper Series. Paper 135.
http://digitalcommons.ilr.cornell.edu/cahrswp/135
WWORKING ORKING PPAPER APER SSERIESERIES
Measuring Organizational Performance in
Strategic Human Resource Management:
Looking Beyond the Lamppost
Edward W. Rogers
Patrick M. Wright
Working Paper 9 8 – 2 4
CAHRS / Cornell University
187 Ives Hall
Ithaca, NY 14853-3901 USA
Tel. 607 255-9358
www.ilr.cornell.edu/CAHRS/
Advancing the World of Work
Measuring Organizational Performance WP 98-24
Page 1
Measuring Organizational Performance in
Strategic Human Resource Management:
Looking Beyond the Lamppost
Edward W. Rogers
and
Patrick M. Wright
Department of Human Resource Studies
School of Industrial and Labor Relations
Cornell University
393 Ives Hall
Ithaca, NY 14853-3901
Working Paper 98-24
http://www.ilr.cornell.edu/cahrs
This paper has not undergone formal review or approval of the faculty of the ILR School. It is
intended to make results of Center research available to others interested in preliminary form
to encourage discussion and suggestions.
Measuring Organizational Performance WP 98-24
Page 2
ABSTRACT
A major challenge for Strategic Human Resource Management research in the next
decade will be to establish a clear, coherent and consistent construct for organizational
performance. This paper describes the variety of measures used in current empirical research
linking human resource management and organizational performance. Implications for future
research are discussed amidst the challenges of construct definition, divergent stakeholder
criteria and the temporal dynamics of performance. A model for performance information
markets to address these challenges is introduced. The model uses a multi-dimensional
weighted performance measurement system and a free information flow exchange mechanism
for determining performance achievement criteria.
Measuring Organizational Performance WP 98-24
Page 3
Measuring Organizational Performance in
Strategic Human Resource Management:
Looking Beyond the Lamppost
"What are you doing?" inquired the policeman of the drunk crawling
on the pavement under the glow of a lamppost. "I am looking for my
quarter," came the reply. "Where did you lose it?" asked the officer
helpfully. "I dropped it over there by that payphone," retorted the drunk.
Incredulous, the officer asked, "Then why are you looking in the middle of
street?" "Because there is more light over here," he replied with his nose
nearly to the ground.
Introduction
Human resource management (HRM) is a relatively young field, which has undergone a
rapid evolution. From its initial roots as the function involved in the administrative aspects of
hiring, firing, and payroll, it has seen stages where union relations/avoidance, employee
satisfaction, and legal compliance have served as dominant areas of emphasis and expertise
(Noe, Hollenbeck, Gerhart & Wright, 1997). Most recently a trend has developed toward
justifying the expenditures for and existence of the HR function. HR departments and
programs have become an element of the firm's profit equation to be minimized as a cost and
maximized as a value-adding component of firm strategy. In fact, some in the popular business
press have characterized HR departments as bureaucratic wastelands and suggested doing
away with them (Stewart, 1996). Consequently, HR practitioners have become preoccupied
with demonstrating the value of the HR function, particularly through showing its impact on firm
performance (Pfeffer, 1997; Ulrich, 1997).
Fueled by this practitioner concern, recent academic research has attempted to
demonstrate the impact of HRM on firm performance. Not surprisingly, first attempts at
empirical linkage looked in areas of HRM that were already the most brightly lit by prior
research. Early in this stream, research linked individual HR practices such as training,
(Russel, Terborg & Powers, 1985) selection (Terpstra & Rozell, 1993) appraisals (Borman,
1991) and compensation (Milkovich, 1992) to firm financial performance. Huselid’s (1995)
work linking an index of HR practices to both financial and market outcomes and MacDuffie’s
(1995) study linking bundles of HR practices to productivity and quality exemplified a
progression toward examining the link between systems of HR practices and performance. In
fact, academic interest in showing HR’s impact on firm performance is evidenced by the fact
Measuring Organizational Performance WP 98-24
Page 4
that in the past 2 years three journals (Academy of Management Journal, 1996, No. 4;
Industrial Relations, 1996, No. 3; and International Journal of Human Resource Management,
1997, No. 3) have devoted special issues to research establishing this linkage.
Thus, both research and practice have seen an increasing preoccupation with linking
HRM to the firm’s performance. In spite of this emphasis, current research may not provide
sufficient justification for the HR function for three reasons. First, while a majority of the
published studies do show significant relationships between HR and firm performance, these
relationships are neither universal nor consistent (Becker & Gerhart, 1996; Wright & Sherman,
forthcoming). Second, while models of strategic HRM imply firm performance as the
dependent variable of ultimate performance, theory building in the area requires greater
precision regarding how firm performance should be defined and assessed (McMahan, Virick &
Wright, forthcoming; Wright & McMahan, 1992; Wright & Sherman, forthcoming). Finally, from
the standpoint of HR practitioners seeking to justify their programs alongside those of their
colleagues in accounting and finance, a focus on accounting and financial measures of
performance may be futile, as it requires competing according to accounting rules, time frames
and goal-value assumptions (Pfeffer, 1997). This paper is based on the assumption that theory
should drive decision analysis for research measures. Indeed, the lamppost metaphor is
employed to draw attention to the tendency to adopt highly visible or practical measures
instead of theoretically derived and more difficult to operationalize measures for organizational
performance.
