Journal of Strategic Information Systems 1994 3(4)
261-288
Strategic
users of information technology: a longitudinal analysis of organizational
strategy and performance
Albert H Segars Department of Operations and
Strategic Management, The Wallace E Carroll School of Management, Boston
College, Chestnut Hill, MA 02167, USA
Varun Grover and William J Kettinger Department of
Management Science, College of Business Administration, The University of South
Carolina, Columbia, SC29208, USA
While
discussed extensively, very few studies have attempted to formally integrate
the notions of organizational strategy, competitive advantage, and the
strategic use of information technology. Utilizing the typology of Miles and
Snow, this study attempts to identify the strategic orientation (prospector,
analyzer, defender) of widely cited users of ‘strategic information technology’
before and after the launch of their innovative systems. Also, measures of
financial performance are compared between emergent groups in order to
determine if any particular strategic orientation consistently outperforms the
others. In general, this study reports four findings. First, it appears that strategic
users of information technology are not concentrated along a singular strategic
dimension. The firms examined in this study exhibited characteristics
associated with each of Miles and Snow’s strategy types. Second, it seems that
many firms shifted strategic orientation after the launch of their systems.
Interestingly, these shifts were rather dramatic and seem to represent a
fundamental change in strategic direction from earlier ‘pre-system’ operating
philosophies. Third, case descriptions along with narratives of annual reports
suggest that usage or competitive intent of these strategic systems matches the
prevailing strategic profile of the initiating firms. In other words, the
systems seem to support organizational strategy. Finally, it seems that
prospectors and defenders realized significantly higher measures of financial
performance immediately after the implementation of ‘strategic information
technology’; however, in the long-term no strategic orientation seemed to
outperform the others.
Keywords:
strategic information technology, organizational strategy, competitive
advantage, information technology for competitive advantage
The
recent emergence of theoretical literature and case studies which explore the
‘strategic’ and/or provide extensive evidence of the critical role information
resources can play in the realization of corporate strategy (Clemons and
McFarlan, 1984; Ives and Learmonth, 1984; McFarlan, 1984; Cash and Konsynski,
1985; Clemons and Row, 1991). Clearly, the information system (IS) function has
evolved from a reactive ‘organizational handyman’ into a proactive corporate
resource capable of distinguishing a firm within its industry. Although
information systems will continue to support routinized ‘efficiency’ oriented tasks
such as payroll and process control, informed managers are constantly seeking
new ways to employ IT in support of corporate objectives. In these instances,
the focus of IT planning and deployment shifts from organizational efficiency
to effectiveness and the relevant managerial concern becomes: How can
information resources contribute to the long term effectiveness of the firm in
relation to other industry participants? A critical component in the
development of IT-enabled competitive strategy is the integration of the firm’s
strategic and IS plans (King, 1978; Pyburn, 1983). In essence, a level of
‘strategic validity’ is achieved when long-term corporate strategy is
formulated with both the existing and potential uses of IT considered. Without
this integration, strategic options of the firm can be severely limited as IT
architectures resemble the vision of technical rather than strategic planners.
Conversely, a ‘link’ between both corporate and IS strategic plans facilitates
competitiveflexibility (the capability of responding to changing industry
conditions) as well as competitive innovation (the capability to ‘change the
rules of competition’) (Keen, 1991). Thus, the strategic use of IT can be
conceptualized as technological architectures developed, deployed, and used as
a result of, and in support of, the overall strategic objectives of the firm.
Much of the early research attention in this area has focused on frameworks
for: (1) identifying opportunities, (2) creating managerial awareness, and (3)
positioning the firm with respect to its technological abilities and
competitive opportunities (Earl, 1988). In addition, case studies which
describe the features and competitive implications of strategic IT have been
presented as convincing evidence of its ‘industry changing’ ability (Clemons
and Row, 1988; Doll, 1989). These important early efforts can best be
summarized as descriptive in nature. That is, a description of IT-based
competitive advantage was the focus rather than actual empirical measurement of
its antecedents, constructs, or subsequent impacts. Recent literature has
extended the notion of strategic IT to include consideration of performance
measures and the sustainability of competitive gains over time (Clemons, 1986;
Feeny, 1988; Feeny and Ives, 1990). The implications of these works are that
‘true’ IT-based competitive advantage is sustainable and should have a
noticeable impact on the overall profitability measures of the firm. Further,
it is suggested that differences in unique complimentary resources (resources
leverageable with IT) among firms may be an important determinant in the
competitive gains realized through development and deployment of strategic IT
initiatives (Clemons and Row, 1991). While these concepts are relatively new,
they underscore an important agenda for future work in the area of strategic
IT. Succinctly stated, research efforts should broaden in scope from
descriptive frameworks and case studies to explanatory models of firm and
industry-level dynamics. Concepts such as ‘strategy’, ‘performance’,
‘sustainability’ and their changes over time must be measured within the
context of strategic IT use. This study undertakes such an agenda. Drawing on
methodologies grounded in strategic management and industrial economics, the purpose
of this study is to determine the strategic orientation and longitudinal
patterns in performance of much-cited strategic users of IT.
Organizational strategy, competitive advantage, and strategic use of information technology
While
discussed extensively, very few studies have attempted to formally integrate
the notions of organizational strategy, competitive advantage and the strategic
use of IT. Some popular perspectives from each of these areas are presented in
the following sections.
Organizational
strategy Miles and Snow (1978) formally define organizational strategy as an
ongoing process of evaluating purpose as well as questioning, verifying, and
redefining the manner of interaction with the competitive environment. This
concept has been further refined by strategy theorists as consisting of
corporate-level strategies (‘What business should we be in?‘) and business
level strategies (‘How do we compete in this business?‘) (Hambrick, 1980).
Ideally, the formulation of business-level strategy is a top-down process which
flows directly from corporate-level strategies summarized in the firm’s
statement of mission and objectives. Although important, corporate-level
strategies are rather static in nature and are not easily operationalized.
Conversely, business-level strategies represent dynamic managerial decisions
that are continuously made in order to cope with changes in the competitive environment.
Since these actions closely reflect continuous organizational processes of
adaptation and can be operationalized using objective data (Hambrick, 1980;
Cool and Schendel, 1987; Segev, 1989; Tavakolian, 1989), the term ‘strategy’ or
‘strategic orientation’ as used within the context of this research represents
business-level strategies. As noted by Miles and Snow, the complexity of the
strategy process can be somewhat simplified by searching for patterns in the
behavior of organizations. In other words, observed patterns of emergent
behavior can be used to describe the underlying processes of organizational
adaptation. The typology developed by these authors identifies defenders,
prospectors, analyzers, and reactors as the basic strategic orientation of
organizations. Each orientation differs with respect to risk disposition,
innovativeness, and operational efficiencies. l Defenders deliberately enact
and maintain an environment in which a stable form of organization is
appropriate. They attempt to ‘seal off’ a narrowly defined market segment and
ignore developments and trends outside their domain. Defenders also invest a
great deal of corporate resources in efficiently producing products/services.
Levels of ‘organizational slack’ are low in keeping with desired managerial
control over corporate operations. Thus, cost efficiencies, tight resource
control as well as risk-averse development and operational policies
characterize these competitors. l Prospectors respond to their competitive
environment in a manner almost opposite to that of defenders. Prospectors
constantly seek ways to exploit new products and processes. In essence, higher
degrees of ‘organizational slack’ are permitted in order to faciliate
innovation. The focus of these firms is market effectiveness versus efficiency.
Risk-taking behavior, loose resource control, and less focus on cost
efficiences characterize these firms. l Analyzers lie in between the risky
nature of prospectors and the conservative nature of defenders. In essence, this
strategic form is a hybrid of the prospector and defender types and represents
a viable alternative to the two extremes. Analyzers typically minimize risk
while maximizing the opportunities for profit. l Reactors exhibit patterns of
adaptability that are both inconsistent and unstable.
