CAHRS / Cornell University
187 Ives Hall
Ithaca, NY  14853-3901  USA
Tel.  607 255-9358
www.ilr.cornell.edu/CAHRS/
W O R K I N G  P A P E R  S E R I E S
Human Resource Metrics:
Can Measures Be Strategic?
John W. Boudreau
Peter M. Ramstad
Working Paper  9 8 – 1 0
Advancing the World of Work
Human Resource Metrics and Human Resource Strategy                                                                                        WP 98-10
Human Resource Metrics:
John W. Boudreau
ILR School
and
Personnel Decisions International
Professor John W. Boudreau
Department of Human Resource Studies
Cornell University, 393 Ives Hall
phone:  607-255-9358
email:  jwb6@cornell.edu
Thanks to Pat Wright for comments on an earlier draft of this chapter.
Working Paper 98-10
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.
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Human Resource Metrics and Human Resource Strategy WP 98-10
ABSTRACT
For SHRM to advance, it must eventually be based on a theory that specifies not only
concepts and relationships, but appropriate and high-quality measures to express and test
them.  For metrics to advance beyond simply a large inventory of potentially-useful indices with
no integrating logic or theory, they must be driven by a strategic perspective that can identify
key measures, their necessary characteristics, and the linkages necessary to test and enhance
their quality.  To date, metrics theory and SHRM theory have not connected, to the detriment
of both.  This chapter suggests a general framework for strategic HR metrics,  as a starting
point for integrating SHRM and measurement research, demonstrating the key role that the
metrics issue plays in fundamental SHRM theoretical dilemmas, and showing how principles
and evidence from measurement theory (e.g., linkages, constraints and constituent responses)
may inform the theoretical and operational issues facing future SHRM research.
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Human Resource Metrics and Human Resource Strategy WP 98-10
The idea that an organization’s people represent a key strategic resource is widely
accepted.  The business press is filled with examples of top executives proclaiming how
important it is to engage people’s minds and spirits in the quest for competitive advantage
(Boudreau & Ramstad, 1997; Boudreau, 1995).  Virtually every currently-popular business
model emphasizes the key role of people in organizational success.  Tracey & Weirsema
(1997) suggest that organizations compete through Operational Excellence, Product
Leadership, or Customer Intimacy, with each market discipline implying different organizational
and human design factors such as “culture” “organization,” and “management systems” that
embody human attributes such as “discipline” and  “desire to win.”
Kaplan & Norton’s  (1996) “balanced scorecard” concept of measurement,
incorporating Financial, Customer, Internal Business Processes, and Learning/Growth implies
that employee learning and growth must be clearly linked and measured consistently with the
organization’s key strategic approach to success.  They propose that a measurement system
should embody a “theory of the firm,” with measures serving as ongoing tests of that theory,
and indicators to show when the theory or the outcomes need to change.  Similarly, Reichheld
(1996) notes that the “Loyalty Effect” rests on creating loyal employees who engender loyalty
among customers,  which in turn leads to loyal shareholders, willing to provide capital for the
long run.  There is also mounting scientific evidence that certain “bundles” of “high-
performance” work practices (e.g., performance-contingent pay, team-based work structures,
selective recruitment and hiring, extensive training, etc.) are associated with higher
organizational financial performance (Arthur, 1992; Becker & Huselid, in press; Ichniowski,
Shaw & Prennushi, in press; MacDuffie, 1995; Welbourne & Andrews, 1996).
Clearly, human resources are widely recognized as fundamental to organizational
strategy, and SHRM is seen as a key and leading determinant of organizational success,
similar to capital, land, marketing, finance and operational investments (Boudreau & Ramstad,
1997).  Yet, it remains rare to find organizations whose human resource investments are
clearly linked and measured in accordance with strategic goals.  Linkage is often articulated,
even at the highest levels, in phrases such as “People are our most important asset,” but HR
measurement systems rarely reflect a logical theory regarding how human factors translate
into strategic outcomes.  For the most part, the management of people retains a focus on
administrative efficiency, traditional and disconnected functional initiatives, and measurements
that focus on activities rather than strategic outcomes. There are literally thousands of cost-
based and ratio-based measures available to researchers and managers (e.g., cost per hire,
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Human Resource Metrics and Human Resource Strategy WP 98-10
trainee, recruit, employee; number of HR employees per total employees, etc.).  Witness the
broad variety of metrics currently reported in the area of intellectual capital (Edvinsson &
Malone, 1997;  Stewart, 1997).  This proliferation of HR measures may actually contribute
significantly to the difficulty in associating cause and effect in SHRM.  While many of these
metrics may emerge as useful leading indicators of strategic organizational outcomes, not all
of them are likely to be equally as valuable in practical strategy making or strategy research.
Thus, metrics theory can benefit from frameworks that merge measurement with SHRM.
At the same time, the field of strategic human resource management (SHRM) lacks a
framework of measurements that reflect the richness of the linkages between human factors
and strategic outcomes.  As other papers in this volume observe (McMahan, Virick & Wright, in
press; Chadwick & Cappelli, in press), SHRM research often proceeds from very disparate
conceptual frameworks, adopting measures that are often derived for one particular study, that
may or may not be comparable across studies, and that may not reflect key intermediate
linkages underlying general relationships.  One study may relate organization-wide financial
measures to reported HR practices, while another may measure outcomes at a particular
production site and relate them to site-level indicators of efficiency.  Can these approaches be
linked within a common framework that might encourage more integrative contributions?
For SHRM to advance, it must eventually be based on a theory that specifies not only
concepts and relationships, but appropriate and high-quality measures to express and test
them.  For metrics to advance beyond simply a large inventory of potentially-useful indices with
no integrating logic or theory, they must be driven by a strategic perspective that can identify
key measures, their necessary characteristics, and the linkages necessary to test and enhance
their quality.  To date, metrics theory and SHRM theory have not connected, to the detriment
of both.  While a complete inventory of SHRM measures is not feasible today, this chapter
suggests a general framework for strategic HR metrics,  as a starting point for integrating
SHRM and measurement research.  The chapter demonstrates the key role that the metrics
play in fundamental SHRM theoretical dilemmas, and shows how a metrics framework may
inform and reveal theoretical and operational issues facing SHRM in the future.
