Reference Process and expertise

SCS Reference Process for Digital Transformation

Companies’ value creation is increasingly founded on data. To safeguard their future success, companies must therefore embrace digitization at all levels of their business processes. With this in mind, Fraunhofer SCS has developed its own SCS Reference Process for Digital Transformation, allowing classical industrial processes to be elevated to a data-driven level. By placing data at the heart of optimization – be it of processes, organizations, or business models – this four-step process serves as an example of how companies can generate added value from data and what expertise is needed for a successful transformation.

Four steps to digital transformation

SCS Reference Process for Digital Transformation

The process always begins with data, which is the basis for any successful digital transformation: all data sources – both internal and external – must be tapped, and the data must be structured, integrated, and sorted in suitable data spaces.

Step 1 – Business strategy and applications

The first step revolves around business strategy and applications, and proceeds as follows: the company must develop a vision for the digital future, break it down into data-driven applications, evaluate these applications in terms of their technical and organizational feasibility and potential quantitative and qualitative benefits, and embark upon an implementation roadmap or initial implementation projects.

Step 2 – Generating knowledge

An appropriate solution is then defined by focusing on a specific use case from the road map created in the first step, which involves selecting suitable procedures and populating them with the right data. Relevant data are either drawn from existing sources or curated specifically for the procedure as necessary.

Step 3 – Applying knowledge

In this step, solutions are implemented into processes in the form of technical prototypes in order to test their usefulness and functionality. Here, success depends on the involvement and consultation of end users, customers, and employees – in other words, it is essential to consider the human factor.

Step 4 – Decision-making guidelines

The final step is about making concrete decisions, such as determining the cost of the solution, defining the business case or a suitable business model, developing decision-making guidelines for company management, and finally reviewing and reassessing the decisions made in step 1 as required.

Necessary expertise

For this approach, it is necessary to fundamentally rethink processes, organizations, and business models. At Fraunhofer SCS, we believe that this requires expertise in the development of:

  • data spaces and IoT solutions for complete networked systems in which data are prepared independently of the application or system that gave rise to them, making them portable;
  • analytics methods and procedures in the field of artificial intelligence that can transform seemingly unmanageable amounts of data and related material into manageable, high-quality data and information; and
  • business models and organizations that open the door to fresh perspectives by giving equal consideration to imminent trends, technological opportunities, and the human factor.
 

Scientific support from Fraunhofer SCS


In keeping with the SCS vision of »Success and added value thanks to data«, Fraunhofer SCS supports companies throughout the entire process of digital transformation.

By leveraging the appropriate methodological expertise, staff work with and on behalf of companies to develop solutions for sustainable processes, organizations, and business models based on economic and mathematical procedures and methods: from the provision of structured data by means of appropriately designed data spaces and IoT solutions, through to analysis and optimization of data for valid forecasts using analytics and AI, or strategic utilization of data for future-proof business models and organizations.