How to Forecast Accounts Receivable

To forecast accounts receivable, analyze historical payment patterns, calculate your Days Sales Outstanding (DSO), segment customers by their payment behavior, and use tools like aging schedules and cash flow scenarios. This process helps you anticipate cash inflows, plan expenses with confidence, and reduce the risk of liquidity problems.

Collect Historical Data

The foundation of AR forecasting is your past invoicing and collection trends. Gather at least 6–12 months of historical data to understand how quickly clients usually pay.

Key data points to collect:

• Invoice amounts (total billed per month or quarter)
• Due dates vs. actual payment dates
• Customer payment behavior (who pays on time, late, or very late)
• Write-offs (bad debts that were never collected)

Example: If you billed $50,000 in March, but only $40,000 was collected within 30 days, your AR forecast should account for a 20% delay in cash inflows.

Calculate Your Days Sales Outstanding (DSO)

DSO measures how many days, on average, it takes your clients to pay invoices. A lower DSO means faster payments and healthier cash flow.

Formula:

Example:

• AR = $100,000
• Total credit sales in the period = $400,000
• Days in period = 90
• DSO = (100,000 ÷ 400,000) × 90 = 22.5 days

If your DSO is 22.5 days, you can expect most clients to pay within about 23 days.

Segment Customers by Payment Behavior

Not all clients pay alike. Segmenting helps you forecast more accurately.

• Reliable clients: Always pay on or before due dates.
• Occasional late payers: Typically 10–15 days late.
• Chronic late payers: Frequently 30+ days late.

Example: If you bill $20,000 to reliable clients and $10,000 to chronic late payers, you can forecast $20,000 arriving within 30 days, while $10,000 might take 45–60 days.

Build an AR Aging Schedule

An aging schedule organizes outstanding invoices by how long they’ve been overdue. This provides insights into when you can expect cash inflows.

Using this, you can forecast that $25,000 will arrive soon, while only a portion of older invoices may be collected.

Factor in Seasonality and Growth

Look at past trends to identify seasonal patterns or business growth that could impact AR.

• Seasonal example: A landscaping business may issue more invoices in summer than winter.
• Growth example: A contractor signing larger projects may expect higher AR totals but longer collection cycles.

Adjust forecasts to account for these patterns instead of assuming uniform collections every month.

Apply Cash Flow Scenarios

To make your forecast actionable, create multiple scenarios:

• Best case: Most invoices paid on time (low DSO).
• Expected case: Based on historical averages.
• Worst case: Higher-than-usual delays or defaults.

Example: If you expect $100,000 in AR:

• Best case: $90,000 collected within 30 days.
• Expected case: $80,000 collected, $20,000 delayed.
• Worst case: $60,000 collected, $40,000 significantly delayed.

Use AR Forecasting Tools or Software

Manually tracking AR can be complex, especially if you manage many invoices. Accounts receivable automation does this by:

• Integrating invoices, payments, and customer data.
• Generating AR aging reports automatically.
• Predicting payment timelines using AI/ML algorithms.

This reduces errors and saves time while giving you real-time insights into your cash flow.

Review and Adjust Regularly

AR forecasting is not a one-time task—it should be updated monthly or quarterly to reflect current realities.

• Compare forecast vs. actuals each cycle.
• Adjust for customer changes (e.g., new clients, lost contracts, payment policy changes).
• Refine assumptions about late payments or defaults.

Consistent review ensures your forecasts remain accurate and useful.