Definition (simple)
– Blue ocean: a market space that is new or little contested, where a firm can offer something novel and face little direct competition.
– Red ocean: an established, crowded market where firms fiercely compete for existing customers (often by price or incremental improvements).
Key idea in one line
– Blue-ocean strategy is about creating or finding a market where competition is minimal so a firm can grow profits and set its own rules rather than fight rivals for share.
How a blue ocean works (what it gives you)
– First-mover advantages: being first into an uncontested market can let a company shape customer expectations and standards.
– Pricing and margin flexibility: with little direct competition, a firm can often set prices more freely.
– Marketing efficiency: fewer rivals means less advertising waste directed at stealing share.
– Strategic freedom: the firm can experiment with product, distribution, and business model without immediate benchmarking to competitors.
Contrast with a red ocean
– In red oceans companies mostly compete for the same customers using price cuts, feature improvements, or promotions. Blue oceans require creating demand rather than fighting over it.
Examples (short summaries)
– Ford (Model T): In the early 1900s, Ford introduced a standardized, mass-produced car at much lower cost than the many small makers offering custom-built autos. That repositioned the car from a luxury/novelty item to mass transportation.
– Apple (iTunes): In 2003 Apple created a legal, easy-to-use marketplace for single-song downloads. That offered a convenient paid alternative to widespread piracy and opened a new revenue stream for music producers and Apple.
– Netflix: Instead of joining the crowded video-rental market, Netflix first offered mail-order rentals and later became one of the first major subscription streaming services — initially a new model rather than a direct head-to-head with rental chains.
Worked numeric example (using figures from the Ford case)
– Data: Model T market share rose from 9% in 1908 to 61% in 1921 (13 years).
– Rough compound annual growth rate (CAGR) of market share = (Ending/Beginning)^(1/years) − 1 = (61/9)^(1/13) − 1.
– Calculation: 61/9 ≈ 6.7778; 6.7778^(1/13) ≈ 1.1584 → CAGR ≈ 0.1584 or about 15.8% per year.
– Interpretation: Under a simple exponential model, the Model T’s share increased at roughly 15.8% per year—illustrating how a
illustrating how a simple exponential model can approximate adoption over a limited interval but breaks down as limits (market saturation, capacity, regulation) appear. In other words, the CAGR number is useful for back-of-envelope comparisons but should not be treated as a mechanistic forecast for long periods.
Key limitations of the CAGR market-share approach
– Ignores saturation. Market share cannot grow indefinitely; it is bounded by 100% and often by a much lower practical ceiling.
– Omits competition dynamics. New entrants, incumbent responses (price cuts, innovation), and regulatory changes can materially change the path.
– Assumes smooth growth. Real market adoption often follows an S‑curve (logistic growth) with slow start, rapid adoption, then slowdown—not pure exponential.
– Neglects cost structure and profitability. Share gains can be unprofitable if achieved via unsustainably low prices or high acquisition costs.
– Data quality and definition issues. “Market” must be defined consistently (by revenue, units, geography, product scope).
Practical steps to analyze a potential “blue ocean” move (checklist)
1. Define the market precisely.
– Total Addressable Market (TAM): all potential demand for the category.
– Serviceable Available Market (SAM): portion you can reach with current channels.
– Serviceable Obtainable Market (SOM): realistic share you can capture in the near term.
2. Map value innovation.
– List features and attributes where you will increase value and where you will reduce or eliminate features to cut cost.
– Use a 2×2 canvas (value vs. cost) to show differentiation and lower cost.
3. Model adoption with boundaries.
– Select a growth form: logistic (S‑curve) is usually more realistic than exponential for long horizons.
– Calibrate parameters to historical analogues (e.g., Netflix vs. Blockbuster) or industry adoption benchmarks.
4. Build financials.
– Revenue = projected market size × expected share × price.
– Profitability = revenue − variable costs − fixed costs − customer acquisition costs.
– Compute simple break-even: Fixed Costs / (Unit Contribution Margin).
