Business Forecasting | 11 mins read

Guide to Choosing the Right Business Forecasting Strategy

guide to choosing the right business forecasting strategy
Jin Hyun

By Jin Hyun

A business forecast uses the experience, insights, analytics and data to make reliable predictions about the future of a business.

While choosing a method is far from a one-size-fits-all solution, by understanding the purpose of forecasting, businesses can easily make informed decisions on which strategy will produce the most accurate results for their specific needs.

The best strategies will combine information collected from past data and current sales information to create an accurate picture regarding the future of the business. When companies know what happened in the past and why it happened, they will have a better understanding of what is likely to take place in the future.

How much of a specific product will customers want to purchase within a particular season? What is the best time to stock up on inventory? Are there days your business would benefit from longer operating hours? These are all questions that an in-depth business forecasting strategy can address.

Regardless of the industry, without the help of accurate forecast information, it will be near impossible to optimize the workforce and sales profits.

The Importance of Accurate Labor and Inventory Forecasts

Local stores in North America lose money every day to e-commerce websites because they fail to forecast accurately. Customers looking to purchase specific products often turn to platforms such as when their local retailers are out-of-stock.

This explains why a 10-year survey of out-of-stocks suggested that as much as 24% of Amazon's annual revenue could be coming from consumers who could not find the products they were shopping for at their local stores.

Since 2005, e-commerce businesses (including Amazon) have added over $27.8 billion in apparel revenue while department stores have lost $29.6 billion during the same period. Add this to the results of a study from the IHL Group which showed retailers had lost $1.75 trillion due to the consequences of overstocking or under-stocking in 2015, and we can begin to see a clear pattern.

All of these factors have contributed to the increasing number of offline retailers closing their doors across the US. The closure of major offline stores such as Toys R Us and Sears captured the attention of news headlines.

Meanwhile, business owners braced for impact as analyses revealed that 2019 saw more offline store closures than the total recorded in 2008 (the Great Recession). The growing online competition and the decline of malls make forecasting even more important for businesses with physical storefronts.

Accurate labor and inventory forecasting don't just help predict and manage product demand; they also help in managing cash flow and keeping operations as efficient as possible.

Just as stocking up on certain items without paying adequate attention to demand can lead to wastage, having more employees working than necessary for certain periods of time, would be an inefficient use of funds.

Benefits of Using POS Data

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The Point of Sale (POS) system is much more than just a simple device to process card payments. Modernized, cloud-based POS systems on the market today hold valuable information from sales transactions that can be applied directly to the business forecasting strategy.

Most systems seamlessly integrate with business accounting and management software, which means businesses have all sales volume and labor-related data conveniently available in one report.

POS data is also used to produce accurate sales and labor predictions by-

1. Ensuring Optimal Inventory and Stock Levels
Sales forecasting is generally based on monitoring historical activity for a specific time period. This eases the process of making important decisions about inventory and eliminates the need for guesswork.

For instance, tracking sales from last year's holiday season can provide a reliable picture of anticipated demand in the coming holiday months, allowing for more accurate preparation.

Many common issues plaguing businesses around the country such as inefficiency, excessive waste and high costs, are the result of poor inventory planning when businesses fail to realize their stock has dwindled or run out, while others are subject to overstocking.

Accurate forecasting and inventory monitoring can save the business as much as 10% in overall costs, all of which can be accomplished through the use of software solutions.

2. Improved Customer Behavior Monitoring
There are many factors that can affect customer behavior. Poor weather, special sporting events, traffic, holidays, seasonal changes, are all examples of circumstances that can influence traffic to a business. Modern POS systems make it easier to store sales data while also taking these factors into consideration.

The datasets will give deeper insights into how customers are influenced and ensure appropriate preparation during peak times. The analysis can also highlight key opportunities to bring in more revenue.

3. Better Staff-related Decisions
Staff-related costs can make up one of the biggest percentages of the overall budget. Using POS-based forecasting data, businesses can make informed decisions and get more ROI instead of losing money.

