Chapter 20: Financial and Quantitative Feasibility

Chapter 20: Financial and Quantitative Feasibility

Video: Financial Analysis in Cases: Situation Review, Modelling, and Sensitivity

Learning Objectives

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

• translate a strategic recommendation into financial and operational implications;

• identify the economic drivers behind a recommendation;

• distinguish incremental financial impact from existing business performance;

• develop clear and defensible assumptions;

• estimate Revenue, costs, profitability, investment, and cash-flow effects;

• select financial measures appropriate to the decision;

• calculate break-even points and identify performance thresholds;

• use scenario and sensitivity analysis to test uncertainty;

• recognise when the numbers require a strategy to be revised, staged, or rejected;

• communicate financial results in language that matters to decision makers.

Why This Matters

A strategy may be attractive.

• Customers may value it.

• Employees may support it.

• It may align with the organisation's capabilities.

• Competitors may struggle to copy it.

• It may score highest in the decision matrix.

The organisation must still determine whether the strategy is economically viable. A recommendation that produces Revenue but destroys margin is not necessarily attractive. A profitable project that creates an immediate cash shortage may not be feasible. A strategy with a positive expected return may still expose the organisation to unacceptable downside risk. Financial analysis provides an essential reality check. It helps answer:

• How much will the recommendation cost?

• When will the money be spent?

• Where will the Revenue or savings come from?

• When will the organisation realise the benefits?

• Does the recommendation improve profit?

• Can the organisation afford the required investment?

• What must be true for the recommendation to succeed?

• What happens if those assumptions are wrong?

• Is the expected value sufficient to justify the investment and risk?

For a CEO, board, investor, or senior executive, financial implications are not a separate section of the recommendation. They are part of the decision itself.

Discover Your MAD Skills Principle

Don’t just calculate the numbers. Use the numbers to make the decision.

The objective is not to produce the largest spreadsheet or use the most sophisticated financial formula. The objective is to understand whether the recommendation creates enough value, whether the organisation can afford it, and which financial assumptions must be managed during implementation.

Deciphering Case Characteristics

The depth and type of financial analysis must be appropriate to the case.

Growth Case

Focus on:

• market size;

• customer acquisition;

• pricing;

• volume;

• contribution margin;

• capacity requirements;

• scalability;

• timing of growth.

Cost-Reduction Case

Focus on:

• current cost base;

• addressable costs;

• implementation costs;

• one-time restructuring expenses;

• recurring savings;

• payback period;

• service or quality trade-offs.

Market-Entry Case

Focus on:

• addressable demand;

• entry investment;

• pricing and volume;

• customer acquisition costs;

• local operating expenses;

• time to break even;

• downside exposure.

New Product Case

Focus on:

• development cost;

• launch cost;

• expected adoption;

• price;

• variable cost;

• product cannibalisation;

• contribution margin;

• break-even volume.

Operational Case

Focus on:

• productivity;

• capacity;

• utilisation;

• throughput;

• waste;

• labour hours;

• cost per unit;

• service-level effects.

Nonprofit or Public-Sector Case

Financial feasibility still matters, but success may not be measured by profit. Consider:

• cost per beneficiary;

• funding requirements;

• budget sustainability;

• social return;

• programme reach;

• cost-effectiveness;

• resource allocation;

• long-term funding risk.

Don't force the same financial model into every case. Ask which numbers will help the decision-maker make the decision?

Start With the Economics of the Recommendation

Before opening a spreadsheet, describe how the recommendation is expected to create value. Ask:

• What changes because of this recommendation?

• What produces the financial benefit?

• What resources are required?

• When do the costs and benefits occur?

• What could prevent the expected value from being realised?

Most recommendations affect six areas.

Revenue

How will the recommendation change:

• customer volume;

• purchase frequency;

• price;

• average transaction value;

• retention;

• market share;

• product mix;

• new revenue streams?

