Prospective analysis, including the use of data

Welcome to Prospective Analysis!

Welcome, future CPAs! Today, we are diving into Prospective Analysis. If Financial Statement Analysis is like looking in the rearview mirror to see where a company has been, Prospective Analysis is like looking through the windshield to see where it’s going. This is one of the most exciting parts of the BAR (Business Analysis and Reporting) exam because it's where we use data to "predict the future." Don't worry if this seems a bit like fortune-telling at first—it’s actually a very logical, step-by-step process that you can master!

What is Prospective Analysis?

Prospective Analysis is the process of forecasting a company’s future financial results, such as its future earnings and cash flows. It is the final step in business analysis and is used for everything from valuing a stock to deciding if a company can pay back a loan.

Think of it like this: If you are planning a long road trip, you look at your past gas mileage (historical data) and the distance to your destination (future goals) to estimate how much money you’ll need for gas. That’s prospective analysis in action!

Why do we do it?

Investors and creditors don't just care about what happened last year; they care about what will happen next year. We use prospective analysis to:
1. Value a company's equity.
2. Assess a company's creditworthiness (can they pay their bills?).
3. Evaluate the feasibility of management's strategic plans.

Quick Review: Prospective analysis = Forecasting the future based on the past and current environment.

Step 1: Analyzing the Drivers

Before we can predict the future, we have to understand what "drives" the business. Every company has key performance drivers—the specific factors that cause revenue and expenses to change.

Common Drivers include:
- Sales Volume: How many units are being sold?
- Sales Price: Are prices going up or down?
- Cost of Goods Sold (COGS) %: How much does it cost to make the product relative to its price?
- Market Share: Is the company winning against competitors?

Pro Tip: Most forecasts start with Revenue. Why? Because almost every other line item on the financial statements (like COGS, accounts receivable, and even some equipment needs) depends on how much the company sells!

Step 2: Forecasting the Income Statement

To forecast the Income Statement, we usually use a "top-down" approach, starting with sales and working our way down to net income.

1. Projecting Sales

We look at historical growth rates and adjust them for the future.
Formula: \( \text{Projected Sales} = \text{Prior Year Sales} \times (1 + \text{Growth Rate}) \)

2. Projecting COGS and Operating Expenses

These are often forecasted as a percentage of sales. If COGS has historically been 60% of sales, and we don't expect major changes, we assume it will be 60% of our new projected sales figure.

3. Projecting Interest and Taxes

Interest expense is tied to the amount of debt the company has, and tax expense is usually projected using the statutory or historical effective tax rate.

Common Mistake to Avoid: Don't just assume every expense grows at the same rate as sales. Some expenses are fixed (like rent), meaning they stay the same even if sales go up!

Step 3: Forecasting the Balance Sheet

The Balance Sheet must stay in balance! To forecast it, we use several techniques:
- Working Capital Accounts: Accounts Receivable (AR), Inventory, and Accounts Payable (AP) are usually linked to sales or COGS using turnover ratios.
- Capital Expenditures (CapEx): We look at management's plans to buy new equipment or buildings.
- The "Plug" Figure: Often, after we forecast everything else, we use Cash or Short-term Debt as a "plug" to make sure Assets = Liabilities + Equity.

Key Takeaway: The forecast must be internally consistent. If you project a 50% increase in sales, you probably need to project an increase in Inventory and AR to support those sales!

The Role of Data in Forecasting

In the modern BAR environment, we don't just guess; we use data. There are two main types of data used in prospective analysis:

1. Internal Data: This comes from within the company (e.g., historical financial statements, sales reports by region, production capacity limits).
2. External Data: This comes from outside the company (e.g., GDP growth rates, industry trends, competitor actions, inflation rates).

Using Regression Analysis

Sometimes, we use a statistical tool called Regression Analysis to see how one variable (like advertising spend) affects another (like sales).
The formula looks like this: \( Y = a + bX \)
- \( Y \) is the Dependent Variable (what we want to predict, like Sales).
- \( a \) is the Intercept (fixed costs/baseline).
- \( b \) is the Slope (the rate of change).
- \( X \) is the Independent Variable (the driver, like the number of stores opened).

Did you know? Even if your math is perfect, if the data you put in is bad, your forecast will be bad. This is called "GIGO"—Garbage In, Garbage Out!

Sensitivity and Scenario Analysis

Because the future is uncertain, we use two "What If" tools:

1. Sensitivity Analysis

This tests how sensitive our results are to a change in one specific variable.
Example: "What happens to our Net Income if our raw material costs increase by 5% but everything else stays the same?"

2. Scenario Analysis

This tests several variables at once based on a specific event. We usually create three scenarios:
- Best Case: High sales, low costs.
- Base Case: Most likely outcome.
- Worst Case: Recession, high competition, or supply chain failures.

Memory Aid: Sensitivity = Single variable. Scenario = Several variables (a whole situation).

Summary of Key Concepts

- Prospective Analysis is forward-looking and used for valuation and credit analysis.
- Sales is usually the primary driver for all other projected line items.
- Percentage of Sales method is a common way to forecast variable expenses and working capital.
- External and Internal Data must both be considered for a realistic forecast.
- Regression, Sensitivity, and Scenario Analysis are the "tools of the trade" to handle uncertainty.

Don't worry if this seems tricky at first! The more you practice looking at how one change (like an increase in sales) ripples through the financial statements, the more intuitive this will become. You've got this!