Q

Q is a retail platform designed to streamline inventory management for retailers. According to Quantum Retail, the vendor of Q, the product aims to eliminate complexities and optimize inventory processes. It is suitable for retailers of all sizes, from small businesses to large enterprises, and caters to professionals in the fashion, specialty, and grocery industries.

Key Features

Allocation & Replenishment: According to the vendor, Q allows users to create real-time forecasts to monitor and replenish inventory based on demand and merchandising goals. It enables responsive inventory decisions to optimize allocation and ensure products are sent where they are expected to earn the most return.

Order Planning: Quantum Retail claims that Q helps optimize inventory and provides predictive insights for intelligent merchandising decisions. It offers data-driven recommendations for quantity and timing of purchase orders to anticipate product performance, demand, turnover, and profitability.

Analytics: According to the vendor, Q offers cloud-based analytics services tailored to target specific retail problems. It provides advanced demand analytics to improve order planning and gain insights into market challenges.

True Historical Demand: Q enables users to generate data to reveal the true potential of products by location and channel, according to the vendor. It helps identify missed sales opportunities and make future decisions based on accurate historical demand.

Size Optimization: The vendor claims that Q allows users to align stock and allocation with real-time selling patterns across sizes, locations, and channels. It aims to optimize inventory in each store based on how each product type sells.

Pack Optimization: According to Quantum Retail, Q helps determine the most cost-effective prepack configurations to move products through the supply network. It enables purchasing and replenishment decisions to evolve according to demand patterns.

Network Flow Optimization: Q aims to identify the most cost-effective path for moving inventory from the supply network to the consumer, according to the vendor. It aims to reduce lead times and minimize handling costs for more responsive and profitable operations.

Promotional Flow Effectiveness: According to the vendor, Q captures data on promotional product flow to maximize demand and improve efficiency during promotional periods. It helps identify the ideal cadence for moving inventory into place prior to promotions.

Promotional Demand Effectiveness: Quantum Retail claims that Q allows users to measure the historical performance of products during promotional periods. It aims to help understand the effectiveness of different promotional models in meeting sales goals.

Historic Buy Optimization: According to the vendor, Q enables users to evaluate the performance of short life products using true historical demand functionality. It aims to help develop strategies to capture demand and improve future sales performance.