3 Ways Predictive Sales Forecasting Software Can Drive Profits

What is Predictive Sales Forecasting?

Sales Forecasting
In basic terms, forecasting can be defined as a technique that talks about the possible future value of a selected data. If we apply the definition of forecasting model to sales , sales forecasting can be termed as predicting revenue based on the amount of sales of a particular product in the upcoming months or years based on the past sales of products , services. Accurate sales forecast enable a business to predict future sales performance in the short and long term.

Predictive sales forecasting
Predictive sales forecasting is an extension of classic forecasting method. It is a data driven process which takes into account multiple of inputs, values, trends, cycles and fluctuations in different business areas to predict future sales. The process of forecasting sales enables a business to make better decisions based on comprehensive and analytical insights.
A data driven predictive forecasting model makes use of historical data to predict sales trends based on seasonality and current sales performance.
Sales forecast based on historical sales patterns can help a restaurant take into account seasonal demand to optimise staffing and ensure better inventory management. An accurate sales forecast is the building block for a restaurant to manage future sales, expenses, profits, and growth.

Why is Predictive Sales Forecasting Important?

Most businesses say that making a sales forecast is still a major challenge. As per a Gartner report on sales, over 50 percent of those polled still have difficulty making accurate sales forecasts based on past average sales and sales performance. Most sales forecasts are based on historical sales data, current market situation and the gut instinct of the sales team, which introduces human bias in forecast accuracy.

But predictive sales forecasting method can help a business predict its revenue. The forecasting method views historical and real time data to identify sales patterns, understand market trends and improve sales. The forecasting method takes into account variables such as search queries, competitor prices and extraordinary events.

Here are some key benefits of predictive sales forecasting

• A company can efficiently allocate resources for future growth based on accurate sales forecast. It also helps a business manage the cash flow.
• Sales forecasts can help a business set benchmarks and allows for course correction in case of any extraordinary event like a natural calamity or launch of new product. The data analytics can help sales team leaders set sales quotas to optimise revenue expectations.

How is Predictive Sales Forecasting Conventionally Done?

A business can optimise the production capacity and material purchase to ensure optimum business sales with accurate sales forecasts. Conventionally, forecasting models can be divided into three patterns.

• Qualitative techniques

Qualitative sales forecasting method uses experts' experience, expertise, and instinct to predict numerical sales forecasts. The method also takes into account customer opinions about their new product needs and also check with distributors about sales of products. Most of these techniques are better for forecasts of sales cycles of upto three months.
Qualitative forecasting methods are quick and generally don't need elaborate statistics. They also improve sales forecast by taking into account factors like state of economy, shortages and new product launches. These methods are also useful when there is not enough data and can give a more broad-based view.

On the other hand, these methods need a lot of time and resources and the Forecast Accuracy may not be as high as compared to some quantitative forecasting methods. Sometimes sales reps can be overly optimistic or pessimistic about predictive sales.

• Quantitative methods

The quantitative sales forecasting process relies only on historical data to predict the trajectory of sales. The method puts to use data on sales so that business can see past and future trends. The process then derives to forecast future sales. The quantitative methods are used to forecast sales for up to a year.
The forecast method is objective and unbiased as it uses historical data to decide on future sales operations. The method also puts forth past trends of spending, sales, and scheduling and their consistency. This allows a business to make changes to supply chain, workforce or inventory management in an average sales cycle.
But the method, while producing clear forecast sales data, does not allow businesses to account for external factors which can impact sales. The cost is also high compared to qualitative demand forecasting methods. But this can be easily addressed by using affordable business sales forecasting software.

• Causal models

As per a report in Harvard Business Review, a causal model is the forecasting process that takes into account everything known of the dynamics of the flow system and utilizes predictions of related events such as competitive actions, strikes, and promotions'.
The data required is not limited to a company's internal sales data but also needs external data like surveys, product features, social chatter, etc. Usually, causal models are continuously revised to make sure the latest information is incorporated. The model is used for planning sales forecasts for a period of quarter , year.

