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Learn about improving supply chain retail allocations with OCI Forecasting

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 1. Architecture Center
 2. Solution Playbooks


LEARN ABOUT IMPROVING SUPPLY CHAIN RETAIL ALLOCATIONS WITH OCI FORECASTING

Back to Architecture Center
Retail Industry
 * Enhance retail store allocation with predictive analytics
 * 
   Fine-tune supply chain retail allocations with OCI Forecasting
   * 
     Business Solution
     * Dashboards
   * 
     Technical Solution
     * Architecture
 * Explore More
 * Acknowledgments

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 1. Learn about improving supply chain retail allocations with OCI Forecasting
 2. Enhance retail store allocation with predictive analytics


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.

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Title and Copyright Information

Learn about improving supply chain retail allocations with OCI Forecasting

F73944-01

February 2023

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