Quantifying vendor relationships for optimized payment decisions

Sherry: Hello, and welcome to all our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I'm very excited to have Leon Deckter here with me, who is an experienced operations and finance leader, with a track record of driving growth, optimizing processes, and leading successful exits and mergers. Thank you so much for being here with us, Leon. Today we'll be talking about quantifying vendor relationships and criticality for optimized payment decisions. To get us started, Leon, how do you define vendor relationship criticality? Why is it important to make payment timing decisions?

Leon Degtar: Sure. Thanks, Sherry. I take a look at vendor relationships in a few different ways. There are quantitative and qualitative aspects to determining that relationship. To quantify, you can look at things like transaction volume, historical relationships, longevity, and criticality to the business. How much does it drive operations, and how critical is that vendor? Beyond that, there are also relationship dynamics that may exist—external qualitative relationships that are meaningful between that vendor and the company working with them. All of those factors help determine vendor priorities.

Sherry: And what factors do you consider when quantifying vendor relationships?

Leon Degtar: Factors are really about criticality to the business. What is that vendor providing? If that vendor were to go on pause, would it have a meaningful impact on business operations? Then there’s the relationship itself—are there additional factors at play? Is that vendor potentially a business driver beyond the direct service they provide? Ultimately, you have to ask: In times of cash crunch, is this a vendor that can be turned off, or is it a must-have service or product? Those are the key considerations.

Sherry: And these factors that you talked about—how do you integrate them into a vendor relationship score using AI?

Leon Degtar: When you can pull all that data into a system and not have to manually map it, you don’t have to wait until there’s an urgent need to evaluate vendor relationships. Traditionally, you’d have to manually gather data in Excel or from different sources. With AI, this process is always on and tracked in real time. When we’ve worked with Hyperbots, for example, we could see vendor relationships dynamically, weighing risks and making determinations regarding payment terms, payment timing, and vendor criticality. Some of these insights might otherwise be overlooked in daily operations, but having them at your fingertips in real-time adds immense value.

Sherry: And how does this vendor relationship score influence your decision on payment timing?

Leon Degtar: It’s a critical factor in payment timing. Especially during cash crunch situations, making informed payment decisions is essential. You don’t want to put the business at risk or damage vendor relationships. Having this information allows you to gauge where you have flexibility and where you don’t. It saves time because you’re making executive decisions based on real-time data rather than crunching numbers manually.

Sherry: And to help us visualize all of this better, can you provide an example of how vendor relationship metrics have influenced payment decisions?

Leon Degtar: Absolutely. Vendor relationship metrics can help determine when to pay vendors based on discount terms or when to negotiate extended terms. This can reduce reliance on external financing and improve cash flow management. For instance, we’ve used these metrics to take advantage of early payment discounts when cash flow allows. Conversely, in tighter situations, we’ve proactively adjusted payment schedules without jeopardizing key vendor relationships. The key is having foresight—you don’t want to push delays too far and risk damaging partnerships, but with clear data, you can make informed adjustments.

Sherry: And what data sources are essential for modeling vendor relationships in your AI system?

Leon Degtar: The core data sources always include accounting and finance platforms. Many companies use tools like Ramp or Bill.com for vendor management. Additionally, vendor data might be stored in external portals, internal procurement systems, or intranets. As long as the data can be pulled together and normalized, AI can work across multiple sources. That’s what’s great about tools like Hyperbots—they can integrate existing vendor relationship data, providing a unified view.

Sherry: Thank you so much for being with us today, Leon. It’s always such an insightful conversation when you’re around.

Leon Degtar: Thank you so much, Sherry. Appreciate it.