Information Technology Sector Playbook
This playbook covers the Information Technology sector of the Indian stock market. Use it to understand how companies in this sector make money, what metrics...
Sector Overview
This playbook covers the Information Technology sector of the Indian stock market. Use it to understand how companies in this sector make money, what metrics matter most, and how to value them.
What you will learn
- Business Model: How Information Technology companies generate revenue and create value
- Key Metrics: Essential financial metrics for evaluating Information Technology companies
- Competitive Landscape: Market structure, barriers to entry, and competitive dynamics
- Risks & Opportunities: Key risks, regulatory factors, and growth catalysts
- Valuation: Valuation frameworks and peer comparison methods
Sub-industries in this sector
| Basic Industry | Playbook |
|---|---|
| Computers - Software & Consulting | View playbook |
| Computers Hardware & Equipments | View playbook |
| IT Enabled Services | View playbook |
| Software Products | View playbook |
How to use this playbook
Start with the Business Model lesson to understand how companies in this sector generate revenue. Then move through metrics, risks, and valuation in sequence. Each lesson builds on the previous one.
1. Information Technology — Business Models
What you will learn
- IT services revenue model: people × billing rate × utilization
- Contract types: Time & Material vs Fixed Price vs Outcome-based
- Delivery model: offshore leverage as the margin engine
- Service lines: ADM, consulting, cloud/infra, BPO, digital
- Company profiles: TCS, Infosys, HCL Tech, Wipro, Tech Mahindra, and tier-2 specialists
The IT services revenue formula
Revenue = Headcount × Utilization × Billing Rate
| Input | Description | Typical Range |
|---|---|---|
| Total headcount | Engineers + support | 50K (mid-cap) to 6L (TCS) |
| Utilization rate | % on billing projects | 80-88% |
| Billing rate | $/hour to client | $25-35 offshore, $90-150 onsite |
| Offshore mix | % delivered from India | 70-80% |
Contract types
| Type | Revenue Model | Risk | Margin | Trend |
|---|---|---|---|---|
| Time & Material | Bill per hour/day | Low | 28-32% | Declining share |
| Fixed Price | Bill per deliverable | Moderate (scope creep) | 25-35% (variable) | Stable (40-50%) |
| Managed Services | Monthly retainer | Low-Moderate | 30-35% | Growing (20-25%) |
| Outcome-based | Bill on business results | High | 35-45% (if executed) | Early (5-10%) |
Delivery model — offshore leverage
| Factor | India (Offshore) | US (Onsite) | Leverage |
|---|---|---|---|
| Engineer salary | ₹8-20L/year | $80-150K/year | 6-10x cost advantage |
| Billing rate | $25-35/hour | $120-150/hour | 4-5x |
| Margin per person | 40-60% gross | 20-30% gross | Offshore = margin engine |
Offshore mix impact
Every 1% increase in offshore mix = ~0.5% improvement in EBITDA margin. TCS/Infosys at 75-80% offshore = highest margins. Wipro at 70-75% = moderate.
Company profiles
| Company | Revenue ($B) | Employees | EBITDA Margin | Key Strength |
|---|---|---|---|---|
| TCS | $29-30B | 6,00,000+ | 26-28% | Execution excellence, lowest attrition |
| Infosys | $19-20B | 3,20,000+ | 21-23% | Digital/consulting brand, automation |
| HCL Tech | $13-14B | 2,20,000+ | 19-21% | Products (DRYiCE), infrastructure |
| Wipro | $10-11B | 2,40,000+ | 16-18% | Turnaround story (execution issues) |
| Tech Mahindra | $6-7B | 1,50,000+ | 12-15% | 5G/Telecom specialization |
| LTIMindtree | $4-5B | 80,000+ | 17-19% | BFSI + manufacturing, L&T backing |
| Persistent | $1.2-1.4B | 23,000+ | 15-17% | Product engineering, highest growth |
Vertical revenue mix
| Vertical | TCS | Infosys | HCL | Why It Matters |
|---|---|---|---|---|
| BFSI | 32-34% | 28-30% | 20-22% | Largest IT spend globally; cyclical |
| Retail/CPG | 15-17% | 14-16% | 10-12% | Discretionary — cut first in downturn |
| Manufacturing | 10-12% | 12-14% | 18-20% | HCL strength |
| Telecom | 8-10% | 12-14% | 12-14% | Tech M dominant (45%+) |
| Healthcare | 8-10% | 8-10% | 12-14% | Defensive, growing digitization |
Indian context
🗣️
"IT services business model simple hai: PEOPLE × RATE × UTILIZATION = Revenue. TCS 6 lakh employees at $50K per person = $30B. India ka moat: 6-10x cheaper engineers. Ek Indian engineer ₹15L salary, bill $30/hr = 40% gross margin per person. Wahi US mein $130K salary + $150/hr billing = 20% gross margin. Offshore leverage is THE margin driver. TCS/Infosys 75-80% offshore = 26%+ margin. Wipro 70% + poor execution = 16% margin. Digital revenue 60%+ means company relevant for next decade."
✅ Checklist
- ○I understand revenue formula: headcount × utilization × billing rate
- ○I know offshore mix is THE margin lever (1% increase = ~0.5% EBITDA)
- ○I can differentiate T&M (safe) vs Fixed Price (risky but higher upside)
- ○I track revenue per employee as quality metric ($50K+ for large-cap)
- ○I know digital revenue % indicates future relevance (55-65% benchmark)
Key takeaway
Indian IT services is a people × billing rate business where the structural moat is offshore leverage (6-10x cost advantage). Key metrics: utilization (82-86%), offshore mix (75-80%), revenue per employee ($50-62K). TCS is the execution benchmark, Infosys leads digital positioning, HCL has unique product revenue, Wipro/Tech M are turnaround stories at discount.
2. Information Technology — Key Metrics
Revenue metrics: CC growth, $ revenue growth, large deal TCV, revenue per employee Operational metrics: utilization, attrition, offshore mix, subcontracting...
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3. Information Technology — Competitive Landscape
Tier1 vs Tier2 vs global competitors positioning Market share dynamics and growth differential Competitive moats: scale, relationships, domain, technology Ho...
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4. Information Technology — Risks
Demand risks: client budget cuts, vertical concentration, macro sensitivity Structural risks: AI/GenAI disruption of peoplebilling model Operational risks: a...
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5. Information Technology — Valuation
Why P/E is the primary valuation metric for IT services Historical P/E bands for Tier1 and Tier2 companies PEG ratio as the real comparability metric $ reven...
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