Transshipment – where there is a green will, there is a profitable way
Green principles are now prevalent at all levels of doing business, not just to make companies appear more attractive from an external marketing perspective but also in a conscious effort to reduce greenhouse gas emissions and, ideally, costs at the same time.
Logistics have increasingly come into the equation as an area where such efforts could and should be made, representing added value for companies at the same time. By re-assessing the way they transport, store and deliver goods to their many customers from a multitude of points, companies could make major financial and ecological strides.
The widespread use of environmentally-friendly raw materials, recycling of paper for packaging, and reducing fossil fuel consumption are amongst the most common initiatives taken up by businesses to improve their eco-footprint. To this list can now be added supply chain management, especially as regards transportation. Globalisation has caused a great many companies to increase their level of outsourcing, and with this has come extra miles of road travel to be covered (amongst other forms of transport) and therefore a higher potential threat to the environment.
Adding value without raising emissions
Logistics is now a widely-recognised source of added value for the same companies that are also under pressure to improve their environmental track record. Freight transport, storage, inventory management, and the handling of materials all represent areas where companies can optimise their service, beat off competition, and boost profits. However, this can potentially come at an ecological cost which, in the eyes of customers seeking a greener, more responsible service, could ultimately lead to a financial loss. The Inventory Routing Problem examines this precise dilemma, seeking to identify the happiest possible medium between smooth business operations and minimal pollution levels.
Identifying the optimal shipment and storage conditions
The four main drivers of added value through logistics mentioned above need to be assessed through six lenses: the planning horizon (i.e. how far ahead a company plans its storage and shipments), periodicity (the milestones in a planning horizon during which decisions are made about quantities for transportation, type of vehicle, routes etc.), the number of customers involved, the items concerned by shipments, the type of vehicle(s) used, and the level of demand. However, there exists a seventh and arguably even more important lens – the ecological one. It is for this reason that “transshipment” has been proposed in theory and applied in practice as a solution to the above dilemma.
Adding in the middle man
In many business models it is highly desirable to “cut out the middle man” in order to avoid adding extra stages (and therefore costs) to a process. However, transshipment offers supply chain managers a flexible option that involves adding intermediary drop-off, storage and pick-up points to the whole procedure, as well as the option of changing vehicle type and route, according to the ecological sense that they make. This can take the form of combining small shipments into a large shipment (consolidation), or dividing the large shipment at the other end (deconsolidation), with the end result of reducing production and distribution costs. Typically transhipment would take place in transport hubs but recent research suggests it could also occur in supplier zones, where stock could be temporarily stored rather than freight vehicles having to make extra trips all the way back to the starting point at extra financial and ecological cost. The multi-point model being proposed involves extra miles being driven, but by fewer and larger vehicles, so the overall cost is ultimately lower.
More than balancing the books
This new model is not entirely cost-free, as extra storage time incurs an additional holding cost (renting a warehouse, hiring keeper, etc). However, as suppliers already have their own warehouses and the required keepers; therefore the associated holding cost for the amount of products which are stored temporarily in supplier warehouses is not very considerable based on economies of scale (1) . This temporary storage enables companies to shorten the travelling distances through eliminating some journeys. Even in the worst case scenario, the additional holding cost is equal to the saving made in transportation cost. However, invariably this is more than offset by the saving made in greenhouse gas emissions.
Extra miles to be travelled
This specific model relating to freight transport is worthy of application to other supply chain structures, as well as products providing different kinds of constraints. For example, perishable goods would exert a time pressure that would not necessarily allow for the multi-point storage method espoused here. The model also pre-supposes relatively controllable transport and storage conditions, so adding an uncertainty dimension would also be revealing and no doubt of great practical use for companies wishing to anticipate more variables within the equation, such as fluctuating holding and/or transportation costs. However, what this model clearly shows is a possible path towards simultaneous financial and ecological gains through delicate logistical handling of the supply chain from A to Z, and not just from point A to point B.
This article draws inspiration from the paper Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach, written by S.M.J. Mirzapour Al-e-hashem and Yacine Rekik and published in The International Journal of Production Economics, Mathematical Finance 157 (2014).
S.M.J. Mirzapour Al-e-hashem is an assistant professor of Logistics and Supply Chain Management at ESC Rennes School of Business, France. His research interests include Mathematical Modelling, Decision Making under Uncertainty, Green Supply Chain Management, and Logistics.
1. In microeconomics, economies of scale are the cost advantages that enterprises obtain due to size, output, or scale of operation, with cost per unit of output generally decreasing with increasing scale as fixed costs are spread out over more units of output.