Product Life Cycle (PLC): Definition

This video breaks the Product Life Cycle (PLC) into five phases—R&D, Introduction, Growth, Maturity, and Decline—and uses simple graphs to show how sales, unit cost, and cash flow typically behave as a product moves through each stage. Watch it with an end-to-end supply chain lens: PLC is a practical trigger for changing your planning settings (forecasting approach, inventory buffers, capacity posture, sourcing choices, and end-of-life controls). Done well, PLC thinking prevents the classic pitfalls: launch shortages, growth constraints, maturity cost creep, and decline obsolescence/write-offs.

Plain-language translation (supply chain lens)

Think of PLC as a policy switchboard. As a product moves from launch to exit, you should deliberately change planning parameters, service targets, sourcing strategy, inventory rules, and capacity decisions—not only marketing messages.

The graphic is designed to make one point unmistakable: the same supply chain rules cannot work across all Product Life Cycle (PLC) stages. PLC isn’t just a marketing concept; it is a governance trigger that tells planners when to change the “dials” that control service, cost, cash, and risk across the end-to-end supply chain.

In practice, the image helps leaders answer two questions:

1. What stage is this product really in (Introduction, Growth, Maturity, Decline)?

2. Which planning and execution settings must change right now to match that stage?

(Definitions and terminology alignment reference: ASCM Supply Chain Dictionary, 19th ed.) ASCM Dictionary- Updated - 19th…

The top PLC curve = demand reality + supply chain stress points

• Introduction: uncertainty is highest; data is thin; engineering changes are common.

• Growth: volume accelerates; constraints show up; service failures become market share losses.

• Maturity: volume stabilises; competition increases; cost-to-serve and margin pressure dominate.

• Decline: demand becomes intermittent; obsolescence and write-offs become the main risk.

The curve is not “academic.” It’s a stress map: each stage brings a different failure mode if the supply chain doesn’t adapt.

The five “control panel” dials (what must change by stage)

The lower panels deliberately show the five decision levers that most strongly determine supply chain performance:

A) Forecast method

• Introduction: Analogs + scenarios (use comparable products, market intelligence, and launch scenarios; refresh often).

• Growth: Bias control + frequent reforecast (stop “optimism bias” early; shift to short-cycle demand sensing).

• Maturity: Statistical + promotion logic (separate base demand from uplift; stabilise the model).

• Decline: Run-out + intermittent demand logic (don’t forecast like a stable item; plan depletion and substitution).

Why this matters: forecast method mismatch is the fastest way to create whiplash—shortages in growth, then excess in maturity/decline.

B) Safety stock posture

• Introduction: keep buffers targeted (critical components, long lead items, launch risk points).

• Growth: buffers protect service at constraints (where shortages cause customer churn).

• Maturity: buffers become a turns vs service trade-off (segment by channel and variability).

• Decline: buffers must shrink aggressively (exposure limits and “no stranded stock” rules).

Why this matters: late-life stock is rarely “just inventory”—it becomes write-offs, markdowns, and trapped cash.

C) Lot size (and replenishment frequency)

• Introduction: smaller, flexible lots (learn fast; avoid early overbuild).

• Growth: scale lots cautiously while monitoring constraints (avoid capacity chaos).

• Maturity: optimise lots for cost and stability (separate promotional builds from base demand).

• Decline: minimise lots (shift to “last-time-buy / run-out” discipline).

Why this matters: lot size is the hidden driver of cash cycle time, obsolescence, and capacity instability.

D) Capacity posture

• Introduction: flexibility first (outsourcing, rapid changeovers, postponement).

• Growth: scale-up and debottleneck (capacity becomes a strategic weapon).

• Maturity: optimise and stabilise (utilisation, efficiency, cost-to-serve).

• Decline: ramp-down and decommission (remove fixed cost and avoid building ahead of demand).

Why this matters: most organisations fail PLC because they treat capacity decisions as operational, not strategic—then they pay with overtime, premium freight, or underutilised assets.

E) Supplier strategy

• Introduction: resilience and responsiveness (dual source critical items; shorten lead time where possible).

• Growth: secure supply (capacity commitments, tighter execution discipline, lead time reliability).

• Maturity: cost and standardisation (contracts, consolidation, VA/VE, supplier scorecards).

• Decline: rationalise and exit (supplier discontinuation planning, last-time-buy, substitution plans).

Why this matters: supplier strategy must shift from speed → scale → efficiency → exit control, or the supply chain becomes unmanageable in late stages.

The “stage behaviour” summary (what good looks like)

Introduction stage supply chain behaviour

• Plan for uncertainty, not accuracy.

• Protect launch-critical materials and long lead items.

• Use short planning cycles and rapid learning loops.

• Design flexibility into the network (postponement, alternate supply, rapid response).

  
  

Growth stage supply chain behaviour

• Win on service and availability.

• Treat constraints as strategic: capacity, suppliers, and logistics must scale together.

• Tighten allocation and prioritisation rules during shortage.

• Reduce bias and “hero planning” through governance.

  
  

Maturity stage supply chain behaviour

• Optimise cost-to-serve and working capital.

• Segment customers/channels: not everyone gets the same service promise.

• Separate base demand from promotional demand.

• Standardise, simplify SKU complexity, and lock in stable execution.

  
  

Decline stage supply chain behaviour

• Execute an end-of-life (EOL) plan, not “business as usual.”

• Freeze unnecessary changes; control builds; manage run-out.

• Shift to substitution and service obligations (spares, warranties).

• Minimise exposure: aged stock, last-time-buy, and supplier exit plans.

  
  

How to use the image in real decision-making (End2End execution lens)

Use the image as a monthly PLC governance agenda:

1. Confirm stage (trend + volatility + margin trajectory + competitive intensity).

2. Check dial settings (forecast, safety stock, lot size, capacity, suppliers).

3. Trigger policy changes (e.g., service targets, planning cycle time, allocation rules, last-time-buy gates).

4. Track stage KPIs:

   • Intro: forecast bias learning rate, launch fill, engineering change impact

   • Growth: OTIF, constraint utilisation, backlog recovery time

   • Maturity: cost-to-serve, turns, promo forecast accuracy

   • Decline: obsolescence %, aging, run-out adherence, write-off avoidance

This is the practical value of the graphic: it turns PLC into a repeatable operating mechanism, not a textbook diagram.

Why it matters (service, cost, cash, risk)

PLC mismatches drive launch shortages, growth stockouts, maturity cost creep, and late-life obsolescence. Getting the stage right improves service, reduces premium freight and write-offs, releases working capital, and lowers end-of-life risk.

How it shows up (symptoms)

Typical signals include repeated forecast overrides, volatile service performance, capacity whiplash (rush expansions followed by under-utilisation), and rising aged inventory and write-offs in late life.

Root causes

Common drivers are one-size-fits-all planning rules across SKUs, weak phase-in/phase-out governance, lead time and MOQ constraints that don’t fit volatility, and commercial incentives that push supply long after demand has shifted.

How to measure (simple diagnostic)

Classify stage using volume trend and volatility, margin trajectory, competitive intensity, and promo dependence. Track forecast bias and MAPE by stage, inventory turns and aging, obsolescence percentage, OTIF/fill rate by segment, and capacity utilisation at constraints.

How to improve (practitioner playbook)

1. Classify SKUs by lifecycle stage.

2. Set stage-based policies (forecast method, service targets, safety stock logic, replenishment frequency, MOQ rules).

3. Run a cross-functional phase-in/phase-out cadence.

4. Protect launches with flexibility.

5. Optimise maturity with cost-to-serve discipline.

6. Execute end-of-life with run-out plans, substitution, and exposure limits.

Explanation of Product Life Cycle by using case studies

This video is a quick, visual walk-through of the Product Life Cycle (PLC) using familiar examples (like iPhone and Coca-Cola). Watch it with a supply-chain lens: each PLC stage should trigger a deliberate policy shift in forecasting approach, inventory buffers, capacity decisions, and service targets. The real value is not the marketing labels—it’s recognising when your product has moved into a new stage so you can prevent the classic PLC failures: launch shortages, growth stockouts, maturity cost creep, and decline obsolescence/write-offs.

SCOR lens

Plan: stage-based demand and inventory policies; Source: flexible suppliers and last-time-buy logic; Transform: ramp-up/ramp-down controls; Fulfill: allocation and channel rules; Return: warranties and EOL returns; Orchestrate: decision rights and KPI alignment across functions.

CSCP exam cues

Expect questions that link PLC stages to appropriate supply chain strategies and policy shifts. A common distractor is applying mature-stage efficiency settings during launch—or keeping growth assumptions into decline.

The image below indicate the tyupical supply chain impacts during the different phases of the PLC.