Over time, persistent change may have a considerable effect on the codebases of enterprise resource planning (ERP) systems. Small changes, however, are not always expressions of intentional and incremental transformation. They may result from unplanned but necessary and urgent corrections for repairing undesired functionality that entered the ERP system via previously applied change. Every such repair will affect the performance and prioritization of operational processes and, by extension, influence the business that the system intends to support. We developed a change log data view to assess business impact by classifying repairs into one of two mutually exclusive classes. Repairs are either effective, meaning that the next change delivers the fix, or defective, meaning multiple successive attempts are required to satisfactorily correct the initial erroneous change. Investigating the extent to which both repair types on proprietary codebase customizations affect competence center operational performance, our view delivered two finds. First, change size is a poor indicator for repair resolution efficacy. Second, most repairs appear to be defective suggesting poor codebase change process control. Our data originated from 25 SAP landscapes, representing an average system age of around five years and an average landscape size of 57 ERP system instances.

PurposeDespite the relevance of how enterprise architecture (EA) contributes to organizational performance in contemporary digital technology-driven strategic renewal, little is known about the position of EA artifacts. Therefore, this study aims to build an integrative model of EA artifact-enabled EA value supplemented with a research agenda to enhance our understanding further.Design/methodology/approachThis study leveraged grounded theory techniques and a systematic review approach to develop the integrative model and research agenda.FindingsWe inductively build a model of the position of EA artifacts in EA value creation. Additionally, we elaborate a research agenda that proposes (1) an investigation of the role of an EA practice in successful strategic change, (2) an examination of how to manage EA practice value generation and (3) longitudinal research to gain insight into the evolution of value creation by EA practices.Originality/valueThis study presents a model of EA artifact-enabled EA value, thereby contributing to our understanding of the mechanisms, inhibitors and success factors associated with EA value. Following our model, the proposed research agenda contains future research areas to help us better understand the mechanisms and interrelatedness of EA practices in highly dynamic environments.

IT project portfolio management is in place in most large organizations to effectively manage complex portfolios of IT projects and balance them with business strategy. To achieve portfolio performance, a realistic view of the so-called health of the IT project portfolio is crucial. Nevertheless, portfolio risks can affect the success of a portfolio and the achievement of its strategic intentions. Several studies have been published on criteria that determine the health and risks of a project portfolio. However, current scientific literature lacks a theoretically grounded and practice-based understanding of how a specific occurring risk may affect the future health of an IT project portfolio. Therefore, this study designs and validates a reference model of relationships between portfolio risks and health. We argue that this reference model can help organizations assess and monitor their IT project portfolio risks with greater confidence.

: IT Project Portfolio Management has been implemented in most organizations to effectively manage complex portfolios of IT projects and balance them with business strategy. Several standards for portfolio management have been published, but the scientific literature still lacks a theoretically grounded and practically validated reference model for analyzing the implementation of IT Project Portfolio Management in an organization. Therefore, this study designs and validates a reference model for systematically analyzing IT Project Portfolio Management design choices in an organization in terms of processes, roles, responsibilities, and authority. Organizations can use the reference model to systematically assess their local implementation of IT Project Portfolio Management and identify areas for improvement.

Many organizations have established IT Project Portfolio Management to effectively manage portfolios of IT projects and balance them with their business strategy. Despite quite significant investments in IT projects and following IT Project Portfolio Management best practices, organizations often fail to actually realize the expected value with their project portfolio. To realize portfolio value now and in the future, a periodic assessment of the so-called health and risks of the IT project portfolio is essential. Several portfolio management standards have been published, but the scientific literature still lacks a theoretically based and practically validated approach for assessing IT project portfolio value in terms of health and risk. This study established such an approach for assessing IT project portfolio value, validated in a multiple-case study. We argue that this approach can support organizations in assessing their IT project portfolio in terms of health and risk, identifying areas for improvement, and thus having better control over realizing portfolio value.

