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Improve Your Accounts Receivable

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Improve Your Accounts Receivable
Challenges (8) Goals (7) 6 Steps Preview Outcomes Data FAQs (4)

Optimize Your Accounts Receivable for Faster Cash Flow

Our platform helps you uncover hidden bottlenecks and late payment patterns within your data. By analyzing your invoice lifecycle, you can identify why certain steps take longer than expected. Use these insights to streamline your operations and improve your overall cash flow.

Download our pre-configured data template and address common challenges to reach your efficiency goals. Follow our six-step improvement plan and consult the Data Template Guide to transform your operations.

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Optimize Your Accounts Receivable for Faster Cash Flow

In the modern financial landscape, maintaining a healthy cash flow is the lifeblood of any successful organization. Our process mining solution for Accounts Receivable offers an unprecedented level of visibility into your entire invoicing cycle, from the moment an invoice is generated until the final payment is cleared in your books. By leveraging the data already residing within your ERP, ProcessMind acts as a diagnostic tool that maps out every step of the journey for every Invoice Number. This allows you to move beyond static reports and see the dynamic flow of capital through your business, revealing not just what is happening, but exactly why certain processes might be slowing down your financial operations. Whether you are dealing with a single global instance or a fragmented landscape of regional platforms, our tool harmonizes your data to provide a single, truthful version of your financial reality. This transparency is the essential first step toward transforming your finance department from a cost center into a strategic value driver.

Many organizations struggle with invisible bottlenecks that inflate their Days Sales Outstanding, or DSO. These issues often manifest as manual workarounds, lengthy dispute resolution cycles, or inconsistent payment behaviors from customers that go unnoticed in traditional spreadsheets. Regardless of the specific technical setup of your source system, these challenges remain consistent across industries. Without a clear view of the process, your team might be spending valuable time chasing low priority payments or navigating complex approval chains that add unnecessary days to the collection cycle. Policy compliance also becomes a concern when manual adjustments are made to payment terms or discounts without proper oversight, leading to potential revenue leakage and audit risks. Understanding these friction points is the first step toward building a more resilient and efficient credit to cash process that protects your bottom line and ensures operational stability.

By analyzing your data with ProcessMind, you gain the ability to pinpoint the exact locations where friction occurs. You can discover the deviations from your standard operating procedures that contribute to payment delays and quantify the financial impact of every bottleneck. The platform allows you to compare different regions, customer segments, or business units to identify best practices that can be scaled across the entire organization. You will gain insights into which customers consistently pay late, which dispute types take the longest to resolve, and where automation could most effectively reduce manual effort. Beyond the numbers, process mining provides a unique window into the health of your customer relationships. Frequent disputes and long resolution times are often symptoms of underlying communication gaps or master data inaccuracies. When you can see the entire lifecycle of an Invoice Number, you can identify patterns where certain products or services consistently lead to payment friction. This allows your team to address the root causes, whether they are logistical errors or billing discrepancies, before they impact the customer experience.

Embarking on your process mining journey is a straightforward process designed to be inclusive of any technological infrastructure you currently have in place. To begin, you will need to extract key data points from your ERP, such as document dates, posting dates, clearing dates, and the associated Invoice Number for each transaction. We provide a comprehensive data template that outlines exactly which fields are required to build a robust process model. By mapping your internal data to this template, you can quickly upload your information to ProcessMind and start visualizing your Accounts Receivable process in minutes. This flexible approach ensures that your organization can achieve financial excellence and operational transparency, regardless of the complexity or age of your source systems. Our goal is to help you unlock the value hidden in your transaction logs, turning raw data into actionable intelligence that drives results and supports the long term financial health of your enterprise.

Accounts Receivable Cash Flow Process Mining Financial Optimization Collections Invoicing

Common Problems & Challenges

Identify which challenges are impacting you

Excessive days sales outstanding tie up critical capital and limit business growth opportunities. When payments are consistently late, the organization faces liquidity risks and increased borrowing costs to fund operations, which can be particularly damaging in high-interest environments. This issue often stems from a lack of visibility into which specific stages of the invoice lifecycle are causing the longest delays.

ProcessMind visualizes the entire lifecycle of an invoice to pinpoint exactly where delays occur. By analyzing the time between invoice creation and final clearing, users can identify specific customer segments or regions that contribute most to high DSO, allowing for targeted process improvements and more effective collection strategies.

Customer disputes often sit unresolved for weeks because of unclear ownership or missing documentation. These delays prevent the timely collection of funds and consume significant administrative resources across the finance department as staff spend hours searching for historical data. Unresolved disputes also damage customer relationships and can lead to uncollectible debt if not addressed quickly.

