Lesson 32: Activity-Based Costing

Lesson 32 of 33 · 96%

Why traditional costing breaks

Traditional overhead allocation uses one or two broad activity bases — typically direct labour hours or machine hours. That worked when factories made similar products at scale. But modern factories produce a mix of high-volume simple products and low-volume complex ones, and a blanket rate distorts product costs badly: simple products end up subsidising the complex ones. Pricing decisions made on these distorted numbers lose money silently for years.

Activity-Based Costing (ABC) replaces the blanket rate with multiple rates, one per activity, each driven by what actually causes that cost. The result is more accurate per-product cost.

ACTIVITY-BASED COSTING — Two-Stage Allocation STAGE 1 — Resources → Activities (cost pools) Machine setups Driver: # setups Quality inspection Driver: # inspections Order processing Driver: # orders Material handling Driver: # moves STAGE 2 — Activities → Products (by driver usage) Better than blanket OH rates for diverse product mixes.
Two-stage allocation. Resources flow first to activities (cost pools), then activities flow to products in proportion to each product’s driver usage.

The five steps of ABC

  1. Identify activities. What activities consume resources? Machine setups, quality inspections, material handling, order processing, engineering changes.
  2. Assign costs to activity pools. Aggregate all costs (labour, depreciation, supplies) associated with each activity into a single pool.
  3. Identify the cost driver for each activity. What measure best explains how the activity consumes resources? Number of setups, number of inspections, weight moved, number of orders.
  4. Compute a rate per driver unit. Total pool cost ÷ Total driver units = Rate per setup, inspection, kg moved, etc.
  5. Apply to products. Each product gets charged based on its actual driver consumption.

Worked example

A factory makes two products: a high-volume standard widget (Product A, 1,00,000 units) and a low-volume custom widget (Product B, 5,000 units). Annual overhead: ₹50,00,000.

Traditional method (DLH-based):

Total DLH = Product A (50,000) + Product B (10,000) = 60,000 hours. Rate = 50,00,000 ÷ 60,000 = ₹83.33/hour.

  • Product A gets 50,000 × ₹83.33 = ₹41.67 lakh overhead → ₹41.67/unit
  • Product B gets 10,000 × ₹83.33 = ₹8.33 lakh overhead → ₹166.67/unit

ABC method:

ActivityPool (₹)DriverProduct A useProduct B use
Machine setups12,00,000# setups100400
Quality inspections10,00,000# inspections200800
Material handling8,00,000# moves400600
Order processing5,00,000# orders50450
Power & other15,00,000machine hrs8,0002,000

Computing per-unit ABC cost (rate × product usage ÷ units produced) shows that Product B actually costs around ₹450-500/unit overhead, not ₹166.67. The traditional method underestimated Product B’s overhead burden by ~3x. Pricing Product B was almost certainly leaking margin.

Choosing the right driver

A good cost driver has three properties:

  • Causation. It actually causes (or is strongly correlated with) the cost.
  • Measurement. You can actually count or measure it without excessive effort.
  • Differentiation. It varies enough across products to distinguish them.

Picking number of setups when every product needs roughly the same setups gives no differentiation — the driver is useless even if measurable.

When ABC is worth the effort

  • Significant overhead as a % of total cost (typical: >30%).
  • Diverse product mix in volume, complexity, batch size.
  • Suspicion that current product costs are misleading pricing or product-mix decisions.
  • Customer or market diversity that may also distort costs.

ABC is not worth it for: single-product factories, businesses where overhead is small, or organisations without the data infrastructure to track activity drivers reliably.

Time-driven ABC

A modern simplification: instead of tracking every cost driver separately, estimate the time each activity takes per product and the cost per minute of departmental capacity. Faster to implement; easier to maintain. Pioneered by Robert Kaplan in the early 2000s and widely adopted since.