HOW HR METRICS ADD VALUE
Metrics support SHRM in at least two ways.  The first, and perhaps most obvious, is
that testing SHRM theories and propositions requires developing or finding measures of key
variables.  The second is the effect that metrics may have on the strategy and decision-making
process.
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Human Resource Metrics and Human Resource Strategy WP 98-10
Guiding the Choice of Variables to Test Theory
Obviously, in order to test SHRM propositions, operational measures of the variables
must be developed.  Less obvious are the underlying assumptions and inferences behind the
measures.  For example, a correlation (even lagged over time) between reported HR practices
and financial performance may create an inference that HR practices lead to financial
performance, but does not necessarily prove this inference.  As Gerhart (in press) points out in
this volume, these results may support several alternative explanations, including the
possibility that those reporting the HR practices modify their perceptions of the practices based
on their assumptions about which practices associate with good or poor firm performance.
McMahan, Virick and Wright (in press) characterized existing SHRM research as “data -driven
theory application,” meaning that data are collected and linked to elements of one or more
theories, and results are interpreted within one or more of those theories, but in many cases
“the relationship between the two variables is dependent upon a number of intervening
conditions” implicit in the theory, but perhaps not tested.  Thus, the choice and presentation of
particular metrics reflects both explicit and implicit assumptions and frequently leads to
inferences about unobserved effects.
A framework for SHRM metrics should enable researchers to better articulate which
processes they are choosing to measure, which are unmeasured, and what metrics might be
used to fill in the gaps.  Thus, as SHRM researchers consider appropriate variables to test
theory, a metrics framework can assist by showing the nature of the measures necessary to
support or refute the inferences being made.  It is not sufficient merely to provide a list of
alternative measures. HR metrics must systematically link to the strategic objectives of the
organization, and serve as a template on which to test and validate a “theory of the firm” that
comprises the link between people and organization performance (Boudreau & Ramstad,
1997; Becker & Huselid, in press).  Thus, it is incumbent on those who develop and apply
SHRM theory to choose appropriate measures, but it is also incumbent on measurement
developers to provide a theory-based framework , not simply an ever-growing list of new
measures.
For example, while there is no shortage of financial measures that can be correlated
with human resource activities or bundles, rarely does theory precede the choice of the
measures.  It is quite interesting to discover that stock price or Tobin’s Q correlate with the
number or bundles of HR activities reported in a firm. Certainly stock prices and market value
creation get attention from investors, but it is the intervening variables and their measurement
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Human Resource Metrics and Human Resource Strategy WP 98-10
that define the theoretical logic of the relationship.  Perhaps market share, sales growth, cost
reduction, margin growth, etc. are more appropriate outcome measures, and perhaps attitudes
a more appropriate indicator of HR health.  One can envision an explosion of studies
correlating every imaginable index of HR with whichever financial measure is currently
fashionable, but without a measurement framework, it will be difficult to develop theoretical
logic or measurement rigor to support the inference that investments in human resource
strategies lead to organizational success.  A framework articulating the strategic and
measurement linkages provides an ability to direct and compare such results.
Constituent Responses:  Effects of Metrics on Strategic Decision-Making
Boudreau (1995) noted that HR metrics create value (or harm) according to their effects
on key constituencies, suggesting that metrics research adopt a "choice" model of HR
measurement, in which such systems are adopted based on communication goals and
probable receiver responses (Shelby, 1988, 1991).   Possible uses of HR metrics include
persuasion, fashion-setting and decision support.   Persuasion involves influencing receivers
of HR information in ways that benefit the senders of that information (Quinn, Hildebrandt,
Rogers & Thompson, 1991; Reardon, 1991; Perloff, 1993).  Thus, an alternative framework for
viewing the strategic impact of measures is the whether information receivers (e.g.,
employees, managers, shareholders, regulatory agents) react in ways that favor the
information provider (often an HR manager). “Fashion-setting” involves convincing others that
practices are innovative and based on the latest thinking (Abrahamson, 1991).  Under this
theory, metrics have value in this framework if they signal that HR practices are “progressive”
in emulating fashion setters or are frequently emulated by others.  Finally, “decision-support”
suggests that HR metrics create value to the degree that they improve more decisions, that the
decision improvements have significant value, and that the cost of the metrics does not offset
this value (Boudreau, 1991).
Thus, the choice of HR metrics will affect the strategy-making process.  Metrics are not
neutral.  The choice of metrics conveys values, priorities and a strategic framework.  Moreover,
metrics generally reflect an implicit constituency for the strategy process. Thus, whether
intentional or unintentional, the choice of HR metrics sends signals that will affect the decisions
of these constituents.  Consider the strategic decisions involved in mergers and acquisitions,
for example.  The measures used to guide such decisions virtually always reflect resources
such as capital, markets, technology, brands, etc.  They frequently omit any explicit index of
human factors, and are often presented as a method of shedding extraneous labor.  A
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Human Resource Metrics and Human Resource Strategy WP 98-10
strategic approach to measurement must incorporate the likely effect of such measures on the
perceptions of employees involved.
To be “strategic,” metrics must be perceived and experienced to enhance decisions or
other valued outcomes for key strategic constituents. Constituents typically considered are the
shareholder or client for human resource outcomes (usually a line manager), but in fact metrics
will send signals and likely affect the behavior of a broad set of constituents including
employees, unions, governments, communities and customers.  Subsequent sections will note
how the role of metrics in the strategy-making and strategy-interpretation process is a key
component of a strategic measurement framework, and the importance of explicating the
constituents for HR metrics and SHRM.
