Industry analytics is the discipline of studying an industry with data to answer questions such as: how big is it, how fast is it growing, who earns the profits, who is likely to win, and where are the openings? A firm’s results depend heavily on the industry it competes in, so analysing the industry comes before analysing the firm.
1. What an industry is, and how to scope it
An industry is a group of firms producing close substitutes; a sector is a broader group (financial services), and a market is where buyers and sellers meet. Scoping decisions matter: is “mobility” the industry, or “cars”, or “electric cars in India”? Define by product, geography and customer. Standard classifications (such as NIC in India, NAICS and GICS globally) allow comparison and data pulls.
An analysis sets out: size, growth, structure, profitability, drivers, risks and outlook.
2. Industry structure and concentration
The structure–conduct–performance idea: structure (number and size of firms, barriers to entry) shapes conduct (pricing, competition) which shapes performance (profit).
| Measure | Meaning |
|---|---|
| Concentration ratio (CR4) | Combined share of the top 4 firms |
| Herfindahl–Hirschman Index (HHI) | Sum of squared market shares (in %); higher means more concentrated |
| Barriers to entry | Scale, capital, regulation, brand, access to distribution, network effects |
Example: four equal firms with 25% each give HHI = 4 × 25² = 2,500; one firm with 100% gives 10,000. Competition authorities (the CCI in India) watch HHI changes in mergers. Industries range from fragmented (many small players: restaurants) to consolidated (few large players: telecom).
In the real world: Indian telecom consolidated from well over ten operators in the late 2000s to a market with three large private players and one state-owned operator, a move from fragmentation to oligopoly that changed pricing behaviour.
3. Porter’s Five Forces
Michael Porter’s framework judges industry profitability by five forces:
| Force | Stronger when… | Effect on profit |
|---|---|---|
| Rivalry among competitors | Many equal players, slow growth, high fixed costs, low differentiation | Lowers |
| Threat of new entrants | Low barriers | Lowers |
| Threat of substitutes | Alternatives are close in price and function | Lowers |
| Buyer power | Few, large buyers; low switching cost; price-sensitive | Lowers |
| Supplier power | Few suppliers; unique inputs; high switching cost | Lowers |
The firm responds by building a position that defends against the forces or tilts them (switching costs, scale, differentiation, backward integration). A sixth force, complementors (as in app ecosystems), is often added.
In the real world: airlines face strong rivalry, strong buyer power (price comparison), strong supplier power (aircraft makers, fuel, airports) and high fixed costs, so the industry has historically struggled to earn consistent profits; several Indian carriers have failed. Software with strong network effects and switching costs shows the opposite pattern.
4. The macro environment: PESTLE
A PESTLE scan lists political, economic, social, technological, legal and environmental forces, then ranks them by impact and uncertainty. These forces drive scenario planning: build two or three plausible futures (for example, fast or slow EV adoption) and test strategy against each.
In the real world: subsidies and policy on electric vehicles, falling battery prices, charging infrastructure and consumer attitudes are PESTLE factors that jointly shape the Indian auto industry’s outlook.
5. Industry life cycle and growth
Industries pass through introduction, growth, maturity and decline, with changing features:
| Stage | Growth | Competition | Profit and strategy |
|---|---|---|---|
| Introduction | Slow | Few players, experimentation | Losses; build awareness and standards |
| Growth | Fast | New entrants, a race to scale | Rising profits; invest in capacity |
| Maturity | Slow | Shakeout, consolidation | Cost and efficiency; stable margins |
| Decline | Falling | Exits, price pressure | Harvest, niche or exit |
Related: S-curve adoption, and disruptive innovation (Christensen), in which a cheaper, simpler product from below gradually displaces incumbents.
In the real world: feature phones went through the whole cycle; smartphones in India have moved from rapid growth to near maturity, while EVs and quick commerce are in earlier stages.
6. Strategic groups and competitor analysis
Strategic groups are sets of firms following similar strategies within an industry (premium vs budget; full service vs low cost). Rivalry is strongest within a group, and mobility barriers limit movement between groups. Map groups on two axes such as price and breadth of range.
Competitor analysis profiles rivals: strategy and goals, resources and capabilities, financial strength, likely moves, and weaknesses. Tools: SWOT, the value chain, benchmarking of cost, quality and service, VRIO (valuable, rare, costly to imitate, organised to exploit) for sustained advantage, and key success factors (what must be done well to win).
7. Market sizing and forecasting
| Approach | How | Example |
|---|---|---|
| Top-down | Start with a large known market and apply filters | India’s population × share who are online × share who shop online |
| Bottom-up | Build from units × price × customers | Number of outlets × average sales per outlet |
| Analogue | Use a similar market’s trajectory | Compare a new product with the early path of a similar one |
Forecast growth through CAGR = (End value ÷ Start value)^(1/years) − 1. Example: an industry growing from ₹100 crore to ₹200 crore in 5 years has CAGR = 2^(0.2) − 1 ≈ 14.9%. Use time-series trend and seasonality, regression on drivers (income, price, penetration), scenarios and expert judgement. Always show ranges, since the future is uncertain.
8. Data sources and analytical tools
| Source | Examples |
|---|---|
| Government and regulators | Ministries, RBI, SEBI, TRAI, Census, Annual Survey of Industries, CCI orders |
| Industry bodies and agencies | NASSCOM, SIAM, CII, FICCI, IBEF, CMIE, ratings agencies |
| Company filings | Annual reports, investor presentations, exchange disclosures |
| Commercial data and news | Market research reports, financial data providers, business press |
| Primary research | Surveys, expert interviews, channel checks |
| Digital data | Web traffic, app downloads, search trends, social listening |
Analytics tools: spreadsheets, BI dashboards, SQL, Python or R for modelling, and ratio analysis across firms (growth, margin, ROCE, leverage). Benchmarking compares each firm with industry medians and best performers. Cross-check numbers across sources, since definitions and years differ.
In the real world: an analyst studying Indian IT services would combine industry-body revenue data, listed company reports (revenue growth, margins, attrition, headcount), client concentration and macro factors such as technology spending. A start-up scanning its sector uses web and app data to see competitor traction.
One-minute recap
| Topic | Key idea | Where you meet it |
|---|---|---|
| Scoping | Define by product, geography, customer | Market reports |
| Concentration | CR4 and HHI; barriers to entry | Merger reviews |
| Five Forces | Rivalry, entrants, substitutes, buyers, suppliers | Industry attractiveness |
| PESTLE and scenarios | Macro drivers; future cases | Policy-led sectors |
| Life cycle | Introduction to decline; disruption | Timing of entry and exit |
| Strategic groups | Similar strategies cluster; mobility barriers | Competitor maps |
| Sizing and forecasts | TAM top-down and bottom-up; CAGR | Business cases |
| Data and tools | Government, filings, BI, benchmarking | Analyst work |
Next in MBA Revisited: Marketing Research.
Written by Claude, Anthropic’s AI assistant, as part of MBA Revisited, a quick refresher of the PGDM subjects one at a time.