Thus, the purpose of this paper is to review the measures of firm performance that
have been used in strategic HRM research, and to provide some recommendations for how the
field might expand both its conceptual definition of performance, as well as broaden the
measures used to assess the construct. In order to accomplish this, we will first examine the
concept of construct validity and its importance in organizational research. We will then
examine the construct of performance within both the strategy and strategic HRM literatures.
We will then analyze the ways that performance has been operationalized in strategic HRM
research. Finally, we propose some suggested future directions for assessing performance in
this research including a performance information market concept as a means for addressing
the challenge of construct definition within this stream of research.
Measuring Organizational Performance WP 98-24
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Construct Validity
Construct validity concerns the interface of psychometric and theoretical issues (Wright
& McMahan, 1992). Schwab (1980) defined construct validity as “the correspondence
between a construct (conceptual definition of a variable) and the operational procedure to
measure or manipulate that construct (p. 6). This differs from substantive validity, which is
concerned with the relationship between two different constructs. The construct validation
process consists of rigorously defining the referent construct, demonstrating internal
consistency of the measure, demonstrating both the measure’s convergence with other
measures of the construct and divergence from measures of other constructs, and specifying
and substantiating its relationship with other constructs in the nomological net (Cook &
Campbell, 1979; Nunally, 1978; Schwab, 1980).
The importance of construct validity in the theory building process is often
underestimated. Bacharach's (1989) model of theoretical social scientific inquiry examines the
relationships among constructs, theory and the research process. (See Figure 1.) In this
model, four links are proposed. Links A and B represent construct validity, or the relationship
between constructs and operationalized measures of those constructs. D represents the
theoretically specified relationship between two constructs of interest and C represents the
empirically observed relationship between the respective measures of the constructs. The
importance of construct validity stems from the fact that within the model, any one of the links
can be inferred as valid only to the extent that the other three are demonstrated or assumed to
be valid. Thus, if a statistically significant relationship at C is observed, the validity of the
theoretical proposition D can only be inferred to the extent that both the A and B (construct
validity) linkages can be convincingly assumed or demonstrated empirically.
In fact, Schwab stated that a consequence of inattention to construct validity concerns
is that “our knowledge of substantive relationships is not as great as is often believed, and
(more speculatively) not as great as would be true if the idea of construct validity received
greater attention,” (1980: 4). In other words, when inadequate attention is paid to construct
validity, our knowledge of substantive relationships is deficient. Such deficiency impedes the
theory building process (Bacharach, 1989; Schwab, 1980). Given the calls for greater
theoretical development in the field of strategic HRM (Becker & Gerhart, 1996; McMahan et.
al., forthcoming; Wright & McMahan, 1992), it seems logical to examine the construct validity
of the field’s major dependent variable: organizational performance. The lack of clear definition
Measuring Organizational Performance WP 98-24
Page 6
and validity for a performance construct may the limiting factor in current strategic human
resource management research.
This paper attempts to address this deficiency by proposing a theoretical framework for
defining and operationalizing organizational performance in a broad sense. First, we will
review current usage and meaning of organizational performance.
Figure 1
The Organizational Performance Construct
Organizational Performance in Other Fields
Organizational performance is probably the most widely used dependent variable in
organizational research today yet at the same time it remains one of the most vague and
loosely defined constructs. The struggle to establish a meaning for performance has been
ongoing for many years, and is not limited to the field of strategic HRM. Over thirty years ago,
Katz and Kahn dryly commented that, "The existence of the problem of developing satisfactory
criteria of organizational performance is clear enough; its solution is much less obvious" (1966:
150). Even twenty years ago Scott lamented the state of measures of organizational
effectiveness, concluding, “After reviewing a good deal of the literature on organizational
effectiveness and its determinants, I have reached the conclusion that this topic is one about
which we know less and less.” (1977: 63). More recently, Murphy, Trailer & Hill, after reviewing
theoretical
proposition
of linkage
construct
validation
empirical
hypothesis
of linkage
construct
validation
SHRM Knowledge Claim
HRM
Configuration
Construct
Organizational
Performance
Construct
HR Activities,
Policies and
Practices
Indicators of
Performance
Dimensions
B
A
C
D
Measuring Organizational Performance WP 98-24
Page 7
measures of performance in entrepreneurial research, concluded that, "… the lack of construct
validity for what we call performance is so clear that we as a field should consider
discontinuing the use of the term in research" (1996: 21).
Within the strategy field, the focus of attention on the performance construct has been
almost entirely on financial measures of performance (Rowe, Morrow & Finch, 1995).
Conceptually, it has been viewed as the comparison of the value created by a firm with the
value owners expected to receive from the firm (Alchian & Demsetz, 1972; Barney, 1997).
Venkatraman and Ramanujam (1986) noted that a narrow definition of performance “…centers
on the use of simple outcome-based financial indicators that are assumed to reflect the
fulfillment of the economic goals of the firm,” (1986: 803). They argued that the narrow
performance construct of “financial performance” had dominated the strategic management
literature, and proposed a broader performance construct of “business performance” that
would include both financial and operational (new products, product quality, market share)
indicators. In addition, they proposed a construct of “organizational effectiveness” which would
consist of business performance plus account for the accomplishment of the superordinate
goals held by multiple stakeholders.
