Since 17 years, lawyer Pascal Tschachtli has been dealing with data questions and since 2015 he has been advising companies in the matter. In this undertaking, data governance is becoming increasingly important, because it provides the rules and tools to transform data into valuable information. Thomas Göbel is driving the topic of data governance forward at Audi. In an interview with blog author Lisa Först, Tschachtli and Göbel explain what exactly data governance means and why it is so crucial for autonomous driving, artificial intelligence and the daily search for information.
Data Governance at Audi
A valuable resource that doesn’t diminish, but replenishes instead? For data governance experts this dream is reality. Their task: To refine data as the new oil, so it can become the sustainable drive of the future.
Mr. Tschachtli, you advise companies that want to conduct data governance? Why is this topic important?
Tschachtli: Out of the five most valuable companies of the world, three are pure data processors: Google, Amazon and Facebook. Already in 2006, market researcher and data scientist Clive Humby classified data as the new oil. However, only a few know how the quote ends: “It’s valuable, but if unrefined it cannot really be used.” Similar to any resource, we have to process data in order to use it profitably.
And this is possible with data governance?
Tschachtli: Exactly. I need to put the data I have into context, so it can be transformed into valuable information. This entails that my data has the necessary quality and the validity for my use case. As a company, I then need measures and standards to regulate the availability, integrity and security of my data during its whole life cycle. The wholeness of these measures is what we call data governance.
Mr. Göbel, you are an expert for data governance at Audi. Why does a car manufacturer need data governance?
Göbel: For Audi as a car manufacturer, data governance is a central element on the way to a premium digital car company. Therefore, we are digitizing business models and our production and we are developing autonomous driving and intelligent mobility services. But it’s clear that only those who have defined the standards for the interaction with data and use a basis of reliable data, can use the potentials of the new business models to the fullest, e.g. autonomous driving and artificial intelligence.
Does this mean that data governance is the basis for autonomous driving and the connected factory?
Göbel: Yes, because data governance regulates data sharing – without the latter autonomous driving or our Smart Factory, meaning the connected factory, wouldn’t work. Let’s take a look at the robots in our production. The latest models are equipped with the so-called “predictive-maintenance” function. This means that they transfer operating data into the cloud of the robots manufacturer. In the cloud then, artificial intelligence will manifest, for example, that a part of the robot has to be changed. Data governance helps me regulate the rules for data exchange with the manufacturer: Which data do I submit to the cloud and what will be done with this data? And we especially make sure that the data is secure. We see the same in the car-to-x communication.
Göbel: For autonomous driving or the communication between car and infrastructure, the so-called car-to-x communication, it is important that all participants speak the same language. Therefore, data governance will become important in the cooperation with traffic authorities.
What exactly are the measures for data governance?
Tschachtli: Data governance consists of different building components. First of all, it’s about the quality of my data. I have to ensure that all relevant data used in the company is accurate. Secondly, it’s highly important that I comply to legal requirements, such as the protection of personal data. Thirdly, I need data maintenance, the administration of data through its whole life cycle, making sure that the topicality is always up-to-date. The fourth building component is data management. This means that all the statistical data in a company needs to be put together in a conclusive entity, the so-called single source of truth. This includes data from products, customers and suppliers. In the fifth component, all applications that take care of maintaining my data, access the master data platform. Thus, I enable reliable analyses and reports in all branches of the company. This also means that data governance needs to be cross-functional and interdisciplinary.
What does data governance look like at Audi?
Göbel: At Audi, the topic of data governance for data that regulates the company is actively pursued by the finance division. Because there the data of different company divisions flows together. As part of the transformation program 1Finance for Audi, data governance is implemented at an interdisciplinary level. We’ve had a lot of good experience with that. It’s as Mr. Tschachtli says: It is essential that the master data is accurate and complete, can be maintained at one location and is available in a harmonized state for other company divisions. Only then can I ensure that sales, technical development and production have the same understanding – and that means throughout the Audi company in all markets.
How do you ensure that all divisions speak the same data language?
Göbel: In the first step, we take a look at the how the different divisions use their respective master data. Together, we then agree on a unified definition and check the processes in which they have to be handled. These standards have to be made available in the master data platform and integrated into our systems. In other words, we create the technical prerequisites for ensuring that our harmonized data is centrally available and can be used universally. And of course, we share our experience with integrating data governance with other company divisions. Thither, where the data emerges primarily.
This sounds very complex and time-consuming…
Tschachtli: It is. With data governance, it’s not about quick wins. It’s about using the full potential of a company in the long run. Up until now, many companies have a hidden treasure trove of data that hasn’t been pulled up from underneath the sea. Endurance is needed to claim this treasure.
Göbel: But this investment will pay off. If I enrich, combine and analyze data, I can create a lot of new processes and products
Tschachtli: This is also important for the work within a company. Studies show that up to a quarter of daily work time is used for informational search. Information isn’t collected centrally, but everywhere and in different formats and applications. This data has to be processed so that it is available for the whole company and quickly accessible. That’s how you save valuable time with data governance.
So working as a data governance expert at Audi is a real dream job?
Göbel: For me, it is. I can lay down the tracks today and create a lot. It is a lot of fun. And it’s most definitely a job with a future perspective. The amount of data we have to process will increase continuously. All of this indicates that data governance will become more and more important in the future.
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