Forecasting – Methods, Features, Process and Examples

Published by: Madhubala Minda

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What is Forecasting?

Forecasting is how information available from the past and current times can be used to predict future conditions. Specifically, it is the method of using information from data based on past trends in history to come up with good predictions that can be used to see what trends would be like in the future outcomes.

It uses trends and information from the past to help companies mitigate future risks. It is a device for planning that lets a company design a budget that can account for unforeseen hurdles in the coming years and decide its next steps.

How does Forecasting work? (Forecasting Methods)

There are two options available to any organization for prediction and business forecasting techniques: qualitative and quantitative methods.

1. Qualitative method

Qualitative forecasting gives subjective answers. They are also called judgemental methods, as these come from forecasters’ and specialists’ opinions and personal analyses. These tend not to be neutral as they are based on people’s experience, instinct, and expertise and not on a raw data set. It is not an arithmetic method.

2. Quantitative method

The quantitative forecasting methods are more factual and uniform. It chooses to use much quantitative information and not depend on instinct. Statistical forecasting analyses numbers and is a mathematical method using dependant variables, independent variables, etc. There are various statistical methods involved.

Budgeting vs. Forecasting

Many organizations use forecasting tools and budgeting to strategize for the future. However, there are key differences:

Budgeting is a document with some financial data points. This can be the investments, cash flow, costs, or income over a specific period. Companies use it for decision-making related to finance. Multiple departments pitch in to construct the budget. So, it is a time-intensive process.

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Although forecasting is done over a period of 3 or just one month, these are generally annual estimates. Financial forecasting allows the company to tweak the budget. So, the budget greatly rests on the forecasts. The company might choose to allocate resources in the budget according to the forecast.

Features of Forecasting

Features of Forecasting

Some qualities of forecasting are mentioned below

1. Focus on future events

Forecasting is integral to production planning as it tries to assess the future.

2. Uses current and historical data

Forecasts are derived from various important statistical data including, figures and facts. They also depend upon guesses, intuitions, and opinions. Before deciding the outcome of a forecast, many things must be considered. These contain vital information about the organization’s history and future sales.

3. Employ forecasting methods

The budgeting process and planning need quantitative data. It is used very frequently.

The Process of Forecasting

There is a detailed method that can reveal accurate information that has been highlighted below:

1. Create the foundations for forecasting

The company should start off by finding the state the organization is currently in. Then, it has to know why forecasting is needed. Finally, the company must also find the present position of the brand in the industry.

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2. Predict the forthcoming Business operations of the company

The investigation into the needs has to be done first. After that, future data and industry trends can be evaluated. It assesses and predicts how the organization will perform.

3. Modulate the forecast

This requires the company to assess all the forecasts that have been previously done. These must be paired against how the organization actually fared. The present forecast is compared to the past ones. The factors behind the differences are counted and evaluated.

4. Check the process

All steps are reviewed. Alterations and fine-tuning are carried out.

Sources of Data for Forecasting

1. Primary sources

Primary sources use first-hand data. Collecting this is time exhaustive. However, it is still highly dependable and can be very accurate. The information is gathered through focus groups, survey forms, interviews. The forecasters themselves gather this information.

2. Secondary sources

Secondary sources provide statistical data that has been gathered and printed by other people. Industry reports are a type of such data. The already gathered data has to be assessed, allowing the process to take less time.

Forecasting Examples

Forecasting Examples

1. Apple

Even with the pandemic all around, Apple predicted an incredible Q2 2022. There was a reason why Apple was optimistic about the quarter: Q1 2022 broke record numbers. A lot of unpredictability existed because of the pandemic. There were also supply disruptions. So the guidance was more vague. Nevertheless, CFO Luca Maestri claimed the company thinks the increase in income can be “solid on a year-over-year basis.”

Maestri held an Apple earnings call with analysts and stakeholders. On behalf of Apple, he claimed that the Q2 sales forecast predicted a bumper revenue in spite of serious supply hurdles that would be there in that period.

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Tim Cook also mentioned these barriers to supply in his interview with Wall Street Journal: ‘We saw supply constraints across most of our products.’ As Apple made its results public, Cook said, ‘We’re forecasting that we will be less [constrained] in March than we were in the December quarter.’

2. Tesla

Tesla’s Target: 20 Million EVs Sold Annually By 2030.

Tesla’s CEO, Elon Musk, manages to hog the limelight at every annual meeting for shareholders. However, there was a moment when Tesla’s Board Chair Robyn Denholm drew attention by stating, “By 2030, we are aiming to sell 20 million electric vehicles per year.”

In 2020, they barely managed to reach 500,00s cars, so naturally, this was an ambitious thing to say. Tesla is currently mushrooming at an alarming rate. Musk grabbed attention when he stated that the compound annual growth rate shot up by 71% since 4Q in 2016. This is accompanied by a more remarkable rise in the company’s stock prices.

“I think this might be the fastest that any large manufactured object has grown. Like – yes, certainly, one of the fastest, perhaps the fastest and it looks like we have a good chance of maintaining that [growth] into the future, really dependent on supplier challenges… but I feel confident of being able to maintain something like this, at least above 50% for quite a while,” Musk has stated on the expansions. There are reasons to be optimistic. Musk claims, “The Model 3 became the best-selling premium vehicle globally.” To top it off Musk, predicts, “We think the Model Y will be the best selling vehicle of any kind globally. So I think it will exceed the Model 3. I think we’ve got a good chance of it being the best-selling vehicle by revenue next year and then I think quite likely to be the best-selling vehicle in just – of any kind, numerically in 2023.”

Conclusion

Forecasting involves the different methods through which the future trends of a company are predicted. This involves the use of various data points. The relevant information is usually gathered from various present sources and historical data. This information can be of two types: qualitative and quantitative forecasting models. Qualitative information is also called judgemental information, as it relies more on the opinions and judgments of specialists than on solid data. Therefore, it is not always very reliable. Quantitative data relies more on mathematical processes with the use of figures and data points. It is more consistent and thus more reliable.

Forecasting is also often confused with budgeting, but the two are different. Budgeting is reliant upon short-term forecasting. Budgeting involves gathering and using financial data points to see how resources will be allocated over the course of a year with a long-term perspective. On the other hand, forecasting is done over the course of one to three months. The actual forecasting results are then used to make changes in the budget regarding resource allocation, etc.

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Article by:

Madhubala Minda

Madhubala Minda is a content writer for Digiaide. She writes unique and research-driven content on various Brands, Competitors, Management topics and wellness. With years of content writing under her belt, Madhu Bala is one of the strengthening pillars of Digiaide content team.