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The Complementarity of Industry-level vs. Firm-level Factors Leading to Consolidation in the ERP Industry

The Complementarity of Industry-level vs. Firm-level Factors Leading to
Consolidation in the ERP Industry

Introduction

Three firms control now 43% of the enterprise software applications market, whose growing
revenue is projected by Gartner to surpass $253.7 billion in 2011.1 This level of industry
concentration is part of an ongoing trend that characterizes the declining stage in an industry
lifecycle model (Porter 1980). As such, the research opportunity is to build a formal model to
explain the industry factors leading up to such high levels of concentration, while being able to
capture firm level strategies as well. Moreover, given the magnitude of change in a relatively
short period of time in this industry, the transformation that is still going on makes for a quasi-
natural experiment, whereby the researcher can test theory driven hypotheses.

It is my objective in undertaking this work to build a testable model that answers the following
research question: What are the industry-level vs. firm-level factors leading to industry
consolidation in the enterprise software applications industry? The immediate contribution
would be to establish conceptual and methodological linkages between industry and firm level
factors leading up to consolidation higher concentration. In other words, a potential contribution
is to expose the often-ignored ‘conduct’ part in the structure-conduct-performance paradigm. At
a later stage, the model is to be tested not only on the focal industry herein, but also on other
industries.

The industry level working hypothesis is that a significant decrease in environmental
munificence triggers both the emergence of a dominant design, and a shakeout in the industry
(Utterback et al. 1993; Klepper et al. 2005). The emerging dominant design in the enterprise
software industry realizes platform economies—of scale, scope and skill—by vertically
integrating complementary assets (Teece 1986; Rothaermel et al. 2005). The formal model
suggests that the enterprise software applications market tends to settle towards the Bertrand
equilibrium around the marginal cost of the most efficient player.

In this work I will employ a mix of qualitative and quantitative methods. More precisely, a
stylized history of the enterprise software applications industry is used as stage for deriving the
hypotheses and building the formal model.
In the next section, I will explain the research setting by familiarizing the reader with the
enterprise software applications industry in broad terms. Next, industry-, and firm-level theories

1
Gartner is one of the top information technology groups of industry analysts. The source of this quotation is at:
http://www.gartner.com/it/page.jsp?id=1535314

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explaining industry evolution amid discontinuities are reviewed with the idea of suggesting
testable hypotheses and building the model along the stylized history of the industry.

Research Setting: Background and Data Collection
The object of this exploratory investigation is the enterprise software industry, and the factors
and conditions leading to its consolidation.2 A measure of this industry change is given by a
survey revealing a decrease from 300 publicly traded enterprise software firms in 1997, to 111 in
2006 (Cusumano 2008).3

The gross margins in this industry can theoretically be as high as 99%, assuming that the
marginal cost of an additional copy of the software is zero. This feature would make this
industry a candidate for the very high scale economies associated with monopolies, yet there is
no consensus about this among economists (Baumol et al. 2008).4 The top firms by market share
are SAP, Oracle and Microsoft, and their cumulative enterprise software market share was 43%
in 2010.5 It should be also noted that SAP has grown organically into a complete solution, that
is, its applications supporting different business processes could interoperate by design. On the
other hand, Oracle and Microsoft started as vendors of database and operating system solutions,
respectively, and have grown through acquisitions into complete enterprise software architecture
providers. These top tier enterprise software firms target large Global 1000, multi-location and
multi-national firms, whose complex operations require complex implementations interfacing
with multiple systems. The target firms are characterized by the number of users, from 60 to
over 1000, the number of employees, over 2000, and the annual revenues, in excess of $250
million. A firm spends on a top tier enterprise software package more than $750,000 and an
additional amount, 3 to 10 times higher, on implementation.6

According to Gartner, enterprise software consists of:
Software products designed to integrate computer systems that run all phases of an
enterprise’s operations to facilitate cooperation and coordination of work across the
enterprise. The intent is to integrate core business processes (e.g., sales, accounting,
finance, human resources, inventory and manufacturing). The ideal enterprise system
2
Throughout this paper, enterprise software applications and enterprise resource planning (ERP) are used
interchangeably.
3
This comprehensive industry survey covered those firms selling “services-prepackaged software,” listed under US
Standard Industrial Classification (SIC) code 7372, from 1990 to 2006.
4
The authors raise the open question of whether or not the software industry is a natural monopoly (ibid. p. 222).
The implication of an affirmative answer would then be a natural tendency towards industry concentration, which in
turn would render the research question as trivial. However, the answer is not always trivial, especially in an
industry where technological change is going apace. This discussion will continue later within the context of
platform economies.
5
See Annex 1 for the exact breakdown.
6
http://www.softresources.com/software-market-overview SoftResources is the former IT practice of KPMG Peat
Marwick.

