jackpot or fool’s gold: services as a dynamic...

JACKPOT OR FOOL’S GOLD: SERVICES AS A DYNAMIC CAPABILITY IN

PRODUCT INNOVATION Paper 245

Phillip C. Anderson

October 2008

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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

[email protected]

October 3, 2008


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.


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.


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:


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):


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


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.


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


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.


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 competence-

enhancing know-how and to subsequently produce incremental product innovations while


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.


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.


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.


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 third-


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


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


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, middle-aged, and mature), and firm structure (vertically integrated vs. specialized).


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, Campbell-

Kelly 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


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.


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 32-

bit, 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 EDS was a spin off from General Motors Corporation in June 1996. 4 Andersen Consulting is now known as Accenture.


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.


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. ______________________________


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 10-

K, 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.


distinguish between technical and business consulting, Figure 2 only contains a

consulting category. The goal was to create categories only when unique skills, know-

how, 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


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.


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


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


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


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.


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 firm-

year.

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.


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.


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.


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:


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 one-

stop shops of IT expertise for their customers.


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.


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


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.


______________________________

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


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


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?


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.


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


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.


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 product-

service 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


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


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 intensely-

competitive 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


integration of multiple devices, access points, and massive data is likely to continue to

attract a larger role for services from product firms.


Appendix 1 – Figures and Tables

Figure 1. Product - Service coupling continuum.

Figure 2. Services taxonomy in product firms.

Tightly Loosely Uncoupled Coupled Coupled

Products

Services


Figure 3. Qualitative measures of service capabilities breadth and depth.


Figure 4. Evolution of service capabilities breadth.

(4a) Average number of service capabilities in a given year

(4b) Average number of professional services (4c) Average number of business model services


Figure 5. Product and service revenue contribution between 1994 and 2006.

(5a) Averaged across all firms in the sample

(5b) Hardware firms only (5c) Software firms only


Figure 6. Service contribution relative to product sales.

(6a) Averaged across all firms in the sample

(6b) Hardware firms only (6c) Software firms only


Table 1. IT product firms.

Hardware firms Software firms

Firm SIC code Firm

SIC code

Compaq 3571 BEA 7372 DEC 3571 BMC 7372 Dell 3571 CA 7372 HP 3571 Intuit 7372 IBM 3571 Microsoft 7372 SGI 3571 Novell 7372 Sun Microsystems 3571 Oracle 7372 EMC 3572 Red Hat 7370 NCR 3578 SAP 7372 Avaya 3661 Siebel 7372 Cisco 3669 Symantec 7372

Table 3. t tests of means by firm type

Variable H/w Firm

Mean S/w Firm

Mean Alternative Hypothesis

t test Significance

Firm age (years) 38.58 19.07 Phw != Psw 0.001 Firm size (log employees) 10.38 8.81 Phw != Psw 0.001

R&D spending (%) 8.06 16.40 Phw != Psw 0.001 Revenue from US sales (%) 52.60 61.57 Phw != Psw 0.001

Revenue from product sales (%) 74.69 54.21 Phw != Psw 0.001 Revenue from sales of services (%) 25.31 45.71 Phw != Psw 0.001


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. ______________________________


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. ______________________________


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