What it actually tells you
It indicates cash collection intensity. It is an aggregate approximation, not the actual average age of every customer invoice.
THE CALCULATION
Formula
Receivable days = average trade receivables ÷ credit revenue × days in period; total revenue is a disclosed proxy when credit sales are unavailable
A simple example
Educational example: ₹50 crore average trade receivables against ₹365 crore annual credit sales gives 50 days. At the same sales level, ₹60 crore receivables would imply 60 days and ₹10 crore more tied up.
All figures in this guide are illustrative teaching examples.
Read both sides of the number.
What high can mean
High days may signal generous credit terms, slow collections or disputed invoices. Rapid sales changes can also affect the measure.
What low can mean
Low days may indicate prompt payment, cash sales, advance collection or receivables sold to a financier.
When a high reading may be justified
Long contractual payment cycles may be normal for some customers, provided recovery is reliable and pricing compensates for financing.
When a low valuation may be dangerous
A low P/E can hide sales booked well before cash collection, with eventual credit losses reducing the apparent profit.
BEYOND THE TEXTBOOK
Professional interpretation
Read ageing schedules, customer concentration and credit-loss provisions. Separate trade receivables from loans and other balances; inspect factoring and related-party transactions.
Compare in context.
Live comparison data is not connected. No company or market averages are supplied here.
Sector context
Cash retail differs from government contracting or industrial projects. Revenue recognition and billing milestones can create large differences.
Industry context
Customer bargaining power and contract terms set the context. Rising unbilled revenue may require separate analysis from invoiced receivables.
Historical comparison
Compare equivalent seasonal dates and calculate averages across the year. Look for collection deterioration alongside revenue growth.
Peer comparison
Use the same credit-sales proxy, gross versus net receivable basis and tax treatment. Mixing receivables including indirect tax with revenue excluding it introduces approximation.
Limitations
Period-end balances and total-sales proxies can misstate collection time. Invoice ageing remains essential to identify overdue accounts.
Common investor mistakes
Assuming DSO equals contractual payment terms; ignoring factoring; treating rapidly rising receivables as harmless growth.
Example interpretation
A rise from 50 to 60 days ties up another ₹10 crore at unchanged sales. Investigate collection delays before accepting the earnings growth at face value.
Questions worth asking
What if credit sales are not disclosed?
Use total revenue only as a labelled approximation and keep the same convention in comparisons.
Does falling DSO prove better collections?
No. Factoring, write-offs or changes in customer mix can also reduce the reported balance.
Analyse these together
A single ratio cannot capture the business. Combine it with:
Further reading
TROUGH editorial explanations and educational examples. Sources provide reference material; they do not supply live company figures.
FROM UNDERSTANDING TO RESEARCH
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