A research and education initiative at the MIT
Sloan School of Management
JACKPOT OR FOOL’S GOLD:
SERVICES AS A DYNAMIC CAPABILITY IN
PRODUCT INNOVATION
Paper 245
October 2008
Phillip C. Anderson
For more information,
please visit our website at http://digital.mit.edu
or contact the Center directly at digital@mit.edu
or 617-253-7054
JACKPOT OR FOOL’S GOLD:
SERVICES AS A DYNAMIC CAPABILITY IN PRODUCT INNOVATION
Phillip C. Anderson
Ph.D. Student
Massachusetts Institute of Technology
Sloan School of Management
50 Memorial Drive, Room E52-557
Cambridge, MA 02142
phila@mit.edu
October 3, 2008
P.C. Anderson
Page 1
Abstract
After-sales product support is considered a complementary asset and often viewed as a
second class citizen within the high-tech product firm that must continually innovate in a
fast-moving industry. During the Internet age, many product-oriented firms amplified the
role of services in their business strategy through disruptive (e.g., multi-billion dollar
acquisitions) and organic (e.g., hiring thousands of employees) measures that resulted in
a growing proportion of total revenues coming from services. While some experts saw
this phenomenon as the next economic boom others saw this as a trap for the product
firm. This paper explores the evolution of this services phenomenon during a period of
revolutionary and incremental change to show that services are no longer peripheral
“second class citizens” but are in fact a central and growing dynamic capability within
product-oriented firms. Using a longitudinal study of a sample of product firms in the
intensely-competitive computer industry between 1994 and 2006, this paper begins to
explore how services evolved during a period of significant technological change, how
services affect firm performance, and how this phenomenon differs by technological
focus (hardware systems vs. software). This paper emphasizes the heterogeneity of
service functions beyond basic customer service – maintenance and product support – by
proposing a taxonomy of service categories and a product-service coupling continuum –
tightly coupled, loosely coupled, and uncoupled.
P.C. Anderson
Page 2
JACKPOT OR FOOL’S GOLD:
SERVICES AS A DYNAMIC CAPABILITY IN PRODUCT INNOVATION
The Jackpot Scenario:
Professional-services companies have always been the unglamorous part of the computer
business… But suddenly, services are in vogue… All this activity is catching the eye of Wall Street,
which once ignored these businesses in favor of flashier high-tech companies… Professional
services are hot now because they’re a way for hardware and software companies to add value to
their products.
The next boom in computers: services
Business Week magazine
July 7, 1986
The Fool’s Gold Scenario:
[Bill] Gates and I discussed the service trap. It is his proposition that if software is good enough,
all those services in which people install products and hook them together are not necessary…
The more screwed up the product is, the more service is required and the more money the
company makes. Not good.
Gates holds that service income is a death trap slyly presenting itself as a safe haven from
bloodletting product wars… What’s more, as producers retreat from the front lines, exhausted
from battling the latest Silicon Valley startup and its kamikaze products, shareholders will cheer.
Stock prices may spike on the expectation of predictable cash flow.
The road to ruin—services
Forbes magazine
Oct 12, 1998
I. Introduction
During the Internet age, many product-oriented firms began to amplify the role of
services in their business strategy. This paper explores the evolution of this services
phenomenon during a period of revolutionary and incremental change to show that
services are no longer peripheral but are in fact a central and growing dynamic capability
within product-oriented firms. As evidenced by the opening quotes, computer industry
experts have been divided over the role of services within product firms. Are services the
next economic boom or a trap to be avoided? This paper begins to explore how services
might also affect firm performance.
P.C. Anderson
Page 3
The Phenomenon
In April 1993, version 1.0 of the Mosaic web browser was released and Lou Gerstner
began his tenure as IBM CEO. The Mosaic web browser was the spark that ignited the
Internet revolution which was marked by radical technological change, an information
explosion, and a new era in commerce. Gerstner was the spark that ignited a historic
turnaround of an ailing computer industry legend. The System/360 mainframe business
was in decline, a lingering 13-year antitrust suit had extinguished their competitive fire, a
series of miscalculations relative to the PC squandered competitive advantages away to
Microsoft and Intel, and the overall industry structure was shifting away from vertically
integrated firms like IBM to a disaggregated mix of specialized firms.
IBM's services business was a quiet multi-billion dollar revenue source in the early
1990's. However, the services business was viewed as a complementary asset (Teece,
1986, Tripsas, 1997, Rothaermel, 2001) and “a second-class citizen next to IBM's
hardware [product] business” (Gerstner, 2002). Gerstner and his team made a big gamble
based on a conjecture that the industry would become less interested in processor speeds,
storage capacities, and proprietary systems and more interested in solutions that combine
products and services to solve specific customer problems. At the time, IBM made a
conscious decision to expand their services footprint from IBM product specific services
to multi-vendor service offerings that would often recommend competitor’s products.
But this would require a dramatic shift in skills, organizational routines, and culture.
Gerstner (2002: 133) recalls the situation:
P.C. Anderson
Page 4
We were expert at managing factories and developing technologies. We
understood cost of goods and inventory turns and manufacturing. But a
human-intensive services business is entirely different. In services you
don't make a product and then sell it. You sell a capability. You sell
knowledge. You create it at the same time you deliver it. The business
model is different. The economics are entirely different.
Between 1996 and 2001, IBM added 98,000 employees to the new IBM Global Services
division. In 2002, IBM gained another 30,000 services employees as the result of their
$3.5 billion acquisition of PricewaterhouseCoopers Consulting (PwCC). By 2003,
service revenues were beginning to exceed product-related revenues.
While IBM began to talk internally about a major shift towards multi-vendor services in
1993, DEC was already publicly articulating its strategic focus on multi-vendor service
opportunities in its 1993 annual report. In fact, Dell in its 1993 annual report
acknowledged DEC as a provider of next-day onsite service for Dell machines.
During the Internet age, more and more product-oriented firms in the computer industry
began to amplify the role of services in their business strategy. Prior to Carly Fiorina’s
arrival as HP CEO in 1999, HP had fallen behind in many of its product markets and was
woefully unprepared (as many other incumbents at the time) for the Internet revolution.
Fiorina recalls her view of HP's competitive position as follows (Fiorina 2006: 186-188):
P.C. Anderson
Page 5
We had great capability and deep resources, but we were spreading them
too thin. We were organized around products, and although this had
worked in the past, we now competed internally, duplicated effort, and
were difficult to do business with.
We were viewed as a product company, while IBM was viewed as a
systems company; our services business couldn't compete against IBM's.
… in the Internet age the pure product era had come to an end. We were
building stand-alone products, but our customers demanded systems and
solutions.
While Fiorina and team made internal structural changes as an attempt to leverage
synergies across various product business units, the need for a stronger position in
services was clearly on their radar. In 2000, HP was secretly in negotiations to acquire
PwCC in a bid that dropped from $16 billion to $3 billion (Fiorina, 2006). Although
interested in a stronger services position to compete against IBM, Fiorina recalls that she
walked away from the deal due to concerns over integrating a vastly different culture and
concerns over structural changes occurring in the technology market. HP would later
make a bold and controversial acquisition of Compaq in 2002 which provided better
competitive positioning in some product markets and a larger services footprint thanks in
part to Compaq's 1998 acquisition of DEC. Several years later under the leadership of
CEO Mark Hurd, HP would make a $13.9 billion acquisition of EDS, the largest
P.C. Anderson
Page 6
independent IT professional services firm with 2007 annual revenues of $22 billion and
over 130,000 employees.
Not only have the large established firms like IBM, DEC, and HP been amplifying
services within their strategy, some of the younger and smaller product-oriented firms
have been doing likewise. Red Hat, an open source software product firm, had almost
500 employees by the end of 1999. Not long after a successful IPO in August 1999, Red
Hat acquired Cygnus Solutions for $674 million in January 2000 to expand the scope of
their service offerings and professional services staff. The firm views services as a
mechanism for increasing the diffusion rate of their product (Red Hat 1999 annual
report):
We believe that providing these services and establishing ourselves as our
customers' technology development partner will allow us to facilitate the
widespread adoption of Red Hat Linux and other open source solutions as
full scale enterprise solutions.
BEA, a fast-growing software firm founded in 1995, reported services as a key element
of their strategy (BEA 1999 annual report):
[We continue to] develop new services offerings that focus on accelerating
delivery of end-to-end e-commerce solutions based on robust transaction
and application platforms. BEA continues to enhance its services offerings
through acquisitions and aggressive hiring.
