Business Forecasting

How to Do Better Business Forecasting

Business forecasting is key for business owners who want to endure in the industry. Successful business owners consistently rely on data analysis to make informed decisions about the future. While forecasting can’t always give you 100% accurate predictions for the future, being close enough can help your business endure past tough times.

What is Business Forecasting?

Say you conducted a business analysis on how macroeconomic factors have affected businesses in the past. You discovered that certain businesses endured while others failed, and were able to isolate factors that contributed to the success. You also learned about the early warning signs that indicate a potential economic downturn is on the horizon.

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This data lets you know what to look for in the future when it comes to the state of the economy. It informs you of the choices that can improve your business’ chances to endure and succeed. Although this is one example, business forecasting can be used for everything from improving sales, to conducting better digital marketing campaigns. Statistical models are used to study variables and ascertain how they interact with each other. Business forecasting is integral for business success, and here’s how you do it:


In essence business forecasting is an investment to protect your company against unknown risks. There are other ways you can protect your business as well. Consider getting business insurance and find coverage in case your business is ever at risk.


Business Forecasting: Statistical Models and Data Analysis:


Forecasting is always done by gathering data. This data can come in two forms:

  • Primary Sources: This is data that you gather by yourself. Primary sources can include interviews, surveys, questionnaires, etc. The person or people conducting the analysis goes out to gather data personally.
  • Secondary Sources: This is data that is gathered from external sources. These external sources can include governmental or academic publications, financial statements, industry reports, etc.


Business forecasters are increasingly making use of available digital tools to improve their predictions. Big data and artificial intelligence now make it easier for analysts to work with large data sets. Once the data is gathered, a statistical model is chosen.


Then, by using that statistical model, analysts determine forecasts based on the relationships between chosen variables. There are two kinds of statistical analysis performed by forecasters:


Qualitative Analysis:

Qualitative statistical models are usually chosen where insufficient historical data makes gathering large data sets difficult or impossible. New and emerging industries typically make use of qualitative models to determine possible predictions.


When there is no or limited historical precedent for certain industries, market experts are brought in to provide their opinions. Since data analysis is limited in qualitative models, such forecasts are better suited to short-term predictions.


There are two kinds of analysis that fall within qualitative models:

  • Market Research and Analysis: Here, data is gathered from surveys, questionnaires and interviews. Then, the opinions and current trends are used to determine possible future trends and outcomes.
  • Delphi Method: Here, field experts and reputed figures in the industry provide their opinions on possible future outcomes.


In both these cases, opinions are mainly used to make predictions. Qualitative models are highly dependent on human opinion, which is in stark contrast to the next set of models.

Quantitative Analysis:

More commonly used than qualitative analysis, here, data is gathered and used to make forecasts. The idea is that the past informs the future. By gathering and analyzing history, businesses can avoid the same pitfalls and make better decisions about the future.


Quantitative analysis removes the need for human opinion, and instead relies solely on data. Variables are selected that align with the analysis being conducted, and then that data is used to make predictions.

The common kinds of qualitative analysis include:

  • Econometric Modeling: Data is gathered and analysed. Then the consistency of that data is repeatedly gauged by checking whether the variables correspond to real life scenarios over time. This gives this model a high degree of reliability for forecasters. Data analysed can also be used for long-term decision making.
  • Indicator Modeling: A much simpler model, the relationship between selected variables are analysed to understand how they will interact in the future.


A third statistical model is also often used, known as the casual statistical model. An example of how this is used can be seen in the time series methods. Essentially, historical data is used to make future forecasts.

How Are Business Forecasts Made?

The process of making business forecasts is relatively simple. It involves:

  1. Asking the Question: Why is the analysis being conducted? What forecasts are being asked for? How are they likey to be used?
  2. Gathering Data: Variables are selected that can answer the question that was asked in the previous step. Then, data related to those variables are gathered.
  3. Assumptions: Analysts don’t have unlimited time to make forecasts. To get faster forecasts, they begin the process by making certain assumptions about the future. These are usually done for common and accepted ideas about upcoming trends.
  4. Statistical Model: Next, a statistical model that can best answer the question is utilised.
  5. Analysis: Then, the chosen statistical model is used to make forecasts.
  6. Success Rate: The last step comes into play in the long-term. Here, analysts verify whether the forecasts were successful or not.

Business forecasting is necessary for business owners that want longevity and continued growth for their businesses. Conducting a business forecast doesn’t necessarily guarantee accurate predictions, but the results still provide guidance that can save businesses. Making informed decisions based on data or expert opinions can help businesses succeed and sustain past turbulent scenarios.


Aside from business forecasting, there are other ways you can protect your business as well. Consider getting business insurance and find coverage in case your business is ever at risk.

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