NCR Wins Four GOOD DESIGN™ Awards
Out-of-stocks could be costing you more than money
These figures underscore the necessity of finding the right balance between optimization software, inventory visibility and store personnel. It’s incredibly risky to completely replace one system with another on a live store without running parallel processes for a period of time, to look for and resolve issues. During this time, it’s important to continuously monitor and identify the cause of out-of-stock issues and adjust for them. Plus, adopting new systems, especially those managing critical tasks such as inventory ordering takes time, and user adoption of the technology is as important as the technical rollout. We’ll talk through how to make an inventory replenishment system rollout successful.
When diagnosing the root cause of an out-of-stock, a few key items should be investigated:
- On-hand inventory (on the shelf and in the back room): The most common cause of out-of-stocks is inventory distortion, typically caused by vendor mis-shipments, counting errors, or inventory disorder.
- Forecasted movement: Projection of expected sales, typically calculated based on recent selling history, sales trends, promotional history and adjusting for long-term trends such as seasonality.
- Manual adjustments: A key area to monitor is the extent to which store users are manipulating recommended orders, either directly or by adjusting influencing factors used in the calculations.
The good news is that the right solution provides analytical tools for monitoring all these key diagnostic areas. This allows users to easily identify anomalies that may be causing incorrect ordering and make adjustments accordingly.
Retail operations teams should gain a holistic view of inventory across the retail enterprise with the ability to move product through the supply chain to support stores with the greatest demand. Additionally, inventory replenishment systems must have the ability to seamlessly communicate with the retail website or retailer mobile app. This simple integration prevents customer dissatisfaction due to ordering a product online that isn’t even available at the time of ordering.
Application forecasting capabilities can be validated using the Mean Average Percentage Error (MAPE) calculation, which compares expected performance against actual performance. Retailers should review this discrepancy, and tweak system parameters that could influence forecasts in order to optimize orders for each SKU. It’s also important that system administrators confirm all possible data points are being provided to the forecasting engine – including promotions, major weather events, and any other influencing.
Proper user training is also important in making a roll-out go more smoothly. Store users with expertise in manual ordering might not understand how the technical solution works, and may assume their performance will be better than that of an automated system. Store users should be trained to recognize computer assisted ordering systems as tools that accept their input, rather than autonomous systems. By working hand in hand with a forecasting and ordering solution, a store manager will be more effective.
Monitoring current performance of an inventory-replenishment system and understanding how stores are using the technology helps retailers drive down out-of-stocks and reduce overstocks – which helps them recognize greater, more profitable sales!
At NCR, we have a team of implementation consultants who work closely with our clients to oversee the smooth roll out of our demand-driven replenishment solution. With boots-on-the-ground experience, NCR consultants leverage proven best practices and years of experience to help with both process optimization and change management needs. Our inventory replenishment solution learns every item’s movement, taking into consideration seasonal and promotional factors, to create a specific forecast for every SKU. In addition, our solution has a special focus on highly perishable items with short shelf life, as these items incur very different demand replenishment cycles than shelf-stable goods.