Variable Costs

Which costs change with each unit sold or customer served? Examples include:

• materials;

• packaging;

• delivery;

• sales commissions;

• transaction fees;

• direct labour;

• customer support.

Fixed and Operating Costs

What recurring costs are required regardless of short-term volume? Examples include:

• salaries;

• rent;

• software;

• marketing;

• administration;

• maintenance;

• partnership fees.

Initial Investment

What must be spent before the organisation receives the benefits? Examples include:

• equipment;

• technology development;

• facilities;

• training;

• implementation support;

• market-entry costs;

• working capital.

Profit

What happens after the incremental Revenue and costs are combined? A recommendation that increases Revenue may still reduce profit if the cost of creating that Revenue is too high.

Cash Flow

When does the organisation spend and receive cash? A recommendation can be profitable over three years while still creating a serious cash shortage in the first year.

Build the Model Around the Decision

A useful case model should be:

• simple enough to explain;

• detailed enough to support the decision;

• transparent enough to challenge;

• flexible enough to test assumptions;

• connected directly to the recommendation.

A practical structure is: Baseline → Recommendation Drivers → Revenue & Benefits → Costs & Investment → Profit and Cash Flow → Decision Metrics → Sensitivity. This keeps the model focused on the choice rather than on producing disconnected calculations.

Establish the Baseline

You cannot measure impact without understanding what would happen in the absence of the recommendation. The baseline may be:

• current performance;

• projected performance under the status quo;

• performance under the next-best alternative;

• the cost of doing nothing.

This distinction is important. Suppose the organisation currently earns $5 million in annual profit. Your recommendation produces $5.5 million. The relevant benefit is not $5.5 million. It is the incremental $500,000 created by the recommendation. The basic question is: What changes compared with what would otherwise happen?

Focus on Incremental Impact

Include only Revenue, costs, investments, and savings that change because of the recommendation.

• Incremental Revenue: Revenue created or protected by the strategy.
• Incremental Costs: Costs incurred as a result of the strategy.
• Avoided Costs: Costs the organisation will no longer incur.
• Cannibalisation: Revenue or profit lost when a new product takes demand from an existing offering.
• Opportunity Cost: Value sacrificed by choosing this alternative instead of another use of the organisation's resources.
• Sunk Costs: Costs already incurred that cannot be recovered.

Sunk costs may provide context, but they should not determine whether a future investment is worthwhile.

The Assumption Chain

Every financial projection depends on assumptions. A strong model makes the logic chain visible. For a customer-based growth recommendation:

• Target customers → Awareness → Conversion → Active customers → Purchase frequency → Average transaction value → Revenue Then:
• Revenue → Variable costs → Contribution margin → Fixed costs → Operating profit Finally:
• Operating profit → Investment and working capital → Cash flow → Financial return

For example:

• 100,000 target customers;

• 20% reached through marketing;

• 10% conversion;

• 2,000 acquired customers;

• six annual purchases;

• $80 average transaction value.

Projected Revenue: 2,000 customers × 6 purchases × $80 = $960,000. This chain is more defensible than simply stating: "We expect approximately $1 million in new revenue." It shows where the result comes from and which assumptions matter.

Separate Facts, Estimates, and Assumptions

Not every input has the same level of confidence. A useful model distinguishes among:

Case Facts

Information directly provided in the case. Examples:

• current price;

• existing customer count;

• historical gross margin;

• available investment budget.

External Evidence

Information supported by credible research or benchmarks. Examples:

• industry conversion rates;

• average customer acquisition costs;

• market growth forecasts;

• competitor pricing.

Calculated Estimates

Values derived from available information. Examples:

• estimated market size;

• cost per customer;

• projected annual demand.

Assumptions

Inputs selected because reliable evidence is unavailable. Examples:

• expected adoption;

• future price;

• launch timing;

• retention improvement.

Label these clearly. An assumption is not a weakness if it is reasonable, transparent, and tested.

