By Sebastian Kaus, Data Governance Lead, Vattenfall
Sebastian Kaus is an engineer and Data Governance Lead at Vattenfall, a leading European energy company. He helps people work more efficiently by bridging the gap between conventional engineering disciplines and innovative data-driven approaches. In this blog, Sebastian shares how Vattenfall uses Alation to promote data culture as they evolve into a data-driven organization.
The Goal: Become a Data-Driven Organization
At Vattenfall, our vision is to achieve “fossil-free living within one generation.” In fact, Vattenfall uses hydrogen to operate our power plants more efficiently, sustainably, and profitably. These are complex processes that we’re focused on continuously improving. This requires optimizing asset management and scheduling maintenance in a smarter way. For that, we need trusted data.
The need for trusted data extends to all areas of the business. Not only are we decarbonizing the production of electricity — we’re also working with partners in other industries, such as steel production. For example, we’ve developed a process where we use hydrogen instead of coal to create steel. Creating this product requires exchanging information with our partners, who need to trust the data from Vattenfall.
To make the right decisions, we need to have deep insights and understanding. Vattenfall needs to become more data driven. We need to be on top of the data as a resource to achieve the goal of fossil-free living within one generation
How to Facilitate a Data-Driven Culture
Here are key strategies to establish a data-driven culture within your organization:
Create a Data Culture
How does a company become data driven? Would it surprise you if I said it’s about building a data culture? It’s easy to deploy BI models and databases and so on. But if you don’t have a data culture in place, you’re going to have issues.
I use the analogy of Health and Safety initiatives. Power plants can be dangerous, and these initiatives keep workers safe by enforcing safety-first behavior. Today these initiatives are so much a part of most company cultures that a technician on a production site won’t hesitate to tell the CEO to put on a safety helmet.
But now imagine if that same technician goes to the site to fix a piece of equipment, like a cracked boiler. If he doesn’t have the right information about the problem, he might bring the wrong tools and the wrong spare parts. He might attempt to fix the wrong problem, and in so doing, set the stage for catastrophe. In this sense, incomplete data can be just as dangerous as not wearing a safety helmet. It ultimately affects safety, production, and the company’s profitability because the asset remains offline.
Being data driven should be treated in the same way as health and safety, where everybody in the company understands how important it is for everyday situations.
Focus on the Business Problem Behind the Data Problem
If you want people to understand why becoming data-driven is so important, start with the business problems behind the data. Ask leaders:
- What’s important to the business?
- Can we mitigate risk by better understanding data?
- How can we use data to increase profits?
Convert the data problems into business problems; don’t make it just about the data, using fancy buzz words. It’s tempting, but at the end of the day you’re running a business. Describe what you’re doing with data in terms of that business, and people will understand the need because they understand the business.
In the case of Vattenfall, we had several siloed departments, all working with data, some of it even overlapping. Although their work also often overlapped, people weren’t collaborating around the information. If they don’t talk to each other, they won’t trust each other.
Before Vattenfall had a data catalog: Departments were siloed, and only some data was shared.
To build trust and communication, we began with a business problem that affects all departments: How can we improve the lifespan of the assets that create electricity for our fossil-free steel production?
The solution was to implement predictive maintenance, which would require the departments to work together and to share data among themselves. First, we documented the entire proposed process, especially the data behind it. Then we needed to break down the silos and connect the dots between departments, while providing context and transparency about the information we were working with.
For that, we implemented the Alation Data Catalog. It helps us to collect the information and share it with the people who need it. It’s user friendly and requires virtually no training. We use the catalog a bit like Google, adding simple search terms so people can find what they’re looking for.
Our vision is to create a community around our data where people simply reach out to each other and share information. We’re creating a culture where people know and trust the data they are working with.
After implementing a data catalog: Departments collaborate around shared data with ease.
Implement People-Based Data Governance
While we were documenting the data, we also identified the people who knew the most about that data. From there, it was straightforward to assign those people as data stewards. They’re already responsible and accountable for the data, so information stewardship within the data catalog came quite naturally. And because they already feel accountable, they’re quite willing to help when we ask them how we can do things better.
Let me be clear: This is not a fancy “data project” that we’re running. We’re embedding a data culture around information governance. Collaboration around well-governed data is becoming more and more part of our organizational DNA, our culture. We basically sneak it into the normal way of working.
We don’t have a “governance program” like some companies seem to have. Data governance is something we do every day.
Let The Experts Do the Talking
Once you’ve implemented data governance by assigning data stewards, you need to continue to reinforce your growing data culture. You might implement a data governance council or similar group. But the best people to spread the word about adopting the data catalog are the influencers in your company. Those are the people who are actively using the catalog to solve their own business problems. They can help build and strengthen your data culture.
At Vattenfall, these folks are our best ambassadors. When they talk about how Alation helped them to solve issues, such as finding information more easily, others learn best practices for data culture, too. It’s basically an avalanche effect as word spreads and use of the data catalog snowballs.
One thing I’ve learned: You can’t just push the data catalog on people. Force doesn’t work. If you try and force it, you will end up with bad quality data and no community.
Collaborate for Success
Today, our reporting and analysis processes are a lot more rational because we closed that trust gap between departmental silos. This enables us to progress and become more and more data driven. We’re documenting what we’re doing and working together instead of in siloes. And there are clear roles and responsibilities because of our data governance through the Alation catalog. All of this is underpinned by our data culture, which is where we started our journey.
Alation is democratizing our data. It’s bringing people together to collaborate to solve our business problems. The more people trust the data and collaborate around it, the more efficient and profitable Vattenfall will be.
And our success is good for the planet. As we strive to end human dependence on fossil fuels, we know data is a powerful ally in this journey. And with Alation, we empower our entire team with trusted data for a brighter tomorrow.