LINKAGE AND STRATEGIC HR METRIC SYSTEMS
Throughout SHRM, there are increasing calls for greater cause-effect theory and
knowledge. Wright & Sherman (in press), in this volume, call for models that can test linkages
between HR practices, through potentially mediating employee attributes and behaviors, to
financial performance, noting that no study to date has tested the full model.  This is another
illustration of the lack of integration between measurement research, which has largely
focused on effects of programs on relatively proximal outcomes (learning, attitudes,
performance ratings), and strategy research which has focused on relationships between
groups of HR programs and unit-level outcomes.  Wright and Sherman note inconsistencies in
the SHRM literature with regard to what is meant by HR (practices, employee skills, employee
behaviors), what HR practices constitute the commonly-used notion of “high-performance work
systems,” and in the organizational outcomes studied.  We contend that defining which HR
practices should be included in SHRM cannot be done without a measurement framework that
articulates linkages.  A metrics framework can provide guidance and the beginning of a
common language for dealing with these issues.  We need not strive for a single definition, but
rather we require a framework for articulating which measures reflect a particular construct and
why.
Let us take the “value-based” theory as an example.  The “value-based” theory of the
organization suggests that sustainable competitive advantage is created through resources
that are valuable, rare, difficult to imitate, and supported by organizational structures that allow
them to be exploited effectively (Barney & Wright, 1997).  An effective HR metrics system
would focus on linkages that are most likely to have these characteristics.  Barney & Wright
(1997) and Coff (1997) give several examples showing how human resources can contribute
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Human Resource Metrics and Human Resource Strategy WP 98-10
to sustainable competitive advantage by creating links between levels of effect.  The key is
related not just to the resources themselves, but to the ability to use resources to strategic
advantage (Stalk, Evans & Shulman, 1992), which requires theories and metrics that reflect
linkages.
Figure 1 presents these concepts graphically. This chapter will discuss each element of
the Figure in detail. Human resource activity “bundles” support human attributes of Capability,
Opportunity and Motivation (COM).  These attributes enable employees to enact critical
behaviors that represent the “Moments of Truth” experienced by key constituents.  These
moments of truth affect constituent perceptions and reactions, forming the basis for
successfully accomplishing the key “Business Processes” of the organization, including “new
product introduction,” “market intelligence,” “productivity/quality,” etc.  Finally, the successful
execution of the business processes leads to success in achieving the value propositions.
Examples include “operational excellence,” “product leadership,” and “customer intimacy”
(Treacy & Weirsema, 1997).
Value Propositions
“How Do We Compete?”
Business/Organization Processes
“What Must We Execute Well?”
Moments of Truth
“What Employee Behaviors 
Must Constituents Experience?”
People COM
(Capability, Opportunity, Motivation)
“What People Elements Must Exist?”
Human Resource Bundles
“What Work Practices 
Support High Performance?”
Figure 1.  The Linkages Integrating Human Resource Metrics and Strategic
Human Resource Management
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EXECUTION
PLANNING
Human Resource Metrics and Human Resource Strategy WP 98-10
Notice the two arrows in Figure 1.  They are meant to convey the synergy between
strategic planning, measurement and execution.  When planning, the development of metrics
proceeds downward, from the value proposition to the bundles.  However, when executing the
strategy, the causal direction moves upward.  Similarly, metrics should be designed based on
the strategic vision embodied in the value proposition, and work downward to articulate ever-
more specific outcomes, but actual implementation of metrics systems will frequently involve
tracing linkages from the bottom up.   Moreover, the effect of metrics is often best measured at
all levels, because key constituents are likely to exist at all levels.  Becker and Huselid (in
press, Figure 1) suggested a similar model, and noted the need to “peel back the onion,” and
identify the intermediate relationships that seem to underlie the association between bundles
of high-performance work practices and overall organizational success.  This model is also
consistent with the premise of the “loyalty effect” (Reichheld, 1996) and with Treacy and
Wiersema’s (1997) notion that competitive strategy is supported by “Culture, Organization, and
Management Systems” (a mix of the Human Resource and Organization levels) which create
and support certain “Core Processes,” which in turn enhance the organization’s capability to
enact its competitive discipline and reap market rewards.  The notion of intellectual capital
(Bontis, 1996) encompasses human capital (capability), customer capital (moments of truth),
and structural capital (opportunity). The model is also consistent with Guest’s (1997)
suggestion that SHRM extend theories about how performance and HRM are linked.  Finally,
we see expressions of the linkage concept in some empirical SHRM studies, where
researchers focused on a level of analysis at which clear intermediate links could be
discerned, such as distinct lines of business in insurance (Chadwick & Cappelli, in press) or
auto assembly plants (MacDuffie, 1995).
Kaplan & Norton (1996) propose that a measurement system should embody a “theory
of the firm,” with measures serving as ongoing tests of that theory, and indicators to show
when the theory or the outcomes need to change.   This means that strategic HR metrics
should express a theory of the firm through linkages from people to organizational outcomes.
HR metrics are not simply an evaluation tool, or a method of justifying HR investments.
Rather, they represent the operational expression of the theory of how people contribute to
organization success, and the HR investments that lead to that success.
CONSTRAINTS AS A KEY TO STRATEGIC HR METRICS
Like the  concept of constituent responses, the concept of constraints is fundamental to
measurement theory in management.  As Boudreau and Ramstad (1997) noted, this concept
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Human Resource Metrics and Human Resource Strategy WP 98-10
explains the emergence of key measurement systems throughout financial history.  The
principle is that measures provide the most information when they enhance decisions about
key constraints.  For example, there was little need to measure time zones until travel speed
created a strategic constraint in the capability to integrate delivery schedules across regions.
Similarly, the familiar DuPont model on which most financial reporting is based emerged with
the advent of capital markets, and reflects a fundamental premise that capital is the key
constrained resource (hence the common goal to maximize overall return on capital
employed). Boudreau and Ramstad (1997) proposed that this underlying premise explains
many limitations in the DuPont model in a world in which human factors may be the more
significant constrained resource.
Thus, strategic HR measurements should focus on key constraints.  Less obvious is the
corollary that HR strategy must also identify and address key constraints (Ramstad, 1996).
