Why standard bill of materials fail on the factory floor: by-product and scrap costing

The business scenario: the edible oil refinery losing sales to 'cheaper' competitors

Consider Shreenath Oil & Agro Industries, a soybean processing and solvent extraction plant in Madhya Pradesh crushing 100 metric tons of soybean seeds per day. In their standard ERP system, the finance team set up a rigid Bill of Materials (BOM): 1,000 kg of raw soybean seeds yields 180 kg of refined edible soybean oil. The entire cost of raw seeds (₹42,000 per ton), solvent processing chemicals, power, and factory wages was loaded onto the refined oil.

Because the static BOM loaded 100% of the manufacturing expense onto the oil, the calculated unit cost came out to ₹142 per kg. Meanwhile, competing refineries were bidding for bulk institutional supply contracts at ₹126 per kg. Shreenath's management concluded their plant was inefficient and rejected profitable tenders.

The truth was completely different: the crushing process also produced 800 kg of De-Oiled Cake (DOC / Soya Meal) per ton of seed—a highly valuable protein feed exported globally at ₹34,000 per ton. Because their software could not handle dynamic by-product credits, the value of the soya meal was treated as windfall revenue when sold, while the edible oil was priced out of the market. Shreenath was flying blind on product profitability.

Why standard static BOMs fail in process manufacturing

Standard manufacturing software designed for simple assembly (like assembling a bicycle from a frame, two wheels, and handlebars) assumes a one-directional tree structure: Inputs → Output. However, the vast majority of Indian industrial enterprises operate in process, chemical, agro, food, or metallurgical manufacturing where inputs yield multiple outputs:

• Co-Products: Two or more products of significant commercial value produced simultaneously from the same common process (e.g. refined oil and de-oiled cake; butter and skimmed milk powder; caustic soda and chlorine).
• By-Products: Secondary outputs of relatively lower value produced unavoidably during the primary manufacturing cycle (e.g. molasses in sugar milling; sawdust in timber processing; bagasse in sugarcane crushing).
• Process Scrap & Offcuts: Trim waste, metal turnings, defective sprues, or plastic purge that can either be recycled internally or sold to scrap dealers.

When an ERP forces a multi-output industrial process into a single-output BOM, product costing collapses. Without dynamic by-product allocation, the main product carries inflated costs, while secondary stock enters the warehouse at zero value.

The mathematics of dynamic by-product allocation: Net Realizable Value (NRV)

Under modern managerial cost accounting and Indian AS-2 guidelines, the standard method for costing joint operations is the Net Realizable Value (NRV) Deduction Method. The net realizable value of the by-product is credited against the total batch expenditure:

Let us examine a real-world batch calculation for a 10-ton soybean crushing run:

Notice the dramatic difference: instead of ₹142 per kg, the true cost of refined soybean oil is ₹112.22 per kg. By crediting the ₹2,72,000 generated from the protein meal, management discovers that selling oil at ₹126 per kg yields an excellent ₹13.78 per kg operating margin.

Normal shrinkage vs abnormal scrap: the audit distinction

In manufacturing accounting, mixing up normal shrinkage with abnormal scrap creates significant tax and audit liabilities under GST and Income Tax laws:

Under Section 17(5)(h) of the CGST Act, Input Tax Credit (ITC) must be reversed on goods lost, stolen, destroyed, written off, or disposed of by way of gift. Falsely labelling abnormal scrap as normal process shrinkage can lead to disallowance of ITC and severe tax penalties during GST audits.

Step-by-step process: configuring multi-output BOMs on the shop floor

1. 01Configure multi-output Bill of Materials

   Define the recipe with explicit primary product outputs and secondary by-product/scrap items, specifying expected recovery percentages and valuation basis (Fixed rate vs Market selling price).

2. 02Capture actual material consumption at batch issue

   Scan raw material batch barcodes and issue actual weights into the active Work Order, recording FIFO or Weighted Average cost layers.

3. 03Log secondary output recoveries at stage completion

   When intermediate separation occurs (e.g. skimming cream, collecting metal shavings, bagging bran), operators log the verified weight and storage location.

4. 04Execute automated by-product cost crediting

   The ERP calculates the total realizable value of secondary goods, credits the active WIP account, and generates finished goods inventory vouchers at the true net cost.

Accounting entries: posting joint products in double-entry

Here is how a double-entry ERP architecture records the complete flow without manual spreadsheet journals:

1. Material and Overhead Issue to Work Order:

Debit: Work-in-Progress (WIP) - Solvent Extraction = ₹4,74,000 Credit: Raw Material Inventory - Soybean Seeds = ₹4,20,000 Credit: Consumable Inventory - Solvent Hexane = ₹18,000 Credit: Factory Overhead Absorption Clearing = ₹36,000

2. By-Product Receipt into Sellable Stock:

Debit: Finished Goods Inventory - De-Oiled Soya Cake (8,000 kg) = ₹2,72,000 Credit: Work-in-Progress (WIP) - Solvent Extraction = ₹2,72,000 *(WIP balance drops from ₹4,74,000 to ₹2,02,000)*

3. Primary Product Receipt into Warehouse:

Debit: Finished Goods Inventory - Refined Soya Oil (1,800 kg) = ₹2,02,000 Credit: Work-in-Progress (WIP) - Solvent Extraction = ₹2,02,000 *(WIP account balance cleanly resolves to zero)*

How Naffo handles dynamic manufacturing recipes

Naffo's manufacturing ERP module was purpose-built for continuous process and batch operations. Unlike traditional discrete ERPs, Naffo's BOM architecture supports multiple outputs per recipe. When designing a BOM in Naffo, you can designate lines as Primary Output, By-Product, or Scrap.

During production execution, Naffo's Dynamic Cost Allocation Engine automatically recalculates unit costs based on actual batch output rather than rigid theoretical standards. If a batch yields 3% more by-product due to seed quality, Naffo immediately reflects that additional cost credit, giving your sales team accurate, rock-solid pricing data.