This is the third in our blog series on solving logistics problems with data. In this post, we focus on how clean, actionable data can give you the insight you need to select the right freight carriers and get the best rates from your existing carriers. Too often, companies are saddled with laborious, outdated methods for selecting carriers that result in inefficiency and wasted money. Thankfully, there’s a better way one that takes the guesswork out of selecting your freight carriers.
Obsolete Methods for Selecting Freight Carriers Cost Time and Money
Most shippers are tasked with performing an annual or biannual request for proposal (RFP) from their freight carriers. This is a huge chore for the shipper, involving a lot of manual data gathering, data cleansing and spreadsheets. Once this laborious work is completed, the shipper sends the requests for proposal to their list of carriers typically their incumbents with a few new carriers added to the mix.
Once the proposals from the freight carriers are received, they are given the ‘eyeball test,’ comparing the RFPs to the current pricing to see if the results are favorable or not. This archaic, inexact way of evaluating RFPs means that some proposals aren’t even compared to current pricing because it is either too much work, or the proposal never passed the initial eyeball test.
Once the final decisions are made and the new pricing is published, the arduous job of setting the new rates up in the production system begins. This involves a large amount of manual work on the part of the shippers, taking a tremendous amount of time and producing results with a large margin of error. Usually, after all this time and effort, the shipper ends up with a nearly identical list of freight carriers.
Using Data and Intelligent Invoice Management to Select the Right Carriers
In contrast to the labor-intensive, inefficient methods we’ve described above, RateLinx/s PayLinx Intelligent Invoice Management (IIM), powered by our proprietary rating engine, allows you to make informed tactical decisions about your freight carriers.
With IIM, all the manual data gathering, data cleansing and spreadsheet production is removed from the process. That’s because IIM already has the data required and is integrated to the RateLinx Rate Modeling environment. Now, instead of having to put in a request to IT to gather the relevant data, it only takes a click of a button. This gives the shipper more time to focus on strategy instead of tactical data gathering, and the ability and time to add more carriers to the RFP and test more complex strategies.
The benefit of having one rating engine to maintain is it removes the manual work required at the beginning and ending of a bid, and makes the bid more accurate. At the beginning, you don’t have to set up any of your routing constraints, as they are copied into the Modeling environment from Production. During the bid, you’re able to implement new strategies (adding constraints or removing constraints) knowing that they will be adhered to in Production, since both environments are using the same rating engine.
Once the RFP is completed, the rates are copied (with a click of a button) from the Modeling environment into Production. Post-bid support is also easier because you don’t have to spend months adding a few more lanes that were missed during the bid due to incorrectly cleansed lane data. You’re also able to view analytics on the RateLinx Dashboard to monitor compliance (Lost Savings KPI), strategy (Savings KPI), and future opportunities to maximize the efficiency of your shipping lanes (Potential Savings KPI). Because every customer is different, RateLinx does custom installations for all our clients to make sure you have the information and data you need to manage your freight.
Fortune 500 Client Uses Big Data to Find Big Savings
One of our clients, a Fortune 500 company in the construction supplies industry, had been using outdated methods for evaluating and bidding their freight carriers. Due to a lack of actionable data and visibility into their supply chain, the company had been using the same freight carrier in the same shipping lane for many years. However, over time this had transitioned into an expensive lane for the carrier and our client had no way to see this. RateLinx was able help the client diagnose the issues with its carrier selection, for both less-than-truckload (LTL) and truckload freight.
For LTL, we pulled the historical shipment data and normalized it using each carrier in the bid. The RateLinx modeling engine showed which lanes each carrier should be servicing and how much money they should be receiving for it. It also showed that there were some non-incumbent carriers that were a good fit in terms of price and service that we recommended the client use.
On the Truckload side, the client used the data to understand the capacity constraints on shipping lanes caused by the fact that they were awarding too many shipments to the carrier for a certain lane. For both LTL and Truckload, the strategy was to use a few new carriers in key places while retaining their incumbent carriers in other areas where they were more efficient.
The result? Our client created a cost savings of 20% across all modes of transportation and 34% for Truckload shipments. That’s the type of impact actionable data can have on your freight carrier relations.
Don’t Wait to Start Saving
Many companies I talk to stick with their incumbents for many years and are unable to bring in new carriers for a few lanes because the work required on the shipper side to vet the rate for the small amount of freight is deemed not worth it. With the RateLinx Modeling, the computer does all the work and does it very quickly. That’s why a 34% reduction for our client’s Truckload shipping was achievable using the right carriers in the right lanes for the right price.
Don’t wait to start maximizing the efficiency and minimizing the cost of your shipping operations. I’d love to talk to you about how RateLinx can work for you, just contact us and we’ll get the conversation started.