Thus,
these firms exist in a state of almost perpetual uncertainty. Unlike other
strategic types, actions are taken in a reactive versus proactive mode. These
firms can be thought of as possessing no formalized mechanisms for competitive
adaptability.
Clearly,
this typology focuses on outcomes rather than the complexities involved in
formulating and implementing strategic plans. Nonetheless, the framework
provides a convenient mechanism for broadly categorizing strategic thrusts and,
more importantly, observing changes in strategic orientatation of firms and
industries over time. As noted by Hambrick (1983), the framework is
parsimonious and appears to account for significant variations across
industries. It also allows the strategy construct to be operationalized in
other than industry-specific terms. Much literature in the area of strategic
management has attempted to uncover differentiating attributes of Miles and
Snow’s strategic types as well as the impact of environmental factors on the
‘appropriateness’ of strategic orientation (Snow and Hrebiniak, 1980; Hambrick,
1983; Shortell and Zajac, 1990; Das et al., 1991). A typical view is that
particular competitive environments favor certain types of strategies. That is,
strategy should favorably align the business with its environment (Porter,
1980). Others, however, have suggested that the various strategic types would
perform equally well in any industry, providing that the strategy was well
implemented (Snow and Hrebiniak, 1980). Of these views, the former has thus far
received the most empirical support (Hambrick, 1983; Shortell and Zajac, 1990).
Although other typologies have been developed and empirically operationalized
in an effort to capture the strategy construct (most notably Porter’s (1980)
generic strategies), the Miles and Snow framework has a number of features
which we believe justify its use in relating strategy to patterns of IS
management. First, empirical research has shown a general congruence between
Miles and Snow’s categories and Porter’s cost leader and differentiator
strategies (Segev, 1989). Although these findings do not suggest that the two
typologies are exactly the same, it does suggest that both capture essentially
the same fundamental dimensions of strategic behavior. However, unlike Porter’s
typology, the framework developed by Miles and Snow richly describes underlying
attributes of organizational structure and managerial style providing perhaps a
more robust insight into strategy and its supporting organizational resources.
Secondly, a number of studies conducted within the area of strategic management
have rigorously validated the measures associated with the Miles and Snow
typology (Hambrick, 1983; Segev, 1989; Shortell and Zajac, 1990). In general,
the strategic types have been found valid across three different aspects of
strategic behavior: (1) intended versus realized strategy, (2) overall
portfolio of products/services offered, and (3) market strategies regarding
core business offerings. Additionally, associated measures of these types have
exhibited strong properties of reliability and validity (Shortell and Zajac,
1990). Finally, previous studies within IS have successfully employed this
typology to explain both patterns in management (Tavakolian, 1989) and use (Das
et al., 1991) of IT across organizations. Therefore, in the interest of
consistency, and relatedly cumulative research tradition, its use within this
context seems appropriate.
Competitive
advantage Competitive advantage describes unique characteristics (distinct
competencies) which enable the firm to maintain a dominant position within its
respective industry. Porter (1980) defines true competitive advantage as
meeting three conditions - the product or process must: (1) truly alter the
industry structure by changing competitive relationships; (2) improve the
organization’s position in its existing business through cost reductions or
product differentiation; and (3) create new business opportunities that can be
extended into new areas. To be capable of sustained success, any business
strategy must be predicated on building and maintaining a competitive advantage
(Porter, 1980). To the extent that a firm can capture and maintain the
initiative, competitors are forced to respond to the initiator’s moves defensively
and to do so under conditions not of their own choosing. As noted by MacMillian
(1982) the challenge to top management in capturing and retaining an offensive
initiative involves: (1) anticipating what it will take to be an industry
leader during the next few rounds of strategic moves; (2) planning a series of
moves aimed at throwing competitors off balance, keeping them on the defensive,
and giving them little time to launch initiatives of their own; and (3) gaining
a shrewd understanding of offensive strategy tactics and what organizational
capabilities are needed to carry them out. A number of tactics can be used by
each of Miles and Snow’s strategy types to pro-actively seize competitive
advantage. Defenders may resort to price cutting, employing more efficient
inbound/outbound logistical systems, making changes in production operations
that lower costs, giving more responsive after-sale support to buyers, or
developing a lower-cost product design. Prospectors, on the other hand, may
pioneer new distribution channels for products, escalate marketing efforts in
undeveloped market segments, develop new products/services, or develop product
features which substantially change the nature (and market) of existing
products. Analyzers may choose a combination of the tactics outlined above.
However, they would typically make fewer and slower product/market changes than
prospectors and be less committed to stability and efficiency than defenders.
It is important for firms to pursue through such tactics sustained competitive
advantage. This refers to the firm’s ability to maintain initial gains in
business performance (ie profitability, market share) with respect to
competitors. Increasingly, both offensive and defensive tactics used to create
or sustain competitive advantage contain some component of information
technology as a catalyst. Such instances have created a whole new arena of
competition for managers and a new area of inquiry for researchers. Concepts
such as ‘technology based strategy’, ‘strategic IT’, and ‘information
technology for competitive advantage’ have captured much attention within IS
literature and have been a key issue of IS executives for much of the past
decade (Niederman et al, 1991). Given the quickening pace of technological
development, it is likely that this interest will only increase in the near
future.
Strategic
uses of information technology The advancement of communications and computing
technologies has heightened the stature of information technologies from an
operational resource unrelated to strategic goals to an integral ingredient in
strategy formulation and implementation leading to competitive advantage (King,
1978; Parsons, 1983; McFarlan, 1984). Numerous studies have sought to raise
managerial awareness regarding the competitive importance of technology and its
imperative in the formulation of competitive strategies (Ives and Learmonth,
1984; Porter and Millar, 1985; Wiseman, 1988). Utilizing the ‘five forces’
model of Porter (1980), Parsons (1983) describes the potential competitive
influence of advanced IT at the industry, firm, and strategy level.
At
the industry level, IT may change the very nature of product and service
offerings, markets, and/or production economics. A much-cited example of this
is McKesson’s Economost system (Clemons and Row, 1988). This order entry system
completely revolutionized the service offerings of drug wholesalers. The ease
of electronic ordering and subsequent reporting capabilities of this system
were a stark contrast to the industry norm of labor-intensive and inefficient
wholesale operations. A subtle but important second-order effect of this
technology was market based. That is, previously satisfied retailers quickly
demanded from their wholesalers the same services offered by McKesson. Those
firms which could deliver survived; those which could not quickly vanished.
Other systems cited as having similar industry effects include ATMs (Brady,
1986; Neo, 1988; Clemons, 1990), Air Line Reservation Systems (Doll, 1989) and
Point of Sale Systems (Brady, 1986; Neo, 1988). Firm level impacts include the
competitive forces of buyers, suppliers, intra-industry rivalry, new entrants,
and substitution. An example of IT’s impact on these forces is the use of
interorganizational systems (10s) as a means of coordinating activities among
members of the firm’s value chain (Cash and Konsynski, 1985; Johnston and
Vitale, 1988). As noted by Keen (1991), not only must the firm’s systems
communicate with each other, increasingly they must also be able to communicate
with those of suppliers and customers. Thus, strategic partnerships form an
important input into the building of the firm’s technological platform. A much
cited example of this phenomena is American Hospital’s (AHS) ASAP (Clemons,
1986; Neo, 1988). With this system, customers can quickly procure products from
AHS or other vendors. In addition, AHS is linked to multiple suppliers, thereby
guaranteeing ample supply at the best market price. Interestingly, attempts to
duplicate this system by competitors with superior technical resources were
unsuccessful due to AHS’s ability to ‘lock in’ customers. In this vein, the
ability to build vertical and horizontal strategic alliances with IT and erect
large barriers to entry can be a competitive bonanza for innovators. For those
unable to detect IT-related changes in these competitive forces, the result can
be competitive disaster. The final impact of IT noted by Parsons is on
organizational strategy. Specifically, IT can impact the ability of the firm to
execute a particular generic strategy. The integration of strategic and IT
planning facilitates the prioritization and development of systems which will support
the strategic objectives of the firm. Related to the impacts discussed above,
technological architectures must be fashioned in order to facilitate
appropriate response to changes in markets, products, and other modes of
competition. Without this integration, strategic alternatives may be limited,
rather than enabled by, the firm’s collection of IT resources. Thus far, the
majority of evidence supporting the impacts discussed above has been in the
form of case studies. Strategic innovators, such as those previously mentioned,
are typically studied within the context of initial or short-term competitive
impact. An implied conclusion in the vast majority of these studies is that
initial gains in competitive performance are sufficient and sustainable enough
to justify the sometimes large amounts of corporate resources necessary for
planning, developing, and implementing innovative IT. Perhaps deceivingly,
these descriptions also suggest that identification of exploitable competitive
opportunities, along with enabling technologies, guarantee competitive success.
