Enterprise-Level IS Research:

Challenges and Potentials of Looking Beyond Enterprise Solutions

Robert Winter

Institute of Information Management, University of St. Gallen, Mueller-Friedberg-Str. 8, 9000 St. Gallen, Switzerland

Keywords: Enterprise Systems, Enterprise Level of Analysis, Information Systems Management, Information Systems

Complexity, Information Systems Coordination, Information Systems Governance.

Abstract: For more than 40 years, enterprise solutions, specifically enterprise systems, allowed companies to integrate

enterprises’ operations throughout. Starting with integrating core operational functions, the integration scope

of enterprise solutions has increasingly widened, now often covering customer activities, activities along

supply chains, and business analytics. IS research has contributed a wide range of explanatory and design

knowledge dealing with this class of IS. During the last two decades, however, not only technological

innovations, but also managerial / organizational innovations not only extend the affordances of enterprise

solutions, but also challenge traditional approaches to their design and coordination. Particularly in large

enterprises or complex business ecosystems, many IT/business alignment issues have not yet been

fundamentally addressed, and novel, more decentralized (aka agile) forms of coordination have not yet been

integrated with mainstream IS design and management practice. At the same time, IS complexity is not

harnessed at all, and is increasingly threatening to impose limits to IS efficiency and flexibility gains. This

position paper presents a cross-solution (= enterprise-level) perspective on IS, discusses the challenges of

complexity and coordination for IS design and management, presents selected enterprise-level insights for IS

coordination and governance, and explores avenues towards a more comprehensive body of knowledge on

this important level of analysis.

1 INTRODUCTION

The history of enterprise systems can be traced back

to the 1970ies. In the beginning, the integration scope

was limited to a functional domain such as production

planning, invoicing, payroll processing, or inventory

management. Since functional integration cannot

provide efficient support for cross-functional, end to

end business processes (e.g., order-to-cash), the

1990ies brought a wide adoption of integrated

enterprise systems as core component of corporate IT

(Scheer & Schneider, 2005). Process-oriented

enterprise systems facilitate cooperation and

coordination of work across functional and

organizational silos, thereby enabling significant

efficacy and efficiency gains. Extending integration

scope and leveraging such gains, later not only

internal operative functions were integrated, but also

customer activities and activities of partners along

supply chains (Österle et al., 2001). Modern

https://orcid.org/0000-0001-9383-2276

Enterprise Systems (e.g., SAP S/4 Hana) go even

further by integrating operational functions of the

‘extended enterprise’ with advanced business

analytics. Figure 1 illustrates the principle of

integration, the common denominator of all evolution

stages of traditional enterprise systems.

IS research has contributed a wide range of

explanatory and design knowledge dealing with

enterprise systems. During the last two decades,

however, this (predominantly integration and

adoption related) knowledge has been challenged not

only by technological, but also by organizational

innovations. On the technology side, cloud computing

can enable easier and more flexible integration of

functionalities across solutions, platforms, and / or

vendors (Maliza Salleh et al., 2012). Digital

innovation platforms (e.g., the Salesforce platform)

enable to use customized complex services (of the

platform core and complementors) without having to

deal with their integration (Staub et al., 2021). On the

Winter, R.

Enterprise-Level IS Research: Challenges and Potentials of Looking Beyond Enterprise Solutions.

DOI: 10.5220/0012078800003467

In Proceedings of the 25th International Conference on Enterprise Information Systems (ICEIS 2023) - Volume 2, pages 9-14

ISBN: 978-989-758-648-4; ISSN: 2184-4992

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

managerial side, decentralized control approaches

(e.g., agile operations and agile development) not

only influence the way organisations are structured,

but also allow faster changes and concurrent

variations of processes and supporting systems. The

new ‘ecosystem’ level of management creates new

integration affordances, but also induces a higher

heterogeneity of data and supporting systems.

Figure 1: Integration Principle of enterprise systems (Murer

et al., 2010, p. 127).

Over almost 50 years, the enterprise systems

journey enabled ever increasing opportunities for

efficacy and efficiency gains. The integration scope

extended from function to process to ‘extended

enterprise’ to ecosystem, while successively adding

conceptual integration layers such as a shared

operational data layer, a workflow management layer,

an infrastructure integration layer, or a business

networking layer. Not only computational power and

digital proficiency in companies exploded over this

long period, but also did enterprise system

complexity - and thus IS complexity in general. Since

many fundamental issues of IT/Business alignment

seem to have not been fundamentally addressed yet

(Luftman et al., 2013), complexity and governance

challenges may increasingly impose limitations to the

current and future efficacy and efficiency gains of

enterprise integration. A more holistic, truly

perspective “beyond enterprise systems” would allow

for IS insights and designs that help to continue the

success story.

2 THE ENTERPRISE LEVEL

Before discussing challenges for IS design and

management and avenues towards a more

comprehensive body of knowledge on the enterprise-

level of IS research, we need to specify how the

enterprise-level differs from other levels of analysis

and how enterprise-level IS themes relate to existing

IS discourses.