With an accurate sales forecast, it's possible to optimize labor by matching employee schedules to the expected volume of patronage. Whether the business operates in the food, retail or hospitality industries, the customer experience suffers when there isn't enough staff on hand.

Understaffing is one of the main reasons for negative reviews. If customers are unhappy with the speed of delivery and choose to express their thoughts on review platforms, the brand will lose prospective clients.

Additionally, if staff members are overworked, the employee turnover rate will likely increase. This revolving door can increase the overall cost of onboarding and may also affect the company's bottom line, as new hires will have to be trained before becoming fully independent.

Overstaffing, on the other hand, will lead to wasted funds and decreased productivity. When there are too many employees working during slower periods, the business will be wasting resources on unnecessary labor costs.

Depending on the business and their unique goals, using POS data for forecasting may not be enough. There are additional qualitative and quantitative forecasting techniques that can further increase the chances of producing more accurate predictions, especially when combined with the POS data.

Quantitative BusinessForecasting Techniques

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Quantitative sales forecasting techniques predict potential future revenue by using objective sets of historical sales data. This method is well-suited for longterm forecasts and eliminates room for human bias as it focuses on statistical methods involving quantifiable information to predict future demand in numerical reports. Some of these techniques may include-

Historical Growth Rate
This technique uses data from one historical period to predict what will happen over the same period in the future. The time window can be weekly, monthly or yearly.


  • Easily verifiable
  • Data can be updated or refined whenever needed
  • Newer businesses may not have enough data to work with
  • Historical data may not give an accurate picture of new trends

Linear Extensions
With this option, the past sales data is plotted on a chart, and a line is drawn through the middle of the points, extending it into the future.

  • Easily processed in most spreadsheet applications
  • Straightforward visual presentation
  • Sales revenues rarely increase linearly

Run Rate
This is an average calculated from past sales data. It is generated by calculating the total revenue divided by the sum of the past sales period.

  • It is used to forecast revenue for the remainder of a period
  • It gives more accurate short-term forecasts
  • It is not too forward-looking

Simple Moving Average

This technique is similar to the run rate because it also involves gathering sales data from a specified period. However, the period is dynamic.

  • Generally more accurate than other techniques
  • Best for industries with a lot of fluctuation
  • More difficult to calculate

All quantitative methods have their own pros and cons. It is important, therefore, to use options that best reflect the business' needs.

Qualitative Business Forecasting Techniques

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Qualitative methods are useful when creating short-term forecasts. They are best used in conjunction with quantitative sales forecasting techniques as they rely on opinion-based tactics such as the survey method. Some of the most popular qualitative forecasting models include-

Executive opinions
This option collates the subjective views of a jury of executive and key players in the business to generate a forecast about future sales and business activity. The views are often collected in a group.


  • Quick forecasts without dissecting elaborate statistics
  • Feasible forecast option in the absence of data
  • There is a risk of group-think
  • Personal biases may affect the accuracy

Delphi method
With this technique, a group of experts and high-ranking personnel are interviewed to find out their opinions on sales forecasts. However, the interviews are done individually to reduce the impact of groupthink, and the average of the group's views are adopted as the forecast.

It is similar to the Executive Opinions method, but instead of meeting the key personnel in a group, they are approached individually. Their opinions are collated separately and analyzed by an independent body.

  • Useful for long-range forecasting
  • No need to form a committee or hold a debate
  • No fear of group-think or peer pressure
  • Lack of consensus can lead to prolonged back and forth with participants

Sales personnel polling
Businesses that use this technique seek the opinions of customer-facing staff members to find out what they think about future sales prospects. The opinions can be averaged to form a forecast or combined with other techniques.