Recent research has challenged this notion. In essence, there is a growing
realization that competitive gains through strategic uses of IT may be more
difficult than implied (Vitale, 1986). Additionally, it has been suggested that
resource differences between firms may be a determinant in the success and
sustainability of IT-based strategy (Clemons and Row, 1991). Such suggestions
clearly call for empirical work beyond the frameworks for planning and ‘home
run’ cases which currently dominate the field. This section has set forth a
conceptualization of organizational strategy, competitive advantage, and the
strategic use of IT. Both strategic management and IS literature suggest that
progressive firms formulate strategic plans based on current and forecasted use
of technological resources within their respective industries. In many
instances, this strategic use of IT has revolutionized the underlying patterns
of business activities within industries. However, given the theorized
interdependence of strategy and IT, little research has attempted to measure
the actual strategic orientations of these ‘much heralded’ users. Further, the
existence and sustainability of competitive gains have been ignored by case
studies which typically focus on broad short-term impacts while ignoring
performance evaluation and competitive adjustments. In order to gain a richer
understanding of the strategy-IT link and its potential for creating
competitive advantage, the constructs of ‘strategy’, ‘sustainability’, and
‘performance’ must be operationalized and studied within the context of
strategic IT use. Only then can theory evolve from its current state of
ungeneralizable descriptions to causal models reflecting both organizational
and industry-related contingencies regarding the use and success of strategic
IT.
Research questions
Based
on our prior discussion of organizational strategy, competitive advantage, and
strategic uses of IT, we formulate two basic research questions:
l.
Are there differences in strategy (strategic orientation) among organizations
which utilize IT as a strategic resource and is this use of technology
consistent with prevailing strategic direction?
2.
Are there performance (competitive advantage) differences among resulting
strategic orientations and are they sustainable?
Utilizing
the typology of Miles and Snow (1978) along with associated operationalizations
developed in the strategic management literature (Hambrick, 1980, 1983; Cool
and Schendel, 1987; Segev, 1989), this study seeks to address these questions.
As noted earlier, IS literature abounds with case descriptions of strategic IT
users. In addition, much literature in the area of strategic management and
organizational economics has been devoted to operationalizing the construct of
strategy. Therefore, it seems appropriate that these lines of research be
merged in order to determine the nature of IT based strategy, its change over
time, and differences in performance between strategic orientations.
Methodology
In
order to adequately address the research questions posed by this investigation,
three broad methodological issues must be considered: (1) selection of firms
which utilize IT as an integral component of their competitive strategy; (2)
development of a well-grounded procedure for operationalizing strategy; and (3)
development of a procedure to measure initial and longitudinal performance
which, at least in part, may be attributable to the implementation of an
IT-based competitive strategy. Each of these considerations is detailed in
subsequent sections.
Sample
selection - the strategic IS cases ‘Strategic IS cases’ form the sample
population for this study. A literature review of relevant IS research and
‘trade press’ was undertaken to locate these cases. As a starting point, a 1986
information Week article (Brady, 1986) which asked a panel of 11 IS experts
(Emery, Ives, Johnson, King, McFarlan, McLean, Millar, Scott-Morton, Thompson,
Wetherbe, Wiseman) to select the top strategic IS systems, was used to develop
an initial sample set. Many of these cases were included by Neo (1988) in a
content analysis of 14 strategic IS cases. Next, popularized cases were
identified based on a review of additional published materials, including:
MZSQ; Communications of the ACM; ICIS Proceedings; information & Management;
JMIS; Harvard Business Review; Planning Review; Harvard Business School Cases;
Computerworld; CIO; Information Week; and popular IS textbooks. On the basis of
this search, 60 well-documented cases were identified as strategic applications
of IS (see Appendix A). These information systems range across several
industries and represent both process and product oriented systems. Content
analysis was used to determine the launch dates of each of the 60 identified
strategic systems. This technique has gained increasing importance in IS
research and provides an objective method in determining the content of written
documentation (Neo, 1988; Jarvenpaa and Ives, 1990). Launch dates were
designated as the date on which the IT or IS was generally available (in the case
of a product technology), or widely in use (in the case of a process
technology). The initial process of launch date determination involved copying
25 years of annual bibliographic references from the Funk and Scott listing of
corporate events. This time period was chosen because it was believed that none
of the 60 cases was launched prior to 1966. This search resulted in excess of
1000 pages of bibliographical citations. These references were read and all
titles of the reference that related to IS or IT were highlighted. A second
researcher reviewed these citations and determined whether the phrase was
relevant enough to warrant referring to the actual magazine and journal article
cited in the bibliographical reference. A file for each case was established.
In some cases the Funk and Scott reference specifically announced the launch of
a system. In other cases it was necessary to review the referenced article to
determine the date. In several cases it was necesary to telephone company
representatives to determine the appropriate date. In eight cases it was
impossible to determine the launch dates from any source; these cases were
eliminated from the sample. Next, the authors reviewed the directory of the
COMPUSTAT II financial data set of industrial firms. COMPUSTAT II was selected
because of its widespread use in finance, strategy, and accounting literature.
Based on this review, an additional 17 firms were dropped from the sample
because all or some of the years of annual financial data were missing. Reasons
for missing or incomplete data included: acquisitions or mergers, existence of
subsidiaries in which a clear stream of financial data could not be determined,
and/or inconsistencies in financial reporting. Based on this review, 35 firms
with launch dates and complete COMPUSTAT II data sets remained for further
analysis. Industry data was then gathered via the COMPUSTAT II financial
database. COMPUSTAT aggregates firms within industries based on Standard
Industrial Classification (SIC) code. SIC is the US governmental standard for
classification of firms based on the primary product(s) and/or service(s)
produced. Determination of these product(s)/service(s) is made from the firm’s
mission statement of the 10K report filed annually with the US Securities and
Exchange Commission (SEC). In addition to mission statement, the SEC requires
all firms to list major competitors. These listings are used in conjunction
with product/service descriptions in determination of SIC groupings. Defined in
terms of the SIC scheme, the ‘industry’ is generally the accepted unit of
analysis in industrial organization economics and strategic management (Bain,
1956; Montgomery, 1975; Scherer, 1980, Palipu, 1986; Fiegenbaum et al, 1990).
For each firm the authors carefully checked the face. validity of other firms
classified within the same SIC. Inconsistencies, possible mis-classification,
or potential cross-clarification resulted in the removal of five additional
firms from the sample. The remaining sample tended to have a strong banking
representation and lacked non-US firms. However, other attributes such as size,
scope, and diversity of industry tended to be fairly consistent across the
selected and non-selected samples.
Strategy
operationalization Much industrial organization and strategic management
literature has been devoted to identifying generic business strategies or
strategy types based on ‘strategic indicators’ such as the scope or domain of
the business; resource deployment in marketing, production, and research and
development (R&D); asset management; and production efficiencies (Snow and
Hrebiniak, 1980; Hambrick, 1983; Cool and Schendel, 1987; Douglas and Rhee,
1989; Tavakolian, 1989; Fiegenbaum et al, 1990; Das et al, 1991). Typically,
these constructs are operationalized through either secondary ‘accounting’ data
such as total sales, total assets, R&D expenditures, and marketing
expenditures etc or primary data such as survey or interview. Subsequently,
multivariate grouping techniques such as factor or cluster analysis are
employed to identify sets of homogenous firms (sometimes referred to as
strategic groups). The intent of these studies has been to examine the link
between strategy, environment, and performance in order to determine
appropriate investment strategy and/or future business direction. As noted by
Douglas and Rhee (1989), a number of typologies of business and competitive
strategies have been identified, some based on a priori conceptual frameworks,
others on empirical studies. In addition, the number and precise nature of
strategy types may vary depending upon the specific variables included and
methodology employed.
