Business forecasting allows your company to make long term plans and prepare for any changes in the market. Based on the unique needs of your business, your approach to business forecasting must be targeted and tweaked to be useful.
In order to help you better understand business forecasting and choose the right path for your company, we’re breaking down every element of the forecasting process—beginning with the types of business forecasting.
What is business forecasting?
Business forecasting is predicting the economic future—along with how your business will respond.
Business forecasting involves the collection of primary and secondary sources of data, analyzing the data, creating strategies for projections, and then comparing your forecasting model to the realized outcomes.
This type of analysis can allow businesses to prepare for shifts in the market or a change in demand. Business forecasting may change the investment and saving strategies of businesses and individuals, as well as affect the timing of new offerings.
The business forecasting process typically involves:
- collecting primary and secondary sources of data
- analyzing the datasets
- creating strategies for projections, and finally
- comparing your forecasting model to the realized outcomes.
Types of business forecasts
There are a lot of ways to estimate data and scenarios for your company. Each type of business forecast focuses on a specific metric or outcome.
What you want to know or predict about the future will help you decide which type of forecast you pursue.
Business forecasts can range from the general (sales next month) to the incredibly specific (consumer demand for a specific product for the holiday season). Here is a quick run down of the 6 most common types of business forecasts you’re likely to use.
- General business forecasting
- Financial forecasting
- Accounting forecasting
- Demand forecasting
- Sales forecasting
- Capital forecasting
1. General business forecasting
A general business forecast is used to determine the overall business climate for a future date, and can be widely applied and useful for many different businesses and industries.
Used for: Determining overall market conditions and the impact of the environmental factors in which your business operates
Best for: Businesses operating in influential environments, such as countries experiencing political upheavals, major technological advancements, or dramatic seasonal shifts.
Example: Analyzing the impact the 2020 U.S. Presidential election will have on the American economy at large.
2. Financial forecasting
Financial forecasting is about getting a clear picture of where your company is headed. It includes weighing assets and liabilities, accounts payable and account receivable, operating costs, capital and cash flow, and general market conditions.
Used for: Tracking the future trajectory of your company as a whole.
Best for: All businesses looking to stay on top of their business’s health through financial projections.
3. Accounting forecast
An accounting forecast is the practice of predicting the future costs which will be incurred by your company, using past and present data to estimate how much your business will pay for raw materials, inventory, man hours, utilities and rent, insurance, and more.
Used for: Determining future operating costs for your business.
Best for: Every business concerned with covering future costs.
Example: Estimating cyclical changes in a seasonal product’s cost, such as fresh produce for a restaurant.
4. Demand forecasting
Your demand forecast will go hand in hand with a sales forecast, as demand forecasts will predict what the market needs or wants and a sales forecast will predict how your business will be able to capitalize on those needs with sales.
Used for: Determining market and customer demand for a good or service in the future.
Best for: Planning how much to invest in raw materials or inventory, deciding if a new product will perform well.
Example: Predicting the demand for a new toy at Christmas so you can buy the appropriate inventory.
5. Sales forecasting
A sales forecast estimates future sales, whether overall or of a specific product or service within your business offerings, based off of sales data. Sales forecasting allows your business to anticipate the future needs for workforce, resources, cash flow, inventory, and investment capital. A sales forecast will show the sales revenue your company might expect over the next month, quarter, or year of a sales cycle.
Used for: Predicting your sales for a future period of time, and estimating growth and cash flow.
Best for: Businesses relying solely on sales history, or looking to project sales for investors and funding.
Example: Projecting revenue for the 2021 fiscal year to determine how many salespeople to hire and their commission structure.
6. Capital forecasting
A capital forecast is based on current and future assets and liabilities, as well as predictions for liquid capital and cash flow estimates.
Capital forecasting is tricky, and not as reliable as other forecasts simply because it involves guessing at a number of factors. Capital may involve the following factors:
- Cash & savings
- Accounts receivable
- Investment funding
- Lines of credit
Used for: Predicting available capital for a future date or event.
Best for: Companies preparing for investment, growth, hiring, acquisitions, or other changes that will require cash.
Example: Estimating working capital for purchasing a larger office building in the coming year.
Forecasting methods vs. forecasting types
The forecasting method is the tool you use to gather and evaluate relevant data for your forecast type. Within each of these forecasting techniques you’ll use different recipes or methods of forecasting to create the data you need.
The methods are qualitative forecasting (using opinion and observation) or quantitative forecasting (using data and historical evidence), or a combination of the two.
There are a wide range of methods you can use to forecast business data, and you’ll make your choice based on the type of forecast you aim to create and the data available to you.
For example, you may want to create an accounting forecast, so you’d use the method of regression analysis to test and compare multiple variables of cost over time.
What is qualitative forecasting?
A qualitative forecasting method is based primarily on the best judgment and opinions of knowledgeable industry observers. While a qualitative forecast does involve some data, it relies on expert opinion rather than extensive data projections.