Use Units to Strengthen the Logic

Write the units beside each major input:

• customers;

• transactions per customer;

• dollars per transaction;

• dollars per unit;

• months;

• percentage conversion;

• labour hours.

Units help reveal modelling errors. For example: Customers × Transactions per customer × Dollars per transaction = Revenue. If the units don't logically produce the expected output, the formula may be wrong. This simple discipline can prevent major errors under time pressure in competition.

Revenue Is Not Value

Teams often focus on revenue because it appears impressive, but revenue alone doesn't indicate whether the recommendation creates financial value. Suppose a campaign produces $2 million in incremental revenue but requires:

• $1.2 million in variable costs;

• $500,000 in marketing;

• $400,000 in additional staffing.

The recommendation increases revenue while reducing profit by $100,000. Always follow Revenue through the economics of the recommendation. A simplified income structure is: Revenue – Variable Costs = Contribution Margin – Incremental Fixed Costs = Incremental Operating Profit. If the recommendation requires an upfront investment, include it in the cash-flow analysis.

Contribution Margin

Contribution margin shows how much Revenue remains after variable costs, covering fixed costs and contributing to profit.

• Contribution Margin = Revenue – Variable Costs
• Contribution Margin per Unit = Price per Unit – Variable Cost per Unit
• Contribution Margin Ratio = Contribution Margin ÷ Revenue

Suppose a meal-kit company charges $80 per order and incurs $52 in variable costs. Contribution Margin per Order = $80 – $52 = $28. Each additional order contributes $28 towards fixed costs and profit. This number can help teams evaluate:

• break-even volume;

• the value of customer growth;

• the effect of discounts;

• the impact of changing delivery costs;

• whether the business can scale profitably.

Profit Is Not Cash

Profit records economic performance. Cash flow shows when money enters and leaves the organisation. The difference matters when a recommendation requires:

• a large upfront investment;

• inventory purchases;

• long customer payment periods;

• delayed cost savings;

• substantial working capital;

• several years before benefits are realised.

A project can report an accounting profit while creating a near-term cash problem. Ask:

• When is the investment required?

• When does Revenue begin?

• When are suppliers paid?

• When do customers pay?

• Can the organisation fund the period before it breaks even?

• Does growth create additional working-capital needs?

Financial attractiveness doesn't guarantee financial affordability.

Useful Financial Measures

Choose the measures that help answer the decision. Don't calculate every available metric simply because you know how.

• Revenue Growth: Shows how Revenue changes over time. Useful when growth is central to the decision, but it should be paired with margin and profitability.
• Gross Margin: Shows how much Revenue remains after the direct cost of producing the product or service.
  • Gross Margin = Revenue – Cost of Goods Sold
  • Gross Margin Percentage = Gross Margin ÷ Revenue
• Contribution Margin: Shows how much each unit or sale contributes towards fixed costs and profit. Useful for pricing, growth, product, and break-even decisions.
• Operating Profit: Shows the profit generated after operating expenses. Useful when the recommendation affects both Revenue and the organisation's cost structure.
• Return on Investment: A simplified ROI calculation is:
  • ROI = (Financial Benefit – Investment Cost) ÷ Investment Cost
  • Because ROI can be defined in different ways, state exactly which benefits, costs, and time period you used.
• Payback Period: Shows how long it takes for cumulative cash benefits to recover the initial investment. A simplified version is:
  • Payback Period = Initial Investment ÷ Annual Net Cash Benefit
  • This simplified formula works only when annual cash benefits are reasonably stable. Otherwise, calculate the cumulative cash flow period by period. Payback is useful when liquidity, uncertainty, or speed of return matters. However, it ignores value created after payback and may ignore the time value of money.
• Net Present Value: NPV converts future cash flows into today's value using a discount rate.
  • NPV = Present Value of Future Cash Flows – Initial Investment
  • A positive NPV generally indicates that the project is expected to create value at the selected discount rate. NPV is useful when:
    • cash flows occur over several years;
    • alternatives have different timing;
    • the investment is material;
    • the time value of money matters.
• Internal Rate of Return: IRR is the discount rate at which the project's NPV equals zero. It can help compare investment returns, but it should be interpreted carefully when projects differ significantly in size, timing, or cash-flow patterns.
• Break-Even Point: Break-even analysis identifies the level of performance required to cover costs.
  • Break-Even Volume = Fixed Costs ÷ Contribution Margin per Unit 
  • Suppose a recommendation requires $280,000 in fixed investment and creates a $28 contribution margin per order. Break-Even Volume = $280,000 ÷ $28 = 10,000 orders

