Collections Automations: How Automation Helped a Lean Credit Team Keep Collections Ahead of the Industry

In construction supply, receivables are where profit is made or lost. Materials go out the door on credit, jobs stretch for months, general contractors pay on their own schedule, and one missed deadline can erase the right to collect at all. At LKL, a family-owned supplier with locations across the Intermountain West, the A/R department manages a large, complex receivables portfolio with a small team. That team keeps pace because it has steadily replaced manual, repetitive work with automated systems.

The problem with doing it by hand

Traditional collections work involves a lot of preparation before any collecting starts. Someone pulls aging reports, sorts accounts by risk, finds out who has already been contacted, checks which jobs are close to lien deadlines, and builds a call list. Credit decisions often wait on bureau reports gathered one at a time from different sources. None of that brings in cash. It only prepares someone to go get it, and in a department where every person already carries a heavy book of accounts, it pushes the calls that actually bring in cash later in the day or off the list entirely.

Automating the groundwork

LKL’s approach was to automate the preparation, so the team’s time goes to conversations with customers. Much of this was built in-house, using Excel macros and custom reporting that turn raw system data into collection work that’s ready to use. Tasks that once took hours of copying and formatting now run in minutes, and every collector starts the day with the same clean, current picture of the accounts.

Consistency matters as much as speed. When reports are built by hand, each person does it a little differently and things slip through. Automated reports apply the same rules every time, so an account that crosses a past-due threshold gets flagged whether anyone remembered to check.

Faster, better-informed credit decisions

Collections begins at the credit decision. An account opened to the wrong customer becomes a collections problem months later. LKL uses Nuvo, a credit platform that brings various credit report data and bank insights into one place. Information that used to be gathered from several sources now comes through a single workflow, and the time it takes to reach a credit decision has dropped noticeably. Sales get answers faster, customers get set up faster, and the credit team decides with more information, not less.

The results

The results show what this approach has produced. LKL’s days sales outstanding (DSO) runs well below the construction supply industry average, even though a meaningful share of sales is on extended terms, because regular-terms customers pay on time or early. That performance frees up significant working capital. Bad debt stays at a small fraction of the industry-standard range, and the large majority of receivables stay current, including the company’s biggest customer accounts.

Automation isn’t the only reason for these results. Credit policy, training for sales and customer service staff, and strong relationships with contractors all play a part. What automation does is let a small team carry a large volume of accounts without losing discipline. DSO improves as the team’s systems and training have matured.

Resilience, not just efficiency

A less obvious benefit is resilience. A department that depends on one person’s knowledge and manual processes struggles when that person is out. Automated, documented workflows let team members work independently and consistently, and they make the work easier to hand off. That matters more as LKL grows, where the same systems and policies can be applied to a new receivables portfolio.

The takeaway

Collections automation isn’t about replacing the collector. It’s about removing everything that keeps the collector from collecting. For LKL, automation has meant faster credit decisions, protected lien rights, clearer daily priorities, and results well ahead of industry benchmarks, all achieved by a team much smaller than the portfolio would suggest.