Organizational Performance in Strategic HRM
Wright and McMahan in 1992 defined strategic HRM as “the pattern of planned human
resource deployments and activities intended to enable the firm to achieve its goals.” (p. 298).
Implicit in this definition is that the ultimate goal of strategic HRM is to contribute to
organizational performance through increasing the likelihood of goal attainment. For simplicity
the goal is often assumed to be financial performance or wealth creation. Considerable
research has attempted to test strategic HRM propositions, usually with the ultimate criterion
being how strategic HRM contributes to some measure of firm financial performance (Dyer &
Reeves, 1995; Wright & Sherman, forthcoming).
In their review of research on the efficacy of “bundling” HR practices within the field of
strategic HRM, Dyer and Reeves (1995), proposed four possible types of measurement for
organizational performance: 1) HR outcomes (turnover, absenteeism, job satisfaction), 2)
organizational outcomes (productivity, quality, service), 3) financial accounting outcomes
(ROA, profitability), and 4) capital market outcomes, (stock price, growth, returns). They
proposed that HR strategies were most likely to directly impact human resource outcomes,
followed by organizational, financial, and capital market outcomes. This stemmed both from
Measuring Organizational Performance WP 98-24
Page 8
the facts that HR strategies are primarily designed to impact HR outcomes, and that the
increasing complexity of factors which influence higher level outcomes would diminish the
relative contribution of HR factors to those outcomes. They suggested these facts, coupled
with the reality that human resource outcomes are deficient from the standpoint of most
executives might explain why most of the strategic HR research has focused on organizational
outcomes rather than the other three.
Note that implicit in this model, as well as others (e.g. Huselid, 1995; Truss & Gratton,
1994) is the basic idea that outcomes can be differentiated at hierarchical levels, with
outcomes at one level contributing (along with other outcomes) to outcomes at the next level.
While each model differs in the number of levels and the exact outcomes, a generic form of
the model is that HR practices have their most direct impact on HR outcomes, which in turn,
contribute to higher level organizational performance constructs.
The following section presents a detailed examination of the types of measures of firm
performance that have been used in strategic HRM research. By reviewing the measures
used, we sought to answer 3 basic questions: (1) What kinds of measures are being used, (2)
are the types of measures systematically related to aspects of the research such as the level
of analysis or source of the information, and (3) what control variables seem to be most often
used in this research. We also sought to clarify some of the tacit assumptions that color
thinking about organizational performance in hopes of shifting the research focus from where
there may be the most current research light to where there is the greatest need for further
empirical illumination.
Frequency of Use of Different Measures of Firm Performance
To assess the different types of measures of firm performance that have been used in
strategic HRM research, we examined the published literature linking HR practices to
organizational-level measures of performance. Studies were gathered from the three special
issues noted above, along with other studies of a similar caliber that have appeared in top
level HR journals. We limited our search to published studies because we felt it important to
examine only those measures used in research studies which have passed a refereeing
process. We recognize that this may skew the results if studies using certain types of
measures are being systematically rejected (i.e., it is the referee process, and not the research
designs which have limited the types of measures). However, if that were the case, the
Measuring Organizational Performance WP 98-24
Page 9
implication might only be that our suggestions regarding performance measures might apply
more to reviewers than to researchers.
This investigation builds on work done by Dyer and Reeves (1995) and Paauwe and
Richardson (1997). Dyer and Reeves (1995) reviewed 4 studies on the impact of “bundling”
HR practices on firm performance. Paauwe and Richardson (1997) identified 9 different
studies containing 22 empirically established relationships between HRM and performance.
Expanding on these lists, we identified a total of 33 studies on this relationship. Of these 29
were found to have quantifiable comparable variables (empirical data). Thus, our analysis is
based on the empirical results of the 29 studies containing 80 distinct observations of an
empirically tested link between HRM and organizational performance.
In categorizing the different measures, we adapted the typology offered by Dyer and
Reeves (1995). These authors broke down performance measures into human resource,
organizational, financial, and market measures. We followed these categories as closely as
possible using only the preselected group of articles from the journals previously mentioned.
In our analyses, the human resource category consisted of 3 studies that measured turnover.
The organizational category contained measures of productivity, quality, customer satisfaction
and manufacturing flexibility. The financial accounting category included measures of return
on assets (ROA) return on equity (ROE), profits, sales and employee value. The financial
market category consisted of measures of stock price, and two other measures derived from
Tobin's Q.
In addition to the performance measure, we classified the studies based on the level of
analysis, the source of the performance measures, the type of HR practices examined, and the
types of control variables used. Level of analysis was coded as the firm (corporation),
business unit (SBU), or plant (site). The source of the performance measure was classified as
being either via survey, company records, or publicly available information. The HRM
variables were grouped into six categories: work organization, high performance work systems
(HPWS), strategic HRM (SHRM), participation and motivation, training and selection, and
compensation. The studies were also coded as to control variables used in order to provide
guidance regarding what kinds of control variables seem most popular and/or appropriate. The
purpose of the data collection was not to perform a meta-analysis to determine a population
effect size, but rather to simply assess areas of opportunity for further research and to see
Measuring Organizational Performance WP 98-24
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what the empirical research to date reveals about an implicit meaning of performance for
SHRM.