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could control all major business processes in real time via a single software architecture
on a client/server platform. Enterprise software is expanding its scope to link the
enterprise with suppliers, business partners and customers.7

From a technology perspective, the single software architecture in the above definition ought to
be visualized as a vertical stack whose top layer consists of several isolated software
applications, each supporting a core business process, and often sold by a different vendor; the
next layer down consists of middleware software, which abstracts the application layer from the
operating system and hardware layers at the bottom of the stack. The enterprise applications are
segmented by the type of core business process supported, as follows: enterprise management,
human capital management, supply chain management, product lifecycle management, customer
management, and sourcing and procurement (Jacobson et al. 2007). These segments are relevant
to this analysis from a couple of perspectives.

First, applications are the result of an evolutionary process in the supply and demand. An
enterprise application, such as customer resource management, is just one among several that
require integration services to interoperate. This is a process fraught with risk that is correlated
with the number of different application segments or modules (Davenport 1998).8

Second, when successfully integrated in an organizations, these applications automate and
integrate business processes, share common data and practices, and produce and access
information in real-time (Markus et al. 2000). The functional integration among the top
applications is achieved by virtue of a database, which normalizes and synchronizes the data
flows among the applications at the top layer (Davenport 1998)—see Annex 2 for a diagram
illustrating the central position of the database in an enterprise software system.

Theory
In this section we look at industry level factors followed by firm level factors, which together
can help explain the transformation in the enterprise software applications industry, and then
assist with the formulation of hypotheses. The industry level factors are environment
munificence, industry shakeouts and dominant design. The firm level factors are complementary
assets and platform economies.

Environmental munificence
Environmental munificence, defined as the “scarcity or abundance of critical resources needed
by (one or more) firms operating within an environment,” determines firm growth and survival

7
http://www.gartner.com/technology/research/it-glossary/
8
An idea of the risk of implementing enterprise software systems is given by the 40-60% rate of failure estimated by
several industry analysts. A compilation is available at: http://www.it-cortex.com/Stat_Failure_Rate.htm

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(Dess et al. 1984; Castrogiovanni 1991). The so defined resources can be any exogenous factors
that influence a group of firms in aggregate, e.g., availability of capital, customer markets, and
labor unions. In a theoretical work on environmental munificence, Castrogiovanni (1991) argues
that it is at this level of analysis that industries ought to be studied. Moreover, Porter’s (1980)
model of external forces operationalizes the effects of environmental munificence on firms’
strategy and performance at this same level in terms of concentration of market power, entry
barriers, changes in demand, or changes in product characteristics. The general idea of topical
relevance is that when these types of resources become scarce, the range of strategic options for
firms in the focal industry decreases, and industry-level competition intensifies (Dess et al. 1984;
Tushman et al. 1986).

Industry shakeout & Dominant design
In many industries, the transition from the growth stage to maturity is marked by an increase
followed by a sharp decrease in the number of firms in a process called industry shakeout
(Klepper et al. 2005). Being such a consequential transformation, there are several theories
dealing with shakeout as research artifact, yet this research looks specifically for insights into the
post-shakeout period. Among the variety of theoretical accounts, there has been a long line of
organizational change models whose explanations fit the shakeout pattern in the enterprise
software applications industry. This body of research, based on empirical and analytical studies
done across several industries, points to the shakeout of firms just as a dominant design emerges
in the industry from the interplay between technical and market choices (Utterback et al. 1993;
Agarwal 1998; Klepper et al. 2005). Utterback and Abernathy defined the concept of dominant
[product] design and attributed to it the standardization followed by complementary and scale
economies in the focal industry (1975). In closing, it should be mentioned that Utterback and
Suarez empirically showed that industry concentration round dominant design follows shakeout
in several American industries (1993).9

Complementary assets
Before examining the relevant works in these streams of literature, I should make the reader
aware of the change in the unit of analysis. We are moving down at firm level, yet given the
market share of the leaders in the enterprise software applications industry, the implications
become consequential at industry level.

