written by | November 2, 2022

Business Forecasting: Concept, Importance And Processes

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Organisations that run well don't make decisions on the spur of the moment; they are constantly working on their business forecasting and planning. Businesses make decisions based on data from business forecasts, market research, business intelligence tools, and scenario planning. A company's long-term strategy depends on predicting market trends to be successful.

In addition to highly sophisticated statistical methods, some business forecasts rely on experience and past data. Others follow their gut instincts, and business forecasting is a constant in all industries. This article provides insights on business forecasting, types of forecasting and examples.

Did You Know? Wesley Mitchell, who was deeply involved with forecasting in the 1910s and 1920s, invented business forecasting. One of his students, Simon Kuznets, developed the Gross National Product measurement in the 1930s.

What is Business Forecasting?

Business forecasting projects the future development of a business or industry by using trends and patterns from past and present data. As a result of this business practice, you can strategically determine the allocation of resources and plan for projects, activities, and costs. Organisations can manage their resources, align their goals with current trends, and stay competitive by forecasting. 

You can secure your business's future by using relevant data from the past and present to develop better strategies and project plans. Investing in good business forecasting gives organisations unique insights into likely future events, enables them to maximise their resources, sets product teams' OKRs, and establishes their market leadership. Making data-driven, logical decisions rather than decisions based on emotions or gut feelings is a requirement for managers.

Also read: What Are The Top 10 Business Ideas in Delhi?

Importance of Business Forecasting

It is not always the same market in which a business operates, and businesses that prepare for situations well will perform better than their competitors. By forecasting future trends, companies can change and adapt their business strategies according to the directions. Businesses need quantitative, qualitative, statistical, and econometric models to obtain accurate projections and estimates, 

Managers can strategise more confidently using business forecasting tools that provide data-backed results. For forecasting to be effective, you must consider the company's data and industry factors. In business strategy and decision-making, business forecasting brings logic and data together. 

Methods of Business Forecasting

There are several methods for forecasting business activity. In general, they fall into two categories: 

  1. Quantitative forecasting
  2. Qualitative forecasting

Businesses need quantitative and qualitative forecasting techniques in different product life cycle stages. There is a loss of connection between past and future trends when a company's focus changes, its competitors or strategy changes, or its compliance requirements change. Therefore, it is even more essential to choose the proper forecasting method. 

1. Quantitative Business Forecasting

To predict future events in your business or industry, use quantitative forecasting when there is accurate past data available. 

By analysing existing data, quantitative forecasting determines more probable outcomes. Different variables are connected and analysed to establish cause-and-effect relationships between events, elements, and results. In quantitative forecasting, past sales data is an example.

Quantitative models use numbers, formulas, and data. Quantitative analysis involves little human intervention. Business forecasting quantitative models include:

Indicator approach: This approach relies on the relationship between specific indicators remaining stable over time, e.g., GDP and unemployment rates. Forecasters can estimate the performance of a business by examining the relationship between these two factors. 

Average Approach: By using the average approach method, future values are predicted based on the average of past values. It is best to use this approach when assuming the future will be like the past.

Econometric Model Approach: Using econometric models for forecasting is mathematically rigorous. Generally, forecasters assume that the relationship between indicators will remain the same and check the consistency and strength of the relationship between datasets.

Time Series Approach: Predicting future outcomes using historical data is known as the time-series method. Forecasters expect to be able to predict the future by looking at what has happened in the past.

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2. Qualitative Business Forecasting

In qualitative business forecasting, experts and customers make predictions and projections. The method works best when there is not enough past data to analyse to make a quantitative forecast. By combining available data, industry experts and forecasters can make qualitative predictions.

Short-term projections are the most successful for qualitative models. The discussions are expert-driven, presenting contrasting opinions and relying on judgment over calculable data. Business forecasting qualitative models include:

Market Research Method: Market research involves polling professionals, customers, and employees to find their preferences and opinions.

Delphi method: Delphi involves soliciting opinions and recommendations from a panel of experts and compiling them.

Integral Elements of Business Forecasting

Conceptually, all forecasts follow the same process, regardless of the forecasting technique or method. Business forecasting involves the following standard elements:

  • Get the stage ready: Establish a system for investigating your company's current state before you begin.
  • Choose a data point: For example, what is our sales projection for next quarter?"
  • Decide how to collect the data: Identify the relevant indicators and data sets you need.
  • Initial assumptions: Forecasters may make some assumptions to begin the forecasting process.
  • Choose Forecasting Technique: Your forecast will be most accurate if you choose the proper technique.
  • Analyse data: Select a forecasting technique and analyse available data.
  • Estimate forecasts: Make a data-driven prediction based on your gathered data. 
  • Verify Forecasts: Check your forecast against the actual results. By identifying problems, tweaking errant variables, and correcting deviations, you can continue to improve your forecasting skills.
  • Review the forecasting process: Determine if there is a difference between your forecasts and actual results.

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Examples of Business Forecasting

Here are a few examples of forecasting for business: 

  • Calculating cash flow prediction. A cash flow forecast is a prediction of your financial needs at a particular point in time
  • Identifying new competitors in your market and estimating their threat
  • Analysing the possibility of developing new products or services
  • Analysing recurring bills and estimating their costs
  • Analysing past sales performance to predict future sales growth
  • Examining the relationship between variables, such as Facebook ads and revenue potential
  • Allocating resources efficiently and budgeting for contingencies
  • Analysing the relationship between customer acquisition costs and customer lifetime value.

How To Choose The Right Business Forecasting Method?

It is essential to consider many factors when choosing a business forecasting technique. Here are a few examples:

  • A brief description of the forecast's context
  • The availability of past data and its relevance
  • An accurate level of performance is required
  • Allocate a certain amount of time to conduct the estimates
  • Defining the forecasting period 
  • Benefits and costs of forecasting
  • When a product or business needs a forecast

Managers and forecasters need to consider the stage of the product or business as this influences the availability of data and how they establish relationships between variables. In the case of a new start-up without previous revenue data, it would not be possible to use quantitative methods for forecasting.

To succeed in business forecasting, you must understand how different forecasting techniques work, their capabilities, and their impacts.

Limitations of Business Forecasting

Business forecasts can be wrong even when you use the proper methods and follow the rules. Ultimately, it involves predicting the future. There are some limitations to business forecasting, including:

  • A forecaster's or manager's biases and errors 
  • Customer, expert, or employee information that is incorrect 
  • Numbers in the past are inaccurate 
  • Market conditions suddenly change
  • Regulations new to the industry 

Despite its negative aspects, business forecasting is here to stay. Forecasting effectively allows businesses to plan for their needs, increasing their chances of remaining competitive. All investors can benefit from that function of business forecasting.

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Conclusion:

Businesses need forecasting to make informed business decisions. A financial forecast is fundamentally based on educated guesses, and relying on past data and methods that exclude certain variables carries risks. Quantitative and qualitative forecasting approaches are available. Use these approaches in your business to do forecasting and make your business succeed. 

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FAQs

Q: Why is business forecasting important?

Ans:

Forecasting helps to predict potential issues and making better decisions, and measure the impact of those decisions.

Q: What do you know about the business forecasts? Are they accurate?

Ans:

Business forecasting is a process of making decisions based on projections of the future. Forecasters are responsible for analyzing data and coming to conclusions on what will happen in the future based on this analysis. Businesses can use time series forecasting to predict product sales, revenue and expenses for future months, quarters and years. The forecasts are created with line charts that provide visual representations of seasonality, cycles and trends that repeat from year to year.

Q: Is there a type of forecast that is most accurate?

Ans:

Seven-day forecasts are usually 80% accurate, whereas five-day forecasts are generally 90% accurate. Typically, one-day forecasts are within 2.5 degrees of their original predictions.

Q: How accurate are forecasting methods?

Ans:

As long as forecasts fall within a specific error range, statisticians will say that predictions are accurate. Those bounds, however, might not be appropriate for your business.

Q: How is business forecasting based on assumptions?

Ans:

In business forecasting, a time series is a set of observations over a period of time. Time series data can be used to create forecasts and perform trend analysis. While there are many time series forecasting models, we will focus on the Exponential Smoothing (ES) method in this discussion. The Exponential Smoothing method works by breaking down the time series into smaller chunks and calculating the forecasted value based on the SMOOTH function.

Estimating data points is often the first step in forecasting future performance. Some businesses use forecasting techniques to anticipate purchases, sales, or even interest rates. Using historical trends and patterns, forecasters make three common types of assumptions: trend-based assumptions, cycle-based assumptions, and seasonality-based assumptions.

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Disclaimer :
The information, product and services provided on this website are provided on an “as is” and “as available” basis without any warranty or representation, express or implied. Khatabook Blogs are meant purely for educational discussion of financial products and services. Khatabook does not make a guarantee that the service will meet your requirements, or that it will be uninterrupted, timely and secure, and that errors, if any, will be corrected. The material and information contained herein is for general information purposes only. Consult a professional before relying on the information to make any legal, financial or business decisions. Use this information strictly at your own risk. Khatabook will not be liable for any false, inaccurate or incomplete information present on the website. Although every effort is made to ensure that the information contained in this website is updated, relevant and accurate, Khatabook makes no guarantees about the completeness, reliability, accuracy, suitability or availability with respect to the website or the information, product, services or related graphics contained on the website for any purpose. Khatabook will not be liable for the website being temporarily unavailable, due to any technical issues or otherwise, beyond its control and for any loss or damage suffered as a result of the use of or access to, or inability to use or access to this website whatsoever.