Balancing Innovation and Operations

Transcription

The Flagship of the Association of Management JOURNAL OF
MANAGEMENT SYSTEMS
THE CONTINUING MISMATCH
BETWEEN IT GOVERNANCE THEORY
AND PRACTICE: RESULTS FROM A SYSTEMATIC
LITERATURE REVIEW AND A DELPHI STUDY WITH CIO’S
Daniël Smits & Jos van Hillegersberg
WAL-MART’S LEADERSHIP IN RETAIL SUPPLY CHAIN
Seungjae Shin, Jack E. Tucci & Dustin Odom
BALANCING INNOVATION AND OPERATIONS:
OPPORTUNITIES AND CHALLENGES OF
SECOND GENERATION ENTERPRISE MOBILITY
Sabine Berghaus, Thomas Sammer, Hans Brechbühl & Andrea Back
ENRICHING ENTERPRISE DATA MODELS:
INCORPORATING ACTIVE TAXONOMIES
Peter Aiken, Long Flory & Amita Goyal Chin
VOLUME 24, NUMBER 3, 2014
ISSN 1041-2808
EDITORIAL STAFF
EDITORIAL BOARD

EDITOR-IN-CHIEF
Anil K. Aggarwal
University of Baltimore, USA
Kenneth Kendall
Rutgers University, USA
Q B. Chung
Dorothy E. Agger-Gupta
Fielding Graduate University, USA
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PeriscopeIQ, USA
JoongHo Ahn
Seoul National University, Korea
Johnny Lee
Drexel University, USA
Steven Alter
University of San Francisco, USA
Eldon Li
National Chengchi University,
Taiwan
Villanova University, USA

MANAGING EDITOR
Willem A. Hamel
Maximilian Press Publishers

FOUNDER & FOUNDING
EDITOR-IN-CHIEF
Karin Klenke
Leadership Development Institute
(LDI) International, USA

