Harsh market conditions make optimising the performance in shipping more and more important. Shipping companies are becoming more and more data driven due to developments in data systems and these harsh market conditions. The goal of this research is to determine how and how much added value can be realised through shipping performance management with the help of a ship performance monitoring system within Spliethoff Group. This research continues after the development of the performance monitoring system. The demand or this research arrived from the fact that simply putting a performance monitoring system in place does not realise added value. Applying the knowledge creation from the performance monitoring system through well structured performance management is what realises the added value. Determining the methods and quantifying the potential results is what is done to realise the goal of this research.
During the research it is found that high data quality is of the utmost importance in order to accurately asses the performance of a vessel. A structured method for assessing the data collected by the performance monitoring is found and applied to the performance monitoring system as a verification. Data quality deficits such as the speed of the ETL processes, incorrect data blending and calculations are identified and corrected. This led to a near live, high quality data stream which can be used to asses and optimise the performance. Continual assessment and improvement of the data quality is recommended.
Suitable methods to analyse this data to create knowledge are determined. A form of hybrid modelling where simple theoretical models are fitted to the filtered data using regression is used to create baselines and give a clear overview of the effects of certain operational parameters on the performance of a vessel. These models can then also be used to increase the accuracy of tools such as the weather routing and voyage planning tool. Benchmarking between sister vessels or the baselines is seen as a good means to identify performance deficits. Visualising and analysing the data with the help of a BI tools is a good way to share the knowledge throughout the company.
The performance management in place at Spliethoff is assessed to form a baseline to improve upon. It became apparent that Spliethoff overall has a good idea how to optimise performance but it does not have the information or data needed to do so. Since there is no information about the gain in performance of certain tools they are not used correctly. Being able to show the performance gain from using these tools is an important benefit of the performance monitoring system. The communication and knowledge sharing throughout the company can also be improved with the use of the performance monitoring system. Poor follow up from upper management when performance deficits on top of this indicate that a lot of value can be created with an improved performance management plan which incorporates the performance monitoring system.
A new performance management plan based on ISO 50001 is proposed to realise this value. Due to the available data the management plan focuses on reducing fuel costs and optimising voyage planning.This is done by awareness creation through performance dashboards which also increase the information sharing between shore and vessel. A change in company culture to a more data based decision making and communicative culture is promoted and implemented through this plan.
To determine how much added value can be realised, the costs and value realisation potentials of the performance management system are specified. These are then used to determine the net present value of the performance management project for several scenarios. A large fleet and a small fleet implementation are researched. The total capital investment is either €543,000 when only the large consumers of the fleet are included (small fleet) or €1,310,000 when almost the entire fleet is included (large fleet). Only the direct monetary value is used to determine the net present value but indirect and non monetary values are also mentioned. The direct monetary value potentials are derived from operational cases where performance deficits have been identified. The resulting total added value (NPV) of the small fleet implementation ranges from €2,165,970 in a pessimistic scenario to €8,711,272 in an optimistic scenario after 11 years. €6,000,146 is the expected total added value realisation for the small fleet implementation after 11 years. For the large fleet the results are: €4,966,756 for the pessimistic scenario, €18,103,704 for the optimistic scenario and and expected added value of €12,805,994 after 12 years. Most scenarios have a pay back period of less than 2 years with the exception of the pessimistic scenario of the large fleet which has less than 3 years. All indirect and non monetary value is seen as a bonus on top of this meaning that there certainly is a lot of added value to be realised by implementing performance management which is supported by a performance monitoring system.