While many professionals have attended at least one typing class in their lifetime, it is likely that none ever encountered freight invoice-specific direction. Yet, a stutter among fluttering fingers can drastically change the meaning of this critical billing item. While this is not always the cause for the freight invoice errors that have become so prevalent within the trade, it does beg the question, how can shippers maximize their billing accuracy? To discover this, let's consider the top ten causes for freight billing discrepancies and what could stop them in their tracks.
The last few years have seen an abundance of new, fluctuating surcharges due to rising diesel prices and a dysregulated market. This added freight accounting responsibility has complicated manual processes. Streamlining carrier invoices through AI and ML automation can simplify this added variable by learning from past instances of specific charges, fees, and waivers.
When items are popular within the retail supply chain, it is not abnormal for a shipper to send off similar orders repeatedly to the same place. This situation can easily lead to duplicate shipment invoices that can go unnoticed by employees for weeks or longer. Shippers can combat this by leveraging smart notifications to ping whenever their auditing software finds duplicate numbers in the billing process.
When shippers pull their monthly OSD report, it may reveal the need to correct fees on several invoices. Perhaps a shipment was damaged due to the lack of accessories previously discussed in the contract. Regardless of the situation, shippers must utilize anomaly detection to investigate every corrected freight invoice carefully to ensure no details get skipped.
Despite the constant weighing and reweighing of items as they move from one mode of transportation to the next, it is easy to mistype these numbers. Shippers can prevent this from happening by utilizing a central source of data truth to automate the passing of freight invoice details to and from. Automating these details precludes the potential for declined freight claims that can be the thorn on the side of every transportation and logistics provider.
When a company drafts up its payment terms, late fees are often one of the first things discussed. However, late fee charges are often forgotten or completely different from the contract, leaving room for cost-saving opportunities, if observed. When shippers feed their machine learning-enabled tech with all contract details, the software becomes aware of when late payment fees are inaccurate.
One of the fastest ways to ruin a company's rapport is for them not to pay their bills. The shipping industry is no different, even evolving into an industry that credit checks any partnership they can before doing business. Shippers can secure their freight invoice success by optimizing billing methods with AI for maximum credibility among competitors and customers.
While artificial intelligence can't do all the work, the evolved technology is beneficial within billing terms. By automating the communication process between shippers, clients, and carriers, shippers experience fewer penalties from late bills. In addition, automating the shipment invoice communication process gives back time to the workforce that they can use to build personal relationships with their network.
Because every shipment requires a unique fit, carriers often provide shippers with unique quotes. Shippers must consider that some of the most straightforward errors to avoid are expecting all rates to be the same. Deep learning skips over this basic assumption and equips shippers with intelligent software to get the ball rolling on rate variance errors.
It's essential for shippers going through freight claims management to understand how to get proper refunds due to service failure. While acknowledgment and retribution are important, refunds give shippers the cash flow they need to move on to the next shipment. When shippers leverage machine learning emails and automated reminders, the responsible parties won't forget to send them the money they deserve.
When mistakes happen, decision-makers know that the earlier they know, the better. The more notice shippers have to correct a carrier invoice, the faster that shippers can receive and respond with correct data. Machine learning anomaly detection is impeccable at observing incorrect data at any shipment step based on the smallest details.
According to McKinsey and Company, "autonomous supply chain planning can lead to an increase in revenue of up to 4 percent, a reduction in inventory of up to 20 percent, and a decrease in supply chain costs of up to 10 percent. But capturing these benefits is a journey, not a one-time transaction, and it entails thinking beyond technology to include process redesign, talent, performance management, and other aspects of operations.” If you're a shipper ready to start your journey with automation and learn how it can positively impact your freight invoice process, learn why Intelligent Audit is one of the most trusted business intelligence companies and start a conversation today.
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