This article is an excerpt from the report: Part Three: Analytics for Improving Carrier Performance and Leveraging Trade Data
A copy of the full report can be downloaded here.
This is the third in a three-part series on using analytics in transportation and logistics to achieve a competitive advantage:
- Part One: The Democratization of Analytics for Transportation and Logistics — In Part One, we explore the kinds of data being produced by transportation and logistics systems, how that can be used to create a data-driven enterprise, the substantial obstacles to achieving an analytic advantage, and how those obstacles can be overcome.
- Part Two: Analytics for Private Fleet and Driver Performance — In Part Two, we look at how analytics uses real-time location data, combined with orders, plans, proof-of-delivery, vehicle data, and more to drive significant improvements to fleet and driver performance.
- Part Three: Analytics for Improving Carrier Performance and Leveraging Trade Data — Here in the third and final part, we discuss how analytics can create improvements to carrier performance while substantially reducing costs, as well as how trade data can help importers and exporters gain competitive insights, manage supply chain risk, optimize total landed costs, and more.
Analytics for Improving Carrier and Supplier Performance
Carrier scorecards are largely derived from transportation-related data and can be used to measure and improve on-time pickup/delivery, detention/congestion, lower falloffs (cancellations), damage rates, billing accuracy, and more. Some elements of supplier performance can also be derived from transportation data (e.g. on-time delivery, routing guide compliance).
Companies using for-hire transportation services depend on their transportation carriers to deliver on time and provide a good customer experience. The carriers’ drivers become the shipper’s ‘face to the customer’ at the point of delivery, so shippers have a strong interest in measuring and improving carrier performance and controlling costs. Many types of data can be brought together to measure and improve carrier performance, including:
- TMS data (contracts, forecasts and capacity bookings, load tenders and responses, etc.)
- Carrier-provided data (shipment status, truck location, pick-up and arrival events, manifests, invoices, etc.)
- Data from non-TMS internal systems such as ERP, CRM, WMS, and purchasing systems (orders, customer data, payments, receiving records, etc.)
- External data (freight indexes for rates, volumes, expenditures; CSA ratings, fuel prices, etc.).
Carrier and supplier performance analytics can be divided into three main buckets: 1) Carrier Performance, 2) Shipper’s Self-Scorecard, and 3) Supplier Scorecard.
Carrier scorecards are commonly used to track key performance indicators, which can then be used in decision-making about which carriers to use, as well as discussions with carriers about improving their performance. Analytics enables not only collection and reporting of these metrics but doing analysis to gain insights. This can help uncover the reasons behind poor performance and accelerate fixing the problems. Here we discuss some of the areas that analytics can help with, including transportation cost reduction, carrier delivery performance, reliability and responsiveness, and information sharing.
Analytics can help with cost reduction in at least three main ways: 1) transportation strategy, 2) carrier negotiations, 3) freight audit. Taken together, these can reduce freight costs by 15%-25%. Regarding transportation strategy, analysis can help with carrier rationalization — figuring out who are the right carriers, and the right number of carriers. Using the right number of carriers can help to optimize volume discounts and build strategic relationships, while ensuring enough choice to retain the needed flexibility and resilience. Analytic tools, with the right data, can identify carriers who are based near your frequent ship-to locations, thereby turning your loads into backhaul opportunities for them. Analytics can also help discover untapped opportunities for consolidating shipments, intermodal shipments, shipping on off-peak days or night pick-up (the latter gives carriers an opportunity to turn your load into a backhaul), and optimizing shipment sizes.
Analytics enable data-driven carrier negotiations. For existing carriers, you will have granular data on their performance and your own firm’s behavior. Market intelligence (current and forecasted spot rates, freight demand/market expansion or contraction, fuel prices, benchmarks, etc.) can also be an important part of the discussion. Regular feedback should be provided to carriers about their performance. However, contract negotiation is a point in time when you are more likely to have leverage and the full attention of the carrier for a heart-to-heart discussion on opportunities for improving performance and lowering costs. Analytics can bring many details and angles of carrier performance into those conversations — not just the KPIs, but insights into causes and possible remediation. Some of these are discussed further in the sections below on reliability and responsiveness, delivery performance, information sharing, and driver/vehicle.