5. Run scenarios & sensitivity.
– Base, optimistic, and pessimistic cases for TAM growth, share attainment, price, and acquisition cost.
– Tornado or sensitivity table showing which assumptions most affect profit.
6. Validate with a pilot.
– Small market test to measure acquisition cost, churn, and unit economics before major roll-out.
7. Consider strategic risks.
– Potential for incumbents to imitate, regulatory barriers, supplier concentration, and technological obsolescence.
Worked numerical illustration (continuing Model T intuition)
– Given: Model T market share rose from 9% to 61% in 13 years → CAGR ≈ 15.8% (as shown earlier).
– What happens if you extend that CAGR 5 more years (pure exponential projection)? Share ≈ 61% × (1.1584)^5.
– Compute: (1.1584)^5 ≈ 2.09 → projected share ≈ 61% × 2.09 ≈ 127% (impossible).
– Lesson: Exponential extrapolation quickly violates physical constraints (share >100%). Instead use a logistic model:
– Logistic formula (simple form): S(t) = K / (1 + A·e^(−b·t))
– K = carrying capacity (max market share, ≤100%)
– b = growth rate
– A = (K − S0)/S0 where S0 is initial share
– Choose K based on economic/competitive judgment (e.g., 70% practical ceiling rather than 100%).
– Calibrate b to match observed early-period growth, then project to avoid impossible outcomes.
– Practical numeric example using logistic intuition:
– Suppose K = 80% (practical max), S0 = 9% at t0, and you calibrate b so S(13) ≈ 61%. Solve A = (K − S0)/S0; estimate b numerically. The exact algebra requires fitting; the point is logistic projects a slowing approach to K rather than unbounded growth.
How to use these analyses for strategic decision-making (actionable rules)
– Rule 1: Convert qualitative “blue ocean” claims into quantifiable assumptions (TAM, share, price, cost).
– Rule 2: Use bounded growth
– Rule 2: Use bounded growth assumptions (continued)
– Translate any “unlimited upside” claim into an explicit upper bound K (practical maximum share, percent of TAM). State whether K is theoretical (100%) or practical (e.g., 40–80%). Write K as the fraction (0–1) of the target market you expect the product can realistically obtain.
– Always show how revenues would look if the firm hits K, and how they look if it reaches only 25%, 50%, or 75% of K. That makes optimism explicit and testable.
– Rule 3: Calibrate early growth to infer speed b
– Use the logistic form S(t) = K / (1 + A e^{−b t}), where A = (K − S0)/S0, S0 is initial share at t = 0, and b is the growth-rate parameter (per time unit). This assumes growth starts exponential then slows as it approaches K.
– Practical calibration: pick two empirical points (S0 at t0 and S1 at t1) and solve for b numerically. Example (worked):
– Assume K = 80% (0.80), S0 = 9% (0.09) at t0 = 0, and S(13) ≈ 61% (0.61) at t = 13 months.
– Compute A = (K − S0)/S0 = (0.80 − 0.09)/0.09 = 7.8889.
– Solve 0.61 = 0.80 / (1 + 7.8889 e^{−13 b}) → 1 + 7.8889 e^{−13 b} = 0.80/0.61 = 1.31148.
– 7.8889 e^{−13 b} = 0.31148 → e^{−13 b} = 0.03950 → −13 b = ln(0.03950) = −3.2288 → b ≈ 0.248 per month.
– Project further: S(24) = 0.80 / (1 + 7.8889 e^{−0.248·24}) ≈ 78.4%. Interpretation: with this b, share climbs quickly toward K and then flattens.
– Assumptions: logistic shape, single market segment, no structural shocks. If supply constraints, multi-segment competition, network effects, or regulatory limits exist, modify the model.
– Rule 4: Convert share into cash—TAM → Revenue → Free cash flow
– Define TAM explicitly (total addressable market; annual $ value or units). Then compute:
– Revenue_t = S(t) × TAM_t (if TAM grows, model TAM_t separately).