The strategic question becomes: Can the organisation realistically generate at least 10,000 incremental orders? That is much more useful than presenting the calculation alone. 

Select Metrics Based on the Decision

Decision	Particularly Useful Measures
Pricing	Contribution margin, volume response, break-even
New product	Development cost, contribution margin, break-even volume, NPV
Cost reduction	Recurring savings, implementation cost, payback, ROI
Market entry	Revenue, margin, customer acquisition cost, break-even, NPV
Capacity expansion	Utilisation, incremental volume, cash flow, payback, NPV
Technology investment	Productivity savings, implementation cost, payback, NPV
Social programme	Cost per beneficiary, reach, budget impact, social outcomes

The best metric is the one that clarifies the decision maker's concern.

Quantitative Feasibility Extends Beyond Finance

Not every feasibility question is expressed in dollars. Your recommendation may also depend on:

• production capacity;
• staffing requirements;
• employee hours;
• delivery capacity;
• facility space;
• inventory;
• customer-acquisition volume;
• implementation time;
• technology performance;
• service levels.

Suppose a recommendation requires 40,000 additional deliveries each year. The strategy is not feasible if the organisation's network can support only 15,000. Ask what physical or operational quantity must be available for the financial result to occur? The financial model and operating model should tell the same story.

Capacity and Constraint Checks

For each major recommendation, identify the limiting resource. Examples include:

• number of employees;
• available production hours;
• warehouse capacity;
• number of sales representatives;
• technology throughput;
• supplier capacity;
• available capital.

A simplified capacity calculation might be: Available Capacity = Employees × Productive Hours per Employee × Output per Hour. Then compare Required Capacity to Available Capacity. If required capacity exceeds what is available, the model must include:

• new hiring;
• overtime;
• equipment;
• outsourcing;
• process improvements;
• staged implementation.

Otherwise, the projected Revenue cannot be delivered.

Scenario Analysis

One forecast creates the impression that only one future is possible. Scenario analysis recognises that important assumptions may change. Develop three coherent scenarios:

• Downside Case: What happens if the important assumptions are worse than expected?
• Base Case: What happens under the team's most reasonable assumptions?
• Upside Case: What happens if performance is stronger than expected? A scenario should change a small set of related assumptions, not every number randomly. For example:

Assumption	Downside	Base	Upside
Customers acquired	1,400	2,000	2,600
Annual orders per customer	5	6	7
Average order value	$76	$80	$82
Variable cost per order	$55	$52	$50

The team can then compare:

• revenue;
• contribution margin;
• profit;
• cash requirement;
• payback period;
• break-even timing.

The objective is not to predict three futures. It is to understand how the decision performs across a reasonable range of conditions.

Sensitivity Analysis

Sensitivity analysis changes one important assumption at a time to see how much the result changes. Potential sensitivity variables include:

• customer adoption;
• conversion;
• retention;
• price;
• market growth;
• purchase frequency;
• customer acquisition cost;
• variable cost;
• implementation cost;
• launch timing;
• discount rate.

Focus on the variables that could materially change the decision.

The Critical Assumption Test

For each major assumption, ask:

1. How uncertain is it?
2. How much does it affect the result?
3. Can management influence it?
4. Can it be tested before full investment?
5. What threshold would make the recommendation unattractive?