P.C. Anderson
Page 7
The examples highlighted above begin to hint at four characteristics of a services
phenomenon within the computer industry. First, firms often established a separate and
distinct services organization which had internal links to R&D and sales divisions and
external links to customers. Second, firms often pursued an aggressive incremental
expansion via the addition of human capital to the dedicated services organization.
Third, firms often pursued a radical approach to services through acquisitions of
independent service firms and acquisitions of product firms with a strong services
footprint. Acquiring firms were willing to face the daunting task of integrating large
numbers of employees and vastly different cultures. Fourth, as a product firm amplified
its services focus, the firm's services revenues grew as a percentage of total revenues.
This paper explores the evolution of this services phenomenon during a period of
revolutionary change to show that services are no longer peripheral second-class citizen
but are in fact a central and growing dynamic capability within product-oriented firms.
Using a longitudinal study of product firms in the intensely-competitive computer
industry between 1994 and 2006, this paper begins to explore the following questions. 1)
How have services evolved during a period of technological change? 2) How have
services affected firm performance? 3) How has this evolution differed by technological
focus (hardware systems vs. software)? Differences by firm size, firm age, and firm
structure (vertically integrated vs. specialized) are potential subjects of future research.
This paper emphasizes the heterogeneity of service functions beyond basic customer
service (i.e., maintenance and product support) by proposing a standardized set of service
P.C. Anderson
Page 8
categories through which comparisons can be made across different groupings of firm
types.
The paper is divided into the following sections. Section II searches for an appropriate
theoretical perspective to help frame the discussion about services within a product
innovation setting. Section III describes the empirical setting for the paper and highlights
some of the key environmental forces shaping IT product firms between 1994 and 2006.
Section IV discusses the data collection methodology used to explore the evolution of
services from a qualitative and quantitative perspective. A taxonomy of service
capabilities is defined so that a comparison across firms can be conducted. Section V
presents the empirical results. Section VI discusses the empirical results and explores
why services have been on the rise among the product firms in our sample. Section VII
concludes with implications for practitioners and ideas for future research.
II. Theoretical Perspective on Services
While the services phenomenon has involved the flow of thousands of employees and
billions of dollars in acquisitions and revenues, the phenomenon has not yet found a firm
theoretical home in the academic literature. The following discussion will examine
services through a few theoretical lenses – product/process innovation, resource-based
view, and dynamic capabilities – and determine which lens will be most productive at
helping us frame the emergence of this services phenomenon during a period of
technological change.
P.C. Anderson
Page 9
Services and Product/Process Innovation
Most of the research on product-oriented firms in the computer industry has focused on
product innovation and product development. On one hand, the product development
literature focuses on micro level process-related issues such as development process
flexibility (Eisenhardt and Tabrizi, 1995, MacCormack, Verganti and Iansiti, 2001),
product design (Baldwin and Clark, 2000, Utterback, 2006), communication flows among
individuals and teams (Allen, 1977, Ancona and Caldwell, 1992a), team structure
(Ancona and Caldwell, 1992b), and decision-making (von Hippel, 1994). On the other
hand, the product innovation literature explores macro level issues such as the patterns of
technological change, lifecycles, industry dynamics, firm adaptation, and firm failure.
Our discussion begins with an attempt to situate services within the product innovation
literature.
One of the prevailing frameworks used by innovation scholars to explain the patterns of
technological change has been the Abernathy/Utterback ((Utterback and Abernathy,
1975, Abernathy and Utterback, 1978, Utterback, 1994)) product lifecycle model. The
hallmark of the framework is a diagram that qualitatively graphs the rate of product
innovation and process innovation over time. The nature of innovation, competition, and
rivalry pivots on the emergence of a dominant (product) design. Prior to the dominant
design in the era of ferment, the focus of innovation is product centric as new firms enter
and incumbents reorganize around the competence-destroying technologies or face a
possible demise. Following the establishment of a dominant design in the era of
incremental change, we expect the remaining firms to leverage their competenceenhancing know-how and to subsequently produce incremental product innovations while
P.C. Anderson
Page 10
simultaneously competing on the basis of lower costs driven down by process
innovations from the manufacturing division (Tushman and Anderson, 1986). The cycle
repeats when the next technological disruption occurs (Anderson and Tushman, 1990).
Perhaps services fit into the Abernathy/Utterback framework in one of three ways. First,
a service is often assumed to be just another product. Services that contain a high degree
of explicit knowledge can be codified within a technological system and offered in a
standardized manner. For example, a bank that offers a web-based mutual fund for its
customers is certainly providing a product. However, many other types of services
involve deep tacit knowledge and idiosyncratic know-how that is more human intensive
and less technological in nature. Cusumano et al. argue that services exist on a
continuum from standardized to customized, and hence they begin to highlight a
heterogeneity in service offerings (Cusumano, Kahl and Suarez, Forthcoming). A
standalone standardized service offering may perhaps follow a product lifecycle model,
but customized services may follow a completely different innovation model which could
be orthogonal to the product models. Another dimension for possible heterogeneity to
consider is how services are coupled with “traditional” products.
______________________________
Figure 1. Product – Service coupling continuum.
______________________________
Figure 1 demonstrates how a product-service coupling is not a homogeneous across all
product-service combinations. Services such as maintenance and product support are
usually bundled and tightly coupled to the product. Systems integration and installation
are examples of services typically offered as optional and loosely coupled to the product.
P.C. Anderson
Page 11
Project management and consulting are types of general services that can be independent
and uncoupled from the product. An example of a loose product-service coupling is
mentioned in EMC’s 2005 annual report:
“Installation and professional services are not considered essential to the
functionality of our products as these services do not alter the product
capabilities, do not require specialized skills and may be performed by our
customers or other vendors.”
Given the variation in services along a standardized-customized continuum and along a
product-service coupling continuum, the product innovation graph in the
Abernathy/Utterback framework is not well suited to capture the dynamics of the services
phenomenon.
Second, services may follow the process innovation graph in the Abernathy/Utterback
framework. If a product is in the mature phase of its lifecycle when the market has been
saturated and new sales are difficult, maintenance services become an important source
of revenue as the product firm refocuses its attention on the installed base of customers
(Cusumano, 2004). While this is certainly a plausible explanation, it lacks explanatory
power at addressing the heterogeneity in service functions beyond maintenance and
product support. A firm whose product sales have drastically declined is not likely to be
a legitimate source for cutting edge consulting advice. Therefore, a consulting service
may follow a different innovation rate curve than maintenance.
P.C. Anderson
Page 12
To limit services to a post-product innovation view of the world is to miss an additional
role that services may play relative to product innovation. Earlier in the paper, I
mentioned how Red Hat uses services as a mechanism to help establish the legitimacy of
their Red Hat Linux product and related open source technologies during the era of
ferment. In other words, services can positively influence the diffusion of a new
technology which is a crucial function for a young firm that faces a liability of newness
(Stinchcombe, 1965). Another example is how the diffusion of the mechanized reaper in
the 19th century was greatly influenced by service-oriented business models such as
renting and cooperative sharing arrangements early in its product lifecycle when the
average farmer could not afford to outright own the product (Olmstead, 1975). With
services playing a role during early and mature product stages, we should not try to
squeeze the services phenomenon into the process innovation graph.
Third, the services phenomenon could be a third innovation graph in the
Abernathy/Utterback framework or perhaps follow a reverse product cycle as proposed
by Barras (Barras, 1986). Given the heterogeneity of service functions, a third innovation
curve would be neither plausible nor generalizable across other industrial settings. The
product-service coupling would not fit within the Barras reverse product cycle
framework. The setting for Barras’ framework is the financial services sector and he
equates services to products whereas this paper treats products and services separate yet
with varying degrees of coupling. After examining three possible scenarios, the
Abernathy/Utterback framework provides a very limited fit for services.
P.C. Anderson
Page 13
A second highly influential work within product innovation research has been
Christensen’s study on the rigid disk drive industry (Clayton M. Christensen, 1993,
Christensen, 1997). His findings posit that “good, well managed” incumbent firms fail in
the face of radical and disruptive innovations which tend to be best exploited by new
startup firms with “good enough” technologies. Although incumbents often have access
to the new technologies, they are paralyzed because they listen too attentively to their
customers and remain fatally bound to the existing technologies. Christensen’s work
follows a component technology within a fast-moving industry undergoing a structural
change from vertically integrated to disaggregated specialized firms. The firms in this
paper face a similar turbulent and fast-moving industrial setting as the ones in
Christensen’s study, but the level of analysis here is more of a systems view (of services)
rather than the analysis of one specific component technology (or service). A systems
level approach is at a higher level of abstraction and subsequently is able to explore the
insights gained from the interdependency of individual components (Henderson and
Clark, 1990). In the typesetter industry (Tripsas, 1997), incumbents who possessed the
font libraries and sales/service network complementary assets were able to increase their
survival chances during technological disruptions since the new entrants did not possess
such complementary assets (Teece, 1986).
