The Datentreiber Method: Data Strategy Design
Using the data strategy design method you achieve your goals securely and you find the right way faster. Data strategy design helps you and your team to collaborate efficiently and effective to develop unique as well as the most promising strategies for utilizing your enterprise data.
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What Is Data Strategy Design?
To holistically advise its clients regarding individual data strategies, Datentreiber has developed its own strategy method which has been used, proven successful as well as continuously refined in numerous client projects: the data strategy design method is based on Design Thinking. It extends the original method’s user-centric and value-oriented mindset with Data Thinking, a perspective which is, coming from the users’ needs and available enterprise data, identifying, concretizing and evaluating data-driven solutions and business models. The Datentreiber method provides a collection of free to use tools – the Data Strategy Designkit – as well as a library representing typical design patterns – the Data Strategy Designguide.
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What Is a Data Strategy?
A data strategy consists of three essential parts:
- Short-term: an overview of the company’s data landscape including the exploration of external data sources as well as the qualitative evaluation of the data.
- Mid-term: concrete use cases having a positive cost-benefit ratio as well as functional, technical and analytical concepts for an imminent implementation.
- Long-term: a roadmap for a gradual increase of the company’s analytical maturity by implementing further data-driven applications.
The data strategy is aiming at a transformation of the company towards data-driven business models and processes in order to get a leading position in the digital race.
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What Is the Datentreiber Designkit?
Working on a data strategy requires an interdisciplinary team of experts. This means for example experts coming from the marketing or production department, IT specialists, data analysts or data scientists as well as further people which are for instance working as managing director or in the legal department in their day to day job. Datentreiber has developed the Data Strategy Designkit to efficiently structure this process: it consists of a collection of visual collaboration tools (called “canvas”) which are used to jointly work on a data strategy in a creative and interactive way. The tools are available for free based on a Creative Commons License. They can be used as (printed) poster as well as digitally.
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What Are the Datentreiber Canvas?
The Datentreiber Designkit consists of various canvas posters. Data strategy designers can use these as an ensemble or one by one to clarify different questions related to a data strategy within their team. Because of their structure, the canvas help to raise the critical questions and to find the right answers. The canvas are divided into three areas:
Data
Data Landscape
Analyze
Analytic Maturity
Prioritize
Data Strategy
Conceptualize
Data Management
Concretize
Strategy
Value Chain
Analyze
Growth Horizons
Prioritize
Business Model / Case
Conceptualize
Strategy Pyramid
Concretize
Design
Stakeholder Analysis
Analyze
Value Curve
Prioritize
Analytics Use Case
Conceptualize
Customer Touchpoints
Concretize
As a generic tool for prioritization, the Priority Matrix is available as a canvas, as well as the 3 Boxes Canvas as a generic tool for categorization. Another tool is the Generative AI Canvas for the development of innovative application ideas of Generative AI. For root cause analysis of problems, the Cause and Effect Canvas is available. An overview of all canvases and a representation of the connections between the canvases is provided by the Data Strategy Design Kit Canvas, and the Data Strategy Design Guide Canvas is suitable for planning and visualizing workshops.
Here you can download all 18 canvas
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What Is the Datentreiber Designguide?
Companies can use the Datentreiber canvas in different combinations and ways depending on the company’s specific situation and objectives. Datentreiber has developed design patterns for typical starting points or areas of applications. These design patterns are summarized and classified in the Data Strategy Designguide. The following picture shows an exemplary template process for a data driven marketing strategy:
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What Is the Best Starting Point?
All beginnings are…easy. To keep this promise we are offering various content regarding data strategy design:
Datentreiber:
Social Media:
- Blog (Articles)
- SlideShare (Presentations)
- YouTube (Videos)
- LinkedIn (Group)
Partner:
- Stattys (Print, Notes etc.)
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