EXCLUSIVE Q&A: Ollie Pets scales finance operations with AI
A direct-to-consumer pet food retailer is supporting growth and streamlining financial processes using artificial intelligence technology.
Chain Store Age recently spoke with Kyle Lambert, controller, Ollie Pets, about how the direct-to-consumer pet food brand is leveraging an AI solution from Stampli to transform its finance operations, achieving results which typically require a much larger team while using a dedicated financial staff of three people.
What made Ollie Pets decide to investigate financial AI?
One issue was we kept running into limitations with our previous accounts payable provider, which we were using alongside our ERP system. Ollie Pets is a fast-growing direct-to-consumer pet food company, and we were having to split up our large vendor payments due to our previous solution having a hard cap at $999,999.
We would end up sending vendors multiple payments for what should have been one transaction, which wasn't a great look professionally.
The other big pain point was the manual purchase order matching process. Our staff accountant was spending hours every day trying to match invoices to purchase orders.
Given the nature of our business, distributing human-grade pet food to customers which is made by our co-manufacturing partners in production runs that can vary in quantity, there are always small variances to deal with. We have agreements with our vendors that an order is considered complete even if there is a variance within an agreed-upon range, typically around 5%, but our old system couldn't handle that flexibility.
Instead, we would have to manually check everything, calculate unit prices, and get additional approvals even for these expected variances. This led Ollie Pets to look into financial AI solutions.
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How did you select and implement your financial AI technology?
Financial software vendor Stampli recently provided early access to test out their new cognitive AI for PO matching solution. Instead of just looking for exact matches like most systems do, it can actually figure out when slight differences in quantities or descriptions are okay based on our business rules.
We implemented Stampli in June 2024. What really sold us was how the system could handle our specific needs around production variances. Our food vendors typically want quick payment, often on 10-day terms.
The ability to automatically approve invoices within that 5% variance window without requiring another round of approvals from our already busy ops team was a major benefit. The fact that we could do everything in one system instead of bouncing between multiple platforms was also a big win.
What have the results been?
The biggest impact has been on our month-end close. We have gone from taking about 15 days to close our books to five days. This wasn't just because of the AI implementation, we've made other improvements as well, but faster invoice processing has definitely been a significant factor.
One unexpected benefit has been the solution’s ability to handle different naming conventions. Our purchase orders use internal SKU names that don't always directly match vendor descriptions.
The Stampli solution’s AI capabilities recognize these variations and automatically correlate items even when the naming conventions differ. It can also identify price or unit discrepancies. This is particularly valuable in food production, where slight variations in order quantities are common and expected.
Looking at the day-to-day impact, we used to spend one to two hours daily just on PO matching. Now we just perform a quick verification of what the system has already matched and are not wasting time getting re-approvals for those small variances that are actually within our vendor agreements.
The efficiency gains have been so significant that we have been able to postpone hiring additional staff, even as we continue to grow very steadily, which is a huge win from both a cost and operational perspective.
Are there future AI plans you can discuss?
Ollie Pets is still pretty light on AI usage across the company. We're at an interesting point as a company, transitioning from being a scrappy startup to becoming what I'd call a medium-sized fish.
Our big focus for 2025 is maturing as a business. For the first five years, it was pretty much a free-for-all in terms of processes, but now that we're growing and have significantly more assets to protect, we need to get more sophisticated with our business processes and internal controls. AI might be part of that evolution, but we need to get our foundation solid first.
