Understand Your Inventory NeedsThe first step to avoiding overstocking is understanding what you actually need. This might sound obvious, but many businesses fall into the trap of ordering more than necessary because they lack precise inventory data.
Descriptive AnalyticsDescriptive analytics involves analysing historical data to understand past trends and patterns. It helps businesses comprehend what has happened and why.
- Historical Sales: Look at your historical sales data to identify patterns and trends. This will help you forecast demand more accurately.
- Store Clustering: Group stores with similar sales patterns to tailor inventory levels more precisely and align stock with local demand.
Predictive AnalyticsPredictive analytics uses historical data and statistical algorithms to forecast future trends and behaviours. It helps in anticipating what might happen next and preparing for it.
- Seasonal Adjustments: Factor in seasonal variations in demand. For example, if you sell products that are in higher demand during the holiday season, plan your inventory accordingly.
- Market Analysis: Leveraging external data, such as industry trends and competitor pricing, market analysis helps forecast inventory needs by identifying market gaps and opportunities, enabling more accurate and strategic decision-making.
Prescriptive AnalyticsPrescriptive analytics suggests specific actions based on data analysis to optimise future outcomes. It focuses on how to handle expected scenarios and improve decision-making.
- Set Reorder Points: Determine the optimal reorder points for each product. This is the inventory level at which you need to place a new order to avoid running out of stock.
- Collection Planning: Assess the composition of your inventory, such as the proportions of seasonal fashion items, basics, and replenishment products, to meet demand effectively throughout the year.