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Dynamic Capacity Planning for Optimal Slot Selection and Vehicle Utilization

dynamic-planning-blog

Effective capacity planning is essential in the hectic world of logistics and transportation to guarantee the best possible vehicle use and slot selection. Dynamic capacity planning emerges as a critical tactic to help firms satisfy customer demands while keeping costs as low as possible.

Static models that distribute resources according to predetermined parameters are frequently used in traditional capacity planning. However, this strategy might produce less-than-ideal outcomes in the changing world of contemporary supply chains. Static capacity plans’ effectiveness can be greatly impacted by variables including shifting market conditions, unforeseen disruptions, and changeable demand.

Background

A B2C dynamic delivery ecosystem involves selecting a delivery slot from a pool of available capacity and then building the delivery routes. Traditionally, these are two distinct operations – slot selection and route/vehicle optimization. Typically, the delivery area is divided into multiple smaller geographical regions. Each region will have a pre-defined capacity in terms of total customer deliveries or service times etc. In this situation, the capacities allocated to each region are non-competing capacities. i.e. on a given day if there is more demand in region A and no demand in another region B, some of the orders from region A will not find capacity for that day whereas the capacity of region B goes unused. This problem gets multiplied exponentially as the volume of demand increases.

Flexible Approach to Match Capacity With Demand

nuVizz Dynamic Capacity Planning capability combines the slot selection and resource allocation in an intelligent way to optimize the slots and vehicle utilization. The nuVizz algorithm allows capacity definition as a global pool at the entire delivery area instead of at individual  delivery regions within the area. As demand comes in, the algorithm automatically pulls the resource from the global pool earmarking that resource for that region. The next demand may use the same resource if there is one already for that region and if not pull another resource from the global pool if the demand is for a different region for which there is no resource already allocated. The global capacity is intelligently allocated to orders from different regions utilizing the existing capacity in the most optimal way, eliminating wasted resources, and improving customer satisfaction.

The route optimization then builds the routes in the most optimal driving sequence honoring the order service promise window and honoring all the constraints.

All this can operate in a true network ecosystem. i.e. operations that have multiple terminals can leverage the platform to centrally manage the capacity planning and route planning activities reducing resource requirements at each of the terminals.  

A true network-based platform with the capabilities built to inherently support the network model provides the best possible outcome and most possible ROI.

Benefits of Dynamic Capacity Planning

  • Better scheduling options for end customers improving customer satisfaction
  • Ability to use shared vehicle pools with minimal administration
  • Flexibility to deploy delivery capacity dynamically with changing customer demand
  • Improved vehicle capacity visibility and utilization
  • Reduced dispatcher time for route planning due to balanced preallocation of capacity

Conclusion:

Static capacity planning may not be adequate in today’s dynamic corporate climate. Businesses must implement dynamic capacity planning strategies in order to remain competitive and responsive to market demands. Enterprises may enhance vehicle usage and establish a more flexible and robust supply chain by utilizing adaptive algorithms, real-time visibility, and effective slot selection.

Embrace the future of logistics with dynamic capacity planning and unlock new levels of efficiency in your operations. Stay ahead, stay dynamic!

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