Variable
selection. Consistent with, and utilizing studies which formally model aspects
of organizational strategy, this study operationalizes strategic orientation
within the context of Miles and Snow’s typology. As discussed earlier, this
typology identifies four strategic types based on degree of innovation in
product or market development. Further, three of these strategies (prospector,
analyzer, defender) can be pursued with equal success within any industry,
regardless of the market environment. Much empirical research has operationalized
and investigated the functional attributes or policies that characterize these
viable strategy types (Snow and Hrebiniak, 1980; Hambrick, 1983; Cool and
Schendel, 1987; Douglas and Rhee, 1989; Tavakolian, 1989; Fiegenbaum et al,
1990; Das et al, 1991). In addition, their effectiveness and performance under
different environmental conditions such as stage of product life cycle, high vs
low growth markets, and industry innovativeness have been examined using
cross-sectional and longitudinal data. In general, these studies conclude that
firms classified as either analyzers, defenders or prospectors differ with
respect to functional attributes such as research and development (R&D) and
marketing expenditures. Specifically, self-reported prospectors seem to exhibit
higher expenditures in ‘innovativeness’ measures such as R&D and marketing,
while defenders exhibit higher financial concentration and higher ‘efficiency’
measures along variables such as capital intensity, employee productivity, and
cost of production. Further, differences have been found to exist in the
effectiveness of the various strategies depending on environmental context (Hambrick,
1983; Shortell and Zajac, 1990). In contrast to the three viable strategic
types, reactors typically have no formal strategic orientation. In essence,
these organizations exist in a state of perpetual uncertainty and therefore are
likely to succumb to the competitive pressures of their particular industry
(Miles and Snow, 1978). Given the profile of the final sample (see Appendix A)
in terms of size, management structure and history, it seems certain that none
of these organizations would exhibit traits associated with the reactor
strategy. Additionally, because most studies within strategic management also
focus on established entities, attributes of this orientation have thus far not
been thoroughly investigated or operationalized within this stream of research
(Shortell and Zajac, 1990). Given these considerations and past practices in
similar studies, the reactor strategy is not considered within this analysis.
Consistent with past studies, the dimensions of competitive scope, risk
disposition, innovativeness and operational efficiency are operationalized in
order to capture the differentiating characteristics of defenders, prospectors
and analyzers. Table I outlines these ‘strategic dimensions’; their associated
operationalizations; and the characteristics of analyzers, prospectors and
defenders. Scope variables including assets, sales and inventory are utilized
as measures of firm size. Segmentation along this dimension provides an initial
indication of strategic orientation based on market strength and breadth of
asset base.
Scope Assets Sales
Gross
book value of assets HighorLow.. .......... HighorLow Firm’s total sales
HighorLow.. .......... HighorLow
Risk
disposition Current ratio Current assets/current liabilities Low
................................ High Quick ratio Short term
receivables/current liabilities Low ................................ High Times
interest earned Operating income over interest expense Low
................................ High Equity to debt Owner’s equity over
long-term debt Low ................................ High Innovativeness R&D
intensity R&D expense over total sales High
................................. Low Marketing intensity Marketing expense
over sales High ................................. Low Slack resources Firm
cashflow over investment High ................................. Low Sales over
total assets High ................................. Low Sales over working
capital High ................................. Low Operational efficiency Cost
efficiency Sales over cost of goods sold Low ................................
High Employee efficiency Sales over employees Low
................................ High
Studies
conducted on both intra-industry (Cool and Schendel, 1987; Segev, 1989) and
inter-industry firms (Douglas and Rhee, 1989) utilize similar or exact
operationalizations as those listed in Table 1. Although there is no a priori expectation
that size is unique to a particular strategic orientation (ie prospectors,
analyzers and defenders, may be small or large), the use of this variable in
numerous studies of this nature along with its ability to discern differences
in organizational resources which may be influential in the success of IT-based
strategy (Clemons and Row, 1991) necessitate its inclusion. Risk disposition is
concerned with management’s willingness to utilize financial or operating
leverage in pursuit of competitive goals. Similar to studies by Fiegenbaum et
al (1990), Cool and Schendel (1987), Dess and Davis (1984), as well as Miller
and Bromiley (1990), multiple ratios are utilized to operationalize this
construct. As argued by these authors, these operationalizations yield insight
into management’s complexion concerning risk taking, not only in terms of
utilizing financial leverage but also in terms of investing in riskier business
ventures. Within the context of Miles and Snow’s typology, prospectors would be
classified as ‘risk takers’, thus these firms would be expected to exhibit
smaller ratios than either defenders or analyzers. In contrast, the highest
measures should be associated with ‘risk averse’ defenders. Intuitively,
analyzers should fall near the middle of these extremes. Prospectors constantly
search for ways to expand current products and markets through innovation.
Conversely, defenders serve a very well defined niche with very little emphasis
on innovation. As a strategic construct, innovativeness has most often been operationalized
using marketing and R&D expenditures over sales (Snow and Hrebiniak, 1980;
Hambrick, 1983; Cool and Schendel, 1987; Das et al, 1991). Clearly, more
innovative firms would be expected to exhibit higher levels of these measures.
Recent work by Chakravarthy (1986) suggests that the ability of firms to
generate organizational slack may also be an important indicator of
innovativeness. In essence, levels of organizational slack refer to the firm’s
‘internal capital’ or the ability to generate cash flow for purposes of
reinvestment. Consistent with the recommendations of Chakravarthy (1986),
multiple measures are used as proxies of available organizational slack.
Operational efficiency is concerned with managerial control over operations and
assets. As noted earlier, defenders are much more attuned to operational
efficiency than either prospectors or analyzers. Thus, these firms should
exhibit higher measures of cost efficiency and employee efficiency. Again,
previous literature in the area of strategic management provide the foundation
for these operationalizations (Snow and Hrebiniak, 1980; Hambrick, 1983; Cool
and Schendel, 1987; Das et al, 1991).
Determination
of group membership. Within most research of this nature, hierarchical cluster
analysis is typically employed to determine the presence of similar groups
along variables of interest (Harrigan, 1983, 1985; Cool and Schendel, 1987;
Douglas and Rhee, 1989; Fiegenbaum et al, 1990). Although several clustering
algorithms exist, Wards minimum variance criterion was chosen for this analysis
based on past practice (Harrigan, 1985) and its accuracy in identifying
clusters in several simulation studies (Punj and Stewart, 1983). The clustering
criteria of this technique is minimization of total within-group sums of
squares. In other words, objects (in the present case firms) are assigned to
clusters (or groups) based on how similar they are to existing members along
the variables of interest. As the clustering algorithm progresses, it
eventually joins all objects into a single cluster. Hence, cluster solutions
range from a single cluster containing all firms to n clusters each containing
a single firm. In determining the appropriate cluster solution, the statistic
pseudo F is used. This statistic is defined as the mean square between groups
divided by the mean square within groups. Various clustering solutions are
plotted against pseudo F. ‘Jumps’ or ‘elbows’ in the plot are then used to
identify the appropriate number of clusters to retain. Examination of other
statistical criterion, namely root mean square and semipartial R square, are
often used to confirm visual conclusions. Once clusters of firms have been
identified, multivariate analysis of variance (MANOVA) techniques can be
employed to explore the existence of performance differences. Measures such as
return on assets (ROA), return on sales (ROS), return on equity (ROE), and
market share are typically tested across the emergent clusters for overall
effects. Univariate statistical techniques are then employed to determine
specific group differences (Harrigan, 1985; Cool and Schendel, 1987; Fiegenbaum
et al, 1990). Although several benchmarks for organizational performance exist,
analysis of similar studies suggests the use of profitability measures. This is
also consistent with research conducted by Woo and Williard (1983) of p er
ormance f criteria used in strategic management. Through factor analysis, these
authors uncovered four orthogonal factors identified as profitability, relative
market position, change in profitability and cash flow. Of these factors,
profitability demonstrated the highest factor magnitude. Chakravarthy (1986)
also notes the value of profitability measures as performance criteria in
distinguishing outstanding firms. Consistent with past studies and the
suggestions of these observers, multiple profitability measures are employed in
this study. Specifically, ROA, ROS and ROE will be used as measures of
organizational performance.
