Demand planning is a process in supply chain management that helps companies to plan future demand for a product or service and execute an operational strategy to successfully adjust the output accordingly, balancing sufficient inventory levels with customer demand without having a surplus.
Demand forecasting is a vital part of production planning, usually impacting strategic, long-term decisions that affect budgeting, financial planning, capacity planning, sales and marketing, and capital expenditure.
Effective demand planning often requires demand forecasting methods to predict demand trends accurately, bringing added benefits, such as increased efficiency and customer satisfaction.
Demand planning requires sales and consumer trends analysis, seasonal data, statistical forecasts, demand history, and the use of effective statistical models. Demand management works through several functions integrated into supply and demand processes, including demand planning, supply planning, sales, and marketing.
Demand planning is the cornerstone for effective supply chain management, assisting companies in driving efficiency by improving the management and allocation of inventory space.
Demand planning can help businesses avoid the risk of overstocking — such as increased inventory carrying costs and financial conditions that require discounts or other temporary measures to prevent overstocking by selling stock as quickly as possible.
Effective demand planning increases profit and customer satisfaction by helping businesses balance sufficient inventory levels and customer demand.
Excess inventory locks up working capital, adds inventory carrying costs, and increases the risk of inventory obsoletion.
Poor planning can result in supply chain disruptions that lead to backorders, stockouts, or costly materials, leading to delays and unhappy customers.
Internal Trends - Relevant Internal Data
Different events and promotions usually substantially affect the future demand for products. IF products are promoted, there will probably be an increase in sales. That increase in sales must be a part of your prediction, or you will not buy enough to meet this increased demand. It is also essential to build a sound forecast in cases as launching new products. Holidays and calendar events USUALLY also strongly affect sales and marketing.
Past sales can often be used to forecast future performance. Therefore, it is imperative to maintain product data regularly. (including inventory, stockouts, seasonality, sales, and customer demand). Statistical forecast, historical sales, inventory, and demand data are good indications of future performance.
Continual performance review and adjustment against sales forecasts, inventory turn, fill rates, order fulfillment lead times, or cost of goods sold (COGS).
The increasing use of IoT sensors and exponential advances in machine learning, together with the availability of Cloud-based software and the growing functionality of mobile devices, enhance the ability of demand planners to share real-time data and quickly react to changes in supply and demand.
The growing sophistication of demand forecasting and the global aim toward entirely digitized business processes gradually connects more supply chain stakeholders, providing finer-tuned control over the goods' movement supporting demand-driven supply chain management.
ERP software provides demand planners, forecasters, and S&OP experts with supply chain management solutions that help them prepare for future customer demand. ERP allows companies to predict their customers' long-term needs and better prepare for upcoming orders by ensuring that the inventory is in stock when needed. It integrates machine learning software to increase predictions by analyzing historical data.
ERP enables coordination between various business units, making the management and tracking of product specifications, costs, suppliers, workflows, deadlines, and sales more easily streamlined.
Enterprise Resource Planning helps logistics departments quickly collect and summarize data about products and customers, process it, and generate demand forecasts.