While Christensen argues that firms who pay too much attention to their customers risk a
possible demise, firms in this exploratory study appear to view services as a mechanism
for gaining deeper insight into customer needs and product usage patterns. Hence,
services as a complementary asset – “a second class citizen” at IBM –are not likely to be
the sole cause of a product firm collapse given that substitutes are available from thirdP.C. Anderson
Page 14
party service providers. Although the industrial setting of this paper is very similar to
the rigid disk drive industry in Christensen’s work, the exclusive focus on a component
technology is not likely to help explain the evolution of services as a complementary
asset during a period of technological change.
Services and the Resource Based View of the Firm
In the previous section, I showed how services fit very nicely into the complementary
asset perspective. In Teece’s paper about profiting from technological innovation, the
examples of complementary assets provided were “marketing, competitive
manufacturing, and after-sales support” (Teece, 1986). As I explained earlier, services
are more heterogeneous than maintenance and product support, but the overall fit as a
complementary asset is quite appropriate. A complementary asset may also be a
complementary product or technology that is owned by another firm. Rothaermel
showed how complementary assets are accessed beyond firm boundaries through
strategic alliances and how the number of alliances an incumbent formed with new
entrants had a positive effect on firm performance in the biopharmarceutical industry
(Rothaermel, 2001). A service in this study is a complementary asset that is managed by
the product firm although the asset could be owned or implemented by an external
service provider.
Although not originally articulated as such, a complementary asset is a resource. More
specifically, a complementary asset is a type of resource that is peripheral to the core
resources of the firm. Within a product firm in this study, the technological know-how
embodied within the R&D organization is typically the core resource of the firm. The
P.C. Anderson
Page 15
resource-based view of the firm is based on the idea that a firm’s idiosyncratic resource
endowment will provide it with a competitive advantage over firms who do not possess a
similar resource endowment (Wernerfelt, 1984). Earlier in the paper, we saw how
Fiorina was concerned about HP’s ability to compete with limited service resources
against IBM. At the time, her team acknowledged that IBM had a competitive advantage
over them based on a stronger services resource endowment. The resource-based view of
the firm shows promise as a lens through which to consider services. However, I see two
shortcomings. First, the firms who create a separate and distinct services organization are
actually creating an idiosyncratic mix of resources, know-how, and organizational
routines. (Nelson and Winter, 1982). This sounds much broader than a resource and
perhaps more like a capability. Second, the resource-based view of the firm is often
criticized for being a static framework (Teece, 2007). Since this paper examines the
evolution of services over time, perhaps the dynamic capabilities literature is the most
salient theoretical lens through which to explore the services phenomenon.
Services as a Dynamic Capability
In general terms, the strategic management literature views a firm’s organizational skills,
know-how, and routines as a capability (Nelson and Winter, 1982, Leonard-Barton, 1992,
Kogut and Zander, 1992, Teece, Pisano and Shuen, 1997, Zollo and Winter, 2002).
Polaroid had a competitive edge based on its strong technical capabilities in instant
photography and strong manufacturing capabilities in precision camera assembly and thin
film coating (Tripsas and Gavetti, 2000). HP developed a strong capability in
measurement equipment technology (Leonard-Barton, 1992). As market conditions
changed over time, the capabilities that made Polaroid and HP leaders became liabilities
P.C. Anderson
Page 16
and ceased to provide a competitive advantage. Conceptually, a dynamic capability
speaks to how a firm is able to adjust its resource endowments and how those
adjustments affect firm performance during changing market conditions. Eisenhardt and
Martin view dynamic capabilities as the strategic and organizational processes (e.g.,
product development, strategic alliances, and decision making) that create value for firms
in changing markets (Eisenhardt and Martin, 2000).
Helfat et al. (Helfat, et al., 2007) define a dynamic capability as “the capacity of an
organization to purposefully create, extend, or modify its resource base.” The evolution
of services within the computer industry fits the definition of a dynamic capability. First,
managers made intentional and purposeful decisions related to their services position.
Second, many product firms set out to expand their services resource base through
disruptive (e.g., acquisitions) and organic (e.g., hiring new employees) means. Using a
longitudinal study of product firms in the intensely-competitive computer industry, this
paper begins to explore how a services dynamic capability evolved during a period of
technological change, how a services dynamic capability affects firm performance, and
how has this evolution has differed by technological focus (hardware systems vs.
software)?1 This paper emphasizes the heterogeneity of service functions beyond basic
customer service (i.e., maintenance and product support) by proposing a standardized set
of service categories through which comparisons can be made across different groupings
of firm types.
1
Future research can explore differences by firm size (small, medium, and large), firm age (young, middleaged, and mature), and firm structure (vertically integrated vs. specialized).
P.C. Anderson
Page 17
III. Empirical Setting: The Computer Industry
Background of the Computer Industry
Due to space constraints, this paper will briefly summarize the broad themes that have
shaped the computer industry structure leading up to 1994 (Flamm, 1988, CampbellKelly and Aspray, 2004, Campbell-Kelly, 2003). The computer industry has gone
through four major eras: mainframe computers, minicomputers, personal computers, and
networked computers. The big players in the mainframe era were IBM and the Seven
Dwarfs (Burrows, Univac, NCR, Control Data, Honeywell, GE, and RCA). The pinnacle
of this era was the introduction of the IBM System/360 family of mainframe computers.
The minicomputer era was primarily dominated by DEC with its PDP and VAX systems
followed by Data General, Wang Laboratories, and Prime Computer. The leading firms
during the mainframe and minicomputer eras competed as vertically integrated with a
proprietary bundle of integrated circuits, the computer system, operating system
(software), and software applications along with product-specific services.
The PC era marked a significant sea change in the industry structure as the dominant
players were no longer the vertically integrated firms from the previous eras but rather
specialized firms who focused on one particular technological area – e.g., Intel for
microprocessors, Apple and Compaq for personal computers, Microsoft for the operating
system, and many small software product firms. The PC era also marked a shift from
proprietary systems to open systems based on industry standard interfaces. As new
specialized players entered with narrowly focused strategies, the basis of competition
became very product centric. The next major era began as users wanted to share
resources among the many personal systems. The networking era started with local area
P.C. Anderson
Page 18
networks (LANs) based on client-server architectures but eventually exploded with the
creation of the web browser that sparked the beginning of the Internet revolution in 1993.
The computer industry is known for being fast-paced and intensely competitive
(Eisenhardt and Tabrizi, 1995, Bourgeois III and Eisenhardt, 1988, Eisenhardt, 1989,
Cusumano and Yoffie, 1998). Although product development processes for hardware
and software products came to rely increasingly more on modular architectures and open
standards, the products have become increasingly complex to develop (Iansiti, 1995) and
also complex to integrate into diverse customer environments (Goodstadt, B. and Kessler,
S., 1999, Graham-Hackett, 1999). While each era was marked by a punctuated change
with new entrants and product categories, customers were more likely to add capacity
with the new products than to rip and replace the older legacy systems that dated back to
the mainframe era.
By 1994, the industry was structured into three main sets of players: hardware systems
firms, software product firms, and independent services firms.2 [NOTE: need an analyst
report from 1993. Until then, I’m using 1998 S&P industry reports.] By 1998, hardware
revenues were approximately $250 billion with nearly 70% coming from PCs and the
remaining from workstations, servers, and the high-performance market. The market
share leaders were Compaq, IBM, Dell, HP, and Packard Bell-NEC (Graham-Hackett,
1999). By 1998, packaged software was a $135 billion market where the top five
vendors were Microsoft ($16.8 billion), IBM ($13.5 billion), Oracle ($8.0 billion), and
2
The semiconductor (primarily Intel), storage, peripherals, and telecommunications sectors have also
shaped the general computer industry.
P.C. Anderson
Page 19
Computer Associates ($5.1 billion), and SAP ($5.1 billion) (Goodstadt, B. and Kessler,
S., 1999). By 1998, worldwide computer services was a $296.4 billion market with IBM
as the leading vendor with revenue of $23.4 billion. Two of the leading independent
services firms were EDS3 ($16.9 billion), Andersen Consulting4 ($XXX billion), and
Computer Sciences Corporation $7.4 billion (Goodstadt, 1999).