PUBLISHER
Maximilian Press Publishers
Tammy Arthur
Mississippi College, USA
Robert P. Cerveny
Florida Atlantic University, USA
Amita Goyal Chin
Virginia Commonwealth University,
USA
H. Michael Chung
California State University, Long
Beach, USA
Rashmi Malhotra
St. Joseph’s University, USA
Michael Mulvey
Dublin Institute of Technology,
Ireland
Makoto Nakayama
De Paul University, USA
Samuel Rabinowitz
Kevin D. Clark
Bonnie Roach
Ohio University, USA
Robert Giacalone
University of Denver, USA
Elliot B. Sloane
Center for Healthcare Information
Research and Policy, USA
Richard Grover
University of Southern Maine, USA
John Hamilton
James Cook University, Australia
Stephen C. Hayne
Colorado State University, USA
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University of Kentucky, USA
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Central Washington University, USA
Soon-Young Huh
Korea Advanced Institute of Science
and Technology (KAIST), Korea
Richard Jacobs
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Georgia State University, USA
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Oakland University, USA
Euiho Suh
Pohang University of Science and
Technology, Korea
Junping Sun
Nova Southeastern University, USA
Minoo Tehrani
Roger Williams University, USA
William Wagner
George L. Whaley
San Jose State University, USA
J
JOURN
NAL OF MANA
AGEMEN
NT SYST
TEMS
V
Vol. 24, No. 3, 2014
A
ARTICLE
ES
T
THE CONT
TINUING MISMATCH
M
H BETWEE
EN IT GOVE
ERNANCE
E THEORY
Y
A
AND PRAC
CTICE: RES
SULTS FRO
OM A SYST
TEMATIC LITERATU
URE REVIE
EW
A
AND A DEL
LPHI STUD
DY WITH CIO’S
C
D
Daniël Smitss & Jos van Hillegersber
H
rg ......................................................................................................... 1
W
WAL-MAR
RT’S LEADE
ERSHIP IN
N RETAIL SUPPLY
S
CH
HAIN
S
Seungjae Shiin, Jack E. Tucci
T
& Dusttin Odom ....................
.
..................................................................... 21
B
BALANCIN
NG INNOVA
ATION AN
ND OPERAT
TIONS: OP
PPORTUNITIES
A
AND CHAL
LLENGES OF
O SECON
ND GENERA
ATION EN
NTERPRISE
E MOBILIT
TY
S
Sabine Bergh
haus, Thomaas Sammer, Hans
H
Brechb
bühl & Andrrea Back ................................................... 31
E
ENRICHIN
NG ENTERP
PRISE DAT
TA MODEL
LS: INCOR
RPORATING
G ACTIVE
E
T
TAXONOM
MIES
P
Peter Aiken, Long Flory & Amita Go
oyal Chin ....................
.
..................................................................... 45
IInformation
n for Contriibutors ................................................................................................................. 63
Journal off Managementt Systems, Vool. 24, Numbeer 3, 2014
JJournal of Maanagement Sy
ystems, Vol. 24, Number 3, 2014
1
Journal
J
of Managgement Syystems
ISSN #104 1-2808
A Publiccation off the Assoociation of Managgement
____________
__________
___________
__________
__________________________________________________ THE
T
CON
NTINUING
G MISMAT
TCH BETW
WEEN IT GOVERN
NANCE
THEORY
T
AND PRA
ACTICE: RESULTS
S FROM A SYSTEMATIC
LITERAT
TURE REV
VIEW AND A DELP
PHI STUD
DY WITH CIO’S
Daniël Smits, Un
niversity of Twente,
T
Ensschede, The Netherlandss
Jos van Hillegersber
H
g, University
y of Twente, Enschede, The Netherlands
AB
BSTRACT
IT governanc
ce (ITG) con
ntinues to be a ‘top ten’ issue for C
CIOs. The g
goal of this sstudy is to d
determine
w
which disciplines and fra
ameworks are used for ITG and wh
hich streamss in ITG literrature best a
align with
ccurrent prac
ctices. Anoth
her goal is to
t collect in
ndications on
n how to im
mprove ITG using litera
ature and
e
experts from
m practice. This
T
study describes
d
th
he results off a systema
atic literature
e review an
nd Delphi
sstudy of ITG effectivenes
ss and matu
urity and ass
sesses the (m
mis)match b
between ITG
G theory and practice.
T
The Delphi study
s
was conducted
c
with
w a group of 14 CIOs of mid-size
ed and large
er organizations. The
rresults show
w that six ITG streams can be distiinguished. W
We conclude
e that these
e six stream
ms are an
e
effective way
y to study the variety of
o ITG practices. The sttudy further concludes that a mism
match still
e
exists between ITG theo
ory and practtice and as well
w as the n
need for an ITG maturityy model.
K
Keywords:
IT govern
nance, CIO,, IT architecture, Portfo
olio manage
ement, Beh
havior, Delphi study,
Systemattic literature review
INTR
RODUCTIO N
IT governance (ITG) is a “top 10” is
ssue for CIO
Os. “IT gove
ernance con
ntinues to ap
ppear as an
n ongoing
‘t‘top 10’ CIO
O management issue in
n Gartner’s annual EXP
XP survey off CIOs,” wa
as the concclusion of
G
Gartner analyst J. Maho
oney based on the Exec
cutive Progrrams’ worldw
wide surveyy of more than 2,300
C
CIOs (Mahon
ney, 2012).
ITG is also a relatively new
n
topic: The
T first pub
blications ap
ppeared in th
he late 1990
0s (Webb, P
Pollard, &
R
Ridley, 2006
6). While a considerable
c
e body of lite
erature on IT
TG exists, d
definitions off ITG in the literature
vvary greatly (Webb et al.,
a 2006; Lee & Lee, 20
009). The un
nderlying vie
ews can be clustered in
n several
w
ways. For ou
ur research we
w adopt thrree views: IT
TG as a fram
mework or au
udit processs; ITG as IT decisionm
making; and ITG as a brranch of corp
porate goverrnance (Mussson, 2009).
T
There are qu
uite a lot of opinions
o
on the question
n: “What exa
actly is ITG?
?” (Webb et al., 2006; L
Lee et al.,
2
2009). These opinions are
a sometim
mes colored by the inte
erests of sup
ppliers or institutions. M
Moreover,
2
The Continuing Mismatch between IT Governance Theory and Practice
researchers have suggested that a gap exists between theoretical frameworks and practice (Peterson,
Parker, & Ribbers, 2002).
Our Research
The goal of our research program is to determine how to improve ITG effectiveness and maturity. The
goal of this study is to determine which streams in ITG literature best align with current practices and
which disciplines and frameworks are used for ITG. Another goal is to collect indications on how to
improve ITG using literature and experts from practice.
In literature, constructs like dimensions, focus areas or principles are often used to refine the concept of
ITG. Dimensions may include IT compliance management or business/IT alignment (Novotny,
Bernroider & Koch, 2012); examples of focus areas are value delivery or resource management (ITGI,
2003); and principles could be strategy or responsibility (ISO/IEC, 2008). For applicability in practice we
use the more practical term ‘discipline.’ Examples of disciplines are architecture or portfolio
management which directly relate to roles or functions in an organization, such as architect or portfolio
manager.
The goal of this study is to answer the following questions:
a. Which stream(s) of ITG best align with current practices?
b. According to practitioners, which disciplines should play an important role in ITG?
c. Is there (still) a mismatch between ITG practice and theoretical frameworks?
The last question was added because we expect a mismatch and are looking for new or innovative
ways to improve ITG. Another important goal thus was to collect indications on how to improve ITG
using experts from practice and literature.
This paper is organized as follows. The next section presents the research methodology. The section
on ITG shares some insights from ITG literature and the design of our initial model. Next follows
sections on the results of the systematic literature review and the Delphi sessions. The paper
concludes with a discussion of the research questions and a section on conclusions, limitations and
implications for future research.
RESEARCH METHODOLOGY
We adopted a research method based on a combination of a systematic literature review and a Delphi
study using the Spilter Group Decision Support System (GDSS). Our research process started with
exploring the research domain through a systematic literature review in the domain of ITG. As a next
step we performed a Delphi study in a meeting with a group of Dutch CIOs (see Figure 1).
Systematic Literature Setup
A systematic literature review (Petticrew & Roberts, 2008) on ITG was set up and performed using
Scopus and the Association for Information Systems (AIS) database. Scopus is the world’s largest
abstract and citation database and includes scholarly journals and book publishers including Wiley
Blackwell, Springer Science & Business Media, Taylor & Francis, Sage Publications, Nature Publishing,
IEEE and ACM. It also includes content from providers such as LexisNexis, Thomson Reuters (Web of
Science), JSTOR, ARTstor, Credo Reference, Encyclopedia Britannica, World Book, ABC-CLIO, The
HathiTrust Library and many others.
Journal of Management Systems, Vol. 24, Number 3, 2014
3
Figure 1. Overview of the Study
Literature study
Initial model
Delphi study
Result model
In recent papers, ITG is sometimes called ‘corporate governance of IT’ as in ISO/IEC 38500 (Calder,
2008). Others use ‘enterprise governance of IT’ or ‘enterprise governance’ (Dietz & Hoogervorst, 2012;
Van Grembergen & De Haes, 2010). In some papers ITG is called ‘IS governance’ in which IS stands
for ‘information systems’ management (Brown & Renwick, 1996). In the period of August 2012 to
September 2012 we made an initial selection of documents in Scopus searching for ITG in the title,
abstract or author keywords. For our selection we used the keywords: ‘IT governance,’ ‘governance of
IT,’ ‘IS governance’ and ‘enterprise governance.’
The use of additional keywords also resulted in the selection of a substantial set of non-IT related
corporate governance or enterprise governance documents which were excluded during the selection
process.
After analyzing the set we discovered our set was missing important documents. In the period of April
2013 to May 2013 we updated our set from Scopus and used the same keywords in the eLibrary of the
AIS. The AIS is a worldwide professional association with a large eLibrary of documents which are not
completely covered by Scopus.
The search capabilities of AIS are less advanced, which resulted in a less clean result set. After
removing doubles the resulting set was manually selected by title and abstract. Author keywords were
not available in the export files. During the manual selection process documents were selected which
satisfied the following rules:
‐
‐
‐
‐
‐
The topic of the document must be ITG;
Performance related;
Written in the languages English, German or Dutch;
Claims must be justified or based on research; and
Duplicated studies are excluded.
To collect indications on how to improve ITG from literature we also made a breakdown on a few
subjects which might deliver clues on new or innovative ways to improve ITG. First, we are interested in
ITG maturity as our research program is focused on improving ITG effectiveness and maturity. Second,
we are interested in the disciplines architecture and portfolio management. Recent literature presumes
that linking ITG with these disciplines can greatly improve IT efficiency and IT effectiveness (e.g.
Wittenburg, Matthes, Fischer & Hallermeier, 2007; Nieman, 2006). Third, we are interested in
documents related to social aspects. Contemporary literature is often based on structural, top-down,
planning processes. Critics argue that social aspects like culture, behavior and collaboration need more
attention (more on this in the next section).
To select papers related to ITG maturity we used the keywords: ‘maturity’ or ‘mature’ to search in the
title, abstract or author keywords. To select papers related to the disciplines of architecture and portfolio
management we used the keywords ‘architecture’ and ‘portfolio.’ Selecting papers related to social
aspects in a systematic way is more difficult because it is less clear which keywords should be used.
We expected the use of social related phrases like behavior, culture or collaboration. This means
4
however that the selection found might not be complete. The keywords we used were ‘behavior,’
‘behaviour,’ ‘collaborate,’ ‘collaboration,’ ‘culture’ and ‘social.’
A manual selection afterward was used to determine if the document was in scope. To be in scope the
document had to satisfy the additional rule that the topic of the document is ITG, in relation to the
relevant keywords.
Delphi Study Setup
A Delphi method may be characterized as a method for structuring a group communication process so
that the process is effective in allowing a group of individuals, as a whole, to deal with a complex
problem and obtain “the most reliable consensus of opinion of a group of experts” (Linstone & Turoff,
1975). There are several types of applications of the Delphi method in information systems research
(Okoli & Pawlowski, 2004). We use it to generate propositions and as a construct validation. The
construct in this study are the six ITG streams (see Table 6 below).
Careful selection of participants is important. The quality and responses of a Delphi panel are as good
as the experts (Linstone et al., 1975; Taylor-Powell, 2002). To accomplish this “structured
communication” several elements should be provided: Some feedback of individual contributions of
information and knowledge; some assessment of the group judgment or view; some opportunity for
individuals to revise views; and some degree of anonymity for the individual responses (Linstone et al.,
1975). With 14 participants, we also complied with the next guideline: “Ten to 15 people may be
adequate for a focused Delphi where participants do not vary a great deal.” (Taylor-Powell, 2002).
Earlier research of the IT Governance Institute (ITGI, 2008) showed that CIOs and IT management are
the best parties to ask questions about ITG: “Although championship for ITG within the enterprise
comes from the C-level, in daily practice ITG is still very much a CIO/IT director issue” (ITGI, 2008).
Technical Details of the Delphi Study
The Delphi study was conducted during a meeting of the CIO Platform Netherlands (CIOPN). The
CIOPN counts more than 100 members and delivers a good reflection of the Dutch situation within the
government and private enterprises. To become a member of the CIOPN an organization must have at
least 1,000 employees, have a sales volume of €500 million and/or an IT budget of more than €25
million. For governmental organizations no specific sales volumes are required.
Different people often have different understandings of the same concept. To address this we first
presented, explained and discussed what ITG is using the six identified ITG streams. The efficiency of
the meeting was increased by a supplemental group communication process (Linstone et al., 1975).
We used the GDSS to improve the effectiveness of the group meetings (Fjermestad & Hiltz, 2000). For
this purpose we selected the innovative tool Spilter by Canast which is a user-friendly, web-based
GDSS (Spilter, n.d.).
The participants had to respond to questions and statements using a laptop or tablet. There was no
hierarchy or dominance; each opinion counted and could be recorded. Responses were anonymous to
the rest of the group. For example, when asked to rate the streams, we used the tool to show graphs of
the responses and obtain consensus before going on to the next step. For some questions, for example
when asked to enter disciplines, responses were shared. Each participant was shown all responses
instead of only his or her own. Participants could also add their own responses or adopt them from the
group list. In advance we defined a maximum number of responses for each question.
5
IT GOVERNANCE
A survey conducted by the ITGI showed that in practice frameworks are the most important enablers for
effective ITG (ITGI, 2011). Other enablers are toolkits, benchmarking, certifications, networking, white
papers and ITG related research. Some of the frequently cited frameworks are: COBIT, ITIL, ISO/IEC
27001, ISO/IEC 17799 and BS 7799 (Musson, 2009). The frameworks which are used for ITG vary a lot
as can be seen in different surveys from the ITGI which are summarized in Table 1 (ITGI, 2008; ITGI,
2011).
Table 1. Use of ITG Frameworks
Framework
2011
2007
2005
ITIL or ISO/IEC 20000
ISO/IEC 17799, ISO/IEC 27000 or other security frameworks
Internally developed frameworks
Six Sigma
COBIT (ISACA)
PMI/PMBOK
Risk IT (ISACA)
IT Assurance Framework (ISACA)
CMM or CMMI
ISO/IEC 38500
BMIS (Business Model for Information Security, ISACA)
PRINCE2
Val IT (ISACA)
TOGAF
COSO ERM
28%
21%
24%
10%
14%
2%
14%
1%
13%
9%
33%
5%
9%
3%
4%
4%
2%
0%
0%
1%
4%
15%
13%
13%
12%
10%
9%
8%
8%
6%
5%
3%
2%
With 13% growth for Six Sigma, 12% growth for PMI/PMBOK, 11% growth for security frameworks, 4%
growth for ITIL, 3% growth for TOGAF (from 0), 1% decrease for COBIT in a period of four years there
is no clear leader. Furthermore it shows that more general frameworks like Six Sigma are fast growers
too.
The relation with project and portfolio management frameworks like PMI/PMBOK, PRINCE2 and
architecture frameworks like TOGAF can be illustrated with cases found in academic research in which
ITG is implemented using portfolio management and architecture (Wittenburg et al., 2007).
COBIT uses a classification which consists of five focus areas: Strategic alignment, value delivery,
resource management, risk management and performance measurement. The latest COBIT release is
COBIT 5.0 (ISACA, 2013). In COBIT 5.0 the concepts and ideas contained in these focus areas are
maintained and built upon in the framework, but the focus areas themselves have not been literally
maintained (Bernard, 2012; ISACA, 2013).
A recent literature survey by Novotny et al. (2012) on dimensions and operationalization of ITG reveals
nine ITG dimensions which are listed in Table 2.
Four dimensions are clearly complementary to the focus areas of COBIT 5.0: Compliance management,
decision authority and responsibility, investment management and ITG improvement.
6
Table 2. Dimensions of ITG (Novotny et al., 2012)
Dimension
Input
IT compliance management
IT risk management
IT decision authority and responsibility
IT performance and quality measurement
IT investment management
IT resource and capability management
ITG improvement
Output
Business/IT alignment
Business value delivery
Another well-known classification is the trichotomy of Peterson, O’Callaghan and Ribbers (2000):
structure, processes and relational mechanisms (De Haes & Van Grembergen, 2005). This is concise
and practical but as Willson and Pollard (2009) have shown, ITG is not limited to structure, processes
and mechanisms but also relies on complex relationships, between history and present operations.
Furthermore, culture and human factors are seen as one of the factors that most influenced the
implementation of ITG by 50% of the participants of a large global survey conducted by ITGI (2011).
Human behavior was included into the ISO/IEC 38500—the international standard for ITG—too. The
standard defines six principles for directors and top management which are: Responsibility, strategy,
acquisition, performance, conformance and human behavior (ISO/IEC, 2008).
RESULTS OF THE SYSTEMATIC LITERATURE REVIEW
The first selection between August and September 2012 using Scopus resulted in a set of 484
documents. During the second selection between April and May 2013 using Scopus an additional 169
documents were found (see Table 3).
Table 3. Totals systematic literature review
Library
Documents
Scopus
1st selection (8/2012–9/2012)
2nd selection (4/2013–5/2013)
Total selected
Remove doubles
Total excl. doubles
In scope
484
+ 169
665
- 6
659 100%
269 41%
AIS
Added (4/2013–5/2013)
+ 62
Total
In scope
#
331
%
7
After removing doubles a result set of 659 documents was left. When applying the selection criteria
listed in the former section the result set decreased to 269 documents. A manual selection on AIS using
the same criteria produced 62 additional documents.
In summary, after completing the first and second analysis the systematic literature review resulted in a
set of 331 documents in scope. The analysis of the resulting documents will be repeated several times
in the future.
Breakdown by Subject
The breakdown of the result set into subsets for the three topics is summarized in Table 4.
Table 4. Documents on ITG Grouped by Specific Topics
Documents (Total # selected = 331)
#
%
On ‘maturity’ or ‘mature’
22
7%
On ‘architecture’
On ‘portfolio’ management
On ‘architecture’ or ‘portfolio’ management
25
14
35
8%
4%
11%
On ‘collaborate’ or ‘collaboration’
On ‘behavior’ or ‘behaviour’
On ‘culture’
On ‘social’
On all social related keys
5
6
15
7
33
2%
2%
5%
2%
10%
The numbers included in the table are the totals after the manual selection to determine if the document
was in scope.
A summary of the year of publication of the documents is shown in Table 5.
Table 5. Publications by Year
Documents (per topic)
AIS
Scopus
Total complete set
Maturity
% of total
Architecture & portfolio
% of total
Social aspects
% of total
1995–2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total
7
5
12
3
1
4
1
25%
3
25%
3
3
6
3
8
11
1
9%
1
2
17% 18%
3
21
24
2
8%
1
4%
21
21
5
30
35
1
5
5% 14%
5
3
24% 9%
1
5%
7
34
41
3
7%
2
5%
3
7%
7
48
55
7
60
67
17
33
50
4
6
3
7% 9% 6%
7
9
6
13% 12% 12%
6
5
11
17% 7% 22%
5
5
62
269
331
22
7%
35
11%
33
10%
The percentages are the number of documents in a year compared to the number of documents in the
same year in the complete set.
8
The Complete Set
The oldest documents in our complete set of 331 documents are from 1995 but the vast majority is from
2006 or later. Documents from 2013 are sparse because of the time of the selection and the fact that it
always takes some time before publications are added to the databases.
The Topic ‘Maturity’
Related to ITG ‘maturity’ we found 30 unique documents. From this set 22 documents were found to be
in scope. This set also includes papers which minimally discuss the topic. Regarding ITG maturity the
COBIT framework is used the most in contemporary research papers. The maturity model of COBIT is
based on the Capability Maturity Model (CMM). Other maturity models are only found when focusing on
other than general ITG perspectives. These maturity models are mostly based on CMM too.
Documents on ITG maturity are relatively new. The first documents on ITG maturity are from 2007/2008.
The Topic Disciplines (‘Portfolio’ Management or ‘Architecture’)
We found 43 unique documents which combine ITG with ‘architecture’ and/or ‘portfolio’ (management).
From this set 35 documents were in scope, also including papers which minimally discuss the topic.
Table 4 shows the number of selected documents related to the disciplines ‘architecture’ and ‘portfolio’
(management) individually and both disciplines combined.
The list of documents mainly consists of case studies (14), models or frameworks (9), a few surveys (4)
and several other more specific types of papers (8). Some of the more interesting papers include a
case study at the BMW group (Wittenburg et al., 2007), a paper discussing ‘enterprise engineering’
which is relevant to the ‘bottom-up’ view (Dietz et al., 2012) and a paper on quantitative portfolio
management reporting anomalies or ambiguous ITG rules (Verhoef, 2007).
As can be seen in Table 5 documents which combine ITG with architecture and portfolio (management)
are mostly relatively new too. The number of publications started to grow from 2006/2007, just like the
rest of the set.
The Social Aspects Topics (‘Collaboration,’ ‘Behavior,’ ‘Culture’ or ‘Social’)
When selecting papers related to social aspects we found 39 unique documents. From this set 33
documents were found to be in scope, which also includes papers which minimally discuss the topic.
This set of documents is very diverse. These documents however might contain indications on how to
improve ITG because they use a clearly different perspective on ITG. Some of the more interesting
papers discuss the relation between ITG and Chinese culture (Zhong, Vatanasakdakul, & Aoun, 2012),
user-driven innovation or ‘shadow IT’ (Györy, Cleven, Uebernickel, & Brenner, 2012) and
‘entrepreneurial behavior’ influencing ITG (Bradley & Pratt, 2011).
Documents on social aspects were written in all periods examined and could be found in the complete
period as with the complete set of documents.
The Initial Model
Scholars have different opinions on what exactly ITG is. In our literature review we identified six
streams based on two views. The first viewing angle handles the scope of ITG. The second viewing
angle handles the direction in which ITG works.
9
Scope of ITG
Different streams can be distinguished; some use a small and others a broad scope.
Weill and Ross (2004) use a short definition, defining ITG as “the decision rights and accountability
framework for encouraging desirable behaviour in the use of IT.” These authors can be viewed as the
main contributors to this stream that focuses on decision-making. They look at ITG from a decisionmaking perspective. As components for ITG, this stream uses elements like IT decisions or decision
archetypes (Weill et al., 2004; Weill & Ross, 2005). Others complement this with the context in which
the decision is made (Xue, Liang, & Boulton, 2008).
A clear proponent of the broad definition and founder of COBIT is the ITGI. Currently, however, ITIL or
ISO 20000 are the most frequently mentioned external frameworks used as a basis for ITG (ITGI,
2011). Some researchers define ITG “as the process by which decisions are made around IT
investments” and claim ITIL V3 can provide a well matured framework for ITG (Nabiollahi & bin
Sahibuddin, 2008).
In this study we use three streams of ITG as a starting point: IT auditing, decision-making and ITG as
integral part of corporate governance (Musson, 2009). At one end of the continuum, stress is put on
corporate conformance; at the other end, the concern with corporate performance (Bhimani &
Soonawalla, 2005).
Since our research focuses on performance and not on conformance we need to differentiate between
both parts of corporate governance. We define ‘corporate governance, conformance perspective’ as
related to rules and regulations and ‘corporate governance, performance perspective’ as related to
performance and value creation.
Working Direction of ITG
Most scholars see governance as a top-down phenomenon often based on structure, processes and
planning. Another view on ITG is bottom-up. To explain this view we make a side-step to institutional
economics in which two contrasting worldviews coexist, which go all the way back to the 18th century
Enlightenment and can be described as top-down or bottom-up (Easterly, 2008).
The top-down view of ITG sees the governance of an organization as determined by the rules written
by the management and leaders of the organization. The bottom-up view sees ITG as emerging
spontaneously from the social norms, customs, traditions, beliefs and values of employees within the
organization in which the governance only formalizes what is already mainly shaped by the attitudes of
individuals.
Followers of the second view often also criticize structural, top-down, planning processes. Lindblom
(1959) for example proposes an alternative to the analytical planning approach by “muddling through”
with the argument that real world problems are far too complex to solve this way. Humans face
dilemmas "that are quite different from the wide number of options that management models lay out in
front of decision makers" (Ciborra, 1997). Schwarz and Hirschheim (2003) have found that IT
executives should approach their governance structure as an ‘architecture’ instead of formalized
hierarchies and argue that researchers “need to change their views of IT ‘structure’ to embrace a more
social and dynamic existence.” Dietz et al. (2012) use the designation distributed governance to make
clear that the involvement of the employee should include governance.
10
Table 6. Six ITG Streams
View
IT Governance Stream
Scope
1. IT audit
2. Decision-making
3. Part of corporate governance, conformance perspective
4. Part of corporate governance, performance perspective
Direction
A. Top-down
B. Bottom-up
While the top-down view is related to structure, processes and planning the bottom-up view is related to
social aspects like culture, behavior and collaboration.
This results in four ITG streams for the first view (scope) and two ITG streams for the second view
(direction) are summarized in Table 6.
RESULTS OF THE DELPHI STUDY
The participants of the Delphi meeting can be characterized as fourteen Dutch CIOs responsible for IT
budgets larger than €25 million. The attendees provided a well balanced mix from different branches
(see Table 7).
Table 7. Meeting Attendance
Attendee #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Type of organization
Agriculture
Hospital
Heavy industry
Wholesale
Engineering
Chemical industry
Non-profit
Retail
Power company
Seaport
Health insurer
City
Public health care
Finance
Of the participating CIOs 57%, report to the CFO and 21% to the CEO. Of the remaining three CIOs,
one reported to the COO, one was a member of the Board of Directors and the third has the function of
CTO (see Table 8).
11
Table 8. Reporting Line
As a CIO I report to:
CEO
CFO
COO
Other
Total
3
8
1
2
21%
57%
7%
14%
14
100%
When questioned on the rate of effectiveness of their current ITG practice (anonymously), 29% of the
CIOs rated it as sufficient (grade = 6; 10 = excellent in the Netherlands). An even larger group of 65%
rated it as good (grade = 7 or 8). Only one CIO rated it as poor (grade = 3) and did not answer the rest
of the questions.
In regard to our second research question we asked the CIOs to rate the current level of ITG
implementation for the first four ITG streams. The answers of the CIOs varied a lot (see Table 9).
Table 9. Views on ITG Implementation (regarding Scope)
#
IT auditing
Decision-making
Conformance
Performance
Min
Max
Mean
σ
5%
50%
18%
12%
10%
60%
33%
17%
10%
50%
22%
7%
10%
70%
27%
18%
The first two rows show the minimum and maximum values. The third and fourth rows show the
arithmetic mean and standard deviation between the answers (σ).
Furthermore we questioned participants about the direction of the implementation, i.e. the last two
streams. Five answers were possible: ‘Completely top-down,’ ‘Largely top-down,’ ‘Mixed,’ ‘Largely
bottom-up’ or ‘Completely bottom-up’ with a free format field for motivation (see Table 10).
Table 10. Working Direction of ITG
Responses
Completely
top-down
Largely
top-down
Mixed
Largely
bottom-up
Completely
bottom-up
#
%
0
0%
6
46 %
5
38 %
2
15 %
0
0%
As a part of the third research question we asked, “Which disciplines play an important role for ITG in
your opinion?” We added three examples of disciplines (architecture, portfolio management and IT
management) to explain what we meant by disciplines. The nonsense and too generic answer of ‘IT
12
management’ was added to the examples and accurately detected by each of the CIOs. None of them
added this discipline to the list.
The results are summarized in Table 11. The most often mentioned disciplines are portfolio
management and architecture, which were mentioned by 62% and 46% of the CIOs respectively.
Table 11. Important Disciplines for ITG according to the CIOs
Discipline
Portfolio management
Architecture
Security
Project and program management
Demand management
Innovation
Process design and management
Number of
times
mentioned
%
8
6
4
4
3
3
3
62%
46%
31%
31%
23%
23%
23%
Thirteen CIOs answered the next question, “What has to be done to improve ITG in your opinion?” Six
of them also prioritized the results (see Table 12).
It was planned to cluster the ‘Actions to improve ITG’ but due to lack of time this was done manually
afterwards by the researchers. The answers are categorized using the six principles of ISO/IEC 38500
which are ‘Responsibility,’ ‘Strategy,’ ‘Acquisition,’ ‘Performance,’ ‘Conformance,’ and ‘Human behavior.’
The highest scores were received for ‘Good ownership of processes and corresponding applications,’
‘Maturity benchmark’ and ‘Educate business managers.’ Ownership was seen as especially important
by all six CIOs who also prioritized. Due to double answers this was also repeated in ‘Process owners
(having)’ and ‘Responsibility push towards business owners.’
On the question, “Do you want to be kept informed on the results of the research?” all CIOs responded
positively.
DISCUSSION
Current levels of ITG implementation were appraised by the CIOs as sufficient or better (with one
exception). This was a surprise. However it is possible that self-rating results provides a more positive
appraisal than an objective evaluation by an independent third party. The discussion concerns our three
research questions:
Research Question (A): “Which stream(s) of ITG best align with current practices?”
None of the CIOs rated any of the scope streams at 0%, which means all four streams are seen as
relevant by the CIOs.
13
Table 12. Actions to Improve ITG
Action
Group
Responsibility
Strategy
Details
1
 Good ownership of processes and
3
corresponding applications
 Process owners (having)
 Responsibility push towards business
owners
 IT fixed on agenda board, with IT present.
BPO assigned on senior level on key
processes by the board.
 Confront business with the consequence of
their choices
 Formally approved information management
strategy
2
3
4
1
Priority
5 6 7
Total
1
1
5
83%
1
3
50%
1
17%
3
50%
1
17%
1
1
1
1
1
1
1
Performance
Conformance
Human
Behavior
Not grouped
For infrastructure too!
 Determine the fundament: IT is yield driven
and not cost driven.
 Agile IT
 Lean IT
 The CIO role must disappear in favor of a
control instrument
 Educate business managers
 Professionalize the client (NL:
opdrachtgeverschap)
 Communicate and collaborate; business
result first
 Observe the engagements (more discipline)
 Simplification
 User groups
1
1
1
1
3
50%
7%
1
4
0%
67%
0%
1
3
50%
3
50%
1
1
17%
17%
1
17%
4
67%
3
50%
2
1
1
1
1
1
1
3
1
1
1
31%
1
Acquisition
 Maturity benchmark
 Consider IT as a part of a business project.
%
Overall
%
1
29%
2%
26%
1
1
1
1
1
1
2
33%
2
1
1
33%
17%
17%
42
5%
100%
When asked for the working direction of ITG none of the CIOs chose one of the extremes (‘Completely
top-down’ or ‘Completely bottom-up’), which means that both are seen as relevant too. Our research
further reveals that on the question “What stream is most important?” the CIOs have different opinions.
So all six ITG streams of the initial model (Table 6) were seen as relevant. Because the six streams are
a result from the literature study this means that the literature and the CIOs are in agreement on this
part. As such, a broad definition of ITG best aligns with current practices.
Mixed or largely bottom-up was chosen by 54% of the CIOs which means that more than half of the
group think bottom-up is at least the same or even more important than top-down. Or as one of the
14
CIOs stated, “Bottom-up is naturally just as important” as top-down. Contemporary ITG approaches are
mostly top-down.
That none of the CIOs chose completely top-down or completely bottom-up and the relative high score
of 54% for mixed or largely bottom-up implementation relevance can be seen as a confirmation of the
opinions of critics on current top-down approaches.
Research Question (B): “According to practitioners, which disciplines should play an
important role in ITG?”
Our literature review showed that publications on research covering ITG combined with portfolio
management and architecture are still rare and seemed to start growing from 2006/2007. Case studies
in literature contain clear descriptions on the way ITG, architecture and portfolio management relate in
practice (Wittenburg et al., 2007). Books describing best practices on the combination of disciplines are
also available (e.g. Nieman, 2006). In the literature, architecture and portfolio management are seen as
important disciplines for ITG too. This was confirmed by the CIOs (see Table 11). The disciplines which
are most often mentioned are portfolio management and architecture with respectively 62% and 46%.
The Delphi study confirms that the participating CIOs agree on the relevance of these disciplines and
encourage this direction for our research program. The extra disciplines that were put forward by the
CIOs give us input for additional research.
When asked for indications on how to improve ITG, it is interesting to see that the answers to the
question: “What has to be done to improve ITG?” did not include disciplines (Table 12). Improvement of
portfolio management, architecture, security, project management, program management or innovation
