Understanding the obvious. That’s the purpose of our activities centered around Data Driven Innovation.
While it’s meanwhile common language, that both Big Data and Artificial Intelligence (AI) have at least a growing, sometimes even disruptive impact on every aspect of our society, understanding the drivers and dynamics of those transformative forces is the key to unlock the potential of the ongoing transformation.
When it comes down to questions of economy, the impact of those new technologies is striking: today, there’s barly any industry, market, value creation process or organization, that is not affected by the impact of data & algorithms. Although the capabilities to address, analyze and use these forces to create new business opportunities vary from company to company, the need to deal with it is unquestioned and widly accepted across all industries.
That’s the point where our Data Driven Innovation Framework comes into play. In order to capture these new types of value creation, any design of data-driven business opportunties needs to incorporate various perspectives in a structured and systematical way.
Ranging from specific users and their needs (plus their willingness to pay for new data-driven solutions) through questions of data quality and technological constraints up to measurable network effects in an existing ecosystem of customers and partners, those perspectives must be skillfully combined in order to exploit the power of any Data Driven Innovation.
By using a coherent, thoughtfully crafted and empirically proven concept for addressing the business needs of corporates and SME’s alike, any company should be able to adapt its strategies and successfully address the biggest challenge of our times: transforming itself into a future-proofen, sustainable and competitive organization by exploring and exploiting data-driven business opportunities.
Here’s our claim and aspiration: By using the DDI Framework, any organization – both profit and non-for-profit – should be able to answer the majority of questions centered around the irreversible rise of global data businesses. By transforming non-specific threads into (calculable) risks, organizations will be able to untap the full potential of data driven business opportunities and successfully manage their transition towards completely new business models and processes of value creation.
HOW
By using the DDI Framework, any company should be able to develop a consistent strategy plus comprehensive content for exploring data-driven business opportunities. The DDI framework is used to run online and offline webinars, workshops as well as coaching formats with research projects, start-ups, SMEs and corporates. The framework consists of three parts:
- 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.
PART 1: DDI CANVAS
The DDI Canvas is guiding users in exploring all relevant dimensions on the supply and demand side of a data-driven innovation in systematic manner.
1
Anticipate customer’s future demands
2
Understand the data assets that are available
3
Select the right tools for data-driven innovations
4
Deliver your innovation to specific users
5
Whom else is required to develop the data driven innovation
6
Understand keyplayer, dynamics and leverages of innovation ecosystems
7
Leverage network effects on data, infrastructure and marketplace level
8
How to develop a business and earn money?
9
Choose an optimal market position
PART 2: DDI NAVIGATOR
DDI Guiding Questions that support users in exploring each dimension in more detail by carefully selected deep dives.
PART 3: DDI TOOLS
Specific DDI Tools and Methods 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.
Value Proposition Designer
Focus on user needs (instead on technology) is key to add value through data. The starting point for any data driven innovation is a comprehensive and clear value proposition.
Data Explorer
Get a systematic, in-depth overview of the kind of data you need to set up your data driven solution. Analyze how feasible this data is for your recent and future business.
Data Processing Analyzer
Recognize the underlying functionalities of various data analytics and semantic technologies. Understand how they fit to different types of data sources.
Data Application Analyzer
Explore how to generate value with new and / or existing data. Realize how to support and automate human decision-making processes.
Partner Evaluator
Identify necessary co-innovation partners. Understand the importance of their contributions and identify strategic options to mitigate potential risks.
Ecosystem Strategizer
Recognize your most important co-adoption partners. Identify associated risks and develop appropriate strategies to manage your ecosystem.
Network Effects Navigator
Understand network effects and their dynamics to build better data-driven products and services. Investigate strategies to leverage those effects.
Revenue Roadmap
Select a promising revenue strategy. Combine different revenue streams and continuously adapt them to support the growth of your business.
Business Strategy Board
Assess different ways of positioning your data-driven offering in a market. Identify the most promising way to succeed in business.
OFFERING
Together with carefully selected partners we are able to provide a range of offerings that will support start-ups, SME’s and larger organizations to successfully develop and expand their data-driven business.
- In highly customized, interactive workshops companies can gain practical experience of how to apply the DDI Framework and Canvas for either an in-depth check of all relevant factors of data-driven business opportunities, or as a tried-and-tested approach how to systematically address in-house challenges for data-driven innovation.
- Individual sparring sessions with key persons being responsible for driving data-driven businesses provide guidance for any question related to our DDI Framework and specific use-cases.
