journal of management systems - dartmouth college

JOURNAL OF MANAGEMENT SYSTEMS

The Flagship of the Association of Management

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 Q B. Chung 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

Anil K. Aggarwal University of Baltimore, USA

Dorothy E. Agger-Gupta Fielding Graduate University, USA

JoongHo Ahn Seoul National University, Korea

Steven Alter University of San Francisco, USA

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

Kevin D. Clark Villanova University, USA

Robert Giacalone University of Denver, USA

Richard Grover University of Southern Maine, USA

John Hamilton James Cook University, Australia

Stephen C. Hayne Colorado State University, USA

Clyde W. Holsapple University of Kentucky, USA

Robert Holtfreter Central Washington University, USA

Soon-Young Huh Korea Advanced Institute of Science and Technology (KAIST), Korea

Richard Jacobs Villanova University, USA

Julie Kendall Rutgers University, USA

Kenneth Kendall Rutgers University, USA

Mohamed Latib PeriscopeIQ, USA

Johnny Lee Drexel University, USA

Eldon Li National Chengchi University, Taiwan

Rashmi Malhotra St. Joseph’s University, USA

Michael Mulvey Dublin Institute of Technology, Ireland

Makoto Nakayama De Paul University, USA

Samuel Rabinowitz Rutgers University, USA

Bonnie Roach Ohio University, USA

Elliot B. Sloane Center for Healthcare Information Research and Policy, USA

Detmar W. Straub Georgia State University, USA

Vijayan Sugumaran 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 Villanova University, USA

George L. Whaley San Jose State University, USA

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2 The Continuing Mismatch between IT Governance Theory and Practice

Journal of Management Systems, Vol. 24, Number 3, 2014

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.

Daniël Smits & Jos van Hillegersberg 3


Figure 1. Overview of the Study

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

Literature study

Initial model Result modelDelphi study



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.



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 28% 24% 13% ISO/IEC 17799, ISO/IEC 27000 or other security frameworks 21% 10% 9% Internally developed frameworks 14% 33% Six Sigma 15% 2% 5% COBIT (ISACA) 13% 14% 9% PMI/PMBOK 13% 1% 3% Risk IT (ISACA) 12% IT Assurance Framework (ISACA) 10% CMM or CMMI 9% 4% 4% ISO/IEC 38500 8% BMIS (Business Model for Information Security, ISACA) 8% PRINCE2 6% 2% Val IT (ISACA) 5% 0% TOGAF 3% 0% COSO ERM 2% 1% 4%

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.



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) 484

2nd selection (4/2013–5/2013) + 169

Total selected 665 Remove doubles - 6

Total excl. doubles 659 100% In scope 269 41%

AIS Added (4/2013–5/2013) + 62

Total In scope 331



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’ 25 8% On ‘portfolio’ management 14 4% On ‘architecture’ or ‘portfolio’ management 35 11%

On ‘collaborate’ or ‘collaboration’ 5 2% On ‘behavior’ or ‘behaviour’ 6 2% On ‘culture’ 15 5% On ‘social’ 7 2% On all social related keys 33 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) 1995–2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Total

AIS 7 3 3 3 3

5 7 7 7 17

62 Scopus 5 1 3 8 21 21 30 34 48 60 33 5 269 Total complete set 12 4 6 11 24 21 35 41 55 67 50 5 331

Maturity

1 5 3 4 6 3

22 % of total

5% 14% 7% 7% 9% 6%

7%

Architecture & portfolio

1 1 2 5 3 2 7 9 6

35 % of total

25% 9% 8% 24% 9% 5% 13% 12% 12%

11%

Social aspects 3

1 2 1 1

3 6 5 11

33 % of total 25%

17% 18% 4% 5%

7% 17% 7% 22%

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.



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.



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 decision-making 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.



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 # Type of organization

1 Agriculture 2 Hospital 3 Heavy industry 4 Wholesale 5 Engineering 6 Chemical industry 7 Non-profit 8 Retail 9 Power company 10 Seaport 11 Health insurer 12 City 13 Public health care 14 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).