Regarding bringing your own firm’s behavior into carrier negotiations, if you always pay promptly and/or have much quicker than average turnaround times for trucks coming to your facilities — and you can back up your assertions with data — that should be worth something to the carrier and should help your negotiating stance.
Analytics can also help with the challenging task of freight audit. Typical estimates are that firms can usually recover 2% – 5% of their freight spend by doing a proper audit. Analytics can help with the task of uncovering incorrect rates, duplicate payments, payments to the wrong carrier, incorrect currency, incorrect accessorial charges,1 and other issues. Accessorials can be particularly challenging to research and audit manually. Analytics can be used to semi-automate the process, not only to find incorrect charges, but also to discover what behaviors or decisions your own company could change in order to avoid or reduce these charges.
Delivery performance is central for measuring carriers. Typical KPIs measure on-time pickup, on-time delivery, and exception-/claims-free delivery. It is critical to know as early as possible when on-time delivery is slipping, as it directly impacts customer satisfaction. Analytics can help highlight the problems and diagnose them. If problems are showing up for just one carrier, in just one region, it may be a problem with their regional hub. If you are seeing slowdowns across the board, with all carriers and regions, then it might point to an industry-wide capacity crunch. Analysis can also help identify which carriers are above and below average for different lanes or ports, enabling you to choose the best carrier for each lane.
Reliability and Responsiveness
Strong on-time delivery performance by a carrier is not nearly so useful if their tender acceptance rates are low or falloff rates (cancellations) are high. This includes the availability of the right kind of equipment (e.g. a reefer with a liftgate) when needed. The same applies to rate/bid adherence. After spending all that time negotiating a good rate and committing to volumes with a carrier, you would like to actually get what you bargained for. Having data on tender acceptance, falloff, and rate adherence can drive discussions with a carrier to mutually figure out what the problem is, how to solve it, and get back on track.
Other dimensions of responsiveness to track include claims settlement timeliness (e.g. % claims settled within 30 days) and customer service responsiveness (average response time, duration to complete requests). The carriers’ vehicle inspection and maintenance practices, as well as their CSA2 score, may be taken into consideration, to reduce the chances of an equipment breakdown or accident with a truck carrying one of your shipments.
Carriers should be measured on how well they are sharing information with you. Data from your carriers are used for many purposes, such as tracking whether your shipments are on time or whether you are paying the correct amount. Data from your carriers also feeds many of the analytics we are discussing here. One of the most important types of desired data is on the shipment status, including both the timely logging of events and milestone, and near-real-time GPS tracking/location data. The latter can be invaluable to alert your own facilities and your customers when orders are running late, or when they are imminently arriving so they can ready the necessary resources (e.g. dock door or parking space, unloading crew, etc.).
Electronic PoD (Proof of Delivery) data is critical for reducing disputes as well as more timely and accurate invoicing of your customers. EDI messages3 to/from the carrier can be invaluable in digitizing and automating your businesses. Tracking the accuracy of invoices from carriers can help reduce incorrect billing in the first place, rather than having to discover them later with audits.
In Part 3B, the final installment of this series, we examine how analytics can be used by a shipper to improve their own performance, as well as creative uses for trade data.
1 Accessorial charges may include fuel surcharges, redelivery, layover, reclassification, driver load/unload, sort/seg, after-hour delivery, truck ordered not used, diversion miles, storage, detention, pallet fees, and many other types of charges. — Return to article text above
2 CSA = Compliance, Safety, and Accountability, a safety compliance and enforcement program run by the Federal Motor Carrier Safety Administration (FMCSA), to hold carriers and their drivers accountable for their road safety. — Return to article text above
3 For example, EDI 214 transactions can be used to update status upon pickup and drop-off, and can include PO information, proof-of-delivery, BoL, and other status details. — Return to article text above
To view other articles from this issue of the brief, click here.