The results of the analysis are frequency tables shown in tables 1 through 3. The
tables presented are for a descriptive look at what progress has been made in establishing
empirical linkages and what gaps still exist particularly with respect to converging on a
meaningful construct for organizational performance.
Table 1
Level of DV Analysis
DV TYPE Firm Bus Unit Plant Total
HR Outcomes 2 0 1 3
Organization Outcomes 14 4 16 34
Accounting Measures 21 1 2 24
Fin Market Measures 19 0 0 19
Total 56 5 19 80
It is immediately apparent that HRM outcomes have indeed become less interesting in
the context of organizational performance as there were few studies reporting HRM outcomes
(only three in this set that reported a turnover variable outcome). This would confirm what
Dyer and Reeves (1995) pointed to as the deficiency of HRM outcomes to be credible
indicators or meaningful representations of organizational performance.
Noticeable from Table 1 is the paucity of studies done at the business unit level. Only
5 of the 80 relationships came from studies at the business unit level. In addition, 56 of the 80
relationships were at the firm level. The preference for firm level performance measures is not
surprising given both the concern with demonstrating HR’s impact on firm level performance
and the relatively easy availability of these measure from public data bases such as
Compustat. However, the preference for firm over business level measures may be
problematic for both empirical and theoretical reasons. Empirically, the numerous complex
factors that operate to determine performance at this level (Dyer & Reeves, 1995) may make it
difficult to get accurate estimates of the impact of HR practices. More importantly, theoretically,
one would expect a tighter link between HR and strategy at the business rather than firm level
(Chadwick & Cappelli, forthcoming; Wright & Sherman, forthcoming). Clearly there is a need
for more empirical work at the business unit level to determine linkages between HRM and
Measuring Organizational Performance WP 98-24
Page 11
performance in the context of strategic parameters influencing choice and direction of HRM
policies and practices.
Table 2 reports the source of the data for the dependent variable used as a measure of
organizational performance. Not surprisingly, public data is most often the source for market
measures and surveys are the most frequent source of organizational, HR, and attitudinal
outcomes. While not overly surprising given the characteristics of the type of data in each
case, the fact remains that what is being called organizational performance is construed
differently and obtained from very different sources. Clearly, there is room to integrate these
different sources of data into a broader construct of organizational performance instead of just
choosing from among them.
Table 2
Source of DV Data
DV TYPE Survey Company Public DB Total
HR Outcomes 3 0 0 3
Organization Outcomes 25 7 2 34
Accounting Measures 4 2 18 24
Fin Market Measures 2 0 17 19
Total 34 9 37 80
Table 3 shows a surprisingly good distribution across the different HRM variable
categories. However, it is important to note that many authors have questioned the
operationalizations of the HR construct itself. Dyer and Reeves (1995) noted a failure to
observe significant overlap among items across the “bundles” of purported effective HR
practices in the 4 studies they reviewed. Becker and Gerhart (1996) also noted very little
overlap of items in the 7 studies they reviewed. Wright and Sherman (forthcoming) noted the
need to achieve some theoretical stability on both which HR practices should be measured
and how they should be measured. To empirically investigate the full relationship between
HRM and performance will require many more studies and much closer attention to the
operationalization of both the HR and performance constructs.
Measuring Organizational Performance WP 98-24
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Table 3
HR Independent Variable
DV TYPE WorkOrg
HPWT
SHRM PartMot TrainSel Comp Total
HR Outcomes 0 1 1 1 0 0 3
Organization
Outcomes 7 3 8 4 6 6 34
Accounting
Measures 3 0 3 5 4 9 24
Fin Market
Measures 0 5 2 5 2 5 19
Total 10 9 14 15 12 20 80
Finally, control variables are used in research because they are related to both the
independent (HR) and dependent (performance) variables. Failure to control for such
variables can result in either observing spurious relationships (observed relationships which
are entirely due to both variables covarying with the control) or suppression (when no observed
relationship is observed between the IV and DV because one of those variables has a
negative relationship with the control) (Schmitt & Klimoski, 1988). Thus, we wanted to identify
those variables that strategic HRM researchers have believed to be relevant to control for in
the HR - performance relationship. The most common control variable by far is size (75% of
studies), followed by Industry (35%), age (27%), location (24%) strategy (18%), and
Unionization (11%). This variance in controls used across studies may be due to the fact that
the large number of plant level studies do not allow for most of the controls commonly used.
Another reason may be the different hypothetical frameworks employed do not cover all of
these control variables. While using only study-relevant controls is appropriate for each
research endeavor, the poor overlap of control variable usage makes comparative analysis
among studies difficult or impossible. Further confusion may be buried in different methods of
controlling for size since proxy indicators such as number of employees, sales volume or even
profits may be used as a measure of size.1
Surprisingly, if strategic HRM propositions are correct that strategy is related to HR
practices and fit between strategy and HR is a precondition for effective performance then
business strategy seems clearly underutilized as a control variable. This may stem from the
fact that the plethora of typologies and matrices make strategy definition and codification
Measuring Organizational Performance WP 98-24
Page 13
difficult. Few studies seem willing to venture beyond familiar Miles and Snow (1978) or Porter
(1985) frameworks. Chadwick and Cappelli (forthcoming) have noted problems with such
measures of strategy in strategic HRM research.
