Business Forecasting: Methods & Analysis

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  • 0:03 What Is a Financial Forecast?
  • 1:18 Qualitative Methods
  • 2:44 Quantitative Methods
  • 5:16 Lesson Summary
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Lesson Transcript
Instructor: Deborah Schell

Deborah teaches college Accounting and has a master's degree in Educational Technology.

Businesses create financial forecasts for a number of variables, such as sales volume. In this lesson, you'll learn about the qualitative and quantitative methods used to prepare forecasts.

What Is a Financial Forecast?

A financial forecast is developed by identifying trends in past data and using this information to predict a company's financial position for the future. In other words, a financial forecast is really an educated guess. For example, a company might use its past sales information to make predictions about what its sales volume will be for the next 12 months. Forecasting helps a business identify in advance what resources (such as employees) might be required to meet the forecast.

Financial forecasts can be either qualitative or quantitative. A qualitative method of creating a financial forecast involves gathering information that cannot be measured, such as consumers' opinions about new packaging for a product that is being reintroduced to the market. A quantitative method of developing a forecast uses data to predict future results. An example would be using past sales data to forecast sales volume for the upcoming year

Let's meet Mr. Bubble, owner of the Chews Bubble Gum Company. He would like to use financial forecasting to solve two current problems: will his customers buy his new flavor of chewing gum, bombastic blueberry, and how can he create a sales forecast for his company for the first quarter of next year? Let's see if we can help Mr. Bubble.

Qualitative Methods

Qualitative methods of financial forecasting are useful when a new product is introduced since there's little or no historical data available. In Mr. Bubble's situation, the company has never offered this flavor of gum before, so there's no sales data to analyze.

Examples of qualitative methods include:

  • Market research
  • Delphi method

Market research involves discussing a product or service with current and future customers. For example, Mr. Bubble could poll a sample of people to determine if they would buy the new bombastic blueberry bubble gum when it is released to the market. The information would assist Mr. Bubble in determining whether there would be demand for this new flavor before he starts producing large amounts of it. While this method provides great information on consumer buying habits, it's very expensive and takes a great deal of time to complete.

The Delphi method involves asking experts their opinion about a product or service and continuing the process until a consensus is reached. Questionnaires are used for each round and the results of one questionnaire become the foundation for the next one until consensus is reached in the group. This method takes a great deal of time and is most useful when creating long-term forecasts.

Management often begins with qualitative methods since they provide a rough estimate about the viability of a new product or the future demand for a product in certain economic conditions. If more accurate information is required, management can use quantitative methods.

Quantitative Methods

Quantitative methods use data to predict what will happen in a future period. For example, quantitative methods could be used to create sales forecasts or predict economic growth. For Mr. Bubble, quantitative methods would be useful in creating his future sales forecast since he would be able to use past sales data as a starting point.

Examples of quantitative methods include:

  • Causal methods
  • Time series methods

Causal methods assume that a relationship exists between one or more items and that a change in one item will cause a change in the other. The primary method used in causal analysis is regression analysis, which involves examining the relationship that exists between two things.

For example, Mr. Bubble would like to forecast future sales for his company. Let's assume that sales of chewing gum depend on the worldwide price of sugar. Regression analysis could be used to determine the strength of the relationship that exists between sugar prices and chewing gum sales so that predictions can be made. Perhaps after completing regression analysis, Mr. Bubble determines that the price of sugar is increasing by 1%. The regression analysis will help him identify what impact this change will have on the sales volume of chewing gum.

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