Feasibility Analysis and Venture Decision-Making

Introduction

Entrepreneurial opportunity recognition is only the beginning of venture creation. An idea becomes a responsible investment proposal when evidence indicates that customers value the proposed solution, the venture can deliver it, the organization can operate it, and the expected benefits justify the risks. Feasibility analysis is the disciplined process of testing these claims before substantial resources are committed.

Feasibility is not the same as certainty. New ventures operate with incomplete information, changing markets and uncertain behaviour. The purpose of analysis is therefore not to eliminate uncertainty but to reduce avoidable uncertainty, expose critical assumptions and establish whether the next step should be to proceed, revise, investigate further or stop. A well-designed feasibility study protects scarce financial and human resources while improving the quality of entrepreneurial judgment.

This chapter presents an integrated approach to product, market, technical, operational, organizational, financial and legal feasibility. It combines SWOT, PESTLE, Porter’s Five Forces, risk analysis, assumption testing and evidence-based go/no-go criteria.

Learning Objectives

By the end of this chapter, students should be able to:

1. Explain the purpose, scope and limitations of feasibility analysis.
2. Assess product, market, technical, operational, organizational, financial and legal feasibility.
3. Apply SWOT, PESTLE and Porter’s Five Forces appropriately.
4. Identify assumptions, rank risks and design tests that produce useful evidence.
5. Use basic financial measures, including break-even analysis and contribution margin, in venture decisions.
6. Construct evidence-based go/no-go, pivot or investigate-further recommendations.
7. Recognize ethical, regulatory, data-governance and sustainability issues in feasibility decisions.

1. Feasibility as an Evidence-Based Decision Process

A feasibility study asks whether a proposed venture is sufficiently desirable, viable and executable under specified conditions. It differs from a business plan. A business plan often explains how the venture will operate and grow; a feasibility study first examines whether the underlying opportunity deserves that planning effort.

A useful feasibility logic is:

Opportunity → assumptions → tests → evidence → decision → learning

An opportunity typically contains several connected claims:

• Desirability: a sufficiently important customer problem exists.
• Value proposition: the proposed solution provides meaningful benefits.
• Market attractiveness: enough customers can be reached at an acceptable cost.
• Technical feasibility: the product or service can be created reliably.
• Operational feasibility: processes, suppliers and service systems can support delivery.
• Organizational feasibility: the founding team can acquire the capabilities it lacks.
• Financial feasibility: revenues, costs, funding and cash flow can support survival.
• Legal and ethical feasibility: the venture can operate lawfully and responsibly.

These dimensions are interdependent. For example, a technically excellent product may fail because customers will not pay enough to cover production costs. A profitable-looking model may be infeasible if a required licence cannot be obtained. Consequently, feasibility should be analysed as a system rather than as a collection of isolated checklists.

Feasibility, viability and desirability

Desirability concerns whether customers want the solution. Feasibility concerns whether the venture can deliver it. Viability concerns whether the economic model can sustain the venture. These questions overlap but should not be confused. Customer enthusiasm is evidence of desirability, not proof of a viable business.

Levels of evidence

Evidence may be classified as:

Evidence quality depends on relevance, reliability, recency, independence and the method used to collect it. Ten enthusiastic interviews from a narrowly selected sample may be less informative than a smaller but more representative test.

2. Defining the Venture and Its Critical Assumptions

Before testing feasibility, the entrepreneur should define the proposed venture precisely. A useful opportunity statement identifies the target customer, problem, proposed solution, delivery channel and expected economic exchange.

For example: “A subscription service will provide verified low-cost bicycle maintenance to university students within 48 hours through campus collection points.” This is more testable than “We will revolutionize mobility.”

Assumption mapping

An assumption is a belief treated as true for planning purposes. Common assumptions include:

• a particular customer segment experiences the problem frequently;
• customers will pay a stated price;
• a supplier can deliver required inputs at a specified cost;
• the product can meet performance and safety standards;
• customer acquisition cost will remain below a defined limit;
• a founder or employee can perform a critical activity;
• a regulation will permit the proposed operating model.

The most dangerous assumptions are not necessarily the most uncertain; they are the assumptions whose failure would seriously damage the venture. A practical prioritization score is:

Here, Impact is the consequence of assumption failure, and Uncertainty is the current lack of reliable evidence. If each is rated from 1 to 5, a score of 20 or 25 indicates an assumption that deserves early testing. The score is a managerial prioritization device, not a probability calculation.

A test should be designed around a decision rule. For example, “Proceed with a paid pilot if at least 8 of 20 qualified customers pay a deposit and at least 70% complete the first transaction.” The rule should be established before results are observed to reduce confirmation bias.

3. Product and Customer Feasibility

Product feasibility examines whether the proposed offering solves a sufficiently important problem and can deliver benefits that customers recognize. It includes product functionality, quality, usability, safety, accessibility and the fit between the solution and the customer’s work or lifestyle.

Problem–solution fit

The entrepreneur should investigate:

1. Who experiences the problem?
2. How often and how severely does it occur?
3. What alternatives are currently used?
4. What costs, risks or frustrations do those alternatives create?
5. What would cause a customer to switch?
6. Who makes the purchase decision, and who uses the product?

Interviews should focus on past behaviour rather than hypothetical praise. “Tell me about the last time you faced this problem” is generally more informative than “Would you buy this idea?” A minimum viable product (MVP) should test the riskiest value proposition with the fewest resources, not merely provide an incomplete version of every feature.

Product feasibility also requires attention to product–market fit. Useful early indicators may include repeat purchase, retention, referrals, task completion, complaint rates and willingness to pay. A high number of downloads without continued use is weak evidence of product value.

Market size and segmentation

Market size should be stated in operational terms. Total addressable market (TAM) is the broadest potential demand; serviceable available market (SAM) is the portion accessible through the proposed geography, technology and channel; serviceable obtainable market (SOM) is the realistically attainable share during a defined period.

A top-down estimate begins with an industry total and applies filters. A bottom-up estimate is often more useful for a start-up:

The variables must refer to the same period and customer population. If 10,000 target customers each make 3 purchases per year at $40, annual revenue potential is $1,200,000. This is potential revenue, not a forecast, because it assumes all identified customers can be reached and will purchase.

Segmentation should be based on meaningful differences in needs, purchasing behaviour, access, regulation or willingness to pay. A segment described only by age or location may be too broad to guide a marketing decision.

4. External Analysis: PESTLE, SWOT and Five Forces

PESTLE analysis

PESTLE examines external conditions:

• Political: public policy, trade rules, political stability and public procurement.
• Economic: inflation, interest rates, income, employment, exchange rates and credit availability.
• Social: demographics, lifestyles, cultural values, trust and consumption patterns.
• Technological: infrastructure, innovation, cybersecurity, standards and technology substitution.
• Legal: licensing, employment, competition, consumer protection, intellectual property and data regulation.
• Environmental: climate exposure, resource use, pollution, waste and sustainability expectations.

PESTLE is a scanning framework rather than a prediction tool. It should identify developments that may alter assumptions, not produce a long list of unrelated trends. Each factor should be linked to an implication, such as “new packaging regulation may increase unit cost” or “falling mobile-data prices may improve service accessibility.”

SWOT analysis

SWOT combines internal and external considerations:

SWOT is most useful when evidence supports each item and when the analysis leads to action. “Strong brand” is not a strength unless customers recognize it or it produces measurable advantage. The framework should not be used as a substitute for market research or financial analysis.

Porter’s Five Forces

Porter’s framework evaluates industry structure:

1. Rivalry among existing competitors: price competition, differentiation, capacity and switching costs.
2. Threat of new entrants: capital needs, regulation, scale economies, brand loyalty and access to channels.
3. Bargaining power of suppliers: supplier concentration, uniqueness of inputs and switching costs.
4. Bargaining power of buyers: buyer concentration, price sensitivity, alternatives and switching costs.
5. Threat of substitutes: different products or behaviours that satisfy the same need.

The framework helps explain potential industry profitability, but it is not a complete analysis of a particular start-up. Complementors, ecosystems, platform effects and rapid technological change may also matter. A small venture should ask not only whether the industry is attractive but whether it has a defensible position within it.

5. Technical, Operational and Organizational Feasibility

Technical feasibility

Technical analysis asks whether the solution can be built, integrated, maintained and scaled at acceptable performance, cost and risk. Key questions include:

• Are required technologies mature enough?
• Can prototypes meet functional, safety and reliability requirements?
• Are components, data or APIs available under acceptable terms?
• Can the venture protect or lawfully use relevant intellectual property?
• What cybersecurity, privacy, interoperability and maintenance requirements apply?

