DONG Energy backs up clean power vision with hard enterprise data.
by Tara Swords, May 2011
Energy companies that have a largely coal-based power supply are in a unique position of being both the cause of and the answer to many of the world’s environmental problems. Denmark-based DONG Energy is one such company. Acknowledging its status as one of Denmark’s largest emitters of carbon dioxide (CO2), its leaders have committed to becoming part of the solution with aggressive sustainability goals that aim to minimize the company’s environmental impact. The company’s official policy is to cut its CO2 emissions per kilowatt-hour by 50 percent between 2006 and 2020, and by 85 percent by 2040. By the end of 2010, DONG Energy was already further ahead in meeting its goals than anticipated. The company has begun closing down coal-fired power-generating units and has shifted its focus to natural gas, biomass, offshore wind energy, and the development of second-generation bioethanol.
The current incarnation of DONG Energy formed in 2006 when a number of large Danish energy companies merged to become DONG Energy. From the outset, the company’s decision-makers took environmental sustainability seriously, and that same year they joined the United Nations Global Compact calling for voluntary adherence to 10 principles, including three that are intended to protect the environment.
But there’s no sense in setting goals if you can’t track progress toward them.
“I think many companies have visions for the sustainability or corporate social responsibility [CSR] work that they are doing, but if they are not converted into concrete goals that you can measure, it’s very hard to know if it is just talk or if it’s also action,” says Niels Strange Peulicke-Andersen, common systems manager in the Quality, Health, Safety, and Environment group at DONG Energy.
In 2006, DONG Energy also became part of the Global Reporting Initiative, which provides a universally accepted framework for reporting nonfinancial sustainability data. The company went a step further and brought in an external auditor to declare the data solid so it could be included in the company’s annual CSR report.
Unfortunately, things didn’t go as planned.
“The first assurance statement we got wasn’t very good, actually,” Peulicke-Andersen recalls. “It said they could state that we are very good at adding numbers together on a company level, but we were not completely sure of the quality of data that we gather at that level. That’s when our department got the assignment from the CEO that next year he wanted a very good assurance statement from the external auditor.”
These reporting problems are typical of enterprises just beginning their CSR journey and preparing their first CSR reports, says Birgitte Mogensen, the PricewaterhouseCoopers auditor who performed DONG Energy’s first nonfinancial data audit. “When no consolidated CSR reports are prepared in an enterprise, there is no need for group accounting instructions, and I often experience that this is forgotten by those responsible for reporting at the group level,” Mogensen says.
So the executives at DONG Energy turned to Oracle Hyperion Financial Management to replace a cumbersome and error-prone spreadsheet-based system for tracking sustainability data. In the process, they dramatically improved data quality, gained visibility into every part of the business, and created new appreciation for the company’s environment, health, and safety goals.
Finding the Right Solution
The first audit went poorly for several reasons. First, Peulicke-Andersen’s team was collecting data using a Microsoft Excel spreadsheet. Every month, people in different business segments e-mailed their spreadsheets to Peulicke-Andersen’s team, which copied and pasted the numbers into the master spreadsheet. But spreadsheets are prone to human error; it’s all too easy for someone to accidentally delete a formula in a cell, overwrite someone else’s data, or overwrite an entire file version. The spreadsheet owners might never know that something was incorrect.
Even if users were careful to avoid breaking formulas or overwriting data, the data itself was sometimes bad. For example, the spreadsheet required users to record things such as “production” and “emission,” but those terms didn’t have universal meaning throughout the company. People were also using different conversion factors when entering data, resulting in apples-to-oranges comparisons.
“You can measure something at different points in the system,” Peulicke-Andersen says. “But you need to agree: is it, for example, net or gross production? You have to have the same definition of the data.”
In addition, DONG Energy’s current power generation ownership structure is far more complex than it was in the past. For example, the data reporting must allow for partial ownership of wind farms. If DONG Energy owns only a portion of a facility and partners own the rest, the spreadsheet would need to indicate that the company is responsible and consolidate only a portion of the facility’s production.
Finally, it was almost impossible to know whether all relevant data—correct or incorrect—had even been collected. DONG Energy has more than 160 legal entities, and some of those entities were being overlooked in the spreadsheet.
