What Is a Business Forecast and Why Is It Useful?
By Indeed Editorial Team
Published November 26, 2022
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
Businesses across several industries use forecasts to make meaningful and educated decisions about their operations. They are predictions made about the future direction of a company, and use a mixture of financial modelling, market analysis, and trend estimates. Understanding this process can help you conduct them yourself and make more informed decisions. In this article, we discuss what a business forecast is, explore why it’s useful, investigate the various types, and explain what you can use it for with tips.
What is a business forecast?
A business forecast takes the findings of both qualitative and quantitative prediction methods and uses them to evaluate the probability of an event happening in the future. This prospect can then influence company operations and ensure informed business decisions. For example, an organization can use forecasts to predict the success of certain trends. They can then use this information to time the release of their new product that's in line with that. If predictive models indicate the trend may not be successful, the business can choose to launch a different product.
Companies can use forecasts for many types of decisions. This can be something simple, such as finding out the optimal time to launch a new product, or it may be complex, such as predicting if a recession may take place. Depending on the information collected in these methods, businesses can use forecasts to gather insights into almost any type of decision. The more information a business obtains, the more accurate their calculations can be.
Why is it useful?
By predicting the probability of an event, organizations can plan their product launches, company changes, and other decisions around the ideal timeframe. While these models can't guarantee an event might take place, they can increase the evidence towards or against a business decision. By using predictive data, companies can make decisions based on numerical statistics, which is more reliable than guessing which direction the industry may take. This can increase the chances of a successful decision and a positive outcome.
Types of business forecasts
Businesses can use several forecasting methods to collect predictive data, including:
This is a form of qualitative predictive data model that involves interviewing a representative sample of the market to identify trends and patterns. Companies collect research through interviews, surveys, and focus groups to better understand the opinions and behaviours of the participants. After collecting this information, they compile it and use it to make informed predictions about the behaviours of the market and how they can influence business decisions.
For example, an organization looking to launch a new product may interview a sample of their target market to better understand their buying behaviour. They may collect information on their opinions regarding trends and popular items, then ask them the probability of them making a purchase. The business can then use this information to predict the success rate of their new product and make required changes before launch.
This technique is a qualitative method of forecasting that involves asking field experts their opinions and predictions and compiling them to draw conclusions. Professionals consider the information drawn from this method to be effective at estimating trends and patterns, therefore it is common practice for many businesses. For example, a company trying to predict the direction of the market may compile the opinions of leading economists to make an informed decision about their future operations.
This quantitative method model identifies trends over time by tracking changes in their value. By doing this, researchers can identify repeating patterns and predict when they may occur in the future. This type of forecasting becomes more accurate as businesses add more data to the model, but it cannot account for major events that don't occur regularly. Companies can use the time series model to track their own data and identify patterns that are unique to their customers, products, and operations.
For example, an organization looking to launch a new product can use their existing data on customers to identify periods of high sales and product shortages. Using this information, they can predict the best time to launch their item and ensure they have enough stock prior to this. Combining this data with market research can improve the quality of predictions made by a business.
How can businesses use forecasts?
These forecasts have several practical uses, including:
Companies can use forecasting to make more informed and educated business decisions. By basing their planning and operations management around predictive models, there is a higher chance their outcome may be successful. Organizations can use forecasting to plan several aspects of their business, including:
Businesses can use forecasting to predict product demand and anticipate the needs of their customers. By tracking previous periods of this, they can anticipate repeat behaviour and prepare their inventory accordingly. By monitoring the requirement for similar products in the market, they can anticipate how many products may sell if they launch within the same area. By combining internal and external forecasting, companies can get an accurate picture of what they may encounter at a given time in their business cycle.
Organizations can use forecasts to improve their product marketing and capitalize on the periods of increased demand for their product or service. Using the time series method, they can anticipate customer requirements and market their products accordingly. Using market research, they can predict the demand for potential types of products amongst their audience and tailor these to what is most likely to succeed. Using both these methods in tandem can allow businesses to calculate the best product details and launch times, increasing the chances of success.
Not only can companies use predictive models to anticipate the future of their business, they can use them on their competitors as well. Doing this can help you alter your business decisions and product launches in ways that benefit your operations. For example, if your competitors release a new product at the beginning of each year, you can use market research to identify trends and make predictions about what that product may be. Using this information, you can launch your own product ahead of your competitors and use your predictive knowledge to your advantage.
Tips for forecasting
When conducting a forecast, consider following these tips:
The greater the consistency of your forecasting, the more accurate it may be, especially with time-regression predictive models. As these models become more accurate with more information, consistency in adding data can further improve their reliability. Consider developing a process to collect required data at regular intervals and input it into your system regardless of whether you need a calculation. This can ensure that when you forecast, you have enough information to draw relevant and accurate findings from your data points.
Check for accuracy
The accuracy of a business forecast depends on the data used to make it. Before using any predictive model, check the precision of your data and the source of your information to ensure you are using relevant and reliable inputs. This can help ensure your calculations are correct and increase the chance of the predictions being successful. Internal data is an excellent source, as you have complete control over how it's collected and can understand how accurate it is.
Allow a margin of error
Predictive models cannot guarantee an event may occur and, as such, it may require businesses to account for a margin of error in their findings. Forecasting can provide insight into the probability of an occurrence, which can greatly benefit a company, but there is always a chance that the predictive models may falsely determine an outcome. When using these methods, collect as much information as possible, as the more data they have, the greater their rates of accuracy are.
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