Technological change between 1994 and 2006
The computer industry underwent disruptive and incremental technological change
between 1994 and 2006 that subsequently shaped the environment and product firm
strategies. The most notable source of incremental technological change is characterized
as Moore’s Law, a popular rule-of-thumb for predicting the increased speed of computers
over the last four decades (Campbell-Kelly and Aspray, 2004). While some view
Moore’s Law as less of a predictive mechanism and more of a self-fulfilling prophecy
(Mollick, 2006), raw performance and price/performance continued to improve between
1994 and 2006 for memory, storage, communication, and processing technologies. This
period was marked by major transitions in microprocessor technology from 16-bit to 32bit, 32-bit to 64-bit, and single-core to multi-core on a single chip. As component
technologies advance, the corresponding ripple effects occur throughout the industry as
witnessed by new hardware systems, devices, and peripherals; new software applications,
middleware, and tools; and the accompanying services that help users integrate these
products into their IT environment. Users have up to three options for services: their own
3
4
EDS was a spin off from General Motors Corporation in June 1996.
Andersen Consulting is now known as Accenture.
P.C. Anderson
Page 20
internal IT staff, product suppliers, and third-party IT services providers (e.g., EDS or
Accenture).
While Moore’s Law describes the high-velocity incremental march towards greater
performance in this industry, the Internet is the primary disruptive technological change
during this period. Although engineers, scientific researchers, and university students
were using the Internet by the late 1980’s, it wasn’t until the Mosaic/Netscape browser
was made generally available in 1993 that the extraordinary growth of the Internet began
to unfold (Campbell-Kelly and Aspray, 2004). The Internet and the subsequent
technologies built on it have been a catalyst for new organizational forms (e.g., Internet
firms and open innovation projects), new business models, new collaboration tools, and
unprecedented access to an abundance of information. The Internet became as much a
commercial revolution as an information revolution.
Between 1994 and 2006, several open source software projects emerged as credible
alternatives to traditional “closed source” proprietary software products. For example,
the Linux operating system – started as a hobby by Linus Torvalds in 1991 – evolved into
a legitimate business-critical product that is actually favored for some enterprise
workloads. At a minimum, open source is a non-technological disruptive change that
represents a different development model and forces firms to rethink software product
business models. While the product firms in this sample who offer open source software
products utilize a services-oriented business model, the long-term competitive and
economic implications of the open source model on the existing closed source software
model remains uncertain.
P.C. Anderson
Page 21
IV. Research Methodology
Data and Measures
Twenty-two large, publicly-traded computer industry product firms were selected as an
exploratory sample for this study. These firms have a significant presence in the
intensely competitive and financially lucrative enterprise computing market. While many
of the firms have a presence in the consumer market, the focus on service capabilities was
very evident in the enterprise space. Eleven of the firms generate a majority of their
product revenues from software product sales across various categories such as operating
systems, middleware, applications, systems management, and tools. The remaining 11
firms generate at least half of their product revenues from hardware systems product sales
across categories such as computer systems, networking equipment, storage, and
peripherals. Many of the hardware firms also have strong capabilities in software
development which results in standalone software products, systems software bundled
with the hardware, or as complementary tools. Firms in the sample represent diverse
product markets (consumer, enterprise, and technical), innovation models (proprietary
and open source), and distribution channels (direct and indirect). See Table 1 for a listing
of the firms by SIC code. Although the sample of firms is biased towards large product
firms, a shift towards more of a services orientation may possibly become an
institutionalized norm throughout the industry. In that case, the findings from this study
may indicate a larger industry-wide phenomenon.
______________________________
Table 1. IT product firms in this study.
______________________________
P.C. Anderson
Page 22
Qualitative Measures of Service Capabilities
Data was analyzed and coded from annual 10-K reports that were filed with the U.S.
Security and Exchange Commission (SEC). The 10-K reports were downloaded from the
SEC’s Electronic Data Gathering, Analysis, and Reporting (EDGAR) database. I started
a content analysis of the business (i.e., Item 1) and management discussion (i.e., Item 7)
sections within 257 10-K reports to specifically capture the dialogue relative to a firm’s
service capabilities. Electronic copies of the 10-K reports are not available across all 286
firm-years (i.e., 22 firms x 13 years) because two firms were founded after 1994, three
firms were acquired prior to 2006, and a few reports were not available in electronic form
in the EDGAR database.
As I began the content analysis of the 10-K reports, I noticed very little year-to-year
fluctuation in categories within a firm. Once a service capability is mentioned in the 10K, it tends to persist across multiple years. Therefore, I coded service capabilities in
three-year intervals – 1994, 1997, 2000, 2003, and 2006.
Services Taxonomy
Although often identified by different names, the coding of service capabilities began to
reveal a similarity across firms during the initial phase of the content analysis. For that
reason, I sought to utilize a standardized taxonomy that facilitates the ability to compare
and contrast service capabilities across firms. In Figure 2, I propose a taxonomy of
service categories that highlights the heterogeneity in service capabilities. Lah et al.
(Lah, O'Connor and Peterson, 2002, Lah, 2005) present a services taxonomy of computer
industry firms that emphasizes the professional services categories. Whereas Lah et al.
P.C. Anderson
Page 23
distinguish between technical and business consulting, Figure 2 only contains a
consulting category. The goal was to create categories only when unique skills, knowhow, and routines were identified. The taxonomy also includes services-oriented
business model categories. The hope is that the taxonomy will be a robust lens through
which other product industries can be evaluated in future research.
______________________________
Figure 2. Services taxonomy for product firms.
______________________________
The eight categories in Figure 2 are organized into three broad themes consistent across
the IT product firms in our sample. Customer service is the baseline level of product
support that comes bundled with the product. Professional services tend to be optional
services that are typically knowledge worker intensive. Business model driven services
are service capabilities that provide customers with new ways to use and access the
suppliers’ products. Many of these types of business models began to emerge between
1994 and 2006 (Cusumano, 2008).
Customer Service
Maintenance and product support services are the baseline level of services usually
bundled with the product. Firms often offer extended levels of support beyond the
baseline for additional fees.
Professional Services
P.C. Anderson
Page 24
Deployment services include any optional for fee work activities that help customers
deploy the product within their data center. Examples are installation, implementation,
configuration, systems integration, and migration services.
Custom development services involve customization work above and beyond the mass
market product offering.
Education and training services include product training and certification programs.
Consulting services involve a range of technology to business advice which typical.
These services may also overlap with implementation services which are included under
deployment in this taxonomy.
Business Model Driven Services
Outsourcing services provide customers with an opportunity to transfer installation and
day-to-day operations to the product firm or a third-party. For this study, we will focus
only on outsourcing provided through the product firm.
Utility computing services provide customers with metered usage of a high-tech product
similar to a public utility such as gas or electric service. The product may or may not be
installed and maintained on the customer premises. This category has some overlap with
outsourcing and exists under various names such as “on demand” computing, pay per
use, and software as a service (SaaS). I also lump “pay for access” subscription services
under this category.
P.C. Anderson
Page 25
Financial services provide creative options for customers to purchase products.
Examples include leasing and financing.
Figures 2 and 3 provide one way to explore the heterogeneity of service capabilities in a
longitudinal study of IT product firms. Although Figure 2 shows all service capabilities
with a uniform connection to products, Figure 1 earlier highlighted a variation in the
product-service coupling with tightly coupled (e.g., bundled services such as maintenance
and product support), loosely coupled (e.g., deployment), and uncoupled (e.g., project
management or business consulting) services. The maintenance and product support
capability is so tightly coupled with the core product that a product-service distinction is
often blurred. A few firms changed their categorization of maintenance revenues from
services to products between 1994 and 2006. As a qualitative measure in this study, I
preserve the original categorization of maintenance as a service capability. This causes
no degradation in the qualitative breadth measures because there is no variation in
maintenance across firms and years (i.e., maintenance always exists and is always coded
as “1”).
Breadth and Depth of Services
In a given year, a firm’s aggregate service capability index ranges from one (e.g.,
maintenance is a default service available across all product firms) to eight. A variable is
maintained for each of the eight categories and each is coded at three-year intervals (0 =
no capability, 1 = service capability). The firm’s aggregated service capability index is a
sum of the eight indicator variables. The aggregated index measure provides a rough
P.C. Anderson
Page 26
breadth indicator of a firm’s strategic intent towards its service capabilities and how the
mix changes over time. A firm may subsequently deepen its presence in a service
category over a number of years, but that is not captured by the breadth index. Figure 3
presents a two-dimensional framework for analyzing the evolution of services within
product firms.
