German SMEs must digitize.

What is the situation?

German SMEs are currently facing major challenges — not only due to economic developments in Germany, but also due to the growing pressure that companies are confronted with when it comes to digitization. A study by the Federal Network Agency shows that the potential of digitization has not yet been exhausted in all areas of the company. Although German companies use data analysis above the EU average in all sectors, at 37.1%, the proportion of companies (excluding the financial sector) that carry out data analyses still appears to be significantly expandable.

Why is this the case in medium-sized companies?

In general, medium-sized German companies are highly profitable and are often referred to as the backbone of the German economy for a reason. But that is purely a past perspective. The need to increase efficiencies and potential based on the use of data was attributed rather little importance in recent economic phases. If we look into the future, it becomes clear that adequate use of data is becoming increasingly relevant in order not to miss the connection and make SMEs fit for the future.

What is to be done now?

The question now is how to help companies that do not yet use data at all or make little use of data to take the first step or catch up with digitization. The short answer is to implement a data strategy. Namely, the introduction of a data strategy as part of the corporate strategy. Data should not be viewed as a side issue, but should be the focus of every company.

Data Strategy — What is that?

A data strategy defines how an organization collects, stores, manages, analyzes, and uses data and how the use of data affects business goals. It ensures that data is viewed as a strategic resource and is used systematically. Without an appropriate data strategy, companies risk not using data effectively and therefore unable to derive valuable insights. Such a strategy usually involves several factors:

• ‍Data Governance - Rules and guidelines for handling data to ensure its integrity and quality
• Data integration - Methods for combining data from different sources to create a uniform database
• ‍Data storage - Tools for central and continuous storage of data in an easily accessible database
• ‍Data analysis - Tools and methods for analyzing and interpreting data to gain valuable insights
• ‍Data security - Measures to protect sensitive data from unauthorized access and misuse

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Why is a data strategy so important?

An effective data strategy is crucial for success and future orientation for companies. By setting up such a strategy, significant added value can be achieved. These include in particular:

• Competitive advantage — companies that use data effectively can make informed decisions that lead to a clear competitive advantage
• Decision-making - Data-driven decisions enable companies to react more precisely and quickly to market changes
• Customer experience — data makes it possible to better understand customers and to personalize and improve the product, resulting in higher customer satisfaction and retention
• Increasing efficiency - The development of systematic data management enables accelerated analyses to be carried out and, as a result, the use of resources for revenue-increasing activities

How can the issue of data strategy be addressed?

As The Data Institute, we support the development and introduction of a data strategy following predefined steps in order to carry out the implementation in a targeted and rapid manner:

• Basis audit - Evaluation of existing data, systems and tools to understand the company's status quo
• Objective and KPI definition - Identification of company goals and finding out or setting key performance indicators (KPIs) that measure the success of the goals
• Technology selection - Choosing the right tools and methods that support the strategy and make it easier to handle data
• Setting up the data organization - Recruiting and training people who have or learn appropriate skills to implement the strategy
• Fostering data culture - Establishing a corporate culture that supports and promotes data-driven work

What challenges can be expected?

As part of our previous projects, we have noticed some pain points that companies are repeatedly confronted with when introducing a data strategy:

• Data silos - Data is available in isolated systems and cannot be used ad hoc without circumstances
• Data quality - Data is inaccurate or incomplete, which can result in incorrect decisions
• Data culture - Certain groups of people want to make greater use of data, but other stakeholders refuse
• Data skills - The skills required to implement the data strategy are not available in the company

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