Subsequent sections will suggest how this principle of constraints informs the integration of
SHRM and HR metrics.
ELEMENTS OF THE STRATEGIC MEASUREMENT MODEL
The Value Proposition …  How do we Compete?
Kaplan & Norton (1996), drawing on Porter (1985),  define the value proposition as “the
attributes that supplying companies provide, through their products and services, to create
loyalty and satisfaction in targeted customer segments.” Treacy & Wiersema (1997) distinguish
“Operational Excellence,” “Product Leadership,” and “Customer Intimacy,” suggesting that
successful firms will choose to excel in one, and meet competition in the other two.  Chadwick
& Cappelli (in press), in this volume, observe that such prescriptions may overlook the
necessary richness needed to discern relationships with strategy, and the common tendency
for researchers to rely on simplistic strategic definitions.  They suggest that for strategy to be a
competitive advantage, either the strategy or its related “path dependencies” or links, must be
difficult to imitate.  Figure 1 suggests that the appropriate strategy definition and granularity will
be determined by considering  what measures support the linkages expected, rather than what
generic strategy definitions are available.  In essence, the model suggests working from the
bottom up, to ask “if we surmise these linkages, then what value proposition measures are
necessary to express them?”
What are the likely indicators of success at value creation?  Kaplan & Norton (1996)
suggest such while metrics must link to the financial outcomes of the organization, they cannot
be limited to financial outcomes, which often lag success.  They suggest adding customer
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Human Resource Metrics and Human Resource Strategy WP 98-10
satisfaction, retention, new customer acquisition, customer profitability and market and account
share.  As Chadwick and Cappelli (in press) note, the appropriate unit for the measurement of
SHRM relationships will often be the unit, not the broader corporation, because only at the unit
level can the value proposition be discerned with enough detail.  The metrics model in Figure 1
suggests using the linkage concept as a guide.  One might ask, “what is the largest
organizational unit at which it is reasonable to infer and measure the linkages” and “what is the
smallest unit at which it is reasonable to define a value proposition?”?  SHRM effects may best
be investigated at that level.  Thus, this element of the measurement model may provide a
methodological diagnostic, that can be tested by the reliability and inter-rater agreement
around the definition of the value proposition.
For example, several studies of the auto industry focused on plant-level outcomes
(e.g., production costs, scrap, etc.) related to the adoption of high-performance work systems
(Ichniowski, Shaw, & Prennushi, 1997; MacDuffie, 1995).  While plant-level outcomes may not
map directly to ultimate share prices for multinational auto companies, the richness of the
description and the clear logical and theoretical linkage is enhanced because measurement
linkage is clear.  At the other extreme, correlations between firm-level HR practices and stock
price are intriguing, but more difficult to articulate linkages.  The measurement model of Figure
1 thus suggests that SHRM research decisions about the unit of analysis be driven, at least in
part, by the availability of sufficient measurement linkage.  Moreover, incorporating the value
proposition, rather than simply financial measures, in Figure 1, we attempt to capture the
notion that SHRM researchers should begin by asking whether a value proposition can be
articulated at the level of their analysis.  At too small a level (e.g., the HR activity), no value
proposition may be visible.  At too high a level (e.g., the total HR actions of General Motors),
the value propositions are simply too diverse.
Constituent Responses to the Value Proposition
While it is useful when the key constituents for HR metrics can agree on value
propositions, it is frequently the case that even shareholders and line managers have not
considered this question.  Kochan (in press) in this volume suggests that when SHRM defines
this proposition only in terms of business success and shareholder value, SHRM risks missing
significant elements of the broader value proposition, and the effects of strategy on
constituents such as communities and governments.  Another implication of the concept of
constituent response is the effect of metrics on the strategy-making process.  For example,
Bamberger and Feigenbaum (1996) noted the role of “strategic reference points” in framing
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Human Resource Metrics and Human Resource Strategy WP 98-10
how decision makers evaluate strategic options.  Thus, the metric chosen may well influence
the strategic response.
Constraints and the Value Proposition
The appropriate choice of constituents and value propositions is difficult.  How can one
begin to choose which value proposition or constituent is key?  There is no complete answer to
this question, but consider the idea that useful measures tend to reflect limiting constraints
(Boudreau & Ramstad, 1997).  One can find clues to the key factors by examining constraints.
To take a simple example, consider two pharmaceutical companies, one that relies on drug
development and being first with the newest product (e.g., the newest breakthrough in disease
treatment), the other that relies on quick and low-cost production of standard drug therapies
(e.g., over-the-counter pain medication).   The first company may have plenty of new proven
drug ideas, competitive marketing and distribution, and ready production facilities, so is not be
limited by operational, customer, or even product innovation propositions.  The key limit may
be getting through the drug approval process as efficiently as possible.  Thus, the key
constituents are the drug regulators.  The second company manufactures products that have
already survived the approval process, and so would face completely different constraints.
Despite the fact that the two companies share the same industry, constraints suggest
suggesting a very different value proposition, and thus metrics reflecting how human resources
contribute to strategic success.  Without understanding constraints, SHRM research may well
focus on the wrong factors. With attention to constraints it becomes clearer which value
propositions are key, and at what level they should be measured.
Business Processes …  Initiatives for Achieving Value
With value-creation metrics established, it is possible to begin “drilling down” into the
organization level of analysis to identify the business processes that logically support the
value propositions.  What metrics would indicate that the business or business unit is
achieving results that will lead to the value propositions?  For example, Kaplan & Norton
(1996) describe “internal processes that will have the greatest impact on customer satisfaction
and achieving the organization's financial objectives”.  We would argue that the constituent
set should be far broader than customers and financial observers, as Kochan (in press)
suggests.  Kaplan and Norton further note that metrics at this level should go beyond
examining the performance of existing business processes, (e.g., terms of time, cost or
quality), which they call the “short wave” of success, but should also explicate new business
processes, or processes in need of reengineering, and measure the performance of those
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Human Resource Metrics and Human Resource Strategy WP 98-10
efforts as well.  Thus, metrics should include innovation, to capture the organization’s
performance on the “long-wave” of success.  The literature on intellectual capital similarly
suggests attention to both the “stock” of such capital and the organization’s ability to
efficiently promote a productive “flow” of the existing capital, and its translation into value
through the value propositions (Bontis, 1997).  Treacy & Wiersema (1997) note that each
value discipline has a corresponding set of  “core processes” (e.g., “product leadership” is
supported by  “invention/commercialization, market exploitation, and disjoint work processes,”
p. 90).