The significance of enterprise architecture (EA) in strategic renewal, such as digital transformations, is evident and widely accepted. Firms rely on EA to support strategic renewal, especially digital technology-driven strategic renewal. EA artifacts are used to document and communicate decisions and facts about the EA's current, future, and transition states. They facilitate bridging the communication gap and alignment between business and IT stakeholders. However, despite extant research in the area of EA, its role in strategic renewal, and its contribution to improving organizational performance, EA artifacts' contribution mechanism is still unknown. Therefore, this research explores how EA artifact creation and use facilitate strategic renewal, such as digital transformations. Based on 29 interviews at 4 case firms, we found 17 different EA artifacts and 16 ways EA contributes to strategic renewal, i.e., 16 EA values. Moreover, we determined the interrelatedness of EA values and a model of how EA artifacts contribute to strategic renewal and improved organizational performance. The EA artifact value contribution mechanism described in this study is simple and universal and, thus, has significant implications for both practice and research.

Change to business information systems, like enterprise resource planning (ERP) systems, is inevitable. The problem is that the processes degrading these highly complicated systems during their life cycle are poorly understood. To that end, we present an approach that operates as a degradation lens to view technical change data collected from ERP systems. We reconstruct a customization change stream from available log data and investigate structural degradation effects on one designated ERP system codebase in a system landscape. Our results indicate that, contrary to commonly held belief, changes do not maintain the customization in an initial architectural component but tend to evolve across several functionality clusters to evade degradation. Our data suggest that release-driven, complete redesigns of customized parts of ERP systems take place.

The rapid development of novel, innovative digital technologies significantly impact organizations and their business ecosystem. Organizations must stay abreast of the latest developments and respond to them continuously to remain competitive. Many organizations make significant investments in enterprise architecture management (EAM) to manage the transformation of their complex information technology (IT) and information systems (IS) landscape and to guide their digital transformation. However, empirical research on EAM benefit realization is limited. This research conceptualized EAM as a particular type of dynamic managerial capability. Survey data (N = 110) was used in a set-theoretic approach (fsQCA) to identify EAM configurations that lead to a presence of technical IT capabilities and strategic IT alignment. The results indicate the importance of system changes induced by the EAM function itself to improve technical IT capabilities. Furthermore, setting up clear standards and rules, and developing and planning the migration to target architectures is particularly important to align business and IT in larger organizations. This research contributes to the academic knowledge base on EAM benefit realization and supports the needed reconceptualization and evolution of EA and EAM to better support organizations' digital transformations. Furthermore, the outcomes can help decision-makers justify and guide their EA investments while implementing a digital strategy.

IT project portfolio management has been implemented in most organizations to effectively manage and balance complex portfolios of IT projects with business strategy. Portfolio risks can affect the success of a portfolio and the achievement of its strategic intentions. While recent literature identifies potential risks in sub-areas of ITPPM, a validated comprehensive list of risk factors and an understanding of why these factors are perceived as risks by practitioners is lacking. Therefore, this study designs and then validates a reference set of risks based on practitioners’ experiences with these risks. Our validated reference set of risk factors can be used by organizations to more confidently assess the risks of their IT project portfolio.

The ability to systematically anticipate changes in an increasingly complex environment has been referred to as dynamic capability. Therefore, dynamic capabilities contribute to successful digital transformations. Firms use information about the configuration of people, processes, and information technology-also known as an enterprise architecture (EA)-to enable digital transformation strategies. However, it is unclea r what EA information drives digital transformations from a dynamic capabilities perspective. Hence, we performed a multiple case study to identify the EA-information that drives the dynamic capability for digital transformations. 22 interviews, and the 36 documents we analyzed, were used to establish information inputs and outputs for an EA-driven dynamic capability. This study extends previous research on EA-driven dynamic capabilities with a framework of EA information driving the dynamic capability for digital transformations. Furthermore, decision-makers and enterprise architects of organizations can use our results to organize the information needed for an EA-driven dynamic capability.

As the world of Information Technology (IT) engineering becomes more complex every day, the formal study of project complexity becomes more and more important for managing projects effectively, to avoid poor performance and failure. Complexity is not yet clearly understood nor sufficiently defined and the terminology itself is being overloaded and over-used. This paper is a systematic literature review that attempts to identify and classify proposed definitions and measures of IT project complexity. The results include a map of the identified approaches and definitions, a list of classifications of project complexity, a set of proposed measurement tools and complexity measures available to practitioners. The paper contributes to establishing a common language when discussing complexity, as well as to a better understanding of project complexity and its implications to practical IT engineering projects.

