Why a data strategy is essential
Many companies face the challenge of making effective use of their data. Obstacles such as fragmented systems and poor data quality make it difficult to harness this data. At the same time, new regulatory requirements – including the EU Data Act and the forthcoming EU AI Act – call for a cross-use-case approach to data management. A well-thought-out data strategy is the key to overcoming these challenges and utilising data profitably. Companies that establish such a strategy at an early stage secure a decisive competitive advantage.
The cornerstones of a successful data strategy
1. Define clear business objectives
Data should not be viewed in isolation; rather, the data to be collected must be derived from the business objectives. A successful data strategy is therefore aligned with the company’s objectives:
- Which markets should be targeted?
- What use cases do we need to achieve this?
- How can we implement this technically?
2. Identify the right use cases
Not every data-driven application contributes to the company’s success. Materna, for example, uses Data Design Thinking to identify the relevant use cases. Criteria such as strategic relevance, economic benefit and feasibility help in this process. The highest-priority use case is examined in more detail, and its interdependence with other use cases is assessed. Companies should always develop data-driven approaches with a clear business focus, rather than being guided solely by technical possibilities.
3. Implementation using an iterative approach
Once the most promising use case has been identified, step-by-step implementation follows:
- Check data availability: Is the required data of high quality and accessible?
- Short time-to-market through agile development: A proof of concept demonstrates the added value at an early stage and is developed iteratively via a minimum viable product (MVP) to market readiness.
- Integration into existing processes: The system is integrated into day-to-day operations.
- Scaling and further development: User feedback is incorporated into the optimisation process to ensure long-term success.
Data strategy as a long-term success factor
A successful data strategy is not a one-off project but an ongoing process. Key success factors include:
- Data governance: Define and implement precise guidelines for data usage, security and quality control.
- Technological infrastructure: Introduce a flexible, scalable data architecture that enables data-driven innovation. Data integration platforms enable the integration of existing data infrastructure.
- Data culture within the organisation: Communicate the value of data-driven decisions to your workforce (data literacy). Empower your staff to make data-based decisions.
Case study: AI-supported automation of aerial image analysis
An energy supplier is legally obliged to regularly inspect its power line network from the air in order to identify changes in development along the routes at an early stage. In our example, the aerial images were previously analysed by two external service providers, who manually mapped objects over a period of several months. However, due to the high staffing costs involved, only part of the network could be covered. Furthermore, because of the lengthy processing time, some of the shapefiles created were already out of date by the time they were handed over.
During a workshop with the Materna team, it quickly became clear that an AI-supported approach would enable significant efficiency gains and cost savings. The company subsequently developed a proof of concept (PoC) for an image recognition AI that automatically analyses the aerial photographs. This PoC was then further developed into a minimum viable product (MVP) through the integration of publicly available map data.
By implementing a cloud-based data processing pipeline, the company can now map the entire route network in a fraction of the time previously required, with significantly greater precision. This results in annual cost savings of around 90 per cent, whilst the results are available much more quickly. The insights gained from this project can also be applied to other sectors and companies that stand to benefit from the combination of data strategy, AI technology and digital platforms.
Setting the course for a data-driven future
Companies that pursue a clear data strategy benefit from:
- Efficiency gains through optimised processes
- New business models and revenue opportunities
- Improved customer loyalty through data-driven services
Data is the key to future-proofing your business. Would you like to find out more about how a bespoke data strategy can drive your business forward? You can find further information on the data economy here.
