Logistics with Intuition
Do you remember the clanking of glass bottles in a van? Which, over time, went down to the convenience of PET bottles. Since, we changed our habit of consuming the cold drinks, ‘more on the move’ as against ‘sedentary dining tables’. These glass bottles also carried an additional burden of being returned to the bottling plant (at least in India), so most of the retailers stocked both empty as well as full bottles. In hindsight, these empty bottles seem to me like a hidden supply chain masterstroke for the bottling plants.
Traditionally, logistics have been 3 factor oriented viz. Distance, Time & Fuel (cost), which probably is incomplete from an optimum value utilisation of the process. For optimum utilization, we also need to consider another factor viz. Quantum of load. For example, we will continue with the cold drink logistics. A fully loaded van will embark from point zero (i.e. Warehouse), delivering till point 5 and returning back to the warehouse. Now, from pt zero to pt 1, our van is still fully loaded with content/cargo. However, at pt 1 it unloads 20 % of the load, from pt 1 to pt 2, our van is 20 % lighter vis-a-vie the cargo/contents. Which according to ‘fuel consumption vis-a-vie haulage’ dynamic is efficient.
If we continue with the same example, at point 5 this van should be at the highest point of efficiency, considering it has nil % of cargo, making the van’s return journey to the warehouse most efficient in the circuit/loop. This is mainly due to logistics being perceived from the cost saving/conservatism angle only. This is where we will reconnect to the point above(glass bottles), as to why reverse logistics by soft drink manufacturers was a supply chain master stroke. So, their vans always carried the empty glass bottles to the warehouse or bottling plant. Which always ensured optimum utilisation of the cargo bearing capacity of a van or vehicle.
As per this theory, apart from traditional cost efficiency dynamics, one should also focus on cargo’s or haulage per unit distance of travel, which can turn into an interesting mix, if synchronised with points of reverse logistics. This reverse logistics could be even in the form of waste collection to process critical components. In the long run, Cargo Per Unit Distance of Travel could potentially model the entire supply chain, giving an advanced estimate of the optimality of a particular transit loop/circuit. Based on which, a manufacturer could structure his manufacturing/assembling/passthroughs (More like ‘Just in Time’ got intuitive).
Unstructured loops/circuits of food delivery could also work out their offerings based on above theory, due to spontaneous nature of the deliveries it might get difficult to preempt with precision, but God created probability for all the events, how-so-ever random.
Remember ‘JIT with intuition’.
Warm Regards,
Prathamesh Acharekar.