______________________________
Figure 3. Qualitative measures of breadth and depth.
______________________________
While firms are more than willing to publicize (e.g., in 10-K reports and press releases)
their range of capabilities, firms are very reluctant to disclose the accompanying depth of
resources and investment levels behind those capabilities. Hence, a corresponding
service capabilities depth index cannot be measured from 10-K report data. However,
depth is being thought of at multiple levels as shown in Figure 3. The baseline begins
where a firm provides one or more tightly-coupled product specific services for its own
products. As the firm adds service capabilities for products beyond the boundary of the
firm such as for partners’ products and competitors’ products, the firm’s service
capabilities are considered to be deepening. As a means to expand their sphere of
influence, firms often position themselves as a “one-stop shop” and offer comprehensive
services that also provide coverage of their competitors’ products. Finally, a product firm
may offer services that are entirely product independent such as business consulting or
project management. Preliminary evidence of this deepening effect is discussed later in
the paper.
Quantitative Measures of Service Capabilities and Firm Performance
P.C. Anderson
Page 27
Since the qualitative measures provide an indication of the strategic intent of firms during
a period of technological change, the paper further explores the effect of services on firm
performance. Financial data was gathered from 10-K reports, COMPUSTAT, and
Mergent Online for the sample of 22 firms between 1994 and 2006. In general, all
revenue figures were based on original SEC filings and not restated filings. Exceptions
were made in a few cases when original services revenue data included product revenue.
For example, in 1994 and 1995 HP’s service revenue included sales of consumable
supplies and product parts. In 1996, the service revenues were restated for 1994 and
1995 without the parts and supplies revenues. When revenue data from the public
databases (i.e., COMPUSTAT and Mergent Online) did not distinguish between product
and service segment revenues, I consulted the 10-K reports and often found the
segmented data located in the business or management discussion section.
In 1997, a new accounting standard (SFAS 131) was passed stating that firms must report
segment financial data by business segments, geographic segments, or both. By 1999, all
firms in the sample were reporting segmented services revenue figures. For firms that
were not reporting services revenues prior to SFAS 131, the services financial data could
often be captured for the two years prior to the first SFAS 131-compliant annual report.
Using a cross-sectional time series model, I set out to explore the effect of services on
firm performance. Since firms do not consistently break out service revenues across the
service categories, I was constrained to explore only the aggregated effect of services
contribution on firm performance. With the firm as the unit of analysis, a fixed effects
P.C. Anderson
Page 28
model is used to explore within firm variation. The results of this model have been
moved into the Appendix.
Dependent variable
Operating income. Operating income is a measure of a firm’s earnings before deduction
of interest payments and income taxes.
Independent variables
Service revenue contribution. This variable is the percentage of total revenues attributed
to services. When not accessible in the COMPUSTAT and Mergent Online databases,
service revenue data were gathered from the 10-K reports. In order to consider a possible
nonlinear relationship between services and firm performance, I include a service revenue
contribution squared term.
Firm control variables
US sales. This variable measures the percentage of sales coming from the United States.
In cases where US sales were not available, I operationalized US sales using an estimated
percentage of North America sales (e.g., 98%) or Americas sales (e.g., 95%). The 98%
and 95% estimates were chosen because historically these firms reported large sums of
revenue from US operations. When new geographic segments (e.g., North America or
The Americas) were created, most of the sales are still believed to be coming from the
US.
R&D expenses. This variable measures R&D expenses as a percentage of annual sales.
P.C. Anderson
Page 29
Firm size. Firm size is operationalized as the log of the total number of employees in a
given year.
Lagged product sales. The log of one-year lagged product sales is included in order to
see how strong or weak product sales from a prior year affect financial outcomes in the
following year.
Hardware product sales. Although each firm is categorized broadly as either a hardware
or software firm during the entire longitudinal study, a fixed effects model drops
variables that have no variation across the time period. Therefore, the hardware product
sales variable measures the proportion of actual hardware product sales in a given firmyear.
Industry control variables
Y2K. This variable is included as an indicator of sales that are perhaps driven by the
concern for the Year 2000 problem (Y2K) facing firms on January 1, 2000. Y2K
contains a value of one across all firms for calendar years 1998 and 1999 and zero
otherwise.
Dot com bust. This dummy variable controls for the downturn in 2001 caused by the
bursting of the dot com bubble. The variable holds a value of one across all firms in
calendar year 2001 and is zero for all other years.
P.C. Anderson
Page 30
V. Empirical Results
Qualitative Results
Exploring Breadth
The graphs in Figure 4 measure the average service capability breadth across the firms as
coded at the three-year intervals of 1994, 1997, 2000, 2003, and 2006. Figure 4a
suggests that on average all product firms increased their total services footprint between
1994 and 2006 by two capabilities while the net increase for software product firms was
approximately one greater than for hardware product firms. Most of the breadth
increases occurred by 2000 and remained relatively flat up through 2006. A net increase
of three capabilities by software firms slightly exceeded a net increase of two by
hardware firms. However, by 2006, hardware and software firms were active with an
equivalent number of service capabilities.
Figure 4b captures the change in the professional services grouping and suggests that on
average all product firms increased their professional services footprint between 1994
and 2006. The net increase for software product firms was nearly two while the net
increase for hardware product firms was approximately one capability. Although most of
the professional service breadth increases occurred by 2000, software firms experienced a
slight increase while hardware firms experienced a slight decrease in professional
services between 2000 and 2006. Some hardware firms either withdrew from custom
development services altogether or they began to deemphasize custom development as a
strategic capability to highlight.
P.C. Anderson
Page 31
Figure 4c captures the change in the service-oriented business model grouping and
suggests that on average all product firms increased their business model services
footprint between 1994 and 2006. The net increase for hardware product firms was one
while the net increase for software product firms was less than one whole capability.
Although most of the business model service breadth increases occurred by 2000 for
software firms, hardware firms experienced a continued increase between 2000 and 2006.
Intuitively, the business model service capabilities are likely underrepresented in these
results due to insufficient data directly available about these capabilities in the 10-K
reports.
______________________________
Figure 4. Evolution of Service Capabilities Breadth.
______________________________
Exploring Depth
A rigorous operationalization of service capability depth is near impossible to gather
from only 10-K reports. However, excerpts from several 10-K reports are suggestive of a
deepening effect in services relative to products (i.e., firm, partner and competitor) and
services driven independent of any specific products. Intuitively, product suppliers are
more likely to provide expanded services for products at or above the level of products in
their portfolio relative to a technology solutions stack. More specifically, I expect to see
hardware systems firms provide services for products equivalent to their own hardware
systems and also for software products further up the stack. However, I do not expect
software firms to move down the stack and offer services for a partner’s or competitor’s
hardware products.
P.C. Anderson
Page 32
Services Depth for Firm Products
Oracle announced an outsourcing service for its enterprise applications in 1999 where the
equipment was hosted on Oracle’s premises:
By 2002 Oracle introduced a broader outsourcing service with more flexible options
where the equipment could be located on Oracle’s premises, at the customer’s data
center, or at a third-party location:
Services Depth for Partner Products
HP demonstrated an increasing level of services for ERP software products from its
partners between 1998 and 2000 in 10-K reports:
P.C. Anderson
Page 33
Services Depth for Competitor Products
Several product firms have sought to position themselves as not only competent in their
own product portfolios, but also with respect to products from their partners and even
their competitors. For example, DEC in 1994, IBM in 1999, EMC in 2001, and HP in
2002 mention their ability to offer multi-vendor services to position themselves as onestop shops of IT expertise for their customers.
P.C. Anderson
Page 34
Similar to DEC, IBM, and HP, EMC positioned itself more as an expert general
contractor as it continued to articulate its growing support agreement portfolio ties most
likely with partners and competitors.
P.C. Anderson
Page 35
Services Depth Independent of Products
As firms started to understand the opportunities available through internet technologies,
they began to expand their support delivery mechanisms. While BEA offered basic and
comprehensive 7x24 product support via a telephone hot line in 1998, by 2006 they had
expanded the support delivery mechanisms to include telephone, web, email, and fax. In
1997, Symantec began to offer a fee-based technical support service called Chat Now!
™. In 1998, Dell “introduced an interactive web-based tool to provide additional
customer support.” The ability to have a web-based real-time interactive chat is likely
one of the bigger leaps in delivery mechanisms compared to long hold times that often
accompany telephone support calls. However, Dell and other firms were offering product
support through paid online services such as CompuServe, America Online, and Prodigy
and on electronic bulletin boards in the early 1990’s. By 2006, all firms were leveraging
online communication mechanisms for product support.
