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September 30, 2025
Revenue Recognition Methods: ASC 606 vs IFRS 15 Guide
Woosung Chun
CFO, DualEntry
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Revenue recognition rules might look technical, but they shape how a business is judged. Investors use them to track performance, auditors test them line by line, and CFOs know the method chosen can decide whether a close runs smooth or drags into weeks of cleanup.
Under ASC 606 (U.S) and IFRS 15 (global), companies follow a common framework: show revenue when it’s earned, not when cash arrives. Simple in theory, harder in practice. Product sales, multi-year SaaS contracts, and usage billing all follow different paths – and timing changes the story your numbers tell.
Older methods like completed-contract still surface in some industries, but most teams now operate under the five-step model. The rules set the baseline, but the real test is execution, especially across geographies, currencies, or bundled services. Here, automation helps to cut through manual risk and give leadership numbers they can trust.
What Do We Mean By ‘Revenue Recognition Methods’?
In the past, GAAP let industries pick methods that fit their contracts but not each other. Retailers booked sales when goods moved, construction businesses used percentage of completion, and other business models waited for finished projects under the completed contract method. High-risk sales followed cash through installment or cost recovery.
These approaches made investor comparisons messy – for example, a construction firm and a software vendor could book similar deals in completely different ways. ASC 606 (U.S. GAAP) and IFRS 15 (international) replaced this confusion with one principle-based framework.
Today, the question isn’t which method to choose from a menu. It’s whether obligations are satisfied at a point in time or over time. When it’s over time, finance teams decide how to measure progress: output (milestones, units delivered) or input (costs, hours worked). The method has to mirror the economics of the deal, not convenience.
For SaaS, input measures often track costs tied to servers or platforms. Construction projects lean toward output tied to delivery. The standard doesn’t dictate the choice, but it requires consistency and rationale.
Point-in-time vs over-time recognition
Under ASC 606 and IFRS 15, the core question is control: when does the customer actually gain use of what they purchased? That timing sets the recognition pattern.
Some sales finish in a single moment. A retail purchase is the obvious case: once the goods leave the store, the seller’s obligation is done, and revenue belongs in that accounting period.
Other contracts stretch across months or years. SaaS subscriptions, long-term service deals, or construction projects deliver value gradually, so revenue is recognized in that same rhythm. Progress can be tracked by outputs such as milestones reached or units delivered, or by inputs like costs incurred or hours worked. A variant of the input approach is the proportional performance method, which spreads recognition evenly as services are provided – for example, a consulting retainer billed monthly.
The important part is showing that the choice fits the contract’s economics. Auditors will expect consistency across similar deals and a clear explanation of how progress was measured.
Measuring progress for over-time recognition
When revenue is recognized over time, the challenge is deciding how to track progress. ASC 606 and IFRS 15 permit two main approaches: output methods and input methods.
Output methods tie recognition to results delivered – milestones completed, units handed over, or a percentage of a project finished. They give clarity because progress is visible and tied directly to deliverables, but they’re not a fit for every case. A SaaS platform, for example, can’t measure value by units delivered when access is continuous.
Input methods use effort as a stand-in for performance – usually costs incurred, hours worked, or time elapsed. SaaS companies often spread subscription revenue evenly over the contract term, while construction firms may tie recognition to actual costs versus total estimated costs. Input methods are simpler to apply, but they assume effort equals value, which isn’t always true.
The key is alignment. If milestones or deliverables reflect progress, output makes sense. If effort is the better proxy, input works. The standards require consistency and documentation of the chosen method. Miss that, and revenue may be misstated, inviting questions from auditors and investors.
Common revenue recognition methods
Sales-basis method
Here, revenue is booked when a sale closes (delivery or completion). This is still common in retail, ecommerce, and tax reporting.
Percentage of completion method
Revenue is spread as work progresses, tied to costs or milestones. This is standard for construction and long projects, and is now treated as “over-time recognition.”
Completed contract method
This means no revenue until the project ends. It’s a conservative approach, sometimes used for short jobs or tax.
Installment method
Here, revenue follows cash collections. This method’s common in real estate or big-ticket sales with credit risk.
Cost recovery method
This is even stricter, and probably the most conservative approach to revenue recognition: no revenue until costs are recovered. It’s still referenced in high-risk contracts and tax codes.
Milestone-based method
Often used in biotech, pharma, and government contracting, here revenue is booked when a contract milestone is hit. Today, these factors map to performance obligations, but the language persists.
