Late payments have caught the attention of regulators around the world, and of FinTechs exploring ways to accelerate cash flow for B2B companies struggling to make a profit when invoices are left unpaid. But even as FinTechs introduce solutions — from early payment discount programs to accounts receivable (AR) automation platforms — days sales outstanding (DSO) can continue to rise for many businesses.
Analyzing accounts receivable data locked within those platforms is critical to an organization’s cash flow management strategy — which, in turn, becomes an essential component to accelerating DSO and combatting late and unpaid invoices. But it’s a delicate process for a company to accelerate cash flow from an AR starting point, as Carlos Vega, co-founder and CEO of cash flow management company Tesorio recently told PYMNTS.
“Exchanging money or being reminded to pay can be uncomfortable,” he said. “A poor experience in collections could be damaging to a customer relationship. And poor payments behavior by customers could be an early indicator for sales or customer success. But [collections] can help build trust when handled well.”
Embracing AR automation solutions have proven effective at reducing DSO and invoice aging, he added, however even companies with more modern enterprise resource planning (ERP) systems often lack sophisticated AR technologies in-place. Further, it’s even rarer for an organization’s AR ecosystem to integrate directly with other financial processes through which cash flows, including accounts payable (AP).
The AR-Cash Flow Connection
Using accounts receivable data to accelerate the order-to-cash cycle is only part of the broader picture of cash flow management — and indeed, AR data is only part of the solution to enhanced cash flow forecasting.
The ability to analyze AR, AP and ERP data can certainly provide an accurate forecast in the short-term, added Hope Cochran, managing director at Madrona Venture Group, which recently announced a $10 million investment in Tesorio.
But if businesses want to truly elevate cash flow forecasting and look further into the future of their cash positions, they must embrace more sophisticated technologies like artificial intelligence and machine learning.
“By sitting over an ERP system and capturing payables and receivables, you get a fairly accurate [cash flow] picture on about the next two months,” Cochran said. “But if you need 12 months, you have to apply machine learning to the patterns that you see, pull out [information] from the sales pipeline in the CRM [customer resource management] system, commitments from longer-term contracts, purchase order details, bank data, your budget, etc.”
But that data is siloed and often unstructured. For instance, both Vega and Cochran pointed to information that can be useful to predict cash flow stuck in company emails, like an accounts receivable representative’s interaction with a corporate customer — information not easily quantified and categorized when businesses continue to rely on Excel spreadsheets and manual data entry to manage and forecast cash flow.
Further, even with businesses embracing AR and AP automation, a lack of integration between those platforms, and to other sources of financial information, can further stifle an accurate financial forecast.
The Financial Consequences
Accounts receivable’s connection to cash flow management is reciprocal: AR data is key to predicting cash flow, while accurate cash flow forecasting is essential to accelerating accounts receivable.
Vega pointed to opportunities for cash flow to empower AR executives to develop their collections strategy, or to prevent acting as a late-payer themselves by ensuring they remain cash-rich enough to continue making payments in the last few weeks of a quarter. Optimizing outbound payments and accelerating inbound cash flows make for a much healthier financial operation — and, as more sophisticated data analytics technologies get involved, Vega and Cochran said businesses can obtain a complete view of the financial value “of nearly every activity, from one sales team to another, across marking campaigns, across partner relationships, and different elements on the AR team.”
The consequences of lackluster cash flow management can be significant, they added.
“At a minimum,” said Vega, “not understanding cash flow can mean that you are not deploying your working capital as efficiently as possible.” That could mean paying invoices too early, or allowing payment terms with customers to extend too long.
Cochran expanded on those financial errors, noting that inaccurate cash flow forecasting can mean placing too many or too few hedges, holding onto too much cash across company bank accounts, unnecessarily pulling down too much on a letter of credit, or spending too much and incurring overdraft or other fees as a result.
“Ultimately, in a business that is still in the ‘usage of cash’ phase, miscalculating your cash-out date and having it come up on you faster than you expect is an existential risk,” she added.
Cash flow management is a strategy of data coordination: aggregating, categorizing and analyzing data across AR, AP, ERP and other platforms, all to ensure that those AR, AP and other financial processes are operating as strategically as possible. When businesses let go of the spreadsheet and embrace the opportunities B2B FinTech has introduced, said Vega and Cochran, businesses can not only forecast cash flow in the long-term, they can forecast overall growth in the long-term, too.