Teece defines complementary assets that are specialized as those necessary to the successful
commercialization of [technical] innovations (1986). At about the same time, Tushman and
Anderson distinguish two major [technological] shifts, competence-destroying vs. competence-
enhancing, relative to their respective effects on the incumbent firms in an industry (1986).
Rothaermel and Hill combine these two insights and show that, following a competence-

9
Their model could not be verified by the integrated circuits industry at that time.

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destroying technological discontinuity across four industries, the position of the incumbent
firm(s) is strengthened if the complementary assets it owns are specialized (2005).

Platform economies
The second firm level phenomenon of relevance to this work is the platform defined by
Bresnahan and Greenstein as “a bundle of standard components around which buyers and sellers
coordinate efforts” (1999). These authors make their case around the IBM System/360 and show
that in the computer industry the competition takes place between platforms and not firms (ibid.).
The multi-sided networks or markets are a special case of platforms, in which an increase in one
kind of membership increases the value of a complementary product to another distinct kind of
membership. Rochet and Tirole are among the first to have studied two-sided markets by
looking at the credit card two-sided network of buyers and sellers, and showing that an optimal
pricing strategy subsidizes one side of the market, as in increased adoption and growth in use by
buyers, by increased revenue from the other side of the market, as in sellers accepting credit card
payments (2003). In the software industry in general, and the enterprise software applications in
particular, certain technologies such as operating systems, or databases, are platforms enjoying
the economies of multi-sided markets (Rochet et al. 2003). These are coordinators of demands
from two or more types of customers.

Method
The game-theoretical approach in the industrial organization literature has introduced and
legitimized the use of time as a variable. Sutton makes a compelling theoretical case for the use
of history at the intersection with economics in the better explain the business phenomena in the
following terms:

An approach which seeks to characterize the range of feasible scenarios which are possible in a
given environment, while retaining the richness and depth of understanding which can only come
from a detailed historical analysis (1994).

An example of such work is Malerba and colleagues’(1999); they generate an ‘history-friendly’
formal model to “capture, in stylized form, qualitative and ‘appreciative’ theories about the
mechanisms and factors affecting [the computer] industry evolution” (ibid.).

The current work uses a stylized history of the enterprise software applications industry to
generate the hypotheses and build a model explaining the factors driving the industry evolution
in its increasing concentration stage.

For future empirical research based on inferential statistics, it should be mentioned that for the
ERP industry the starting point is the Industry Sector under SIC Code: 7372, from which the
software games developers will be ignored.10 Then Standard & Poor’s COMPUSTAT data will

10
See Annex 3 for a complete description of this sector

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be available. Moreover, for contrasts between the focal industry and other industries, whether or
not the latter exhibit platform economies, random sampling of firms within compare and contrast
industries can be employed. This way, relations between the ERP and other industries can be
explored and explained. For example, industries may exhibit different rates of consolidation, or
concentration despite undergoing the same environmental stress as the focal industry. In such
case, a lifecycle argument can be made in each case.

The Evolution of Enterprise Software Applications Industry
To survey the history of the enterprise software industry, Porter’s four-stage industry cycle is a
natural guide (1980). The four stages in the industry lifecycle according to this model are
introduction, growth, maturity and decline (Porter 1980:161). In the growth stage there are many
firms competing on price; in the maturity stage, the competition is even more intense and a
shakeout of firms is likely to lead to the lowest prices and margins throughout the life cycle; in
the decline stage, the number of firms drops and the price and profit margins are pushed down.

For a stylized history of the focal industry, data is adapted from the history of enterprise resource
planning by Jacobs and Weston (2007), and public sources about the key individual firms, e.g.,
SAP and Oracle.

Introduction
Enterprise software applications came into being as result the need to integrate functional silos,
the dominant technology paradigm promoted by IBM. In 1976 and 1977, SAP, developer of
standard software for integrated business solutions, and Oracle, developer of the first commercial
relational database, were founded to achieve data integration at firm level. The first milestone of
the nascent industry was reached in 1978, when SAP released R/2, the integrated version of its
software allowing for interactivity between application modules. From its release, R/2 had been
designed to work with Oracle’s database as complements.11 In 1985, PeopleSoft was founded
and by the end of the 1980s it released the first fully integrated human resource management
system solution. In 1987, Oracle founded its Applications division to build business
management software closely integrated with its database software; in 1988, it released its first
ERP application, an accounting system. By the end of the 1980s, all the major enterprise
software application vendors had come into being (Jacobs et al. 2007).