“When the external auditors came to us, they said, ‘How do you know that you get all the data from all the companies into your accounts?’” Peulicke-Andersen says. “They took the legal entity chart of DONG Energy. They just put their finger through a few of them and said, ‘What is happening in that company? What kind of production? What activity is happening? What data are you gathering from that specific entity?’ And it was a completely new way for us to look at the company.”
It became clear that Peulicke-Andersen and his team needed to overhaul data gathering and reporting at DONG Energy. A spreadsheet wouldn’t cut it.
“We knew that we needed a database to put the data into, instead of spreadsheets, and we knew that we had to import or use all of the basic principles of financial reporting,” Peulicke-Andersen says. “We researched the market for suitable software solutions and asked around: what did other companies use?”
As it turned out, Peulicke-Andersen’s department wouldn’t need to invest in a new solution. The answer to its problem was already within the organization.
Raising the Bar for Data Quality
Elsewhere in the company, complex reporting was already being done without a hitch every day: on the financial side. When Peulicke-Andersen learned that the finance department used Oracle Hyperion Financial Management, he asked his colleagues in finance to show him how the tool worked.
“I saw that it’s a very flexible tool,” he says. “You can specify your own accounts, so they don’t really have to be financial accounts.” Using this approach, Oracle Hyperion Financial Management would let Peulicke-Andersen’s team track things such as CO2 emissions or waste. He was intrigued, but the finance department wasn’t eager to open up its Oracle Hyperion server to the nonfinancial side until Peulicke-Andersen and his team could dramatically improve their data quality. So they started with a separate database on a separate server. But one thing that Peulicke-Andersen could use was the finance department’s in-house knowledge of the Oracle Hyperion solution and its map of the corporation’s complex structure.
The results came quickly. Oracle Hyperion Financial Management helped DONG Energy improve visibility into every area of the energy production chain and spot where the greatest improvements could be made. The Oracle Hyperion solution not only improved the quality of the nonfinancial data collected; it also gave Peulicke-Andersen’s team the ability to look beyond raw numbers and understand the relationships between them.
“You need to be able to show the numbers in many different ways depending on the target group and the content that it’s being used for,” says Peulicke-Andersen. “That’s why it’s very good to have the data in a database where you can extract data in multiple ways. You can relate emission to production. You can relate it to an index number. You can say, ‘Now I just want to look at the Danish part of the production.’”
Subsequent audits have proved the value of the new system. Mogensen says there are two ways to perform an audit: the auditors either test data themselves or they test the controls the company uses to collect data. In CSR reporting, she says, there is growing consensus that auditors should be testing controls, not the data itself.
Mogensen says DONG Energy is at the leading edge in this regard. “I expect that in three to four years, our assurance will be based only on DONG Energy’s own controls being effective for ensuring correct data for the CSR reporting.”
From Sustainability to Profitability
Although the majority of DONG Energy is owned by the Danish state, it operates as a company and must remain profitable to stay in business. That means no matter how beneficial its CSR initiatives are for society, the environment, and end customers, they also must contribute to the bottom line.
“I think the next step, when you have raised the quality of the nonfinancial data, will be that people will expect companies like us to link the data closely together and help interpret for stakeholders what it means in terms of financial performance when the nonfinancial data is going up or down, or vice versa,” Peulicke-Andersen says. DONG Energy has put itself in a unique position in that regard, making the core of its business strategy to help solve society’s need for reliable and clean energy—and to do so on a sound commercial basis. While DONG Energy aims to halve CO2 emissions per kilowatt-hour between 2006 and 2020, management also wants to double earnings in the meantime.
Currently, DONG Energy uses Oracle Hyperion Financial Management to consolidate data at the corporate level while the business segments use their own software to gather the data initially. In the near future, Peulicke-Andersen anticipates that the other segments will begin using the Oracle Hyperion solution too. They also plan to streamline the processes by using automatic transfer of data from datasources into Oracle Hyperion Financial Management and to evolve further in the direction of financial reporting by adjusting the procedures that define who can input and alter data at what times, helping to ensure that data quality is maintained and numbers are thoroughly vetted before being locked down and moving up the corporate approval chain.
Peulicke-Andersen says the software’s flexibility and the ability to use the entity-based company structure that the financial department founded and maintains in the system has changed everything.
“We got most of the data in before, but it’s nothing compared to today, where we have implemented the financial principles for reporting on financial data gathering. We are much better prepared for answering the need for reliable and transparent data in a rapidly growing international company with an increasingly complex company structure,” he says. “It’s a completely new world.”