If IT/Business alignment and integration are

considered to be essential perspectives for

understanding and designing enterprise systems (and

their interplay), the enterprise-level of analysis should

include primarily concepts that (1) link business

aspects to IT aspects and (2) are significant enough to

be relevant on this ‘global’ level of analysis (i.e., are

relevant beyond ‘local’ IS views by individuals,

workgroups, functions, projects, etc.). While a

business process, a software system, an

organizational role or a business function are

certainly relevant on other levels of analysis, they

serve only as references on the enterprise level. The

most relevant concepts on this level are (A) how

software functionalities are used or could support

business activities and (B) which functional

capabilities are relevant to run the business – and thus

need to be supported by organizational as well as

business technology (usually IT) solutions. Since in

complex organizations, thousands of business

activities, software functionalities and functional

capabilities exist (with a magnitude more

interrelationships and references to business and

technology concepts), multi-level aggregate views

need to be established to keep enterprise-level models

accessible to humans and to support ‘architectural’

coordination – in line with TOGAF’s definition of

enterprise architecture that focuses on “fundamental”

components, their inter-relationships, and the

principles and guidelines governing their design and

evolution over time.“ (The Open Group, 2022).

Figure 2: Principle of alignment models (Aier & Winter,

2009, p. 4).

ICEIS 2023 - 25th International Conference on Enterprise Information Systems

Based on general systems theory and in analogy

to design theories from Computer Science, Aier and

Winter (2009) proposed “alignment” architecture

concepts that (1) represent interdependencies

between business and technology concepts and (2)

can be aggregated to global models that are accessible

for humans (Figure 2). They differentiate for aspect

(A) “applications” as clusters of links that represent

software support of business activities and (B)

“capabilities” as aggregates of elementary

capabilities. Capabilities constitute a common

language for business concepts (e.g., activities) on the

one side, and IT concepts (e.g., supporting IT

functionalities) on the other. While the aggregation of

applications is determined by the integration scope of

respective enterprise systems, the aggregation of

capabilities is based on their semantic closeness.

In practice, enterprise-level models of

applications and enterprise-models of capabilities are

frequently used in the context of Enterprise

Architecture Management. Figure 3 illustrates how

the references of an application architecture model to

business concepts (in “business architecture” model)

and IT concepts (in “infrastructure architecture”

model) can be used to analyse and improve

IT/Business alignment.

Figure 3: Enterprise-level analysis – Illustrated for

application architecture (Source: Ernst, A.: Guest Lecture

“Business Engineering Navigator”, University of St.Gallen,

2013).

Based on requirements (1) and (2), the difference

between enterprise-wide analysis and enterprise-level

analysis can be defined: Enterprise-wide models

represent entities across different units of an

enterprise, but not necessarily linking business and IT

aspects. In contrast, enterprise-level models are

enterprise-wide models focusing on that linkage.

Consequently, process architecture or software

architecture models are enterprise-wide models, but

(aggregate) application architecture and capability

architecture models are enterprise-level models.

3 ENTERPRISE-LEVEL

CHALLENGES AND

EXEMPLARY APPROACHES

From the perspective (1) of IT/Business alignment

and (2) significance to the entire enterprise,

particularly the need for “architectural” coordination

and the need to harness complexity stand out. Both

challenges cannot be sufficiently approached in a

decentral way, and both challenges have significant

impact on enterprise performance. In the following,

we present exemplary approaches to deal with these

challenges from two contexts: large enterprise IS and

digital platform-based business ecosystems.

3.1 Coordination and Governance

IS components generally do not act in isolation, but

are interdependent with other IS components (Bernus

& Schmidt, 2006). Not only needs component design

to consider operational dependencies adequately, but

also any changes to a single IS component may have

unintended effects on multiple related IS components

(Mocker, 2009) – both on the same architectural layer

and on other layers.

Local business entities, such as project teams,

tend to advocate for IS solutions that fit their specific

needs and individual preferences. In contrast, global

business entities, such as strategic initiatives, aim to

improve the overall efficiency and effectiveness of

the entire IS from an overarching, organization-wide

perspective (Beese, Haki, et al., 2023). Consequently,

concurrent ‘local’ change projects and increasing

design / management autonomy lead to potentially

inconsistent or redundant solutions (Hanseth &

Lyytinen, 2010). In response to this challenge,

researchers have investigated how to better restrain

and control local change activities (Cram et al., 2016;

Wiener et al., 2016)

In practice, many organizations

employ enterprise architecture management (EAM)

for that purpose (Ross et al., 2006). While EAM

activities aim at aligning local short-term, project-

related activities with long-term, organization-wide

objectives (Sidorova & Kappelman, 2011), e.g., by

design sign-offs or architectural principles, decentral

business structures and the prioritization of local

project goals constantly create incoherencies. Large

enterprises and digital platforms serve as two themes

for illustrating how IS research can contribute to

address this challenge.

