A planning solution can be a great asset in helping to optimize inventory levels and availability, but what happens if the data coming into the system is inaccurate? Or when that data leaks into other areas of operations?
Because a planning solution is only as good as the data coming into the system, identifying where there are problems in the inventory data stream can help maximize a solution’s ROI (Return on Investment) and improve inventory management and accuracy.
Why Accurate Data is Vital to Inventory Management
Apart from preventing a planning solution from being used optimally, incorrect inventory data can influence other areas of operation, including store KPIs, customer availability, spoilage, and sales.
For instance, if the record shows that there are 20 bananas in stock, but there are actually 100 in the store, then 80 bananas are at risk of spoiling. On the other side of the problem, if the stock record shows 100 bananas, but only 20 are on the shelves, there is a risk of lost sales and a drop in customer satisfaction.
Data discrepancies aren’t restricted to affecting store operations, either. Minor inaccuracies add up across a full network of stores and can escalate into far more significant losses. A costly item such as steak with a recorded stock count of 100 for £700 and an actual stock number closer to 200 can cause budgetary inconsistencies. Multiplying that inaccuracy by 50 or 100 stores demonstrates the impact of these irregularities on financial control.
At worst, this inventory inaccuracy can cause a financial loss from spoilage and lost sales and, at minimum, a lot of time-consuming manual intervention. Re-inputting these numbers by hand might help fix the problem but negates the benefits of having an optimized inventory planning solution in the first place. Identifying where initial data collecting can go wrong is a good first step when searching for a solution.
Four Common Causes of Inventory Data Inaccuracy
1. Merchandising Considerations
When products of similar nature and appearance are shelved next to each other, it’s easy for store personnel to scan the wrong labels or count the same item multiple times when taking inventory. Products with different varieties, such as soups, might come in 12 assorted flavors and result in 12 different labels that could be mistaken for one another and counted incorrectly.
Scanning these types of items at the cash register or self-checkout can also result in items being scanned more than once or rung up as a different product during checkout. Monitoring or preventing the use of multiplication keys during the checkout process can ensure that similar products are accurately recorded at the point of sale.
2. Product Locations
Products with multiple locations throughout the store can also cause confusion during inventory counts. Have all the products been counted in every location within the store? Chocolate bars, for example, might have a certain amount of stock located near the registers but a secondary location in the internal candy aisle.
Problems also arise from the assumption that all stock is in its proper location. Larger pallets and loose items such as eggs and sports drinks can be overlooked or miscounted. A consistent unit of measurement across these different products during counting can help remove complexity that might result in errors from the process.
3. Timing of Deliveries
The timing of both stock counts and deliveries can have an impact on the data reflected in inventory levels. A store with a standard opening, closing, and delivery schedule might not have any issues. However, a 24-hour store or one with irregular delivery hours might miss inventory numbers in their morning or evening counts.
If inventory counts occur at 10:00 AM and fruit and vegetable deliveries occur at 11:00 AM, stock numbers could be off by hundreds of produce counts. Trying to make decisions throughout the day on this live data can cause uncertainty, so any actions regarding inventory counts must take place in a proper sequence.
4. Unrecorded Use of Stock
The internal consumption of store stock, such as in-store cafes or bakeries, should also be documented with care. If an in-store restaurant uses 15 packs of sausages for meals during the day and does not accurately record those numbers, that means 15 packs of sausages are missing from the stock count every day. Not to mention baking ingredients, salad bar options, and to-go meals can all pull from otherwise stable inventory numbers.
How to Improve Data Collection and Inventory Accuracy
These minor discrepancies in stock data can become significant problems in inventory accuracy, so getting ahead of stock input mistakes is critical. A good planning solution can record when stock measurements change and evaluate key performance indicators that can help identify a scenario where input data might be incorrect.
While investing in automated methods of maintaining stock record accuracy (such as advance shipping notices, RFID tags, or other electronic tracking mechanisms) can help greatly, they can also be expensive and take a long time to implement. However, retailers can analyze their own inventory data to identify patterns indicating a stock record error.
For instance, building a report to find items with a positive stock record but no recent sales would help identify cases where the stock record is too high. On the other hand, reports for an item with sales larger than the stock record would show the opposite and drive the stock to show a negative or zero. Monitoring areas with a high number of stock adjustments is also a good practice for retailers to catch inaccurate data early.
A good retail planning solution can use available data to create views and alerts for users, making it an excellent tool for someone looking to identify these patterns.
Retailers should maintain a steady measurement of changes and inconsistencies in inventory levels while avoiding the pitfalls of inventory data collection to ensure their planning system is proactive instead of reactive and that their inventory plans are accurate and optimized. Monitoring product areas that have consistently poor inventory accuracy can help retailers identify the root causes of the inaccuracy and allow companies to alter their supply chain policies early to mitigate a poor customer experience.