Table 8. Reporting Line

As a CIO I report to:

CEO 3 21% CFO 8 57% COO 1 7% Other 2 14%

Total 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 5% 10% 10% 10% Max 50% 60% 50% 70%

Mean 18% 33% 22% 27% σ 12% 17% 7% 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 6 5 2 0 % 0 % 46 % 38 % 15 % 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



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 Number of

times mentioned

%

Portfolio management 8 62% Architecture 6 46% Security 4 31% Project and program management 4 31% Demand management 3 23% Innovation 3 23% Process design and management 3 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.



Table 12. Actions to Improve ITG

Action Priority Overall

Group Details 1 2 3 4 5 6 7 Total % %

Responsibility

Good ownership of processes and corresponding applications

3 1 1 5 83%

31%

Process owners (having) 1 1 1 3 50% Responsibility push towards business

owners 1 1 17%

IT fixed on agenda board, with IT present. BPO assigned on senior level on key processes by the board.

1 1 1 3 50%

Confront business with the consequence of their choices

1 1 17%

Strategy Formally approved information management

strategy 1 1 1 3 50% 7%

Acquisition

0% 0%

Performance

Maturity benchmark 1 1 1 1 4 67%

29%

Consider IT as a part of a business project. For infrastructure too!

1 2 3 50%

Determine the fundament: IT is yield driven and not cost driven.

1 1 1 3 50%

Agile IT 1 1 17% Lean IT 1 1 17%

Conformance The CIO role must disappear in favor of a

control instrument 1 1 17% 2%

Human Behavior

Educate business managers 3 1 4 67%

26%

Professionalize the client (NL: opdrachtgeverschap)

1 1 1 3 50%

Communicate and collaborate; business result first

1 1 2 33%

Observe the engagements (more discipline) 1 1 2 33%

Not grouped Simplification 1 1 17%

5% User groups 1 1 17%

42 100%

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



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



‘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 top-down. 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



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



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. References

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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.

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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

Seungjae Shin, Jack E. Tucci & Dustin Odom 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, cross-docking, 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.



DATA COLLECTION A total of 25 companies, including Wal-Mart, are examined in this study. The 24 competitors of Wal-Mart 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 (Pre-RFID, 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, 2008-2013. 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.)

Period 1 Period 2 Period 3

ITR 5.09 (2.87) 5.04 (2.72) 5.43 (3.10) ISR 0.16 (0.06) 0.16 (0.06) 0.16 (0.06) DII 90.06 (38.27) 90.18 (37.29) 86.20 (38.80) GMROII 2.21 (0.92) 2.23 (0.75) 2.31 (0.84) PEGP $49,546.93 (23,003.89) $58,360.08(31,234.56) $64,577.45 (37,056.13)



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.)

Period 1 Period2 Period3

ITR 7.32 (0.30) 7.57 (0.31) 8.30 (0.48)

ISR 0.11 (0.31) 0.10 (0.00) 0.09 (0.01) DII 49.92 (2.11) 48.27 (1.97) 44.11 (2.53) GMROII 2.21 (0.12) 2.53 (0.15) 2.97 (0.19) PEGP $38,267.82 (2,996.60) $43,973.98 (2,015.98) $53,449.13 (2,865.79)

Table 3. Null Hypothesis

Period 1 Period2 Period3

ITR µCompetitor = 7.32 µCompetitor = 7.57 µCompetitor = 8.30 ISR µCompetitor = 0.11 µCompetitor = 0.10 µCompetitor = 0.09 DII µCompetitor = 49.92 µCompetitor = 48.27 µCompetitor = 44.11 GMROII µCompetitor = 2.21 µCompetitor = 2.53 µCompetitor = 2.97

PEGP µCompetitor = 38,268 µCompetitor = 43,974 µCompetitor = 53,449

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)

ITR ISR DII GMROII PEGP

Period 1 (n = 96) -7.595 (0.000)

8.589 (0.000)

22.520 (0.000)

0.057 (0.955)

4.804 (0.000)

Period 2 (n=96) -9.130 (0.000)

10.159 (0.000)

11.013 (0.000)

-3.948 (0.000)

4.513 (0.000)

Period 3 (n=143) -11.093 (0.000)

12.332 (0.000)

12.974 (0.000)

-9.402 (0.000)

3.591 (0.000)



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 1.00000 ISR -0.86178 1.00000 DII -0.87241 0.96601 1.00000 GMROII 0.68350 -0.73302 -0.64109 1.00000 PEGP 0.44709 -0.45714 -0.44586 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 (LN-PEGP) 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.