The variance in use of controls may be somewhat problematic. One would expect that
if control variables stem from theoretical analysis of the types of variables that might be
relevant to the HR - performance relationship, then a consistent set of variables would
emerge., Without a clear and consistent definition of performance researchers are left to
choose the dependent variable according to what exogenous variable information may be
available or particularly pertinent to their own research question. The choice of level of
analysis may likewise simply be that of convenience. This ambiguity of construct definition
makes clear the need for clarity and consistency in future research as well as the need to
move beyond the circle of light below the lamppost of traditional micro HRM approaches in the
search for HRM significance at the organizational level. The remainder of this paper will
explore a new model for conceptualizing the measurement of organizational performance.
Towards an Expanded Model of Organizational Performance
The previous analysis identified some of the empirical trends in the use of performance
measures in strategic HRM research. As noted, while this research has helped advance the
field, the measures used seem to have some problems, that if not rectified, might result in
impeding theoretical development. In this section, we will examine some of the implications
and suggestions for measuring firm performance in future strategic HRM research. These
implications include varying the levels of analysis, distinguishing between efficiency and
effectiveness measures, integrating purpose and stakeholders into the performance construct,
and dealing with timing issues.
Varying Levels of Analysis
Again, our analysis indicates that significant research has tied HR to performance at
the firm and the plant levels of analysis, but that little research has examined this relationship
at the level of the SBU. With regard to specific HR practices, it is quite likely that a strong link
should exist at the level of the plant or site as MacDuffie (1995), Arthur (1994) and Delery and
Doty (1996) have demonstrated. In another study by Youndt, et al (1996), organizational
performance as a three dimensional concept of productivity, machine usage and customer
1 We thank Glenn Rowe for pointing out this multi-level confusion around size measurement.
Measuring Organizational Performance WP 98-24
Page 14
alignment was linked to HR practices in the context of quality improvement programs at the
plant level. In addition, as previously noted, significant theoretical rationale exists for a tightly
linked relationship between strategy and HR practices at the level of the SBU, yet this
relationship seems virtually untested (Rowe and Wright, 1997). Finally, the link between HR
practices and corporate strategy and corporate performance are less theoretically clear, yet
this seems to have been the focus of most of the strategic HRM research.
Wright and Sherman (forthcoming) suggested that one of the reasons for the failure to
find support for the efficacy of “fit” between HR and strategy may be a failure to recognize level
of analysis issues. Similarly, Chadwick and Cappelli (forthcoming) noted with regard to the
operationalization of strategy measures that level of analysis issues are important. For
example, they suggest that production strategies (e.g., lean manufacturing) are more relevant
to most auto assembly plant managers than Porter’s generic cost/differentiation/focus
(business unit level) strategy might be. In addition, within the strategy literature, corporate-level
strategies consist of decisions regarding the proper level and type of diversification and the
types of controls used by corporate headquarters to manage different business units rather
than the cost/differentiation/focus typology (Hill & Hoskisson, 1987; Hoskisson, 1987;
Hoskisson, Hitt & Hill, 1991; Rowe & Wright, 1997). Interestingly, most of the measures of
strategy have been based on the Porter typology (a business unit level typology), yet only 7%
of the effect sizes are from studies at the business unit level. The remaining 83% of the effect
sizes come from research at either the corporate or plant level, where a business unit level
typology may be less appropriate. In addition, corporate-level strategies (i.e., diversification,
controls) remain untested in strategic HRM research at the corporate level (Rowe & Wright,
1997).
In defense of the corporate level of analysis, Becker and Huselid (1998) argued “In our
work, we have chosen to emphasize the link between HPWS and corporate financial
performance. We do not argue that this is the only appropriate level of analysis, or that this
research question is not without [sic] methodological challenges. It is, however, ultimately the
raison d'être for a strategic HRM role in a firm." (italics authors) (p 14).
While we do not question the usefulness of examining the relationship at this level, we
believe that given the methodological and theoretical problems, it has been overemphasized in
strategic HRM research. Adopting simple market based measures may be a useful (and
practical) starting point for a new stream of research, but it does not negate the need for
Measuring Organizational Performance WP 98-24
Page 15
construct validity of the dependent variable. The fact that 'everyone is using it' does not make
stock price a valid research construct. More importantly, it does not begin to help unravel the
theoretical mechanisms in SHRM models. For example, Rogers and Boswell (1998) proposed
a Knowledge Utilization construct as a mediator between HRM practices and organizational
outcomes for knowledge intensive organizations. In order to pursue this type of linkage
research, there must be a stable sense of the dependent variable.