The platform tracks the duration of every dispute case from opening to resolution to help managers identify systemic bottlenecks in the review process. This visibility ensures that disputes are handled according to internal benchmarks, significantly reducing the time funds remain locked in contested invoices.

Manually matching bank statements to open invoices is a labor-intensive process that leads to errors and unallocated cash. When payments are not cleared promptly, the credit availability for customers is inaccurate, which can block new sales orders and create unnecessary friction between the sales and finance teams. This manual effort also prevents the finance team from focusing on high-value analytical tasks.

ProcessMind analyzes the activities leading to invoice clearing to determine the percentage of payments processed through automated versus manual steps. It highlights specific scenarios where manual intervention is highest, enabling targeted configuration changes to improve the hit rate of automated bank statement processing.

Issuing credit memos or adjusting invoices after they have been sent indicates underlying data quality issues or billing errors. These corrections disrupt the customer experience and require double the effort to process a single transaction, essentially duplicating the administrative cost of the billing cycle. Frequent rework also decreases the reliability of financial reporting and forecasting.

By monitoring the frequency of credit memo issuance relative to the initial billing, ProcessMind identifies the root causes of rework in the Accounts Receivable stream. This allows teams to fix upstream errors in sales orders or master data before invoices are generated, leading to a much higher first-time-right rate.

Collection teams often work without clear data on which activities lead to the fastest payments. Without insight into agent effectiveness or the impact of reminders, resources are often wasted on low-priority accounts while high-risk invoices age. This lack of data-driven strategy means that collections are reactive rather than proactive, leading to inconsistent cash flow.

ProcessMind provides a transparent view of the collection process by mapping every reminder and promise to pay against the final settlement date. This enables managers to optimize collection strategies based on proven outcomes, ensuring that agents focus their energy on the accounts and activities that yield the highest return.

Even a minor delay in sending an invoice to a customer directly impacts the payment date and extends the cash cycle. Many organizations struggle with internal processing lags between the time an invoice is created in the system and when it actually reaches the customer. If an invoice sits in a queue for days, the payment term clock has not even started, effectively granting the customer free credit.

By tracking the gap between invoice creation and dispatch activities, ProcessMind exposes hidden friction in the billing workflow. Reducing this internal lag ensures that the payment term clock starts as early as possible, accelerating overall cash inflow and ensuring that customers receive their bills while the transaction is still fresh.

Dealing with partial payments creates significant administrative overhead as invoices remain open and require manual reconciliation. This complexity often leads to aging balances that are difficult to track and resolve over time, as the remaining amounts are frequently subject to secondary disputes or confusion regarding original terms. The effort required to chase small remaining balances is often disproportionate to their value.

Using process mining, teams can identify the frequency and causes of partial payments across different customer segments. ProcessMind reveals the path these invoices take, helping to streamline the follow-up and clearing process for remaining balances by identifying patterns that lead to full settlement.

When customers fail to take advantage of early payment discounts, it often signals that the invoicing process is too slow to allow for timely payment. This missed opportunity reduces the incentive for customers to pay early, which slows down the overall cash cycle and can signal deeper inefficiencies in how customers receive and process their bills. It also results in higher effective costs for the customer.

ProcessMind correlates discount eligibility with actual payment timestamps to see where the process fails to meet discount windows. It helps Accounts Receivable teams identify if delays are due to internal approvals or external customer behavior, allowing for adjustments that encourage faster settlement.

Typical Goals

Define what success looks like

Lowering the time between invoice issuance and final settlement improves working capital and liquidity. ProcessMind analyzes the entire invoice-to-cash cycle to identify specific customer segments or process stages where delays occur, allowing for targeted interventions that accelerate cash flow.

Long dispute windows trap revenue and frustrate customers while increasing the risk of bad debt. By visualizing the lifecycle of dispute cases, ProcessMind identifies repetitive loops and hand-off delays between departments, helping teams resolve discrepancies faster and release blocked payments.

Manual matching of payments to invoices is labor intensive and prone to error. ProcessMind highlights root causes of matching failures, such as inconsistent reference data, enabling you to refine automation rules and achieve higher straight-through processing rates without human intervention.

Frequent credit memos often indicate upstream issues with billing accuracy or order fulfillment. The platform tracks the triggers for these adjustments to help you identify and fix root causes at the source, ensuring invoices are correct the first time and reducing administrative rework.

Any delay between invoice creation and dispatch extends the payment cycle unnecessarily. ProcessMind measures the lag time in your billing process to uncover technical or procedural friction, ensuring customers receive invoices immediately so the payment clock starts ticking sooner.

Customers frequently push boundaries on agreed payment terms, leading to hidden costs for the supplier. By comparing actual payment dates against contractual terms, ProcessMind detects systematic outliers and helps credit teams enforce agreements or renegotiate terms for consistent late payers.

