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Data scientists are often called on to predict future events.
There are four main types of forecasting methods that financial analysts are likely to use.
• Perform financial forecasting
• Reporting, and operational metrics tracking
• Analyse financial data
• Create financial models use to predict future revenues
3.1.2 Four common types of Forecasting Models
Businesses use forecasting models predict outcomes related to sales, supply and demand, consumer behaviour, etc. This
is possible through forecasting models. These models are used in the fields of sales and marketing. There are several
forecasting methods that businesses use that provide a wide range of information. The appeal of forecasting models,
whether simple or complex, stems from having a visual representation of expected outcomes.
Companies use these methods to improve their business practices and enhance the customer experience. Let us now
learn about the four main types of models or methods that companies use to predict actions:
• Time series model: This type of model uses historical data for reliable forecasting. Knowing how the variables
interact in terms of hours, weeks, months or years helps to better visualise patterns of data.
• Econometric model: People from an economic background usually use an econometric model to predict changes in
supply and demand, as well as prices. Throughout the process of creation, these models assimilate complex data and
knowledge. This statistical model proves valuable, when forecasting economic future developments.
• Judgemental forecasting model: This model uses subjective and intuitive information to make forecasts. In times
when there is no data accessible for reference, a judgemental forecasting model is used. Launching a new product or
facing uncertain market conditions also creates situations in which this model proves advantageous.
• The Delphi method: This method is often used to predict trends based on the information given by a think tank. This
series of steps is based on the Delphi method, which is about the Oracle of Delphi. It assumes that the answers given
by a group are more helpful and unbiased than those provided by a single person. Based on the objective or aim of
the group's researchers, the total number of rounds involved may vary.
Predicting future sales by using historical sales data and other information to make informed business decisions about
everything from inventory planning to running flash sales, making estimations about future customer demand is known as
demand forecasting. It also helps predict total sales and revenue.
3.1.3 advantages of Forecasting
Nearly all companies engage in forecasting. Forecasting provides companies an edge over their competitors. Let us
now learn about the advantages of forecasting in detail.
• Gaining valuable insight: Looking at past and real-time data is a pre-requisite to predict future demand through
forecasting. This will , in turn, help anticipate demand fluctuations more effectively. Also, it will give you an
understanding of your company’s health and provide you with an opportunity to make necessary amendments.
• Learning from past mistakes: You do not go back to square one after each forecast. Even if your prediction was
completely off the mark, you now know where to begin.You can easily analyse why things didn’t happen the way you
predicted. This will help you improve your predicting techniques. You can also reflect on your past achievements, as
introspection can be a powerful driver of company growth.
• Decreasing the life cycle costs: If demand forecasting is done the right way, it will help you modify your processes
to multiply your efficiency all along the supply chain. Anticipating what and when customers will demand aids in
reducing excess inventory and increasing gross profitability.
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