DESIGNED TO OBTAIN STRONG CORPORATE GOVERNANCE AND INCREASED PROFITABILITY
Forum Traffic Light is a decision support tool designed to improve timing of your bunker procurement. Optimized timing will reduce your procurement cost and improve operational efficiency. The Traffic Lights system requires no software installation and no change of current procurement routines. The intuitive design makes it easy to use and requires minimal training before use. The savings occurs as soon as the system is implemented, offering a unique value proposition with no investment required before savings obtained.
Traffic Light System
Predictive models combine human behaviour science, artificial intelligence, fundamental research and Machine learning for continuous development and quality improvement.
- The system uses API solutions from live oil prices and runs daily/intra-day calculations and forecasts for bunker prices world-wide.
- Actual performance studies confirm that use of TL methodology will over time save 3-5USD pr ton bunker consumed.
- More than 63% of potential savings in each bunker windowed obtained over time.
- Operators enter vessel name, ETA and best estimated bunker window (first and last possible day of ordering). The system advises on the optimal procurement date.
- The system will keep track of its own performance when procurement data have been entered into the system, and make this available to the clients.
- Thru API we can connect to any other system for integration and optimal operation.
- The traffic light model can be explained in three steps
- Monthly underlying forecast combined with daily oil price (predictors)
- 15 days forecast on oil price is calculated
- Our algorithm decides which light to give each vessel
- Monthly underlaying forecast and daily oil price
- Used to decide direction of the market
- Other layers in the model:
- Pattern recognition
- Filters of market sentiments and human behavior science
- Combined it creates a 15 days forecast on oil price
- Input for the algorithm
- The algorithm then decides which light to give each vessel
- Based on market direction, previous forecast and traffic lights combined
Using Machine learning we are continuously working on improving the algorithm