Why these methods still matter
Old habits and tax rules keep these methods alive, even in the post-ASC 606 and IFRS 15 era. Finance teams must bridge the old terms with compliance with accounting standards and clear communication.
Industry applications of revenue recognition methods
How revenue gets booked depends heavily on the industry, even though ASC 606 and IFRS 15 apply everywhere. The framework is the same, but contracts and customer expectations change the application.
Construction and engineering
These projects run for years and recognition follows the work. Progress can be measured by costs incurred or by milestones. That avoids the problem of showing no revenue for months while crews are pouring concrete or wiring a facility.
SaaS and subscriptions
Subscriptions spread revenue over the contract term. If the deal includes usage-based elements, recognition ties directly to consumption (e.g. API calls, storage, and transactions). Upgrades or add-ons become separate obligations, each with its own schedule.
Retail and ecommerce
Here, revenue usually lands at the point of sale. Control passes to the buyer once goods ship or are delivered. Extras like warranties or shipping services have to be carved out and deferred.
Professional services
Consulting or legal projects often qualify for over-time recognition if the client benefits as work is done. Fixed-fee jobs might track hours or costs, while contingency fees hinge on outcomes. The accounting follows the contract’s economics, not just the invoice.
Disclosure requirements related to methods
ASC 606 and IFRS 15 don’t just dictate when revenue is recognized – they also require companies to explain how. That means disclosing:
- The methods used to recognize revenue (point-in-time vs over-time)
- The measures of progress chosen (input vs output) and why they best reflect performance
- The significant judgments applied (allocation of variable consideration, timing of satisfaction of obligations, contract modifications)
Disclosures must give investors and auditors enough information to see both the numbers and the reasoning behind them. A company can’t simply report revenue totals; it has to detail how revenue was earned.
Example disclosure note (simplified):
Narrative disclosure would also explain management’s judgments – for example, why SaaS subscriptions are spread ratably, or why project services use cost-to-complete as the input method.
These notes are closely reviewed in audits. Any inconsistency or vague rationale can draw scrutiny, so clear, consistent disclosures are as important as the revenue numbers themselves.
Challenges in selecting and applying methods
Revenue recognition looks straightforward in the standards, but applying it to live contracts is where the complexity shows up. Most challenges stem from judgment calls, and those judgments drive the numbers investors, auditors, and regulators rely on.
Variable consideration is one of the biggest pressure points. Discounts, rebates, credits, and bonuses are common in SaaS and services. You can’t just plug in a number – you have to estimate. Overstate and you risk pulling revenue forward; understate and you undersell growth.
Complex contracts add more weight. Multi-year SaaS agreements with implementation, support, and usage tiers don’t align neatly with billing. Teams must split them into obligations, allocate prices, and spread revenue over time.
Marketplaces and platforms face the principal vs. agent test. If you control pricing and the customer, you book gross; if you’re just facilitating, you book net. The wrong call can swing results by millions.
Auditors know these are gray zones and they focus on them. Misclassified contracts or inconsistent logic risks adjustments, questions, and even restatements — in earnings as well as in how and when tax liability’s triggered.
How AI automation simplifies revenue recognition methods
The revenue recognition process used to rely on spreadsheets, subjective calls, and last-minute reconciliations. ASC 606 and IFRS 15 define the rules, but they don’t fix the execution problem. AI-native ERPs do.
Contract classification
One of the hardest tasks is deciding whether a contract is point-in-time or over-time. SaaS trials converting to paid, subscriptions with add-ons, and construction milestones all require careful review. AI-powered systems read contract terms, billing triggers, and obligations, then flag the right category, reducing judgment calls and audit dispute.
Measuring progress
Over-time recognition forces a choice between input methods (costs, hours) and output methods (milestones, units). AI platforms pull data in real time from project, billing, or usage systems and recommend the method that best matches the economics.
Dynamic allocations
Discounts, credits, or mid-contract changes usually break spreadsheets. AI re-allocates transaction prices automatically, posts revised entries, and updates ledgers without slowing the close.
Built-In disclosures
ASC 606 and IFRS 15 require narrative as well as numbers. Instead of hand-built tables, AI ERPs generate disclosure reports straight from source data, linking every figure to its origin.
The Result
Automation allows you to enforce rules at scale, saving time and repetitive work. Close cycles shrink, adjustments drop, and finance teams can refocus on analysis instead of chasing formulas. It also keeps the balance sheet aligned with delivery, so the financial position reflects reality, not spreadsheet timing.
Real-world example: comparing methods
Take a $1 million construction contract running for two years. How revenue is recognized depends on the method:
Completed contract method
In this case, no revenue shows until the project is finished. The full $1 million lands in year two, leaving year one at zero. It’s conservative but distorts interim results, which is why it’s mostly phased out.
