s costs – especially when it comes to LTL expenses.
Formulated with the help of a University of Texas at Austin professor, Natarajan (seen at right) figures that if manufactures use his new algorithm, they could slice up to 10% out of their annual distribution costs.
That might not be such a great deal for truckers, though. Again, according to Natarajan’s estimation, manufacturers spend some $150 billion dollars per year to move their gods via third-party logistics providers (3PLs) to big retailers.
Thus a 10% reduction in that expense means $15 billion flowing back into the manufacturer’s pockets – portions of which I am sure truckers might like to keep so they can fund driver pay increases and the like.
Natarajan noted in a statement that his new calculations – detailed in IIE Transactions, which is published by the Institute of Industrial Engineers – move away from relying on rates solely based on tables provided by the rating engines of transportation data companies.
“Those rate tables do not offer a good price indicator because they do not reflect the long-term collaboration between manufacturer and 3PL, the variability in quantities shipped, and/or the periodic nature of the deliveries,” he explained.
“Our math model provides a much-needed tool in the industry that considers various aspects that play into distribution costs, and offers a structured approach to negotiating customized rates with 3PLs that also offer cost-savings to manufacturers,” Natarajan added.
He emphasized that his new algorithm “re-frames” the problem of negotiating delivery fees as an optimization model that incorporates several different factors:
- The distance of each store from the distribution center;
- The probability of delivery weights to each store;
- And the total delivery cost incurred by each 3PL provider.
It then offers what he dubs a "tailored rate" solution that incorporates industry benchmarks as well as the specific dynamics of each manufacturer-3PL partnership – ensuring, in Natarajan’s words, “fair compensation” to logistics providers while “generating significant savings” in distribution costs.
“We based the model on building product manufacturers but are confident it could work for many other sectors like electronics, home improvement and clothing,” he pointed out.
Thus this is a formula with a potentially long reach when it comes to re-computing the logistics bill for shippers across a variety of industries.
Let’s just hope it doesn’t shortchange trucking companies in the end.
