What is the principle and functioning of business forecasting?In order to choose the most relevant sales forecasting methods and understand what they can bring to the company, it is first necessary to understand precisely what the concept of sales forecasting encompasses. Indeed, even if this concept seems simple to define, it integrates in reality a multitude of data, techniques and stakes, which it is necessary to master to produce relevant results.
In order to help you know everything about sales forecasting, we go into detail about the interest of creating a forecasting plan, the factors to take into consideration and everything you can get out of a reliable forecast. Your sales performance and turnover will undoubtedly improve!
Why make sales forecasts?
For any company, the short, medium and long term vision is essential to anticipate difficulties and seize opportunities. Sales forecasts are a central variable in order to be able to see more clearly into the commercial and financial future. But what are the stakes of sales forecasting in a concrete way and on which departments of a company do they have an impact?
Sales forecasting to optimize the logistics modelEstimating the quantity of items to be sold is first of all a way to anticipate the production and inventory of goods. This will allow you to avoid stock-outs which have repercussions on the turnover and the reputation of the company with the customers. It is also a way to avoid overstocking, which can be very costly.
Without forecasting, the risk is simply to disorganize the Supply Chain, both in terms of internal warehouse management and logistics flows.
Anticipating human resources needs through forecasts
If the forecast results indicate a potential increase in the number of products sold or services to be delivered, staffing needs should be adjusted accordingly. If not, it will be necessary to consider reducing the number of hours worked, or even laying off staff if the forecasts show a decrease in sales over the longer term. Forecasting sales therefore also means optimizing human resources management in order to produce sufficient quantities and reduce costs.
Forecasting as a driver for the sales team
Sales are primarily the domain of the sales and marketing teams. By making forecasts, whether through the sales pipeline method, historical data or market research, you can adapt the company's strategy. It is a way to define new objectives and to determine the weak points of the purchasing process, in order to implement the necessary actions to increase the conversion rate, build customer loyalty, etc.
Optimizing the company's offer on the basis of forecasts
Being able to forecast sales is also essential to "sorting out" the company's product and service portfolio. Using forecasts, combined with other marketing data, managers are able to determine whether a particular item should be discontinued, promoted, etc. The idea is to achieve optimal profitability by selecting the products with the most promising forecasts.
What information should be taken into account to anticipate sales?
A good sales forecast cannot do without reliable, varied and numerous information. Depending on the forecasting method chosen, the data needed for a sales forecast will vary, but it is possible to establish a list of typical parameters that are generally found in a sales forecasting plan.
Data specific to the products involved
To estimate the future sales of a product, it is necessary to have several pieces of information about it:
- quantities sold during the last month, quarter or year;
- sales price of the product;
- sales cycle;
- conversion rate;
- purchase frequency;
- new customer/loyal customer split, etc.
The data used depends on the method chosen: for example, the historical data method uses only sales from previous periods, whereas the sales pipeline method involves looking closely at the ongoing customer qualification and acquisition process. And when the multi-variable analysis method is preferred, a much greater variety of data needs to be combined.
Information on logistics and production capacity
Having knowledge of internal sales data as such is not enough to make a business forecast. It is also necessary to consider the quantity of services or products that the company is ready to provide or produce. To do this, you need to use indicators such as warehouse availability, productivity, number of days' inventory in advance, scrap rate, delivery times, etc.
External data that affect the quantity of products sold
Some companies are content to use internally collected data to forecast the level of activity for the coming quarter or year. However, the importance of external factors should not be overlooked, some of which can be measured with varying degrees of accuracy:
- short-term weather or trend over the year;
- seasonality of sales, reflected by a seasonality coefficient, for example;
- vacation periods and public holidays;
- positioning in relation to the competition, in terms of price and range;
- changes in consumer needs, determined through market research, for example;
- development of new technologies, etc.
Of course, not all of these external factors are relevant: they must be taken into consideration according to your company's line of business and assessments of their impact on previous sales.
What elements can call into question the forecasts?Even if you try to take as much hard data as possible into consideration, sales forecasting is never 100% certain. However, it is possible to reduce the probability of error and implement procedures to manage this risk by being aware of the factors that influence the sales forecast.
The economic situation is one of these factors, because although it is possible to assess a trend, unexpected events can quickly change the situation. Examples are the subprime crisis, armed conflicts in strategic locations around the world or the coronavirus health crisis.
Other elements can disrupt a brand's reputation and thus cause its sales to drop substantially. This can happen when a brand's muse is involved in a scandal, when employees' working conditions and company ethics are widely questioned, when conflicts of interest taint the image of a company director, etc. Nowadays, these difficulties are even more numerous and unpredictable with social media and the easy access to continuous information.
Technical and computer problems also represent a danger for companies and can call into question the established forecasts. A hosting company that experiences a large-scale outage or a group of hackers that steals data or freezes the use of workstations, and the company is directly impacted.
Even if some of these problems can be anticipated, it is important to keep in mind that sales forecasts can be a solid basis for the sustainability of a company's activity, but that they can always include a more or less significant margin of error. Forecasting is a probability, not a certainty.
What are the data that emerge from a forecast plan?
Now you know the ins and outs of the sales forecasting process. But you may still have questions about the actual results that come from these estimates. Don't worry, here are some of the important elements that constitute the sales forecast and the type of data you will find in the forecast tables and graphs coming from a CRM or other forecasting software.
The first important piece of information is the time frame, i.e. the forecast horizon (one week, one month, several years, etc.) and the breakdown of the different forecast periods (daily, weekly, etc.).
Next, there are the figures for the sales for each period. This can be the number of articles/services sold, but also the calculation of the projected turnover (volume/value distinction).
In addition, comparative elements such as growth rates, conversion rates, etc. can be added.
A complete CRM software coupled with a WMS will also help you to plan your logistics and to establish your commercial objectives. Indeed, depending on the estimated forecasts and taking into account data from the warehouse or the sales team, it can tell you how to manage stocks, how many quantities to produce on average each day, when to place orders for goods, etc.
By opting for a more sophisticated solution, integrating a machine learning model for example, you can benefit from even more and more precise decision support. This includes the optimization of sales prices and promotional offers. The new generation of sales forecasting becomes a much more efficient tool, allowing you to optimize your business from the purchase of raw materials and other goods, to the point of sale where you meet the end customer.
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