Strategic
and performance measurement by stages Changes in organizational performance
and/or strategic orientation can be attributable to a multitude of controllable
organizational variables as well as uncontrollable environmental variables.
However, as noted by several IS researchers (McFarlan, 1984; Vitale, 1986;
Clemons and Row, 1991), IT utilized as a strategic resource involves enormous
outlays of both financial and human resources. These systems tend to be
broad-based in their organizational and/or market impact and therefore should
have a direct influence on the firm’s financial measures (Clemons, 1986;
Clemons and Row, 1991). Thus, it seems plausible that measurement of strategic
variables before and after implementation of such systems can yield insight
into the contribution of these systems in maintaining or changing the firm’s
strategic orientation. In essence, the time order of events provides the means
to infer some degree of causality between implementation of strategic IT and
changes in strategic orientation and performance. Therefore, for each firm,
measures of organizational strategy and performance are formulated in three
stages: l Stage I (pre-launch): The five-year period before system launch. l
Stage 2 (post-launch I): The period from system launch to five years
post-system launch. l Stage 3 (post-launch 2): The period from five years
post-system launch to 10 years post-system launch.
Utilizing
objective variable proxies and multivariate clustering techniques previously
discussed, strategic orientation will be operationalized for the set of sample
firms in each of these time periods. Also, measures of financial performance
are compared between emergent groups in each time period in order to determine
if any particular strategic orientation consistently outperforms the others. To
reduce the impact of environmental and inter-industry influence, all data used
in this analysis is standardized. * Capturing variables in standardized form
helps eliminate differences in magnitude and variation which are likely to be
observed in cross-industrial analysis (Douglas and Rhee, 1989). In essence,
each observation will contain information about that particular firm’s position
relative to the industry average across the variables of interest. Such
information can be meaningfully compared with other firms within differing
industries. Year-to-year fluctuations are controlled by averaging data across
each five-year period. Doing so helps offset the effects of accounting changes
and environmental impacts which are temporary, yet may confound conclusions
regarding overall patterns in corporate resource allocation and profitability
(Hambrick et al, 1982). The use of these techniques is consistent with other
studies performed within and between industry boundaries (Harrigan, 1985; Cool
and Schendel, 1987; Hambrick et al, 1989; Segev, 1989; Fiegenbaum et al, 1990).
However, research designs of this type are complex and a great deal of care
must be taken in eliminating confounding influences. In Appendix B we include a
table outlining the methodological issues and associated control measures
pertinent to this particular study.
Results
Nature and change in strategic orientation Within each stage examined, a four
cluster solution was manifested by the strategic variables. In each of these
periods large ‘elbows’ in the plots of pseudo F were observed suggesting a
well-defined structure of organizational strategies among the sample firms. In
each of the time periods (Sl, S2 and S3) and for each strategic variable, the
standardized scores of firms comprising each cluster were averaged. These mean
values can be interpreted as the average distance in standard deviations the
firms in each respective cluster lie away from their industry averages. For
example, if a cluster’s mean score on the measure ‘assets’ is 2.00, then on
average the firms within this cluster lie two standard deviations above the
overall average for their respective industries (implying significantly large
firms). Table 2 summarizes the mean scores and sizes of each cluster across the
three time periods examined. Utilizing these measures, strategic orientations
were labeled as: large scale analyzers, moderate scale prospectors,
large-moderate defenders and large scale prospectors. Interestingly, in all
time periods each of the three strategic orientations seems present among this
sample of strategic IS users. Additionally, each identified cluster seems to
consist of firms that are of moderate to large scale. Differences among these
emergent clusters, however, are readily evident along the dimensions of risk
disposition, innovativeness and operational efficiency. As shown in the columns
of Table 2, both large and moderate scale prospectors exhibit standardized
scores which are indicative of riskier operating practices. Unlike the ‘risk
averse defenders’ and ‘middle ground analyzers’, the firms of these clusters
utilize greater amounts of financial leverage in their approach to competitive
practice. Thus, it can * Standardized data are obtained by dividing mean
corrected data by the respective deviation (X - p)/u. The mean of a
standardized variable is zero with variance equal to one. Hence these Z-scores
indicate how far above or below the mean (in terms of standard deviations) a
particular observation falls. Such measures are useful in the present research
context as they eliminate differences in scale across industries.
Table 2 Mean scores of emergent strategic orientations
Strategic
variables
Large
scale Moderate scale Large scale Large-Moderate prospectors prospectors
analyzers defenders
Sl
s2 s3 Sl s2 s3 Sl s2 s3 Sl s2 s3 n=4 n=9 n=9 n=13 n=5 n=5 n=4 n=4 n=4 n=9 n=12
n=12
Scope
Assets Sales
Risk
disposition Current ratio Quick ratio Times interest earned Equity to debt
Innovativeness
R&D/total sales Marketing/total sales Cashflow/investment Sales/total
assets Sales/working capital
Operational
efficiency Sales/COGS Sales/employees
2.50
2.54 2.61 1.06 0.98 1.14 2.20 2.25 2.14 1.70 1.67 1.56 2.34 2.40 2.43 0.97 1.10
1.04 2.12 2.15 2.11 1.13 1.21 1.25
-0.45
-0.33 -0.38 -0.79 -0.66 -0.68 0.11 0.08 0.10 1.61 1.53 1.73 -0.44 -0.33 -0.35
-0.66 -0.58 -0.55 0.08 0.14 0.11 1.40 1.42 1.35 -0.23 -0.55 -0.78 -0.44 -0.20
-0.12 0.01 0.09 0.03 1.53 1.55 1.54 -0.28 -0.55 -0.33 -0.26 -0.23 -0.28 -0.22
-0.26 -0.27 0.62 0.77 0.83
1.56
1.63 1.61 1.36 1.24 1.40 0.05 0.10 0.04 -0.98 -0.80 -0.86 1.28 1.33 1.41 1.44
1.32 1.38 0.03 0.05 0.06 0.60 0.53 0.58 0.75 0.78 1.10 1.02 1.11 1.06 0.78 0.67
0.66 1.11 0.99 1.01 0.93 0.94 0.93 1.12 1.17 0.91 0.96 0.95 0.98 0.66 0.72 0.80
0.71 0.81 0.80 0.95 0.99 0.97 0.29 0.33 0.33 0.56 0.44 0.43
-0.51
-0.42 -0.44 -0.71 -0.10 -0.55 0.15 0.09 0.10 1.65 1.71 1.69 -0.95 -0.91 -0.82
-0.85 -0.41 -0.57 0.22 0.18 0.13 1.55 1.53 1.44
All
figures arc standardized based on respective industry (SIC) data. Sl: Stage 1 -
five-year period prior to system implementation. S2: Stage 2 - five-year period
after system implementation. S3: Stage 3 - five-year to ten-year period after
system implementation.
be
inferred that these firms also exhibit higher thresholds for riskier
competitive investment. The identified prospectors also exhibit greater levels
of innovativeness. Higher levels of R&D and marketing expenditures, coupled
with the availability of slack resources, suggest a greater willingness and
ability by these firms to innovate within their competitive environments.
