With the help of system-integration, cloud platforms and AI, the management of the supply chain is heading step by step towards an increasing level of autonomy. So far, self-driving supply chains are still a vision. Nevertheless, it would allow the supply chain planner, inventory or procurement manager to focus on more value adding tasks or respective exception management. On the other hand, repetitive tasks will be handed over to systems that – once trained – will be faster and more accurate. One typical area of application being discussed, are decisions to be taken, when real-time tracking information or other sources will indicate a disruption in the supply chain. Another area will be the procurement or freight tendering processes.
Both shippers and logistics service providers (LSP) nowadays dedicate a considerable amount of time to conduct market research and elaborate quotations. Tendering can easily take up to three months for regular 3PL contracts. Considering that this often happens on an annual basis, the tender and pricing teams find themselves working on repetitive and time-consuming tasks every year. Beyond the time and effort dedicated to this exercise, it is also not necessarily providing the best result, as e.g. the pricing is often heavily influenced by seasonal effects, volumes are provided only as averages and incomplete.
Hence, the revision of the freight rates by annual tendering or rate updates only provides a questionable quality at a high effort. Today, it often requires a whole procurement team researching the market full-time for suitable providers and quotations. Thereby, they intend to achieve a valid, holistic and current market overview. Does the relation of input and output justify this immense effort?
Outlining a solution
What would you think, if the process of tendering could be mostly automated and what would be the benefits of an automation? How could this be achieved?
A first step of this approach would require access to a massive amount of consolidated freight rates of global LSPs and shippers through a harmonized data source. This way, necessary quality standards of valid, holistic and current freight rate information, required for negotiations on the global market, can be fulfilled. Having a consolidated data source gives you also the opportunity to identify price trends during a specific time frame or on a specific lane. Ergo, more complex data mining allows you to realize further cost optimization and improved forecasting along your value chain.
The second step is a review of the contracting process. Considering the time spend of a procurement department on evaluating quotations from LSPs, even with state-of-the-art tools, you need to question the benefit. What if they only had to setup a contract with an LSP every three to five years? Nowadays most contracts end after a shorter period because prices shall be renegotiated or key performance indicators (KPI) are not met. What if your freight rates are automatically adjusted in relation to the average market level, the benchmark, on an annual or even quarterly basis? It is conceivable that you pay a reasonable price and your LSP is compensated fairly as well. This would represent a win-win situation.
Both sides lay the foundation for a long-term relationship by eliminating the dispensability of contractual processes. If assumed that KPIs are met and volumes did not significantly change, there is no hurdle to close a contract for three to five years. As long-term relationships provide a higher level of planning reliability, both parties benefit: LSPs can e.g. calculate with continuity regarding volumes as well as margins and shippers profit from competitive freight rates.
How to realize this new approach?
First, it requires access to a pool of current freight rates of various LSPs and shippers. Out of this data, an average market price per lane is formed. There are rate benchmark platforms available offering exactly this kind of subscription-based data pool. Additionally, they offer tools to perform analyses to some extent. So far, there is no platform offering all transportation modes, e.g. ocean, road and airfreight, and covers respective subsets e.g. temp control or dangerous goods at the same time. Therefore, a distinct solution might be required, which combines assets from multiple platforms complemented by providing sophisticated data analysis possibilities. A rate import function into the transport management systems (TMS) provides additional value.
With a comprehensive tool in place, it is step two to implement a new contracting process. The goal, here, is to establish long-term relationships with LSPs, where this can be agreed by both parties. This way, it is conceivable to agree upon renewal periods, when the freight rate is revised or even automatically adjusted to the average market level – a freight rate renewal.
Process steps like e.g. determining KPIs and reviewing service capabilities of LSPs will not omit. See below an exemplary illustration.
Figure: Own Illustration – quarterly rate adjustments
According to this example both LSPs and shippers can be assured to be remunerated – respectively charged – fairly.
The here outlined concept of an automatic freight rate renewal is dependent upon two conditions: First, a valid data pool containing global, multi modal freight rates must be available. Second, todays common contracting approach has to be rethought. Away from an iterative tender process towards a one-time contracting event laying the foundation of common partnership for more than the usual one-year period. If both conditions are fulfilled, it gives reasons for financial benefits for both sides. Reasons are increased planning reliability as contracts prolong e.g. half a decade. Moreover, procurement efforts can be streamlined and focused. Besides, the motivation increases to align processes of common daily operations. In sum, such approach is worth looking into and to be tested.