Lesson recap

  • Traditional one-rate overhead allocation distorts costs in mixed product environments.
  • ABC uses multiple pools, each with its own driver.
  • Five steps: identify activities → pool costs → identify drivers → compute rates → apply.
  • Most useful when overhead is large and products are diverse.
  • Time-driven ABC simplifies the approach for ongoing use.
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Practitioner Insights

ABC implementation tools: SAP CO Module for full ABC; Oracle Hyperion Profitability and Cost Management; Tally TDL customisation for cost-driver tagging; ICMAI’s ABC implementation guide; case studies from major Indian pharma and auto-component companies that have shared their ABC journeys.

Worked Example — Bharat Pharma ABC vs Traditional

Imagine Bharat Pharma’s traditional costing loads ₹500 of overhead per unit of all SKUs. Under ABC, a small-batch generic SKU that requires 12 setups, 25 inspections and 6 dispatches in a month gets allocated ₹120/setup + ₹40/inspection + ₹80/dispatch = ₹1,440 + ₹1,000 + ₹480 = ₹2,920 of overhead, while a large-batch flagship SKU with 1 setup, 4 inspections, 2 dispatches gets ₹120 + ₹160 + ₹160 = ₹440. The small-batch SKU, sold at a ₹600 ‘margin’ under traditional costing, is actually losing ₹1,820 per unit. ABC tells the firm to either reprice, discontinue or batch-consolidate the small SKU.

Common ABC Implementation Mistakes

  • Choosing too many cost drivers — complexity overwhelms benefits
  • Not capturing activity data accurately (timesheets, transaction logs)
  • Failing to communicate ABC results to product managers and sales
  • Treating ABC as a one-time project rather than ongoing process

Frequently Asked Questions

Is ABC mandatory in India?
No, but Cost Records under Rule 5 of the Companies (Cost Records and Audit) Rules 2014 require allocated costs by product/service. ABC is one of the accepted methodologies.

Why don’t all firms use ABC?
Data collection and software cost. ABC needs detailed activity logs which simple ERP/Tally setups may not capture without customisation.

Can ABC be applied to service firms?
Yes — banks use ABC to allocate branch overhead to products, hospitals to allocate to procedures, IT firms to allocate to projects.

ABC Implementation in Indian Industry

Activity-Based Costing has gained traction in Indian pharma, auto-components and specialty chemicals where product complexity varies widely. Cipla, Sun Pharma, Bharat Forge and Sundram Fasteners use ABC to allocate quality-control, regulatory and setup costs accurately. Bank-CMA reports under ICMAI guidelines accept ABC as a valid cost method. The cost-benefit calculus favours ABC for firms with: (1) wide product variety, (2) high indirect-cost ratio above 25%, (3) complex customer demands, (4) regulatory pressure for accurate costing. Bharat Forge analyses two product lines: standard automotive crankshaft (high volume, simple) and aerospace forging (low volume, complex). Traditional costing using machine hours allocates ₹400/hour OH. Under ABC, aerospace forging gets allocated 60× higher per-unit overhead than the standard crankshaft.

Implementation Path

Start small with ABC — pick 5 SKUs across high/low volume tiers, run ABC manually in Excel, compare with traditional cost allocation. Often, “profitable” small-batch SKUs turn out to be value destroyers under ABC. Reprice them at +15-25%, restrict order minimums, or discontinue. The exercise typically delivers 2-4% margin uplift on the analysed SKU set without operational change — pure analytical alpha.

Time-Driven ABC — The Modern Evolution

Classical ABC uses dozens of cost drivers (number of setups, inspections, dispatches) which makes data collection expensive. Time-Driven ABC (TDABC), pioneered by Robert Kaplan, simplifies — every activity is measured in TIME (minutes) and time-driven cost = capacity cost per minute × minutes consumed. Capacity cost per minute = total department cost ÷ practical capacity (in minutes). The simplification cuts data collection by 50-70% while preserving accuracy. Major Indian users include Hindustan Aeronautics Limited (HAL), Bharat Forge, Tata Steel for select departments. TDABC also handles unused capacity explicitly — the difference between practical and used capacity reveals “cost of unused resources” that drives capacity optimisation decisions. As an analyst, TDABC results often surprise — efficient-looking departments turn out to have 30-40% unused capacity, while “busy” departments may be capacity-constrained.