Quantitative Results
While Cusumano showed the rise in service revenue contribution within software firms
(Cusumano, 2004, Cusumano, 2008), Figure 5 shows the product-service contribution
proportions between 1994 and 2006 across the collective sample of firms in this study
and also split by hardware and software firms. While all IT product firms in this sample
experienced a greater contribution from their aggregated services business, software
firms became service oriented at a much faster rate than hardware firms. Although the
increase in service revenue contribution is quite apparent in Figure 5, that graph only tells
a part of the story. If product sales are dropping, a corresponding service contribution
P.C. Anderson
Page 36
increase may signal a greater reliance on maintenance revenues whereas a simultaneous
increase in product sales and service contribution signal product momentum and perhaps
an intentional effort to expand the firm’s service capabilities. Figure 6 shows that service
contribution has been growing during both product downturns and growth periods.
______________________________
Figure 5. Product and service revenue contribution.
______________________________
______________________________
Figure 6. Product $ vs. service revenue %.
______________________________
Table 2 displays the firm-year means and correlations for the key variables used in the
models. The mean operating income across all firms between 1994 and 2006 is 1.7
billion US dollars and the median value (not shown in Table 2) is 323 million US dollars.
IBM and Microsoft are the primary outliers with respect to high levels of operating
income during this period. Across all product firm years, the services business generates
35.77% of total sales revenue. The mean number of employees is 38,636 (not shown in
Table 2). The mean age is 28.26 years. This sample of firms relies on over half of its
sales from customers in the United States. Therefore, in the fast-moving IT industry, our
sample represents firms that are relatively large and mature. Due to the wide variation in
firm size (i.e., 103 to 355,766 employees) and product revenues (i.e., $0 to $74.2 billion)
across firms, the logarithm of those respective variables is used in the models. Although
a wide variation in operating income exists across firms, one-fourth of the values are
negative and so I did not use logarithms.
______________________________
Table 2. Means and correlation coefficients.
P.C. Anderson
Page 37
______________________________
While Table 2 provides the means across all firm years, Table 3 shows that there is a
significant difference between the hardware and software firms in the sample by firm age,
firm size, R&D spending, and revenue contribution from services. The difference in firm
age is likely skewed by the inclusion of IBM and NCR, founded in 1924 and 1884
respectively. Of the firms in this sample, two software firms and one hardware firm were
founded while one software firm and two hardware firms were acquired between 1994
and 2006. Consistent with the graphs shown earlier in Figure 5, software product firms
are experiencing a growth in services revenue contribution at a faster rate than hardware
product firms. Hardware firms require a greater level of capital investment to develop
and reproduce their products than software firms. The capital constraints within
hardware firms appear to have a moderating effect on the transition to services by
hardware firms.
______________________________
Table 3. t tests on mean firm value.
______________________________
VI. Discussion
This paper set out to research the evolution of services within an exploratory sample of
product-oriented firms and to subsequently see how this phenomenon differs by
technology focus (i.e., hardware vs. software firms). The empirical results suggest that
product firms in this sample have amplified their services position beyond basic customer
service into professional services and into service-oriented business models. While the
P.C. Anderson
Page 38
professional services functions have similar characteristics to tacit knowledge, the
business model services are often new ways of delivering products to market.
Technologies such as open source software and virtualization software have forced firms
to explore service models such as subscriptions and utility computing, respectively.
A further content analysis of 10-K reports suggests preliminary evidence for an increased
depth of services from firms in this sample. On one hand, an expansion of existing
capabilities relative to the firm’s products is to be expected as a firm continues to grow
and mature. On the other hand, an expansion of the role of services that is inclusive of
partner products and competitor products is a somewhat surprising and risky tactic. The
firm must grow or acquire the expertise as well as exceed a legitimacy threshold in the
eyes of customers who may normally obtain such services from the competitor or a third
party service provider.
During periods of technological change, we know that new firms often drive disruptive
change which subsequently causes incumbents to fail (Christensen, 1997). According to
Christensen’s framework, we should have seen more incumbents fail and new startups
dominate the industry. The empirical setting for Christensen’s work is the rigid disk
drive industry which is one device within a larger complex system. Incumbents in
complex product categories have opportunities to use standard components in novel ways
that provide distinguishable advantages (Henderson and Clark, 1990). Since a
component supplier is easier to replace than a vendor of a complex computer system or
enterprise software product, I would expect greater turnover in a component industry. As
with the typesetter industry (Tripsas, 1997), incumbents that possess a key
P.C. Anderson
Page 39
complementary asset are more likely to buy more time during an era of technological
change or are more able to fight off technological disruptions caused by new firms that
do not possess the complementary asset. For firms whose core technological know-how
is tied to its products, services appear to be a complementary asset. Through the use of
an exploratory longitudinal study, this paper has shown the heterogeneity of service
capabilities and also how the evolution in services fits the characteristics of a dynamic
capability within the computer industry between 1994 and 2006 (Teece, Pisano and
Shuen, 1997). The paradox is that in some firms a complementary asset has become the
core revenue generating engine. In other words, some product firms who are
traditionally rewarded by analysts and Wall Street for innovative products (i.e., the core
resource) are generating their core economic value from services (i.e., the peripheral
resource). This paper provides new insight into how a “second class” complementary
asset evolves into a central strategic asset. This paradox is more pronounced among the
software firms in this sample.
Although Figure 5 shows how software firms are moving faster towards services, the
preliminary results from the models in Table 5 suggest that the hardware firms may have
a better approach. Somewhere between 25% and 40% is the point at which service
contribution has a positive effect on firm performance. However, future research ought
to explore the effect of the service mix on product revenues. In other words, which mix
of service capabilities – maintenance, consulting, outsourcing, etc. – is likely to have the
greatest effect on product revenues?
P.C. Anderson
Page 40
IT customers have three options for services: in-house IT staff, third-party service
providers (e.g., EDS and Accenture), and product vendors. The causal mechanisms
behind the march towards more services by product vendors are beyond the scope of this
data set. However, I speculate that five reasons may contribute to this shift by product
firms. First, many IT customers began to look to external partners for help with their IT
tasks. While the pace of change increased and the competitive environment intensified
between 1994 and 2006, IT customers faced a double-edged sword of implementing new
strategic initiatives while simultaneously maintaining their basic infrastructure needs
(Hoffman, 1997, Hoffman, 2003). Consequently, CIOs were more willing to outsource
some basic infrastructure services to external vendors while facing greater scrutiny of IT
budgets from senior executives (Hoffman, 1997, Hoffman, 2003). Following the burst of
the dot come bubble, CIOs continued to look for ways to reduce costs through IT
enablement but under conditions of greater scrutiny from senior executives (Rosen,
2001).
Second, many product categories have shifted away from proprietary products to
products based on industry standards. As product margins erode, incumbent product
firms are likely to search for new sources of revenue that can be built up in a competence
enhancing manner (Tushman and Anderson, 1986). Starting from a base of services
coupled to its own products, firms have expanded into services covering partner products
and competitor products. However, whether services are the next economic boom for
this industry or simply a trap for incumbents no longer able to compete with “the latest
Silicon Valley startup and its kamikaze products” (Karlgaard, 1998) remains unclear in
the short term.
P.C. Anderson
Page 41
Third, IT product usage and integration with existing data centers remains complex.
Complexity has increased as customers seek to avoid lock-in with one IT product firm
which consequently has led to heterogeneous IT environments. This complexity drives
the need for more professional services and more flexible support options. With product
categories becoming less proprietary and more based on open industry standards, product
firms are well-positioned to leverage their product know-how to become legitimate
service providers for products beyond their own by either organically growing or
acquiring these service capabilities (Zollo and Winter, 2002).
Fourth, as customers have reduced their IT budgets, they have become very reluctant to
purchase new products when their current IT resources are underutilized. IT customers
are searching for ways to increase the efficiency within their existing IT environments.
This climate has spurred talk of on-demand and pay-per-use business models as an
attempt to solve the underutilization problem (Hamm, 2005). As customers become more
dependent on the benefits of IT, customers need increased levels of support service
guarantees. The need for increased system uptimes and better resource utilization
highlights the need for increased efficiency within business operations.
Fifth, professional services and customer support provide additional opportunities for the
product firm to strengthen ties with customers and increase learning about future
customer needs. While Christensen argued that firms paid too much attention to their
customers in the rigid disk drive industry, firms with diverse product portfolios appear to
be convinced of the value of customer ties and of the role of services in helping to harvest
P.C. Anderson
Page 42
that knowledge. Even Microsoft’s support group is intent on creating strong ties with
customers as articulated below from their 1994-1999 annual reports.
