European Big Data Value Forum Agenda by Whova

Bernhard Krusche

Managing Director, Next Society Foundation

"Companies are far too busy maintaining the status quo. What’s missing is working on a sustainable culture of future readiness. Staying above the algorithms will become a question of survival not only for those organizations, but for all of us." As anthropologist, organizational consultant and managing director of the "Next Society Foundation", Bernhard Krusche focuses on the cultural dimension of digital change, which is increasingly pushing existing organizations to the limits of their capabilities. Instead of becoming intoxicated by the successes of the past or limiting themselves to the gardening of the present, decision-makers both in organizations and society must focus on working on their own future viability. Providing appropriate tools for this endeavor is key to a future not only for a happy few, but for the rest of us. This purpose fuels his activities - and determines both the subject of his new book, on which he is currently working and his engagement within the DDI Framework.

Bernhard is speaking at

Parallel session on Data Driven Innovation workshop

Focus Track 3 - Market uptake: Bringing AI and Data Sciences to Practice

November 3, 2020

3:30 pm - 5:30 pm

Speakers

Sonja Zillner (Parallel session chair) Lead Trustworthy AI , Siemens
Jean-Christophe Pazzaglia (Parallel session chair) BDVe Project Manager, SAP
Bernhard Krusche (Parallel session chair) Managing Director, Next Society Foundation
Tomás Pariente Lobo (Parallel session chair) Associate Head of AI, Data & Robotics Unit, Atos

Description

The Data-driven Innovation (DDI) Workshop is based on the (DDI) Framework addressing the challenges of identifying and exploring data-driven innovation in an efficient manner. It guides entrepreneurs in scoping promising data-driven business opportunities by reflecting the dynamics of supply and demand by investigating the co-evolution and interactions between the scope of the offering (supply) and the context of the market (demand) in systematic manner.

In this workshop, business champions, entrepreneurs and interested techies will gain practical experiences of how to use the DDI Framework and Canvas for the continuous analysis of all influencing factors of data-driven business opportunities. The participants of the workshops will get to know a set of methods and tools that will guide them in redefining their own data-driven business opportunity.

We will take the opportunity of this EBDVF workshop to officially launch the DDI canvas site. We encourage you to contact us to assist you in using DDI, to share with us your return of experience to help us to improve the methodology or provide domain specific know how.

The DDI framework was developed and tested in the context of the Horizon 2020 BDVe project[1] and is backed by empirical data and scientific research encompassing a quantitative and representative study of more than 90 data-driven business opportunities. The results of the research study guided the fine-tuning and updating the DDI framework as well as helped to identify success patterns of successful data-driven innovation. Currrently the DDI framework is used to run workshops with PPP projects, data-driven start-ups, SMEs and with corporates. It consists of a

The DDI Canvas guides you in exploring all relevant dimensions on the supply and demand side of a data-driven innovation in systematic manner.
The DDI Navigator will support you in exploring each dimension in more detail by carefully selected deep dives.
Specific DDI Tools will help you to work through each of the eight DDI dimensions, producing a conclusive set of results that will guide a company-specific setup of new, data-based products and services.

The DDI Framework is based on a conceptual model in form of an ontology with a set of categories and concepts describing all relevant aspects of data-driven business opportunities. Its categories are divided into supply side and demand side aspects. On the supply side the focus is on the development of new offerings. For a clearly defined value proposition, this includes the identification of and access to required data sources, as well as the analysis of underlying technologies. On the demand side the focus is on the dynamics of the addressed markets and associated ecosystems. The analysis includes the development of a revenue strategy, a way forward of how to harness network effects as well as an understanding of the type of business. As data-driven innovations are never done in isolation, the identification and analysis of potential development partners as well as partners in the ecosystem help to align / balance the supply and demand aspects in a way that its competitive nature will stand out.

Documents

Data Driven Innovation Framework presentation