Growth
In the early 1990s, with the coinage of the term ERP by Gartner, the enterprise software
applications industry enters its growth stage. The growth of the industry throughout the 1990s
11
http://www.oracle.com/us/solutions/sap/database/index.html

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had been carried on the wings of business globalization and the technological shift in computing
architectures, from the IBM mainframe to client-server, and later internet, architectures. By
1999, the dominant position of IBM had been eroded as the crop of enterprise software
application firms founded since the mid-1970s controlled much of the ERP software market
(Jacobs et al. 2007). A measure of the growth period is also the peak in the number of publicly
traded firms developing enterprise software applications, reached in 1997 (Cusumano 2008), see
Figure 1. Jacobs and Watson identify the year 2000 (or Y2K) problem first as a growth factor,
then as a marker of the upcoming consolidation in the enterprise software application industry
(2007).

Fiure 1. The lifecycle of the publicly traded enterprise software application firms,
from 300 publicly traded enterprise software firms in 1997, there are only 111 in 2006
(Cusumano 2008), and the trend continues.

Maturity
Jacobs and Watson posit that Y2K was “the single ‘event’ that signaled both the maturing of the
ERP industry and the consolidation of large and small vendors,” whose effects had been
accelerated, beginning in 2000, by the crash on the March 11 of the technology stock market
(2007). Cusumano adds to these factors the diffusion of open source software as another
contributor to the maturation of the enterprise software applications industry. All these point to
environmental pressures to downsize and/or become more efficient. These lead to the
formulation of the first two hypotheses:

• H1: Sudden decrease in environment munificence leads to industry shakeout
(Utterback & Suarez 1993; Klepper & Simons 2005).
• H2: Triggered by the shakeout, the dominant design in the focal industry emerges
around platform economies (Teece 1986; Rothaermel & Hill 2005; Evans et al. 2007).

The dominant design in the ERP industry is round Oracle database technology. Indeed,
enterprise customers, wanting to take advantage of vertical enterprise software applications or
modules, would need to integrate these applications, and the database is the integration platform
(Davenport 1998; Markus et al. 2000). The first hypothesis above should test the effects of the
post-2000 shakeout against what seems from Figure 1 to be a case of industry lifecycle decline.
In order to test the second hypothesis, a trending change in an industry concentration index, e.g.,
Herfindahl-Hershman Index, along with an increase in Oracle market share should be observed.

For a qualitative view of the ERP industry shakeout in this period, a vignette describing the
convulsions of two market leaders in vertical enterprise software applications, before being
acquired by Oracle in 2005, is included in Annex 4.

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Decline
Given the technical and functional requirements for integration of the enterprise software
applications, we can observe that databases, middleware and operating system pieces of software
are complementary product extensions of the application software pieces, and vertical mergers
are likely to occur (Shy 1995).12 In 2005, Oracle, major database player in the enterprise
software market, and theoretical candidate for dominant design, begins to acquire firms in its
industry at an unprecedented intensity. Annex 5 is a graphical illustration of the type and size of
firms Oracle has acquired since 2005—more than 50 firms worth more than $50Bn. According
to the industrial organization literature, Oracle’s database is a multi-sided platform (Evans et al.
2004). This leads to the formulation of an analytical hypothesis that suggests a model of
equilibrium for the ERP industry:

• H3: The ERP market tends to settle towards the Bertrand equilibrium as determined
by the marginal cost of the most efficient player, provided that there is no collusion.

A graphic with the equilibrium line in monopolistic competition is included to place the Bertrand
equilibrium in context.

Market equilibrium under imperfect competition can occur at many points on the demand curve. In this
figure, which assumes that marginal costs are constant over all output ranges, the equilibrium of the
Bertrand game occurs at point C, also corresponding to the perfectly competitive outcome. The perfect-
cartel outcome occurs at point M, also corresponding to the monopoly outcome. Many solutions may
occur between points M and C, depending on the specific assumptions made about how firms compete.
For example, the equilibrium of the Cournot game might occur at a point such as A. The deadweight loss
given by the shaded triangle is increasing as one moves from point C to M (Nicholson et al.).