Conversely, the observed clusters of defenders and analyzers exhibit a lower
tendency to innovate, particularly as indicated by marketing and R&D
intensity. Defenders do, however, exhibit significantly greater levels of
operational efficiency compared with prospectors or analyzers. As shown in
Table 2, measures of cost and employee efficiency underscore the cost focus of
firms within this strategic group. Upon further analysis of emergent clusters
over the three periods, it was discovered that their membership was not
consistent. That is, a signficant number of firms had shifted group membership
over these time periods, suggesting a fundamental change in strategic
direction. Figure I illustrates the initial and final membership of sample
firms among the identified strategic orientations. Over the stages examined, a
single shift in membership occurred between Stages 1 and 2. Interestingly, no
change in strategic orientation was observed between Stages 2 and 3. As
illustrated in Figure I, firms lying within the intersection of the respective
strategic orientations shifted membership in the direction indicated by the
arrow. Eight firms which were clustered in Stage 1 as moderate-scale
prospectors (Mellon, Bane One, Digital Equipment, Bergen, Federal Express,
Baxter, Corestates, First Chicago) shifted strategic orientation in Stage 2 to
defender. In addition, five firms classified in Stage 1 as defenders (CIGNA,
Dow Jones, Nucor, McKesson, Air Products) shifted in Stage 2 to prospector.
Interestingly, the cluster of analyzers remained stable across the entire
period examined. In all, 17 firms (57 per cent) remained stable in terms of
group membership across the three stages.
American
Express
Digital
Equipment
Federal
Express
Prcder
& Gamble
General
Electric
Figure 1 Nature and changes in strategic orientation of IT innovators
Performance
differences among strategic orientations Given the identification of strategic
orientations across the stages of systems life, assessment of performance
differences between these emergent orientations was undertaken for insight into
those strategies which may be more leverageable through IT. As noted earlier,
the profitability measures ROA, ROS and ROE are used as indicators of
performance differences between observed strategies. Like the data used to
operationalize strategic orientation, these variables are standardized to
eliminate scale and variation differences between industries. Given the
potential correlation among these measures, a multivariate analysis of variance
(MANOVA) is employed to determine overall effects. If an effect is detected,
then univariate tests are utilized to determine the nature of pair-wise
differences. Table 3 contains the results of the MANOVA formulated during Stage
1. As shown, no overall effect is detected among emergent strategic
orientations. Thus, group membership was not useful in explaining patterns of
performance among the
Table 3 Comparison of financial performance between strategic orientations: Stage 1 (five-year pre-launch period)
MANOVA
4 Profitability measures F P>F Conclusion
Return
on assets (ROA) Return on sales (ROS) Return on equity (ROE)
No
significant overall effect two groups of prospectors and remaining groups of
defenders and analyzers before the launch of their strategic IT initiatives.
Stage 2 is measured from time of systems launch through the ensuing five years.
As noted earlier, a total of 13 firms (43 per cent) shifted strategic
orientation between Stages 1 and 2. Table 4 reveals the results of MANOVA tests
formulated during this second time period. As shown, a significant overall
effect is observed. Thus, these strategic orientations are different among at least
one of the performance measures tested. Utilizing Scheffe’s multiple comparison
test, both ROA and ROS were found to be significantly higher for large scale
prospectors vs large scale analyzers. In addition, large-moderate scale
defenders demonstrated significantly higher ROA and ROS measures than
large-scale analyzers. These findings seem to suggest the existence of an
‘initial impact’ of system implementation. That is, the two extremes of the
strategic continuum (defender and prospector) seem to be more initially
leverageable than the ‘compromise’ or middle-of-the-road strategic orientation
associated with analyzers. Analyzing performance differences from five to 10
years beyond systems implementation (Stage 3) yields insight into the
sustainability of the differences in performance uncovered in Stage 2. That is:
Are the prospector and defender strategies more leverageable in the long run?
In addition, the delayed emergence of a leverageable strategic orientation can
be detected. The findings of Table 5 seem to indicate that in the long run no
strategic orientation differentiates itself in terms of the performance
criteria tested. Specifically, no difference in performance measures among
strategic orientations was detected.
Discussion
In
general, the preceding analysis has revealed three important findings. First,
it appears that strategic users of IT are not concentrated along a singular
strategic dimension. The firms examined in this study exhibited characteristics
associated with each of the three strategic orientations of Miles and Snow.
Secondly, it seems that many of the firms shifted strategic orientation after
the launch of their systems. Interestingly, these shifts were from one extreme
of Miles and Snow’s typology to the other (ie prospector to defender or
defender to prospector). Finally, it seems that prospectors and defenders, as
opposed to analyzers, were more initially successful in terms of the
performance criteria tested. However, neither of these orientations were found
to be significantly better in the long run (five to 10 years after systems
launch). In the sections that follow we more fully develop the
Table 4 Comparison of financial performance between strategic orientations: Stage 2 (1-5 years post-launch period)
MANOVA
Profitability measures F P’F Conclusion
Return
on assets (ROA) Return on sales (ROS) Return on equity (ROE)
Significant
overall effect
Univariate
analysis Scheffe’s Multiple Comparison Test (p < 0.05, Df = 26) ROS, ROA for
large-scale prospectors significantly higher than large-scale analyzers ROS,
ROA for large-moderate scale defenders significantly higher than large-scale
analyzers
Table 5 Comparison of financial performance between strategic orientations: Stage 3 (S-10 year post-launch period)
MANOVA
Profitability measures
Return
on assets (ROA) Return on sales (ROS) Return on equity (ROE)
F
1.75
P>F
Conclusion
practitioner
and research implications of these findings. We will also seek to uncover
qualitative evidence which might lend support and further insight into the
patterns uncovered through the statistical methodology.
Strategic
orientation The fact that each of Miles and Snow’s generic strategy types was
well represented by the sample firms seems somewhat contrary to earlier
thinking which suggests that only innovative, riskier management styles and
strategic orientations are necessary to exploit advanced IT (MacMillian, 1982;
Wiseman and MacMillian, 1984). However, consistent with early and current
thinking (Clemons and Row, 1991), all firms exhibited large degrees of scale
relative to their competitors. This may suggest that size is an important
prerequisite for the large amounts of financial and human resources necessary
to formulate and implement IT-based strategy. In essence, scope may lessen the
competitive risk of developing these strategic technologies. However, because
of the breadth of resources and market activity associated with size, it may
also be inversely proportional to the impact of the system on profitability.
Importantly, it should be remembered that the sample drawn was not random and
consisted of well known systems; therefore, a bias may exist towards larger
firms. However, the magnitude of the scope variables seems to suggest that
market breadth and asset base may be important foundation factors in
implementing IT-based strategy. Notwithstanding the scale characteristics of this
sample, managers should view this set of findings with some degree of optimism.
It is interesting that many of these strategic users (analyzers and defenders)
generate and invest only moderate amounts of capital for the purpose of
research and development. These same firms are also rather conservative in
their approach to financing the operations of the firm. Thus, it would seem
that IT-based strategy is not restricted to pioneering firms with huge R&D
budgets and risk-taking managerial practices. Perhaps a more realistic view of
this phenomenon is that strategic opportunities to employ IT can be found
through internal analysis of operations and enhancement of pre-existing
systems. Such an analysis is typically inexpensive and risk-free in comparison
with developing and implementing completely new technologies and, as this
analysis seems to suggest, may be just as effective as more innovative courses
of action.
Shifts
in strategic orientation A second finding of this study concerns the shift in
strategic orientation by firms from Stage 1 to Stage 2. Here, our results imply
that IT may have facilitated the adoption of a different strategic orientation
for some firms. Interestingly, these shifts were from one extreme of Miles and
Snow’s typology to the other. A rather large number of prospectors shifted to
defenders, while a lesser number of defenders shifted to prospectors. From
Stage 2 to Stage 3, no shift in strategic orientation was detected. To further
explore the nature of these strategic shifts and the role of IT in supporting
strategic direction, annual reports of ‘transition firms’ (those firms which
changed strategic orientation during Stages 1 and 2) were analyzed. In these
reports, we specifically sought direct references regarding the system, firm
strategy, and competitive or technological imperatives for changing strategy.