Technical feasibility should distinguish a demonstration from a production-ready system. A prototype may work under controlled conditions while failing under realistic load, environmental variation or user error. Testing should define measurable acceptance criteria, such as response time, defect rate, battery life or service availability.

Operational feasibility

Operational feasibility concerns the repeatable delivery of the value proposition. It includes procurement, production, inventory, quality control, logistics, customer support, payment processing and information flows.

Process mapping can reveal bottlenecks and hidden dependencies. For a service, the map may begin with customer acquisition and end with renewal or referral. For a physical product, it may include design, sourcing, manufacturing, inspection, storage, distribution, returns and disposal.

Capacity must be considered. If a process has several sequential stages, the stage with the lowest effective capacity can constrain the entire system. Outsourcing may reduce fixed investment but introduce supplier dependence, quality risk and loss of control.

Organizational feasibility

Organizational feasibility evaluates whether the team has the skills, time, governance and relationships required to execute. A capable team does not need to possess every skill internally, but it must identify gaps and credible remedies. These may include hiring, partnerships, advisory support, training or specialist contractors.

Important issues include founder role clarity, decision rights, conflict management, incentives, succession, culture and ethical leadership. Investors and employees may view unacknowledged skill gaps more negatively than acknowledged gaps accompanied by a realistic plan.

6. Financial Feasibility

Financial feasibility translates operating assumptions into revenue, cost, cash and funding requirements. It should use scenarios rather than a single precise forecast.

Revenue, variable cost and contribution

A basic unit model uses:

Contribution is the amount available to cover fixed costs and profit. If price is $50 and variable cost is $30, contribution per unit is $20.

The contribution margin ratio is:

In the example, the ratio is $20 ÷ $50 = 0.40, or 40%. The measure is meaningful only when price and variable cost are defined consistently and variable costs change approximately in proportion to volume.

Break-even analysis

If fixed costs are constant over the relevant operating range, break-even volume is:

Suppose fixed costs are $60,000 per year, price is $50 and variable cost is $30. Break-even volume is $60,000 ÷ $20 = 3,000 units. Break-even revenue is:

Thus, break-even revenue is $60,000 ÷ 0.40 = $150,000.

These formulas assume one principal product, a stable selling price, a constant variable cost per unit, and fixed costs that do not change within the relevant range. They do not account for taxes, financing costs, capacity constraints, inventory timing or multiple products with changing sales mix. A venture should therefore treat break-even as a sensitivity tool, not as a complete financial forecast.

Cash flow and runway

Profit and cash are different. A venture may report accounting revenue while cash is delayed, or may incur cash expenditure before revenue is recognized. Cash-flow analysis should identify timing of receipts, wages, rent, inventory, taxes, debt payments and capital expenditure.

A simple runway estimate is:

If available cash is $120,000 and average monthly net cash burn is $20,000, runway is 6 months. This estimate is unreliable if burn varies significantly; in that case, a month-by-month cash budget is preferable.

Scenario and sensitivity analysis

A scenario changes several connected assumptions coherently, such as a recession scenario with lower demand, delayed payment and higher financing costs. Sensitivity analysis changes one assumption while holding others constant, such as examining the effect of price changes on break-even volume. Both approaches help reveal which assumptions deserve testing.

Risk-adjusted evaluation may use expected monetary value:

Here, pᵢ is the probability assigned to outcome i, Vᵢ is the monetary value of that outcome, and the probabilities must sum to 1. For example, a project with a 0.6 probability of a $100,000 gain and a 0.4 probability of a $40,000 loss has expected monetary value of (0.6 × $100,000) + (0.4 × −$40,000) = $44,000. Expected value does not capture risk attitude, liquidity constraints or the possibility of catastrophic loss, so it should not be used mechanically.

7. Legal, Ethical and Sustainability Feasibility

Legal feasibility should be assessed early, especially in regulated sectors. Relevant areas may include business registration, permits, tax, employment law, consumer protection, advertising, product safety, intellectual property, competition law, privacy, data retention, accessibility and sector-specific licensing.

Legal advice is often necessary because a general checklist cannot determine how a rule applies to a particular business model. Entrepreneurs should document ownership of code, designs, content, customer data and inventions. They should also verify contractual rights when using contractors, platforms, open-source software or third-party datasets.

