In today’s economic climate, and with many businesses having to layoff people, the benefits of demand forcasting can bring enormous dividends. Recently, demand forecasting has become essential for retailers to survive in the growing competitive market. Demand forecasting assists businesses in making smart decisions about product offering, staffing, inventory, and marketing. Without demand forecasting, businesses are at the risk of making costly mistakes. Top retailers cannot depend on inaccurate and traditional forecasting methods for forecasting demand.
To meet demand on a real-time basis, retail businesses need accurate demand forecasts for every SKU unit in their store. To achieve this accuracy level, businesses need to adopt big data analytics and artificial intelligence to forecast the right quantities of products.
What is Demand Forecasting?
Demand forecasting examines existing data to identify future events and sales to meet consumer demand at the right time. Forecasting analyzes the purchasing behavior of customers. Demand forecasting is one of the significant necessities of running a successful business. A retailer cannot satisfy the fluctuating demand and prepare for the ever changing market conditions without correct demand forecasting.
Demand forecasting in retail estimates consumers’ purchasing trends regarding a particular product at a specific time and area. Demand forecasting enables businesses to create a win-win situation for themselves and their customers. It assists businesses in establishing control over the supply chain, customer success management, and financial planning.
Why is Forecast Accuracy at the Granular Level Important?
In today’s contemporary world, retailers need accurate forecasts at the granular level – For being able to store the right amount of inventory at every location in the network to meet demand, optimize the pricing and inventory decisions, and maximize profit. Although it is impossible to predict demand perfectly, businesses should try to be as accurate as possible with all the data available.
By integrating artificial intelligence and machine learning algorithms into an efficient demand forecasting software that supervises the change in the demand side and aligns it with the supply side to account for the incorrect demand forecasts, retailers can improve their efficiency.
Forecasting demand is essential due to the complexity of supply chains and fierce competition. It also helps to make better supplier purchasing decisions and enhances allocation, production, and replenishment abilities. Different levels of granularity assists in maintaining optimal stock across all the supply chains and look at different time frames that involve hourly, daily, weekly, and monthly forecasts. This can be helpful for businesses in gaining a competitive advantage. Granular level forecasts assist retailers in lowering safety stocks and preventing spoilage while increasing sales and maximizing customer satisfaction.
It is essential to implement a demand forecasting software for generating accurate forecasts and ensure that the retail business strives in the competitive market.
- Increase sales with an optimally stocked inventory
One of the most despised things by retailers other than overstocking is stockout situations. Stockout situations mean lost sales because of unavailability of a product which in turn implies lost revenue. An accurate demand forecasting software assists in preventing these situations as they inform retailers beforehand about how much product should be stocked. AI-based demand forecasting can minimize mistakes by about 50% across the supply chain. It results in reducing lost sales by about 65% as the inventory is always optimally stocked.
- Improved margins and timely discounts
Ai based demand forecasting software can generate accurate predictions about when demand is going to be high and when demand would be low and can assist businesses to understand when to offer a discount for attracting customers and when the demand is high, suggest retailers to increase prices so as to obtain the highest margin possible.
- Minimized operational cost with shift optimization
Staff shortages can lead to customer dissatisfaction and the retailer will suffer if the business has too many people at work when customer numbers are low. Forecasts can help businesses to plan optimal shift trends so that companies need not spend any unnecessary amounts than is required.
- Avoid bottlenecks due to unforeseen demand
When demand is more than the company’s capacity, the operations can become congested. Businesses might not be able to fulfill orders or the staff may be inadequate for resolving queries. With accurate forecasts, retailers can increase personnel as and when required.
- Fresh produce and less wastage
Grocery stores and retailers have a hard time maintaining stock as fresh products have a limited shelf-life. It is estimated that food waste costs retailers about $18.2 billion every year. Demand forecasting thus becomes essential for preventing shelves overstocking i.e retail shelves stacked with fruits and vegetables that are rotting.
- Expenses and carbon footprint reduction
Food wastage is not the only challenge that retailers face. No business would want to stock up/produce in excess and use up extra resources/inventory. By estimating seasonal sales, shops can stock the optimal amount of inventory and thus minimize the carbon footprint and the unnecessary expenses. According to a report by Mckinsey, artificial intelligence-based demand forecasting results in a 10 to 40% decrease in storage expenses.
Thus, retail businesses can reduce uncertainty in retail operations by incorporating a demand forecasting software that allows retailers to accurately forecast, refill, order, and allocate resources accordingly. Moreover, it is also advantageous for scheduling the workforce and optimizing capacity management platforms.
Fountain9 helps Retail and food businesses predict demand accurately at granular level with their AI-powered demand forecasting software– Kronoscope, which considers nine unique factors for predicting demand accurately. It helps businesses to maintain a high availability of products and forecast future inventory needs in order to stock inventory optimally to meet consumer demand at the right time. Thus helping retailers avoid out-of-stock loses and overstocking.
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