AGILE CONTRACTS: LEARNINGS FROM AN AUTONOMOUS DRIVING SOURCING PROJECT

New digital services and products rely heavily on digital technologies and need to be deployed in an ever-shorter timeframe in response to rapidly changing market demands. To address this challenge, more and more companies are applying agile practices to increase speed and flexibility. In consequence, companies review their sourcing strategies to shorten the duration of tenders for large-scale IT projects and to increase flexibility in contracting of IT services to cope with the anticipated consequences of digital transformation. This study aims at revealing how agile practices could help to reduce time-to-market and to increase contract flexibility. As the automotive industry is especially affected by the adoption of new digital technologies, this revelatory case study shows how a German car manufacturer increased agility in sourcing and contracting of an autonomous driving development platform. Agile practices turned out to be essential in dealing with technological novelty and hurdles, regulatory uncertainty, and frequently changing requirements. We contribute to the extant knowledge by providing practical recommendations on how to increase agility in sourcing and contracting of large-scale IT projects

Evolution of Digital Innovation Units for Digital Transformation – The Convergence of Motors of Change

To face the challenge of digital transformation as well as to implement digital innovation many incumbent companies have set up digital innovation units (DIUs). Despite a steadily growing body of knowledge, there is a rather static picture of DIUs in the literature to date, and we have little knowledge of how these units evolve over time to continuously contribute to digital transformation and innovation. To lay the foundation for an understanding of DIUs as dynamically evolving entities, we conduct a multiple-case study with DIUs of five manufacturing companies and identify DIU evolution as a process driven by an interplay of life-cycle and dialectic motor of change. In the course of this, we also outline specific triggers, sequences, and the nature of change. We generalize our findings with a conceptual process model of DIU evolution and three propositions on their current and future development to inform the existing and forthcoming literature

Towards Bridging the Gap Between BDA Challenges and BDA Capability: A Conceptual Synthesis Based on a Systematic Literature Review

Big data analytics (BDA) and strategies for implementing BDA have received attention among researchers and practitioners alike. However, success stories pertaining to the implementation of BDA remain scarce. The notion of the BDA deployment gap describes the chasm between the attributed value potential of BDA and its actual value realization in organizational practice. Several research articles indicate challenges encountered in implementing BDA but lack a comprehensive systematization of BDA implementation-related challenges. This research article aims to systematize those challenges through a systematic literature review. As a result, we derived five overarching challenge dimensions related to the BDA implementation. Based on this systematization, we adopt the lens of a big data analytics capability and delineate future research avenues through the derivation of propositions on how to overcome the BDA implementation-related challenges, while enhancing our understanding about how to solve the BDA deployment gap

SENSEMAKING IN AI-BASED DIGITAL INNOVATIONS: INSIGHTS FROM A MANUFACTURING CASE STUDY

Organizations strive to innovate with Artificial Intelligence (AI) to tap new value potentials and outperform their competition. However, despite the enormous expectations associated with AI, incorporating the latter induces novel uncertainties and can even result in business value destruction. Therefore, organizations innovating with AI must manage these AI-induced uncertainties in their sensemaking process. Drawing on an exploratory case study, we investigate organizational sensemaking in two AI-based digital innovation projects at a globally leading automotive manufacturer. We account for the properties by which AI differs from traditional information systems and carve out how distinct AI properties unfold in AI-based digital innovations. We deduce four AI sensemaking mechanisms (i.e., cognition, interaction, regulation, and concretization) to understand better how AI challenges digital innovation endeavors in organizations

A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project

The ability to generate business-relevant information and its use for business process improvements is a key success factor for businesses today. Answering the call for further research on success-relevant practices and instruments for managing business analytics, we report on the results of a three-year action design research project at a global car manufacturer. Drawing on the socio-technical systems theory, we identify seven meta-requirements and specify four principles for the design of an instrument to manage Analytics-as-a-Service(Aaas) portfolios. Our results reinforce the importance of coordinating different socio-technical components in business analytics initiatives and demonstrate how concrete management instruments, such as the proposed portfolio management tool, contribute to socio-technical alignment. For practitioners, the documented design components may provide guidance on how to design and implement similar instruments that support the management of Aaas portfolios

Towards a Capability Model for Big Data Analytics

Big data analytics is becoming a veritable source of competitive advantageas it helps companies to better understand their business environment and to create or improve their products and services accordingly. However, big data analytics also poses challenges to organizations with respect to establishing the required capabilities. Building upon a design science research approach and the Work System Theory as a kernel theory, we identify several capabilities necessary to leverage the potential of big data analytics. To achieve this goal, we conducted 16 interviews with experts from an IT-strategy consulting firm. We furthermore organize the identified capabilities into a coherent model. The resulting capability model consists of eight capability groups that contain 34 capabilities. It provides a basis to systematically develop the necessary capabilities for the adoption und strategic usage of big data analytics

