Enhance retail store allocation with predictive analytics

Oracle Cloud Infrastructure (OCI) Forecasting service can be used to enhance retail store allocation with predictive analytics. Inventory is the single most important physical asset of a retailer, and the ability to accurately and efficiently allocate inventory to the stores is one of the most challenging, yet critical areas of retail.

Note:

Oracle Cloud Infrastructure Forecasting is currently in limited availability. To access Forecasting, go to Oracle Beta Programs page and click Oracle Data & AI Cloud Services Umbrella Beta Program.

Retailers must ensure the right supply of the right products at the right location at the right time to avoid both out of stock and overstock. Both conditions can be very costly to the retailers. Out of stock costs direct business revenue and also lost customer satisfaction. While overstock leads to poor capital allocation, reshipment costs or deep discounting. The more SKUs, variants and locations a retailer has, the more complex this becomes. To manage the complexity of allocations, retailers use specialized application packages, including Oracle Retail Allocation, Blue Yonder (formerly JDA) or others for the initial allocations or initial plan.

As time passes, things tend to happen including weather changes, logistical delays, market shifts, local events, and changing tastes - all of which can take the demand of a product in a location up or down. To reliably predict inventory need changes after initial allocations but before final shipping is an opportune time to make changes.

Allocation needs can be determined based on manual input, historical data, plan information, demand forecasts, or a combination of plan information and history, which compares actual sales to plan information and reforecasts based on actual performance in season. However, even when sophisticated allocation software packages are used, there are situations when the planned inventory allocations turn out to be wrong.

This is also an example of how a data lakehouse provides data-driven retail insights to improve operational efficiency, supply chain visibility and customer experience.