When prospects talk with us about our Radar Track & Trace and Intelligent Invoice Management the discussion of our supply chain rate modeling is usually part of the conversation. By taking a customer’s data and placing it in our modeling environment we’re able to show how clean, standardized data can be used to make a strategy change and how much that strategy change could impact the bottom line. The strategy change is often very simple, involving the customer’s exact carrier mix. This accelerated supply chain intelligence combined with the related cost benefit of using our rate modeling helps the logistics manager make a clear and convincing business case for the RateLinx solution.
A Single Rating Engine Allows Real-World Supply Chain Rate Modeling
A hallmark of the RateLinx data services solution is our single rating engine. What makes it notable is the single rating engine allows modeling to be a practical, real-world exercise and not a hypothetical one. Each customer has constraints they’ve had to build into their shipping operations and those constraints prevent them from using the low-cost carrier every time. Sometimes the constraint is transit time, or it’s a customer requirement, or it’s an accessorial, or it’s the fact that they have a limited amount of dock doors. No matter which one or how many, these constraints must be accounted for to ensure that the potential savings that are being shown by the modeling are achievable by our customer. This is where our single rating engine approach excels. Because the same rating engine also powers our ShipLinx TMS solution, the modeling “understands” the routing constraints that a customer has in their TMS. This allows the modeling environment to show the true savings that can be realized, which in turn allows our customer to make the best decisions.
A Better Way to Buy Freight
Effective rate modeling is the only real way to reduce freight costs. There are logistics consultants who claim instead they can reduce total costs by negotiating the contracts better—because they say they understand all the carrier’s tricks. The reality is that there are no tricks. The carriers must make a fair profit, and if shippers use the right data, they can reduce their freight costs at the same time.
When a carrier puts their pricing in place, they consider their operating ratio (OR). An OR of 100 means that the carrier is breaking even, whereas an OR of 90 means that the carrier is making $0.10 for every dollar of revenue. If there is a “trick” it is that the carriers peg a customer to an OR under 100 to make their profit. The shipper can also win in this situation. By making sure that they have clean, standardized, and normalized data, the shipper will know the freight to give to each carrier so the carrier has an OR under 100 while also driving savings to the shipper.
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Integrated Data Leads Rate Modeling
To find the low-cost lanes that each carrier has and match them to your shipments, you must use technology that uses clean, standardized data (i.e. integrated data). Each carrier has types of shipments that they haul most efficiently. Freight type is more than, say, heavy dense freight; it also includes areas of the country and accessorials. Some carriers are incredibly efficient in the Southeast while others are great in the Midwest. Some carriers are great with lift gate while others are great with retail. Our modeling engine uncovers all of this and it shows our customers where they’ve been misusing their carriers. This intelligence allows them to rationalize their carriers to provide them with the most optimal mix of freight for the service they need. It’s a true win-win situation.
Rockwell Automation, A Real-World Example
Our rate modeling was instrumental in fine tuning a new supply chain strategy for Rockwell Automation to reduce their freight costs. Using our Intelligent Invoice Management, we captured their freight data history with all the relevant details. Rockwell also has transit time constraints that we had to consider. Then we put this into the modeling environment to see if there was a better way for Rockwell to buy their freight, which there was.
Previously, they were using a common base rate for all carriers for shipping quotes. The modeling engine showed that by using carriers’ base rates, we were able to identify each carrier’s strengths so Rockwell could be more strategic about their specific carrier selections. It was this detailed data that allowed Rockwell to make the decision to introduce new carriers for the right shipments while still obtaining the same transit time that they have historically received on those lanes. Rockwell was able to get more accurate pricing and save money and the carriers could make more money because they could haul in lanes where they are more efficient. This process provided overall benefits for the company’s transportation execution as well. With all freight, the company now has real-time access to cleaner, more precise data with accurate reports of missed savings opportunities and routing guide violations. This accelerated intelligence allows the company to make more strategic long-term decisions and work more collaboratively with its locations, suppliers and customers, which is how a company becomes a “Shipper of Choice.”