When accounts payable departments run smoothly and efficiently, invoices are paid on time, and organizations gain a reputation among suppliers and partners for prompt payments. Therefore, one key element to optimizing the AP department for efficiency and cost is understanding the correct accounts payable (AP) metrics.
Learn more about how enterprises can efficiently manage AP process workflows with AI and automation. Efficient management of accounts payable process is important for a business’s operations to expand.
Why is measuring accounts payable (AP) metrics important for businesses?
Tracking Accounts Payable (AP) metrics is advantageous in many ways, but the ultimate goal is to measure and examine results for improvement. A company with high AP ratings is posed to be more successful than its peers. It is challenging to identify AP areas requiring change without regularly tracking, measuring, and analyzing the correct metrics. By monitoring the relevant accounts payable metrics, companies can quickly identify ways to make their AP process more effective and cheaper. This also helps improve financial reporting since the data from AP can be used for budgeting, supply chain planning, and other financial analysis.
Measuring the performance of an accounts payable process is the first successful step involved towards building a zero-touch invoice processing process powered by AI and automation. Learn more about the most relevant metrics for the Account Payable process.
AP Metric 1: Average processing cost per invoice
Average processing cost per invoice is the most critical AP metric to track. AP leaders can directly determine the impact of inefficiencies on their budget by monitoring the overall cost of processing each invoice. Of course, some invoices cost more to process than others: those with exceptions and non-PO invoices may be costing more than clean ones. To calculate the average processing cost for each invoice, you divide the total number of invoices for a specific period by the expenses incurred to pay them. The resulting figure is your AP cost per invoice.
Learn about the five most important roles played by Artificial Intelligence (AI) technology that enterprises should be aware of before considering automating invoice processing. It completely changes the AP dimensions for a business and helps in reducing invoice processing costs.
AP Metric 2: Average payment processing time
The average processing time for an invoice is a key AP Metric that can help you understand where your accounts payable staff is spending the most time - manual data entry, collaborating with a team, or strategic activities? The invoice processing workflow is the same in all companies, with minor differences depending on the parties involved. The longer the average processing time, the more likely AP staff is engaged in labor-intensive, low-value tasks rather than focusing on high-value activities.
AP Metric 3: Invoices processed per FTE
The number of invoices processed by each AP staff member is a measure of productivity. This helps process administrators with a granular view of the reasons behind delays. This critical KPI may differ and is purely based on the company and which industry it runs its operations.
Learn from Karan Yaramada (CEO and Founder – Kanverse.ai) about How Enterprises can Leverage AI to Make Document Processing Touchless and enhance the performance dimensions of their AP processes.
AP Metric 4: Percentage of exceptions vs. total invoices processed
Exceptions are the errors found in invoices as they are processed. Some common types of exceptions are invoice data is entered incorrectly, data lost as paper invoices are digitized, data does not match the corresponding purchase order, etc. AP teams must frequently deal with these exceptions and the impact of such erroneous processing in terms of costs incurred, delays, and other effects. Tracking the percentage of exceptions vs. the total number of invoices processed lets AP managers monitor how much time your AP staff is productive instead of fixing mistakes and processing errors.
AP Metric 5: Number of discrepancies & disputes from suppliers & vendors
Disparities can happen after invoice payments are processed, leading to vendor disputes – such disparities lead to poor rating of the effectiveness of the AP process. Measuring the number of conflicts from vendors can help detect opportunities for validating invoice accuracy. If invoices are incorrectly matched PO (Purchase Order) or recorded poorly, this can eventually impact vendor relationships and harm the supply chain.
AP Metric 6: ROI (Return on Investments) on invoice automation
Digitization and optimization offer CEOs real-time visibility and transparency to drive strategic decision-making, efficiency, and growth. Investing in invoice automation will yield a significant uplift across all your AP KPIs. If your team is having trouble providing the numerical justification for the business case, try using an ROI Calculator, which will help you determine the potential savings and convince your CEO of automation's value. After incorporating automated invoice processing, compare the data with your pre-automation data to view the impact of automation on your accounts payable process.
Request a demo to experience how Kanverse Hyperautomation platform combines multiple AI technologies (Computer vision, ML (Machine Learning)NLP (Natural Language Processing), fuzzy logic) with OCR (Optical Character Recognition) that delivers astronomical data extraction accuracy from invoices – which helps the organization achieve the desired ROI faster than other players.
AP Metric 7: Percentage of straight-through processing
Effectively handling invoice processing exceptions require manual efforts for rectification before the invoices are to be sent for approval. This process break leads to increased operational costs and late payments and hampers vendor relationships - making it one of the most significant sources of operational challenges between the AP team and Procurement. By monitoring how many invoices could be matched with POs (Purchase Order)immediately and paid without any manual intervention, companies can better fine-tune processes and manage by exception.
In addition, tracking straight-through processing helps you understand how many “successful” invoices you have each month.
Improving Accounts Payable (AP) process by tracking the metrices
Automating error-prone parts of the Account Payable process makes collecting the data a lot easier. AP solutions can automatically extract the data from invoices and populate it in the accounts payable systems and downstream applications. Workflows and SOPS in the software ensure the right people see the expense, verify its legitimacy, and approve it. Reducing the number of manual activities required to input invoice data and accomplish the approvals process saves time and increases accuracy. In addition, when you automate your Accounts Payables process, you have the ability to capture and monitor AP metrics more closely while using your metrics to influence change within your overall organization. As a result, you can significantly reduce errors, decrease vendor queries through AP Automation, and actively review your AP metrics.
Learn more about Zero-touch invoice processing with UiPath and Kanverse.
About Kanverse.ai
Kanverse brings you the best optical character recognition software to automate Accounts Payable (AP) Invoice processing for enterprises right from ingestion, classification, extraction, validation to filing. Extract data from a wide gamut of documents with up to 99.5% accuracy using its multi-stage AI engine. Say goodbye to manual entry, reduce cycle time to seconds, optimize cost by up to 80%, minimize human error, and turbocharge productivity of your team.
AP automation software like Kanverse APIA (AP Invoice Automation) is built to do the heavy lifting across your AP cost centers while your staff can focus on productive and business-critical activities.
Kanverse can also automate insurance submission workflows and seamlessly process ACORD and supplemental forms. Schedule a demo with us today to find out more.
About the Author
Kingshuk Ghosh, Product Management, Kanverse.ai