was not mentioned. This might be explained by the fact that there are other issues for improvement
besides disciplines with higher priorities.
The indications mentioned are of a completely different kind. Most answers (86%) can be categorized
as part of: Responsibility, performance and human behavior. The highest score for ‘Good ownership of
processes and corresponding applications’ shows there are still issues regarding responsibilities and
accountabilities. Being one of the core issues of ITG, this seems a little contrary to the high scores for
the rating of the ITG practices. More research on what lies behind is needed.
As a result of our literature review we found that COBIT is the framework which is most often used in
contemporary research papers on ITG maturity. Relating to our streams, COBIT especially covers ‘IT
audit’ and ‘Top-down.’ There are critiques of COBIT, especially from the group of scholars we
categorized as being in the stream of ‘Bottom-up.’ Further research is needed to determine why the
CIOs don’t use existing maturity benchmarks for ITG. The need for such a benchmark is a welcome
confirmation of the relevance of the maturity part of our research program. It indicates the need for
another ITG maturity model. This might be so because contemporary maturity models are mostly
similar to CMM. CMM is largely based on process maturity. In contrast, literature and practice indicate
the need for maturity models which pay more attention to the social aspects of ITG.
The high score for ‘Educate business managers’ shows there are still issues in the collaboration
between business and IT management. We expect these to be a mix of content and social factors too.
Research Question (C): “Is there (still) a mismatch between ITG practice and
theoretical frameworks?”
The use of internally developed frameworks is diminishing fast as can be seen in Table 1. In the survey
of 2011, this was not an option in the questionnaire. However it was possible to choose the option
15
‘Other (please specify).’ Because ‘Internally developed frameworks’ was not included in the tables we
conclude it was often declined, with a percentage not high enough to reach the result tables (below
1.6%). So contemporary organizations don’t use internally developed frameworks for ITG.
Comparing the resulting disciplines with the results of the ITGI surveys (Table 1) there are a few things
that attract attention. Service management (ITIL or ISO/IEC 20000) was ranked top of the ITGI lists,
while in our results it was only mentioned twice.
Portfolio management, architecture, security and project and program management are the most
frequently mentioned disciplines. PMI/PMBOK and PRINCE2 deal with project, program and portfolio
management which are fast growers in the ITGI survey too. Architecture has a clear link with TOGAF
which received a negligible percentage of 3% in the ITGI survey of 2011. Security was in the top four in
our research. Several security frameworks like ISO/IEC 17799/27000 are indeed used as the second
most frequently used frameworks for ITG in practice (ITGI, 2011).
So we can see there is a substantial correspondence between the mentioned disciplines and the
frameworks used in practice. These disciplines however deviate from a conventional list of dimensions
(Table 2). The literature study also delivered examples of papers in which alternative factors are
suggested (e.g. Chin, Brown, & Hu, 2004; Maidin & Arshad, 2010; Nfuka & Rusu, 2010; Mohamed,
2012).
Some disciplines can be used to implement some of the dimensions. An example is IT investment
management or resource management using portfolio management. So dimensions, disciplines and
frameworks do not match.
Demand management, innovation and process design and management can only be related to the
more general frameworks.
The interest of the CIOs in the research is a confirmation of the relevance of our research program.
CONCLUSIONS
The research goals of the study are to determine if there is still a mismatch between ITG practices and
theory and to collect indications on how to improve ITG using literature and experts from practice. To
answer these questions we defined three sub-questions. The conclusions are grouped around these
questions.
“Which stream(s) of ITG best align with current practices?”
We defined six ITG streams, four of which define the scope of ITG. ITG can be seen as an audit
process, as IT decision-making, as an integral part of corporate governance from a conformance
perspective and as an integral part of corporate governance from a performance perspective. Two
streams define the direction in which ITG works (top-down or bottom-up).
Our results show that ITG is a broad working field in which all six streams (as shown in Table 4) are
seen as relevant. ‘Mixed’ or ‘Largely bottom-up’ were chosen by 54% of the CIOs which means that
more than half of the group considered bottom-up as at least equally or even more important than topdown. Contemporary ITG approaches are mostly top-down.
We conclude that a broad definition of ITG best aligns with current practices and that these six streams
are an effective way to study the variety of ITG practices. There was consensus between the CIOs in
16
the Delphi study on the relevance of each stream in the initial model and thus on the initial model itself
(Table 6).
“According to practitioners, which disciplines should play an important role in ITG?”
In literature, constructs like dimensions (as shown in Table 2), focus areas (COBIT) or principles
(ISO/IEC 38500) are often used. For recognition in practice we use the more practical term ‘discipline.’
The most often mentioned disciplines are portfolio management and architecture which were
mentioned by 62% and 46% of the CIOs (Table 11). Publications on research covering ITG combined
with portfolio management and architecture are still rare but seem to have started growing from
2006/2007.
When asked on what has to be done to improve ITG the disciplines did not show up again. As
indications to improve ITG the highest scores were received for ‘Good ownership of processes and
corresponding applications’, a ‘Maturity benchmark’ and ‘Educate business managers.’ Thus current
ITG maturity models seem to deliver no or no appropriate maturity benchmark information. This
indicates the need for another ITG maturity model.
“Is there (still) a mismatch between ITG practice and theoretical frameworks?”
We conclude that there is a substantial correspondence between the mentioned disciplines and the
frameworks used in practice. These disciplines however deviate from conventional lists of dimensions,
e.g. Table 2.
There is no clear match between the disciplines and the frameworks used in practice. Because
dimensions, disciplines and frameworks do not match we conclude it seems most likely there is still a
mismatch between ITG practice, frameworks and theory.
Implications of the Research
Some scholars prefer a small scope for ITG. Our study shows that a broad definition of ITG best aligns
with current practices. One of the reasons ITG continues to be a 'top 10' CIO management issue might
be an oversimplification of the reality in contemporary organizations. Current approaches and
frameworks are mostly ‘top-down’ based on process, structure and planning. This study shows that
‘bottom-up’ is just as important. This means that frameworks which lack sufficient attention to the social
aspects of ITG are incomplete.
We conclude there is a need for a framework and/or an ITG maturity model which combines elements
like process, structure and planning as can be found in current frameworks with elements related to
social aspects like behavior, collaboration and culture.
Limitations of the Research
The data collection was limited to a small number of Dutch CIOs. The results might be impacted by the
culture in Dutch organizations. Thus the composition of the group and the country of origin might have
impacted the results.
Future Research
As the results might be impacted by the culture in Dutch organizations it would be interesting if the six
streams are seen as relevant by CIOs in other countries too. More research has to be done to
17
determine the implications of the indications to improve ITG collected during the literature study and the
Delphi study.
The design of a framework and an ITG maturity model which combine ‘top-down’ elements like
processes and structure with the more social ‘bottom-up’ elements like behavior, collaboration and
culture will be the next step in our research program. As a next step we will also determine the focus
areas and capabilities needed to improve ITG.
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Author Biography
Daniël Smits is a management consultant at Sogeti Netherlands B.V. specialized in
governance, portfolio management and enterprise architecture. He followed the traditional career path
of programmer, designer, information analyst and project manager, and gained much experience in
complex, mostly strategic, projects covering the interface between business and ICT. In addition to his
regular activities as consultant, he is responsible for Sogeti’s governance services, and is the chairman
of the Ngi department Governance (Ngi is the Dutch association of ICT-professionals) and the
chairman of the NAF workgroup IT governance (NAF is the Dutch Architecture Forum). In 2012, Daniël
started doctoral research at the University of Twente on governance maturity and effectiveness.
Jos van Hillegersberg is a full professor of Business Information Systems at the School of
Management and Governance, University of Twente. He is head of department of the Industrial
Engineering and Business Information Systems Group (IEBIS). He is leading several research and
university-industry collaborations in both national and international consortia.
21
Journal
J
ISSN #104 1-2808
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more time to reap the
ffull benefit off supply chain operation efficiency frrom the RFI D implemen
ntation.
K
Keywords:
RFID, Wa
al-Mart, Reta
ail Supply Ch
hain, Innova
ation
INTR
RODUCTIO N
W
Wal-Mart is a giant glob
bal retailer and
a much off this successs can be attributed to its cost minimization
sstrategies in supply cha
ain managem
ment that se
et industry sstandards. A
As such, it is not surpriising that
W
Wal-Mart is ranked 9th in Gartner’s
s Top 25 Su
upply Chain in 2012. In Gartner’s liist, there is no other
rretail company ahead off Wal-Mart.
W
Wal-Mart is superior in its informattion technolo
ogy operatio
ons. Wal-Ma
art invested heavily in a central
d
database sys
stem and sa
atellite comm
munications system in th
he 1980s. In
n the 1990s, Wal-Mart de
eveloped
the largest private
p
secto
or data warrehouse in the
t
world (M
Mark, 2012).. In the 21sst Century, W
Wal-Mart
invested hea
avily in Radio
o Frequency
y Identificatio
on (RFID) te
echnology. R
RFID is defin
ned as a wire
eless tool
u
used to track
k merchandise. Combin
ned with its database
d
syystem to colllect data, de
ecode it, and
d make it
ccomputerized for better inventory op
peration, it is
s the heart o
of supply cha
ain management system
m (Hsieh,
P
Prudilova, & Binshan, 2010).
2
Wal-M
Mart’s historry is one of making an effort to reduce inventtory cost.
W
Wal-Mart’s annual
a
reporrts from 2000 to 2013 re
eport that (1
1) inventory share from net sales de
ecreased
old decreased from 52 d
to 9% from 11%,
1
(2) a number of da
ays before in
nventory is so
days to 40 d
days, and
((3) a numbe
er of annual inventory tu
urns increased from 7 to
o 9. Wal-Ma
art continuess to make significant
22
Wal-Mart’s Leadership in Retail Supply Chain
efforts to reduce inventory levels using information systems to provide a competitive advantage over its
competitors. An information system with integrated RFID allows Wal-Mart to accurately track product
location from manufacturer, to distributor, to storage pallets, to distribution center, to truck, and finally to
the store.
In this paper, the authors analyze the financial data of both Wal-Mart and its competitors in the retail
industry to answer the following two questions:
(1) Is there a significant relationship between inventory operation efficiency and per employee
profitability in the retail industry?
(2) Are there any changes in the financial ratios related to Wal-Mart’s inventory operation efficiency
and per employee profitability in the periods of pre-RFID, pilot of RFID, and implementation of
RFID against its competitors?
This study is organized as follows: first, the authors provide a literature review, secondly, a discussion
of the research approach, which includes data collection procedure, research hypothesis, and research
methods. Finally, the authors provide analysis and conclusions.
LITERATURE REVIEW
Many academic research papers attribute Wal-Mart’s success to their low cost offerings and consider
this as their competitive advantage. Wal-Mart’s supply chain management is the main distinguishing
factor that allowed for the growth from a small retailer in rural Arkansas to a global leader. Wal-Mart first
displays leadership of the retail industry by adopting a decision making system based on data analysis
provided by a barcode scanning system combined with an Electronic Data Interchange (EDI) with
vendors, and a point-of-sale system with real time data collection (Mark, 2012). Chandran (2003) states
that Wal-Mart is in a leadership position in the retail industry because of efficient supply chain practices
that result from their automated distribution centers and computerized inventory systems. Wal-Mart is
recognized for managing its own trucking system and an innovative cross-docking logistic technique
whereby they can transfer products from inbound trailers to outbound trailers without intermediate
storage.
Wal-Mart continues to validate its leadership role in supply chain management for the U.S. Retail
Industry over time. Some papers compare Wal-Mart’s superiority in inventory operation efficiency with
its major competitors. The first illustration of this is comparison of capital charge for inventory per $1 of
sales. While Wal-Mart pays $0.009 in 1994, K-Mart pays $0.017 for its every dollar of inventory (Gill
and Abend, 1997). The second instance is in 1989 when Wal-Mart’s distributing costs were as low as
1.7 percent of its cost of sales whereas major competitors K-Mart (3.5 percent of cost of sales) and
Sears (5 percent cost of sales) were operating at a higher distributing cost (Mark, 2012). The third
instance is in 2011 when Wal-Mart was able to achieve a more efficient level of inventory turnover (11.5
times) than its major competitors Target (8.7 times), Amazon.com (6.2 times) and Sears (4.7 times)
(Mark, 2012). These three examples of supply chain management efficiency leadership account for
Wal-Mart being the pioneer in Supply Chain Management. Wal-Mart’s pilot Radio Frequency
Identification (RFID) project decreased their stockout rate by 16 percent (Visich, Khumawala & Reyes,
2009). A real time portrayal of stock can be accounted for and identified with RFID communication
technology being placed in crucial spots in Wal-Mart stores.
A critical decision to make in inventory operation is how much and how frequently to reorder. A trade-off
exists between the amount to order and the frequency of the order, except for products where the
demand is unstable (i.e., large order quantity with less frequent order vs. small order quantity with more
23
frequent order). The economic order quantity (EOQ) is a conventional model for inventory decision
making that minimizes the sum of the total ordering cost and carrying cost. Just-in-time (JIT) is a
method for inventory decision making, whose main purpose is to control a restricted size of inventory
with a frequent order and small size order quantity. With coordinating RFID technology and JIT logistic
systems, Wal-Mart controls reduced inventory and facilitates operational efficiency for trucking, crossdocking, and distribution centers with real-time decision making (Qu et al., 2012).
Freeman et al. (2011) claims Wal-Mart as a technology leader as well as a business leader in the retail
sector because Wal-Mart holds the world’s largest private sector data warehouse and operating data
enabled supply chain that permits collaborative planning, forecasting, replenishment (CPRF) and
vendor managed inventory (VMI). Wal-Mart grants access to its data for its suppliers to keep its
inventory cost low. Wal-Mart successfully seized the rewards of information technology by re-organizing
its business lines. Just-in-time as an approach of improving competitiveness and reducing costs has
shown to be very effective for Wal-Mart’s supply chain. With the entrance of RFID allowing the creation
of real-time databases, it presents the opportunity to integrate efficient economic order quantity
targeting a limited inventory. Minimizing inventory is proving to be a tactic to realizing a sustained
competitive advantage in the field of cost reduction. Cost restrictions through effective inventory
management are reducing storage footprint, inventory taxes and insurance costs which are the leading
factors motivating corporations searching for efficiency and profitability (Emiliani et al., 2007; Horngren,
2011). However, one of the biggest dilemmas in obtaining the cost advantage is “supplier” cooperation
and regional economic infrastructure (Glaser, Tucci, & Anghel, 2006). Wal-Mart has defeated much of
this opposition with buyer power. An overlooked advantage of the effect of reduced inventory is that it
adds a societal oriental approach to the entire supply chain by being “greener” through the minimization
of spoilage, shrinkage, and obsolescence resulting from inventory reduction.
RESEARCH METHOD
Research Hypothesis
In this paper, the authors want to investigate how good Wal-Mart’s supply chain operation is compared
with its competitors. Operational efficiency is a measure of output to input ratio which is used for
comparing companies within the same industry. Inventory operation efficiency is used as a
performance indicator for supply chain operation. Per employee efficiency, such as profit per employee
is a useful metric when comparing business performance of retail stores or retail companies. The null
hypothesis examines if the ratios’ mean value of competitors and Wal-Mart are the same in the
inventory operation efficiency or per employee efficiency, i.e., Ho: µCompetitor = µWal-Mart. The alternative
hypothesis examines if the ratios’ mean values for Wal-Mart is better. The last hypothesis is existence
of any relationship between per employee efficiency and inventory operation efficiency, i.e., how to
affect per employee efficiency by improved inventory operation efficiency. The following are main
hypothesis to be tested in this study.
H1: The mean for competing companies’ inventory efficiency is equal to the mean for
Wal-Mart’s.
H2: The mean for competing companies’ per employee profitability is equal to the
mean for Wal-Mart’s.
H3: There is a relationship between inventory operation efficiency and per employee
profitability.
24
DATA COLLECTION
A total of 25 companies, including Wal-Mart, are examined in this study. The 24 competitors of WalMart are chosen from the industry section of Department/Specialty Retail Store on the NASDAQ web
sites (http://www.nasdaq.com/symbol/wmt/competitors). The first criterion for inclusion in this research
is that the companies used must be publicly traded in order to gain available financial data. The next
criterion is the companies examined must be competitors of Wal-Mart in multiple key product segments.
All 25 companies have been listed in U.S. stock markets such as NYSE and NASDAQ for 14 years
since 2000. The following is a stock symbol list of 25 companies: ALCS, AMZN, BBY, BIG, BONT,
COST, CVS, DDS, DG, DLTR, FDO, FRED, HD, JCP, KR, KSS, LOW, M, RSH, SHLD, SWY, TGT,
TUES, WAG, and WMT. Once the companies are selected, the next step is to identify how to measure
labor efficiency and inventory operation efficiency for each firm. It was determined the most objective
way to do this was through observation of each company’s financial statements. Financial statements
are collected for the fiscal years of 2000 through 2013 for each of the 25 companies from the
CompuStat database. Out of 25 companies, only one company does not have 2013 financial
statements (Alico Inc.) at the time of writing this paper. The data is summarized for three periods (PreRFID, Pilot, and Implementation). Therefore, the total number of data in this data set is 349 (25
companies * 14 year -1), which is a sum of period 1 (100 data), period 2 (100 data), and period 3 (149
data).
The financial ratios for efficiency for inventory operation are inventory turnover ratio (ITR), inventory to
sales ratio (ISR), and days-in-inventory (DII). The financial ratio of profitability associated with inventory
operation is gross margin return on inventory investment (GMROII), which is calculated by gross profit
divided by inventory. The last financial ratio related with labor efficiency is per employee gross profit
(PEGP), which is calculated by gross profit divided by number of full time employees. While the higher
ITR, GMROII, and PEGP are, the better they are; the lower DII and ISR are, the better they are.
DESCRIPTIVE STATISTICS
Once the fourteen year information for each financial ratio is collected for the 25 companies, the data
was grouped in three time periods: Period 1, 2000-2003; Period 2, 2004-2007; and Period 3, 20082013. Wal-Mart introduced RFID technology in 2003 and initiated a pilot test (Hunt et al., 2007). In 2004,
Wal-Mart announced the result of RFID pilot study. Wal-Mart issued the first RFID mandate during the
pilot phase, which required its top 100 suppliers to put RFID tags on their pallets and case lots
beginning January 2005 (Hunt et al., 2007). This was expanded quickly to the top 300 suppliers. In
2007, Wal-Mart announced that it would charge Sam’s Club suppliers a $2 penalty for each pallet
without a RFID tag shipped to its distribution centers, beginning January 2008 which was the start of
the implementation period (Weier, 2008). This was a serious message to 60,000 Wal-Mart and Sam’s
Table 1. Competitors Financial Ratio: Mean (S.D.)
ITR
ISR
DII
GMROII
PEGP
Period 1
Period 2
Period 3
5.09 (2.87)
0.16 (0.06)
90.06 (38.27)
2.21 (0.92)
$49,546.93 (23,003.89)
5.04 (2.72)
0.16 (0.06)
90.18 (37.29)
2.23 (0.75)
$58,360.08(31,234.56)
5.43 (3.10)
0.16 (0.06)
86.20 (38.80)
2.31 (0.84)
$64,577.45 (37,056.13)
25
Club suppliers, which meant that without RFID technology, they were not going to deal with Wal-Mart in
the near future. Period 1 is the pre-RFID stage and Period 2 is the pilot stage of RFID technology and
Period 3 is the implementation stage of RFID on a company-wide supply chain level. Table 1 presents
mean and standard deviation of five ratios of the 24 competitors of Wal-Mart in each period. Table 2
shows the same data for Wal-Mart in each period. Table 3 shows null hypothesis to be tested in the
next section.
Table 2. Wal-Mart’s Financial Ratio: Mean (S.D.)
ITR
ISR
DII
GMROII
PEGP
Period 1
Period2
Period3
7.32 (0.30)
7.57 (0.31)
8.30 (0.48)
0.11 (0.31)
49.92 (2.11)
2.21 (0.12)
$38,267.82 (2,996.60)
0.10 (0.00)
48.27 (1.97)
2.53 (0.15)
$43,973.98 (2,015.98)
0.09 (0.01)
44.11 (2.53)
2.97 (0.19)
$53,449.13 (2,865.79)
Table 3. Null Hypothesis
Period 1
Period2
Period3
ITR
ISR
DII
GMROII
µCompetitor = 7.32
µCompetitor = 0.11
µCompetitor = 49.92
µCompetitor = 2.21
µCompetitor = 7.57
µCompetitor = 0.10
µCompetitor = 2.53
µCompetitor = 8.30
µCompetitor = 0.09
µCompetitor = 2.97
PEGP
µCompetitor = 38,268
T-TEST RESULT
Table 4 shows the t-test results for the 24 competing companies’ ratios against Wal-Mart for each time
period. Two-tailed p-values are used for each ratio in each period. In the ITR, ISR, DII, and PEGP, all
p-values are near zero indicating that the null hypothesis is rejected with 1% significance level. In the
GMROII, in Period 1, the null hypothesis is not rejected because of the high p-value, 0.955. However, in
Table 4. T-Statistics (P-value)
Period 1 (n = 96)
Period 2 (n=96)
Period 3 (n=143)
ITR
-7.595
(0.000)
-9.130
(0.000)
-11.093
(0.000)
ISR
8.589
(0.000)
10.159
(0.000)
12.332
(0.000)
DII
22.520
(0.000)
11.013
(0.000)
12.974
(0.000)
GMROII
0.057
(0.955)
-3.948
(0.000)
-9.402
(0.000)
PEGP
4.804
(0.000)
4.513
(0.000)
3.591
(0.000)
26
Period 2 and 3, the null hypotheses are rejected because of near zero p-values. Therefore, in all three
periods, the ITR, ISR, DII, and PEGP of Wal-Mart are significantly improved values than those of its
competitors. There is no difference in GMROII in Period 1 between Wal-Mart and its competitors but in
Period 2 and 3, Wal-Mart’s GMROII values are improved a lot compared to that of competitors.
CORRELATION
Table 5 is the correlation matrix for the above five ratios. According to Anderson et. al, (2008), the rule
of thumb for selecting independent variables of regression analysis is that if the correlation coefficient is
greater than 0.70, then it should not be used in a multiple regression because of multicollinearity. The
GMROII has a common component of inventory with the three inventory operation ratios and a
common component of gross profit with the PEGP. Thus, GMROII is not chosen as an independent and
a dependent variable in the regression models.
Table 5. Correlation Matrix
ITR
ISR
DII
GMROII
PEGP
ITR
ISR
DII
GMROII
PEGP
1.00000
-0.86178
-0.87241
0.68350
0.44709
1.00000
0.96601
-0.73302
-0.45714
1.00000
-0.64109
-0.44586
1.00000
0.36795
1.00000
REGRESSION ANALYSIS
The data set used in the regression study is both a cross-sectional and a time series panel data. As a
cross-sectional data, the values of variables such as inventory related ratios and profit ratio are
collected for 25 retail companies including Wal-Mart. As a time series data, the values of the variables
are collected for 14 years. Therefore, the total number of observation used is 349, which are 25
retailers by 14 years minus one missing data. The independent variables are ITR, ISR, and DII and the
dependent variable is PEGP. Because of high correlation index, instead of multiple linear regressions,
three simple linear regression analyses are used. Because the distribution of PEGP is skewed, log
transformation of PEGP (LN-PEGP) is used. Because the main focus of this study is comparison
between Wal-Mart and its competitors, a slope dummy variable for Wal-Mart, WMT, is introduced with
an assumption that impact of independent variables (ITR, ISR, and DII) to dependent variable (LNPEGP) is different between two groups, competitor groups and Wal-Mart. The slope dummy variable
makes a product term with independent variables. The followings are three simple regression models:
LN-PEGPit = β0 + β1ITRit + β2(ITR*WMT)it +εit .............................................................. (1)
LN-PEGPit = β0 + β1ISRit + β2(ISR*WMT)it +εit ............................................................. (2)
LN-PEGPit = β0 + β1DIIit + β2(DII*WMT)it +εit ................................................................ (3)
For i = 1~25, t = 2000~2013, WMT = 1 if it is Wal-Mart, = 0 otherwise.
27
Estimating the panel data regression model by ordinary least square method (OLS) might provide a
biased solution caused by unobserved heterogeneity (Dougherty, 2006). To test homoskedasticity
assumption, the Breusch-Pagan (BP) Test is used. The BP Test is supposed to detect
heteroskedasticity by running a regression with the squared residuals as a dependent variable. To test
autocorrelation, the Durbin-Watson (DW) statistic (d) is used. Because all three p-values from the BP
tests are near zero, the null hypothesis of homoskedasticity can be rejected with a 1% significance level.
Thus, all three models qualify heteroskedasticity. The DW statistics are far less than critical values of
DW test, all three models have autocorrelation problem. To overcome the problems from BP test and
DW test, the authors choose the panel data regression approach. There are two models in the panel
data regression: fixed effect model and random effect model. According to Greene (2012), while the
fixed effect assumes that individual heterogeneity is correlated with independent variables, the random
effect assumes that the individual heterogeneity is uncorrelated with the independent variables. Jerry A.
Hausman developed a test for determining which model is appropriate, i.e., Hausman Test. To do the
Hausman Test, the individual dummy variables must be introduced in each equation. The null
hypothesis for the Hausman test was that no differences result between the fixed effect model and the
random effect model. Because of the p-value from the Hausman test is greater than 1% significance,
the null hypothesis cannot be rejected. Therefore, the random effect model is more appropriate. Table 6
summarizes the test results of three tests.
Table 6. Results from the Tests
Equation
BP Test: p-value
DW Test*
PH Test: p-value
(1)
(2)
(3)
9.17e-16
4.694e-5
2.01e-4
DW = 0.2929
DW = 0.3359
DW = 0.3226
0.5233
0.5187
0.4935
* Critical Values: DU(n=100,α=.01, k=3)=1.482, DU(n=150,α=.01, k=3)=1.584
Table 7 summarizes the results from the random effect models. All coefficient of variables in each
equation model have near zero p-values and model fit p-value is also near zero. Thus the model and its
coefficients are acceptable with a significance level of 1%. Because the dependent variable has logtransformation, when one unit of increase in an independent variable, the dependent variable changes
β1 % for Wal-Mart’s competitors and (β1 + β2)% for Wal-Mart itself. In equation (2) and (3), Wal-Mart’s
ISR and DII have a stronger impact to PEGP than its competitors. In equation (1), Wal-Mart’s
competitors’ ITR have much stronger impact to PEGP than Wal-Mart’s ITR, because the sign of β1 and
β2 are opposite.
CONCLUSION
The infusion of advanced “real-time” information technology, advanced inventory systems, and the
willingness of the suppliers to conform to RFID standards has allowed Wal-Mart to increase inventory
management efficiency, create a more efficient market, and at the same time, contribute towards the
creation of a greener environment by reducing wastes created by holding excess inventory. With
significant advances in information technology with integration of RFID technology, Wal-Mart has been
able to leverage these assets to significantly overcome the problems of time and distance differentials.
28
Table 7. Result from the Random Effect Regression
Equation
βo
(p-value)
β1
(p-value)
β2
(p-value)
R2
F
(p-value)
(1)
10.5140
(0.0000)
0.0711
(0.0000)
-0.0424
(0.0002)
0.2958
77.669
(0.0000)
(2)
11.5001
(0.0000)
-3.8594
(0.0000)
-4.2333
(0.0000)
0.3755
104.005
(0.0000)
(3)
11.4064
(0.0000)
-0.0059
(0.0000)
-0.0085
(0.0000)
0.3491
92.76
(0.0000)
In the T-test analysis, Wal-Mart shows its excellence for inventory operation efficiency and per
employee gross profit regardless of periods. Thus, Wal-Mart’s RFID initiative cannot explain Wal-Mart’s
superiority in inventory operation efficiency and per employee profit efficiency after the implementation
of RFID technology. But Wal-Mart’s GMROII is improved from the period of pre-RFID to pilot and
implementation periods. Therefore, Wal-Mart has had an excellent supply chain reputation before the
RFID technology adoption. However, improvement in GMROII is important in retail because GMROII is
a ratio of productivity of inventory, i.e., per inventory gross profit. From the GMROII’s point view, WalMart’s RFID initiative has been successful for the last 10 years.
In the regression analysis, we found that there is a strong relationship between inventory operation
efficiency and per employee profitability in the retail industry. Wal-Mart shows a stronger relationship
between ISR/DII and LN-PEGP, but its competitors show a stronger relationship between ITR and LNPEGR. While low ITR usually happens in overstocking, high ITR shows strong sales performance or
shortage of inventory. Under the circumstance of efficient control of inventory, high ITR can be
maintained without stock shortage. The RFID technology is proven to be effective in reducing stock-out
rate (Shin and Eksioglu, 2014). An employee productivity ratio like PEGP, gets less productive as a
company’s size grows because of complexity of internal process, increase of communications cost, and
layers of bureaucracy. In 2013 data, among the 24 retailers, Wal-Mart’s market share is 34%. The
second largest one is only 9%. Even if Wal-Mart has a greater value of ITR than its competitors, the
response of per employee productivity to a change of inventory efficiency is smaller than its competitors
because of its large company size effect. As Hsieh et al. (2010) said, the benefit of RFID technology is
a long run benefit. Even if there has been an improved GMROII and positive relationship between
inventory efficiency and labor productivity, to prove Wal-Mart’s stronger efficiency of inventory and labor
against its competitors, it might need more time.
References
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29
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Saddle River, NJ: Pearson Prentice Hall.
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Universities: Current Status and Future Applications. Proceeding of 2010 Southwest Decision
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Hoboken, New Jersey: John Wiley & Sons, Inc.
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Author Biography
Seungjae Shin received a Ph.D. in information sciences (2003) at the University of Pittsburgh
and a Ph.D. in Industrial and Systems Engineering (2013) at Mississippi State University. He is
currently an Associate Professor of Information Systems and Supply Chain Management at Mississippi
State University, Meridian. His research areas are telecommunications industry analysis and supply
chain management.
30
Jack Tucci received his Ph.D. in 1996 from the Department of Management at the University of
North Texas. He is currently William M. Lemley Chair Professor of Management and Marketing at
Arkansas Tech University. His research efforts are focused on sustainable strategic management.
Dustin Odom received a Master of Business Administration (2011) at Mississippi State
University. He is currently a Counselor for the Mississippi State University-Small Business
Development Center and also an Adjunct Lecturer of Marketing for Mississippi State University,
Meridian.
31
Journal
J
ISSN #104 1-2808
A Publiccation of the Assocciation off Manageement
____________
__________
___________
__________
__________________________________________________ BALANCING IN
NNOVATION AND OPERAT
TIONS: OP
PPORTUN
NITIES AND
CHA
ALLENGES
S OF SEC
COND GE
ENERATIO
ON ENTE
ERPRISE MOBILIT
TY
Sabin
ne Berghaus
s, University
y of St.Gallen
n, St. Gallen
n, Switzerlan
nd
Thomas Sa
ammer, Nam
mics AG, St. Gallen, Swittzerland
Hans Bre
echbühl, Tuc
ck School of Business att Dartmouth College, Ha
anover, New
w Hampshire, USA
Andrea Back, University
U
off St.Gallen, S
St. Gallen, S
Switzerland
AB
BSTRACT
A new generration of mob
bile IT is driv
ving new thin
nking and in
nnovation in most areas of organizattions and
iss challenging corporate IT. From a “computing”” perspective
e, this secon
nd-generatio
on enterprise
e mobility
((SGEM), su
uch as sma
artphones and
a
media tablets, ena
ables perva
asiveness, m
much more intuitive
ccomputing, and
a
contexttual intelligence. This changes
c
wha
at can be d
done with IT
T in enterprrises and
ccreates new
w challenges
s for IT dep
partments. Based
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on th
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Keywords:
Corporate
e IT, Mobile
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g, Enterprisse Mobility, Enterprise Mobile, Ro
ole of IT,
Smartpho
one, Tablet Computer
C
INTR
RODUCTIO N
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bile IT has be
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ser, 2013; Gartner,
G
2013
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ension for
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hich encomp
passes all kiinds of highly portable ccomputer
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ch as tablett computer or smartphones, but a
also wearab
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ording to
G
Gartner will drive 50 % of app in
nteractions by 2017 (G
Gartner, 201
14a). Starti ng with rem
markable