Ethical feasibility goes beyond legal compliance. A legal practice may still be misleading, discriminatory, exploitative or environmentally harmful. Questions include:

• Does the product create foreseeable harm or exclusion?
• Are claims transparent and evidence-based?
• Is consent meaningful when personal data are collected?
• Are workers and suppliers treated fairly?
• Are environmental costs shifted to communities or future generations?

Technology and AI can improve forecasting, market research and operational efficiency, but they introduce risks involving biased data, opaque decisions, privacy, intellectual property and fabricated outputs. AI-generated analysis should be verified against primary evidence, and sensitive information should not be entered into tools without appropriate governance.

8. Risk Analysis and Testing Strategy

Risk is the possibility that an uncertain event affects objectives. A risk register commonly records the risk, cause, consequence, likelihood, impact, owner, response and review date.

A qualitative risk matrix can classify risks as low, medium or high. Quantitative estimates may use probability and impact, but numerical scores can create false precision. A rare safety event with severe consequences may deserve priority even if its probability is difficult to estimate.

Typical responses are:

• Avoid: change the plan so the risk no longer applies.
• Reduce: lower likelihood or impact through controls and testing.
• Transfer: use insurance, contracts or specialist providers.
• Accept: monitor the risk when treatment costs exceed expected benefit.
• Exploit or enhance: in opportunity risk, increase the likelihood or benefit of a favourable event.

Designing useful experiments

A strong experiment has a clear hypothesis, target population, method, metric, duration and decision rule. Examples include:

• customer interviews for problem frequency;
• landing-page tests for message and click-through interest;
• pre-orders for willingness to pay;
• concierge delivery for service demand and process effort;
• technical prototypes for performance;
• supplier quotations for cost and lead time;
• paid pilots for retention and operational reliability.

Experiments must avoid common biases. A landing-page click is not equivalent to a purchase. Friends and family may provide encouragement rather than representative demand. Survey respondents may overstate intentions. A test should measure behaviour as close as possible to the actual business model.

9. Evidence-Based Venture Decisions

A decision should be tied to explicit criteria rather than enthusiasm or sunk costs. Possible criteria include:

A decision memo should state the opportunity, evidence collected, assumptions tested, unresolved issues, alternatives considered, resource request, decision rule and next review date. It should distinguish facts, estimates and judgments.

A no-go decision is not necessarily entrepreneurial failure. Stopping early can preserve capital and reveal knowledge that supports a later opportunity. Similarly, a go decision is authorization for the next learning stage, not proof that the venture will succeed.

Applied Case: GreenBox Campus Meals

The following is a fictional illustrative case.

Background

Two university graduates propose GreenBox, a reusable-container service for takeaway meals sold near a university campus. Customers pay a small deposit for a container, return it to collection points and receive credit toward future purchases. The founders believe the service can reduce single-use packaging and help restaurants meet sustainability expectations.

Problem and assumptions

The critical assumptions are that students care enough about packaging waste to change behaviour, participating restaurants will accept an operational process, containers can be sanitized economically, and return rates will be high enough to control replacement cost.

Analysis

Product feasibility: Interviews with 30 students show strong concern about waste, but only 9 report having changed purchasing behaviour because of packaging. A prototype container is convenient, but some students dislike carrying it after eating.

Market feasibility: The immediate segment is students buying takeaway meals at five nearby restaurants. The founders estimate 2,000 potential weekly transactions, but they have not yet established how many customers are repeat users. A two-week paid pilot is more informative than a general survey.

Technical and operational feasibility: A sanitation partner confirms that washing is possible, but quotes a cost of $0.35 per cycle. The proposed customer charge is $0.50 per transaction. The founders must include collection, loss, labour and payment costs before claiming viability. They also discover that containers need standardized labels and food-safety procedures.

Five Forces: Restaurants have moderate buyer power because they can choose disposable packaging or another provider. Suppliers of standardized containers have moderate power. Substitutes are cheap and convenient disposable containers. GreenBox may create differentiation through measurable waste reduction, but the advantage is not yet defensible.

Legal and ethical feasibility: Food-contact safety, sanitation records, consumer disclosures and waste claims require review. The venture should not advertise “zero waste” unless the claim is supported by measured evidence.