Predictive Sales Forecasting and the POS System

Sales forecasting software
A restaurant or a business is dependent on accurate sales forecasts to be able to create sales, inventory levels, staffing requirements and important trends. Using predictive sales forecasting software can help a business make precise predictions to predict future sales demand.
Automated predictive forecasting can impact sales as it allows continuous adjustment of forecasts to help identify new opportunities and risks. A machine learning approach allows a business to speed up data processing, provide more accurate sales forecast and automate forecast.

POS System
A Point of Sale (POS) system records data every time a business makes a sale. These systems also track inventory counts, helping eliminate problems such as over-spending, product shortages, and excess waste.
Data from the POS system will help businesses process sales information and analyse trends for forecasting process. The business can optimize store management, improve customer relations, boost reputation, therefore increase sales.
An efficient POS system data can help a business make sure that popular items are kept in stock to ensure maximum profitability. A modern, cloud-based POS systems can be seamlessly integrated with sales forecasting software in real time so there is no need for any manual data collection.

3 Ways Predictive Sales Forecasting Software Can Drive Profits

Predictive sales forecasting is important for a business as accurate forecasts can help a business plan sales operations effectively, which in turn can maximise profits.
Here are three ways that a predictive sales forecasting software can drive profits

1. Improve planning and performance of sales team
Sales forecasting software can analyse if the total sales goals can be met or not. Marketing teams can implement strategies that drive additional leads and increase sales based on sales analytics and thus maximise profits. Sales managers can rework their strategies to achieve target set by the forecasting process to adjust their strategies to achieve the target. Predicting future revenue helps to improve the planning and this make makes sales forecasting important for the businesses.

2. Optimized inventory control
Sales forecasting can help a restaurant or any other retail business identify items which are popular with the customers. It can also identify the shift in demand for a particular item. POS information can also help a company create predictions based on historical data trends and make sure that specific products don't run out of stock, maximising profits.


3. Eliminating waste
Based on data provided by a sales forecasting process a business can limit the amount of waste or unsold inventory. Businesses that adopt new POS analyzing technology, such as forecasting software, will be in a position to gain a competitive edge.

Best Restaurant Software for Predictive Sales Forecasting

A restaurant or a business looking for a predictive sales forecasting software has to keep these points in mind.

• Metrics- A sales forecast is based on historical sales data or guest count data. A software that can be customised to the Key Performing indicators unique to your business is the best fit to your specific operations.
• Accessibility- A sales forecasting software should be easy to use. Most softwares with a cloud-based management platform are easy to use.
• Compatibility- The sales forecasting software programs a business opts for should be compatible with preexisting programs.

Based on the above-mentioned criteria, here are the top predictive sales forecasting softwares for restaurants

1. POS Cash Office- The predictive sales forecasting software generate forecasts of 15-minute increments to ensure accuracy. It assigns customized forecast matrices for each site. The sales forecasting process applies critical impacts like store or company events and utilizes historical trends to predict business results.
2. Tenzo AI- Tenzo's predictive sales forecasting software can predict sales for up to 21 days ahead. The algorithm uses historical sales data as well as local weather, holidays, and custom events. It claims that the sales forecasts are 50% more accurate than other methods.
3. a4restaurants- The predictive sales forecasting software examines the impact of different factors like weather, holidays, vacation seasons, trends, other products performance on total sales to predict future sales.

Predictive Sales Forecasting FAQs

But when opening a new business like a new restaurant, having an accurate sales forecast can be difficult as there is no historical data to make an informed decision. But one can still make sales data forecasts based on the following formula.
Restaurant Sales Forecast = Average Number of Guests X Average Per-Person Spend X Number of Days Open Per Week
Predictive Analytics gives sales management a boost as it looks for meaningful patterns in cumulative sales data and then build models that forecast future sales. For example, taking in account a customer's past buying pattern, it can predict how the customer may respond to a particular offer.
The business owner is normally responsible for sales forecasting for the restaurant. However, managers' inputs should also be taken into consideration as they can point out any unique circumstances that may impact the sales forecast.