{"id":177,"date":"2021-01-07T04:59:40","date_gmt":"2021-01-07T04:59:40","guid":{"rendered":"https:\/\/www.emagia.com\/blog\/?p=177"},"modified":"2025-01-28T22:40:41","modified_gmt":"2025-01-29T04:40:41","slug":"5-key-accounts-receivable-metrics-and-kpis","status":"publish","type":"post","link":"https:\/\/www.emagia.com\/blog\/5-key-accounts-receivable-metrics-and-kpis\/","title":{"rendered":"5 Key Accounts Receivable (AR) Metrics and KPIs You Should Track","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Tracking the performance of accounts receivable enables organizations to figure out what is working and what is not. Monitoring your accounts receivable (ar) performance metrics<\/strong> can be the key that that unlocks the doors to improved business performance. <\/em><\/p>\n

\u201cYou can\u2019t manage what you don\u2019t measure\u201d is a widely-accepted rule for managing any operation or process. Makes sense, but the question remains, which and how many individual metrics should be measured to monitor the health of the Accounts Receivable<\/a> (AR) asset and operations? There are many useful accounts receivable performance metrics<\/strong> and KPIs for gauging the health of the asset. The task of reducing them to just five is not easy, but here they are: Use these for your organization\u2019s accounts receivable performance review.<\/p>\n

\"best<\/p>\n

1. Credit Metrics<\/strong><\/h2>\n

Average Days to Complete a New Credit Review<\/strong><\/p>\n

This accounts receivable metric<\/strong> is the elapsed time from receipt of a credit application<\/a> to the assignment of a credit limit. Given the critical need for additional revenue experienced by most companies in the pandemic economy, this accounts receivable<\/a> KPI is judged to be more important now than a risk rating of the AR portfolio.<\/p>\n

Hackett\u2019s World Class performance benchmark is two days. Achieving this performance level requires an on-line credit application with digital signature and automatic<\/strong><\/a> integration with credit<\/a> bureaus, banks, etc.<\/p>\n

2. Collections Metrics<\/strong><\/h2>\n

Average Days Delinquent<\/strong><\/p>\n

This AR performance metric<\/strong> measures the gap between actual Days Sales Outstanding (DSO) and the best possible DSO<\/a>, thereby eliminating the impact of granting extended payment terms.<\/p>\n

To achieve Hackett\u2019s World Class performance<\/a> benchmark of four days, automated, customized collection prioritization logic which drives collector activity and automation of contacts is required.<\/p>\n

3. Cash Application Metrics<\/strong><\/h2>\n

Auto-Cash Hit Rate<\/strong><\/p>\n

This cash application performance metric<\/strong> measures the percentage of customer payments automatically applied to open invoices without any manual involvement. To achieve Hackett\u2019s World Class performance benchmark of 75%, AI driven, automated extraction of remit data from multiple sources in multiple formats and application to open invoices, enhanced by machine learning, is a must.<\/p>\n

4. Deductions Metrics<\/strong><\/h2>\n

Average Resolution Cycle Time<\/strong><\/p>\n

This accounts receivable performance metric<\/strong> measures the elapsed time from when a deduction is created in cash application<\/a> to when it is cleared from the AR ledger or assigned for collection<\/a>. A short cycle time indicates high productivity and enhances the probability of collecting invalid deductions. Hackett\u2019s World Class performance benchmark is seven days. Achieving this requires AI driven, automated, deduction creation and assignment of reason code, via extracting data from customer vendor portals and remit information from multiple sources in multiple formats.<\/p>\n

5. Credit to Cash<\/strong><\/h2>\n

Cost of the Credit to Cash Processes as a % of Revenue<\/strong><\/p>\n

This accounts receivable KPI<\/strong> is a cold, simple measure of efficiency. Hackett\u2019s World Class performance benchmark is 0.04%. While best practice processes are important, efficiency of this level requires AI-driven accounts receivable automation that reduces 70 \u2013 80% of manual and semi-manual work in these five functions.<\/p>\n

Apart from these key accounts receivable metrics<\/strong>, there are two pitfalls that one needs to avoid when measuring the health of the AR processes and operations:<\/p>\n