The assumptions with both high uncertainty and high impact deserve the most attention.

Find the Decision Threshold

A particularly powerful analysis asks at what point does the recommendation cease to be attractive? Examples include:

• minimum customer adoption;
• minimum price;
• maximum acquisition cost;
• maximum implementation cost;
• minimum retention improvement;
• maximum launch delay;
• minimum annual savings.

Suppose the project creates value only if it acquires at least 1,650 customers. The team can compare that threshold with:

• current customer-acquisition performance;
• market research;
• pilot results;
• industry benchmarks.

This turns a forecast into a management decision. Instead of saying: "We predict 2,000 customers." Say: "The recommendation breaks even at 1,650 customers. Our base estimate is 2,000, providing a 21% margin above the break-even threshold." That is more informative and defensible.

Let the Numbers Change the Strategy

Financial analysis should not merely validate the strategy after it has been selected. It may show that the recommendation should be:

• revised;
• narrowed;
• repriced;
• delayed;
• piloted;
• implemented in stages;
• supported through a partnership;
• funded differently;
• rejected.

Suppose a full market entry offers the highest upside but requires $8 million in upfront investment before demand is proven. A regional pilot may generate less immediate value but require only $750,000 and provide evidence about adoption, retention, and unit economics. The numbers may therefore change the recommendation from: "Enter the market nationally." to: "Launch a regional pilot and expand only when customer adoption, contribution margin, and retention exceed predefined thresholds." The financial analysis has now improved the strategy.

Worked Example: Partnership-Led Market Entry

In Chapter 19, the regional meal-kit company selected a partnership-led pilot as its preferred market-entry alternative. The team now translates that recommendation into a simple financial model.

Base Assumptions

• Target customers reached: 25,000
• Conversion rate: 8%
• Customers acquired: 2,000
• Annual orders per customer: 6
• Average Revenue per order: $80
• Variable cost per order: $52
• Incremental annual fixed costs: $180,000
• Initial implementation investment: $280,000

Revenue

• 2,000 customers × 6 orders × $80 = $960,000

Variable Costs

• 12,000 orders × $52 = $624,000

Contribution Margin

• $960,000 – $624,000 = $336,000

Incremental Operating Profit

• $336,000 – $180,000 = $156,000

Simplified Payback

• If the annual cash benefit approximates $156,000:

$280,000 ÷ $156,000 = 1.79 years

• The investment would therefore be recovered in approximately 22 months, assuming performance remains stable.

Break-Even Customer Requirement

• Annual contribution per customer: 6 orders × ($80 – $52) = $168
• Customers required to cover annual fixed costs: $180,000 ÷ $168 = approximately 1,072 customers
• If the team also wants to recover the initial investment during the first year: ($180,000 + $280,000) ÷ $168 = approximately 2,739 customers

This distinction matters. The pilot may achieve annual operating break-even at approximately 1,072 customers but require longer to recover the initial investment.

Interpretation

The base case suggests that the pilot:

• generates positive operating profit;
• recovers its initial investment in under two years;
• requires substantially less capital than a fully owned market entry;
• remains dependent on customer acquisition and purchase frequency.

The team should therefore monitor:

• conversion rate;
• active customers;
• orders per customer;
• contribution margin per order;
• customer acquisition cost;
• cumulative cash flow.

The strategic recommendation is now more precise: "Proceed with the partnership-led pilot, with full expansion contingent on achieving at least 1,200 active customers, a minimum contribution margin of $28 per order, and a projected payback period below 24 months."

Connect the Model to Implementation

The most important assumptions should become implementation metrics and decision triggers.

Critical Assumption	Implementation Metric	Trigger
Customer demand	Active customers	Reassess if fewer than 1,200 are acquired
Purchase frequency	Orders per customer	Redesign offering if below five annually
Unit economics	Contribution per order	Reprice or reduce cost if below $28
Acquisition efficiency	Customer acquisition cost	Pause expansion if above threshold
Payback	Cumulative cash flow	Delay next phase if payback exceeds 24 months

This connection turns the model into a management tool. The numbers are no longer confined to a financial slide. They determine:

• when to invest;
• when to expand;
• when to modify the offering;
• when to pause;
• when to exit.

