Step by step to a data-driven organization
Developing a data strategy resembles city planning: It requires more than just a simple push of a button. Through experience and meticulous planning, a foundation can be established for a vibrant, efficient, resilient, and sustainable outcome.
The data strategy serves as a roadmap to prepare your organization for the future: We collaborate with you to assess how to leverage your data to enhance your current business sectors and explore new digital product opportunities. To facilitate the shift towards a data-driven organization, we develop the essential steps to refine processes and foster innovation. Throughout this process, we remain mindful of regulatory obligations and changes in the market.
A well thought-out data strategy effectively identifies challenges and outlines ways to enhance resources, tools, and processes in data management.
Your contact
Dr. Christoph Reiners
Head of Data Management Consulting
What dimensions are there?
We take into account the following areas of focus for a systematic approach:
- Data Governance: Organizational framework for consistent, secure and value-adding data utilization
- Data Culture & Skills: Promotion of data democratization and development of data competency
- Data Assets & Quality: Supporting trust in data and the use of data-driven decisions
- Technology & Infrastructure: Creating a strong, centralized, and scalable data platform while utilizing contemporary data management tools
- Data Security & Privacy: Protection of sensitive data and compliance with regulatory, industry-specific and company-wide requirements
What are the key steps to successfully develop a data strategy?
Our proven strategy development process is divided into the following phases:
Every data strategy should align with a specific vision for the organization in question. Such a vision provides long-term orientation and motivation on the path to a data-driven organization. One example: In a future where markets are digitally connected, we will be the most customer-centric company in our industry, where our customers can discover, find and buy everything (physical and digital) they want online.
What actions are necessary to realize the vision? To achieve the goals, resources must be organized in iterative cycles and supplied and planned by different stakeholders, akin to budget planning. The goals are designed to be measurable, allowing for effective management of the transformation process.
The framework has been set. It is now crucial to assess the organization's as-is situation in terms of data and analytics. msg provides several options for this, including a maturity assessment. This assessment enables you to evaluate your organization's strengths and weaknesses. Besides measurable indicators, it also considers 'soft facts' that can provide insights into the (data) culture.
Concepts for the to-be situation are formulated according to the vision and goals. This leads to the necessary actions, which may include both technical and organizational modifications and enhancements.
The previously established list of actions is prioritized based on a cost-benefit analysis and segmented into distinct implementation phases. Besides the focus on benefits, the interdependencies among actions are also considered when organizing actions for a phase. Simply executing a technical measure does not yield any value if employees lack the data comprehension necessary to be able to use the system.
The actions of a phase are implemented in separate projects. Both beneficial and adverse experiences are considered when planning the next phases. At the conclusion of each phase, there is added value to inspire and bolster confidence in the goal.
Do you want to develop procedures to make yourself independent of external changes and at the same time take advantage of new opportunities? Let's talk about the solution from a single source.
Tailored solutions for your data-driven organization
Data sovereignty is one aspect of the data strategy. We are also happy to look at other important points with you so that you can make good data-driven decisions: