Operations management

In short

Operations management is the design, planning, control and improvement of the processes that convert inputs (men, material, machines, money, information) into goods and services. It decides what capacity to build, how to lay out a plant, how much to produce and how to raise productivity — the function that actually delivers the product a customer pays for. It is examined in every BBA/BMS production-and-operations paper and in MBA entrance and campus aptitude tests, and it is the base knowledge for operations, plant and process-excellence roles at Maruti Suzuki, Tata Motors, Asian Paints, HUL, ITC, Amazon and Flipkart.

Explained

What operations management covers

• Definition: managing the transformation process so that the right output is produced at the right cost, quality, speed and flexibility.
• Transformation model: inputs → process (conversion) → outputs, with feedback and control loops correcting deviations.
• The five Ps: product, plant, process, programme (schedule), people.
• Competitive priorities: cost, quality, delivery (speed and reliability), flexibility and, increasingly, sustainability. A plant cannot maximise all at once — the trade-off is the decision.
• Goods versus services: services are intangible, perishable (cannot be inventoried), produced with customer contact, and harder to measure — detailed treatment belongs to the service-operations topic.
• Strategic decisions (long term): product and process design, capacity, location, layout, technology. Tactical/operational: forecasting, aggregate planning, scheduling, inventory, maintenance, quality control.

Process types and layouts

• Project: one-off, high customisation, resources brought to site — a metro station, a turnkey plant.
• Job shop: low volume, high variety, general-purpose machines, skilled labour, high WIP — a tool room, a tailoring unit.
• Batch: moderate volume and variety, products made in lots with setups between them — pharmaceutical formulations, garments, paints.
• Mass/line (assembly line): high volume, standard product, special-purpose machines, low unit cost — two-wheelers, FMCG packing lines.
• Continuous flow: 24×7 production of a commodity — cement, steel, refineries, fertiliser.
• Layout follows the process: *process (functional) layout* groups similar machines (job shop); *product (line) layout* arranges machines in the operation sequence (mass); *cellular layout* groups machines into cells for a part family (group technology); *fixed-position layout* for projects.
• As volume rises, variety falls, unit cost falls and flexibility falls — the product–process matrix.

Capacity, planning and control

• Capacity types: *design capacity* (maximum theoretical output), *effective capacity* (after allowances for setups, maintenance, breaks), *actual output*.
• Capacity strategies: lead (build ahead of demand), lag (expand after demand is proven), match (small frequent steps).
• Bottleneck: the resource with the least capacity; the whole line's throughput equals the bottleneck's rate, so improvement anywhere else adds nothing (theory of constraints — identify, exploit, subordinate, elevate, repeat).
• Planning hierarchy: forecast → aggregate (production) plan, usually 6–18 months → master production schedule → MRP for materials → shop-floor scheduling and dispatch → control and feedback.
• Aggregate planning strategies: *chase* (vary output with demand — overtime, temporary staff), *level* (constant output, absorb swings in inventory or backorders), *mixed*. Under the Labour Codes in force from 21 November 2025, working hours, overtime and contract-labour limits are statutory constraints on a chase plan — overtime is paid at twice ordinary wages.
• Scheduling rules for a job shop: FCFS, SPT (shortest processing time — minimises average flow time), EDD (earliest due date — minimises maximum lateness), critical ratio.
• Lean and JIT: produce only what is pulled, in small lots, with quick setups; attack the seven wastes (overproduction, waiting, transport, over-processing, inventory, motion, defects). Widely adopted in Indian auto component plants.
• Maintenance: breakdown, preventive, predictive and total productive maintenance (TPM); measured by MTBF, MTTR and availability.

Productivity and performance measurement

• Productivity = output / input. *Partial* (output per labour hour, per machine hour, per kWh), *multifactor*, *total factor*.
• Productivity is a ratio, not a volume — output can rise while productivity falls.
• Efficiency = actual output / standard or effective output; utilisation = actual output / design capacity.
• OEE (overall equipment effectiveness) = availability × performance × quality — the standard shop-floor metric.
• Takt time = available time / customer demand; cycle time = time between successive units leaving the line. The line meets demand only when cycle time ≤ takt time.
• Little's Law links WIP, throughput and lead time — reducing WIP shortens lead time at the same throughput.
• Advantages of strong operations management: lower unit cost, predictable delivery, less inventory locked up, better quality and safety.
• Limitations: forecasts are uncertain, capacity is lumpy and costly to reverse, lean systems are fragile to supply shocks, and over-focus on cost erodes flexibility and morale.

Key points

• Operations management - converting inputs into outputs efficiently and effectively.
• Five Ps - product, plant, process, programme, people.
• Competitive priorities - cost, quality, delivery, flexibility; trade-offs are unavoidable.
• Process spectrum - project → job shop → batch → mass → continuous, as volume rises and variety falls.
• Layout types - process, product, cellular, fixed-position; layout follows process choice.
• Design vs effective capacity - theoretical maximum versus realistically achievable output.
• Bottleneck - the slowest resource fixes system throughput.
• Aggregate planning - chase, level or mixed strategy over 6–18 months.
• Productivity - output/input ratio; partial, multifactor or total.
• Utilisation vs efficiency - measured against design capacity versus effective capacity.
• OEE - availability × performance × quality.
• Takt time - the pace demand requires; the line must run at or below it.
• Little's Law - WIP = throughput × lead time.
• Labour Codes (from 21 Nov 2025) - hours, overtime and contract-labour rules now bound shop-floor planning.

Formulas and examples

Example 1 — capacity, utilisation, efficiency and break-even. A Pune auto-component plant has design capacity 1,200 units/day. Allowing setups and maintenance, effective capacity is 1,000 units/day; actual output is 900 units/day.

• Utilisation = 900 / 1,200 = 75%
• Efficiency = 900 / 1,000 = 90%
• Fixed cost ₹18,00,000/month, variable cost ₹120/unit, price ₹300/unit → Q* = 18,00,000 / (300 − 120) = 10,000 units/month
• At 900 units/day × 25 working days = 22,500 units, contribution = 22,500 × 180 = ₹40,50,000 → profit = 40,50,000 − 18,00,000 = ₹22,50,000/month

Example 2 — takt time, workstations and OEE. Demand is 480 units per shift; the shift is 8 hours with 60 minutes of breaks, so available time = 420 minutes. Total assembly work content = 21 minutes per unit.

• Takt time = 420 / 480 = 0.875 min/unit (52.5 seconds)
• Minimum workstations N = 21 / 0.875 = 24 stations
• If 25 stations are actually used, line efficiency = 21 / (25 × 0.875) = 21 / 21.875 = 96%
• OEE on the same line: availability 420 min planned, 378 min running → 0.90; performance = actual 396 units ÷ 432 possible at takt in the 378 running minutes → 0.9167 (performance is measured against run time, not planned time, else the availability loss is counted twice); quality = 385 good of 396 → 0.972. OEE = 0.90 × 0.9167 × 0.972 = 0.802 ≈ 80.2%
• Little's Law check: throughput 396 units / 6.3 running hours ≈ 62.9 units/hour; if WIP on the line is 63 units, lead time ≈ 63 / 62.9 ≈ 1.0 hour

Where it is used

• Manufacturing: production planning and control, industrial engineering and TPM roles at Maruti Suzuki, Tata Motors, Bajaj Auto, Bosch, Asian Paints and Hindustan Unilever plants.
• E-commerce and warehousing: Amazon, Flipkart and Delhivery fulfilment centres plan picking capacity, takt and productivity per associate per hour.
• Services and healthcare: bank back-office processing hubs, Apollo and Fortis hospital OT scheduling, IRCTC and airline ground operations use capacity and queue planning.
• Roles and credentials: operations executive, production planner, industrial engineer, process-excellence/Six Sigma analyst; CII and NPC productivity programmes, Make in India and PLI scheme plants.

Interview questions

• Q: What is operations management? A: The design, planning, control and improvement of the processes that convert inputs into goods or services at the required cost, quality, speed and flexibility.
• Q: Difference between efficiency and effectiveness in operations? A: Efficiency is doing the work with the least resources; effectiveness is achieving the intended result — a plant can be efficient at making the wrong product.
• Q: Why does a bottleneck determine a line's output? A: Every unit must pass through it, so the system cannot produce faster than the slowest resource; improving non-bottlenecks only builds inventory.
• Q: When would you choose a process layout over a product layout? A: For low volume and high variety, where general-purpose machines must handle many different routings, as in a job shop.
• Q: What is the difference between chase and level aggregate planning? A: Chase varies output to match demand (flexible, costlier in hiring and overtime); level keeps output constant and absorbs variation through inventory or backlogs.
• Q: How is productivity different from production? A: Production is the quantity produced; productivity is output per unit of input, so production can rise while productivity falls.
• Q: What does OEE tell a plant manager? A: The share of planned time that equipment produced good output at full speed, splitting the loss into availability, performance and quality so the biggest loss can be attacked first.

Common mistakes

• Confusing utilisation (against design capacity) with efficiency (against effective capacity), or reporting one as the other.
• Treating productivity as a volume figure instead of a ratio, and omitting the input unit.
• Improving a non-bottleneck and claiming higher throughput.
• Using available time without deducting breaks and planned downtime when computing takt time, or dividing demand by time instead of time by demand.
• Multiplying OEE components after writing them as percentages (90 × 92 × 97) instead of as fractions.

Related topics

• Supply chain management basics · Total quality management · Project management · Service operations and quality · Logistics fundamentals