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A
An earlier version of this papeer has previoussly been publishhed in the Procceedings of thee Nineteenth A
Americas Confeerence on
Innformation Sysstems (Sammeer, Brechbühl, & Back, 2013).
32
Balancing Innovation and Operations: Opportunities and Challenges of Second Generation Enterprise Mobility
improvements in the hardware capabilities of these devices, mobile IT affects all layers of digital
technology – including the content, service, network and device layer (Yoo, Henfridsson, & Lyytinen,
2010) – by enabling various innovations and technological changes (Yoo, 2010). These changes are
substantial. In the content layer, mobile IT now offers more capabilities than ever for storing and
consuming any kind of multimedia content. This is evidenced mobile traffic making up for 40 % of
YouTube’s total traffic (YouTube, 2014), or the fact that 60 million photos are uploaded every day on
the mobile-only platform Instagram (Instagram, 2014). Remarkable improvements are also evident in
the service layer, as mobile IT now offers an extensive range of application functionality that serves the
user for almost any propose. Facts concerning applications for mobile devices are testimony to this: For
example, Statista reports a total of 75 billion app downloads from the Apple app store between June
2008 and October 2014 (Statista, 2014a) and forecasts 268 billion app downloads by 2017 in total
(Statista, 2014b). Also, Gartner forecasted that mobile apps will have a significant impact on
information infrastructure (Gartner, 2014b). The network layer, so far one of the mayor limitations of
mobile IT, has also made remarkable improvements; wireless high-speed internet access is now
available in most areas of the world and for 2014, the International Telecommunication Union reported
2.3 billion active mobile broadband subscriptions worldwide, with 55 % of them in developing countries
(ITU, 2014). This opens up new market opportunities, as in many parts of the world – especially in
emerging markets – mobile IT is often the only available technology that supports Internet access. And
finally, innovation is also not stagnant on the device layer: There is a growing number of new kinds of
devices which offer intuitive and mostly restriction-free access to services and content with an everincreasing quality and functionality, coupled with decreasing prices for such devices (Harris, Ives, &
Junglas, 2012; L. Pitt, Berthon, & Robson, 2011). These changes are evident and fundamental. In the
context of corporate IT, we therefore label this new generation as second-generation enterprise mobility
(SGEM), which is the focus of our study.
Such wide-reaching technological developments influence organizations (Gillespie, 2007; Klein & Sorra,
1996; Rogers, 2003) and create a need for corporations to respond effectively to these changes and to
exploit the emerging opportunities (Berghaus & Back, 2014). Unlike previous technological innovations,
SGEM is entering organizations faster and more invasively due to the introduction of personal
consumer electronics to the workplace (Harris et al., 2012; Ortbach, Brockmann, & Stieglitz, 2014).
Concerning this challenge of responding to SGEM, research can improve the adoption process of
SGEM by acting as a facilitator for knowledge transfer and support practice by deriving insights from
empirical studies. From an academic perspective, such issues are also valuable and contribute new
insights from the latest industry practice to academic discourse. We therefore adopt an explorative
research approach and examine, on a large scale, how corporations are actually reacting to SGEM by
summarizing opportunities and challenges derived from industry practice. Based on three expert group
interviews with CIOs, and an additional twelve interviews with C-Levels from multinational corporations,
we consider the following research question related to corporate IT: What opportunities and challenges
do IT departments in corporations experience with SGEM?
The remainder of the paper is organized as follows. Section 2 gives an introduction to the theory by
defining SGEM. Section 3 discusses the methodological approach and describes the sample. Section 4
reports on the results and describes the identified opportunities and challenges. Section 5 discusses
the results and implications for theory and practice, as well as the limitations of the study.
THEORETICAL BACKGROUND
So far, mobile IT has been defined by the distinction between portable and non-portable computer
devices (Kristoffersen & Ljungberg, 1999). This definition is sufficient for the first generation of mobile
IT innovation witnessed in the early 2000s, but nowadays the portability of computer devices is only
33
one aspect that sets mobile IT apart from conventional IT. The features of mobile IT now include
additional aspects such as improved human-computer interaction, data visualization methods, usability
and a remarkable market penetration, which offers corporations a new communication and distribution
channel for products and services (L. Pitt et al., 2011; Stieglitz & Brockmann, 2012). We use the term
SGEM to refer to this new generation of mobile IT and its usage in the context of corporate IT.
To frame the research, we define SGEM by three characteristics which we derive from the theory of
ubiquitous computing (Lyytinen et al., 2004; Weiser, Gold, & Brown, 1999; Weiser, 1991). One aspect
of ubiquitous computing is a superior usability and an intuitive human-computer interaction. This is
evident for SGEM, as the intuitiveness relating to such devices has increased to a level at which even
people who are generally uncomfortable with computers are able to interact with media tablets without
prior training. If we compare this kind of usability and intuitive usage with PDAs or tablet computers
from the early 2000s, the distinction becomes clear (L. Pitt et al., 2011). This increased usability
enables also a better integration into the context, providing computer support in situations where
computers had before been perceived as distracting and inappropriate (such as in a sales talk or
counseling interview). We call this intuitive computing.
A second characteristic is the market penetration of such devices. These new devices are a market
success – especially compared with their predecessors – and have reached such a high diffusion rate
that they are now pretty much available to anyone. Along with the market penetration, the portability of
the devices has also increased and led to a situation where SGEM is with us anywhere, and anytime
(Harris et al., 2012). These developments led to a new dimension of connectivity (Dery & MacCormick,
2012), which we call pervasiveness.
Another distinction can be made in terms of the functionality of the hardware (Jonsson, Holmström,
Lyytinen, & Nilsson, 2010; L. F. Pitt, Parent, Junglas, Chan, & Spyropoulou, 2010). SGEM devices
possess a range of sensors that enable contextual intelligence (the devices relate to their environment,
like context-aware applications, automated capture or sensitive and responsive computer
environments). This aspect of ubiquitous computing is frequently mentioned by various different authors
(Begole, 2011; Jonsson, Westergren, & Holmström, 2008) and termed contextual intelligence.
Contextual intelligence can also be counted to one characteristic of the Internet of Things, based on the
concept that everyday objects can be connected anytime, anyplace with anything (Frost & Sullivan,
2014b).
By comparing these characteristics with devices that corporations recognize as the driving force of
mobile IT innovation (Harris et al., 2012), namely novel smartphones, such as the iPhone or Android
devices, and media tablets, such as the iPad or certain Android tablets, it can be recognized that these
devices conform well to the characteristics of ubiquitous computing:
1. Intuitive computing: Mobile IT devices support an intuitive and accessible computing experience.
These devices can be seamlessly integrated into a conversation and enhance, it rather than
detract from it.
2. Pervasiveness: Mobile IT devices are highly portable, allow continuous connectivity – and thus
a constant data and application consistency, and are available to pretty much anyone,
anywhere, and anytime. This not only leads to a better reachability of existing customers, but
also to the possibility to reach new customers (e.g. in emerging markets).
3. Contextual intelligence: Mobile IT devices can interact with and react to the environment, due to
sensory input such as location, acceleration, light conditions, user identification and so forth.
34
We use these three characteristics to define SGEM. These three characteristics also set the scope of
the research, as the article covers only technology that conforms to all of these three characteristics
(such as smartphones and media tablets). However, the characteristics defined can also be applied to
newer technologies, such as wearable technology or connected objects and machines, subsumed in
the term “Internet of Things”. This shows that our definition of SGEM is also sound for the next
generation of technology to be implemented in organizations.
Regarding the research question, we further need to define the terms “opportunity” and “challenge”.
Opportunities refer to fields of application where the adoption of SGEM leads to a relative business
advantage compared to other solutions (Porter & Millar, 1985). In this process of gaining a relative
business advantage due to technology adoption, the objective is to replace existing systems with a
superior one. Such adoption processes are always challenging for organizations (Rogers, 2003).
However, regardless of whether a corporation exploits such opportunities, technological innovation is
an external influence that is inevitably challenging (Gillespie, 2007; Klein & Sorra, 1996; Rogers, 2003).
We therefore define a challenge as a need for a change in approach or action, created by the
emergence of SGEM.
METHOD
In particular with mobile technology it becomes increasingly difficult to separate digital products and
services from technology. Our research therefore follows a socio-materialistic approach (Leonardi,
2012; Orlikowski, 2009) to gain a complete view of the challenges and opportunities associated with
SGEM. As opposed to the understanding of technology as “exogenous force” our definition SGEM does
not see technology as an autonomous impact, but is interconnected with humans in an institutional
context (Orlikowski, 2009). By following this approach, we ensure gaining a complete view and
preventing a blind spot due to focusing exclusively on technology issues. Therefore, we decided to use
qualitative data to capture “the voice” of the participants and conducted three expert group interviews
and twelve telephone interviews. While the individual interviews followed a very structured approach,
the expert group interviews were conducted as moderated roundtable discussions to foster an
exchange of experiences. By combining these two approaches we ensured to capture issues that
would maybe not have been revealed by a too stringent and structured approach. Concerning the
participants, we invited only CIOs or officers in charge of mobility solutions as we assume that they
have a complete view of the challenges and opportunities the associated organization experiences with
SGEM. To have a comparable sample, the study focuses on large corporations and we therefore
gathered data from 31 multinational corporations with more than one million dollars in revenue and
more than three thousand employees. All corporations in the sample are from a variety of industries
that operate globally. The sample includes organizations from the following industries: financial services
(26 %), logistics (13 %), IT (13 %), food (13 %), heavy industry (13 %), manufacturing (10 %),
electronic industry (6 %), and others (6 %). The three expert group interviews were held in 2012 and
attended by CIOs from multinational corporations in Europe and the US. The interviews were
moderated roundtable discussions and lasted five to six hours. For the analysis, the discussions were
audio-recorded and then transcribed.
In addition, we conducted twelve interviews with CIOs or officers in charge of mobility solutions of
multinational corporations from Germany, Austria and Switzerland that employ SGEM devices in
different areas of their corporation. The data collection primarily comprised in-depth telephone
interviews conducted in 2011 (June-December). The interviews lasted an average of about 100 minutes
and were audio-recorded and transcribed. We followed a semi-structured questionnaire that covered
the following areas with respect to the solutions of interest: strategic reasons, benefits of the solution,
organizational issues, and strategic and technological challenges. The analysis followed the approach
recommended by Miles and Huberman for qualitative content analysis (Miles, Huberman, & Saldaña,
35
2014). Based on the transcripts, two of the authors independently identified issues that the corporations
in the sample are experiencing with SGEM. The issues had to apply to the definition of SGEM given in
the previous section. After collecting material on the issues, the authors independently categorized
them into two categories: opportunities and challenges for corporate IT. In a series of three workshops,
the authors jointly synthesized and categorized the data, yielding three opportunities and four
challenges.
RESULTS
In this section, we describe the opportunities and challenges identified in the course of the analysis.
Empirical evidence is presented as direct quotations on a given issue. We identified three generic
opportunities concerning sales, service, and internal efficiency and four challenges for corporate IT,
including the usability vs. security challenge, innovation management, software development style, and
staffing.
Opportunities
In general, all organizations in our sample reported at least one benefit they experience with SGEM. In
the following section, we describe three generic opportunities which we derived from our data. These
opportunities are likely to apply to any industry and any organization.
Sales
Several corporations report that the integration of SGEM into sales activities created value for them.
Common examples are media tablet solutions that introduce computer-support to face-to-face
conversations. In conversations, media tablets are experienced as an appropriate device for enabling
computer support, in contrast to common IT devices, such as laptops or desktop computers. One
company reports that so far, they had a guideline for their field staff not to use laptop computers in
interviews or talks, as they create a barrier between them and the client:
“Why tablets? We have this guideline for our consultants, which says that it is not ideal to use a
laptop. If you open the laptop it creates a psychological wall between the consultant and the
client.” (Head of Sales, Swiss banking company)
However, computers can support such activities with additional information or the possibility to visualize
different outcome scenarios. Through using media tablets, corporations can overcome these limitations
and use software applications to support their staff in such activities. For example, the sales and
consulting personnel of a bank uses a media tablet solution to communicate their offers to clients.
These offers are complex and highly customizable financial services, which are intangible and hard to
communicate to clients. Media tablets are now used during the client meetings and the service can be
customized to the customer’s needs with results depicted onscreen. In addition, SGEM offers
organizations an additional communication channel. For example, the Eaton Corporation now offers
resellers and end-customers a media tablet application that gives them full access to the extensive
product portfolio of the company, and support for cross references for some thousand specific technical
elements. Before, this was only possible for associated consulting experts. However, due to the
possibility of providing enhanced users-services for SGEM, this service now is publically available. By
opening up this comprehensive database to customers and making it available in a user-friendly and
intuitive way, the corporation achieved additional purchases:
“Imagine a pump that goes in a John Deere tractor, or a Boeing 737. It has all kinds of
configurations. […] We search them in the app and boom! ‘This is the pump you need,’ from
36
thousands of different types of pumps. And we’ve made it before. We make it at this plant, and
the lead time is this. Here’s the engineering drawing. Here’s the data that goes with it in an email. Now the customer embeds it into his system. He sees it. ‘I can use that.’ This cycle time
used to take weeks, and we’ve shrunk it down to a couple of hours. We had an engineer in a
design session do a product cross-reference right there, and he made a $470,000 initial sales
deal. It would have never happened without the app.” (CIO, Industrial Sector – IT, Eaton
Corporation)
Service
The pervasiveness and intuitiveness of SGEM has also led to additional customer self-service options.
Due to the increased pervasiveness of SGEM, new opportunities for self-service processes are enabled.
One example is the application provided by an insurance company that allows clients to report claim
cases (e.g. car accidents). The client is guided through the claim report process and additional
information, such as photos and location, are added to the report. The report is then submitted
electronically via the application. In addition, the application provides clients with safety instructions and
other useful information in accident cases. The process is digitalized and no paperwork is needed.
Thus, service availability is increased and the insurance company achieves an increased information
quality for the claim evaluation process. These novel self-service options that SGEM enable are of
particular interest for insurance companies:
“In 5 to 10 years, when the technology is further improved, we will have the opportunity to
provide our customers with an App which will enable them to scan their home and automatically
receive a customized offer.” (Director, Swiss insurance company)
Mobile applications are also employed to outsource a complete process to the customer. Airlines, for
example, now provide customers with applications allowing them to search for flight offers, book flights,
make mobile check-ins with seat reservation, and save the boarding pass on their mobile device. Such
self-service options for clients reduce paperwork, decrease points of contact, and save time for
customers, as they no longer have to queue at a counter.
Internal Efficiency
Pervasiveness is also capitalized in tasks that require employees to travel. Such tasks can be
effectively supported and enhanced with additional information offered by SGEM devices. Standard
corporate approval processes for employee requests are simpler, quicker, and more efficient. Business
cases of even higher impact include advanced computer-support for activities at construction sites, for
inspections of industrial facilities, for job navigation or stock-updates in rural areas. For example, media
tablet usage created efficiency gains on the construction site of an airport in Qatar:
“It’s a huge open space. We put in our own Wi-Fi throughout the construction site, and launched
an iPad-based inspection app for the people in the field. We measured a 3- to 5-fold gain on
daily productivity for people who had the app.” (CIO, Bechtel Corporation)
A comparable example can be given for the inspection of industrial facilities:
“We program operators’ routine duties into their mobile devices, including checklists for
procedures. Every procedure in our complex facilities has to be done exactly right. We saw work
force productivity go up by a factor of two, but for us the greater benefit is the assurance that
our procedures are done right, to make sure we don’t have a catastrophic failure.” (CIO,
Chevron Global Upstream)
37
Other benefits include increased information quality about the inventory of stores in rural areas, for
example the solution used by Holcim’s India sales force:
“Every day they go to the dealer, and they enter into their phones how many bags of cement are
there, from us and from our competitors, as well as the respective prices. The data get sent
centrally for analysis. And our margin has gone up 10 %, because we have the relevant market
intelligence by knowing the development of volume and price.” (CIO, Holcim)
Challenges For Corporate IT
Along with the benefits and possibilities of SGEM, corporations also experience challenges that call for
new approaches to address and benefit from the emergence of this new technological generation.
Usability vs. Security Challenges
SGEM have reached almost everyone, regardless of demographics. This means that when SGEM
devices are not supported or allowed at work, people will enjoy using them anyway in their personal
lives. The convenience of applications used in private lives therefore creates expectations for
professional applications. Hence, experiences with IT in personal life also form the reference point for
experiences with IT in work life (Ip, 2010). CIOs experience this as a spill-over effect between
professional and private life and perceive this as challenging:
“The trend is really coming from consumer IT—people do something at home, then they bring it
to work, and they bring expectations of what it should be.” (CIO, Holcim)
This conforms to the spill-over theory which predicts that experiences in personal or family life positively
or negatively spill-over to work life and vice versa (Grzywacz & Marks, 1999). Employees expect
corporate IT applications to be as convenient as the consumer applications they use in their spare time:
“There is an expectation that it should be just as easy for people to access and use corporate
information from a mobile device as it is for them in their personal lives.” (CIO, Eastman
Chemical Company)
But achieving comparable usability is only one aspect. Corporations often experience usability as a
trade-off with security. Hence, CIOs face the challenge of balancing productivity, ease-of-use, and
security:
“[…] as a corporate entity, we value our intellectual property, […] we try to balance this dynamic
between productivity and security.” (CIO, Eastman Chemical Company)
The core challenge is to ensure data security and to define appropriate policies while exploiting the
usability of consumer applications. IT departments therefore have to achieve both objectives: increased
usability and ensured security. While several corporations report that they already integrate SGEM
devices into the corporate IT infrastructure, issues remain in reconsidering existing and introducing new
policies and governance models. These polices and models are needed to ensure a secure and stable
operation, while adapting existing and prospective software applications to a competitive level of
usability.
38
Innovation Management
These competing demands of usability and security have led to a situation where IT departments are
viewed as an obstacle to innovation:
“Sometimes we were our own worst enemy, because all we started with was ‘No’ with respect to
security every time anybody talked to us. They got tired of it and started finding other ways to go
about it.” (CIO, Bechtel)
But innovation enabled by SGEM occurs in nearly all parts of organizations. The different departments
strive to employ these devices and often start projects independently from one another. Executives
describe this as a quite unstructured and unorganized process with implications for long-term
operability. The challenge for IT departments is to manage these projects and ensure a certain level of
credibility as a facilitator for innovation:
“In talking with our customers, we find that frequently IT is not in the discussion relative to app
development, mobile or social applications. These are being developed in the business units,
with some third party. Often they’re coming out of the marketing department working with media
firms who have gone into the IT space. What’s concerning is, ‘Are these groups taking
responsibility for the operations, and ensuring that this is all going to work and be secure?’ And
the answer is usually not.” (VP of Strategy and Product Line Management, CompuWare)
This requires a change in how IT departments interact with the business units. The challenge for
corporate IT is therefore to manage these innovation projects and bundle the efforts without slowing
down the process:
“[…] we’re trying to push IT people into the business units, because when you are stuck in the
back office, you can’t know everything about what the company is doing. You’ll be missing the
innovation engine, which is the most important part, and which we believe will come from the
business, not from IT.” (CIO, Nestlé)
Software Development Style
To satisfy the expectations of the business units, IT departments see themselves also challenged by a
new paradigm of software development. While conventional software development often takes a
waterfall approach and adheres to rigid plans, application development for SGEM is agile, relies on
flexible, iterative planning cycles, and focuses on delivering working software frequently (Dingsøyr,
Nerur, Balijepally, & Moe, 2012; Fowler & Highsmith, 2001). This has led to a situation where corporate
IT finds itself in competition with third party software developers from the consumer application market,
also because corporate IT often needs to comply with internal process regulations. This challenge is,
for example, manifested in the approach of some IT departments to establish a second track for
software development:
“We set up our own mobile application development organization to compete with the third
parties that the business units go to. We’re saying, ‘Let us be one of those. Let us compete for
the same business, but on their terms, not as an IT group. If you need it in three weeks, we will
have it to you in three weeks. We scrapped our old development methodologies because
they’re just too big and too cumbersome and take too long.” (CIO, Bechtel)
39
Staffing
Adapting to these new expectations on usability and software development cycles also creates staffing
problems. The challenge is that usually the right talent is still absent within IT. This starts with the right
skill-set to develop user-friendly applications:
“[To develop a] total[ly] different UI, that is totally intuitive to our employee, […] a whole different
skill-set for IT [is needed]. So you have to really take a step back and say, […] Intuitiveness is a
very important component, and the UI may not be the same on your mobile devices.” (CIO,
Time Warner Cable)
In addition, IT employees not only need an understanding of IT, but also of the business activities IT
should support. CIOs realized this challenge and recognize that they have to redefine their role profiles:
“We hire folks that fit very well into an ERP organization. ERP is important, but it’s not what
differentiates performance for us. So after looking at that, we’re hiring dual-degree people who
can apply technology to the business problems we’re facing. We have a large IT organization
that’s perfectly suited for the problems we’ve had over the last decade. But when you look at the
problems we’re going to have in the next decade, we don’t have the skills that we need.” (CIO,
Chevron Global Upstream)
IMPLICATIONS AND DISCUSSION
The results reveal that SGEM creates several opportunities for corporations to achieve relative
advantages. However, to obtain such advantages, corporations face a series of challenges. Even when
corporations are not exploiting these opportunities, SGEM creates additional needs to respond, as
these new technologies are so invasive that they change the perception of what IT should look like and
what to expect from an application. This is evident from the sample data and also supported by a recent
study (Harris et al., 2012), which showed that employees and business units are not satisfied anymore
with the established standards in professional computing. This section will present some implications
for organizations that become evident from our findings.
Prepare for increasing ubiquity
With the technological development ongoing, it becomes even more substantial for IT departments and
business units to collaborate. There are predictions that by 2020 a possible 50 billion devices will be
connected – from conveyor belts and machine parts to automobiles and wearable devices. The
“Internet of Everything” has been named one of the top technology trends in 2014 by Gartner (Gartner,
2013). This means for companies that currently embedded IT structures inevitably will become
ubiquitous and mobile devices will make use of sensor technologies and context awareness to provide
information (Aarts & Encarnação, 2006). Corporate IT departments will need to provide the appropriate
technological infrastructure, but also take changing behavior in human-computer interaction into
account. While the advent of ubiquitous computing might increase productivity on the one hand, it also
raises security and privacy issues, that companies will have to prepare for (Amoroso, 2013; Fleisch &
Tellkamp, 2006; Friedewald & Raabe, 2011).
Enabling innovations
Our findings show that while SGEM offers some promising opportunities for organizations it can cause
a range of challenges for IT departments, which are expected to ensure efficient operations, but also to
support the business units in a more dynamic and innovative way to facilitate their projects and
40
activities. These objectives are perceived as competing, and most IT departments focus on
operations, not on innovation. This need for a balanced role of IT departments, of being on the one
hand operational and on the other hand, innovation-focused is also evident in initial approaches to
overcoming the new challenges created by SGEM. For example, one approach is the definition of core
services where operations are ensured, and a flexible boundary where innovation is facilitated.
Through this approach, the IT department maintains core services and grants access to additional
services. This is also supported by a recent study (Drnevich & Croson, 2013) that argues that IT both
enhances current capabilities and enables new capabilities and therefore is required be critical to an
organization’s business level strategy.
Adopting a new role for IT in organizations also has managerial implications. We believe that IT
departments need to be aware that ensuring operations alone will not satisfy the organization’s needs
for IT in the future. We recommend considering a new strategic positioning of IT departments to fulfill
both roles, ensuring operations and facilitating innovation. This will require new capabilities in IT
departments, demanding a broader business understanding and sometimes hiring new people. Since
technology is an important enabler of business success it should be seen as an essential part of an
overall digital strategy.
Toward a digital business strategy
Therefore, these new expectations of IT require IT departments to restructure and rethink the existing
approaches and role of IT within the organization. In the academic literature, this issue is part of the
research stream on IT alignment (Oh & Pinsonneault, 2007), but the objective of IT alignment is limited
to aligning IT objectives with the business objectives of the organization. However, in the past it has
often been the case that business strategy has directed IT strategy, while recent studies stress the
importance of a common and pro-active digital strategy (Bharadwaj, El Sawy, Pavlou, & Venkatraman,
2013; Mithas, Tafti, & Mitchell, 2013). Our results suggest that SGEM requires IT alignment to go even
further than just aligning the objectives. IT departments are now required to collaborate much more
closely with business units and not only aligning the objectives, but go further and be a part of the
business objectives.
This also challenges the established typologies of IS strategies, like that of Chen et al. (Chen, Mocker,
Preston, & Teubner, 2010), which suggests that an organization’s IS strategy falls into one of three
categories: IS innovator, IS conservative, or is simply undefined. Reflecting on the results, we suggest
that successful IS strategies require balancing the two extremes of IS innovator and IS conservative
and adopting both objectives. Going forward this perspective might also develop further. With IT
departments and business departments having to collaborate more closely, we argue that it will be
necessary to develop a common digital business strategy. This has also been confirmed by the work of
(Bharadwaj et al., 2013), who argue that IT strategy should not be subordinate to or even separate from
business strategy, but to merge both into a digital business strategy, which extends its scope beyond
traditional boundaries and covers digitization of products and services and the information around them
as well as transcends current functional and process silos.
CONCLUSION
In this research we have explored the opportunities and challenges that mobile technology creates for
corporate IT departments. We conducted three expert group interviews and twelve interviews with CLevel executives from multinational corporations. The findings suggest that SGEM on the one hand has
great potential to enhance business success in sales, service and internal efficiency, but on the other
hand creates challenges for corporate IT in innovation management, software development style,
staffing and balancing usability and security. We argue that IT departments need to prepare to not only
41
ensure operations but see themselves as enabler of innovations. This will be even more essential in the
future when devices become increasingly connected. In addition to this organizations should not see IT
objectives as subordinate to business objectives but merge both into a common digital business
strategy.
However, this study is subject to several limitations. As we follow an explorative approach, we do not
test for any relationships or causalities. The work contributes to existing theories on IT strategy, but still
needs further empirical validation. Beyond the gathered qualitative data, we recommend that future
research collect quantitative data too and apply a longitudinal research approach. Nevertheless we
think that our results provide valuable insights into the challenges and opportunities of enterprise
mobility for practitioners as well as for researchers.
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Author Biography
Sabine Berghaus is research associate and PhD student at the Competence Center Mobile
Business at the University of St. Gallen. Previously she has worked as senior information architect at
SapientNitro on a number of corporate portal, user interface, e-commerce, and mobile projects for
clients from various industries. Her research interests focus on mobility and technology-enabled
collaboration and its effect on organizations.
Thomas Sammer has earned his PhD in business innovation at the University of St. Gallen and
has been visiting researcher at the Center for Digital Strategies at the Tuck School of Business at
Dartmouth. Since 2014 he is a senior consultant at Namics with a focus on mobile business.
Hans Brechbühl is the Executive Director of the Center for Digital Strategies and an Adjunct
Associate Professor at the Tuck School of Business at Dartmouth. Hans leads the center’s outreach
and partnership-building efforts, building relationships with Global 1000 corporations in the Americas
and in Europe. His research interests focus on the organizational dynamics in a collaborative,
networked environment and the enabling role of information technology in today’s corporations. He is a
judge for the annual CIO 100 Awards and a member of the World Economic Forum’s Global Council on
“The Future of IT Software and Services”.
Andrea Back is professor and director of the Institute of Information Management at the
University of St. Gallen since 1994. She is head of the Competence Centers Business 2.0 and Mobile
Business. Her research focuses on social business software applications, future workplace, mobile
business and knowledge & corporate learning management with a focus on management frameworks
and methods.
45
Journal
J
ISSN #104 1-2808
A Publiccation off the Assoociation of Managgement
____________
__________
___________
__________
__________________________________________________ ENRICHIN
E
NG ENTERPRISE D
DATA MO
ODELS:
INCORPO
ORATING
G ACTIVE TAXONO
OMIES
Peter Aik
ken, Virginia Commonwe
ealth Universsity, Richmo
ond, Virginia,, USA
Long Flo
ory, Virginia Commonwe
C
alth Universsity, Richmon
nd, Virginia, USA
Amita
A
Goyall Chin, Virgin
nia Common
nwealth Univversity, Richmond, Virgin
nia, USA
AB
BSTRACT
E
Effective infformation and
a
system
ms remains an importtant potenttial competiitive advantage for
o
organizations and an important
i
IS
S leadership
p responsib
bility. Enterrprise data models (EDM) are
rrequired components of
o any inte
egration solution. Mana
aging the EDM betterr, permits business
le
eadership to
o more easily collabora
ate with IT to leverage an enterprrise's sole, n
non-depletab
ble, nond
degrading, durable,
d
strategic asset – its data! We
W describe
e the processs of enriching EDMs with active
taxonomies and demons
strate the uttility that the
ese enriched
d enterprise
e data mode
els can have
e both on
o
organizational productiviity and on increasing the
e utility of ED
DMs.
K
Keywords:
Enterprise
e data, Data
a models, Ta
axonomies
INTR
RODUCTIO N
E
Enterprise in
nformation architectures have long been
b
consid
dered key to improving e
enterprise in
ntegration
((Chen et al.,, 2006). Lac
ck of integrated informattion consum
mes inordinatte enterprise
e resources that can
b
be more effe
ectively deployed elsew
where. When
n this occurss both IT prrojects and dependent business
o
operations ta
ake longer, cost more, and deliverr less, at inccreased riskk levels. Entterprise data
a models
componentt of informattion integrattion solution
((EDM) are foundational
f
ns and have
e proven the
emselves
invaluable in
n such divers
se domains as power management
m
and cyber ssecurity ana
alysis (Cheniine et al.,
2
2014; Shash
hidhar et al., 2010), de
eveloping us
seful data w
warehousess (Shashidha
ar et al. 20
010), and
b
business con
ntinuity management (Ba
ajgoric, 2014
4).
W
We present a validated
d means off enriching traditional E
EDM by inccorporating active taxo
onometric
ccapabilities. These capabilities 1) permit better use o
of existing EDM and 2) facilita
ate EDM
improvements – to corrrect internal errors and
d evolve refe
ference EDM
M more dire
ectly into en
nterprisesspecific versions. We illu
ustrate the utility
u
of these
e capabilitie s as experie
enced by a large IT orga
anization.
T
These resu
ults provide promise for broaderr-based ap
pproaches iincorporating
g more on
ntological
ccapabilities in the future..
46
Enriching Enterprise Data Models: Incorporating Active Taxonomies
The next section of this paper describes how EDM provide the necessary underpinnings for achieving
enterprise integration. Next, we describe typical challenges to successful enterprise modeling – ranging
from their enormous complexity to lack of internal diagnostic, correction, and improvement mechanisms.
We describe the EDM enrichment process and illustrate the use of active taxonomies to evolve EDM
more rapidly. We describe the evaluation process, the results, and our assessment. The paper
concludes with some suggestions for future research.
EDM ARE FOUNDATIONAL TO AUTOMATED ENTERPRISE INTEGRATION
“Essentially, all models are wrong, but some are useful.” (Box et al., 1987)
This section describes how EDM provide the necessary underpinnings for achieving enterprise
integration. EDM are a necessary but insufficient prerequisite to automated enterprise integration.
Automated enterprise integration has long been a goal and EDM have always been part of the solution.
A traditional definition of EDM would include building definitions from models to data models and then
to enterprise data models.
A model is a representation of something else. Consistent across multiple definitions is the concept that
the model is of a smaller scale than the thing/concept being modeled. Useful models formally describe
the essence of the modeled object. Similarly, information exchanged using the model constitutes an
essential set of information shared between the two exchanging systems.
Data models are widely understood to be representations of arrangements of things/concepts that the
organization wishes to maintain formally. Data are organized into attributes. Attributes are grouped into
entities. Entities are grouped into models. Models specify arrangements of data attributes representing
modeled details, grouped into data entities corresponding roughly to business concepts, and formally
arranged into models representing conceptual relationships of interest to the organization. Data models
were first used to develop databases for cooperating software programs (Chen, 1976). Software
program families can share data definitions at the attribute, structure, and model levels. This is
immediately useful because data must be perfectly fit-for-use at the most atomic level to avoid an array
of technical challenges. (Model views and other technical devices can be implemented to
programmatically control variability.) System-wide data sharing has long been an ERP goal (Beard et
al., 2004).
When the scope of the data modeling extends beyond a family of systems, it is referred to as an
enterprise data model. In this capacity the EDM function as the specifications required to achieve
integration – optimized to support enterprise strategy.
Most are familiar with the traditional paper/electronic based representations (See Figure 1) including
those maintained using CASE tools. However, EDM can exist in alternative forms including:



Conceptual models existing in the minds of various domain experts;
Model components encoded as rules in various ETL facilities; and
Anything that is used to translate data from one form/format to another.
In all instances, a definitive representation of the source data arrangement and the target data
arrangements are required before it is possible to specify any data transformation operations.
The sum of these and other architectural components constitute the knowledge of the enterprise's data
arrangements – technical knowledge required before any transformation can occur. At the enterprise
level, sharing is optimized when the EDM scope is enterprise-wide (Leonard et al., 2012). In practice,
47
Figure 1. Visual Representation of an Enterprise Data Model
EMD rarely covers the entire enterprise but have proven sufficient utility to be recommended as an
essential component of enterprise strategy (Ross et al., 2006).
Organizations employ their data and other strategic assets in pursuit of strategy. As part of coordinated
efforts, different groups often need data items in other forms. Since these disparate systems were not
designed to work together, they do not automatically interoperate. Systems are built with unacceptable
data variations and thereafter require more resources to operate as well as interoperate.
Data transformations are required to achieve the interoperability. An important goal of interoperability is
minimization of transformation effort. Optimization occurs with 100% automation of enterprise data
transformations replacing manual processing and diagnostics. All organizations suffer to some degree
from poor quality data (acting as fuel) – that is data that isn't fit for use. Data can suffer along an array
of dimensions arranged from architectural to model to value to representational (Yoon et al., 2000). The
suffering comes in the form of confusion and errors resulting from homonym, synonym, incompatible
field types/lengths, inadequate documentation, and other data challenges.
Enterprise integration efforts seek to achieve improvements by facilitating the interaction among
organizations, individuals, and systems (Petrie, 1992). Enterprise integration goals focus on improving
the overall performance of large, complex systems in areas such as processing efficiency, unit
responsiveness, and perceived quality.
48
Figure 2. Spoke and Hub Integration
Application 1
Application 2
Application 3
15 Interfaces
(N*(N-1))/2
Application 4
Application 5
Application 6
Automated integration depends on a conceptual spoke and hub model as shown in Figure 2, and
differing implementation configurations are possible (Nachouki et al., 2010). The appeal of this
approach is based on its three-way scalability that permits variations in the:
1. number of data items (ideally data structures) from each system are to be shared;
2. number of applications connected to the hub;
3. amount of interconnectivity among hub-connected systems.
By varying these three we can describe all integration challenges. In order to implement automated
solutions to these challenges, we must encode various transformations, control their scope and
respond to changes in the volume of data exchanged.
This code is an instance of the process portion of an input  process  output version of the EDM.
Integration is not possible without the implementation of a governed vocabulary (attributes), rules for
what constitute various enterprise concepts (entities), and rules for how they relate to each other
(relationships), combined into an information architecture, representing the essential data that governs
enterprise operations. Poor management of this metadata detracts from organizational performance
(Lee et al., 2003).
CHALLENGES TO SUCCESSFUL ENTERPRISE MODELING
We describe typical challenges to successful enterprise modeling – ranging from their enormous
complexity to lack of internal diagnostic, correction, and improvement mechanisms.
Everyone agrees that using an enterprise data dictionary to achieve common vocabulary is both a good
idea and produces tangible benefits. So why are we not getting better results? Organizational data
management capabilities have not improved over the past 25 years (Aiken et al., 2011). Data volume
has certainly increased markedly, presenting enterprises with increasingly challenging problems to
solve. Fundamentally the characteristics of problem resolution follow the de facto ontology design
criteria from (Gruber, 1993).
49





