In today’s retail climate, retailers need richer and more accurate demand forecasting models to be able to position the right amount of inventory at each location in their supply chain network to meet the demand, optimize inventory levels and pricing decisions and maximize profit. Real-time visibility across the channel plays a crucial role in achieving this goal.
Download this free pocket guide to find out:
- What demand forecasting is in the retail industry,
- Find out what retailers need to do to create better forecasts,
- Deep dive into why forecast accuracy based on AI-driven market research is more important than ever,
- Discover why retailers need granular-level sales forecasting systems,
- And ultimately learn how to forecast demand better.
Key points
- For many retailers, whether they are cross-channel champions or small brick-and-mortar stores, forecasting is king.
- To make better buying decisions and accelerate allocation and replenishment capabilities, retailers need to implement different types of demand forecasts such as short-term demand forecasting in different levels of granularity that consider all time frames.
- Forecasts using advanced AI-decisioning can produce accurate data analysis for a lean business plan, by using historical sales data that affect demand.
- Demand forecasting can integrate two different approaches to decision making such as machine learning and the Delphi method.
- When appropriately implemented, demand forecasting methods can become a source of competitive advantage and help retailers meet the customer expectations of tomorrow. And to achieve that, retailers need to leverage modern demand forecasting systems to succeed.
Speak with an expert in retail optimization at invent.ai now.