Not only companies from Silicon Valley show what economic potential lies in data. Digital data also plays a central role in the daily business of many German companies. But the more successful and larger their digital services become, the more massively the data volumes and their fragmentation within the company increase. This poses the risk that the handling of data will become non-transparent and inefficient. Which divisions and teams store which data? What APIs do I use to access certain data? And how do I have to protect myself? The search for the right piece of data is increasingly becoming a search for the needle in the haystack.
A correct and transparent handling of customer data is a decisive advantage in the competition of digital services. It is the basis for customer trust. Companies that master the balancing act between transparency and simplicity of their services are in a good position to survive in global competition. The key to this is the complete documentation of data processing within the company.
In addition to transparency, consistent data management offers the opportunity for innovation. The aim is to design and develop new services and products by cleverly combining existing elements. Here, it is particularly important to simplify access to the data inventory for specialists from other disciplines, i.e. to provide secure access for strategists, data scientists and designers in the company.
„The systemic view of the overall process is always the first step for us. The seemingly simple visualization of all participants, their different needs and the relationships between them is always hard work, but always pays off in the long run.”
Especially with a supposedly technical topic like this, user research is an essential step for us to get to know all participants in their roles, relationships and needs.
Each role has different data requirements. Data suppliers need an overview of the consumers of their data and smooth release processes. If the exact origin and nature of data is not documented, data consumers usually realize too late whether they meet all requirements. On the other hand, if it is possible to involve all relevant parties in a coherent process, unnecessary development and coordination loops are minimized.
Data stewards and enterprise architects are usually interested in the purpose of the data processing. Is the consumer using the data point appropriately? It is their task to secure the company in the best possible way, to protect the privacy of the customers and at the same time enable innovation.
The basis of all measures is a central catalogue that collects all the necessary meta-information on data and their producers and consumers. And not only technical information, but also organisational information.
Detailed meta-data enable the continuous visualization of the data line - the proof of origin of a date. It is an important component of the solution. At every point in the processing chain, it should be clear where data comes from and how it is stored. This gives data producers a quick insight into how their data is being used, allows them to optimize it, and thus minimize the effort required on the consumer side. Even if the parties involved have different views on a date, the intention is the same in every case: To ensure that the best possible product is developed for the customer. Our concepts therefore focused on making communication between the parties involved as efficient and cooperative as possible.
Well-structured and easily accessible data is a breeding ground and accelerator for the creation of new services. However, a targeted and analytical approach is not the only way of working that needs to be supported. It must also allow room for happy coincidence and browsing through the inventory of data.
An ecosystem around data can therefore inspire a company in many ways: It improves cooperation between the parties involved and accelerates the work of the development teams. Most importantly, it builds trust with key stakeholders - the people who use the services and make their data available.
Do you want to make data-based decisions?