The exploitation of new value propositions enabled by disruptive digital technologies—also known as digital transformations—influences the configuration of people, processes, and technology in a firm and must be considered in the enterprise’s strategy. Strategy planning, i.e., the process that determines strategy, is facilitated by enterprise architecture (EA). Hence, strategic plans are reflected in EA documents called artifacts. Our research identified fifteen EA artifacts that facilitate digital transformations’ strategy planning process through a systematic literature review. Furthermore, a multiple case study in the financial services sector was carried out to verify our theoretical findings. The case organizations show a fragmented implementation of EA artifacts, with each organization having established its own, almost unique, way of using them. Only four of the theoretically conceptualized artifacts were found in all organizations. Moreover, two EA artifacts used in all case organizations were not included in our theoretical conceptualization. In combination with the empirical research, the systematic literature review leads to an improved understanding of EA artifacts and their use in the strategy planning process for digital transformations.

Complexity is ubiquitous in modern IT engineering and project management. It is traditionally associated with risk and failure. But complexity also works: it delivers functionality, creativity, innovation. This paper proposes a conceptual framework to support IT Project Complexity Management in a structured, systematic way, consisting of the following processes: plan, identify, analyze, plan response strategies, monitor and control. The processes interact with each other and with other project management processes; they overlap, are incremental and iterative. They are described in terms of inputs and outputs, with a detailed inventory of available tools and techniques proposed for each process and step.

Complexity is ubiquitous in modern engineering and project management. It is traditionally associated with failure. Also, complexity works! It delivers functionality, creativity, innovation. Complexity management contributes to the success of high-risk IT projects, helps better project understanding, allows for better prioritization and planning of resources. Managing negative complexity reduces project risk. Positive and appropriate complexity are catalysts for opportunities. This paper is a qualitative longitudinal study based on multiple industry project cases, consisting in the repeated evaluation of a set of complexity management tools. The tools were deployed in a classical process framework: plan, identify, analyze, plan responses, monitor, and control. The evaluated tools red-flag and measure complexity, analyze its sources and effects, and plan mitigation strategies. The study aims to provide project managers with methods for increasing project success rates and reducing failure in complex IT project environments.

Developments in big data have led to an increase in data analytics projects conducted by organizations. Such projects aim to create value by improving decision making or enhancing business processes. However, many data analytics projects still fail to deliver the expected value. The use of process models or methodologies is recommended to increase the success rate of these projects. Nevertheless, organizations are hardly using them because they are considered too rigid and hard to implement. The existing methodologies often do not fit the specific project characteristics. Therefore, this research suggests grouping different project characteristics to identify the most appropriate project methodology for a specific type of project. More specifically, this research provides a structured description that helps to determine what type of project methodology works for different types of data analytics projects. The results of six different case studies show that continuous projects would benefit from an iterative methodology.

The exploitation of new value propositions enabled by disruptive digital technologies—also known as digital transformations—influences firms’ configurations of people, processes, and technology and must be considered in the enterprise’s strategy. Strategic planning, i.e., the process that determines strategy, is facilitated by enterprise architecture (EA). Hence, strategic plans are reflected in EA documents called artifacts. Our objective is to construct an overview of essential EA artifacts that are used to facilitate the strategic planning process for digital transformations. Therefore, we analyzed popular EA sources, performed a systematic literature review, and organized an expert session using the Metaplan method. Building on EA’s current knowledge, we propose 15 EA artifacts that facilitate digital transformations’ strategic planning process.

Implementing an ERP (Enterprise Resource Planning) system is a complex, risky, time-consuming, and very expensive affair. Unfortunately, ERP implementations are often still over budget and time, and below expectations. Ticking off critical success factors (CSFs) and risks is supposed to take care of all intricacies during an implementation. However, complexity theory suggests no perfect foresighted knowledge can exist and one should always be prepared for new and unexpected events happening (“unknown unknowns”). Currently, ERP research does not explicitly address this unexpected behavioral aspect of complexity. Therefore, it seems relevant to explore whether this unexpected complexity aspect of ERP implementations can be observed in actual ERP implementations. We demonstrate through an in-depth and structured case analysis that a normal, well-planned, and managed ERP project shows indeed unexpected behavior. That is to say, totally unforeseen major problems appear. From our observations, it is evident that ERP implementations can show significant unexpected behavior despite the best of knowledge, proper preparation, and project management practice. It seems relevant to perform more research into the relevance of appropriate control mechanisms based on acceptance of the inherent complex, i.e. unpredictable nature of ERP implementations. This awareness should complement existing mechanisms as CSFs and risks.