Collaborative shipping: cheaper and better for the environment

‘We can’t wait any longer’, says Professor Robert Boute. ‘Companies are under pressure to deliver our orders faster than ever before. It’s not hard to guess the consequences: trucks full of air rather than goods. Various studies have shown that one in four trucks are driving around empty, and those that are not empty are only filled by 57%. Things can and should be better. We have developed a tool that will help companies substantially raise the efficiency of their shipping operations.’

The solution? Collaboration!

Collaboration between different parties in the same supply chain has been around for a relatively long time, partly in order to manage fluctuations in supply and demand. In the case of collaborative shipping, also called shared shipping, parties from different supply chains join forces to combine their shipping operations as efficiently as possible.

Is that really so unusual? Haven’t logistics providers been combining their shipping for a long time? ‘That’s true’, says Boute. ‘But in the case of collaborative shipping, companies seek out opportunities for collaboration in advance. If required, they will adjust their planning accordingly and bring forward or delay the dispatch of their goods. Logistics providers tend to join forces during the implementation phase rather than in the planning phase, as they generally schedule the various shipments early on in the process.’

Big data analytics

How do you find opportunities for collaboration? After all, that’s the crux of the matter. Boute: ‘We have written an algorithm that is capable of analysing the extremely large data sets for all the transport routes of one or more companies extremely quickly, looking for ways to combine geographically compatible shipments. Among other things, it uses the GPS coordinates of the beginning and end of each route.’

Typical examples of opportunities include:

  • Routes with a starting and destination point in the same area, making it possible to use the same means of transport and thus increase the load factor (bundling).
  • Routes in the opposite direction, thus avoiding an empty return journey (backhauling).
  • Different routes which more or less tie in with each other allowing them to be combined into one return trip, also putting an end to empty return trips (round trip).

‘Bundling, backhauling and round trips are the terms that have us the name of our algorithm: BBaRT’, explains Boute. ‘At the end of the journey, BBaRT provides you with a list of opportunities ranked according to potential cost savings and environmental benefits.’

Participate in the sharing economy

The algorithm also identifies collect and/or drop-off opportunities, allowing you to pick up an extra load en route, i.e. near an existing route, and drop it off further along the same route. Boute is enthusiastic: ‘This allows us to tie in seamlessly with the sharing economy. With collect and/or drop-off, you really are sharing your shipping. Many things will naturally need to be resolved before the “Uberisation” of freight transport is achieved, but one thing is certain: our algorithm demonstrates genuine opportunities for participation in the sharing economy. And the sharing economy is where we are heading, I think.’

What’s wrong with Excel?

The strength of the BBaRT tool is that it can handle data sets of almost any size. ‘You might just about manage to analyse a few hundred transport routes in Excel, but for 10,000 routes you need heavier artillery’, Boute explains with a smile. ‘As far as I am aware, BBaRT is the first and currently the only algorithm which can efficiently select opportunities for collaboration from a huge amount of data.’

‘I often hear people say that they believe that there are opportunities, but can’t identify them’, he continues. ‘Our algorithm can give companies the insight they need. There is a lot of talk about big data and digital transformation. Well, BBaRT is an example of what that really means.’

Not just road transport

It is possible to distinguish between three phases in the collaborative shipping process: (1) the identification of opportunities and possible partners, (2) the planning and synchronisation of the shipping, including its frequency and (3) the effective implementation and maintenance of the collaboration. Boute: ‘Our tool supports the first phase and various companies have already used it successfully. We are currently working hard to expand BBaRT to add the capacity for effective transport planning, taking into consideration such aspects such as frequencies, quantities and delivery conditions.’

BBaRT is also suitable for every mode of transport. So far, Boute’s team has focused on road transport but the big challenge today is precisely the shift from road to rail transport. How can we ensure that more goods are shipped by train? Once again, the solution lies in collaborative shipping. ‘What applies to road transport applies all the more to rail transport. After all, rail containers are even bigger than those carried by trucks. The greater the economies of scale that can be achieved through collaborative shipping, the easier this shift will be. In addition, this will also make multimodal transport accessible to SMEs: working together makes it possible to achieve the freight volumes required to bring rail transport within financial reach.’

What are you waiting for?

Collaborative shipping allows companies to reduce transport costs, which is generally also their primary motive for seeking out opportunities to share transport. However, Boute feels that there is also another motive: ‘Collaborative shipping enhances the sustainability of logistics. Improving the load factor reduces the number of vehicles on the roads. Fewer vehicles means lower emissions of harmful greenhouse gases, less congestion and fewer chances of accidents. Reasons enough to consider collaborative shipping, it seems to me.’

Source: The paper "Tri-Vizor uses an efficient algorithm to identify collaborative shipping opportunities" can be requested from the authors.

About the authors
Robert Boute is a Full Professor in Operations Management at Vlerick Business School and the Faculty of Business and Economics at the University of Leuven. Stefan Creemers is an Associate Professor at the IESEG School of Management and is affiliated with the Research Centre for Operations Management within the Faculty of Business and Economics at the University of Leuven. As a researcher, Gert Woumans was affiliated with the IESEG School of Management and the Research Centre for Operations Management within the Faculty of Business and Economics at the University of Leuven. Jeroen Beliën is a Professor at the Faculty of Business and Economics at the University of Leuven and coordinator of the Research Unit Centre for Information Management, Modelling and Simulation at the Brussels Campus of the University of Leuven.

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