Business Goal
Its extremely critical to replenish items in a timely manner.
The out-Of-Stock scenario occurs when the retailer doesn’t have a product to sell. On-Shelf-Availability means the Product is available in the inventory however it may be placed in the wrong place making it inaccessible to Customers.
Challenges
Out-of-Stock happens primarily due to following reasons
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Ordering too little stock
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Ordering too late
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Not accounting for seasonality
In some cases, the retailers had an accurate forecast, they placed their orders on time, and the products are in storage. However, a lack of proper assortment insights can impact OSA. Sometimes, products don't end up on the right shelves or they are not replenished in time.
When shoppers can’t find what they’re looking for, 70% will buy a different brand, and 30% will visit a different store.
Solution Approach
Sparkflows provide the Self-Service Platform for performing all the different steps of Business Solution development
Data profiling, Exploratory analysis, Data transformation
Creates a continuous range of dates and adds Inventory related information based on incoming dataset.
Computes flag based on each Inventory specific transactions i.e. Replenishment Flag, Promotion Flag
Zero Sales Days - Event of consecutive Zero Sales Days needs to be validated for Out Of Stock situation. Zero Sales Days might be ok for slow moving product however consecutive events need to be analysed.
Computing features like phantom inventor and safety stock
Phantom Inventory - It denotes the gap between the Inventory and the Sales System. This might result due to the misplacement of Products, stolen, loss or issue with the Inventory Tracking system.
Computes flag based on each Inventory specific transactions i.e. Replenishment Flag, Promotion Flag
Safety Stock - It acts as the trigger point to order a product. The Safety Stock level for a product is where replenishment needs to be ordered. If the On Hand Inventory level dips below Safety Stock, it would result in a few days of Zero Stock. This would result in a loss of business.
Forecasting sales over historical data to identify OOS
It runs prediction sales of a product over a historical period
It compares sales prediction against the actual sales data and identifies Out Of Stock issue