Engaged Problem Formulation in IS Research

“Is this the problem?”: the question that haunts many information systems (IS) researchers when they pursue work relevant to both practice and research. Nevertheless, a deliberate answer to this question requires more than simply asking the involved IS practitioners. Deliberately formulating problems requires a more substantial engagement with the different stakeholders, especially when their problems are ill structured and situated in complex organizational settings. On this basis, we present an engaged approach to formulating IS problems with, not for, IS practitioners. We have come to understand engaged problem formulation as joint researching and as the defining of contemporary and complex problems by researchers and those practitioners who experience and know these problems. We used this approach in investigating IS management in Danish municipalities. In this paper, we present the approach to formulating problems in an engaged way. We discuss it in relation to ideas and assumptions that underpin engaged scholarship, and we discuss the implications for IS action research, design science research, and mixed approaches

Improving the Impact of Big Data Analytics Projects with Benefits Dependency Networks

Big data analytics is regarded as the next frontier in creating digital opportunities for businesses. Analytics projects rarely deliver the intended benefits for the organisation that invest in these data analytics, and currently, no widely accepted design method for analytics projects exists. To address this, we report from an action research project in an organisation highly involved with big data analytics and how benefits materialize from these projects through the practices of tailored and focused benefits management. We argue for using the benefits dependency network for orchestrating commitment to benefits. Benefits dependency networks create linkages between analytics technology, organisational change activities, stakeholders’ interests and to-be benefits of a project. With this study, we contribute with: (1) a tailored technique for benefits dependency networks, (2) focus on benefits into established project development practices for big data analytics (3) facilitation as a key capability in developing a benefits dependency network

A Proficiency Model for Design Science Research Education

Design science research (DSR) produces knowledge via the design and evaluation of innovative solutions to real-world problems. DSR provides an improved understanding of how and why the solutions work. While DSR is being widely embraced in many research disciplines, its educational pedagogy so far remains immature with little guidance on how best to inform and train various audiences on relevant and rigorous DSR skillsets. Grounded on the authors’ wide experience in designing and delivering DSR courses over the past decades, we develop a “DSR Proficiency Model” to highlight key skills required to succeed in planning, applying, and communicating DSR. We recognize the different educational environments and student backgrounds that DSR courses must accommodate and provide actionable guidance for mapping the proficiency model to academic, training, and executive audiences. Informative examples demonstrate how we have structured DSR curricula for different academic and executive education programs

Improving the impact of Big Data Analytics Projects with Benefits Dependency Networks

Big data analytics is the next frontier in creating digital opportunities for businesses. However, analytics projects rarely deliver the intended benefits for the organizations that invest in these. To address this challenge, we report from an action research study on improving benefits realization in Vestas, an organization highly involved with big data analytics. Here, we introduce the benefits dependency network, a map of the relationships between analytics technology, organizational change activities, stakeholders’ interests, and the potential benefits of a big data analytics project. Through four action research iterations involving three projects in Vestas, we developed and evaluated a method for benefits dependency networks for big data analytics. In this study, we present lessons on: (1) the usefulness of the method in big data analytics projects, (2) how it can be embedded into existing project methodologies, and (3) how facilitation is needed in connecting the domains supporting benefits realization needs. We conclude the paper by discussing our lessons’ contributions to the extant research on big data analytics and benefits realization management

Construction of Design Science Research Questions

Posing research questions represents a fundamental step to guide and direct how researchers develop knowledge in research. In design science research (DSR), researchers need to pose research questions to define the scope and the modes of inquiry, characterize the artifacts, and communicate the contributions. Despite the importance of research questions, research provides few guidelines on how to construct suitable DSR research questions. We fill this gap by exploring ways of constructing DSR research questions and analyzing the research questions in a sample of 104 DSR publications. We found that about two-thirds of the analyzed DSR publications actually used research questions to link their problem statements to research approaches and that most questions focused on solving problems. Based on our analysis, we derive a typology of DSR question formulation to provide guidelines and patterns that help researchers formulate research questions when conducting their DSR projects