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) 9.17e-16 DW = 0.2929 0.5233 (2) 4.694e-5 DW = 0.3359 0.5187 (3) 2.01e-4 DW = 0.3226 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 log-transformation, 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.



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, Wal-Mart’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 LN-PEGR. 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

Anderson, D. R., Sweeny, D. J., & Williams, T. J. (2008). Modern Business Statistics: With Microsoft Excel, 3rd Edition. Stamford, Conn: Cengage Learning.

Chandran, M. H. (2003). Wal-Mart’s Supply Chain Management Practices. Retrieved from http://mohanchandran.files.wordpress.com/2008/01/wal-mart.pdf

Dougherty, C. (2006). Introduction to Econometrics, 3rd Edition, New York: Oxford University Press.



Emiliani, B., Stec, D., Grasso, L., & Stodder, J. (2007). Better thinking, better results: Case study and analysis of an enterprise-wide lean transformation, 2nd Edition. Kensington, Conn: Center for Lean Business Management.

Freeman, R. B., Nakamura, A. O, Nakamura, L. I., Prud’homme, M, & Pyman, A. (2011). Wal-Mart Innovation and Productivity: A Viewpoint. Canadian Journal of Economics, 44(2), 486-508.

Gill, P. & Abend, J. (1997). Wal-Mart: The Supply Chain Heavyweight Champ. Supply Chain Management Review, 1(1), 8-16.

Glaser-Segura, D. A., Jack E. T., & Anghel, L. D. (2006). Supply Chain Management and the Romanian Transition. The AMFITEATRU ECONOMIC Journal, Academy of Economic Studies - Bucharest, Romania, 8(19), 18-26.

Horngren, C. T., Datar, S. M., Rajan, M. (2011). Cost Accounting: A Managerial Emphasis. Upper Saddle River, NJ: Pearson Prentice Hall.

Hsieh, C., H. Prudilova, and L. Binshan, (2010). Radio Frequency Identification Systems at Universities: Current Status and Future Applications. Proceeding of 2010 Southwest Decision Sciences Institute Conference. Dallas, TX.

Hunt, D., Puglia, A. and Puglia, M. (2007). RFID – A Guide to Radio Frequency Identification, Hoboken, New Jersey: John Wiley & Sons, Inc.

Mark, K. (2012). Half a Century of Supply Chain Management at Wal-Mart. Harvard Business School Press, 9B12D010.

Qu, T., Luo, H., Cao, N., Fang, J., Zhong, R. Y., Pang, A.L.Y., Qiu, X, & Huang, G. Q. (2012). RFID-Enabled Just-In-Time Logistics Management System for “SHIP” – Supply Hub in Industrial Park. Proceeding of 42nd International conference on Computer and Industrial Engineering, Cape Town, South Africa.

Shin, S. & Ekisoglu, B. (2014). Effects of RFID Technology on Efficiency and Profitability in Retail Supply Chains. Journal of Applied Business Research, 30(3), 633-645.

Visich, J. K., Li, S., Khumawala, B. M., & Reyes, P. M. (2009). Empirical Evidence of RFID Impacts on Supply Chain Performance. International Journal of Operations and Production Management, 29(12), 1290-1315.

Weier, M. H. (2008). Wal-Mart Gets Tough On RFID. Retrieved from http://www.informationweek.com/wal-mart-gets-tough-on-rfid/205900561

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.



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.

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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 ever-increasing 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

Sabine Berghaus, Thomas Sammer, Hans Brechbühl & Andrea Back 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.



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,



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



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 e-mail. 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)



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.



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)



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



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 C-Level 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



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. References

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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.

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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,

Peter Aiken, Long Flory & Amita Goyal Chin 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.



Figure 2. Spoke and Hub Integration

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).

Application 4 Application 5 Application 6

15 Interfaces(N*(N-1))/2

Application 1 Application 2 Application 3



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.”



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”



Figure 4. Key is to extend the utility of EDM search to include conceptual neighborhoods.

