Determining profitable customers
Many industries deliver goods to customers without a clear picture of the variable transport costs attributable to each customer.
With the transportation component often representing 25%-40% of the cost of goods sold, integrating an accurate measurement of gross profit after distribution is an essential part of supply chain and distribution management.
Maximising delivery profitability
We developed a new ‘cost-to-serve’ analysis that accurately models complex distribution networks to determine the profitability of individual customers and maximise gross profit after distribution.
Left hand side shows different types of trucks being selected for different delivery routes for Integrated optimisation of the line haul and last kilometre of distribution for Tip Top Bakeries. Right hand side shows the distribution map of the routes the trucks will take.
Cost To Serve models revenues and fixed and variable costs to determine the incremental variable distribution costs and other vital information such as the most profitable direct-delivery customers, the optimal mix of customers, the optimal fleet configuration and street-level routes, while taking into account variations in price, delivery frequency, time-windows, service duration, and customer base selection.
With Cost To Serve, businesses are able make the most efficient use of their existing assets to deliver their goods with fewer journeys.
Tip Top makes big savings
Tip Top bakeries is one of Australia’s largest suppliers of bread, with the company delivering more than one million loaves of bread to 20,000 stores each year.
Points on a map of sources of revenue (left) and the related optimised service routes (right).
With their transportation costs topping more than $100 million each year, they turned to Cost To Serve to tackle the extreme logistical challenges of delivering their product from more than 100 distribution centres across the country.
Using Cost To Serve we developed an improved asset and resources plan focusing on aspects such as ‘more-than-truck-load’, optimal fleet configuration and cross-docking to help Tip Top reduce their operational costs by 10.4%.
As well as reducing their operational costs, Tip Top was able to reduce road congestion and emissions by using fewer journeys to deliver the same amount of goods.