Calculating and Saving Transportation Costs With Analytics

transportation cost analyzer
transportation cost analyzer

Global events over the past few years like the COVID-19 pandemic, the war in Ukraine, rising gas prices, capacity and driver shortages have driven transportation costs to an unprecedented level. While transportation has always been characterized by high volatility, it used to be relatively easier to manage. Supply chain analytics can significantly help by consolidating and analyzing different kinds of data to set and track measurable goals and uncover outliers while saving costs and improving on-time performance and operations.

Just four years ago, typical transportation contracts were negotiated and signed with third-party logistics (3PL) providers usually for one or two years. Meanwhile, transport rates remained valid for a minimum of one year with occasional adjustments required due to currency adjustment factor (CAF), bunker adjustment factor (BAF) in sea transport, or fuel surcharge (FSC) mechanisms in road transport. Business meetings with 3PL providers were held quarterly and only to discuss their performance and review operational KPIs, not pricing and cost levels.

Things have changed drastically since then.


Factors driving up transportation costs

Four factors mainly drive the increase in the costs of road transport: capacity shortages, rising fuel prices, increasing labor costs, and growing costs of purchasing or leasing trucks and trailers.

In 2020, the availability of transportation capacity became a critical issue primarily due to the COVID-19 pandemic. Companies constantly scrambled for trucks to deliver their goods. Meanwhile, containers were waiting to roll off ships due to a lack of available allocations and congestion in the ports. These resulted in delays in deliveries and disrupted the supply chain. 3PL providers also started to increase their prices, but despite this, companies desperate to deliver their goods were only too willing to pay more.

At the same time, many factories were producing at full speed, but mostly for stock. They were concerned about border closures and restrictions on transporting goods, which could result in product shortages and considerable loss in sales. It did what many other manufacturing companies did at the time: producing as much as possible and ensuring product availability by moving goods to warehouses in countries without factories.

The manufacturers’ increased demand for transport created a domino effect on transportation costs over land, air, and sea. For example, the cost of transporting 40-feet dry cargo containers (40’ DC) from Asia to Europe ballooned by over 500% from only US$2,000 in 2019 to US$12,000 in 2022. Road transport rates, on the other hand, increased from a few to several percent depending on the type of transport/trailer, distance, and specific transport lines in different geographic regions. Meanwhile, a mega trailer costs €30,000 in 2022 from €20,000 in 2020.

The transport situation further deteriorated in 2022 due to restrictions related to the Russian-Ukrainian war. Heavy sanctions on Russia significantly reduced fuel supply in Europe, which drove up fuel prices and decreased transport capacity even more.

These massive changes in such a short period brought about the need to rethink how businesses approach service level agreements (SLAs) and replace static KPIs with dynamic monitoring. Quarterly business review meetings with 3PL vendors in the past are now insufficient. It has since become necessary to regularly monitor the changing cost factors in the transport market.

Even adding more workforce isn’t enough these days. For example, a company in the automotive industry that I worked with assigned three staff members from the purchasing department to negotiate costs with transport suppliers. It also hired two students to check the impact of fuel price increases and recalculate it based on fuel surcharge mechanisms. Even so, the team of five couldn’t monitor, adjust, calibrate, and negotiate transportation costs efficiently and quickly enough.

With rapid changes affecting the costs of transportation, businesses can no longer rely on “traditional,” manual, or tried-and-tested solutions to survive. Supply chain leaders and decision-makers must now ask themselves two important questions: if they are in control of their transportation cost, and if they’re sure that their company is not overpaying. These questions might be difficult to answer reliably without the right tools to analyze their costs in an increasingly dynamic transport landscape.

 

Case study: Optimizing spending with a transportation cost analyzer

One of the data and analytics tools we developed is a transportation cost analyzer. It is designed to monitor and manage transport costs that factor in elements that change daily. This tool intends to help businesses determine whether their transport costs are at a reasonable / acceptable level and how they can optimize them.

We tailored the tool for one of our clients, customizing it based on their business needs. We first chose a high-volume transport line that represented a significant part of their transport budget.

We then estimated the “should cost,” which determined how much the client should pay the carrier for the given transport line. We updated all the necessary parameters, including distance, trailer type, cargo weight, and cost elements (e.g., truck and trailer lease cost, insurance, fuel cost for the given distance, and assumed consumption for a given cargo weight and terrain/landscape), and finally added a 10% margin. This allowed us to have the trucking company's perspective and calculate the cost to the customer, which then enabled us to determine how much our client should pay the trucking company for our chosen lane.

Estimating the costs revealed that our client's current rate was higher than the calculated “should cost”. This gave us a great starting point to evaluate and compare costs.

Naturally, businesses can't simply depend on tools based on estimates or high-level calculations to make critical decisions. Thus, we further strengthened our estimate by benchmarking it with real-world costs and rates paid by customers to carriers, since this is the best-in-class approach based on our experience.

We compared the current cost to statistical data and reported transactions in the transport freight platform Transporeon. Here, we compared our current cost with the platform's “market lowest cost” and “market average cost” data.

Our comparison revealed that our client paid 6% more than the market average cost. Since we initially focused only on one transport route, we further confirmed our result by having the indirect purchasing department check all transportation lines in our transport cost analyzer.

The test allowed us to identify both risks and opportunities, which included:

  • Knowing where the client’s current cost is lower than market cost, which showed where they can expect their carrier to propose a rate increase.

  • Understanding where the client’s current cost is higher than market cost, enabling them to start negotiating lower rates with the carriers and achieve savings.

In addition, we calculated our goal to optimize transport costs and generate savings between 5% and 7%, depending on the region and transport lanes.

Overall, businesses will be able to enjoy tangible savings in transportation costs and adapt to rapidly changing market factors using the right data and analytics tools. Similar results can also be achieved in other business areas like inventory management, warehouse processes, and capacity optimization, and carbon footprint monitoring and reporting.

Lingaro’s supply chain analytics practice builds a suite of tools powered by advanced analytics that allow businesses to adapt to rapid changes in their industry. This includes purpose-led and data-driven reporting capabilities that help optimize the business’s flow of people, goods, services, and process across the supply chain. Lingaro’s supply chain analytics solutions also enable organizations to identify, measure, and track relevant data, KPIs, and metrics for calculating and reducing their transportation costs.

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