Dynamic Contracting and Predictable Markets

Future of Supply Chain Podcast, Episode 23

Dynamic Contracting and Predictable Markets

On episode 23, Santosh interviews the CEO of a Dynamo portfolio company, Leaf Logistics.

Anshu Prasad is a supply chain industry veteran; having spent the vast majority of his 22+ year career in the supply chain and logistics space. After spending two decades in the industry, Anshu and his co-founder Stefan Friederichs decided to take action on a problem that is notoriously well-known throughout the industry, and one they had intimate experience dealing with firsthand: delivery efficiency.

Anshu and Stefan noticed that most manufacturers or brands selling a product (known in the industry as “shippers”) have a process in place that would allow them to plan, schedule, and execute the transportation of their goods. This process would inevitably drive the contractual agreement the shipper would make with their logistics partner to deliver goods on time and in conjunction with the thousands of other shipments simultaneously occurring around the world. Ideally, the contracts would stipulate timing and delivery that would function in tandem with the rest of the shipper’s delivery schedule, and would facilitate an efficient drop off and pickup system to maximize the effectiveness of a transport unit.

Unfortunately, the ideal rarely happens in the logistics industry.

Rather than functioning like a well-tuned clock, shippers would find their processes out of sync or thrown off entirely by one missed deadline. Even worse, the manual nature of the planning process ensured there would be empty loads or driver downtime while waiting on a planned shipment.

Insert Leaf Logistics.

What Anshu and the team at Leaf have created is a dynamic contracting system that sets an initial plan in place between the shipper and carrier as per usual. The difference with Leaf’s solution is that their value is introduced when something goes wrong.

Rather than hoping for a miracle, Leaf creates dynamic contracts that adapt with unscheduled events or errors. Now, a shipper can flex their plan in real time to meet the needs of their supply chain, rather than sticking to a rigid schedule that ensures lost revenue.

Additionally, the Leaf’s machine learning algorithm evaluates the historic data for the shipper and identifies patterns that can be leveraged for more efficient scheduling. As result, Leaf has found that 40%-71% of shipment plans are predictable, and 46% of plannable loads can have a round-trip attached to them.

The implications of this type of efficiency are obvious.

Shippers can drive incredible efficiency while lowering their costs and increasing driver satisfaction, to boot. No longer are shippers or their carriers tied to inefficient schedules dictated by an RFP that was hatched in a boardroom. Rather, they can now adapt to the realities of the shifting shipping marketplace, and make adjustments to deliver their loads on time and on budget.

We’re obviously massive fans of what Leaf is building and excited to follow Anshu and the team’s journey as they continue to alter the future of supply chain.

You can listen to the full episode here, and learn more about what Anshu and the team are building by visiting their website.

Image Source: Quintin Gellar from Pexels


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