Gross Margin Method in India: The Underused Alternative to TNMM

The Gross Margin Method (GMM) is one of India’s five prescribed methods (s.92C) and — despite being listed alongside TNMM and CPM in every TPO discussion — one of the least used. It tests a transaction on its gross margin (gross profit as a percentage of sales, or equivalently the resale price less the cost of the goods) rather than on net profitability. For the right fact pattern, GMM is sharper than TNMM; in the wrong one, it collapses under denominator noise.

What GMM measures

GMM compares the gross margin of the controlled transaction with the gross margin of comparable uncontrolled transactions:

Gross margin = (Sales − Cost of goods sold) / Sales

No operating expenses enter the ratio. That is the point and the risk:

• The point: for a function whose value is the spread between what it buys and what it sells — distribution, resale, buying-and-selling — the gross margin isolates exactly the function’s contribution. Operating costs (people, premises, support) are noise that dilute the signal.
• The risk: the ratio is only as clean as the cost of goods sold data. COGS must exclude what it should exclude (admin overheads, finance costs) and include what it should include (direct material, direct labour, manufacturing overhead for in-house production, import duties in the cost where the comparator’s economics include them). One definition difference between tested party and pool moves the whole range.

Where GMM sits in the method family

Method	What it tests	Best fact pattern
CUP	The price	A true uncontrolled price exists
GMM	Gross margin on sales	Resale/distribution where the gross spread is the function’s return
Cost plus / CPM	Mark-up on cost	Services, contract manufacturing
TNMM	Net PLI (OP/OC, OP/S, ROCE…)	Company-level benchmarking where net data is clean
Profit split	Residual allocation	Entrepreneurial, two-sided uniqueness

Note the relationship to RPM (resale price): RPM works backwards from the resale price to a cost/price, while GMM works on the margin ratio directly. In Indian practice the two are often discussed together; GMM is the ratio test, RPM is the price test.

When GMM beats TNMM

1. Pure distribution / buy-sell. The tested party buys, holds, resells — and earns the gross spread. Operating expenses are ancillary. GMM isolates the distribution return directly.
2. Traders with minimal operating cost structure. Where operating costs are a small, stable share of revenue, TNMM’s net PLI and GMM’s gross PLI rank companies similarly — but GMM is less sensitive to the operating-cost noise (support headcount, premises, FX on expenses) that plagues net figures.
3. Where the cost base is contested. A TPO that challenges your operating cost definition (what belongs in “operating cost”) can distort TNMM; GMM’s COGS definition is narrower and therefore harder to argue about — if the COGS data is genuine.
4. Commodity-like goods with thin, stable spreads. Where the gross margin is the market signal (commodity trading, simple resale), GMM matches the economics.

When GMM fails

1. Services. There is no COGS for a service; GMM has no denominator. (Services go to OP/OC or the safe harbours.)
2. Mixed entities. Where the entity both manufactures and distributes, the COGS of self-produced goods (with its embedded margin) distorts the gross spread — the “margin in the base” problem.
3. Where COGS data is unavailable or inconsistent across the pool. This is GMM’s killer in Indian practice: Prowess/Capitaline carry revenue and profit lines reliably, but cost of goods sold at comparable granularity is thin. If the pool cannot compute a defensible COGS, GMM cannot be built.
4. Where inventory valuation policy differs between companies — LIFO/FIFO, write-down treatment, and capitalised overheads all move COGS. The pool must be normalised or the range is comparing apples to oranges.

Denominator discipline: the whole game

GMM lives or dies on the ratio’s construction. The discipline checklist:

• Same definition, every company. COGS = goods sold, at cost, before operating expenses — written down once, applied to the tested party and all comparables.
• Exclude operating overheads, finance costs, non-operating items, and (document it) any capitalised items the pool cannot replicate.
• Include consistently: import duties, freight-in, direct production overhead where the comparator is a manufacturer — or exclude the manufacturer from a resale pool.
• Inventory policy consistency. Check the pool’s inventory valuation; document the treatment of write-downs (they flow straight through gross margin — see the extraordinary events playbook).
• Sales consistency. Net of returns and discounts, for every company.

Worked example: a commodity trader

An Indian entity buys steel products from its overseas parent and resells domestically. FY 2025-26:

Item	₹ crore
Sales	120.0
Cost of goods sold	114.0
Gross margin	5.0%

Three independent steel traders (NIC 27 division, comparable volume band, domestic resale model) screen to gross margins of 3.8%, 5.2%, and 7.1%. IQR: 3.8% to 7.1%. The tested party’s 5.0% sits inside the range.

Now the contrast that shows why the definition matters: if the same tested party’s figures were restated with administrative overheads of ₹2.4 cr capitalised into opening inventory (a valuation quirk), the apparent gross margin would be 4.8% and the pool comparison would be distorted by the definition, not the economics. The documentation shows the COGS definition and the inventory policy — and the 5.0% stands.

How TPOs treat GMM

• Accepted where the pool is clean. A well-built GMM range with a stated COGS definition and a documented pool is respected — it is a prescribed method, not a curiosity.
• Challenged where the data is thin. The usual TPO move against a weak GMM is not to reject the method but to rebuild the pool (different NIC set, different geography) or to switch to TNMM on the ground that net data is more reliable. The defence is the data: if your GMM pool is reproducible and your COGS definition is stated, the switch costs the TPO credibility.
• Watch the “margin in the base” argument. For entities that both make and sell, TPOs routinely argue the gross margin is contaminated by the embedded manufacturing margin — and move the analysis to the manufacturing function. Know where your entity sits on the make/sell spectrum before choosing GMM.

The practical sequence for a GMM study

1. Confirm the function is resale/distribution (the FAR profile).
2. Confirm COGS is available for the pool at consistent granularity (the database check — if it fails, GMM is off the table and TNMM on OP/Sales is the fallback).
3. State the COGS definition and inventory treatment.
4. Build the pool (NIC, size, related-party screens) with the same definition.
5. Compute the range (IQR) and test the tested party.
6. Document the definition, the pool, and the result — the three exhibits a TPO will actually read.

GMM is the method that rewards data discipline more than any other in the Indian set — and the reason it is underused is that most teams check the database for COGS only after they have already committed to TNMM. Check first: where GMM is buildable, it is often the sharper test.