Enterprise-Level IS Research: Challenges and Potentials of Looking Beyond Enterprise Solutions

3.1.1 Large Enterprise IS

Since traditional, coercive control mechanisms for

architectural coordination appear to have reached

their peak effectivity (Winter, 2014) and more formal

control appears to be dysfunctional, clan control and

self-control have been “discovered” by EAM and,

combined with insights from digital nudging,

implemented in the form of informal coordination

interventions in large enterprises (Beese, Haki, et al.,

2023). An example is the design and evaluation of an

“architectural compliance label” that, instantiated for

a change project, indicates the level of harm that

project could create for the rest of the organization

(Schilling et al., 2019). Published enterprise-wide, it

has been shown that such labels have a coordinative

aspect as they prevent local decision makers to

deviate too much or too often from architectural

principles and guidelines.

3.1.2 Digital Platforms

In digital platform-based business ecosystems,

platform orchestrators often struggle to facilitate co-

innovation whilst simultaneously retaining control

over third-party complementors. To address this

challenge, platform owners can deploy a variety of

governance mechanisms such as platform boundary

resources (with interfaces and programming

resources as mechanisms), platform rules (with

gatekeeping, decision rights, intellectual property

sharing, pricing, revenue sharing as mechanisms) and

ecosystem identity (with relational control as

mechanism) (Staub et al., 2022). Staub et al. show

that all except two mechanisms impact both,

generativity and control, so that platform governance

requires a complex design that cannot be solely based

on a simple combination of mechanisms, but instead

needs to be based on deeper insights on how

platform/ecosystem types, platform strategies and

governance configurations relate.

3.2 Harnessing Complexity

Xia and Lee (2005) propose distinguishing structural

and dynamic, as well as technological and

organizational aspects of complexity for change

projects. Beese et al. (2023) show that this

conceptualization of complexity is also useful on the

enterprise level as it goes beyond a purely technical

view on IS architecture and also includes

organizational aspects. Complexity causes the overall

IS architecture to become difficult to maintain and

organizations struggle to flexibly respond to required

or desired changes (Schmidt & Buxmann, 2011).

Structural complexity is positively associated with

dynamic complexity, organizational complexity is

positively associated with technological complexity,

and EAM moderates the relations between

organizational complexity and technological

complexity – and thus can improve IT/Business

alignment (Beese, Haki, et al., 2023).

3.2.1 Large Enterprise IS

For large companies, Ross et al. investigate the

relation between IS governance practices and

business value, and propose a maturity development

path (Ross, 2006; Ross et al., 2006): Starting with

understanding business impacts of IT projects and

establishing IT project standards in organizations

with significant IT/Business disalignment, enterprise-

level steering bodies and the development of

enterprise-level systems constitute stage 2, along with

establishing architecture standards and project sign-

offs. On that basis, stage 3 is characterized by

enhancing integration on the business side, business

leadership of change initiatives, and establishing

architectural guidelines. In any stage, governance

practices need to be constantly adapted to changing

context, technological and organizational change, and

changing ambitions (Beese, Haki, et al., 2023). As

this enterprise-level governance process is not only

open-ended, but also implemented by a large number

of (mostly local) interventions, this process has been

appropriately designated as “managed evolution”

(Murer et al., 2010).

3.2.2 Digital Platforms

According to the theory of platform leverages

(Thomas et al., 2014), digital (innovation) platform-

based business ecosystems promise to reduce

complexity on the user side by providing mechanisms

to flexibly integrate core platform service

components with complementor’s service

components. Complexity on the user side is however

reduced at the expense of significant complexity on

of the supply side, both for platform design /

orchestration and for complementor integration.

Complexity has a pivotal role for determining the

conditions under which innovation platforms

outperform direct transactions between users and

complementors (Schmid et al., 2021). Since these

systems are relatively new objects of analysis, it has

however yet to be clarified which complexity

management mechanisms shall be applied to which

aspects of complexity in digital platforms.

ICEIS 2023 - 25th International Conference on Enterprise Information Systems

4 ENTERPRISE-LEVEL

RESEARCH DOES NOT NEED

TO BE MACROSCOPIC

The presented examples evidence that the enterprise

level of analysis not only implies specific practical

and research challenges, but also allows to develop

specific insights and designs. Looking at large,

complex systems does not necessarily enforce taking

a macroscopic perspective – like much of traditional,

descriptive IS research does. Approaches like agent-

based simulation allow to study complexity and

emergence of even large systems and derive novel

insights. An example is how agent-based simulation

of the interplay of large-scale social, business, and IT

systems yield not only novel theoretical insights how

different combinations of control intervention

influence enterprise-level IS flexibility and efficiency

(Haki et al., 2020). Such insights can also be

translated into guidelines how to deal with

complexity and emergence not only in development

teams or business processes, but also on the enterprise

level.

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