VII. Conclusion
Although the results are limited to a small sample of primarily large, diversified
technology firms, the empirical findings shed more light on how the services
phenomenon is playing out within a very dynamic and rapidly changing industrial setting.
This paper contributes to the strategic management and the product innovation literatures.
The dynamic capabilities literature has stirred up some great theoretical discussions over
the last decade, but the empirical studies have been few and far between. This paper
contributes to this literature by empirically showing how a dynamic capability developed
around a complementary asset (resource) during a period where firms faced radical and
incremental technological change. Within this exploratory sample of firms, we begin to
see how services are no longer peripheral but a central and growing resource base within
product-oriented firms. In a setting where product innovation is greatly rewarded, this
paper shows how a complementary asset evolved into an increasing source of strategic
and economic value. Further research is needed to test these concepts across a more
systematic sample of firms.
P.C. Anderson
Page 43
A second contribution of this paper is that it shows the heterogeneity of services beyond
the classic “maintenance and product support” function. The paper puts forth a taxonomy
by which service endowments across different types of product firms can be compared
and contrasted. In this setting, the paper argues that services should not be viewed in a
silo but rather as an architectural mix of service capabilities that exist along a productservice coupling continuum – tightly coupled, loosely coupled, and uncoupled.
Preliminary evidence suggests that services have a role to play as early as the initial
diffusion of a new technology to as late as a technology’s end of life when maintaining an
installed customer base becomes the top priority. Future product innovation research
would do well to further explore how services affect product innovation.
This paper puts forth evidence that uncovers a possible industry-wide variation in service
evolution between hardware product firms and software product firms. While the
increasing contribution from services in software product firms has been highlighted in
other work (Cusumano, 2004, Cusumano, 2008), this paper shows that service
contribution is also increasing among some hardware product firms. In addition, this
paper shows how service capabilities evolved at different rates among a sample of
hardware and software firms that were seeking to adapt to a rapidly changing business
environment. Future research should explore how this services phenomenon varies
across firm size (e.g., small, medium, and large), firm age (e.g., young, middle-aged, and
mature), and firm structure (i.e., vertically integrated vs. specialized firms).
The software product firms in this sample experienced a greater net increase in service
capabilities and a much more aggressive increase in service revenue contribution than
P.C. Anderson
Page 44
their hardware product firm counterparts. The hardware firms have a greater exposure to
the capital requirements that accompany manufacturing activities such as fixed assets and
inventories that perhaps moderated their evolutionary rate towards and reliance on
services-generated revenues. However, the models suggest that the hardware firms are
better positioned relative to overall firm performance due to more balance between
product and service revenues. Hardware firms may be forced to apply greater discipline
in product pricing and discounting unlike software firms who may feel more compelled
to offer deeper product discounts given that software products can be perfectly replicated
at near zero marginal costs (Davis, 2001). Perhaps the software firms are over extended
into services and this may highlight a weakness in firm product strategies or larger issues
unique to software industry dynamics.
A firm deep in service capabilities without a healthy product innovation strategy is likely
to struggle. Service capabilities alone are not a silver bullet for product firms lacking a
healthy product innovation strategy as we saw large incumbents such as DEC (up to
47%), Compaq (up to 20%), and Seibel (up to 64%) stumble and become acquisition bait
between 1994 and 2006. Yet, firms such as IBM (services contribution up to 56%) and
HP (services contribution up to 20% and likely to grow much higher as it acquires EDS)
continue to increase their dependence on services in the face of technological change.
This suggests that a product firm cannot afford to fall asleep at the wheel of product
innovation. While a services business can generate value during downturns in product
sales, a greater dependence on services within product firms is likely to create a nervous
tension within the firm. If a firm’s culture, identity, and path dependency are deeply
ingrained with respect to product innovation, the rise of services is likely to not only
P.C. Anderson
Page 45
negatively affect margins, but also affect product development and product
commercialization decisions. The long-term implications of this phenomenon are not
clear as to whether this is the source of another boom within the industry or as Bill Gates
believed in 1998 a trap for firms who have grown weary from competing in an intenselycompetitive product-oriented environment.
To further enhance our understanding of services within a product innovation context,
future research is needed at a lower level of analysis than provided in this study.
Exploring how the changing mix of service capabilities affects customer retention and
financial outcomes may better inform the product strategies of firms. Research that
explores the organizational linkages between service and product organizations within
firms is likely to reveal greater insights on how knowledge flows between these
symbiotic entities affect product development, commercialization, and maintenance
activities.
Perhaps the rise in service revenue contribution and in service capabilities among this
sample of firms is a small indicator of a larger shift in IT product firms. While hardware
and software product categories are becoming increasingly more commoditized, this
alone is not sufficient to explain an increased emphasis on services by product firms. On
one hand, perhaps this is a sign of a mature albeit fast-moving industry characterized by
rapid incremental innovations. Much depends on the level of analysis by which one
searches for a dominant design. On the other hand, perhaps the rise of services signals a
new technological era – one in which customers familiar with digital goods are drowning
in a sea of complexity. While commoditization will produce lower prices, the complex
P.C. Anderson
Page 46
integration of multiple devices, access points, and massive data is likely to continue to
attract a larger role for services from product firms.
P.C. Anderson
Page 47
Appendix 1 – Figures and Tables
Figure 1. Product - Service coupling continuum.
Services
Products
Tightly
Coupled
Loosely
Coupled
Uncoupled
Figure 2. Services taxonomy in product firms.
P.C. Anderson
Page 48
Figure 3. Qualitative measures of service capabilities breadth and depth.
P.C. Anderson
Page 49
Figure 4. Evolution of service capabilities breadth.
(4a) Average number of service capabilities in a given year
(4b) Average number of professional services
P.C. Anderson
(4c) Average number of business model services
Page 50
Figure 5. Product and service revenue contribution between 1994 and 2006.
(5a) Averaged across all firms in the sample
(5b) Hardware firms only
P.C. Anderson
(5c) Software firms only
Page 51
Figure 6. Service contribution relative to product sales.
(6a) Averaged across all firms in the sample
(6b) Hardware firms only
P.C. Anderson
(6c) Software firms only
Page 52
Table 1. IT product firms.
Hardware firms
Software firms
Firm
SIC
code
Compaq
DEC
Dell
HP
IBM
SGI
Sun Microsystems
EMC
NCR
Avaya
Cisco
3571
3571
3571
3571
3571
3571
3571
3572
3578
3661
3669
Firm
BEA
BMC
CA
Intuit
Microsoft
Novell
Oracle
Red Hat
SAP
Siebel
Symantec
SIC
code
7372
7372
7372
7372
7372
7372
7372
7370
7372
7372
7372
Table 3. t tests of means by firm type
Variable
Firm age (years)
Firm size (log employees)
R&D spending (%)
Revenue from US sales (%)
Revenue from product sales (%)
Revenue from sales of services (%)
P.C. Anderson
H/w Firm
Mean
S/w Firm
Mean
38.58
10.38
8.06
52.60
74.69
25.31
19.07
8.81
16.40
61.57
54.21
45.71
Alternative
Hypothesis
Phw !=
Phw !=
Phw !=
Phw !=
Phw !=
Phw !=
Psw
Psw
Psw
Psw
Psw
Psw
t test
Significance
0.001
0.001
0.001
0.001
0.001
0.001
Page 53
MOVED FROM TEXT INTO THE APPENDIX DUE TO SMALL SAMPLE SIZE
Table 4 contains six firm fixed-effects models that explore the relationship between
services contribution and operating income. In models 1 and 2, the services contribution
variables provide no significant effect on operating income (R-squared = 0.00). Once the
controls for firm size and age are added, the model improves (R-squared = 0.19) and the
services contribution variables are significant at the 0.001 and 0.05 levels. Most of the
within firm variation is likely explained by the addition of the age variable which is
positive and significant at the 0.001 level. Including all firm and industry controls in
models 5 and 6 provide similar results as in model 4 with only a marginal increase in
within firm variation (R-squared = 0.22). Models 4-6 suggest that services contribution
has a negative and significant effect on operating income up until 66% of total sales and
then it subsequently has a positive effect on operating income. Although a firm is likely
to prefer high-margin maintenance revenues, a services contribution beyond 20% is likely
to come from a considerable investment in professional services and business model
services. Since professional services are typically more customized (Cusumano, Kahl
and Suarez, Forthcoming)and related to know-how (von Hippel, 1994) which
accumulates over time, the initial negative magnitude of services contribution followed
by a positive effect seems plausible due to the ramp up in personnel. However, the
transition point of 66% seems rather high given that many of the hardware product firms
have survived with lower levels of service revenue contributions.