- Together with our partner Evalea we have developed a self-assessment and monitoring tool for CEO’s, decision makers and responsible project leads. This tool kit is meant to support the decision-making process for – often costly – efforts and investments in data-driven initiatives. Once the homework is done, it helps to stay on track while implementing the necessary steps within your own organization.
Please get in CONTACT with us if you are interested and want to know more about one of these tailer-made offerings.
SCIENTIFIC BACKGROUND
The DDI Framework is based on a scientific approach, co-developed with the Technical Universities of Munich and Berlin and the Big Data Value Association.
The corresponding data set was obtained from an empirical study of more than 90 data-driven business models. The goal of this scientific research was to identify the patterns of successful data-driven companies in order to extract key variables for companies.
RESEARCH
The DDI framework was developed and tested in the context of the Horizon 2020 BDVe project and is backed by empirical data and scientific research encompassing a quantitative and representative research study covering more than 90 data-driven business opportunities. The objective of our research study was to systematically analyse and compare successfully implemented data-driven business opportunities.
From the research study, we could derive findings along the main dimensions of the DDI Framework:
SUCCESS PATTERNS
In order to understand typical success patterns of data-driven innovations, our research study relied on unsupervised cluster analysis.
Based on the cluster analysis, we could identify six clusters:
ECOSYSTEM
Over the last years the DDI Framework has been created and continuously improved together with numerous partner organizations, ranging from industry and academia to associations and public bodies. We are proud of being part of a growing European ecosystem boosting data driven business opportunities.
PARTNER
European Commission / BDVe / BDVA
The DDI Framework development is supported by the Big Data Value Ecosystem (BDVe) Project – a coordination and support action, co-funded by the European Commission within the H2020-EU 2.1.1. Programme under the grant number 732630. See www.big-data-value.eu for further information.
Technical University Munich (TUM)
The DDI Framework was continuosly evaluated and finetuned in the context of ongoing lectures in Data-Driven Innovation. See https://www.ei.tum.de/ldv/lehre/data-driven-innovation/ for more information.
Technical University Berlin (TUB)
The early development DDI Framework has been partially funded by the Technical University of Berlin.
Siemens AG
Within Siemens, the Data-Driven Innovation Framework is applied to support various Busines Units to explore their data-driven business opportunities.
European Data Incubator
The Data-Driven Innovation Framework is also used to train startups of the European Data Incubator https://edincubator.eu/.
Evalea GmbH
Evalea is developing tailor-made tools for online evaluation and the follow-up monitoring of the DDI framework within organizations. The modules are part of the Evalea HR Toolbox, a comprehensive toolkit covering all aspects of individual and organizational learning and development.
Foundation for the Next Society gGmbH
The non-for-profit „Foundation for the Next Society“ is hosting the development and rollout of the Data-Driven Innovation Framework with particular focus on its social impact. See www.next-society.org for more information.
PARTNER
European Commission / BDVe / BDVA
The DDI Framework development is supported by the Big Data Value Ecosystem (BDVe) Project – a coordination and support action, co-funded by the European Commission within the H2020-EU 2.1.1. Program under the grant number 732630. See www.big-data-value.eu for further information.
Technical University Berlin (TUB)
The early development DDI Framework has been partially funded by the Technical University of Berlin.
Technical University Munich (TUM)
The DDI Framework was continuously evaluated and finetuned in the context of ongoing lectures in Data-Driven Innovation. See https://www.ei.tum.de/ldv/lehre/data-driven-innovation/ for more information.
Siemens AG
Within Siemens, the Data-Driven Innovation Framework is applied to support various Business Units to explore their data-driven business opportunities.
European Data Incubator
The Data-Driven Innovation Framework is also used to train startups of the European Data Incubator. For more information, see https://edincubator.eu/.
The Foundation for the Next Society is hosting the development and further rollout of the Data-Driven Innovation Framework, thus making it available for a broader audience under a common creative license. In this context, the DDI Framework aims to raise digital awareness and expertise for those of us, who are willing to shape their own future and successfully manage the transition towards a (digital) next society.
See www.next-society.net for more information.
COMMUNITY
The ongoing work with the DDI framework is supported by a growing community of committed people who are concerned with the practical application of the content, both in profit and non-profit organizations.
Prof. Sonja Zillner
Dr. Bernhard Krusche
Dr. Edward Curry
Ana Garcia Robles
Dr. Tjerk Timan
Ingra Marangoni
Thomas Volk
David Maurer
Jean-Christoph Pazzaglia
TESTIMONIALS
