If the financial impact wasn’t so enormous to distributors and retail stores throughout the country, it might be considered a joke that we continue to expect front-line managers to accurately tackle inventory management despite being blind to the data necessary to make an intelligent inventory forecast.
What is the point?
The point is that solving the classic inventory management problem is substantially more than just a weak forecasting issue which has been historically viewed as the core problem.
All the critical data elements needed for a complete picture of every category at the retail store level needs to be readily accessible by the local manager. Without the right data, then effective communication and decision making cannot occur. And the results of each decision over time can’t be observed as well.
For example, who in the chain of command will know and report if a product is ordered but never makes it to the store shelf? Or if promotions or displays are authorized but never actually set up, who will be responsible? Or how will inventory be identified that has been ordered by ‘store A’ but placed on the wrong delivery vehicle and sent to ‘store B’? Who will decide which SKUs are failing to deliver expected results and need to be removed or have reduced shelf space?
Many retail leaders continue to claim they possess great inventory management systems and techniques but due to lack of actionable data, rapidly accessed and in useable formats at store level, the common problems with execution and communication among all key parties drive negative outcomes to sales, margins and volume.
It is not that inventory management is not on the minds of the C-Suite management team. The core problem is concluding that managing inventory is being skillfully handled when SKU reviews for example are occurring quarterly or semi-annually.
Beyond the infrequent time gaps for SKU reviews by management, problems with effective inventory management have been magnified over recent years. Portfolio sizes at store level are now 2-3 times larger, making the effective use of limited space a daily challenge, daily operational and capital costs have escalated, and the trade spending needed to attract the attention of distracted consumers is out of sight – making the impact of poor inventory management of much more critical importance.
First, the store level or distribution manager must be seen by upper management as the key person with the most accurate perspective of the buying preferences and behaviors of local patrons.
Second, upper management must surrender to the ineffective routine of collecting limited performance data and then pushing that data down to the local level where the appropriate actions are expected to occur.
Third, local managers must be trained to be the hunters of the data they need and see the effect of every decision they make.
How would that process take place?
As an illustration, the store manager would have visual access to the sales, volume, margin and SKU level sales for every category in their store over any timeline chosen. From that data viewpoint, the performance of each category would be readily visible and any category failures in overall performance would be immediate suspects.
Taking the hunter approach, a poor performing category could then be dissected to visually see the dominance of sales resulting from just a few key packages and quickly identify the lowest performing of the category in term of sales, margin contribution and total customers sold. This will allow the poorest performing packages to be removed from the shelf or have less shelf space.
Before final category decisions are made, the store manager should be able to view performance of each individual SKU to ascertain which specific SKUs should be removed or reduced in shelf set allocations to maximize unit sales, margin and customer penetration.
This type of analysis enables the local manager to see the market dynamics of customer choice over time and the impact of any decisions made on individual SKUs in each category.
This approach to inventory management also allows upper management to actively monitor the local category and inventory decisions being made by local managers, elevate accountability and tie targeted financial rewards for those decisions which drive profitable growth to the local store.
Managers who are empowered by the right data quickly can also identify seasonal shifts and customer preferences over time thus enabling the right inventory buildup to occur and avoid costly sales losses due to empty shelves.
The overall goal here is getting continuous improvement tools in the hands of those who are most capable of impacting store level results. This is the most effective solution to inventory management.