We are proud to present LevelLoad, a Supply chain planning (SCP) System made in collaboration with ProvisionalAi. LevelLoad serves to eliminate deployment volatility and the associated high costs. In addition, LevelLoad uses load building optimization AutoO2 to create more prominent, legal, and efficient load building.
Deployment volatility and the associated high costs
Fluctuations in volume (volatility) have always been a part of all supply-chain networks. Hence there is volatility in filling customer orders and inventory deployment. Moreover, the replenishment movements of products from plants or suppliers to market-facing distribution centers could be more balanced. The following paragraphs outline the cost impacts and effective ways to mitigate them.
Deployment volatility generates excess cost
If only everything were calm and smooth – but it isn’t. Instead, deployment volumes on any lane (origin-destination) vary significantly daily. It generates a considerable number of bad outcomes:
• Best (preferred) carriers may be unable to handle the volume, so the peak volume may need to be shifted to higher-cost, less reliable truckers.
• Any location may become inundated with volume (or starved) as several uncoordinated ship points release loads that all arrive at once – more product than the site can handle. Equally crucial to managing lane volumes is constraining site throughput to match capacity. Loading or unloading a few extra trucks in a day may come at the expense of some overtime. Trying to load many additional shipments may drive a broader disruption and hurt customer OTIF (On Time in Full). Similarly, when many shipments over capacity are unloaded, a product needed for a customer order may still sit in the yard, and detention may incur– more pain for customer shipments.
• While the dock is a constraint on throughput, the lack of storage space can also adversely impact unloading. Often this generates significant service failures as much-needed product waits in trailers.
Supply-planning systems may exacerbate supply-chain volatility
Supply-planning systems typically react to customer needs unpredictably, creating much supply-chain volatility. For example, the volatility in the number of deployment stock transfer orders (STOs) each day is a reaction of the planning system to customer variability. Because supply-planning systems have limited capability to consider transportation costs and vehicle availability over time holistically, the supply signal tends to be problematic. Additionally, only some supply planning systems actively manage to receive or ship locations’ volume throughput. The problem is complex because receiving volume comprises shipments with varying transit times depending on shipping location and mode. In summary, most planning systems don’t manage volatility and throughput, and their reactions to customer variability may amplify volatility.
Ways to mitigate and eliminate deployment volatility
There are multiple ways to impact volatility and its related costs:
1. Reduce the amount of spot freight by tendering earlier
2. Smooth freight volumes over time by pushing lower-priority deployment demand into a later date and pulling forward more needed requirements
3. Cut the pressure on shipping and receiving sites by shifting limited capacity between lanes.
Under all circumstances, there is a need to prioritize the product needed the most.
Reduce the amount of higher-cost freight by tendering earlier
Tendering deployment loads early (as many companies do) can create problems if it ties the tendering of trucks to the definition of what is on each load. The problem is that the further in advance you determine what to replenish, the less likely it is correct. But because carriers don’t need to know what is on the load (for the most part), it’s possible to reserve trucking capacity without specifying what will go inside the trailer. The Supply chain planning (SCP) System defines the Trailer contents later. Typically, “later” allows the planning system to get more accurate information about needs.
This postponement strategy generates the following results:
• Increased lead time for the carrier because they still receive the tenders early and “first tender acceptance,” – meaning the “most favored carrier” takes the load.
• Better tailored of actual STOs, because the contents are specified as late as possible.
Smooth freight volumes over time by pushing and pulling when deployment happens
Over the next 30, 60, or even 90 days, supply-planning systems typically project when the product is needed based on target stock levels built on forecasts of customer demand along with variability factors for demand uncertainty and transit time.
If there is an effective “trading-off” of risk and reward, bringing high-priority demand earlier or pushing items with ample stocks later does little to impact service. This strategy can effectively eliminate deployment peaks well before they encounter.
Cut site volatility by shifting limited capacity between lanes
As mentioned earlier, equally crucial to managing lane volumes is managing site throughput. Generally speaking, when making deployment decisions for any day, the requirements on any lane range from the high-priority, most-needed demand to lower-priority needs. And some deployment lanes will likely require many more high-priority replenishments than others. Transportation Loading System (TLS) can use the preponderance of priority requirements to favor volume on one lane over another on any given day while setting the total site volume to within capability limits.
LevelLoad and AutoO2 eliminate volatility and high-cost freight
LevelLoad, a SaaS-based replenishment transportation scheduler, has proven effective in smoothing deployment volatility. Together with AutoO2, an optimizing load builder, they can perform the needed smoothing and postponement.
Here is how it works
When the supply planning system runs, it sends the latest requirements and other data to LevelLoad, generating a ~30-day plan for shipments constrained by site and lane/carrier capacities.
It does this by looking at the entire network of plants and distribution centers as well as: the priority of all deployment requirements; other shipments that are using site capability; the physical characteristics of the items required; numbers of loads that can realistically be accepted by preferred carriers each day.
LevelLoad uses fast-linear programming techniques combined with an ultrafast AI-enabled (reinforcement learning) load builder, AutoO2, that simulates the contents of future loads. Then LevelLoad iterates between the linear program and the load builder to identify what trucks need to schedule to move which products on which lanes.
Even for large networks, it quickly settles on a plan and creates the required signal for the TMS (Transportation Management System) to perform early tendering. It is often done at night and can be completely autonomous.
Closer to the shipment date, generally, the day before the load shipment, AutoO2 (an optimizing load builder that considers many more factors than LevelLoad) takes the latest item requirements information from the supply planning system. Then, AutoO2 determines what should ship on each vehicle for each of the tenders initiated by LevelLoad. The diagram of the whole process.
Additionally:
• Because the carrier is known in advance, loads tailor to utilize available capacity rather than build to some “least common denominator.”
• AutoO2 shows the placement of each pallet and, if needed, each case. In this way, the person loading the truck is sure that the load will be legal and arrive damage-free.
The proof are always in the pudding. We can share the results if you contact us.