Business forecast

What is a business forecast?

Business forecasting involves making wise guesses about certain business indicators, regardless of whether they reflect specific conditions of the business, such as sales growth, or forecasts for the entire economy. Financial and operational decisions are made based on economic conditions and future conditions, although there are uncertainties.

Key points:

  • Forecasts are valuable to companies, so they can make smart business decisions.
  • Financial forecasting is fundamentally an informed guess, and relying on past data and methods that cannot contain certain variables is risky.
  • Forecasting methods include qualitative models and quantitative models.

The basis of business forecasting

Understand business forecasts

Companies use forecasts to help them develop business strategies. Past data is collected and analyzed so that patterns can be found. Today, big data and artificial intelligence have changed the method of business forecasting. There are several different ways to make business forecasts. All methods belong to one of two general methods: qualitative and quantitative.

Although there may be significant differences in business forecasts at the practical level, at the conceptual level, most forecasts follow the same process:

  1. Choose a question or data point. This might be similar to “Will people buy high-end coffee machines?” or “What are our sales in March next year?”
  2. Choose theoretical variables and ideal data sets. This is where the forecaster determines the relevant variables that need to be considered and decides how to collect the data.
  3. Assuming time. In order to reduce the time and data required to make predictions, forecasters will make some clear assumptions to simplify the process.
  4. A model is selected. The forecaster chooses a model that fits the data set, selected variables, and assumptions.
  5. analyze. Use this model to analyze data and make predictions based on the analysis.
  6. confirm. Compare the prediction with what actually happened to identify the problem, adjust some variables, or predict accurately in rare cases, pat yourself on the back.

Once the analysis is verified, it must be compressed into an appropriate format so that the results can be easily communicated to stakeholders or decision makers. Data visualization and presentation skills are helpful here.

Types of business forecasts

There are two key types of models used in business forecasting-qualitative models and quantitative models.

Qualitative model

Qualitative models are usually successful in short-term forecasting, where the scope of forecasting is limited. Qualitative forecasts can be considered expert-driven because they rely on market experts or the entire market to weigh informed consensus.

Qualitative models can be used to predict the short-term success of companies, products, and services, but they have limitations due to reliance on opinions from measurable data. Qualitative models include:

  1. Market research: Conduct public opinion surveys on a large number of people for a particular product or service to predict how many people will buy or use it after its launch.
  2. Delphi method: Solicit general opinions from on-site experts, and then compile them into predictions.

Quantitative model

Quantitative models do not consider expert factors and try to remove human factors from the analysis. These methods only focus on the data and avoid the fickle people behind the numbers. These methods also try to predict the long-term position of variables such as sales, gross domestic product, and housing prices, in months or years. Quantitative models include:

  1. Index method: The index method depends on the relationship between certain indicators, for example, GDP and unemployment rate remain relatively constant over time. By tracking relationships and then leading indicators, you can use leading indicator data to estimate the performance of lagging indicators.
  2. Econometric model: This is a more mathematically rigorous version of the indicator method. The econometric model does not assume that the relationship remains the same, but rather tests the internal consistency of the data set over time and the importance or strength of the relationship between the data sets. Econometric models are used to create custom indicators for more targeted methods. However, econometric models are more commonly used in academic fields to evaluate economic policies.
  3. Time series method: Time series use past data to predict future events. The difference between time series methods lies in the details, such as giving more weight to newer data or discounting certain outliers. By tracking what happened in the past, forecasters hope to at least have a better than average view of the future. This is the most common type of business forecasting because it is cheap and not better or worse than other methods.

Criticism of predictions

Predictions can be dangerous. Forecasts have become the focus of attention of companies and governments, and by presenting a predetermined short- to long-term future, they mentally limit their scope of action. In addition, predictions can easily collapse due to random elements that cannot be incorporated into the model, or they may be completely wrong from the beginning.

But business forecasting is critical to companies because it allows them to plan production, financing, and other strategies. However, there are three problems with relying on forecasts:

  1. The data is always out of date. Historical data is the only thing we need to do, and there is no guarantee that the past situation will continue in the future.
  2. It is impossible to take into account unique or unexpected events or externalities. Assumptions are dangerous. For example, suppose that banks have properly screened borrowers before the subprime mortgage crisis. As our reliance on forecasts increases, black swan events become more and more common.
  3. The forecast cannot integrate its own influence. Through accurate or inaccurate predictions, the behavior of companies will be affected by factors that cannot be included as variables. This is a conceptual knot. In the worst case, management becomes a slave to historical data and trends, rather than worrying about what the company is doing now.

Regardless of negative factors, business forecasts will continue to exist. If used properly, forecasts can allow companies to plan ahead to meet their needs, thereby increasing their chances of staying competitive in the market. This is one of the business forecasting features that all investors can appreciate.

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