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Data Management and Analytics in large organizations


Complex business processes have caused the data management and analytics landscapes in large organizations to historically evolve into highly complex information systems that need to interconnect with a large number of source systems. We conduct research on how such complex data management and analytics systems can be effectively managed and improved, to enable organizations to respond to future challenges. Research topics include general data management, data quality governance, platforms, regulatory issues, technology stacks for advanced analytics, and applied data science.



The Data Management and Analytics Community (DMAC) comprises the researchers of IWI1 working together with large European banks on a broad range of current data management topics. Building on a long tradition in applied research in Information Logistics in Competence Centers like Enterprise Information Warehousing or Information Logistics Management, the Data Management and Analytics Community (DMAC) started out as an applied research project on Data Warehouse Management together with UBS and IBM in 2011. Within DMAC, the researchers of IWI1 together with large European banks discuss and work on a broad range of current data management challenges. Recent topics include IS complexity, agile development, banking APIs, data  virtualization, metadata management, cloud migration, data science labs, CDO organizations, analytics ecosystems and data usability aspects of data management in large banks.


Prof. Dr. Jannis Beese


In times of business-driven digital transformation, increased design autonomy in innovation projects and agile principles, traditional coordination approaches in the IS domain are facing growing acceptance issues and, consequently, value contribution barriers. Since coordination challenges of IS on the enterprise level (e.g., IS complexity) persist or even increase with digitalization and design autonomy, organizations are in search of extending their portfolio beyond formal interventions. This paper integrates various descriptive and design knowledge components into a comprehensive analysis and design approach for informal coordination interventions. We cover a problem-oriented discussion of theoretical and conceptual foundations, a taxonomy of generic informal interventions, a catalogue of derived intervention types, and a process to systematically construct and evaluate situation-specific informal interventions. An Action Design Research project in a large company is summarized to demonstrate our proposal and provide evaluative evidence.

get_appSacha Fuchs, Roman Rietsche, Stephan Aier, Michael Rivera
Conference or Workshop Item
More and more employees request feedback from their organizations to develop and learn. This is reflected by a growing number of digital feedback apps which facilitate high-frequency feedback exchange. However, the effect of feedback has hardly been studied on an organizational level due to complexity. Therefore, we strive to analyze organizational feedback exchange with an agent-based simulation model. Concretely, we study the effect of feedback length and feedback frequency on the organizational return on investment (ROI) of feedback exchange. Our study shows that feedback length stays in an inverted U-shape relationship with ROI. Contrarily, feedback frequency is negatively correlated with ROI. When analyzed jointly, two sweet spots arise: one for medium-length, frequent feedback, and the other, for longer infrequent feedback.

Digital platforms (DPs) – technical core artifacts augmented by peripheral third-party complementary resources – facilitate the interaction and collaboration of different actors through highly-efficient resource matching. As DPs differ significantly in their configurations and applications, it is important from both a descriptive and a design perspective to define classes of DPs. As an intentionally designed artifact, every classification pursues a certain purpose. In this research, the purpose is to classify DPs from a business model perspective, i.e. to identify DP clusters that each share a similar business model type. We follow Nickerson et al.’s (2013) method for taxonomy development. By validating the conceptually derived design dimensions with ten DP cases, we identify platform structure and platform participants as the major clustering constituent characteristics. Building on the proposed taxonomy, we derive four DP archetypes that follow distinct design configurations, namely business innovation platforms, consumer innovation platforms, business exchange platforms and consumer exchange platforms.

(a) Problem faced: Due to heterogeneous stakeholder requirements, highly diverse tasks, and massive investments needed, enterprise-wide information systems (e-wIS) are often developed through multiple projects over long time periods. In this context, choosing the ‘right’ evolution paths becomes essential. This is not straightforward because e-wIS comprise technical, organizational, and use-related issues so that development stages need to be aligned over heterogeneous dimensions. Although maturity models (MM) are an established instrument to devise development paths, their respective development processes often lack transparency and theoretical as well as empirical grounding. Moreover, extant MM often focus on the control of certain capabilities (doing things right) rather than on providing the necessary capabilities in a sequence appropriate for a given type of organization (doing the right things). (b) Solution developed: We propose an empirically grounded design method for MMs, which devises capability development sequences rather than control levels. We instantiate the proposed method twice—for developing a Business Intelligence (BI) MM as well as a Corporate Performance Management (CPM) MM as two exemplary types of e-wIS. The artifacts are developed over three laps to successively enhance both their projectability in the problem space and their tangibility in the solution space. (c) Lessons Learned: (1) In DSR projects it often proves valuable to be open for diverse research approaches such as classical qualitative or quantitative approaches since they may purposefully ground and guide design decisions. (2) Complex artifact design processes may not be carried out by a single PhD student or published in a single paper. They require adequate decomposition and organizational integration. (3) Finally, complex and emergent artifact design processes require a reliable network of practice organizations rather than a project contract with a single organization.