Financial Analysis Is Not the Final Recommendation

The option with the highest financial return is not automatically the best strategic choice. Decision makers may also need to consider:

• strategic fit;
• customer value;
• capability requirements;
• implementation feasibility;
• risk;
• stakeholder impact;
• ethics;
• flexibility;
• long-term competitive advantage.

Financial analysis is one part of an integrated decision. A slightly lower-return alternative may be preferable if it:

• requires substantially less capital;
• is easier to reverse;
• protects the organisation from downside risk;
• creates important learning;
• better fits existing capabilities;
• advances the organisation's mission;
• preserves future strategic options.

The financial model informs judgment. It doesn't replace it.

Winning the Room

Judges rarely need to see the entire financial model. Show the numbers that explain the decision:

• required investment;
• major revenue or savings drivers;
• expected profit or cash impact;
• break-even point;
• payback or return;
• most important assumption;
• downside exposure;
• decision threshold.

A strong financial explanation might sound like: "The pilot requires an initial investment of $280,000 and is expected to generate $156,000 in annual operating profit, producing payback in approximately 22 months. The most important assumption is customer adoption. The pilot reaches annual operating break-even at approximately 1,072 active customers, compared with our base estimate of 2,000. We recommend proceeding, but expansion should occur only if the pilot achieves at least 1,200 active customers and maintains a contribution margin of $28 per order." That tells the judges:

• what the recommendation costs;
• what it creates;
• what must be true;
• how uncertainty will be managed.

Coach's Lens

I often see teams present a beautifully formatted financial model and then fail to explain what it means. Don't stop at: "The project generates an NPV of $4.2 million." Explain the decision: "The project creates an estimated $4.2 million in value under our base assumptions. However, it becomes unattractive if customer adoption falls below 18%. We will therefore validate adoption through a six-month pilot before committing the remaining capital."

The first statement reports a calculation. The second shows judgment. A strong financial slide should answer three questions:

1. Is the recommendation financially attractive?
2. Can the organisation afford it?
3. What would have to go wrong for us to change the decision?

Common Mistakes

• Financial Analysis as an Afterthought: If the model is created only after the recommendation has been selected, it may become an exercise in justification.
• Starting With the Spreadsheet: Define the economic logic before building formulas.
• Unsupported Assumptions: Make every material assumption visible and explain its source.
• Confusing Revenue With Value: Revenue growth may produce little profit or negative cash flow.
• Ignoring Incremental Impact: Evaluate only the changes resulting from the recommendation, not the organisation's overall performance.
• Ignoring the Baseline: A recommendation may appear attractive until compared with what would happen without it.
• Ignoring Cannibalisation: New Revenue may replace existing Revenue rather than add to it.
• Confusing Profit With Cash: A profitable project may still create a funding problem.
• Ignoring Timing: Costs may be incurred immediately, while benefits take several years to materialise.
• Ignoring Capacity: The financial forecast is meaningless if the organisation cannot produce or deliver the projected volume.
• Double-Counting Benefits: Don't count the same revenue increase or cost saving more than once in the model.
• Mixing Units or Time Periods: Combining monthly Revenue with annual costs can lead to serious errors.
• False Precision: A forecast of $4,283,721 may imply more certainty than the assumptions support. Round appropriately.
• Calculating Everything: Use financial measures to inform the decision.
• One-Scenario Forecasting: A single forecast hides uncertainty.
• Sensitivity Without Implication: Don't merely show that results change. Explain when and why management should act.
• Hiding a Weak Result: If the recommendation doesn't create sufficient value, revise or reject it. Don't manipulate the assumptions.

