The disruption caused by the pandemic created an environment of uncertainty in the business landscape. In order to properly allocate their resources, business owners need to determine the direction of trends through data and analytics. Knowing where the business is headed with regard to sales, profits and expenses helps keep it afloat or moving forward towards revenue goals, especially during crisis.
Revenue forecasting models, market share forecasting and consumer trends are things that every small business owner needs to strategically allocate their budget for the best possible timeline results.
Qualitative vs. Quantitative Forecasts
Creating forecasts are very methodical, although the processes and calculations vary depending on purpose and how specific you need them to be. Qualitative models are generally more useful with short-term predictions because they are based on judgment and opinion. They make it a point to account for nuances in experience or for intuition to be involved in predicting trends.
Quantitative ones, however, try to eliminate inconsistent analytic elements while focusing on mathematical data. Forecasts are likely to include numerical variables like sales, GDP, housing prices and so on. These forecasting methods make use of historical data to identify important patterns and pattern changes, as well as to establish causal relationships between shifting variables.
Common Revenue Forecasting Methods:
The methods below have varying levels of accuracy depending on the time frame and factors considered. For more accurate results, accountants and business advisers can combine them to make methodologies more comprehensive. They can also use two separate methodologies (qualitative and quantitative) at the same time. Here are the most commonly used and most reliable ones so far:
Market research is a process of sampling representative groups within the market to predict consumer reception once a product or service is launched. This can be convenient for businesses to use when researching for a product launch or looking at how well one service is competing over the other
The Delphi Method
This involves a group of industry experts that can be asked to respond through a series of differing questionnaires about their opinion on current trends. This method aims to reach an accurate answer through a series of questions that would lead to a consensus.
The Indicator Approach utilizes a mathematical formula to determine which indicators are leading, a forecast is made based on fluctuations in sales when these indicators are changed. This approach relies heavily on testing the relationship of certain indicators while the relationship of other factors remain relatively consistent over time.
Instead of assuming that some relationships remain unchanged, this tool includes testing their significance and strength when making a forecast. As a more comprehensive approach than the one above, it is able to present causality and significant turning points more clearly.
This refers to a variety of more specific methodologies relying on past data to find patterns and pattern changes. It is the most common type of forecasting method because business owners usually already have the data they need to track gradual pattern shifts over time – for instance, in analysing financial statements. Each method can include or discount specific factors like how recent the data is and which outliers are more likely to be inconclusive.
Artificial Intelligence Methods
With the advancement of artificial intelligence (AI), businesses are now able use AI to produce accurate forecasts from tremendous volume of data. As AI technology becomes more accessible, small businesses can now employ AI to assist with finance and accounting, human resources, operations, data analytics, and revenue forecasting.
Refocusing your finances is easier when your business has the right numbers to fall back on. Forecasts are the closest you will get to achieving certainty about the future, as well as using the right methods and the right data to make a well-informed business decision.
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This article was first posted 25 February 2015 and edited 30 September 2020