– Gross profit_t = Revenue_t × Gross margin.
– Free cash flow_t ≈
+ Free cash flow_t ≈ NOPAT_t + Depreciation_t − CapEx_t − ΔNWC_t
Where:
– NOPAT_t (Net Operating Profit After Taxes) = Operating income_t × (1 − tax_rate)
– Operating income_t = Revenue_t × Operating margin_t
– Revenue_t = S(t) × TAM_t
– S(t) is the market share at time t (use the logistic S(t) you fitted)
– TAM_t is the total addressable market in dollars (or units × price) at time t
– ΔNWC_t = change in net working capital in period t (NWC_t − NWC_{t−1})
Step-by-step conversion (practical checklist)
1. Choose TAM definition and units
– Decide whether TAM_t is an annual dollar market (e.g., $/year) or units per year × price per unit.
– Document assumptions about TAM growth (e.g., TAM_t = TAM_0 × (1+g)^t).
2. Convert share to revenue
– Revenue_t = S(t) × TAM_t.
– If S(t) is monthly and TAM is annual, convert S to the relevant period (use average share across the year or end-of-year share depending on purpose).
3. Move from revenue to operating profit
– Gross profit_t = Revenue_t × Gross margin_t (gross margin = (Revenue − COGS)/Revenue).
– Operating income_t = Revenue_t × Operating margin_t (or Gross profit − operating expenses).
4. Compute NOPAT
– NOPAT_t = Operating income_t × (1 − tax_rate).
5. Add back non-cash charges and subtract investments
– FCF_t = NOPAT_t + Depreciation_t − CapEx_t − ΔNWC_t.
6. Repeat for each projection year/month and run scenarios.
Worked numeric example (continuing your logistic share result)
– From your previous model, S(24) ≈ 0.784 (78.4% share at month 24).
– Assume TAM_24 = $1,000,000,000 (annual market size at t=24).
Revenue_24 = 0.784 × $1,000,000,000 = $784,000,000.
– Assume:
• Gross margin = 60% (so gross profit = 0.60 × Revenue)
• Operating margin = 20% (so operating income = 0.20 × Revenue)
• Tax rate = 25%
• Depreciation_24 = $20,000,000
• CapEx_24 = $30,000,000
• ΔNWC_24 = $10,000,000
Calculations:
– Operating income_24 = 0.20 × $784,000,000 = $156,800,000
– NOPAT_24 = $156,800,000 × (1 − 0.25) = $117,600,000
– FCF_24 = $117,600,000 + $20,000,000 − $30,000,000 − $10,000,000 = $97,600,000
– Discount the cash flows to present value (PV). Define WACC (weighted average cost of capital) as the discount rate r you use for the firm’s enterprise cash flows.
Assumptions to continue from FCF_24 = $97,600,000
– Treat t = 24 as end of projection period (end of Year 2).
– WACC (r) = 10.0% (example assumption).
– Perpetual (terminal) growth rate (g) = 3.0% (conservative long‑run growth less than nominal GDP/inflation).
– We will use the Gordon (perpetuity) formula for terminal value.
Step A — compute FCF in the first year after the projection (FCF_25)
– FCF_25 = FCF_24 × (1 + g) = $97,600,000 × 1.03 = $100,528,000
Step B — compute terminal value at end of Year 2 (TV_2) using Gordon growth
– Formula: TV = FCF_next / (r − g)
– TV_2 = $100,528,000 / (0.10 − 0.03) = $100,528,000 / 0.07 = $1,436,114,286
Step C — enterprise value at end of Year 2 (EV_2)
– EV_2 = TV_2 + FCF_24 = $1,436,114,286 + $97,600,000 = $1,533,714,286
Step D — discount EV_2 and FCF_24 back to today (PV at t = 0)
– Discount factor for 2 years = (1 + r)^2 = 1.10^2 = 1.21
– PV_FCF24 = $97,600,000 / 1.21 = $80,661,157