HRM measures frequently focus only on HR activities, suggesting that these activities
represent the key business processes of HR.  For example, classroom training is frequently
“measured” by the number of courses offered, the number of trainees signed up for each
course, or the immediate reaction of trainees upon completing the class.  Such metrics signal
that more training courses, large class sizes, and positive reactions are the goal. It should not
be surprising, then, that in many organizations the perceived link between training and
changes in individual, unit and organizational performance is tenuous at best.  Alternatively,
GE, Motorola, Federal Express and others are famous for requiring that training be tied to the
key initiatives of the organization, and that it be evaluated as such.  Training metrics include
the effect on such things as product quality, cycle time, cost reduction, and speed of
execution. In several shipping companies, the benefits of enhanced training or selection is
frequently expressed as “the number of additional trucks/planes that can be loaded for free,
without paying for additional labor.” Steve Kerr, Vice President of HR at GE says they “teach
the initiatives” (Frost, 1997, p. 341), not just the learning objectives.
Constituent Reactions and Business Process Metrics
How does focusing on the key business processes relate to the measurement principle
of constituent reactions?  At Pepsi Cola, IBM, Sears and other companies, the linkage concept
is articulated through “learning maps” that show through pictures and games how the broad
organizational goals reflect value propositions, and then imply improvement in key business
processes.  For example, the business objective might be improved market share, which
requires the value proposition of “product availability,” which means increasing the amount of
shelf space, which might be achieved through enhanced by better inventory tracking and
better-customized product promotion processes.  The learning maps often become the basis
for company-wide meetings, with employees at all levels participating in games and contests to
enhance their knowledge of the value propositions and, even more important, their
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Human Resource Metrics and Human Resource Strategy WP 98-10
understanding of the linkages between business processes and their individual role in
supporting them.  We know precious little about the effects of such articulation on individual
learning, attitudes and behaviors, but these responses are likely to be a key to the success of
HR strategies.  Both SHRM and metrics research can be enhanced by attention to these
effects.  Thus, the choice of business process metrics should reflect not only the SHRM theory,
but behavioral implications of the measures.
Constraints and Metrics of Business Processes
Strategic business processes alleviate strategic constraints.  For example, enhancing
the product knowledge of sales people provides far less valuable in a situation where the
constraint is a lack of competitive products, in which case product innovation may be more
valuable.  The key role of salespeople may be to listen to customers to identify their most
pressing and unmet product needs, rather than to “sell” them on existing (perhaps obsolete)
products.  SHRM research that fails to identify the key constraint may inappropriately focus on
non-essential business processes, such as product knowledge, while ignoring the critical
constraint of product innovation.  A failure to find a link to success in value proposition and
market performance may be due to choosing business processes that are not on the “critical
path” of constraints.  Thus, the constraints concept at the business process level may shed
light on the dilemma of finding “fit” effects in SHRM.
Key Behaviors and “Moments of Truth”
The value propositions and business processes are the typical dependent variables in
SHRM, and have received a significant amount of theoretical and empirical attention.
However, the “moments of truth” have received relatively less attention.  Gronroos (1990,
1994) and Carlzon (1987) noted that “moments of truth” represent pivotal contact points
between employees and customers, whether in providing a service, selling a product, or
providing assistance.  These determine constituents’ perceptions of service and product
quality.
In the classic case of employees meeting customers, the link may be quite clear.  When
Pepsi route drivers talk with buying managers in supermarkets and convenience stores, or
when they “face” the product so that the label is in view of customers, their performance will
affect future sales, and repeat buying behavior.  When retail store associates meet and assist
shoppers, their behaviors, conveyed attitudes, and product knowledge likely affect the
probability of making a sale, and the customer’s impression.  Some of the best empirical
examples of the links in Figure 1 come from areas where such sales associates meet
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customers (e.g., Rucci, Kirn & Quinn 1998).  In fact, it appears likely that the customer
interaction affects not only customer perceptions of the store associate, but also perceptions of
the product and even the company.  This premise reflects the idea of an “upside-down”
organization (Milkovich & Boudreau, 1997), in which those who directly meet customers are at
the top, supported by the other layers of the organization, the CEO at the bottom of the
support structure.
What is often overlooked is that the “moment of truth” concept applies to situations
without a direct customer meeting.  Employees providing technical assistance through call
centers are only slightly removed from direct face-to-face contact.  Moreover, such call centers
frequently collect key linkage data such as repeat business, order or service types, etc.,
making the metrics linkage even more feasible.  Moving to the other extreme, is it possible that
employees who provide maintenance or cleaning services have “moments of truth” as well?
Jay Barney (1997, personal communication) notes that in one organization he approached a
janitor and asked what the organization’s mission was.  Surprisingly, the janitor accurately
stated that the mission was to provide customer intimacy through world-class delivery of their
key products.  The more difficult question came next, “Can you make a difference to this
mission in your work?”  The custodian proceeded to state that he altered his cleaning routine
to emphasize those parts of the manufacturing plant where dirt was most likely to produce
product flaws and failures or injuries.  Deciding where to clean represented a moment of truth
because the cleaning pattern affected other employee work processes that directly supported
the value proposition.  Appropriate metrics might determine how differential cleaning related to
objective outcomes such as  machine failure, or the perceptions of employees who benefit
from these janitorial services.
While it is indeed dangerous to substitute the concept of an internal customer for the
ultimate customer, an HR metric system can use intermediate perceptions of internal
customers to articulate linkages.  If organizational success is built on hundreds or thousands of
small steps taken by many employees, articulating a grand value proposition supported by key
business processes, even when associated with good metrics at each level, will often not
succeed without specific reliable behaviors from thousands of employees (Pfeffer, 1996).
