How do you solve fluctuating supply problems by smoothing the flow of products?
Let’s set the stage.
Companies have developed a network of market-facing distribution centers (DCs) to meet customer demands for fast, unified delivery. For example, in the consumer products industry, this network of warehouses will be supplied by many factories and packers, each of which produces different products in different places. The lead time for production is much longer than customers’ expectations when they place and receive the order. The challenge is to have the right product in the market facing DC before the customer’s order arrives to ensure that when the order arrives, it can be shipped complete and on time. This is achieved through inventory determination by a demand planning system (also known as replenishment planning or distribution requirements planning (DRP) system).
What most people don’t realize is…
Most supply scheduling systems can incur costs and in some cases even position things to prevent the DC from being fully and timely shipped. Here’s why: supply planning systems don’t consider whether the supply chain – carriers and warehouses – can move all the products it wants to develop. They assume infinity:
- capacity with the same level of service and cost
- capacity for all facilities for shipping and receiving
- space in each facility.
All these assumptions are wrong. This leads to a growth signal that can change wildly daily and must take into account cost, storage availability and throughput capabilities. In one lane, we saw 24 trucks deploy one day and three the next. How is any transport operator supposed to provide a cost-effective service with this level of variability? And, when the 24 loads arrive at the pickup location, even assuming the shipping location can muster enough trailers and people to load them, they are faced with dilemmas:
- Many trucks are waiting to unload.
- How do we account for all the booking and overtime charges?
- Which mission should we bring first?
The consequence of keeping products on trailers is that they may be needed for immediate customer orders. The result is often a service failure.
Simple manual solutions can hurt.
A simple approach might be to set some limits on each lane. For example, limit the lane to between 5 and 10 trucks. However, this must include the overall picture. What if there are urgent customer requirements? Is it better to save a few dollars in freight while paying customer fines for poor customer service than spending extra freight dollars? Instead, there needs to be a trade-off and an understanding of the right balance of cost versus service. Also, what if there is limited shipping capacity at the origin and another lane urgently needs that limited shipping capacity? In the CPG world, where moving between locations is done with full loads, it’s important to understand what’s going on in each vehicle. Therefore, it is difficult to ascertain whether the “urgency” of the need in the “A” lane is more critical than the necessary products to be shipped in the “B” lane.
The solution must be holistic and automated.
Any solution must cover the entire network – otherwise, it’s just like squeezing the proverbial balloon: fix something in one place and it pops up somewhere else. Add to that a variety of development shipment lead times and the complexity of only shipping with a full load between facilities, which means any solution needs to be automated. And yes, with new technology, it can be done.
Because the supply planning solution proposes a significant number of requirements – in many cases, more than can be shipped in a capacity-constrained world, priority must be given to what happens with a limited number of trucks. This is not a trivial problem, so it should be automated. This automation needs to create shipments to maximize payload and ensure the most urgent product is loaded and arrives undamaged.
It makes life better.
Making optimized exchanges across the network brings several vital benefits: the most necessary shipments are prioritized, improving customer service. At the same time, as cost and capacity are considered, operating costs are minimized using a single set of trade-offs. This uniformity is another advantage of automation.
Automating the process of modifying supply planning solutions to account for real-world constraints and optimal load construction is a major win.
- Carriers benefit because they see significantly less volatility and can operate more efficiently.
- Shippers win because they can now fulfill orders more fully and at a lower cost.
- The environment wins as carriers travel fewer dead miles and load optimization creates fewer trucks, reducing carbon emissions.
About the Author
Thomas A. Moore is its founder and CEO ProvisionAI, the only provider of a patented replenishment-optimized transport scheduling solution. Tom has founded several successful supply chain software companies. Working with industry leaders such as Procter & Gamble, Unilever, Nestle and Kimberly-Clark, he has led the creation of warehousing, trucking and network optimization solutions such as Auto scheduler, AutoO2and LevelLoad. Tom also held positions in the production, warehousing and trucking line.