Punctuated Multi-Layered Liminality in Digital Transformation: The Case of an Automotive Platform

Digital transformation is often characterized as a liminal process as organizations move from established practices to new ways of organizing afforded by digital technology. Two contrasting views exist, however, on the liminality of digital transformation. One view sees liminality as a discrete transient process, while the other sees it as an on-going continuous transition. Building on a case study around a digital innovation initiative of an incumbent automotive car manufacturer, we offer a third view. We find that digital innovation triggers a phase of punctuated, multi-layered liminality that has a material, structural and temporal layer. We explain how material, temporal and structural tensions unfold at the level of practice, triggering new forms of liminal practices. We further develop three mechanisms (boundary testing, temporal bridging, and structural recoupling) that underpin punctuated multi-layered liminality. We contribute by unpacking the relationship between digital innovation and digital transformation

Smart Dust und Micro Robots im industriellen Sektor : Chancen, offene Punkte und Handlungsempfehlungen

Neben der massiven Erhöhung der Leistungsfähigkeit ist die radikale Miniaturisierung von Technologien ein zentraler Aspekt des digitalen Zeitalters – auch im Bereich der Robotik. In diesem Kontext stellen Smart Dust und Micro Robots mikro-elektro-mechanische Systeme im Sub-Millimeter-Bereich dar, je nach Ausprägung mit Sensorik-, Verarbeitungs-, Kommunikations- und Aktuatorikfähigkeiten ausgestattet. Dieser praxisorientierte Beitrag beschäftigt sich mit der Rolle von Smart Dust und Micro Robots im industriellen Sektor auf der Evidenzgrundlage von Fokusgruppen mit Industrievertretern. Interessierten Fach- und Führungskräften wird aufgezeigt, welche Potentiale resultieren, welche Hürden gemeistert werden müssen und welche strategische Aktivitäten es zur wertschöpfenden Nutzung in die Wege zu leiten gilt. Auch wenn heute in der Praxis noch schwierig umzusetzen, erkennt die Industrie diese Technologien und den damit verbundenen Mehrwert durchaus an

The emergence of smart service ecosystems : the role of socio‐technical antecedents and affordances

As physical products are increasingly augmented with digital technology, manufacturing firms have become part of the development of so-called smart products and smart services. As such, manufacturing firms are challenged by new market participants and ecosystem partners, particularly from the software development industry, and by the dynamic nature of business relationships. While the academic literature on the distinctive characteristics of ecosystems, particularly digital ecosystems, is rich, the effect of smart service ecosystems' emergence on the foundation of smart products remains uncertain. This study reports on case study research based on 47 semi-structured interviews with four companies that participate in an industrial smart service ecosystem. Taking an affordance-theoretic perspective, we uncover the antecedents of and the process of emergent smart service ecosystems. We find that smart service ecosystems have three socio-technical antecedents: a shared worldview, structural flexibility and integrity, and architecture of participation. We explain the emergence of smart service ecosystems as the result of specialisation in shared affordances and integration of idiosyncratic affordances into collective affordances. We derive seven propositions regarding the emergence of smart services, outline opportunities for further research, and present practical guidelines for manufacturing firms

Digitale Plattformen in der Praxis: Einsatz- und Entwicklungsmodelle

Zusammenfassung Viele der wertvollsten Unternehmen der Welt betreiben ihr Geschäft auf Basis einer digitalen Plattform samt umgebendem Ökosystem. Während es in der Theorie zahlreiche Erklärungs-und Gestaltungsansätze für die erfolgreiche Umsetzung gibt, gelten diese wirtschaftlich attraktiven Geschäftsmodelle in der Praxis nach wie vor als herausfordernd. Auf der empirischen Grundlage von sieben Plattform-Innovationsprojekten und mit Methoden der Fallstudienforschung untersucht der vorliegende Artikel, welche Rolle digitale Plattformen in der Praxis spielen und wie diese Artefakte entwickelt werden können. Mit den Ergebnissen in Form von vier Einsatz- (Platform-as-a-Core, Platform-as-an-Evolution, Platform-as-an-Enabler, Platform-as-an-Add-On) und vier Entwicklungsmodellen (Methodic Problem Solvers, Methodic Strategists, Methodic Leaders, Ad-Hoc Developers) kann gefolgert werden: Digitale Plattformen können in der Praxis vielfältige Rollen einnehmen und deren Entwicklung kann mit unterschiedlicher Methodikintensität erfolgen. Für die Praxis profitieren Fach- und Führungskräfte von industrienahen Einblicken und abgeleiteten Handlungsempfehlungen. Für die Forschung wird der Wissensfundus im Bereich des Designs und der Entwicklung digitaler Plattformen erweitert