Move Beyond Traditional Label Maker TMS or Surrender to Amazon’s Profit Squeeze
May 17, 2018 | By Brad Hollister
The challenge: Amazon has synchronized and integrated their supply chain to deliver products to customers when they want, how they want, and at the pricing they prefer. By controlling their own inbound and outbound deliveries (air, land and sea) and connecting all of the pieces in the digital supply chain together, the e-commerce giant is functioning as an independent and “vertically integrated” supply chain, focused both on the customer and on ironing out inefficiencies related to limitations of traditional TMS systems.
Through the use of Artificial Intelligence (AI), Amazon has made every aspect of their supply chain “smart.” Eliminating shipping errors while optimizing routing decisions based on real-time market conditions, Amazon’s supply chain design is so powerful it leaves competitors with few options: sell on Amazon, be pushed out of the market, or adopt a NextGen cloud TMS.
Moving beyond the traditional label maker TMSs commonly utilized by most e-commerce strategies is essential if companies want to succeed among evolving consumer expectations. Rate shopping, label generation, and tracking are not enough in the age of dynamic consumer control.
- Adopt technology that DOES NOT depend on static business rules. Traditional TMS builds in hundreds of static rules to account for order variations, but unfortunately the web of rules we weave always ends up tangling our customers. Food for thought: Table-based business rules fail to leverage AI, which can be quantified by examining shipment invoice data. If our routing is based on rules, then we are by default not routing based on customer needs, delivery windows, or promise dates; these self-inflicted errors are impossible to identify until it is too late (if ever).
- Require financial visibility that allows dynamic controls to impact margin, profitability, and EBIT. Inflexible and subject to human error, traditional TMS technologies lack financial segmentation. Not having the necessary clarity and control prevents costs from aligning with customer profitability.
- Ensure “live” freight audit capability is built directly inside the TMS. Most companies are unable to “own” their freight shipping like Amazon. As a result, the TMS technologies can only compare invoices to the quoted amount. This limited functionality accounting does not take into account optimized carriers, carrier rates being loaded incorrectly, or mode optimization. Three-way freight bill matching is the new standard for freight payment software, one that legacy TMS systems simply cannot accommodate.
- Eliminate costly vendor-inflicted shipping errors that result without established Vendor Scorecards. Managing vendor shipments and order fulfillment is a common problem in even the most advanced supply chain. When companies are able to hold vendors accountable for on-time order fulfillment rates, they gain the kind of control over inbound shipments that can insulate supply chains from bad service, poor fulfillment rates, and high costs.
REAL RESULTS ACHIEVED BY LEVERAGING AI TO AUTOMATE SHIPPING DECISIONS AND REDUCE COSTS
- A government supplier with more than 40 stores saved $2 million annually compared to previous pricing from a Top 5 logistics firm by dynamically routing shipments by mode and eliminating the static carrier routing guides that governed decisions for years.
- A Minnesota-based manufacturer of all-terrain vehicles and snowmobiles was overspending on freight by 40 percent in their garment division by inadequately routing shipments with the proper carrier. Leveraging AI added $12 million to their bottom line and affected earnings.
- A large manufacturer in Wisconsin gained $360,000 in additional profits by implementing a non-rules-based, live TMS in order to dynamically decide not only the best carrier option for each shipment, but also the proper shipping mode (parcel versus LTL).