Defenders
to prospectors. Of the transition firms which shifted from defender to
prospector, the annual reports of Nucor Steel, American Air Products, and
McKesson provide the most interesting commentary on changing strategic
priorities and the role of IT in implementing the needed change. In each of
these instances, a fundamental shift from ‘defender’ tactics of cutting costs
and improving productivity to ‘prospector’ tactics of developing value added
services and new markets is evident. As noted in these narratives, IT seems to
be a substantial factor in enabling this strategic change.
McKesson
- System Launch 1975 (5 years post-system launch - 1979-80) Internal
eficiencies . . . (Defender Tactic) ‘Our internal organizations have been
designed to minimize distribution costs to the greatest extent the company can
achieve.’ ‘ Productivity gains as a result of order entry technologies have
been enormous. The number of warehouses have been cut in half. Inventory turns
seven times a year, so fast that it is generally owned less than two weeks
after payment is made to the manufacturer.’ (McKesson 1979, 1980 Annual
Reports) (6-7 years post-system launch - 1981-82) Specialized needs of market
niches . . . (Prospector Tactic) ‘Although the order entry system is the most
visible of McKesson’s offerings, several other “value added” systems are
available for retail pharmacies, many provided on an d la carte basis, with
additional services supplied for additional fees.’ ‘McKesson also offers
services targeted toward the specialized needs of different market segments.’
‘Value added services are now a profit center. With current pressures on
distribution firms, more and more of the profit for these entities must come
from value added services.’ (McKesson 1981, 1982 Annual Reports)
Air
Products and Chemicals - System Launch 1981 (System launch) Proven capabilities
for future growth . . . (Defender Tactic) ‘Engineering skill, innovative
technology and marketing concepts, reliable products and processes, and the
ability of management at all levels to perform well, have enabled Air Products to
maintain a leadership position in most of its business throughout the world.
Our computerized system for directing outbound logistics has enabled us to
significantly lower our operating costs. These capabilities will be even more
important to the company in the future as we seek new avenues of growth.’ (Air
Products and Chemicals 1981 Annual Report) (2 years post-launch) Creating
market opportunities . . . (Prospector Tactic) ‘Even in today’s recessionary
environment there are opportunities for developing new businesses. By being
alert to these opportunities and responsive to customer needs, the company has
built a customer base that bridges a changing world.’ ‘To further probe the
future, Air Products has established a technical diversification department. It
is charged with seeking out and developing to the point of profitability new technology-based
businesses for the company. These new businesses are being carefully selected
to take advantage of the company’s unique strengths while meeting emerging
societal needs.’ (Air Products and Chemicals 1982 Annual Report) (2 years
post-launch) Keeping costs competitive but looking for opportunities . . .
(Prospector Tactic) ‘Controlling costs and improving productivity are corporate
imperatives in the current environment of slower growth and increased
competition. These are not new objectives for Air Products. The company has a
history of being a low-cost producer of industrial gases and chemicals. Staying
ahead of competition today and tomorrow, however, requires new techniques and
tools.’ (Air Products and Chemicals 1982 Annual Report)
Nucor
Steel - System Launch 1982 (System launch 1982) Focus on productivity . . .
(Defender Tactic) ‘The major strength of the company is in constructing plants
economically and operating them efficiently. These mills utilize modern
steelmaking techniques and produce steel at a cost competitive with steel
manufactured anywhere in the world. We believe we are one of the nation’s
lowest cost steel producers. For a number of years our prices for our steel
products have been equal to or lower than foreign steel prices.’ (Nucor 1982
Annual Report) (2 years post-system launch 1984) New products and processes . .
. (Prospector Tactic) ‘We are continuing to modernize our facilities and expand
our businesses.’ ‘ . . . we are particularly interested in new processes and
new techniques in steelmaking.’ ‘In recent years, Nucor Steel’s product line
has been broadened to include a wider range of steel products.’ (Nucor 1984
Annual Report)
Prospectors
to defenders. Of the transition firms which switched from prospector to defender,
the most clear qualitative evidence of technology-related strategic change was
found in the annual reports of Bergen Brunswig, Federal Express, and First
Chicago. As noted in the excerpts of these reports, IT seems to be aiding these
firms in implementing tactics of cost cutting, productivity enhancement, and
market focusing which are typically associated with defenders. Interestingly,
these reports, similar to those presented earlier, seem to suggest that
adoption of such practices is a fundamental departure from past operating
philosophies.
Federal
Express - System Launch 1980 (System launch) Pioneering new products and
processes
.
. . (Prospector Tactic) ‘Implementation of COSMOS (Customer Oriented Service
and Management Operating Systems) is an example of the advances which gave
Federal Express the capacity to deliver a better “product” to the customer with
a growing return to the company.’ ‘In its day-to-day operations, the underlying
concept of Federal Express is growth-oriented and continually evolving . ’
‘Even though the broad market for express package service has shown a healthy
growth, Federal Express and its market heave been growing much more rapidly.
This growth has not been achieved by increasing market share at the expense of
competitors, but from the creation and development of a market that is itself
an integral part of the growth and development of contemporary post-industrial
society.’ (Federal Express 1980 Annual Report)
(2-3 years post-launch) Improving productivity
. . reducing costs . . . (Defender Tactic) ‘In several major areas we finalized
investments in expanded capacity and more productive systems for the future.
Even so, our profitability was outstanding due to our continuous emphasis on
productivity.’ ‘Federal Express management is dedicated to improving
productivity and reducing costs.’ ‘ Recurring themes throughout the company’s
internal activities are enhanced productivity, maximum utilization of
resources, flexibility in dealing with change, and constant emphasis on
planning.’ (Federal Express 1981, 1982 Annual Reports)
Bergen
- System Launch 1972 (6 years post-launch) Productivity reaches new high
.
. . (Defender Tactic) ‘Another factor contributing to our greatly improved
earnings has been our progress in increasing productivity.’ ‘This further
improvement was made possible by the increasing acceptance by our customers of
our ULTRAPHASE order-entry and management system. In August 1977,70 per cent of
our drug wholesaling volume was received from customers on one or more of our
order entry systems. In August 1978, this figure increased to 82 per cent.
Increased use of order entry by our customers plus management and employee
effectiveness in improving productivity have been key elements in our
successful pursuit of productivity and increased earnings.’ (Bergen 1978 Annual
Report) (6 years post-launch) Focus on key markets . . . (Defender Tactic)
‘While capitalizing on order-entry technology to increase volume, we also have
used strategic planning to change our mix by concentrating on more profitable
customers, operating units, and products. In doing so we discontinued service
to unprofitable customers - reducing our drug wholesaling list to some 4,400
accounts from almost 8,000 about five years ago.’ ‘Management of Bergen
Brunswig Corporation has determined to place total emphasis on the area we know
and do best: Domestic Health Products Distribution.’ ’ By concentrating its
marketing thrust on chains and large independents, Bergen Brunswig sales to
these customers in 1978 rose 28 per cent over 1977.’ ‘A major factor in that
growth has been our success beginning in 1977 in getting new and existing large
customers to adopt our advanced ULTRAPHASE order-entry and management system.’
(Bergen 1978 Annual Report) (6 years post-launch) Technology investment for
controlling costs . . . (Defender Tactic) ‘Order entry has helped control
operating expenses. We are committed to electronic data processing and have
made higher than industry average investments in this area to obtain
technological superiority. Notwithstanding the required expenditures we have
achieved significant reductions in operating expenses. Besides helping increase
sales this technological advantage along with economies of scale has helped
Bergen Brunswig cut operating expenses as a percentage of sales and other
revenues by about a fifth below the industry average.’ (Bergen 1978 Annual
Report)
First
Chicago - System Launch 1983 (1 year post-launch) Market focus
.
