Data driven approach to increasing payment terms with a card program

For companies looking to optimize working capital through a virtual card program, having the right data analysis is critical. By carefully mining accounts payable data, organizations can pinpoint their biggest opportunities to extend payment terms using card payments. This targeted approach maximizes the impact and value achieved from a card program implementation.

What data do you need?

The first step is gathering a complete data set of payment information across all suppliers and spend categories. At a minimum, this should include payment terms, actual payment performance, discount offers, annual spend, and payment frequency for each supplier relationship. ERP, procurement, and AP systems typically house this information, and careful compilation into a unified view is important.

Identifying where card payments can have an impact

With the data compiled, the next phase is identifying which suppliers are best suited for payment term extension via card. This is typically driven by overall annual spend level – the more spent with a supplier, the greater the working capital benefit of extending terms. Traditionally, smaller suppliers (e.g where spend less than $250,000 annually), however with the right early payment incentive structure suppliers where spend is $10,000,000+ per annum may be happy to accept card payments.

Size the opportunity

With those opportunities quantified, the next step is to model out the potential working capital impact. For payment term extensions, this is calculating the cash flow benefit of paying key suppliers 30, 60 or 90+ days later than current terms. For a $1 million annual spent with net 30 terms, paying at 60 days could unlock over $80,000 in working capital flexibility.

This should be balanced against what might have to be offered in terms of earlier payment to incentivise the supplier accept. It is often helpful to consider the minimum working capital benefit you be happy to accept and how early you’d consider paying a supplier as part of a negotiation to encourage them to take card payments. Leading card programs provide insight and analysis that supports these considerations. For example AI technology can now simulate the impact of paying invoices early and the selection of the supplier based on the acceleration needed to incentivise acceptance.

With those two levers of extended terms and early payment offers, organizations can build business cases highlighting the full working capital value, opportunities, and priorities for their card program rollout. This data-driven rationale is critical for securing buy-in, budgeting, and goal-setting across procurement, finance, treasury and leadership teams.

Using data in implementation

As the program gets operationalized, that same core data can enhance supplier outreach and prioritization. By identifying upfront which suppliers drive the highest value opportunities, targeted enrolment workflows can be built. Suppliers can be tiered and approached based on working capital impact, with customized messaging developed for each segment.

The data analysis should be an ongoing process as well, with performance monitoring and supplier portofolios continuously evaluated. New opportunities may emerge over time as supplier relationships evolve. Regularly updating the working capital models ensures organizations are always maximizing the full potential.

At the end of the day, data is a powerful asset for determining where payment term and discount capture opportunities reside. With careful data mining and objective quantification, companies can build strong business cases while developing a strategic roadmap for card program rollout and value creation. In the world of working capital optimization, leveraging data upfront is table stakes for successful virtual card initiatives.