______________________________
Table 4. Firm fixed-effects models.
______________________________
P.C. Anderson
Page 54
Table 5 runs the same models but separately for hardware and software firms. Although
Figure 4 shows how software product firms are increasing their services revenue
contribution faster than hardware product firms, Table 5 suggests that services
contribution has a significant effect on the operating income of hardware firms but is not
significant for software firms. Models 1-4 suggest that services have a negative effect on
operating income up until approximately 30%, and then services have a positive effect.
Although the sample size is very small, the results seem more plausible than those from
the combined sample of Table 4.
______________________________
Table 5. Firm fixed-effects models by technology focus.
______________________________
P.C. Anderson
Page 55
P.C. Anderson
Page 56
P.C. Anderson
Page 57
References
Abernathy WJ, Utterback JM. 1978. Patterns of Industrial Innovation. Technology review
80: 40-47.
Allen TJ. 1977. Managing the flow of technology : technology transfer and the
dissemination of technological information within the R&D organization. MIT Press:
Cambridge, Mass.
Ancona DG, Caldwell DF. 1992a. Bridging the Boundary: External Activity and
Performance in Organizational Teams. Administrative Science Quarterly 37: 634-665.
Ancona DG, Caldwell DF. 1992b. Demography and Design: Predictors of New Product
Team Performance. Organization Science 3: 321-341.
Anderson P, Tushman ML. 1990. Technological Discontinuities and Dominant Designs:
A Cyclical Model of Technological Change. Administrative Science Quarterly 35: 604633.
Baldwin CY, Clark KB. 2000. Design rules. MIT Press: Cambridge, Mass.
Barras R. 1986. Towards a theory of innovation in services. Research Policy, 15: 161173.
Bourgeois III LJ, Eisenhardt KM. 1988. Strategic Decision Process in High Velocity
Environments: Four Cases in the Microcomputer Industry. Management Science 34: 816835.
Campbell-Kelly M. 2003. From airline reservations to Sonic the Hedgehog : a history of
the software industry. MIT Press: Cambridge, Mass.
Campbell-Kelly M, Aspray W. 2004. Computer : a history of the information machine.
Westview Press: Boulder, Colo.
Christensen CM. 1997. The innovator's dilemma : when new technologies cause great
firms to fail. Harvard Business School Press: Boston, Mass.
Clayton M. Christensen. 1993. The Rigid Disk Drive Industry: A History of Commercial
and Technological Turbulence. The Business History Review 67: 531-588.
Cusumano MA. 2004. The business of software : what every manager, programmer, and
entrepreneur must know to thrive and survive in good times and bad. New York: Free
Press.
P.C. Anderson
Page 58
Cusumano MA, Kahl S, Suarez F. Forthcoming. A Theory of Services in Product
Industries.
Cusumano MA. 2008. The Changing Software Business: Moving from Products to
Services. IEEE Computer 41: 20-27.
Cusumano MA, Yoffie DB. 1998. Competing on Internet time : lessons from Netscape
and its battle with Microsoft. Free Press: New York, NY.
Davis R. 2001. The Digital Dilemma. Communications of the ACM 44: 77-83.
Eisenhardt KM. 1989. Making Fast Strategic Decisions in High-Velocity Environments.
Academy of Management Journal 32: 543-576.
Eisenhardt KM, Martin JA. 2000. Dynamic Capabilities: what are They? Strategic
Management Journal 21: 1105.
Eisenhardt KM, Tabrizi BN. 1995. Accelerating Adaptive Processes: Product Innovation
in the Global Computer Industry. Administrative Science Quarterly 40: 84-110.
Fiorina C. 2006. Tough choices : a memoir. Portfolio: New York.
Flamm K. 1988. Creating the computer : government, industry, and high technology.
Brookings Institution: Washington, D.C.
Gerstner LV. 2002. Who says elephants can't dance? : inside IBM's historic turnaround.
HarperCollins Publishers: New York, NY.
Goodstadt B. 1999. Computers: Commercial Services, Industry Report. Standard &
Poor's: New York, NY.
Goodstadt, B. and Kessler, S. 1999. Computer: Software, Industry Report. Standard &
Poor's: New York, NY.
Graham-Hackett M. 1999. Computers: Hardware, Industry Report. Standard & Poor's:
New York, NY.
Hamm S. 2005. A Virtual Revolution. Business week 98.
Helfat CE, Finkelstein S, Mitchell W, Peteraf MA, Singh H, Teece DJ, Winter SG. 2007.
Dynamic capabilities : understanding strategic change in organizations. Blackwell Pub:
Malden, MA.
Henderson RM, Clark KB. 1990. Architectural Innovation: The Reconfiguration of
Existing Product Technologies and the Failure of Established Firms. Administrative
Science Quarterly 35: 9-30.
Hoffman T. 2003. Gartner survey finds continued CIO focus on cutting costs.
Computerworld 37: 13.
P.C. Anderson
Page 59
Hoffman T. 1997. Pressure is on to cut costs. Computerworld 31: 8.
Iansiti M. 1995. Technology integration: Managing technological evolution in a complex
environment. Research Policy, 24: 521-542.
Karlgaard R. 1998. The road to ruin -- services. Forbes: New York.
Kogut B, Zander U. 1992. Knowledge of the Firm, Combinative Capabilities, and the
Replication of Technology. Organization Science 3: 383-397.
Lah TE. 2005. Mastering professional services. Press Services Professional: Westerville,
OH.
Lah TE, O'Connor S, Peterson M. 2002. Building professional services the sirens' song.
Prentice Hall PTR.: Upper Saddle River, NJ.
Leonard-Barton D. 1992. Core Capabilities and Core Rigidities: A Paradox in Managing
New Product Development. Strategic Management Journal 13: 111-125.
MacCormack A, Verganti R, Iansiti M. 2001. Developing Products on "Internet Time":
The Anatomy of a Flexible Development Process. Management Science 47: 133-150.
Mollick E. 2006. Establishing Moore's Law. Annals of the History of Computing, IEEE
28: 62-75.
Nelson RR, Winter SG. 1982. An evolutionary theory of economic change. Belknap Press
of Harvard University Press: Cambridge, Mass.
Olmstead AL. 1975. The Mechanization of Reaping and Mowing in American
Agriculture, 1833-1870. The Journal of Economic History 35: 327-352.
Rosen C. 2001. The shrinking IT budget. InformationWeek 22.
Rothaermel FT. 2001. Incumbent's advantage through exploiting complementary assets
via interfirm cooperation. Strategic Management Journal 22: 687-699.
Stinchcombe AL. 1965. Social Structure and Organizations. Rand McNally: Chicago, IL.
Teece DJ, Pisano G, Shuen A. 1997. Dynamic capabilities and strategic management.
Strategic Management Journal 18: 509-533.
Teece DJ. 2007. Explicating dynamic capabilities: the nature and microfoundations of
(sustainable) enterprise performance. Strategic Management Journal 28: 1319-1350.
Teece DJ. 1986. Profiting from technological innovation: Implications for integration,
collaboration, licensing and public policy. Research Policy, 15: 285-305.
P.C. Anderson
Page 60
Tripsas M. 1997. Unraveling the process of creative destruction: Complementary assets
and incumbent survival in the typesetter industry. Strategic Management Journal 18:
119-142.
Tripsas M, Gavetti G. 2000. Capabilities, cognition, and inertia: Evidence from digital
imaging. Strategic Management Journal 21: 1147-1161.
Tushman ML, Anderson P. 1986. Technological Discontinuities and Organizational
Environments. Administrative Science Quarterly 31: 439-465.
Utterback JM, Abernathy WJ. 1975. Dynamic Model of Process and Product Innovation.
Omega-International Journal of Management Science 3: 639-656.
Utterback JM. 2006. Design-inspired innovation. World Scientiific Pub.: Hackensack,
NJ.
Utterback JM. 1994. Mastering the dynamics of innovation : how companies can seize
opportunities in the face of technological change. Harvard Business School Press:
Boston, Mass.
von Hippel E. 1994. "Sticky Information" and the Locus of Problem Solving:
Implications for Innovation. Management Science 40: 429-439.
Wernerfelt B. 1984. A Resource-based View of the Firm. Strategic Management Journal
5: 171-180.
Zollo M, Winter SG. 2002. Deliberate Learning and the Evolution of Dynamic
Capabilities. Organization Science 13: 339-351.
P.C. Anderson
Page 61