Data Strategy
Data chaos becomes data-driven organization: with a data strategy framework, clear governance and a living data culture for sustainable business transformation.
Download the white paper for free“Strategy without execution is pointless, execution without strategy is aimless.”
In an increasingly data-driven world, it is no longer enough just to manage data — companies must use it in a targeted manner to create real added value. What is often missing is a structured framework for governance, clear responsibilities, and the prioritization of data-driven initiatives.
No company needs an abstract strategy that cannot be integrated into business processes. Nor are inefficient, poorly organized projects sustainable in the long term. This white paper shows you how to successfully shape change with a holistic data strategy framework, a practical roadmap and formats such as the Data Thinking Workshop — from initial quick wins to long-term data transformation.
How do you implement a data strategy?
A good basis for a data strategy project is when the first tangible successes have been achieved. For example, a dashboard that is immediately useful and sparks interest in a larger implementation. The findings from these projects form the basis for the strategy project.
In order to bring more structure to the development of the data strategy, we have divided the process into four horizons, which are maintained throughout the course of the project:
In order to bring more structure to the development of the data strategy, we have divided the process into four horizons, which are maintained throughout the course of the project:
Business & Value Generation
Data drives business models by helping with decisions and processes. The clearer the business goals, the better the data strategy can be implemented.
Data Management
Effective data management is crucial for reliable, consistent, and secure corporate data. This includes data governance, quality assurance, and optimized data processes.
People & Organization
The skill set of employees and a suitable organizational structure are the basis for long-term data-driven success. Clear roles, assigned competencies and defined interfaces enable effective use of data.
Technology & Architecture
Technology comes last because an efficient infrastructure is only useful if it is geared to business goals and not just follows technical trends.
Business Value & Generation
Data drives business models by helping with decisions and processes. The clearer the business goals, the better the data strategy can be implemented.
Data Management
Effective data management is crucial for reliable, consistent, and secure corporate data. This includes data governance, quality assurance, and optimized data processes.
People & Organization
The skill set of employees and a suitable organizational structure are the basis for long-term data-driven success. Clear roles, assigned competencies and defined interfaces enable effective use of data.
Technology & Architecture
Technology comes last because an efficient infrastructure is only useful if it is geared to business goals and not just follows technical trends.
Four insights that move your data strategy forward
Learn how to take the right steps to create a specific data strategy.
Inquire now without obligationCurrent situation analysis
How to analyze your status quo using a framework and maturity model and derive clear fields of action from this.
roadmap
From quick wins to scaling, this is how you plan a data strategy roadmap that fits your business and resources.
culture
Why data culture, curiosity and collaboration are decisive and how you can specifically promote them with data thinking.
Governance
How roles, responsibilities, and standards help you implement data strategies efficiently and sustainably.
Your data expert and white paper author
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By learning not only to collect data, but also to use it in a targeted manner to increase their business success, companies are unlocking the true potential of this valuable resource.
Benedikt Köhler
Senior Data Consultant, taod
Data is a driver of success — when used correctly. Ben supports his customers in this: from dashboarding to use case development to strategy definition. He is convinced that by professionalizing its data practice, every company can move forward and become more economically successful. He develops these specific added values in his projects day by day — based on data and with passion!
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Questions that will help you
FAQ
What is a data strategy and why is it important for companies?
A data strategy determines how a company uses data in a targeted manner to achieve business goals, improve decisions and systematically expand added value. What is decisive here is not data management as an end in itself, but the contribution of data to achieving strategic goals. Especially in data-driven markets, a clear data strategy makes the difference between selective individual initiatives and sustainable competitiveness.
When should a company start with a data strategy?
The right time is usually reached when the first data-driven projects have already provided practical insights. Initial proofs of concept, dashboards or interface solutions create quick wins, show real potential and make it visible where performance, availability or architecture limits lie. It is precisely these experiences that form the reliable basis for a data strategy that is not theoretical but can be implemented.
Is rapid implementation or a long-term data strategy more important?
They both belong together. Pure execution without a strategic framework easily leads to isolated projects, new data silos and a lack of prioritization. A strategy without implementation, on the other hand, remains abstract and has no business benefit. Data Strategy is therefore only effective when combined. Practical experience provides the basis, the strategy provides direction, priorities and a common vision for further scaling.
Which areas does an effective data strategy need to cover?
A robust data strategy looks at four levels simultaneously: Business & Value Generation, Data Management, People & Organization, and Technology & Architecture. This ensures that data is not only technically available. They also contribute to clear business goals. Governance and data quality ensure their reliability. At the same time, they are organisationally anchored and are supported by an architecture that supports the company's needs instead of just following technology trends.
How do you move from individual data projects to a scalable data strategy?
The most effective path starts with a clear vision and a realistic view of existing initiatives, roles, data products and technical dependencies. Measures along the most strategically important fields of action are then prioritized, translated into a roadmap and linked to resources, responsibilities and KPIs. This results in a scalable data journey from decentralized individual measures, which both enables quick results and systematically builds up long-term added value.
More about data strategy
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blog
“We now have a fixed order and structure.”
Dr. Heiner Lütjen from RheinEnergie about data strategic work.
Case
RheinEnergie's data strategy
From decentralized data initiatives to building a central data strategy as a business enabler.
Service
Data Strategy Consulting
We help you align data practice with your strategic business goals.
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