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How to Optimize Inventory Markdowns as Shoppers Return

Rory Borghesi
Oracle Retail Senior Director Engagement & Delivery - Planning & Optimization

Based on the general timing of stay-at-home orders around the world, most stores will own a bulk of seasonal inventory that is mid-season with its selling pattern. If seasons changed during the shutdown, these items have aged well beyond their planned out-of-stock dates. 

Many retailers are experiencing the challenge of managing their distressed inventory. These issues can be addressed with business processes found within the Oracle Retail Science Platform and the Markdown Optimization solution.  

The Challenge

Retailers are asking, “Has the demand for the merchandise truly been lost? Or is it pent-up and still viable?” It may seem that doing general markdowns (60% off all spring merchandise, for example) would be the easiest way to address this inventory. However, in these financially tough times, it might make more sense to be strategic about the markdowns by product and by location.  

Frequently Asked Questions 

  • Is my general business objective to build sales or preserve margin? 
  • Would it be more profitable to pack away the merchandise for next year?  
  • Should the merchandise be transferred to stores with a favorable demand?  
  • If the markdowns successfully clear the inventory, is there fresh merchandise available to reset the floor? 
  • Are all stores belonging to a price zone or a cluster opening at the same time? 
  • Should my markdowns be specific to a store or a grouping of stores, for example, price zone or cluster?

Where to Find Help

Oracle Retail offers science-based markdowns that will account for the factors mentioned above – with your guidance – to provide strategic markdowns for the continuing challenges of recovery. Balancing data science with the art and intuition of your team. 

Accelerated markdown optimization service offering

Using your data, Oracle Retail Consulting (ORC) can analyze and provide a set of markdown recommendations using the Oracle Retail Science Platform. These markdowns are based on your business objectives for the inventory and business rules. The ORC team will continue to provide markdowns built on your required cadence as determined in the engagement.   

Taking a retail data science-based approach

  • Targeting markdowns in areas with excessive inventory drives deeper markdowns for some items while allowing higher demand items to remain at a higher price to preserve margin.  
  • Targeting stores as they are re-opened will likely not follow your existing price structures (price zones or clusters), and you may need to send different pricing to specific stores within a zone.

To get started, ORC will conduct several sessions (remotely) with your teams to cover technical, data, and functional business requirements.

Read more on the markdown optimization service offering and how to set up a meeting.

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