Dirty Data and Legacy ERPs Stall Accounts Receivable Automation

The gap between ambition and execution when it comes to accounts receivable automation is one of the worst kept secrets in modern finance operations.

It is also one of its defining challenges.

“Getting from the vision to the concrete plan is difficult,” Michael Younkie, VP of Product Management at Billtrust, told PYMNTS.

The difficulty is not rooted in a lack of technology, but often in a lack of structure. Too often, organizations begin with tools rather than outcomes or pursue sweeping transformations without a grounded understanding of how AR actually functions inside their business.

To that end, many of the most effective automation journeys, Younkie said, start with restraint rather than speed.

“We like to begin with a detailed AR process assessment that identifies those bottlenecks, the manual tasks you have to perform, the exception paths,” he said, noting that those friction points become the raw material for an automation strategy that is rooted in operational reality, not abstract vision.

The goal is to identify where work slows down, where manual effort accumulates, and where exceptions quietly consume disproportionate amounts of time.

Why Phased Rollouts Beat Big-Bang Transformations

Tying automation directly to business performance, rather than viewing it as a generic efficiency play, can be a key strategy helping finance teams break free of the paralysis of operational change.

“We like to tie clear measurable KPIs to upfront things like DSO reduction, straight-through processing, digital invoice adoption,” Younkie said, adding that this helps automation shift from a technology upgrade to a financial strategy.

This emphasis on prioritization can also shape how automation is rolled out. A phased approach reduces risk, limits scope creep, and creates iterative feedback loops that keep the initiative aligned with its original intent. Rather than attempting a full-scale transformation all at once, successful organizations frequently sequence their efforts to build momentum early.

Equally important is governance.

“Cross-functional ownership early in the process allows that journey of value to be consistent,” Younkie said, underscoring that this helps reduce the risk that implementation drifts away from the original vision and that what goes live reflects what leadership originally intended.

Designing Automation That Adapts to Reality

Alignment also extends beyond timelines and workflows. One of the most underestimated risks in AR automation is integration complexity.

“We see inconsistent and incomplete data structures, bad data, dirty data,” Younkie said. “We see challenges around legacy ERP systems with limited AR API capabilities.”

These issues are not merely technical. They reflect years of incremental system additions and process workarounds that have left many organizations without a clear single source of truth. When data lives in multiple systems and teams operate in silos, automation amplifies inconsistency instead of eliminating it.

Addressing this reality requires confronting integration complexity directly rather than hoping technology will smooth it over. Billtrust’s own approach, Younkie said, is to adapt to the customer’s environment rather than forcing wholesale system overhauls.

“We conduct structured data quality assessments before configuration to make sure we truly understand that depth of your data and how it’s used,” he said, highlighting the use of automated mapping tools and rigorous testing framework designed to ensure consistent data flow across the entire order-to-cash process.

The payoff is trust. Trust in the data, trust in the workflows, and trust that automation is reinforcing rather than undermining existing operations.

Speed to Value and the Levers That Matter Most

When executed well, the impact of AR automation can be felt quickly. Cash application processes benefit from increased straight-through processing, while invoicing and collections see faster digital adoption and quicker payments.

“Customers often see measurable improvements in their system 30 to 90 days after go live,” Younkie said.

The levers that accelerate time to value are pragmatic rather than flashy: clean, standardized data, process alignment before configuration, focused role-specific training and phased deployments that target high-impact areas first.

Still, data readiness remains a point of tension for many organizations. Some expect AR automation platforms to fix underlying data issues automatically. Younkie pushed back against that assumption, while acknowledging the role automation can play.

“We work with clients who have disparate ecosystems across their ERP,” he said, noting that this often involves CRM systems and add-on modules. Billtrust, for its part, helps bring that fragmented data into a structured format, but doing so requires understanding where data lives and how it is used day to day by AR practitioners.

Preparation, not perfection, is the goal.

“We don’t see the go live as the finish line,” Younkie said. “We see this as a continued relationship. … As our clients grow, we grow with them.”

High-performing customers continue to increase digital invoice and payment adoption, improve straight-through cash application rates, and refine automated collections workflows over time. These capabilities reinforce one another, leading to reduced DSO and improved cash flow visibility.

After all, automation succeeds not when it is ambitious, but when it is intentional, and when execution is treated with the same seriousness as strategy.