Data Value Thinking
How is the value of a company significantly increased by the ability to generate and use meaningful data?
DATA VALUE THINKING is a strategic framework that is aimed at business managers and offers guidance and decision support with models and analogies. Creative approaches help to develop pragmatic, feasible and future-proof solutions.

Use new technologies in a sensible way
Rethink data
Big data, predictive analytics, IoT
and artificial intelligence (AI) are just a few
examples of how new technologies require a different way of dealing with data to
achieve real, sustainable value increases. DATA VALUE THINKING supports you in
the classification and sensible use of new technologies.
Creating values through efficient combination
Connecting data worlds Experience shows that the combination of data from different areas generates the highest values. DATA VALUE THINKING supports you in finding these combinations and to avoid thinking in data silos and existing structures.
Creativity,
building innovation on data
Creating data culture
To use the value of the data, in addition to technical competence, more creativity and
innovation is required.
DATA VALUE THINKING offers workshops that use creative
techniques such as gamification and thus quickly show new ideas and
approaches.
Furthermore, a common view of the world of data is created and a data culture is
established.
Data Value Thinking Navigator and partner network
Control data usage
DATA VALUE THINKING offers a navigator system for developing
objectives and adhering to a safe course - similar to a sailing yacht.
To ensure practicability and
implementation, selected solution and technology partners support the approach.
“Realizing” digital strategies using Data Value Thinking
Companies are under increasing pressure to quickly decide whether, how and to what extent they use new technologies such as sensors, robotics, social media or artificial intelligence. This is not about using the technology because it is there, but the technology is a tool for the purpose of sustainably increasing the company’s value. The central element of these new technologies is data. Data control, enable and use these technologies, data is the “raw material” that the technologies use and at the same time the “raw material” they deliver.

New technologies are finding their way into companies now and in the future. With them a whole set of data. But what does these data and technologies mean for the business? Which approaches really help to generate efficiency, optimize usage of resources and generate additional services? What is changing and what needs to be considered?
Business decision-makers must deal with these questions more and more. Even if the basics of these topics are technologies, the business areas have to deal with these questions strategically and economically.
The “becoming real” of digital strategies takes place through the use of Data Value Thinking, which is a set of approaches and methods with the following objectives:
- Common understanding of the current situation of the company in digitization
- Deriving the importance of data as the central resource in digital strategy and its implementation
- Presentation of the new creative approach Data Value Thinking for a minimum change while adding value through innovation and technologies
- Identification of feasible digital use cases
- Providing orientation by presenting selected application examples and technology / solution partners
Usage areas
Awareness of the strategic role and the value of data is growing, particularly in industries that are currently digitizing strongly, such as real estate, manufacturing and retail. Companies aim to increase their company value through the ability to generate, recognize and use meaningful data. To do this, they face the tasks of orientation, strategy and cultural change. All of this must be implemented step by step and pragmatically.

I Orientation & Strategy
Many areas of the company deal with the subject of “data” and “digitization”. These areas can complement and develop a common language through the framework of “Data Value Thinking”. Goals and guidelines are defined.
II Gradual Implementation
Independent and quick-to-install solutions offer advantages, but you shouldn’t block the way into the future. Here it is important to set the right priorities in order to have a quick ROI.
III Pragmatism
Not everything that is technically feasible must be sensible. Many complex technical solutions can also be achieved through pragmatic data analysis.
IV Cultural Change
We are only slowly becoming aware of the value of data. The environment is changing dynamically. Therefore, management and employees must be sensitized and trained in order to act consciously and in a coordinated manner.
Use new technologies in a sensible way - rethink data
New technologies enable new applications. But new technologies also mean new behaviours like the usage of smartphones is showing. Furthermore, technologies complement each other and only then make it possible to create comprehensive, new use cases. Artificial intelligence applications need a basis of sufficient and high-quality data as basic raw material. Technologies such as sensors, the Internet of Things (IoT) provide these data, and storage and evaluation tools from the area of big data make them permanently available. This dynamic is reinforced by efficient communication technologies and the willingness of users to use new technologies.
Data is the raw material. The quality and type of this raw material not only determine the quality of artificial intelligence, but also decisively control all areas of application for new technologies – and therefore at the end the value of the company..

Creating values through efficient combination - connecting data worlds

Creativity, building innovation on data - creating data culture
Data is therefore increasingly becoming a “value” in the minds of companies. To be able to realize this value, creativity and innovative capabilities are required in addition to technical and analytical competence.
In order to be creative, you first have to grasp the complexity and be able to organize it to a certain degree – get an overview (like the box of building blocks that kids first pour out, digs in and look at the stones before the evolve pictures of objects that they want to create or what they want to use).
In addition to “grasping” and “organizing”, it is important, like in design thinking, to look at the topic from different perspectives and to think from the end, the user. Analogies or pictures help with the creative design and help in “grasping” the complexity.

With its approaches and methods, DATA VALUE THINKING supports the expansion of such a data culture in the company. An example of this is the DVT creativity workshop. The workshop aims to capture the world of data and its value. It uses gamification approaches and builds on the DVT card, a map of the data world. It should make the complexity more understandable and gives orientation. It is intended to provide managers and executives with a perspective so that data can be better considered in their management actions. In order to be able to use data better, more and more creative approaches are used by companies. Creativity cannot be forced, but it can be supported. The workshop provides the managers or a management team with a common picture and thus also a common basis and language for future discussions and ideas.
Data Value Thinking Navigator and partner network - control data usage

DATA VALUE THINKING offers clear objectives and safe navigation in the complex world of data with a sophisticated navigator system. This takes into account not only transformational, business and technical, but also cultural issues and also integrates everything!
The Data Value Navigator is composed out of four components
- Business Value: How to leverage the data to invrease the company value
- Data Management: What is required to make data available, manage and protect them
- Data Infrastructure: Where are these data and through which technologies are they accessable
- Data Crew: Who leverages data in business decisions and what is the impact in the corporate culture
Only the consideration of all components will generate the expected success in digitization.
Partner Network
Results of Data Value thinking

Building knowledge in Data Value Thinking

Exchange with other companies

Readiness-Status in Data Value Thinking

Validation of solutions and approaches

Realization of selected use cases