Introduction to Assumptions and Sensitivity in Financial Forecasts

Welcome to one of the most practical parts of your financial management studies! In previous chapters, you learned how to build a forecast. But how do you know if that forecast is actually reliable? In the real world, things rarely go exactly as planned. This chapter focuses on identifying the "foundation" of your forecast (the assumptions) and testing what happens when things go wrong (sensitivity analysis).

By the end of this section, you will understand how to evaluate a business plan not just by its final numbers, but by how "tough" it is when faced with change. This is a Level 3 topic, meaning the HKICPA expects you to be able to integrate these concepts to judge the value of a business plan.

1. The Foundation: Financial Forecast Assumptions

Every financial forecast is built on a set of assumptions. An assumption is a "best guess" or a "given condition" about the future. If your assumptions are unrealistic, your entire forecast will be misleading.

Types of Assumptions

When producing financial forecasts for a business plan, you must consider both internal and external factors:

  • External Assumptions: Factors outside the company's control.
    Examples: The inflation rate in Hong Kong, changes in tax laws, or the market interest rate affecting a loan's WACC.
  • Internal Assumptions: Factors the company can influence.
    Examples: Expected sales growth percentage, the efficiency of a new production line, or the planned selling price of a product.

Did you know? A common mistake in the exam is forgetting that assumptions must be consistent. For example, you cannot assume a massive increase in sales volume without also assuming an increase in variable costs or working capital needs!

Key Takeaway: Assumptions are the "inputs" of your model. If the inputs are weak, the output (the forecast) is unreliable.

2. Testing the Forecast: Sensitivity Analysis

Sensitivity Analysis is a "what-if" technique. It measures how much the final result (like Net Profit or Net Present Value (NPV)) changes when we change one of the underlying assumptions.

How to Perform Sensitivity Analysis

To see how sensitive a forecast is to a specific variable, follow these steps:

1. Identify a key variable (e.g., Sales Volume).

2. Change that variable by a specific percentage (e.g., "What if sales are 10% lower than expected?").

3. Recalculate the forecast (e.g., the new Profit or NPV).

4. Compare the new result to the original to see the impact.

The "Margin of Safety" Concept: In some cases, you might calculate how much a variable can change before the project becomes unfeasible. For example, "How much can the sales price drop before \( \text{NPV} = 0 \)?".

Example: The Hong Kong Coffee Shop

Imagine a business plan for a new cafe in Central. The original forecast shows a profit of \( \$500,000 \).
Assumption A: Rent stays at \( \$100,000 \).
Assumption B: We sell 1,000 coffees a day.
If we change Assumption B to 900 coffees (a 10% drop) and the profit crashes to \( \$100,000 \), the plan is highly sensitive to sales volume. If the profit only drops to \( \$480,000 \), the plan is robust regarding sales volume.

Key Takeaway: Sensitivity analysis helps management identify the critical variables—the factors that could most easily "break" the business plan.

3. Evaluating Business Plans (Level 3 Integration)

In the HKICPA QP, you aren't just asked to calculate; you are asked to evaluate. When looking at a business plan's sensitivity, consider these three points:

A. Identifying the "Make-or-Break" Factors

If a plan is extremely sensitive to the cost of raw materials, management must focus all their energy on securing long-term contracts with suppliers to lock in prices. Sensitivity analysis directs management's attention to where it matters most.

B. Assessing Risk

A project with a high \( \text{NPV} \) might look great, but if a tiny 2% change in the discount rate (r) makes the \( \text{NPV} \) negative, the project is actually very risky. You must decide if the potential reward is worth that high level of sensitivity.

C. Limitations to Remember

Don't worry if this seems a bit simple—that's because sensitivity analysis has limitations that you should mention in an evaluation:

  • One variable at a time: It usually only changes one thing (e.g., price) while keeping everything else (e.g., volume) the same. In reality, if you raise the price, the volume usually drops!
  • No Probability: It tells you what happens if a variable changes, but it doesn't tell you how likely that change is to happen.

Quick Review: Sensitivity analysis identifies "how much" a result changes, but it doesn't predict the "chance" of it happening.

4. Summary and Exam Tips

Common Pitfalls to Avoid:

  • Mixing up variables: Ensure you are only changing one assumption at a time during sensitivity analysis.
  • Ignoring the "Why": In written-style OTQs, don't just say a variable is sensitive; explain why that matters for the entity achieving its objectives.
  • Formula Awareness: While the exam is 100% OTQ, you still need to understand the relationship between variables. For example, if the discount rate \( r \) in the formula \( \text{NPV} = \sum \frac{CF_t}{(1+r)^t} - I_0 \) increases, the \( \text{NPV} \) will decrease.
Final Checklist for Students:

1. Can I identify the key assumptions in a scenario? (Comprehension)

2. Can I calculate the impact of a change in an assumption on the forecast? (Application)

3. Can I explain which variable is the most "critical" and how that affects the business plan's viability? (Evaluation)

Note: For more on the role of business plans, see the chapter "Role and composition of business plans". For the mechanics of building the forecast itself, refer to "Formulate plans and forecasts for a business entity".