Percentage of completion (input method)
Here revenue follows costs. If total costs are $800,000 and half ($400,000) is spent in year one, then 50% of revenue ($500,000) is recognized that year. The rest comes through as costs are incurred. It keeps revenue tied to real progress on the ground.
Percentage of Completion (output method)
This approach tracks deliverables instead of costs. If three of six project phases finish in year one, 50% of revenue ($500,000) is recognized, regardless of actual spend. The other half is booked in year two.
Comparison
The completed-contract method bunches all revenue at the end; input-based spreads it with costs; output-based ties it to milestones. The cash flow is the same, but the reported results differ – highlighting why method choice matters and why ASC 606/IFRS 15 push for consistent, documented logic.
How DualEntry helps with revenue recognition
- AI Copilot
DualEntry interprets contracts, not just data. AI auto-suggests recognition schedules for you, ensuring ASC 606 and IFRS 15 compliance. - AI contract parsing
Contracts are scanned automatically, with obligations flagged and payment terms extracted. Structured data flows into the ERP, eliminating manual entry errors. - Dynamic allocation
Discounts, credits, or upgrades are handled in real time. DualEntry reallocates and reclassifies revenue instantly, without needing you to rerun spreadsheets. - Audit-ready
Every decision – from allocations to deferrals to reclassifications – is logged and tied back to the contract. Plus, disclosure tables are generated automatically, saving extra audit-prep time. - Global scale
Covering 180+ currencies and 240+ jurisdictions, DualEntry automates FX translation, intercompany eliminations, and CTA reporting. Multi-entity, multinational businesses can consolidate without bolt-ons. - Forecasting and risk control
AI detects anomalies and forecasts MRR/ARR, churn, and waterfalls. Finance leaders can run scenarios and model contract changes in clicks.
See how DualEntry automates revenue recognition at scale: schedule a demo.
FAQs on revenue recognition methods
What are the 4 rules for revenue recognition?
Before ASC 606, U.S. GAAP relied on four conditions. Companies recognized revenue only when:
- There was persuasive evidence of an arrangement
- Delivery of goods or services had occurred
- The price was fixed or determinable
- Collectibility was reasonably assured
These rules shaped practice for decades. ASC 606 replaced them with the five-step model, but the logic behind those four points still underpins today’s standards.
What are the 5 principles of revenue recognition?
Under ASC 606 and IFRS 15, companies follow a single framework:
- Identify the contract
- Identify the performance obligations
- Determine the transaction price
- Allocate the transaction price
- Recognize revenue as obligations are satisfied
This model applies across industries, replacing dozens of inconsistent legacy methods.
What is the IFRS rule for revenue recognition?
IFRS 15 is the international standard for revenue recognition. It uses the same five-step framework as ASC 606, but with fewer industry-specific add-ons. The key test is whether control of goods or services has passed to the customer. IFRS also expects companies to explain the judgments behind their informed decisions, not just report the numbers.
How can DualEntry help with revenue recognition?
Many finance teams still handle revenue recognition in Excel. DualEntry replaces that manual work with automation. Contracts are scanned, obligations tagged, and prices allocated automatically. Journal entries flow straight into the ledger, while disclosure tables and waterfalls are generated in real time. That means faster closes, fewer errors, and audit-ready records without the spreadsheet scramble.
Glossary of key terms
Percentage of completion
Legacy method for long projects. Revenue is booked as work progresses, tied to costs or milestones. Smoothed results, but only if progress is measurable.
Input method
Over-time recognition based on effort – like costs incurred, hours worked, or time elapsed. Best when effort reliably mirrors value delivered.
Output method
Tracks performance by results – like units shipped, milestones hit, or services provided. Works when outputs are clear proof of delivery.
Completed contract
An old-school rule: no revenue until the job is finished. Conservative, and still seen in financial reporting.
Variable consideration
Revenue that depends on future events, like discounts, rebates, bonuses, or usage. Must be estimated conservatively to avoid overstating results.
Key takeaways
Revenue recognition used to follow industry-specific methods. ASC 606 and IFRS 15 replaced that patchworked approach with one model. Financial statements are clearer, but finance teams now carry more responsibility to explain methods and judgments in their disclosures.
Manual spreadsheets leave gaps. AI-native ERPs close them – allocating revenue, generating disclosure-ready reports, and keeping recognition consistent across entities. For finance leaders, revenue can finally be booked accurately and fast, with systems that scale.
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