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 parent-child/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. Extract metadata from existing, un-enriched EDM. 2. Develop EDM taxonometric seed metadata. 3. (Re)Establish EDM base-line taxonomy. 4. 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.

Enterprise Data Model

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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):

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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.

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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.

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Box, G. E. P., and Draper, N. R. (1987). Empirical Model Building and Response Surfaces. John 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.

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Chen, P. P.-S. (1976). The Entity-Relationship Model - Toward a Unified View of Data, ACM Transactions on Database Systems, 1(1), 9-36.

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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.

Lee, J., Siau, K., & Hong, S. (2003). Enterprise Integration with ERP and EAI. Communications of the ACM, 46(2), 54-60.

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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 co-authored 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.

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I N F O R M A T I O N ____________________________________________________________________________________

Information for Contributors ABOUT THE JOURNAL Founded in 1989, the Journal of Management Systems (JMS) is the flagship publication of the Association of Management (AoM) and its sister organization, the International Association of Management (IAoM). The primary mission of JMS is two-fold: (1) to promote the integration and cross-fertilization of the behavioral/organizational and information sciences and (2) to encourage, sharpen, and expand the dialogue between academicians and practitioners from an interdisciplinary perspective. AIMS AND SCOPE JMS draws from a number of management disciplines including organizational, human resources, and information systems and information technology, and related disciplines. Papers may be empirical articles, theoretical and methodological papers, surveys and field research, practitioner-oriented papers and case studies, position papers on current management issues, integrative and evaluative reviews, and reports of recent technological advances of applied value. High priority is given to manuscripts that cross disciplinary boundaries as well as those with a dual focus on theory and practice. JMS invites new submissions that address a variety of organizational, managerial, information systems and technology issues in contemporary global economy of the twenty-first century including, management education and development, organizational theory, design and development, leadership, team dynamics, business analytics, decision making, globalization, business strategy, strategic alliances and networks, emerging markets, buyer/consumer behavior, supply chain management, international-multinational marketing, operations management, service operations, human resources management, industrial relations, TQM, integrated marketing management communication, corporate social responsibility, ethics, trust, public policy in a changing marketing environment, international management, comparative management, international marketing, organization communication and information systems, health care administration, labor markets, gender and diversity in organizations, cross cultural business practices, entrepreneurship, technology and innovation management, qualitative-quantitative research methods, measurements, and data analyses, conflict management, marketing strategy, services management and marketing practices in "For-Profit" and "Not-For-Profit" environments, B2B and B2C electronic commerce, and excellence in management education and innovative teaching practices, issues, trends, and advances.

64 Information for Contributors


REVIEW PROCESS JMS employs a double-blind, double-peer review process. All manuscripts are read by the Editor-in-Chief, who assesses them for relevance and goodness of fit with regard to the mission and goals of JMS. At this point, a manuscript which is not congruent with the stated purpose of JMS is returned to the author. Manuscripts which pass the initial screening process are assigned to editorial board members, and then undergo double-blind, double-peer reviewing. The journal’s reviewers are selected based on their content expertise and familiarity with the literature and the methodologies employed in the study. Manuscript evaluations are based on the adequacy of the literature review, conceptual development of propositions, quality of research design, adequacy of data analysis, legitimacy of conclusions, and practical significance along with criteria assessing the quality of the author's writing style and clarity of presentation. Not all evaluation criteria may apply to a given submission. JMS reviewers use a standard manuscript evaluation form and provide open-ended comments for both the editors and the author(s). MANUSCRIPT SUBMISSION Authors are invited to submit their manuscripts electronically to the Editor-in-Chief, Q B. Chung, at [email protected]. In addition to submitting manuscripts, any correspondence about manuscripts under review, and other inquiries about the journal should be sent to:

Q B. Chung [email protected] Editor-in-Chief, Journal of Management Systems Bartley 3089 Villanova University 800 Lancaster Avenue Villanova, PA 19085 USA

All submissions must be made in Microsoft Word or a compatible file format, double-spaced throughout (including abstracts, captions, tables, references, acknowledgments, and quotations) with one-inch margins.