Financial feasibility: Assume a $0.50 service fee, $0.35 washing cost, $0.04 payment cost and $0.03 average loss allocation per transaction. Contribution per transaction is:

$0.50 − ($0.35 + $0.04 + $0.03) = $0.08.

If monthly fixed costs are $2,400, break-even volume is $2,400 ÷ $0.08 = 30,000 transactions per month. This is far above the initial pilot scale. The founders should investigate whether restaurant subscriptions, sponsorship or a higher fee can improve the model.

Approach and decision

The founders should run a paid pilot with two restaurants, 200 customers and clear measures: return rate, repeat use, loss rate, washing cost, restaurant satisfaction, customer complaints and contribution per transaction. A pre-agreed condition is that the pilot must achieve a return rate of at least 85%, repeat use by at least 30% of first-time users and a pathway to contribution of at least $0.20 per transaction.

The evidence does not justify a full launch. The appropriate decision is investigate further with a controlled pilot, not immediate go and not yet no-go.

Learning points

The case demonstrates that environmental enthusiasm is not equivalent to demand, a prototype is not an operating system, and positive unit economics must be assessed with all variable costs included. It also shows how legal claims, customer behaviour and operational design interact with financial feasibility.

Challenges and Limitations of Feasibility Analysis

Feasibility analysis has unavoidable limitations. Forecasts may be based on small samples, competitors may respond strategically, and external conditions may change before launch. Entrepreneurs may also suffer from confirmation bias, overconfidence, anchoring on an attractive market estimate and escalation of commitment after investing time or money.

Frameworks can create an illusion of completeness. SWOT may simplify complex relationships; Five Forces may understate platform dynamics; break-even analysis may conceal cash timing; and probability estimates may be subjective. The remedy is not to abandon frameworks but to make assumptions visible, triangulate evidence, use ranges and revisit conclusions.

A further limitation is ethical: collecting data through experiments can affect customers, workers or communities. Participants should not be deceived unnecessarily, personal data should be protected, and pilot users should understand material risks. Responsible entrepreneurship treats feasibility as a question of whether value can be created without unacceptable harm.

Best-Practice Checklist

A high-quality feasibility study should:

• define the customer, problem and proposed exchange clearly;
• identify the few assumptions whose failure would be fatal;
• use primary and secondary evidence appropriately;
• test behaviour and willingness to pay, not only opinions;
• assess the entire operating process;
• include realistic variable costs, cash timing and funding needs;
• examine legal, ethical, environmental and data risks early;
• use scenarios and sensitivity analysis;
• document decision rules before reviewing test results;
• separate evidence, assumptions and judgments;
• assign owners and dates to unresolved risks;
• recommend go, conditional go, pivot, investigate or no-go with reasons.

Chapter Summary

Feasibility analysis is a structured method for deciding whether an entrepreneurial opportunity merits further investment. It examines desirability, market attractiveness, technical and operational capability, organizational readiness, financial performance, legal compliance and ethical responsibility. SWOT, PESTLE and Five Forces organize strategic analysis, but they are most useful when linked to specific evidence and decisions.

Entrepreneurs should identify critical assumptions, prioritize those with high impact and uncertainty, and test them through interviews, prototypes, paid pilots, supplier research and operating experiments. Financial tools such as contribution margin, break-even analysis, cash runway, scenario analysis and expected monetary value clarify economic conditions, while their assumptions and limitations must be recognized. Evidence-based decisions may lead to a go, conditional go, pivot, further investigation or no-go. The central professional skill is not predicting the future with certainty, but learning quickly and responsibly before committing scarce resources.

Key Terms

Feasibility analysis: Systematic assessment of whether an opportunity can be pursued successfully and responsibly.

Desirability: The extent to which customers value and want a proposed solution.

Viability: The extent to which a venture can generate sustainable economic value.

Critical assumption: A belief whose failure would materially threaten the venture.

Minimum viable product (MVP): The simplest offering capable of testing a critical value proposition.

Total addressable market (TAM): The broadest potential demand for an offering.

Serviceable available market (SAM): The portion of TAM that the venture can serve given its model and reach.

Serviceable obtainable market (SOM): The realistically attainable portion of SAM within a specified period.

PESTLE: Framework for analysing political, economic, social, technological, legal and environmental factors.

SWOT: Framework covering strengths, weaknesses, opportunities and threats.

Five Forces: Industry analysis of rivalry, entrants, suppliers, buyers and substitutes.