Thus, the “moments of truth” are the key employee behaviors that are pivotal to success of the
important business processes.
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Human Resource Metrics and Human Resource Strategy WP 98-10
Constituent Reactions and Moments of Truth
Strategy research and practice that articulates specific moments of truth may be more
likely to affect individual behaviors, because it is possible for individuals to understand the
connection between the outcomes of their behaviors and strategic success.  When such
linkages go unstated, achieving strategic success may be less likely both due to a lack of
information and perhaps due to the signal that such linkages are not important enough to
articulate and measure clearly.  Frequently the informational and motivational effects of these
metrics occur best through anecdotes.  Vivid stories often carry the power of legend or myth in
conveying strategic linkages.  A widely-shared story involves the top officer of a manufacturing
organization who, upon encountering a dirty work area in a plant tour surprised everyone by
grabbing a dustpan and cleaning up the mess, rather than ordering that it be cleaned.  If the
top officer takes a personal interest in cleaning up, the importance of cleanliness as a key
behavior is reinforced.  In the same way, the metrics reflecting moments of truth serve both an
informational and motivational purpose within the organization.  Thus, SHRM research must
not only strive to define appropriate moments of truth based on strategy and theory, but also to
identify the moments of truth that organization members employ to articulate, communicate
and understand their role in organizational success.
Constraints and the Moments of Truth
From a practical perspective, the key at this stage of Figure 1 is to avoid being
overwhelmed by the sheer variety and number of potential measures of employee behaviors.
Once again, the measurement principle of focusing on the constraints may be useful.  First, as
Figure 1 suggests, the most fruitful moments of truth will reflect the link from each behavioral
measure to the key business processes or initiatives that will be enhanced by it, and
subsequently the key value propositions that will be supported.  Second, the key to these
business processes will frequently be to focus on what is the most binding constraint and what
moments of truth will clearly affect it.  To continue the earlier example, for salespeople in a
company where product innovation is the key constraint, measuring selling behaviors and their
effects on business outcomes may be less fruitful than measuring rapid customer intelligence,
listening, and communicating new ideas to product designers.  Thus, SHRM measure
development would again focus on the question of which moments of truth are the key to
alleviating the most serious constraints.
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Human Resource Metrics and Human Resource Strategy WP 98-10
Capability, Opportunity, Motivation (COM)
This element of Figure 1 reflects direct changes in the human resource, in terms of
Capability Opportunity and Motivation (COM):  (1) Capability is the capacity of employees to
create value; (2) Opportunity is the necessary circumstances for employees to create value;
and (3) Motivation is the drive or force employees feel to create value.  These three
components (COM) are derived from traditional work suggesting the notion that individual
performance is a multiplicative function of ability and motivation (Vroom, 1964; Maier, 1955;
Cummings & Schwab, 1973), as well as critiques of the simple model (Campbell & Pritchard,
1976), and suggestions that the nature of the environment determines the expression of ability
and motivation (Gilbreth 1909; Dachler & Mobley, 1964), and more recent work suggesting that
situational constraints and opportunity are key to a theory of work performance (Peters &
O’Connor, 1980; Blumberg & Pringle, 1982).  SHRM metrics should reflect all three
components, as theory suggests all three must be present for human resources to contribute
to organizational value.  Moreover, any single or set of HR activities may contribute to any of
the three components (e.g., more stringent selection to identify workers with experience
working in teams may produce employees not only with team skills, but also those whose
needs and values tend to create motivation in team settings).
The concepts of “capability” and “competency” occur frequently in the SHRM and
human resource literature. The vast majority of measures at this level seek to capture the
capability element.  In this volume, Ulrich (in press) emphasizes “competencies,” and
McMahan, et al. (in press) note the traditional emphasis on “organizational capability” (Amit &
Shoemaker, 1993; Collis, 1994; Kamoche, 1996; Lado & Wilson, 1994).  While these authors
quite appropriately note that these factors combine to create a capacity for strategic change,
the emphasis often seems to be on what Figure 1 defines as capability, with less attention to
motivation and opportunity.  The metrics model suggested here emphasizes that the requisite
human attributes go beyond capability, and that an overemphasis on capability may be
counter-productive.
What about employee attitudes?  Figure 1 does not explicitly incorporate employee
attitudes, such as job satisfaction, focusing instead on their effects on employee motivation to
engage in behaviors (“moments of truth”) such as turnover, citizenship behavior, etc.  Recent
employee attitude research supports this view that strategy and linkage are key  (Johnson,
1996; Ryan, Schmit & Johnson, 1996; Schmit & Alscheid, 1995; Schneider, Ashworth, Higgs &
Carr, 1996).  There seems to be a trend in these studies to link attitudes with organizational
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Human Resource Metrics and Human Resource Strategy WP 98-10
and strategic goals.  Organizations, such as GE and Sears have implemented employee
“attitude” surveys that reflect a linkage concept, for example employees are asked their
perceptions that leaders have communicated clearly the vision (value propositions, business
processes and moments of truth), that resources are sufficient to accomplish goals, that there
is an emphasis on winning, that individuals clearly understand their personal role in meeting
objectives, and the rewards that will emanate from achievement (e.g., Rucci, et al., 1998).
This kind of measurement seems more likely to show relationships through the value
propositions than mere measures of job satisfaction.
A similar approach might be taken toward other common HR metrics.  Capability
indices such as competencies, skills, knowledge, certification, and test scores can be strategic
metrics, but only when embedded within a theory that links them to value.  This will help to
identify the capabilities that are strategic, and to focus research and practice on developing
them.  Opportunity indices such as team composition, organizational design, etc. can also be
developed based on their linkage.  Boudreau & Ramstad (1997) give several examples of
linking COM measures to key organizational initiatives.
