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Despite the adoption of automation, the state of collaboration in retail supply chains is mediocre. As many as 45% of businesses grapple with limited supply chain visibility, and only 15% report visibility beyond Tier 1 suppliers.
Bridging the gap between retailer and supplier during the early stages of product lifecycle is essential for building a demand-driven, collaborative, and resilient supplier network.
AI and ML are the top strategy and collaboration technology choices for more than 60% of retail supply chain stakeholders across the globe.
Intelligent supplier collaboration platforms can not only reduce the overall supply chain costs, they can cut onboarding expenses and time, accelerate new product introductions, and improve end-to-end efficiency.
As many as 40% of retailers cancel at least one in ten orders due to inaccurate inventory data.
Automating demand forecasting streamlines supplier collaboration, reduces lead times, and improves fulfillment.
A lack of mutual trust and communication tops the list of challenges for 63% of retailers and 52% of suppliers.
Digitized supplier-retailer information/data interchange functionalities can effectively curb frauds, delays, and confusion, and overcome communication barriers to unlock greater transparency.
Studies reveal that up to 25% of supply chain data is inaccurate due to siloed information, and poor data quality costs organizations an average of $12.9 million annually.
ML-driven supplier management software inherently overcomes these challenges with built-in workflow automation that can be customized as per business requirements.
Supplier performance is one of the biggest areas of concern in supplier management for 40% of procurement executives globally.
Customizable automated supplier management workflows and self-help portals streamline supplier management, reduce supplier information management costs, and ensure 100% data accuracy.