12
“Product extension: The acquiring and acquired firms are functionally related in production or distribution.
Vertical mergers occur “when a firm producing an intermediate good merges with a firm producing the final good,
or when two companies who have a potential buyer-seller relationship prior to a merger merge” (ibid. p. 173-4).

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In our case, Oracle’s dominant design derived from its platform economies affords it lower
marginal costs than the firms that need to integrate their applications through its database. This
is indeed a case when the strategy of a single firm, provided that it has leveraged its dominant
design into a market leadership position, determines performance at industry levels. Oracle
commands indeed 19% of the ERP market, in a trend that is pushing upwards.

Two observations are necessary at this time. For the time being, there are no signs of anti-
competitive behavior between the market leaders in the ERP industry. Indeed, both Oracle and
SAP have in place migration programs whereby customers of their competitor are incentivized to
switch. Then, in 2008, SAP tried to raise the cost of its maintenance contracts, yet it had to give
up by 2010 due to customer opposition.13 These two observations point out the fact that, for the
time being, absent anti-competitive behavior, the ERP industry is headed towards a Bertrand
equilibrium characterizing competitive markets, despite the market power of the three firms at
the top.

Conclusion
We have seen that in the case of the ERP industry, shakeout was the major discontinuity that
worked as competence-enhancing event, which in turn has led to the emergence of Oracle’s
database technology as a dominant design based on platform economies (Rothaermel et al.
2005).

The contribution of this work is in bringing together a mix of methods to generate testable
hypotheses and a model of equilibrium in an industry.

The future research potential for this work consists of testing the hypotheses and comparing and
contrasting its explanatory power across several industries.

13
http://www.computerworlduk.com/news/it-business/10632/sap-faces-user-wrath-over-price-hikes/

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Agarwal, R. (1998). "Evolutionary trends of industry variables." International Journal of Industrial
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Baumol, W. J. and A. S. Blinder (2008). Economics: Principles and Policy, South-Western College Pub.
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Castrogiovanni, G. J. (1991). Environmental Munificence: A Theoretical Assessment, Academy of
Management. 16: 542-565.
Cusumano, M. A. (2008). "Changing software business: Moving from products to services." Computer
41(1): 20-+.
Davenport, T. H. (1998). "Putting the enterprise into the enterprise system. (information integration)
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Dess, G. G. and D. W. Beard (1984). "Dimensions of Organizational Task Environments." Administrative
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of Operations Management 25(2): 357-363.
Jacobson, S., J. Shepherd, M. D'Acquila and K. Carter (2007). The ERP Market Sizing Report, 2006-2011.
Boston MA, AMR Research.
Klepper, S. and K. L. Simons (2005). "Industry shakeouts and technological change." International Journal
of Industrial Organization 23(1-2): 23-43.
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the computer industry." Industrial & Corporate Change 8(1): 3.
Markus, M. L., S. Axline, D. Petrie and C. Tanis (2000). "Learning from adopters' experiences with ERP:
problems encountered and success achieved." Journal of Information Technology 15(4):
245-265.
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Porter, M. E. (1980). Competitive Strategy. New York, Free Press.
Rochet, J.-C. and J. Tirole (2003). "Platform Competition in Two-Sided Markets." Journal of the European
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Rothaermel, F. T. and C. W. L. Hill (2005). "Technological Discontinuities and Complementary Assets: A
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Shy, O. (1995). Indutrial Organization, Theory and Applications. Cambridge MA, MIT Press.
Sutton, J. (1994). "History Matters. So What?" Journal of the Economics of Business 1(1): 41-44.
Teece, D. J. (1986). "PROFITING FROM TECHNOLOGICAL INNOVATION - IMPLICATIONS FOR
INTEGRATION, COLLABORATION, LICENSING AND PUBLIC-POLICY." Research Policy 15(6):
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Tushman, M. L. and P. Anderson (1986). "Technological Discontinuities and Organizational
Environments." Administrative Science Quarterly 31(3): 439-465.
Utterback, J. M. and W. J. Abernathy (1975). "DYNAMIC MODEL OF PROCESS AND PRODUCT
INNOVATION." Omega-International Journal of Management Science 3(6): 639-656.
Utterback, J. M. and F. F. Suarez (1993). "INNOVATION, COMPETITION, AND INDUSTRY STRUCTURE."
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Annex 1: Example of Top Vendors in the Enterprise Software Market, Their Market Share and
Revenue

Source: http://whatiserp.net/erp-report/erp-market-share-and-vendor-evaluation-2011/

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Annex 2: “At the heart of an enterprise system is a central database that draws data from and feeds data
into a series of applications supporting diverse company functions. Using a single database dramatically
streamlines the flow of information throughout a business” (Davenport 1998).

