Demand Forecast (BF) Module
|Module||Demand Forecast (BF: Baseline Forecast)|
|Overview||Forecast future demand using a combination of past sales performance and various external and internal data sources that impact sales volume. Utilize advanced statistical methods or machine learning techniques to accurately predict future demand trends and optimize sales strategies.|
|Features||By considering various product characteristics such as sales volume and profit margin, we provide guidelines for identifying the items that should be subject to demand forecasting and items that should be focused on for intentional sales growth.
We utilize multiple statistical methods to provide you with the most suitable approach for your specific needs. These methods include:
|Users||The sales representative, sales base sales company manager, and company-wide sales planning management department (such as a Global SCM Department) are all key roles within an organization that play a critical role in driving sales growth and achieving company-wide sales targets.
The sales representative is responsible for direct interaction with customers, identifying new sales opportunities, and closing deals. The sales base sales company manager is responsible for managing a team of sales representatives and ensuring that sales targets are met.
The company-wide sales planning management department, such as a Global SCM Department, is responsible for creating and implementing sales strategies at a company-wide level, coordinating with other departments and divisions, monitoring performance and results, and making necessary adjustments to sales plans to achieve company goals. This department also plays a key role in forecasting future demand and identifying new sales opportunities, working closely with the sales representatives and sales base sales company managers to develop effective sales strategies.
|Planning Cycle||A sales plan is established typically using a monthly or weekly cycle.
A monthly sales plan cycle would involve setting sales targets for the upcoming month, creating a strategy to achieve those targets, and then monitoring progress throughout the month. At the end of the month, the sales team would review their performance and make adjustments to their strategy for the next month. This cycle would repeat itself on a monthly basis, allowing the sales team to make adjustments to their strategy in response to market changes or other external factors.
A weekly sales plan cycle would work in a similar way, but with a shorter time frame. In this case, the sales team would set targets for the upcoming week, create a strategy to achieve those targets, and then monitor progress throughout the week. At the end of the week, the sales team would review their performance and make adjustments to their strategy for the next week. This cycle would repeat itself on a weekly basis, providing the sales team with a more frequent opportunity to make adjustments to their strategy in response to market changes or other external factors.
Both these cycles are examples of how a sales plan can be structured, it depends on the nature of the business and the industry to decide which one is more suitable for them.
|Benefits||For products or items for which the demand forecast result is deemed reliable and accurate, it is possible to automate the sales plan by directly linking it with the demand forecast. This approach allows for a more efficient and streamlined sales process, as the forecasted demand can be used to automatically generate production schedules, order quantities, and inventory levels. Additionally, by linking the forecasted demand with the sales plan, organizations can better anticipate changes in customer demand, and adjust their sales strategies accordingly.
This automation can be achieved through the implementation of advanced technologies such as enterprise resource planning (ERP) systems and inventory management systems, which can integrate data from various sources and generate automated sales plans based on the demand forecast. This approach can help organizations to save time, reduce costs, and improve the overall efficiency of their sales operations.
Moreover, with the automation of the sales plan, companies can focus more on analyzing and interpreting the data, and less on manual data entry and calculations, allowing them to make more informed decisions. This approach can also help to minimize the risk of human errors, and increase the accuracy of the forecasted demand.