. . (Defender Tactic) ‘Over the past three years, First Chicago Corporation has
developed a set of long-term strategic objectives to guide the planning and
resource allocation process. These objectives address the five broad lines of
business that we are pursuing . . . Within these, we have identified specific
market niches or initiatives, in which we feel confident we can achieve
significant success. ’ ‘Our commitment to this strategic focus has strengthened
over the last year with progress becoming apparent in each of our primary
businesses.’ ‘Fundamental changes in payments systems - technological,
regulatory and competitive - present opportunities that are being addressed
through aggressive marketing, resource allocation and operating efficiency. We
have elected to emphasize areas where we can differentiate ourselves through
unique value-adding features or where we can establish the necessary scale of
operations to achieve a cost advantage.’ (First Chicago Corporation 1984 Annual
Report) (I year post-launch) Increased efficiency, reduced costs . . .
(Defender Tactic) ‘To increase efficiency and reduce costs, we are
consolidating processing activities where legal and geographic constraints
allow. Also, investments in hardware and software in recent years have
culminated in the worldwide installation of the copyrighted F.I.R.S.T. system.
This integrated, real-time transaction system reduces back-office costs,
increases control of risk exposure, improves management and trading information
and provides customer relationship data that is useful for developing our
marketing plans.’ (First Chicago Corporation 1984 Annual Report)
The
empirical evidence of strategic change, along with these narratives, highlight
the importance of IT in enabling a ‘change of course’ in competitive
orientation. While the causes of the strategic changes observed in this
analysis are beyond the scope of this particular research design, it seems
clear that IT was a strong driver in implementing the strategic tactics deemed
necessary for competition by the planners in many of these firms. The stability
of strategic grouping in Stage 3 seems to further corroborate these fundamental
shifts in strategic orientation. Such findings should serve as healthy
reminders to top-planners of IT’s importance in setting and changing strategic
course. Perhaps even more importantly, managers must be prepared to adapt to
changing competitive conditions in light of IT-based strategic change by
powerful industry competitors. Firms caught off-guard by such changes may find
their cost structures and/or product lines obsolete, with little prospect for
developing near-term competitive responses. Interestingly, many of the system
descriptions provided in Appendix A seem to match the prevailing strategic
thrust of their respective firms. For instance, systems developed by defenders
such as Deere, Toys‘r’Us, and Digital are primarily inventory management
systems. Such technology would greatly enhance the efficiency orientation of
this strategic type. Conversely, systems developed by prospectors such as
Merrill Lynch, Gannette, IBM, and Xerox have as their focus product or service
innovation. Hence a large degree of strategy-technology congruence seems to
exist within these entities. These observations provide further evidence of the
technology-strategy link in coping with competitive pressures and the value of
the strategy construct in explaining patterns of IT use.
Performance implications
A
final finding of this study concerns the existence of performance differences
among emergent strategic orientations. Prior to systems launch, no strategic
orientation was determined to be superior as measured by multiple performance
criteria. However, immediately after systems launch, both large-scale
prospectors and defenders outperformed analyzers. Interestingly, these findings
suggest that the extremes of Miles and Snow’s three strategic patterns were
superior in realizing an initial impact from implementation of competitive IT.
Somewhat surprising were the results of Stage 3; here it was determined that no
strategic orientation was
Strategic
users of IT: A H Segars et al superior among the performance criteria. Thus, it
would seem that in the long-run no strategic orientation is significantly
better in terms of generating bottom line impacts from the development and
implementation of strategic IT. These findings reinforce the arguments of many
observers who suggest that the flexibility of new technologies make them
potential competitive weapons in both innovative and operational contexts
(Parsons, 1983). Hence, not only are each of the strategy types leverageable
with IT, but each seems to to be equal in its ability to enhance the long-term
profitability of the initiating organization. The findings of this study
illustrate the growing importance of information technology in supporting the
strategic objectives of the firm. Whether prospector, analyzer, or defender, IT
may provide an important capability in realizing and sustaining competitive
advantage. Clearly, the firms in this analysis were different with regard to
strategic orientation, yet each is commonly cited as a ‘first mover’ in
deploying IT for the purpose of establishing competitive advantage. Perhaps as
important, no strategic orientation proved to be consistently better than the
others in terms of relative profitability. Hence, it would seem that long-term
competitive gains are essentially the same whether IT creates new products or
processes (prospector use), simply improves productivity and/or reduces costs
(defender use), or combines elements of both innovating and cost cutting
(analyzer use).
Conclusions
In
many instances, studies of this nature raise as many questions as they answer.
It is clear that information technology will only become a more critical
strategic resource as data highways become established and end-users begin to
fully utilize ever-improving office technologies. What is less clear is how
these technologies can be molded into the overall strategic plan of the
organization and how much use translates into competitive advantage. Beyond its
intent, empirical results, and implications, this study should remind
interested observers of the potential difficulties of conducting research
within this domain. Clearly, a number of uncontrollable factors related to
industry, firm, and environment inhibit the precise testing and identification
of cause and effect relationships between strategic intent, IT, and financial
performance. However, such confounding effects do not diminish the importance
of conducting empirical research within this area. Instead, techniques should
be developed, tested, and improved upon such that the research questions
characteristic of this domain can be modeled and answered with a meaningful
degree of validity. Although we believe this study has taken a step in this
direction, the reported findings must be qualified. Similar to many studies
conducted within strategic management, the research questions addressed by this
study are very encompassing. Questions such as: What is strategy? How does IT
support strategy? and What strategies are most successful? are extremely
relevant and seemingly straightforward. However, formally answering these
questions with any degree of scientific rigor is at best problematic. It is
perhaps too exacting to address such questions with statistical techniques.
Yet, interviews and case studies suffer from the biases of those describing and
those reporting corporate events. Within this study we have attempted to
corroborate statistical findings with more qualitative corporate data. Such an
approach is perhaps the best way to address the larger issues inherent within
this area of inquiry. Our statistical methodology allowed us to identify
strategic characteristics of firms while descriptions provided in case studies
and annual reports allowed us to discern if the relationship between intended
strategy and IT use was valid. Although we believe this study advanced the
merging of these extremes, our work should be viewed as preliminary. Clearly,
much additional work remains to be done in addressing research issues in the
realm of strategic IT. It is also important to note that the statistical
methodology employed within this analysis utilized indirect measures of the
actual traits of interest. Hence, these variables contain a component of
measurement error. Although it is safe to say that grouped firms are homogenous
along sets of these variables, it cannot be stated with perfect certainty that
they are indeed prospectors, analyzers, or defenders. Other strategic
typologies with differing sets of indicators could possibly yield findings
different from those reported here. Further, the use of clustering algorithms
is not as statistically precise as principle components or factor analysis
techniques in determination of group numbers (or number of factors). Although
the groups in this analysis were readily identifiable upon analysis of the
pseudo F statistic, no statistical basis in terms of significant values guided
ultimate determination of group number. Hence, it is possible that different
multivariate grouping techniques would suggest different numbers of groups with
somewhat different membership. However, given the number of observations
required for these techniques and associated statistical assumptions, it is
likely that cluster analysis will continue to be the method of choice in
research designs of this type (Harrigan, 1983, 1985). A final caveat concerns
the strategic systems themselves. As shown in Appendix A, these systems are
quite varied in their purpose, scope, and potentially, in their contribution to
strategy and financial performance. Although this study uncovered several
consistencies between the functionality of these systems and strategic
orientation, it has not measured the magnitude of system influence on strategic
orientation or financial performance. Therefore, we can only say that patterns
in strategy and IT use seem present across the time periods examined, not that
one directly influences the other. Despite these limitations, the findings of
this study seem to confirm the existence of strategy-IT congruence. In essence,
the systems examined within this study seem to match the prevailing strategic
thrust of their initiators. Further, in some instances it seems that the system
may have played a major role in implementing a new strategic orientation.
Although such effects have long been thought to exist, their exact nature in
terms of timing, description, and financial implications have gone
unrecognized. Hopefully, this study has contributed significantly in
systematically describing these effects and, as importantly, stirred debate
regarding viable approaches to measuring constructs of interest within this
area.
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