AI/ML driven Inventory Optimization

Supply Quotient is an inventory optimization solution that focuses on optimising and automating the supply chain with a view of the retailer's network of stores, distribution centres and suppliers combined with broader insights into the operational environment. We aim to help organisations in the retail industry optimise their supply chain by providing an easy-to-use platform incorporating all essential processes and insights, allowing users to make quicker, smarter, and more efficient data-driven decisions to support the ever-changing needs of a business.

 Retailers in the modern retail space who do not utilise automated retail replenishment increase their likelihood of facing several challenges, such as inaccurate inventory tracking, overstocking, understocking, manual process inefficiency, difficulty forecasting demand, and lack of real-time visibility into their inventory levels and sales data. Such problems often translate to wasted resources, lost sales, dissatisfied customers, and the complexity of making informed decisions about restocking pricing and promotions.  

Supply Quotient aims to help retailers overcome challenges while improving their inventory management, operational efficiency, and customer satisfaction. Our platform also incorporates notable features which enable the user to make quick adjustments and long-term strategic changes that will give the business a competitive advantage.   

Product Features

Prebuilt Dashboards

• Flexibility for you to slice and dice based on a store, products, product categories and other entities.  

• Get insights on your inventory, sales, supplier performance etc.  

• 10+ critical metrics required by retailers to optimise the supply chain in the dashboards. 

Intra Network Stock Transfers

• Goods that are moved between different locations within a company's supply chain network are considered.  

• The intra-network includes transfers between warehouses, distribution centres, and retail stores.  

• Notice optimised inventory levels and reduction in unnecessary transportation costs. 

Lead Time Inference

• Predict the accurate delivery time of goods based on historical data. 

• Improve your planning and forecasting processes by predicting lead time. 

• Ensure you have the right amount of inventory to meet customer demand.  

Automated Order Generation

• Automatically generate orders based on inventory levels, customer demand, and other factors.  

• Reduce the risk of stockouts by automating the order process.  

• Ensure you always order the right amount of inventory to meet demand. 

Centralised Store for Data

• Gain insights and optimise the supply chain by providing a platform for centralised data storage.  

• Includes data from various sources, such as inventory levels, supplier information, delivery times, etc.  

• Make better decisions about your supply chain operations and identify opportunities for improvement. 

Customer Case Studies

How BigTapp helped a leading convenience store in Malaysia realize business benefits by leveraging its domain expertise in modern retai...

The client was unable to determine the right store quantity/customer demand. The traditional rule-based approach was failing due to frequent changes in seasonal, holiday, weather patterns and plano...

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