Qualitative forecasting is especially helpful in industries where there have been recent disruptions that make the future vary distinctly from past practices (i.e. new laws, major innovation). It can also be used when you have insufficient historical data to reproduce a meaningful prediction.
Qualitative forecasting methods
The two most common forms of qualitative forecasting are the Delphi Method and market research.
The Delphi Method
The Delphi Method is a forecast technique in which a panel of experts is selected to give their opinions on the specific economic situation, then is asked for their predictions and analysis, independently of the other experts. The depth and breadth of your panel can be used strategically to improve forecast accuracy. For example, you might have experts from various different positions in a company (sales, finance, marketing, customer support) all weigh in on your panel for a broad view of the economic future.
Pros: The Delphi Method is particularly helpful for seeing where experts agree and disagree—without the warping effects of peer pressure. When experts are asked independently they are less likely to adjust their true predictions in response to the opinions of others.
Cons: As with any qualitative forecast, you will lack the cleancut nature of raw data. Each expert may assert a different claim and leave you without definitive results. And, naturally, experts are only human. They may be wrong, and their assertions are always subject to interpretation.
When to use: This method is best used when there is no “right” answer, or when bias is strong. The Delphi Method is often used for long term planning, decision-making, policy making, and in new or emerging fields.
A market research or market survey forecast has been used for generations, and involves speaking to potential customers to determine their likelihood to buy or participate in a particular economic target. For example, driving-age adults might be given a brief questionnaire to determine how likely they are to purchase a vehicle in the next five years. This forecasting technique can be executed in any number of ways, from email surveys, personal interviews, focus groups, and more.
Pros: Market research can be highly targeted for your specific requests, such as an exact demographic audience or regarding a single product. Market research can be done no matter your budget or location.
Cons: The value of market research depends on the quality of your survey and the sample size of your audience.
When to use: Market research is particularly useful when you want to know more about your customers and their buying habits. Sales forecasting and demand forecasting rely heavily on market research.
What is quantitative forecasting?
Quantitative forecasting is usually the best choice for a sales forecast that focuses on observable data. Quantitative forecasting is a complex accumulation of data searching for significant connections and patterns that may predict future outcomes.
The data used in the quantitative method of forecasting can include growth and sales data from your business, demographic information from a census or survey, or any other relevant data which is available.
When cause-effect relationships are discovered (or suspected) your business can leverage the variables for maximum benefit.
Quantitative forecasting methods
The two most common forms of quantitative forecasting are the time series analysis and casual method.
Time series analysis
In this quantitative business forecasting method, the past predicts the future through the use of averages, determining patterns, and extrapolating data. You can look at any number of variables that change over time to provide reasonable estimates for the future.
For example, you might want to analyze the price of a seasonal product like lawn fertilizer. In a time series analysis you would assemble the price of lawn fertilizer over a designated period of time, perhaps the last year. This chronological listing or plotting of prices can provide a map of where lawn fertilizer prices might go in a similar year.
Pros: Time-series analyses are straightforward to create and can be easily visualized in graphs or charts. Trends or changes can be easy to identify, providing an opportunity for leverage in the future.
Cons: Contextual information is usually required to give meaning to the data of a time-series analysis, and past time periods aren’t always a good indicator of what’s to come.
When to use: This method is best used in markets where seasonal and cyclical trends are the norm, or when you wish to find correlations with other conditions, such as GDP or unemployment.
Causal relationships are important in an economic climate, so forecasting how different factors might interact can help businesses better prepare. Causal forecasting can help you determine how elements like price, sales, availability, production costs, and locations might impact future sales. Leveraging a causal relationship can help you harness the power of your environment or market for your own success.
The causal method is often a natural next step to a time-series analysis or used in conjunction with qualitative findings. For example, after completing a time-series analysis of monthly sales by price you might be able to determine that raising the price actually increases your sales for a certain product. This type of sales forecast would enable you to estimate increases or decreases in sales based on the pricing model you choose in the future.
Pros: Identifying cause-and-effect patterns can make decisions, like price or where to spend your budget, clear and easy.
Cons: Identifying causal relationships can be difficult, and it can be tempting to see correlations and jump to conclusions.
When to use: Causal methods are best used when you have multiple variables to compare, and plenty of data to support a statistically significant relationship between them.
Why should you forecast for your business?
It may seem like forecasting is a lot of work for an unpredictable, possibly nonexistent payout. But there are several solid reasons that you should be regularly using forecasting to benefit your business.
Benefits of business forecasting:
- Better grasp on in-house data and business performance
- Competitive advantage
- Setting and enforcing effective budgets
- Faster response to cyclical or seasonal changes
- Ability to identify larger patterns and relationships
- To assist in long-term strategy and goal-setting
Forecasting isn’t perfect, but it is a useful tool and practice for understanding your company’s financial state and remaining agile in a changing market. At the very least, forecasting forces you to know your own company and gather your own data—making you a smarter and better informed business owner.