Constituent Reactions and “COM”
Organizations that modify their attitude, skill and opportunity measures to reflect
linkages to strategic behaviors, business processes and value propositions can then hold
leaders accountable for changes in such measures.  The oft-quoted admonishment to avoid
“rewarding for A while hoping for B” reflects this idea.  SHRM research has devoted relatively
little attention to the effects of measurement choices on the behavior of supervisors and
managers, yet this would seem to be a key linkage in implementing strategy.  Indeed, it seems
likely that the choice of measures probably frames the perceptions of managers and
employees in terms of what is important, so strategy making is also driven by such measures.
At Sears (Rucci, et al., 1998), one important result of using data to demonstrate linkages from
employee attitudes to business success was the  change in perspective among managers as
to the strategic drivers of the organization.  Thus, the COM concept can become the basis for
evaluation and assessment of managers.  Even without such explicit accountability, the choice
of which COM elements are measured sends signals to employees that are likely to motivate a
desire (or at least curiosity) about the action to be taken in these areas.  For example, many
organizations (and SHRM HR assessments) measure the number of hours or dollars spent in
training classes, but do little to measure whether such training is applied at work.  It seems
likely that this may signal to employees and managers that attendance is the key, not
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Human Resource Metrics and Human Resource Strategy WP 98-10
necessarily competency building and application.  Thus, the behavioral effects of metrics at the
“COM” level remains to be examined with SHRM research.  The principle of constituent
responses to metrics has complementary implications for research in utility analysis (UA),
suggesting that studies should focus on how utility models affect the perceptions and reactions
of constituents, rather than simply on the mathematical elegance or completeness of estimates
(e.g., Boudreau, 1991; Latham & Whyte, 1994).  Thus, future SHRM research may benefit
from attention to individual reactions to the COM measures.
Constraints and “COM”
Industrial-organizational psychology research typically measures effectiveness in terms
of increased skills or learning, assuming that such increases are monotonically related to
organizational value (e.g., “utility analysis”, Boudreau, 1991; “HR costing,” Cascio, 1991; and
“human resource accounting,” Flamholtz, 1985).  Such approaches are deficient if they fail to
reflect how the results of HR processes will be used, and whether the metric reflects key
constraints.  For example, Boudreau (1991) noted that the utility values will vary depending on
whether they are used to cut costs, increase volume or increase margins. Much utility analysis
literature has presumed that the key requirement was to translate HR outcomes into the
“language of business” by placing dollar values on them.  As we have seen, strategic HR
metrics require much more than simply a dollar-valued scale.  In fact, it is likely to be more
important to understand the link between HR outcomes, moments of truth and value
propositions, than to express results in dollars.  For example, an organization with unsold
inventory is little served by human resource interventions designed to increase production
levels.  The key constraint is sales volumes, not production.  However, standard utility analysis
theory and measures could quite easily construct equations that would show very high
apparent payoffs to  increasing worker speed, because such models generally assume that
increases in worker productivity are linearly and positively related to attained value.  In this
case, the appropriate question is not “what is the difference in value between a low-producing
factory worker and a high-producing factory worker,” but “is there greater value in increasing
factory worker productivity compared to sales productivity.”  Linking COM to these strategic
paths necessary to integrate SHRM and measurement as depicted in Figure 1.
Human Resource Management Processes … The Bundles
The notion the human resource activities are most effective when bundled into
synergistic combinations, while prominent in SHRM, could be better incorporated into research
and practice in HR metrics.  SHRM research (Arthur, 1992; 1994; Huselid, 1995; Ichniowski, et
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Human Resource Metrics and Human Resource Strategy WP 98-10
al., 1997; MacDuffie, 1995) suggests that bundles of HR processes, often called “high
performance work systems” are a key determinant of performance.  Utility analysis research
has acknowledged the interplay between different HR processes, noting the consequences of
linkages between recruitment, selection, separation, and internal movement for the overall
value of the workforce (Boudreau, 1991).   As yet, utility analysis applications have not evolved
to capture this interplay.  Developing such a system will require the integration of SHRM and
metrics, and articulation of key linkages as shown in Figure 1.
Indeed, this perspective suggests a change in the notion of an “HR program” in both
SHRM and metrics research.  Though HR programs typically are measured as relatively large-
scale interventions applied to many employees, (e.g., formal training, compensation, selection
or recruitment), there is “human resource management” occurring in each interaction between
employees, managers and customers.  How much of the effectiveness of staffing, for example,
rests with the individual judgments that are made after candidates have been screened
through formal evaluation procedures?  How much of the effectiveness of rewards rests with
the individual recognition, appraisal and communication that goes on outside the formal pay
and performance appraisal processes?  How much of knowledge and skill acquisition takes
place on the job, independent of formal training programs?  Capturing these effects requires
an approach to metrics that explicates linkages at levels beyond individual HR programs, and
that flexibly measures the HR programs themselves.
Constituent Reactions and HR Bundles
How HR practices are measured and conceived strategically may affect key
constituents.  If Gerhart (in press) is correct in his suggestion that HR managers, shareholders
and perhaps even customers or employees hold implicit assumptions about the association
between HR and organizational performance, then how the HR bundles are defined and
communicated may affect those perceptions.  Organizations that communicate and track their
HR practices from an integrated perspective of “high performance work systems” may be
perceived as more progressive or effective.  The metrics used to evaluate and describe HR
practices may well influence how they are organized and integrated.  Organizations that adopt
a strictly functional approach, with clear delineation between staffing, compensation, training,
etc. may produce functionally separate decisions by HR managers and others.  Metrics that
instead emphasize integration, “fit” and synergy across functions may elicit different behaviors.
For example, in some organizations, the “staffing” function is defined and evaluated in terms of
the interplay between acquisition, internal movement and retention.  One manager may
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Human Resource Metrics and Human Resource Strategy WP 98-10
oversee this integrated function, with rewards and evaluation based on the combined effect of
these processes.  In other organizations, the sub-components of staffing are strictly
delineated, with separate managers and metrics for each sub-component.  It seems likely that
staffing initiatives are chosen differently in the two organizations.  SHRM researchers who
adopt the more integrative approach for theoretical reasons might do well to consider whether
their metrics carry an implicit assumption about how organization members perceive the HR
bundles.