Clarity: Ontology vocabulary should be objective in the intended meanings.
Coherence: Ontology should be logically consistence.
Extendibility: Ontology should be easily expended with minimal workload.
Minimal encoding bias: Ontology should be independent of implementation mechanisms.
Minimal claims: Ontology should make minimal claims about the domain.
Achieving these has been difficult at enterprise level and more successful at the business domain level
(Calhau et al., 2010).
General Modeling Difficulties
Modeling difficulties are compounded by incorrect documentation – be it missing or inaccurate. This
can be compounded by difficulties achieving appropriate access to SMEs and SME/Analyst
communication that is properly incentivized to share and trained to do so. Enough time must be
allocated to analysis to ensure subsequent phase success. The pressure of that time spent doing
analysis is not viewed as productive by non-system builders. Since data evolve, they can behave
perversely unlike projects (Bernstein et al., 2008).
Specific EDM Difficulties
Aside from general modeling difficulties, EDM are complicated by highly complex subject matter and
deficiencies in the tool-base.
EDM Complexity
EDM are voluminous and complex. Below are statistics from recent EDMs with which we have worked.




ADRM has hundreds of entities.
FTI contains almost 700 entities and more than 3,000 attributes.
The three PeopleSoft modules (pay, personnel and training are often implemented as a set)
contain approximately 7,000 data attributes instantiated approximately 26,000 times on 1,400
screens.
SAP out of the box contains tens of thousands of tables.
For the novice user, these volumes represent a cognitive nightmare and it can take months to become
familiar with a single EDM (Lee et al., 2003).
Lack of Capabilities
EDM typically exist within traditional CASE tools and suffer from generally primitive search functions
such that users desiring access to EDM contents are limited to either:



Exact term matching (searching for entities, attributes, or definitions);
Browsing (I'll know it when I see it);
Or both.
For example, a user wanting information on “customers” from EDM would type “customer” into a dialog
box similar to Figure 3. Unaided the EDM returns all metadata with the word “customers” in title or in
the definition – diving directly from the forest to the leaf level. As a result, users miss opportunities to
get information on related concepts such as “member” and “guest.”
50
Figure 3. Typical CASE Tool Query Facility
If a data map contains these concepts, they can be understood easily with a glance. Data maps
typically do not exist for the conceptual, rule-based, or transformation rules referenced previously.
Reference Data Model Use
Reference data models are a subset of EDMs designed to act as a guide/overview for a specific
domain. Organizations acquire reference data models (RDM) to guide their evolution. Numerous
reference EDMs are sold by organizations such as IBM, Teradata, Financial Transactions International,
ADRM Software, etc. The RDM value proposition rests on domain specific customization and therefore
relevance to the purchaser. Reference models can be purchased for retail, financial services, insurance,
healthcare, etc.
Purchasing organizations analyze their existing (as-is) information architecture capabilities, against the
best practices represented by the RDM. That is the two models are compared. The purchaser
conceptually maps its existing environment against the reference model. The enterprise keeps those
aspects it liked of the old system and combines those with aspects of the reference model and
develops a target, or to-be, architecture as a development goal. The reference EDM severs as a
bridge/framework helping the organization migrate towards better industry practices embedded within
the reference EDM. Reference models are sold and treated as read-only products – incapable of
evolving with the enterprise. Instead they are updated periodically as releases from the vendor.
THE EDM ENRICHMENT PROCESS PERMITS MORE RAPID EDM EVOLUTION
“Enrich:
To add greater value or significance to – to enrich the mind with knowledge;
To make finer in quality, as by supplying desirable elements or ingredients – to
enrich soil”
51
Figure 4. Key is to extend the utility of EDM search to include conceptual neighborhoods.
Keyword Searches
Enterprise Taxonomic Capabilities
(filtering, matching, extensions)
Enterprise Data Model
Exact Matches
Preferred Terms
Synonyms
Extended Terms
We describe the Master Definition Harmonizer (MDH) enrichment process and illustrate the use of
active taxonomies to evolve EDM more rapidly.
MDH Architecture
Figure 4 shows the MDH architecture. It integrates taxonometric capabilities into existing EDM
infrastructures. Without losing existing functionality, analysts will have broad new ranges of
classification, exploration and analysis capabilities.
Any EDM or data model maintained in using popular CASE tools can be exported (using off-the-shelf
spreadsheet technologies) to form EDM taxonometric seed metadata. This is used as a seed file and
compared against thousands of domain specific relationships existing in a COTS taxonomy product
(see Figure 5) through an auto-classification process.
The MDH analyzes all existing relationships against any existing taxonomy. Essentially all parentchild/child-parent relationships are compared in context to all other items. Additional cycles incorporate
coagulation, sub-division, textual substring, and synonym analyses (see Figures 6, 7, and 8) with a goal
of normalizing the vocabulary. Possible matches and logical suggestions as to how the metadata
should be structured are pushed back to the original CASE tool-based model.
The steps required to create a useful version are depicted in Figure 9 and described below.
1.
2.
3.
4.
Extract metadata from existing, un-enriched EDM.
Develop EDM taxonometric seed metadata.
(Re)Establish EDM base-line taxonomy.
Evaluate results/improve EDM taxonometric seed (Repeat from Step 3 with increasing
refinement).
5. Achieve good enough starting EDM taxonomy.
6. Periodically enrich version of the EDM using the EDM taxonomy.
7. Refine terms and re-issue ARM Taxonomy.
5
52
Enriching
E
Enterrprise Data Moodels: Incorporating Active T
Taxonomies
Figu
ure 5. Some
e of the thou
usands of rellationship exxisting in a C
COTS taxono
omy productt
(Wand
d, Inc., 2013
3).
Figu
ure 6. Sub-division ana
alysis resultss
ystems, Vol. 24,
2 Number 3, 2014
53
P
Peter Aiken, Lo
ong Flory & Amita
A
Goyal Ch
hin
Figure
e 7. Textuall substring a
analysis resu
ults
D
During Phas
se I, Steps 3 through 5 repeat until the team ju
udges a suffficiently rich or satisfacttory EDM
taxonomy ha
as been cre
eated – this
s has been repeatedly accomplish
hed in five o
or fewer cyycles and
returns afte
cconsistently reaches the
e point of diminishing
d
er ten cycle
es. Phase III begins once 'good
e
enough' has
s been achie
eved the ED
DM taxonom
my is periodi cally improvved using a manual approach –
ccycling between Steps 5-7.
5 We will illustrate this
s process ass implementted and evalluated by ou
ur subject
d
data architec
cts in the nex
xt section.
gure 8. Syn
nonym analyysis results
Fig
54
Figure 9. Development and use of active taxonometric capabilities
Phase I:
Taxonometric
Seeding
Develop Seed
ADRM Taxonomy
ADRM
Metadata
Develop Seed
ADRM Taxonomy
No
Good
Enough
Starting
Seed?
Yes
ADRM
ADRM V+1
ADRM
Taxonomy
Phase II:
Taxonometric
Improvement
Capabilities
Once the seed has been established but before iterative refinement has begun, it is possible to
enhance query results in a number of ways including the following.