Contribution: Selling price minus variable cost per unit.

Contribution margin ratio: Contribution divided by selling price.

Break-even point: Volume or revenue at which total contribution equals fixed costs.

Cash burn: Net cash outflow over a period.

Runway: Time a venture can continue before available cash is exhausted at a stated burn rate.

Risk register: Document recording risks, consequences, owners and responses.

Sensitivity analysis: Examination of how a result changes when one assumption changes.

Go/no-go criterion: Predefined evidence threshold guiding a venture decision.

Due diligence: Investigation undertaken to verify claims, obligations, risks and ownership.

Review Questions

Short Answer Questions

1. What is the difference between feasibility, desirability and viability?
2. Why should entrepreneurs test assumptions rather than merely describe them?
3. What are the six dimensions of PESTLE analysis?
4. Define contribution per unit and explain its role in break-even analysis.
5. Why is a paid pilot generally stronger evidence than a statement of interest?

Long Answer Questions

1. Explain how product, market, technical, operational and organizational feasibility interact in a new venture.
2. Compare SWOT, PESTLE and Porter’s Five Forces, including the different questions each framework addresses.
3. Discuss the assumptions and limitations of break-even analysis in a multi-product venture.
4. Explain how legal and ethical feasibility can influence the design of a business model.
5. Describe a rigorous process for moving from opportunity recognition to an evidence-based go/no-go decision.

Analytical / Application Questions

1. A venture sells a service for $80 per customer, incurs variable costs of $50 per customer and has monthly fixed costs of $18,000. Calculate contribution per customer and monthly break-even volume. State the assumptions behind your calculation.
2. Select a proposed venture and construct an assumption map containing five assumptions. Rank them by impact and uncertainty, then design one test for the highest-priority assumption.
3. A start-up has strong customer interview results but no repeat purchases, a technically incomplete prototype and a cash runway of three months. Recommend go, conditional go, pivot, investigate further or no-go, and justify your decision using at least three feasibility dimensions.

Multiple Choice Questions with Answers

Question 1

Which statement best describes the purpose of feasibility analysis?

A. To guarantee that a new venture will succeed

B. To eliminate all uncertainty before launch

C. To test whether an opportunity merits further resource commitment

D. To replace all operational planning after launch

Correct Answer: C. To test whether an opportunity merits further resource commitment

Question 2

A product sells for $50 and has a variable cost of $30 per unit. What is the contribution per unit?

A. $20

B. $30

C. $50

D. $80

Correct Answer: A. $20

Question 3

Which PESTLE category includes privacy regulation and product-safety law?

A. Political

B. Legal

C. Social

D. Environmental

Correct Answer: B. Legal

Question 4

Which is generally the strongest early evidence of actual customer demand?

A. A founder’s personal belief

B. A favourable opinion from a friend

C. A customer’s paid pre-order

D. A broad industry slogan

Correct Answer: C. A customer’s paid pre-order

Question 5

In Porter’s Five Forces, an alternative technology that satisfies the same customer need is a:

A. Supplier

B. Substitute

C. New entrant

D. Complementor

Correct Answer: B. Substitute

Question 6

If fixed costs are $60,000 and contribution per unit is $20, what is break-even volume?

A. 1,200 units

B. 2,000 units

C. 3,000 units

D. 4,000 units

Correct Answer: C. 3,000 units

Question 7

Which decision is most appropriate when the problem is real but the proposed customer segment or solution is not working?

A. Pivot

B. Immediate full launch

C. Ignore the evidence

D. Increase fixed costs

Correct Answer: A. Pivot

Question 8

What does a risk register primarily document?

A. Only the venture’s advertising budget

B. Risks, consequences, owners and responses

C. Only competitor logos

D. Personal preferences of the founders

Correct Answer: B. Risks, consequences, owners and responses

Question 9

A venture has $120,000 available cash and average monthly net cash burn of $20,000. Its simple estimated runway is:

A. 3 months

B. 6 months

C. 12 months

D. 20 months

Correct Answer: B. 6 months

Question 10

Which statement about SWOT is most accurate?

A. It proves that a market is profitable

B. It combines internal strengths and weaknesses with external opportunities and threats

C. It replaces customer research

D. It is limited to financial variables

Correct Answer: B. It combines internal strengths and weaknesses with external opportunities and threats