Annex 3: Description of the Industry Sector under SIC Code: 7372 (Prepackaged Software)

Establishments primarily engaged in the design, development, and production of prepackaged
computer software. Important products of this industry include operating, utility, and
applications programs. Establishments of this industry may also provide services such as
preparation of software documentation for the user-installation of software for the user; and
training the user in the use of the software. Establishments primarily engaged in providing
preparation of computer software documentation and installation of software on a contract or fee
basis are classified in Industry 7379, and those engaged in training users in the use of computer
software are classified in Industry 8243. Establishments primarily engaged in buying and selling
prepackaged computer software are classified in Trade; those providing custom computer

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programming services are classified in Industry 7371; and those developing custom computer
integrated systems are classified in Industry 7373.
• Applications software, computer prepackaged
• Computer software publishers, prepackaged
• Games, computer software: prepackaged
• Operating systems software, computer: prepackaged
• Software, computer: prepackaged
• Utility software, computer: prepackaged

Source: http://www.osha.gov/pls/imis/sic_manual.display?id=149&tab=description

Annex 4: The convulsions of two ERP vendors during the industry shakeout and prior to their
being acquired by Oracle (Jacobs et al. 2007).

Our interview with Rick Allen, the former Executive Vice President of Finance and Administration and member of
the J.D. Edward’s Board of Directors during the PeopleSoft acquisition of J.D. Edwards, offered insight into the
consolidations that occurred during this period.
In 2002 the major players in order of size were SAP, Oracle, PeopleSoft and J.D.Edwards; Baan had fallen out by
this time. Allen indicated that, at this time, J.D. Edwards had performed extensive analyses of options for growing
the business. These options included acquisitions of competing companies, mergers, or securing additional financing
for developing new products. Although there were earlier meetings, a major event occurred on 31 October 2002
when Craig Conway, President and CEO of PeopleSoft, contacted Bob Dukowsky, CEO of J.D. Edwards
concerning potentially serious talks about merging the two companies.
Allen reported that the merger looked attractive from a number of points of view. First, the software products were
complementary: J.D. Edwards’s products were stronger in manufacturing, accounting and finance while PeopleSoft
was very strong in human resources products. Second, there was very little overlap in their software offerings.
Further, the merged company could offer a much more complete software portfolio to the combined set of
customers. Finally, the two companies could see that the merger would result in a company that was larger than
Oracle, their major competitor along with SAP.
The PeopleSoft/J.D. Edwards merger was announced on 2 June 2003. On Friday of the same week (6 June 2003), in
a great surprise to the industry, Oracle announced a hostile takeover bid for PeopleSoft. Rick Snow, the Chief Legal
Counsel J.D. Edwards has vivid recollections of this period—including a 6 a.m. phone call on 6 June 2003 from
Rick Allen, then J.D. Edwards’ VP of Finance. Snow recalls this period with the following:
‘‘Rick [Allen] said, ‘Get hold of the lawyers. We’ve got a problem.’ The way that we found out was Bob Dukowsky
[J.D. Edwards CEO] was watching CNBC and saw the announcement that Oracle was starting their hostile takeover
of the combined companies. So Rick called me, I called the partner of <law firm> and got him out of bed on Friday
morning. We all met the following Monday . . . . . . We still had not closed with PeopleSoft and now all the talk was
about this additional issue. So again, the attorneys and the investment bankers, plus the management of J.D.
Edwards, all met and started trying to figure out how we should proceed in light of this addition of Oracle into the
picture.’’
The two companies modified their agreement allowing them to close the deal in August 2003, earlier than originally
scheduled. This allowed the combined company to focus their attention on Oracle. The Oracle takeover bid raised
significant anti-trust questions both in the United States and in Europe. The takeover was finally consummated in
January 2005. This merger has left the industry with two major players Oracle and SAP but with the software
capabilities of the five original players.

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Annex 5: The list of software firms acquired by Oracle since 2005.

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