Distinguishing between Efficiency and Effectiveness Measures
Defining the performance construct necessarily entails a discussion of both
effectiveness and efficiency simultaneously. Here effectiveness means the achievement of
objectives. It is clearly a goal oriented measure (as opposed to a natural systems measure)
(Perrow, 1968). Efficiency refers to rates of resource usage in achieving objectives. To
balance these two dimensions requires an examination of assumptions regarding the
objectives of the organization in order to make a meaningful assessment of achievement. For
example, Ostroff & Schmitt (1993) demonstrated that organizations have different views of
performance in part because they view the relative importance of effectiveness and efficiency
differently. Ostroff & Schmitt (1993) and Steers (1975) both demonstrated that organizations
have different goals relating to effectiveness and efficiency measures. This means that one
simple indicator may not be sufficient to measure a broad array of organizations on simple
effectiveness or efficiency measures as even these are driven in part by organizational
objectives. As we will make clear in the proposed model, the stakeholders all have their own
objectives. The public market for performance information is where stakeholders assess how
well organizations are aligning with and meeting both explicit organizational objectives and
more tacit stakeholder objectives.
It seems reasonable that since different organizations have different goals and
objectives with regard to what effective or efficient means, there should be a dynamic
mechanism of measurement that is able to account for these differences. At the very least,
assumptions about what the organizational objectives are taken to be could be made much
more explicit. Probably some constraint is also in order regarding studies that link an aspect of
HRM with one particular outcome measure. These studies often banner an HRM connection
to organizational performance when a much more specific and narrow linkage is actually what
has been investigated.
Measuring Organizational Performance WP 98-24
Page 16
Considering Organizational Purpose and Stakeholders
Related to the issue of efficiency/effectiveness is the issue of purpose. To clarify
organizational performance, it is necessary to consider notions of organizational purpose since
outcome evaluation dictates an articulation of purpose. Steers (1975), for example, analyzed
17 models of organizational effectiveness and found that the field was not very effective at
measuring effectiveness because researchers for the most part ignored organizational goals.
He concluded that "…attempts to measure effectiveness should be made with reference to the
operative goals that an organization is pursuing; that is, criterion specification should be
flexible enough to account for diversity in goal preferences." (Steers, 1975, p. 555).
Purpose is necessary for performance measurement because it is not the simple
possession of an attribute (say a high sales volume or low turnover) but the utilization of that
attribute toward some end that reflects on performance. A specific utilization implies a purpose
or goal toward which the resource can either be used efficiently (and achieve the goal) or used
poorly, (not used or used for alternatives). For example, a high sales volume could be used to
pay high wages or it could be used to increase stockholder returns or even to pay for toxic
waste cleanup. Thus having a high sales volume in itself does not necessarily indicate high
organizational performance because it depends what the attribute of high sales volume was
intended to accomplish.
The discussion of purpose necessarily causes a reconsideration of stakeholder models
of organizations because purpose implies a beneficiary. Stakeholder theory is by no means
new to HR but was in fact one of the historical arguments for supporting the HR function. HR
was supposed to address a different group of stakeholders (employees) than the investor
relations group or the public relations department. A stakeholder model claims many
individuals and groups have an interest in the existence, processes, outcomes and reputation
of an organization beyond the recognized interest of capital owners. The stakeholder
discussion focuses the attention of organizational research on the dependent variable because
the choice of organizational performance indicator implies a chosen relative importance of
different stakeholder objectives for the organization.
For profit firms are assumed by many researchers to have a goal of wealth
maximization for their shareholders. This is clearly the position of Becker and Huselid (1997)
and Welbourne and Andrews (1996). However, other researchers focus on labor productivity,
safety or equality in compensation (Cowherd & Levine, 1992; MacDuffie, 1995). In addition, as
Measuring Organizational Performance WP 98-24
Page 17
previously noted, researchers within the strategy literature have called for expanding measures
of organizational performance to include the concept of purpose and to account for the desires
of multiple stakeholders (Venkatraman & Ramanujam, 1986). The selection of performance
criteria implies a set of assumptions about the relative importance of possible measures of
performance in relation to organizational goals and the interests of different stakeholders
Recognizing the limitations of single indicator measures of performance has led to
multi-dimensional systems of performance measurement. The correlation of accounting data
and non-accounting measures is an old question in organizational research. Johnson and
Kaplan (1987) argue that accounting data is not really objective at all in the sense that it is
constructed for accounting and management purposes (Johnson & Kaplan, 1987). Johnson
(1992) proposed that firms adopt more quality measures in performance evaluations to better
align organizational incentives with output oriented to the long term success of the enterprise.
Kaplan and Norton (1996) have established the practice of designing performance
indicators around the various stakeholders at the individual level as a means to align
managerial incentive systems with broader organizational goals. This “balanced scorecard”
approach entails identifying the 3-4 major stakeholder groups (usually including shareholders,
employees, and customers), and then developing objective indicators of performance with
regard to each group (e.g., ROE, turnover, and market share, respectively). This balanced
scorecard approach has similarly been advocated as a way for HR to demonstrate its impact
on firm performance (Ulrich, 1997; Yeung & Berman, 1997).
Another approach has been to combine a variety of seemingly disparate measures into
a composite score for performance. Martell and Carroll's (1995) study of SBU performance is
an example of this multi-dimensional weighted performance measurement system (MDWP).
The items on a MDWP type of measure do not necessarily correlate with each other. In fact,
they are theoretically selected specifically because they do not load onto a single factor.
