Analyzing Your Point-of-Sale Data: The Key to Inventory Optimization
As a retail supplier or wholesaler, return on investment is a critical performance indicator. The goal of inventory optimization is to balance inventory levels according to supply and demand to maximize ROI. In this blog post, we will show you a few ways to optimize your retail inventory through point-of-sale data analysis.
Analyze POS Data the Smart Way
Many companies have dedicated analysts who filter through point-of-sale data in spreadsheets, but poring by hand through spreadsheet after spreadsheet can be difficult, and results in slow dissemination of insights and low-impact analysis. By the time you are done analyzing one set of data, it has become outdated and insights are immediately less valuable. Using point-of-sale analytics software is more efficient and actually helps analysts be better at their jobs. Good software will filter out the noise and help you quickly identify the insights and take advantage of opportunities and reduce risks.
When a shopper wants to purchase your product and it is out of stock, it can result in not only lost sales, but also a lost future customer. Out of stocks can be detrimental if you don’t have measures in place to help you anticipate them. Your first step is to quantify how much out-of-stocks are really costing you in lost sales each week, which is quickly done by POS data analysis software. Knowing how well your products are performing at the store level will allow you to identify the high-value, high-velocity articles by location. Then you can easily anticipate stockouts and take action to fix those high value opportunities before they harm your profit and your reputation.
Having excessive inventory is costly. Storing inventory is expensive and you don’t want excessive working capital being tied up in stock that isn’t moving. The key is to balance inventory levels so you have enough stock for demand but don’t have an excess supply of inventory. You need visibility of slow moving articles and where the stock is sitting so you can shift the stock before it becomes a major issue. Using triggers based on weeks of stock can help you not only identify existing overstocks, but also assist with anticipating looming issues before they occur. Additionally, analytics software will help you determine the drivers of slow moving inventory.
Retail is dynamic and is impacted by many variables — seasonality, trends, time of day, day of the week, weather, the economy and more that can lead to suboptimal stock levels. You want to optimize your inventory by calculating the optimal stock by article and store — all while taking these types of variables into consideration. Your supply chain will be more effective when you rid it of working capital that is unnecessarily tied up in the wrong products in the wrong stores.
Allocate Stock Wisely
The goal of stock allocation is to place the right amount of stock in the right stores at the right time. In order to do this, you need to be able to see what your winners and losers are for both items and stores so you can determine where precious working capital is being tied up and where it is desperately needed. Employ a point-of-sale analysis software that performs a Pareto Analysis or the 80/20 rule to help you visualize relative contribution to performance and determine the 20 percent of items that are generating 80 percent of your sales. This will help you identify where to allocate that Open to Buy.
Analyzing your POS data is critical to getting a return on your inventory investment, but analyzing it quickly is even more critical. By using a point-of-sale analytics platform like krunchbox, you can take steps to optimize your retail inventory, resulting in better control over your stock, improved forecasting, reduced stockouts, increased sales and stronger relationships with buyers.