Tech and media companies have a lot riding on improving the quote-to-cash process. If they can build in efficiencies, they can take someone from prospect to customer that much faster. And here’s where AI and ML come into play. If tech and media companies can find ways for AI and ML to automate, for example, 80% of the process involved in quote-to-cash, they can focus their strategic energy on the other 20%.
For Workday customer Blue Yonder, AI and ML make a huge difference in the process of customer payment matching (also known as invoice matching). In this process, invoices are cross-referenced to supporting documents to make sure that vendor payments are made correctly.
A senior accounting specialist at Blue Yonder shared this: “When you’re working through payments and invoice matching, it can take anywhere from an hour to all day to complete. With the help of machine learning, the customer payment matching capability in Workday picked up the three invoices for a payment missing remittance information. I was really impressed by that. Instead of spending time investigating and researching other payments, I was able to apply the recommendations right away.”
Anomalies. Now there’s a word that makes finance leaders shiver. Anomalies are no friend to finance. No CFO wants surprises in their processes (closing the books) or financial results (such as revenue, billing, spend, and payments). So for finance leaders in tech and media, anomaly detection with AI and ML (such as the capabilities built into Workday Financial Management) makes it possible to detect and fix costly errors before they happen. And while you’re at it, add efficiencies across the entire process.
Another word that could fall in the same category as anomalies: audits. While the IRS may come to mind for most individuals when they hear that word, for finance leaders the power of AI and ML come into play for a proactive approach, or as some may call it, always-on audits. What does this mean? The idea is simple yet potentially game-changing: Instead of only running audits on a periodic basis, using AI and ML to constantly monitor your finances makes it possible to stay abreast of what’s happening on a real-time basis. As a result, risk mitigation is much easier and process, control, and governance are being met continuously—and much more accurately than if humans had the final say.