Inconsistent handling of short payments creates confusion and complicates the customer journey. ProcessMind analyzes how partial payments deviate from standard paths to identify manual workarounds, helping you establish a consistent flow that simplifies the closing process and improves ledger accuracy.

6-Step Improvement Path for Accounts Receivable

1

Connect and Discover
2

Map Your Process
3

Identify Bottlenecks
4

Analyze Root Causes
5

Design Improvements
6

Monitor and Iterate
1

Connect and Discover

What to do

Connect your ERP to the platform by mapping invoice numbers, activity timestamps, and status changes like Invoice Created and Payment Received.

View Data Template Guide Download Template
Why it matters

Building a data-driven foundation ensures that process analysis is based on actual transaction logs rather than subjective interviews or guesses.

Expected outcome

A complete event log ready for process mining analysis.

WHAT YOU WILL GET

Gain Complete Visibility Over Your Revenue Cycle

ProcessMind uncovers every deviation and delay in your collections workflow, providing a clear roadmap to accelerate payments. You will see exactly how invoices move through your system and where friction occurs.
  • Map every step of your actual invoice lifecycle
  • Pinpoint specific causes for payment delays
  • Identify manual rework and process deviations
  • Quantify the impact of bottlenecks on cash flow
Discover your actual process flow
Discover your actual process flow
Identify bottlenecks and delays
Identify bottlenecks and delays
Analyze process variants
Analyze process variants
Design your optimized process
Design your optimized process

PROVEN OUTCOMES

Quantifiable Improvements in Accounts Receivable

By analyzing every Invoice Number across your financial systems, organizations identify hidden bottlenecks and streamline the collection cycle. These outcomes reflect the efficiency gains achieved through data-driven process optimization.

0 %
Reduced Days Sales Outstanding

Average decrease in payment lag

By identifying bottlenecks between invoice creation and clearing, organizations accelerate cash conversion and improve overall liquidity management.
0 %
Higher Auto-Matching Rates

Automated bank reconciliation

Optimizing matching logic reduces manual intervention by allowing bank statements to be reconciled against open invoices without human effort.
0 days
Quicker Dispute Resolution

Reduction in resolution cycle

Streamlining internal workflows and evidence gathering ensures that contested invoices are resolved quickly, which helps unlock stalled cash flow.
0 %
Lower Billing Error Rates

Reduction in credit memo volume

Identifying root causes of errors during initial invoice generation leads to fewer credit memos and significantly less administrative rework.
0 %
Improved Term Compliance

Better adherence to due dates

Enhanced visibility into customer behavior helps teams enforce contractual terms and identify segments that frequently miss payment due dates.
0 days
Shorter Dispatch Lead Time

Reduction in administrative delay

Moving invoices to customers faster ensures the payment clock starts sooner, which directly shortens the overall cash conversion cycle.

Individual results vary based on process complexity and data quality. These figures represent typical improvements observed across various organizational implementations.

FAQs

Frequently asked questions

Process mining extracts event data from your financial system to reconstruct the entire lifecycle of an invoice, from generation to final clearing. By using the Invoice Number as a unique identifier, it maps out every activity and status change to show how transactions actually flow through your organization.

You need to extract activity logs that include a unique case identifier, such as the Invoice Number, along with timestamps and the names of the actions performed. This typically includes events like invoice issuance, payment receipt, dispute opening, and final reconciliation, which allows the tool to build a chronological sequence of events.

Yes, the tool identifies the exact friction points that cause payment delays, such as long dispatch lead times or inefficient collection workflows. By visualizing these bottlenecks, finance teams can implement targeted improvements to accelerate cash flow and meet goals like reducing DSO by 15 percent.

While standard reports provide static snapshots of aging balances or total outstanding amounts, process mining reveals the dynamic movement between these states. It highlights non linear paths, such as repeated credit memos or complex partial payment chains, which traditional dashboards often miss.

The software tracks every disputed invoice to show where they stall, whether they are waiting for internal validation or external customer feedback. This transparency helps identify if specific departments or invoice types are causing delays, allowing for standardized resolution steps and faster clearing of contested balances.

By analyzing the specific steps where manual intervention is required, process mining identifies why certain payments fail to match automatically. It reveals patterns in manual rework that suggest where your matching rules or incoming data quality need adjustment to achieve higher touchless posting rates.

Most organizations can view their initial process maps within four to six weeks once the connection to the source system is established and data mapping is finalized. This initial phase focuses on high impact areas like the most common causes for payment delays or manual adjustments in the clearing process.

Data can be masked or pseudonymized during the extraction process to ensure that sensitive customer details are protected while the process patterns remain visible. Security protocols are typically applied to comply with internal financial audits and international data privacy regulations, keeping the focus on process efficiency.

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