Reimagining the Assortment Process

Our engagement began with deep-dive sessions alongside Assortment Managers and Buyers to examine their current processes. Through contextual inquiries, we observed the intricacies of their day-to-day tasks, uncovering the reliance on manual input and placement for assortment decisions. This traditional method, while familiar, presented several challenges:

• Time-Consumption: The manual process is incredibly time-intensive, requiring significant hours to analyze .
• Subjectivity: Reliance on individual judgment without the support of data analytics sometimes led to missed opportunities.
• Scalability Issues: As the retail environment grows in complexity, the manual process struggles to adapt swiftly to changing consumer behaviors, limiting the ability to rapidly respond to new opportunities.

In recognizing these hurdles, it became clear that a transformative approach was necessary, one that leverages machine learning to initiate the assortment process.

It's crucial for buyers to efficiently evaluate the forecasted performance of a system-generated Modular, with a clear presentation of variances. The Modular Relay Summary, prioritizing sales data, provides essential metrics that enable buyers to assess the Modular's potential impact swiftly.

This approach ensures buyers have immediate access to key performance indicators, facilitating informed decision-making and strategic planning.