Maximizing product quality may not maximize profits or minimize costs. It is the Platonic
approach to performance measurement, "moderation in all things," as the key to a long and
satisfied organizational life. The questions remains of how to build a meaningful performance
construct from multi-item factors that must be optimized together.
The appeal of a MDWP approach derives from the implied sub-maximization of some
measures to achieve a higher correlation with the abstract construct of organizational
performance through an optimization across the combined measures. Three assumptions lie
Measuring Organizational Performance WP 98-24
Page 18
behind the design of a MDWP. The first is that the different dimensions included in the scale
cannot be approximated by one of the items alone. Second, maximum organizational
performance does not necessarily mean maximum achievement on any one particular item in
the scale, ie. interaction is assumed. Third, time is recognized as an explicit dimension of
measurement as far as goal setting. Martell and Carroll found no short-term effect for SHRM
but also pointed out that it was probably not visible in cross-sectional data. (Martell & Carroll,
1995) It may be that cross-sectional SHRM studies are overly limited in their ability to detect
any HRM-Organizational Performance linkage. We will return to this issue later in our
discussion of time.
Given the need to integrate organizational purpose and stakeholder interests, it seems
likely that organizational performance will develop into a multi-dimensional construct.
Consequently, there will have to be mechanisms for taking into account different organizational
circumstances. This will likely involve some form of weighting scheme. The dimensions can be
weighted in line with the stated organizational objectives surrounding each area of activity or
policy to produce a desired organizational outcome against which actual outcomes can be
compared. What is still needed is an external set of performance measures and an external
assessment of what the organizational objectives should be. Both of these complications will
be addressed with the new model presented in this paper.
Since there are different dimensions of performance and different weightings of
importance for different organizations, the organizational performance construct must be
contingent to the organization and target audience including the utility of the performance data.
Along with developing multi-dimensional performance measures it is necessary to rejoin
effectiveness and efficiency conceptually. Multi-dimensional performance implies that a
school, for example, must both meet objectives (effectiveness) and meet standards (efficiency)
of operation. Just as managers face an optimization choice under a multi-dimensional
incentive program, organizations in reality face similar optimization choices rather than simple
one-dimensional maximization options. Research constructs for organizational performance
will take this multi-faceted aspect of organizational performance into account in the continuing
theoretical development of SHRM.
We argue that there really is no such thing as organizational performance without
organizational purpose and that there is no meaningful purpose apart from some specific
stakeholder. This concept is what has been called the 'ultimate construct' stream of thinking
Measuring Organizational Performance WP 98-24
Page 19
traceable from earliest philosophers but also recently apparent in specific reference to
organizational studies (Pedhazur & Schmelkin, 1991; Schwab, 1980). The ultimate construct
here is clearly the abstraction of organizational performance and it clearly means different
things to different people. This paper suggests an approach toward simplifying the
stakeholder issue with regard to the ultimate construct through what we call a Performance
Information Market system.
Performance Information Markets
The Performance Information Market (PIM) system will allow organizations to be
evaluated on their stated objectives and allow stakeholders to evaluate both the organizational
objectives themselves and how well the organization is achieving them. Four distinct
performance information markets are proposed: 1) the financial market, 2) the labor market, 3)
the consumer (product) market, and 4) the political (social) market. Organizations compete in
all four markets for success though with different preferential weights of importance.
Without knowing the relative importance of these performance information markets to
the organization, the organization's objectives and therefore its effectiveness cannot be
adequately determined. It seems strange to think of the Internal Revenue Service (IRS) as an
organization driven by maximizing profits. It is equally absurd to assess GM primarily on its job
creation capabilities or a public school system on its financial efficiency. That's because these
organizations have different weights of importance for the four different PIMs. Nevertheless, a
school system grossly inefficient over a long period of time loses credibility and probably
viability in the political market. In other words, organizations play in all four PIMs but with very
different weights and different time frames. Researchers routinely recognize these different
emphases in their choice of performance measures but have not had a way to integrate the
variability across organizations.
Figure 2 is a simple representation of the PIM concept. Organizations set goals and
strive to achieve them. Stakeholders have expectations and standards they look for in
assessing organizational performance. By categorizing the various types of organizational
performance measures into four information markets, these two groups can arrive at a market
clearing 'price' for participation. For example, if a for-profit firm is entirely concerned about
financial returns while it dumps toxic waste in the river, environmental performance demands
will rise and exert pressure for the firm to increase its internal weighting of the importance of
measures of performance relevant to the social/political performance information market. A
Measuring Organizational Performance WP 98-24
Page 20
good example of the interplay of these markets is the story of Ben & Jerry's ice cream
business. The well publicized struggle over salary and the appointment of a new executive
officer were clear examples of their attempts to manage performance simultaneously in
different PIMs.
Likewise, the public expects fairness from the IRS (a high weight on a social PIM) yet
the IRS also clearly participates in the labor PIM. Depending on the organization structure and
purpose, the weighting of the PIMs will vary. These weightings will also change with time and
circumstance. (the Exxon Valdez oil spill accident raised Exxon's relative importance in the
Political/Social market). This framework of PIMs may provide a mechanism to integrate and
quantify organizational objectives to build a multi-dimensional dynamic construct for
organizational performance. Through the use of surveys and ranking studies combined with
already in use objective performance measures, scales for each PIM can be constructed with a
very broad range of application. The markets function because information flows relatively
freely, and the political social environment allows for feedback loops at various levels. The
markets clear when participants are satisfied with the combination of weighted performance
measures presented.
