By Mike Holmes, Solutions Consulting Manager at RELEX Solutions and Robert Jenkins, Regional Programmer Director at RELEX Solutions.
A planning solution can be a great asset in helping to optimise inventory levels and availability. But what happens if the data coming into the system is inaccurate and leaks into other areas of operations?
Data-based solutions are ultimately only as useful as the data that comes into the system. Identifying where there are problems in the inventory data stream can help maximise a solution’s usefulness and improve inventory management and accuracy as well.
Accurate data is vital to inventory management
As well as preventing a planning solution from performing at its best, incorrect inventory data can negatively impact other areas of operation, including store KPIs, customer availability, spoilage, and sales.
Data discrepancies aren’t restricted to negatively affecting store operations. Minor inaccuracies across a network of multiple stores all add up and can escalate into far more significant losses. A costly item such as steak with a recorded stock count of 100 for £700 versus an actual stock number closer to 200 can cause budgetary inconsistencies. Multiply that inaccuracy by 50 or 100 stores, and the damaging financial impact of irregularities on financial control is obvious.
The worst-case scenario for a retailer with inaccurate inventory is financial loss from spoilage, lost sales. Re-inputting these numbers by hand may help fix the problem but it’s time-consuming and negates the benefits of having an optimised inventory planning solution in the first place.
To avoid this, identifying where initial data collecting can go wrong is the first step.
Here are the four most common causes of inaccurate inventory data for retailers to look out for:
- Merchandising considerations
When products of a similar nature and appearance are placed next to each other, it’s easy for in-store staff to scan the wrong labels or count the same item multiple times when taking inventory. Products with different varieties, such as soups, often have similar labels that could be mistaken for one another and counted incorrectly.
Scanning these item types at the checkouts can also result in items being scanned more than once or rung up as a completely different product. Monitoring or preventing the use of multiplication keys during the checkout process can ensure that similar products are accurately recorded as well.
- Product locations
Products situated across multiple locations throughout the store can confuse inventory counts, with staff unsure whether all the products in store have been counted.
Problems often arise when one assumes that all stock is in its proper location. Larger pallets and loose items such as eggs and soft drinks can be overlooked or miscounted. A consistent unit of measurement across these different products during counting can help remove the complexity that might result in errors.
- Delivery timings
The timing of both stock counts and deliveries can impact the data reflected in inventory levels. A store with standard opening and closing times and delivery schedules might not have any issues. However, a 24-hour store or a store with irregular delivery hours is likely to miss inventory numbers in their morning or evening counts.
Attempting to make decisions throughout the day on live data can cause uncertainty, so any actions regarding inventory counts must take place in a proper sequence.
- Unrecorded use of stock
The internal consumption of store stock, such as in-store cafes or bakeries, needs careful documenting. For example, if an in-store restaurant uses 15 packs of sausages for meals across the day and does not accurately record those numbers, the sausages are missed from the stock count. This extends to baking ingredients, salad bar options, and to-go meals, which can all pull from otherwise stable inventory numbers.
How to improve data collection and inventory accuracy
What appear as minor discrepancies in stock data can become significant problems in inventory accuracy. Implementing an effective planning solution lets retailers record when stock measurements change and also evaluate key performance indicators. This in turn helps them identify scenarios where input data might be incorrect.
Investing in automated methods of maintaining stock record accuracy (such as advance shipping notices or other electronic tracking mechanisms) can help. However, they can be expensive and take a long time to implement. Once installed, retailers can analyse their inventory data to identify patterns that indicate a stock record error.
Building a report to find items with a positive stock record but with no recent sales, helps to 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, driving the stock to show a negative or zero. Monitoring areas with stock adjustments gives retailers a chance to catch inaccurate data early.
Proper retail planning is able to use available data to create views and alerts for users. Retailers should maintain a steady measurement of changes and inconsistencies in inventory levels to avoid the pitfalls of inventory data collection. They also need to ensure their planning system is proactive, not reactive and that their inventory plans are accurate and optimised.
Monitoring product areas with consistently poor inventory accuracy helps retailers identify the root causes of the inaccuracy and gives them the insight they need to alter their supply chain policies early enough to avoid disappointment and a poor experience for customers.