Research
The Port of Rotterdam Authority has developed a dashboard that shows the performance of inland navigation in the past (barge performance monitor). Can that dashboard be extended with a prediction of the port staying time on the basis of publicly available data? The research shows that a rough prediction can be made with public data. To increase accuracy, more data is needed.
On the basis of the available data from the past, it is tested whether the current public data set is sufficient in making an accurate prediction. It turned out that this is not yet the case: more data sets are needed to arrive at more reliable predictions.
Influences on the staying time are: wind speed, day of arrival (which day in the week), but also, for example, the operator concerned and its way of working.
Opportunities
- Prediction of staying times – With public information a rough prediction is possible. But only when aggregated data is added to it, maximum predictability and full insight are possible.
- Extra services – Improved service by The Port of Rotterdam Authority to customers.
- Decision information – More information helps the carriers in making them choose for the most suitable modality.
Challenges
- Has all possible data that may be helpful been identified? Or have data sets still been overlooked, and what can their possible added value be?
- Are stakeholders prepared to make their data available? (privacy versus transparency)
- How much certainty in the forecast is desirable? How exact does the prediction have to be, to be useful in practice for the various parties involved?
Impact
It will be possible to better manage expectations, for example in the choice between transport modalities (inland shipping, road, rail).
Partners
Erasmus University Rotterdam, Port of Rotterdam Authority, TNO.
‘The Barge port stay predictor project has given us useful insights into the predictive value of combined open data sources. The project results build on the Port of Rotterdam Authority’s endeavour to provide information on the reliability of the logistic networks throughout the port’
‘The study shows that the port calls that need to be predicted cannot be seen as autonomous processes, but are strongly determined by company specific characteristics.’
‘The project shows that combining different sources can lead towards accurate estimates of port calls. External factors as well as the business models of the various companies have to be taken into account.’
This project is part of the Smart Logistics roadmap. For more information about this project or this roadmap, please contact project developer Anique Kuijpers.