Enterprise architecture management (EAM) in organizations often requires coping with conflicts between long-term enterprise-wide goals and short-term goals of local decision-makers. We argue that these goal conflicts are similar to the goal conflicts that occur in public goods dilemmas: people are faced with a choice between an option (a) with a high collective benefit for a group of people and a low individual benefit, and another option (b) with a low collective benefit and a high individual benefit. Building on institutional theory, we hypothesize how different combinations of institutional pressures (coercive, normative, and mimetic) affect decision makers’ behavior in such conflictive situations. We conduct a set of experiments for testing our hypotheses on cooperative behavior in a delayed-reward public goods dilemma. As preliminary results, we find that normative and mimetic pressures enhance cooperative behavior. Coercive pressure, however, may have detrimental effects in settings that normative and mimetic pressures are disregarded. In future work, we plan to transfer the abstract experimental design of an onlinelab experiment into a field experiment setting and thus into the real-world context of EAM.

To unlock additional business value, most enterprises are intensifying their enterprise-wide data management. In the case of the globally operating bank, we base this article on, a Chief Data Officer (CDO) organization is established for providing data governance and, in a second step, pushing data driven innovation forward. As many employees of the bank were not yet familiar with (or did not acknowledge) the need for enterprise-wide data management, this evolution exhibits characteristics of an organizational learning process. CDOs may want to actively steer this learning process by purposefully designing and adjusting their data management approach over time. Based on the major controversies the CDO has been confronted with, we propose four design dimensions for enterprise-wide data management and discuss the considerations for their configuration: (I) objective, (II) governance, (III) organization of data analytics, and (IV) expertise.

In the context of digital platforms, platform owners strive to maximize both their platform’s stability and generativity. This is complicated by the paradoxical relationship of generativity and stability, as well as associated tensions. To aid B2B platform owners in their design decisions, we aim to derive specific design principles that address the inherent tensions such that generativity and stability are maximized simultaneously. This requires a better understanding of when and to which extent a platform’s generativity and stability are paradoxical, and under which circumstances they can be maximized simultaneously. Thus, we first develop an agent-based simulation model to analyze the effects of an exemplary design decision regarding a tension (i.e. control vs. openness) on a platform’s generativity and stability. The developed simulation model enables predictive analyses of varying degrees of control and openness and their effect on generativity and stability. The simulation model must be further refined and applied to other tensions to thoroughly understand the impact of design decisions on a platform’s generativity and stability, and ultimately derive design principles.

Aligning local business and technology initiatives with enterprise-wide objectives remains a challenge for many organizations. To this end, Enterprise Architecture Management (EAM) imposes formal control mechanisms such as architecture plans and principles aimed at leveraging enterprise-wide standards and harnessing information systems (IS) complexity. Addressing recent calls to complement EAM control portfolios with informal control mechanisms, this study reports on the design, implementation and adoption of an Enterprise Architecture Label at a large multinational engineering company. Based on recent research on nudging, we deliberately designed the choice architecture of local decision makers. The Enterprise Architecture Label aims to influence the decision-making process, so that IS design alternatives that are preferable from an enterprise-wide perspective appear to be more attractive. Following an Action Design Research approach, the paper highlights the process of defining the underlying measurement system, designing an appropriate presentation, and the learnings and theory implications made throughout this process.

Information systems analysis and design (ISAD) ensures the design of information systems (IS) in line with the requirements of a business environment. Since ISAD approaches follow the current dominant logic of business, the rise of a new and thriving business logic may require revisiting and advancing extant ISAD approaches and techniques. One of the prevailing debates in marketing research is the paradigmatic shift from a goods-dominant (G-D) to a service-dominant (S-D) logic of business. The cornerstone of this reorientation is the concept of value co-creation emphasizing joint value creation among a variety of actors within a business network. With the aim of introducing value co-creation as a new discourse to ISAD research, this research note argues that (i) the lens of S-D logic with its core concept of value co-creation provides a novel perspective to ISAD. We also assert that (ii) value-co-creation-informed IS design realizes the paradigmatic shift from G-D to S-D logic. Building on this mutual relationship between value co-creation and ISAD, we propose a research agenda and discuss the ISAD artefacts that prospective research may target.

In this paper, we provide a conceptual model of the knowledge gaps that design science researchers should attend to in order to ensure that their use of justificatory knowledge is made in an appropriate way. We identify nine knowledge gaps between descriptive (cause-effect) relations in kernel theories, prescriptive (means-ends) relations in prescriptive and design theories, and the instantiated relations (instantiated design features and design requirements). The development of the conceptual model of the knowledge gaps was informed by and illustrated with the case of the longitudinal design science research project on team coordination called Coopilot. An initial set of strategies to ensure the appropriateness of justificatory knowledge is identified.