Contextualizing search response visually by illustrating portions of one or more trees to which
the search belongs. This permits 1) resolution of multiple trees to a single authoritative tree and
2) refinement of the original query term into more domain specific contexts.
Enhancing this above information using various counts to illustrate the quantity of occurrences
with each category.
Status of various taxonomy modifications such as unevaluated, proposed, and standard.
Generating ERD configurations illustrating relationships between related entities.
Standard learning capabilities are incorporated where systematically variation candidate terms are
exposed for analysis and harmonization by SMEs/stewards/analysts. Workflow capabilities compliment
existing practices. The refinement process enriches EDM with taxonometric capabilities permits new
searches to return conceptually "surrounding" results including (See Figure 10):




Exact term;
Related terms;
Frequently examined next terms;
Related data sources;
55
P
Peter Aiken, Lo
ong Flory & Amita
A
Goyal Ch
hin










Applicable subjec
ct areas;
Relatted application sources;
Cross
s-referenced
d terms;
Broad
der/narrower/Not related
d terms;
Prefe
erred terms;
Exten
nded terms;
Syno
onyms;
Homo
onyms;
Associated goverrnance/busin
ness roles; or
o
Steward coverag
ge.
F
Figures 11 and
a 12 illustrrate the refinement proce
ess occurs a
as users worrk with termss. Capabilitie
es permit
a
analysts to quickly
q
confirrm and sepa
arate and strructure the m
metadata. T
The enrichme
ent process presents
term analysis, permittin
ng knowledg
ge workers and subjecct matter exxperts to ad
dd metadata further
cclassifying them
t
as brroader, narrrower, relate
ed, etc. Fig
gure 12 illu
ustrates how
w these ca
apabilities
a
accelerate model
m
unders
standing.
ASSESSING OF THE RES
SULTS AND THE ASS
SESSMEN
NT
W
We describe
e the evaluattion process
s, the results
s, and our asssessment. We were fo
ortunate to b
be able to
o
obtain hands
s on review
ws of the acttive taxonom
mic capabilitties working
g with data architects in
n a large
o
organization. They work
ked with a copy
c
of an ARDM referrence mode
el for a yearr as we evo
olved the
technology used
u
to imple
ement B.
Figurre 10. Taxonomy Refine
ement Facility
5
56
Enriching
E
Taxonomies
Figure 11. Taxono
omy Refinem
ment Capabillities for furth
her refining tthe initial au
uto-classifica
ation
Figure 12.
1 Taxonom
my Refineme
ent Capabilitties for refining the hiera
archy
ystems, Vol. 24,
2 Number 3, 2014
57
Primary Usage Scenario – Making sense of the EDM
Querying ARDM (in its native modeling environment) for the term "customer" resulted in more than 100
hits among the entities, attributes, and definitions. Each of the 23 models containing the terms
customer were individually opened and browsed. Individual result sets were copied to an integrative
spreadsheet. Considerable effort was expended to obtain an integrated results set and thus a "holistic"
picture, alphabetized as shown in Figure 13. For an analyst new to the domain the results are at once
overwhelming and misleading.
Working through the Phase I auto-classification cycles resulted in an initial customer metadata
hierarchy showing:
Customer Categories [occurrences]
Customer Support [16 expanded]
Customer order product
Customer order product allocation
Customer account channel product summary
Customer account product distribution
Manufacturer customer account exclusion
Manufacturer customer exclusion
Customer finance term
Customer sales term
Customer spouse (party)
Customer spouse employment
Customer currency usage
Customer language usage
Customer shipment method
Customer activity
Customer ancestry
Customer event
Customer Categorization [30]
Customer Value (Marketing) [16]
Customer Accounting [10]
Customer Restriction [5]
Customer Property [27]
That is, the seeding phase returned six categories of customer data and grouped 16 attributes into the
"customer support" category. This greatly simplified the cognitive load on the analysts. Another
capability permitted analysts to display concepts grouped as an ERD of Figure 14.
Combined these new capabilities were well received by the analysts. It was unanimously agreed that:




Proof of concept was overwhelmingly demonstrated;
From the user perspective modern search capabilities were easily incorporating into the various
analysis processes;
MDH permitted programmatic harmonization of literally many models within EDM framework;
and
Already the system had paid for itself saving hundreds of hours of analyst time.
5
58
Enriching
E
Taxonomies
Figure 13. Terms returrned from AD
DRM in resp
ponse to a se
earch for "cu
ustomer"
Figure
e 14. ER Mo
odel Generatted using MDH
ystems, Vol. 24,
2 Number 3, 2014
59
P
Peter Aiken, Lo
ong Flory & Amita
A
Goyal Ch
hin
U
Unintended Usage Sce
enario – Dia
agnosing an
nd Improvin
ng the EDM
A
An additiona
al use for the
ese capabilitties arose during the co
ourse of the evaluation. During the prior two
yyears of EDM
M use, the organization had collecte
ed a numberr of questions/concerns. These inclu
uded:
S
Structural Fla
aw Categories








Incon
nsistent Entitty Definitions
s
Incon
nsistent card
dinality acros
ss models
Conc
cept inconsis
stencies: Same Entity us
sed in differe
ent taxonomy contexts.
In appropriate joining of independent con
ncepts
Struc
ctural Incons
sistencies
ping)
Incon
nsistent and lack of use of categorization (subtyp
Sema
antic Confus
sion
Missing structure
es and conce
epts
C
Combined, iff true, these
e categories could make
e it difficult to
o use as refe
erence model. The taxo
onometric
ccapabilities were
w
judged invaluable by
b the analy
ysts who prefferred the crrude, beta-version softw
ware to its
a
absence. Th
heir estimate
es were thatt they spentt 80% of the
eir time atte
empting to figure out the project
ccontext and 20% addres
ssing the acttual problem
m. Just lowerring their loo
ok-for time frrom 80 to 60
0% would
in effect double their productivity.
p
This permitted accura
ate diagnosttics required
d to investiigate the
p
potential EDM flaws. The
e ROI was affirmed
a
to be positive.
Figure 15. Acttive Linked T
Taxonomies
CONCLU
USIONS AN
ND SUGGE
ESTIONS F
FOR FUTUR
RE RESEA
ARCH
O
Our work has resulted in
n a set of capabilities rep
presented in
n Figure 15 a
adopted by tthe host organization
a
as best prac
ctices. As da
ata gets bigg
ger it will be increasinglyy important tto develop ccapabilities to
o help us
m
make sense of it all. Sy
ystems are built
b
with un
nacceptable data variatiions and the
erefore requ
uire more
60
resources to operate as well as interoperate. Semi-automating this process makes use of EDMs more
palatable and increases likelihood of overall success by reducing the scale of the challenge.
References
Aiken, P. H., Gillenson, M., Zhang, X., & Raffner, D. (2011). Data Management and Data
Administration: Assessing 25 Years of Practice. Journal of Database Management, 22(3), 24-44.
Beard, J. W. & Sumner, M. (2004). Seeking strategic advantage in the post-net era: Viewing ERP
systems from the resource-based perspective. Strategic Information Systems, 13(2), 129-150.
Bernstein, P. A. & Haas, L. M. (2008). Information Integration in the Enterprise. Communications of
the ACM, 51(9), 72-79.
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Wiley & Sons: New York, NY.
Calhau, R. F. & Almeida, F. D. (2010). An Ontology-based Approach for Semantic Integration. In:
14th IEEE International Conference on Enterprise Distributed Object Computing (EDOC), 111-120.
Chen, D., Doumeingts, G., & Vernadat, F. (2008). Architectures for enterprise integration and
interoperability: Past, present and future. Communications of the ACM, 59(7), 647-659.
Chen, P. P.-S. (1976). The Entity-Relationship Model - Toward a Unified View of Data, ACM
Transactions on Database Systems, 1(1), 9-36.
Chenine, M., Ullberg, J., Nordström, L., Wu, Y., & Ericsson, G. N. (2014). A Framework for WideArea Monitoring and Control Systems Interoperability and Cybersecurity Analysis. IEEE
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Gruber, T. R. (1993). Toward Principles for the Design of Ontologies Used for Knowledge Sharing
(Technical Report KSL 93-04). In: N. Guarino & R. Poli (eds.), International Workshop on Formal
Ontology, Padova, Italy.
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the ACM, 46(2), 54-60.
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231-259.
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Systems. The International. Journal of Database Management Systems, 2(1), 60-79.
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Wand, Inc. (2013). Enterprise Taxonomies. Retrieved from http://www.wandinc.com/wand-taxonomy-libraryportal.aspx
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Author Biography
Peter Aiken founded Data Blueprint (an internationally recognized data engineering company)
in 1999 and is an Associate Professor (Information Systems/Virginia Commonwealth University). His
experience and research has widely explored data and its relationship to systems and business
engineering. He is the author of Data Reverse Engineering and Clive Finkelstein's co-author of Building
Corporate Portals Using XML (McGraw-Hill 1996/99). His sixth book XML in Data Management is coauthored with David Allen. He has held leadership positions with the US Department of Defense and
consulted with numerous organizations around the world. His research has appeared in the
Communications of the ACM, IBM Systems Journal, IEEE Software, and others. He holds Senior
Membership in ACM & IEEE. He was DAMA International President 2009-2012. He has received two of
their Achievement Awards and the International Stevens Award from the IEEE Computer Society. He
has lectured internationally on data and related topics.
Long Flory is a Senior Analyst and Lead Information Architect at AnalyticArt (a managerial and
information consulting firm). She is also a PhD candidate (Information Systems at Virginia
Commonwealth University). Her experience and research have encompassed data quality and
governance, business analytics, big-data processing, information architecture and mining, knowledge
management, decision support, risk management, process improvement, and human resource
management. Her research has appeared in AMCIS, INFORMS, Human Resource Management, etc.
She has developed dozens of innovative and practical solutions that leverage data and technology to
drive value-added business results. She regularly delivers curriculum and lectures in academic and
corporate colleges/universities around the world. She has received various Excellence Achievement
awards.
Amita Goyal Chin is an Associate Professor in the Information Systems Department at Virginia
Commonwealth University. She received her B.S. in Computer Science and M.S. and Ph.D. in
Information Systems, all from The University of Maryland at College Park. Her research interests
include database systems, data management, and data governance. Her research has appeared in the
Communications of the ACM, Journal of Computer Information Systems, Journal of Database
Management, and others.
6
62
ystems, Vol. 24, Number 3, 2014
INFORMATION
63
INFORMATION
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Balancing Innovation and Operations

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