Continuous Improvement In Delivery Performance & Product Freshness

As long as you give me a good price, I can accept deliveries within a time window. This holds true for many companies.

To minimize cost, deliveries are planned to maximize capacity and minimize cost. As such, delivery coordinators will look at say, the number of pallets for customers and assigned the larges trucks to the customers taking the most number of pallets first. The space available is noted for small number of pallet deliveries to the same area. By considering both capacity maximization and route, these deliveries then minimizes cost. Companies usually have limited cold trucks and manpower, so cold trucks are usually assigned to the biggest customer, and/or customers that are most particular. When it is hard for one person to unload products, an assistant is usually assigned. It is also hard to accommodate to specific timing requirements unless the volume and pricing is right.

There are still usually many loose cartons for city deliveries. This is when you can cluster by capacity or location again using small trucks, as it is hard to turn using bigger trucks. In city deliveries

So how do one ensure that delivery schedules are continuously planned to minimize cost? There are 2 ways, one is to set up KPIs for delivery coordinator/driver measure their cartons/delivery cost, break down their delivery cost into fixed and variable transportation cost components. Second, collect travel, product handover times and products that are sent to these customers for continuous improvement.

One way to do this is to associate invoices/delivery orders with delivery personnel and trucks. You can use any GPS system to then collect travel and product handover times by deliver personnel and trucks. This way, any fixed and variable transportation cost can be assigned to specific trucks and even delivery personnel. Measure capacity utilization and overall route timing. Investigate exceptionally long handover times.

What is more associating invoices with delivery personnel and truck is the first step for enhanced track and trace. Invoice information are linked to product sources. Time stamp for delivery start and reach times can be measured to ensure product freshness and traceability.

City Deliveries Approach

City delivery planning is affected by truck requirements (e.g cold or open trucks), customer timing, unloading bay, customer location waiting time (to handover goods), customer location and truck capacity constraints.

A few checks on current routing and capacity of your delivery trucks should yield some opportunities:

1. Check utilization rates of the trucks. Due to historical reasons, some drivers/delivery assistants may focus on delivering to some customers. You can certainly use underutilized trucks to deliver more in one trip. Delivery reach time constraints? Use an assistant and/or do not promise a specific arrival time for customer.

2. Do same trucks go to the same location that can be served by a bigger truck, or better still, do the same trucks have ample capacity that can deliver for all locations. Delivery reach time constraint? Use an assistant and/or do not promise a specific arrival time for customer.

3. Dynamic deliveries due to not being able to control orders? Make sure that these customers are high margin customers. If not, better set cut off times for orders and processing to be done so that delivery routes can be planned to be as economically as possible.

4. Even for highly utilized trucks, are there established procedures for delivery coordinator quickly check available capacity on trucks and consolidate deliveries for days when delivery volumes reduce?


An independent approach to systematically overcome these constraints are as below:
1. Tackle truck requirements, customer timing, unloading bay size, and waiting time to handover goods first. Cluster all your customer timing delivery and unloading bay size constraint points. Use the biggest trucks possible to serve these points. Use next biggest truck of you are not able to serve the locations after factoring time to move to location and waiting time to handover goods. Base on the space available after delivering to timing stores, use space filling curve algorithm to send to the next nearest store.

2. If you cannot meet delivery times after doing #1, use smaller trucks for those delivery points with long waiting times for handover of goods to customer. These smaller trucks may allow you to go straight into carparks and deliver from there rather than from congested loading bays that contribute to long handover time for goods. Alternatively, consider using additional staff. Due to unloading bay constraints, time to handover goods may be significantly shorter with 2 staff.

3. Tackle customers with no delivery timing constraints. For rest of the stores with no timing constraints, use the biggest trucks and space filling curve to route to customers with similar loading bay constraints. Then the next sized trucks.

This approach assumes that it is marginally cheaper to serve another customer at a different delivery point using the same truck, than using the smallest truck possible to do many to and for deliveries from a distribution centre.

Of course, there are also considerations like driving another truck to take back the cold truck at a customer premises and routing from truck capacity limitations.