Constraints and HR Bundles
The concept of internal “fit” in SHRM suggests that HR activities may create synergy
when the compliment each other.  However, there are a huge number of “fit” patterns among
HR activities that might reasonably be considered strategically useful.  For example, while it
may seem logical for organizations pursuing strategies in risky environments to “fit” those with
HR practices that reward risk-taking, one can also make the argument that HR practices that
provide some stability (e.g., a significant portion of pay that is not outcome-based) may be a
better strategy, because reinforcing risk may create chaos, while tempering it may allow
reasoned action.  Barringer and Milkovich (1997) reported that employees and employers
prefer secure, longer-term contracts when the work environment is risky and uncertain.  The
principle of focusing on the key constraints may provide value as an indicator of which of many
“fit” patterns may be most strategically useful.  By beginning with the strategic linkage concept,
metrics theory can identify measures that reflect the most important organizational processes.
By attending to the constraint principle, SHRM researchers may gain clues regarding the fit
patterns that are most important to measure.
Though beyond the scope of this chapter, the concept of constraints linked to
measures of HR bundles highlights the importance of an “optimization” perspective in both
SHRM and HR metrics.  Cappelli & Crocker-Hefter (1996) noted that strategies may be better
formed by looking for ways to apply existing organizational resources strategically, as
suggested by the resource-based model, than by starting with a general strategy and
attempting to fit resources to it.  Each organization will have a very different feasible set of
strategic paths, because it has a very different set of constraints based on the resources it
possesses.  The same applies to optimizing bundles of HR practices.  Simply put, strategic HR
investments require optimizing both the synergy of the bundles and their results, but also the
synergy of the resources used to invest in those bundles.  Organizations with decentralized HR
systems (e.g., a training unit within each business), each investing based on unit needs and
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Human Resource Metrics and Human Resource Strategy WP 98-10
resources, are likely to fail to optimize across units without metrics systems that link the unit
investments together.  Moreover, full optimization requires not only that the bundles work
together, but that the bundle of resources chosen also be optimal.  It is one thing to achieve
synergy using expensive and time-consuming classroom training.  It is quite another to achieve
the same synergy by recognizing that if time is the key organizational constraint, then spending
cash to develop decentralized training that takes less time may be even better.  There is “fit” in
terms of the resources used, just as their is “fit” in terms of the outcomes produced.
SUMMARY AND CONCLUSIONS
Cappelli & Singh (1992) suggested that SHRM is built on two unstated propositions:  (1)
A particular business strategy demands a unique set of responses from employees; and (2) A
particular set of human resource policies produces a unique set of responses from employees.
This chapter supports their call for research that explicitly measures and tests these
propositions. Figure 1 proposes a model integrating SHRM and HR metrics, providing a
departure point for a more detailed set of conditions and components.  The model also
suggests that SHRM may not require the strongest version of these propositions.  A variety of
employee responses may support a given business strategy, and that a variety of human
resource practices may elicit them.  This is not to say that there is no “fit” between strategy and
practices.  Rather, by focusing on the principles of linkages, constraints, and constituent
responses, the appropriate domain of both strategic linkages and measurement imperatives
may become clearer.  While one unique combination may not exist, these principles may guide
researchers toward those that are most supportable.  We’ve illustrated how the challenges
facing SHRM (e.g., more granular and context-rich strategy concepts, cause-and-effect
knowledge) are intimately tied to the nature and quality of metrics, and how progress in HR
metrics (e.g., moving beyond program-specific justification, deciding which of the thousands of
metrics to use, creating measures likely to predict broader outcomes) likewise requires a
strategic focus.  A fundamental premise of this chapter is that a linked set of metrics really
does produce stronger and more reliable relationships than measuring only part of the links.
Future research is needed to test this proposition.
Metrics serve at least two purposes: (1) Operationalizing the theoretical concepts in
SHRM and (2) Affecting constituents who observe and react to the measures.  Both metrics
and SHRM research can benefit from more focus on these two purposes.  Defining value
propositions more granularly and in context should be guided by looking for measures that
affect key constituents that influence contextual constraints.
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Human Resource Metrics and Human Resource Strategy WP 98-10
A fruitful area of research would reflect the impact of HR metrics on key decision
makers.  As Boudreau (1991, 1996) has noted, we know very little about how theories of
persuasion and influence are reflected in the reactions to HR measures.  It seems likely that
metric systems that articulate the frameworks outlined here may have different effects than
those focusing on specific programs, or those that reflect only the macro-level effects.
Research is needed to determine if the metrics used to define and communicate strategy have
differential effects on perceptions, decisions and behaviors.  The effects of HR metrics has
received limited attention from measurement researchers, but by integrating metrics and
SHRM, and explicitly examining the effects of articulating strategy and measuring it in certain
ways, future research can illuminate a key potential source of strategic impact.  To date,
research in both HR metrics and SHRM have not focused on constituent reactions.  Related to
this issue is the question of whether decision makers can articulate the key SHRM concepts,
and whether their articulation of strategy is enhanced when approached from the principle of
constraints suggested here.
Finally, Figure 1 clearly suggest the promise of comprehensive studies that track
variables reflecting each level and step in the process.  While such studies are difficult, the
resulting data would be immensely helpful in articulating the intermediate linkages between the
micro and macro studies.  This has been noted before, but the present model suggests a
specific framework for the variables comprising these linkages.  It seems possible that
organizations have the necessary data bases to carry out such studies, especially
organizations with large numbers of customer-contacting employees and established market
research and financial data (e.g., large retailers, banks, and telecommunications
organizations).  Exploiting such data requires creative integration between disparate data
bases, but may be far less difficult than attempting to gather such data from the outset.
In sum, both SHRM and HR metrics will benefit from a closer integration.  It is hoped
that the framework suggested here will encourage such integration in the future.
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Human Resource Metrics and Human Resource Strategy WP 98-10
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