LONDON--(BUSINESS WIRE)--Quantzig, a global analytics solutions provider, has announced the completion of their latest article on the top demand forecasting trends in the retail industry.
Most future predictions hardly turn out to be true due to some unexpected circumstances or changes in the external environment. The same can be said for demand forecasting in the retail industry as well. But, retailers still perform demand forecasting as it is important for inventory management, production planning, and measuring future capacity requirements. Precise demand forecasting provides businesses with valuable information about their potential in the current market to make smart decisions on market potential, pricing, and business growth strategies. In this blog, Quantzig has listed the top demand forecasting trends in the retail industry.
According to the demand forecasting experts at Quantzig, “The retail industry simply can’t survive without demand forecasting as they risk making poor decisions about their inventory and products, which might result in lost opportunities.”
Speak to an expert to know more about the scope of our research.
Top demand forecasting trends in the retail industry
- Rising popularity of bottom-up forecasting: Today, the retail industry functions over many channels, which demands inventory positioning in several locations. As a result, retailers have to emphasize on bottom-up forecasting to meet the demand through various channels. Using such an approach helps them fulfill orders from both e-commerce and traditional retail channels for a wide array of varieties. It allows the retailers to meet customer demands more rapidly and distribute goods through the customers’ choice of channel. When the need arises, such methods can also help retailers balance inventory between distribution centers and stores through high-frequency inter-depot transfers.
- Focus on forecast quality: When carrying out demand forecasting, retailers usually look at demand signals. But, retailers with less sophisticated planning abilities often seek constancy in demand signals, which is frequently fragmented. As a result, they look for a combined model that lets all stakeholders cooperate via “what-if” simulations. Consequently, retailers have started looking for ways to quantify forecast quality by looking at external associations, including end users and suppliers to get better forecasts, which can then be shared with the sales team and suppliers.
- Fresh view towards long-tail items: A majority of the slow-moving or long-tailed items sell because they are in the inventory. Ensuring service levels is the key to mastering demand forecasting for slow-moving items. Such items cannot be formed consistently, so the retailers turn towards supply chain planning software to robotically model stock-to-service level, which precisely lists how much stock they need.
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