Authors should also state in the e-mail message that the manuscript has not been published previously and is not currently under review elsewhere. The entire manuscript should be prepared as one Word document. MANUSCRIPT PREPARATION 1. Manuscripts should be prepared according to the guidelines of the Publication Manual of the American Psychological Association. Manuscripts which not adhere to these guidelines will not be sent out for reviews but returned to the author(s) for format adjustments. 2. Except in unusual cases, manuscripts should not exceed 25 double-spaced pages, including figures, tables, and references. 3. The title page should include the title of the article, name(s) of the author(s), affiliation(s), address(es), phone number(s), and e-mail address(es), and a suggested running head (not to exceed 40 characters). To facilitate blind review, implications of authorship should appear only on the title page. The title page is to be followed by the abstract. The text of the paper should begin on the third page. 4. The abstract consisting of 100 to 150 words should provide a brief, comprehensive summary of the content of the manuscript. 5. Tables, numbered with Arabic numerals, should be arranged sequentially and numbered in the order in which they appear in the text and placed at the end of the manuscript. Each table should have a caption centered above the table; explanatory notes to a table (e.g., probability levels, explanations of abbreviations, etc.) should appear at the bottom of the table. 6. Figures (graphs, line drawings, photographs, charts), numbered consecutively with their respective captions, should also be cited in the order in which they appear in the text. Figure captions should be typed double-spaced on a separate sheet of paper. All illustrations must be camera-ready; photographs must be of professional quality; and drawings should be prepared in ink or press-on tape. 7. Mathematical expressions and notations should be used judiciously and only as required by the subject matter. All symbols must be identified. 8. Footnotes to the body of the manuscript should not be used. Instead, the material they contain should be incorporated in the text. 9. References should be listed alphabetically at the end of the manuscript. References to the same author(s) are arranged according to the year of publication, the earliest first. Text citations must correspond accurately to the references in the bibliography. In the text, for references to the work of up to five authors, all authors should be cited the first time the reference occurs in the body of the manuscript; in subsequent citations the surname of the first

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author should be followed by et al. and the year. Reference citations in parentheses should be arranged alphabetically. The following examples illustrate the correct style of capitalization and punctuation of journal articles and books for the reference section:

Brook, P.O., Russell, D.W., & Price, J.L. (1988). Discriminant validation of measures of job satisfaction, job involvement, and organizational commitment. Journal of Applied Psychology, 73, 2, 139-145. Locke, E.A. (1976). The nature and causes of job satisfaction. In M.D. Dunnette (Ed.) Handbook of industrial and organizational psychology (pp. 1294-1349). Chicago: Rand-McNally. Vroom, V.R. (1964). Work and motivation New York: Wiley.

10. A biographical sketch of each author of approximately 250 words in length must be included at the end of the paper. 11. Word processing: Do not right justify text; left justification only. Tuck all periods and commas inside quotation marks. Use two hyphens for an en (-) dash. Do not use all capital letters for effect in headlines; use upper and lower case letters. Do not double space between paragraphs. 12. The final version of manuscript accepted for publication in the Journal of Management Systems must be submitted electronically as a single Microsoft Word document or in a compatible file format. PERMISSIONS A copyright release must be executed before a manuscript can be released for publication. Contributors are responsible for obtaining permission from copyright owners for figures (reproduced or adapted), tables (reproduced or adapted), or lengthy quotes (500+words) that have been published elsewhere. The Association of Management Publication Agreement is mailed to authors during the final stages of the editorial review process; return of the signed form completes the review process. PROOFS Once a draft manuscript has completed the review process, any remaining typographical errors must be corrected by the author(s) in a timely fashion, usually 48 hours. Authors receive page proofs for final corrections. At this stage, no content changes, additions or deletions are permissible; such changes will be charged to the author(s). When completed, the manuscript is returned to the Editor-in-Chief electronically for final review. Accepted papers are then



forwarded to Maximilian Press Publishers, which publishes JMS quarterly on the journal’s website. Note: The publisher reserves the right to uphold its standards of publication in the market place. All rights are reserved to reject submissions not conforming to publication procedures. SPECIAL ISSUES The Editor-in-Chief commissions special issues on topics that reinforce the mission of the journal and appoints guest editor(s) to lead the development of the special issue.

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