In today’s rapidly changing energy markets, opportunities abound for firms that can adapt quickly and move fast. However, large energy firms often struggle to be agile enough to beat the competition. Enter consultancy of the year, d-fine. The Germany-based firm has a strong focus on technology and quant-based solutions that help clients operate more efficiently and make better decisions, thereby becoming better able to adapt and move quickly.
The team consists of mathematicians, computer scientists and physicists, who seek solutions to a complex range of clients’ challenges through the employment of machine learning and big-data technologies.
“We have a blend of quantitative and technical skill in the company, which is the basis of our success,” says Tilman Huhne, partner at d-fine. “From day one, we combine our long-term experience in daily energy business and IT processes with our client’s understanding to develop a tailored solution. We don’t need to have any interfaces between business and IT here, because we work together across these groups. That is the DNA of d-fine.”
As well as the physical disruption to energy markets from ever-increasing de-centralised supply and renewables, energy companies are also having to deal with the digital revolution.
“Many companies, especially in the energy sector, approach us with questions on digitisation, and how to position themselves in a rapidly changing business environment,” says Jonas Bräuer, manager at d-fine. “Our role is to find suitable and efficient approaches even under considerable uncertainty, always leaving just the right amount of flexibility for rapid further development as the need arises. In this, we always seek to collaborate closely with our client, respecting his/her specific views and experience.”
Firms are keen to minimise fixed costs where they may face further change, and that includes headcount. Automation is enabling firms to build out operations with feedback loops that support their ongoing growth and reduce the need for additional headcount to manage processes.
Our role is to find suitable and efficient approaches even under considerable uncertainty, always leaving just the right amount of flexibility for rapid further development as the need arises
Jonas Bräuer, d-fine
For example, d-fine has supported firms through the use of predictive systems to provide information to management. The underlying technology has included algorithms and multiple machine-learning techniques such as decision trees and neural networks, which are used to assess different measures, from the conditions of assets over time to the projected feed-in from solar photo-voltaic generation based on weather and sensor data.
It has also worked with several European energy firms to develop intraday power trading operations based on renewable energy sources. The many variables involved in optimising trading volumes for a fluctuating power feed-in requires a highly automated process. D-fine built bespoke systems for its clients based on trading volume optimisation algorithms that took into account real-time intraday pricing and price forecast data.
The firm says it has successfully introduced intraday trading operations into firms, as well as significantly improving trading results at other firms.
“The automation of intraday trading processes mainly helps traders and portfolio managers to focus on the handling of non-standard conditions such as asset outages, unexpected market movements or certain highly volatile weather regimes,” says Bräuer. “To our experience, the risk/return profile can be improved by up to 30% by the implementation of a well-balanced ratio of manual and automated decision processes.”
Automation also allows a larger number of trades to be handled, shortening execution and adjustment times. However, any systems that are reliant on data need to be assured of the quality of information they are using to deliver output.
D-fine has leveraged big-data technology, which can process large amounts of complex and unstructured data, such as photographic images, to feed both analytical and automated functions. For example, it has used granular weather data to improve price forecasts and image-processing to automate quality management in industrial processes.
“Big-data technologies can also offer a viable foundation for those clients whose existing data analytics and storage processes are reaching their limits in terms of performance, size and sustainability,” Bräuer says.
D-fine’s focus on quantitative analytics combined with technological skill has enabled clients to overtake their competitors “within a very short period of time”, the firm claims.
With so much riding on the expertise of its employees, hiring and retaining talent is vital to d-fine’s future success, the firm acknowledges. To this end, there is a strong ethos from management to select and retain like-minded people who enjoy working on challenging projects while putting client interests first. Focusing on a specific set of academic backgrounds helps to ensure a ‘science culture’ and natural fit, the company says.
“We constantly encourage and support our more than 700 experts to learn new concepts and challenge the status quo,” Huhne says. “Apart from offering comprehensive internal and external training, we allow our consultants to advance the development of new business areas and pursue completely new ideas in our think-tank programmes, in parallel to their day-to-day client work. These are very well received.”
This article was amended on May 29 2018 to reflect the fact that not all d-fine employees have previous energy experience.