MAD Skills Drill

Take the preferred alternative from Chapter 19.

Part One: Define the Baseline

What happens if the organisation doesn't pursue the recommendation?

Part Two: Build the Economic Logic

Identify:

• three revenue or benefit drivers;
• three cost drivers;
• the initial investment;
• the timing of costs and benefits;
• any operational capacity requirements.

Part Three: Build the Assumption Chain

Show how the recommendation moves from: Target Market or Activity → Adoption or Volume → Revenue or Savings → Costs → Profit → Cash Flow

Part Four: Calculate the Core Measures

Depending on the case, estimate:

• incremental Revenue;
• contribution margin;
• incremental operating profit;
• cash requirements;
• ROI;
• payback period;
• NPV;
• break-even volume.

Use only the measures relevant to the decision.

Part Five: Test Uncertainty

Identify:

• the three assumptions with the greatest uncertainty;
• the three assumptions with the greatest impact;
• the single assumption that could most easily change the decision.

Develop downside, base, and upside scenarios.

Part Six: Find the Threshold

Calculate the point at which the recommendation:

• breaks even;
• no longer meets the required return;
• exceeds the available budget;
• becomes operationally infeasible.

Part Seven: Convert the Model Into Action

Create:

• one implementation metric;
• one performance threshold;
• one trigger for expansion;
• one trigger for revision;
• one trigger for stopping the strategy.

Finally, answer whether the recommendation creates enough value to justify its investment, opportunity cost, and risk.

Reflection Questions

1. Which assumptions in your model came from the case?
2. Which assumptions were estimates?
3. Which assumption has the greatest influence on the result?
4. Did you compare the recommendation with a realistic baseline?
5. Did you include all incremental costs?
6. Could the organisation fund the recommendation before it reaches break-even?
7. Does the organisation have the operational capacity to deliver the projected results?
8. What would cause you to revise or abandon the strategy?
9. Did the financial analysis validate the recommendation or change it?
10. Can every team member explain the model without opening the spreadsheet?

Chapter Summary

Financial and quantitative analysis translates a strategic idea into its practical economic consequences. A useful analysis moves through: Baseline → Assumptions → Operational Drivers → Revenue & Benefits → Costs & Investment → Profit & Cash Flow → Financial Measures → Scenarios → Decision Thresholds. The goal is not to produce the most complicated model. It is to determine:

• whether the recommendation creates value;
• whether the organisation can afford it;
• whether it can be delivered operationally;
• which assumptions matter most;
• how uncertainty should influence implementation.

The strongest teams don't merely report a return. They explain what creates the return, what threatens it, and how management should respond if performance differs from expectations.

Key Takeaways

✓ Begin with the economic logic of the recommendation before building the model.

✓ Establish a baseline and focus on incremental financial impact.

✓ Make the assumption chain clear, transparent, and defensible.

✓ Distinguish case facts, external evidence, estimates, and assumptions.

✓ Follow Revenue through variable costs, contribution margin, fixed costs, profit, and cash flow.

✓ Remember that Revenue is not profit and profit is not cash.

✓ Match the financial measure to the decision rather than calculating everything.

✓ Test operational capacity as well as financial attractiveness.

✓ Use scenario analysis to evaluate coherent alternative futures.

✓ Use sensitivity analysis to identify the assumptions that matter most.

✓ Calculate thresholds that show what must be true for the recommendation to succeed.

✓ Allow financial analysis to validate, reshape, stage, or reject the strategy.

✓ Convert critical assumptions into implementation metrics and decision triggers.

✓ Explain what the numbers mean for the decision, not merely how they were calculated.

Looking Ahead

We now have:

• a clear understanding of the people affected;
• credible strategic alternatives;
• decision criteria for comparing them;
• a preferred alternative;
• a financial and quantitative test of its feasibility.

The next step is to transform the winning alternative into a coherent strategy one that clearly explains where we will play, how we will win, and what we must do to make the choice succeed.