Our scope of services
The increasing company-wide use of data requires a change in strategy when dealing with data. Success-critical decisions and automated processes are based on reliable data and structures. Strategic data management develops the necessary structures for the so-called data organization. The strategic positioning of the data organization allows the sustainable alignment of data domains, data roles and data applications.
At Fraunhofer ISST, the components of strategic data management that ensure success for data-driven innovations are developed. The goal of strategic data management is the introduction and optimization of a company-internal data organization to realize data democratization. Establishing a data organization increases data quality and usability of AI applications, reduces data search processes, and improves the adoption of data applications. Within its framework, the necessary data capabilities are developed, sustainably established and continuously measurable. The basis for the data organization is the establishment of a data strategy that defines long-term specifications, for example, the prerequisite for participation in data ecosystems or the type of data storage. The data organization is based on these specifications and integrates them into the data governance approaches, which is ensured by means of decentralized and/or centralized corporate units and suitable data roles such as data owners and data stewards. For efficient implementation of the workflows, the concepts are realized in data catalogs and data quality software and rolled out company-wide.
Figure 1: Integrated approach to developing strategic data management with the Fraunhofer ISST toolbox
Fraunhofer ISST's range of services includes data strategy positioning, conducting data assessments and reviews, selecting suitable data governance approaches, developing role and process models, and supporting a proof-of-concept for tools.
Data strategy and data culture
- Strategic positioning of data management in the internal and external corporate environment
- Derivation of data capabilities, structured by technology, organization and people (TOP principle)
- Dovetailing with business strategy by means of data-related target systems, development plan and key performance indicators
- Transformation to a data culture by means of data awareness workshops, data principles and data competence building
- Development and selection of a suitable data governance organizational model to determine centralized and decentralized responsibilities.
- Development and introduction of suitable data roles according to tasks, competencies and responsibilities (AKV principle) in the existing organization
- Process model development based on the relevant data capabilities
- Assessment and support of the proof-of-concept for the implementation of a data catalog
- Assessment for the selection of suitable data quality software
Strategic data management helps solve demanding challenges in a variety of industries. Whether as a toolbox in automotive manufacturing, a framework in medical technology, or an organizational model in transportation, data management as a strategic cornerstone has a positive impact on time to market and the introduction of new applications.