  • It is simple to understand
  • The information can be broken down by product, customer, sales personnel, etc.
  • Since they are involved in the process, sales personnel tend to feel responsible for actualizing the forecast
  • Sales personnel can be overly pessimistic or optimistic with their predictions
  • Economic situations outside the control of the personnel are not taken into consideration

Consumer surveys
In the qualitative technique, companies run a market survey based on specific consumer purchases. The surveys can be collated over the phone, in-person or through questionnaires. The responses are analyzed statistically to create actionable insights.

  • It is an easy approach
  • It can save research costs
  • You will see trends quickly
  • It may be hard to get enough respondents to complete a survey
  • Survey fatigue could lead to biased respondents

It's important to remember that qualitative sales forecasting techniques are not always reliant on their own. They have to be combined with other options to generate reliable results. The key personnel you should be looking to collaborate within your qualitative forecasting include the manager, departmental heads, and supervisors.

How Can Small Businesses Forecast Like Franchises?

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Many small or new businesses ignore sales forecasting because they have limited resources and very little information to work with, unlike larger brands that have accumulated years' worth of data. Nevertheless, it's entirely possible to produce reliable projections to guide the business to success.

Use Qualitative Techniques
Without solid data to rely on, it makes sense to use some of the qualitative techniques to get started with rough predictions. Work with the managers, customer service personnel, and staff members in a business to test qualitative approaches like the Delphi method. If a business already has decent foot traffic, consumer surveys can also be effective.

Use Data From POS Systems and Management Software
If the business is at least six months old, there are already existing datasets to work with on the POS or management software. Pull as many sales and labor data as possible and combine them with qualitative analysis to generate more accurate predictions. Some of the data available from a POS analysis include product affinity (products bought together), order history, sales trends, returns/refunds, etc.

Learn From Inaccurate Projections
During the early stages of a business, it's possible to make some mistakes with sales predictions. Use the incorrect forecasts to fine-tune the method for future use until it's possible to start producing consistently accurate projections. Some common causes of inaccurate sales predictions include-

  • Lack of data
  • Cherry-picking of available data
  • Oversimplification
When businesses can understand why their projections missed the mark, they can avoid repeating those same mistakes in the future.

Necessary Variables

To produce the most effective results, the sales forecasting strategy should incorporate the following variables-

  • Daily capacity of premises
  • Cost of goods sold
  • Packaging cost
  • Costs of materials and supplies
  • Direct labor costs

Benefits of Automation

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Technological advancement means businesses no longer have to worry about manual forecasting. With the right software, it's possible to generate accurate predictions for a business, by taking into consideration factors affecting demand such as economic conditions, business laws, and seasonal trends with minimal effort.

Choosing the right automation software can improve customer experience, ensure less inventory waste, and ultimately increase profits. When inaccurate data causes businesses to miss sales targets, it could lead to deeper problems such as a loss of confidence in the brand by employees, inability to pay staff and vendors due to cash flow constraints, or loss of invested capital. With automated business forecasting software, companies can have more realistic projections with less effort.

Automation also frees up time for managers and staff members. The work hours that will ordinarily go into analyzing data in excel sheets can be put to good use elsewhere.

Helpful Software Features

Some of the features businesses can expect from an automated sales forecast solution include-

  • Demand forecast- This allows companies to create a forecast on a weekly, monthly and yearly basis. They can also generate forecasts for specific products or product categories.
  • Revenue planning- With this feature, businesses can create a sales forecast for a specific period. They can combine current sales prices with historical data to generate revenue forecasts.
  • Approval system- This allows businesses to view and approve generated forecasts or flag them for further attention.
  • Import functions- This enables integration with spreadsheet applications, accounting software, and more.
  • Collaboration- This feature allows team members to forecast collaboratively. Automated solutions that allow collaboration make it easy to see authors of notes and edits.
  • Reporting- This enables users to share the forecast via several mediums. It should also allow them to generate a PDF or share the forecast through email or social sharing.

For any business, the difference between profits and losses could come down to just how well they can handle busy days and react during downtimes.

With the right business forecasting strategy, companies can always stay ahead of the curve, knowing exactly what season they are about to enter and make informed data-driven business decisions.