Operationalizing this model will require a synthesis of stakeholder models, transactional
cost analysis, and resource based view of the firm theories to predict behavior by stakeholders
and organizations. As daunting as this task may seem, it is the charge of SHRM to theoretically
link micro HR with macro HR. The PIM approach may provide a conceptual way forward in that
endeavor.
Measuring Organizational Performance WP 98-24
Page 21
Considering Timing Issues
Finally, strategic HRM research must recognize that organizations exist over time.
They do not necessarily have an endpoint as a goal. To obtain many of the measures used to
assess organizational performance a time frame is arbitrarily chosen. It may be an accounting
cycle, a business cycle or other period of time. Over the chosen time period an intermediate
criterion is used to obtain a point estimate of performance in time. Often an assumption is
made of linearity of change over the time period. The arbitrary selection of a time frame is a
compromise that is accepted. However, it is important to be careful about selecting a time
frame because time frames can be stakeholder specific. Financial returns do not coincide with
cycles of toxic waste dumping. Agency theory may help explain some of the opportunistic
behavior when different stakeholder time frames do not coincide.
The PIM model allows for some differentiation of time frames because the different
PIM's themselves can carry inherently different time bases. By having four different markets,
the non-financial measures can be released from the rigid and short term financial reporting
cycles. The time constraints of financial information markets is a commonly cited obstacle to
achieving more robust measures of organizational performance. Recognizing different PIMs
allows a relaxation of the need for singularity of time period in the performance construct
because the four markets can use different time bases. For example, the financial information
market is primarily driven by investor time preferences. The labor market clearly looks beyond
quarterly performance to career management and long-term equity development (intellectual
Organizational Performance Information
Figure 2
Financial/
Accounting
Consumer/
Product
Social/
Political
Labor/
Employee
Organization
Goals
Stakeholder
Goals
Measuring Organizational Performance WP 98-24
Page 22
asset appreciation). Environmental social concerns may be operationalized on an even longer
time frame. Yet, these markets will still all 'clear' in the exchange of performance information
and recognition between users and providers of performance information.
In one sense, cross-sectional research which is relational by definition, can never hope
to explain HRM causal effects on performance, which are time-laden effects. Issues of
simultaneity and reverse causation will continue to plague research in this area until consistent
and logical time frames are incorporated into the performance measures. Performance will
become a more explicitly time dependent construct in future work of HRM researchers
because research that attempts to show an SHRM effect will need to be more than cross-
sectional in nature. (Ostroff & Schmitt, 1993)
Finally, there may be some lessons for SHRM to learn from the development of
macroeconomics. Von Mises argued vehemently against the Keynesian logic of using
averages to predict means because the aggregates and means are not really related at any
one point in time (Mises, 1990). Indeed, a reason of the downfall of Keynesian theory was its
inability to explain individual behavior in response to money supply or taxation in relation to
economic growth. As Hayek and later Friedman pointed out, it is the microeconomic elements
of individual action, which cause sequential effects over time to affect the relative structures of
price and production. To avoid the same pitfall, SHRM must capture the sequential effect of
micro HR effects over time in assessing organizational performance with respect to different
stakeholder groups. Then SHRM may become more effective at developing a theoretical base
for linking macro HR structures and strategies with micro HR policies and practices.
Conclusion
Like the drunk in the middle of the street, early SHRM research to link HRM with
organizational performance has spent much effort looking where there is already light. As our
quick analysis has shown, there are gaps and thin spots where much more empirical work
needs to be done. Importantly, future empirical work to formulate a clear and comparable
construct for organizational performance that integrates the stakeholder markets with respect
to time will require expanding the concept of performance. The PIM model is suggested as a
means of doing that. Instead of searching for the universal theory of HRM under the lamppost
of stock price, the recommendation of this paper is that the field should establish construct
Measuring Organizational Performance WP 98-24
Page 23
validity and dimensionality that will allow development of theories of macro HRM for all types of
organizations: profit, not for profit, government agencies and perhaps even universities.
Universal application of macro HRM models of analysis with dynamic constructs for
performance may prove more achievable and useful than the search for a single universal
linkage of micro HR to a particular measure of organizational performance. Just as happened
with the field of economics, human resource management is developing a clearly
distinguishable macro side. The HR field must face the questions of micro-macro linkage, bias
in aggregation, and plausible mechanisms of action to connect individual human activity in the
form of HRM with organizational performance. How these questions are answered will in large
part determine the direction and utility of the field in the next decade. A case has been made
for expanding the concept of performance to enable establishment of a general construct for
organizational performance through the adoption of a performance information market
concept. The PIM concept needs to be equipped with variables and the model's mechanism of
interaction verified by empirical investigations. Clearly, more research needs to be done
linking SHRM with organizational performance. Hopefully, this review and the proposed new
model will move the search toward more fruitful hunting grounds than simply the middle of Wall
Street where the light has traditionally been the brightest.
Measuring Organizational Performance WP 98-24
Page 24
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