A guest blog by Felipe Molino, Director of Supply Chain Engineering Solutions at NFI
The Supply Chain Digital Twin is a virtual or digital copy of your business that runs parallel to a supply chain system to identify and quantify continuous improvement initiatives. The tool, which visualizes entire networks and uses data to strategically plan and execute supply chain modifications, tests what-if scenarios to define a company’s most efficient processes and generate savings.
Creating a digital twin is one of the keys to unleashing the full power of your supply chain data. The tool’s scenario planning effectively shortens the operation feedback process and helps analyze your network to predict and mitigate service incidents before they happen. There are countless scenarios that a digital twin can support — including proactive solutions to offset market disruptions, identify continuous cost savings, and improve supply chain network efficacy.
Scenarios and outcomes are unique to each network. The interpretations below represent only a small scope of outcomes NFI’s Digital Twin solution has provided to customers, but illustrates the impact digital twin technology can create at scale.
Issue: Your company frequently leverages the spot market to provide coverage for your truckload shipments, resulting in high transportation costs. The team notices that shipments below 48 hours of lead time have led to an exponential increase in spot market usage.
Model and Interpretation: Your team wants to know what the difference in cost would be if lead times were planned ahead, without moving customer pick delivery dates. With the help of NFI’s Digital Twin, the program models the effect of increasing average order tendering lead time to 48 hours without introducing upstream or downstream expenses.
Outcome: By increasing tendering lead time to 48 hours, the digital twin predicts primary carrier compliance will increase to 97%, ultimately generating an annualized savings of more than $1.2M through a smaller percentage of shipments hitting the spot market.
Issue: Today, your company conducts demand planning for dry and reefer SKUs with different teams. Current operations do not commingle your dry and reefer shipments.
Model and Interpretation: After consultation, NFI uncovers that ~86% of your company’s dry SKUs can ship with refrigerated and frozen products without adverse effects. NFI’s digital twin sets up a model that assumes any reefer and dry orders received in your transportation management system allows commingling shipping where it is optimal.
Outcome: Implementing these changes, the digital twin anticipates that when commingling, your team can expect a savings of over $700,000 a year in shipment costs.
Issue: Your company currently ships multi-stop reefers all over the country on pre-designed, manually built routes. Some of these routes do not have consistent volume, causing potential capacity issues and delays at the warehouse. Additionally, some of these routes require 6-8 stops to fully utilize the trucks, creating expensive and longer routes.
Model and Interpretation: Your team wants to know what happens if you utilize an optimization tool to dynamically define the most economic routes, without impacting service levels. NFI’s digital twin allows your team to use the pre-existing routes as your baseline and make changes to routes only in ideal scenarios.
Outcome: By making these suggested changes the digital twin forecasts that, with optimization of specific shipping routes, your company can expect a savings of $1.5M/year.
Issue: Your company manages five North American distribution centers, one being in Southern Florida. Unexpectedly, a hurricane has been projected to hit the coast, and you need to transfer inventory to the other four locations based on forecasted demand by region.
Model and Interpretation: Using historical data, the digital twin models the expected volume by region over the next four weeks, identifies the next logical distribution center to service each region, and the excess SKU level inventory necessary to fill the demand.
Outcome: By managing all the arms of this complicated scenario with the digital twin, your company can expect a massive cost avoidance associated with the mitigation of loss of sales, inventory claims, and service levels — all without leveraging an army of analysts.
Digital twin technology is limited only by the completeness of network data and the creativity of the engineers modeling the scenarios. NFI’s Digital Twin solution enables our supply chain engineering experts to deliver better results for our customers through advanced analytics and collaborative consulting, designing creative network solutions that unleash the full power of their data.
To learn more about NFI’s Transportation Management services and Digital Twin solution, contact our team for a consultation today.
Felipe Molino is the Director of Supply Chain Solutions Engineering at NFI, a leading supply chain solutions provider in North America. With extensive experience in supply chain design, engineering, and analytics, Molino helps businesses transform their supply chains by leveraging data to find the right balance between modeled solutions and the ability to operate.