Fortum Builds a Company-Wide Financial Reporting Engine with Snowflake, Reducing Costs by 85%

With 130 subsidiaries across the Nordics, Fortum relies on accurate financial reports, delivered at speed, to set the context for business decisions—such as electricity trading. Discover how the company uses Snowflake to deliver a company-wide financial reporting engine  cost-effectively and at scale, enabling a more data-driven culture.

Fortum, headquartered in Finland, is among Europe’s cleanest energy producers and one of the biggest companies of its kind in the Nordics. The company wants to power a world where people, businesses, and nature thrive together. 

But in an increasingly volatile energy market, monitoring the financial position to set the context for business decisions falls largely on Fortum’s finance function, which needs to be able to quickly and flexibly report on the organization’s finances across different sub-companies and timeframes. 

Jaakko Riipinen, Corporate Data Domain Lead at Fortum, explained the importance of data in achieving and maintaining good financial management and agility: “Data is extremely important to Fortum. Because it’s a listed company, we need fast and accurate reporting. Moreover, our finance function covers 130 separate legal entities and frequently handles mergers and acquisitions. And we’re always looking to optimize our assets and customer data.” 

Around 1500 people across a wide range of  roles, from accountants and financial controllers to top-level managers, rely on Fortum’s financial data, meaning it has to be highly accessible while remaining completely secure and compliant. 

But a mix of legacy technology, plus the costly requirement of maintaining monolithic infrastructure, meant that Fortum’s people were hindered by time-consuming, manual processes, which restricted innovation. 

“Our legacy cluster database, combined with traditional code and ETL tooling, meant our work was inefficient,” said Riipinen. “Everything involved lots of manual coding and effort. Our data infrastructure had simply reached the end of its life.” 

To help fulfill its automation ambitions and deliver greater efficiency, consistency, and accuracy across its financial processes, Fortum needed a cross-functional data solution that could combine data from multiple sources and different lines of business. 

Since Fortum was already using Snowflake for other use cases, it decided to carry out a proof of concept (PoC) using Snowflake’s Data Cloud to show that it could meet the company’s financial reporting needs. Since the PoC showed good results, this was followed by a full migration.  “We performed a one-to-one migration from our old environment with support from Snowflake’s Professional Services and local implementation partner, Solita,” explained Riipinen. “We immediately noticed everything accelerated, and far less maintenance was needed.” 

As part of its cross-functional ambitions for the business, Fortum has focused on data democratization. The company uses Snowflake’s Data Cloud to give business users quick and advanced data access using only basic SQL skills, meaning it has accelerated time-to-insight and decision-making. 

The company also uses external tables to directly access the semi-structured data within Snowflake. And by connecting the Data Cloud to its Microsoft Azure Data Lake, the company benefits from fast and seamless data loading between the two platforms. 

But achieving greater flexibility hasn’t come at the cost of security and governance. In fact, Fortum uses Snowflake for role-based access control, ensuring only the people who need to retrieve information from particular data sets can do so. 

The company maps snowflake roles to Active Directory groups to enable Single Sign-on security, and ensure that only the right people have access to data.. And it uses Snowflake’s IP filtering to block access altogether from IP addresses outside of its range. 

Fortum also uses Time Travel, a tool within Snowflake’s platform that allows the company to query, clone, and restore historical data for a defined time period. This means that even data changed or deleted within 90 days is never lost and can be recalled instantly. 

“The security features in Snowflake ensure our data is secure no matter what,” said Riipinen. “The platform has also removed the need for any database administrator involvement, accelerating data access without the risk.”

Moving its data environment to Snowflake’s Data Cloud has opened countless possibilities for Fortum to use its data more innovatively. For example, the ability to consume raw JSON formatted data directly from the data lake enables it to continually adapt to modern data processing techniques. 

And as Riipinen explained, the company can achieve this at a fraction of the cost compared to its legacy environment: “The amount of data we store has a minimal impact on what we’re billed—which gives us the freedom to store an unlimited amount of financial forecast versions without worrying about cost. What’s more, we now have a cross-functional data environment, which would have otherwise been really painful to achieve using our old platform.”

In fact, Fortum has made substantial cost savings of about 85% per year. “Our management team is very happy with the cost savings,” said Riipinen. “Using Snowflake also means we can develop faster with our existing people—and process up to 70,000 queries each day.”

And it’s not just direct savings that now benefit the company. Riipinen and his team have even used Snowflake to improve source-to-pay KPI analysis, streamlining controlled purchase orders and ensuring all vendors are approved. 

“The biggest benefit Snowflake offers us is the ability to reach a level of reporting that we would never have been able to achieve with our old solution,” added Riipinen.

Fortum’s financial data processing improvements have come at just the right time to satisfy new and developing environmental, social, and governance (ESG) reporting standards. It’s why Riipinen is now focusing on automating the company’s corporate sustainability reporting in Snowflake, using the platform’s cross-functional capabilities to combine and process wide-ranging data sets from across the business and each of its branded sub-divisions. 

Going forward, the company also plans to develop a new observability platform in Snowflake,using machine learning to gain insight into the accuracy of its forecasting models.