Revenue management - Cover image
Revenue management - Cover image

Revenue management

DSB Digital Lab

DSB Digital aims to be at the forefront of innovation within DSB, and educate other parts of the business on how to be agile. As an organization, DSB has an enormous ambition to be subsidy free by 2030 and innovation is, therefore, one of the key focus areas. At the beginning of 2018, NoA Ignite became a design partner to DSB digital Lab to bring hands-on design and development skills, outside inspiration, ideas, approaches and insights. One of our first projects was Revenue Management.

The Challenge

The key project for 2018 was for the revenue management part of the business. Having already had success with a previous IT project, the DSB Digital Lab wanted to see how they could bring further value to the business using existing and new data sources.
The structure to the DSB Digital Lab is that each project has a maximum of 2 months for Insight, 6 months for Market and 12 months for Value. Hence the decisions to build anything must be made with a clear understanding of what the problem is and how the solution will bring value.
While this project needed to bring value to the business right away, there is an existing process of moving to a completely new system with much better tools for revenue management. However, this process will take many years and the business will be missing the extra revenue. This project would, therefore, also become a good experiment for learnings that inform the requirements of the new system.

Artboard Copy 2
Artboard Copy

The Solution

The team consisted of data scientists (DSB), developers (HGW + DSB), designers (HWG), the actual revenue managers and a product owner (DSB).
Their first task was to find both the key insights and critical problem spaces. The key human insight found was that “every Revenue Manager feels a sense of confidence in the models they have. By making just one adjustment that confidence increases. Confidence in a model increases when the model is proven and results analyzed”. The key problem space was that “we don’t have time to keep track of all future trains to look for opportunities to optimize”.
After several rounds of ideation and learning from both data and the actual Revenue Managers we developed a solution - a calendar which brings together expected demand (from DSB machine learning data) and event information from Ticketmaster API.
The calendar takes the Ticketmaster events (such as concerts and sporting events) and shows them against expected demand. This highlights the potential for one-off optimizations to the Revenue Managers.
This also allows the Revenue Managers to experiment with making specific changes to pricing at a particular arrival station at a specific time.
The psychological nature of pricing also requires that the Revenue Mangers need to be able to see the exact price of specific trains, so they can adjust it when necessary (for example, 299 kr is more appealing than 301 kr.

The Result

The solution has resulted in a weekly increase of revenue of 1.500.000,- DKK each week. That's 78 million DKK in 2018 alone.

The result comes from intellegent analytics and optimizations, and ability made from the Revenue Managers who are now much more empowered to quickly and easily make changes.