In-season Inventory Management
DeFacto – Multinational Apparel Retailer
DeFacto reached a 100% automated initial allocation & replenishment processes’ accepting 90% of 150+ weekly recommendations
Solvoyo’s integrated and collaborative S2S Transfer solution powered by machine learning will bring automation and advanced analytics to inventory balancing across the omnichannel network
Store-to-store transfers are used for re-balancing inventory across sales channels and locations to maximize sales of fashion and short lifecycle products. Solvoyo Retail Store to Store (S2S) Transfer solution automates inventory balancing decisions to maximize profitability, considering operational constraints, shipping, and handling costs. Predictive AI/ML-powered algorithm makes recommendations by comparing the sales potentials across channels/stores and analyzes various transfer scenarios based on sales conversion targets. Real-time flexible ERP data integration provides actionable outputs for store managers. Solvoyo’s close-loop solution also tracks the acceptance rates, store execution rates, and sales conversions of the transfers to provide full visibility to the transfer recommendations’ outcomes.
"Solvoyo has helped our business improve the accuracy of inventory placement to support forward sales and better serve our customers. In our environment of continual technical advancement, it has proved to be a great advantage."
On-demand Store to Store Transfer model working at SKU level to improve stock balance across the network
Advanced forecasting and optimization capabilities improving full-price sell-through
Improved allocation of team productivity and faster decision making
Digital transformation of manual analysis and workflow management
Status tracking and visibility creating corporate memory
Demand-driven inventory optimization maximizing sales conversion
Optimally allocates stock to locations most likely to sell it
Operational constraints are taken into account for seamless execution
DeFacto – Multinational Apparel Retailer
DeFacto reached a 100% automated initial allocation & replenishment processes’ accepting 90% of 150+ weekly recommendations
Penti – Apparel Retailer
With smarter replenishment decisions, Penti balanced inventory across the chain enabled 25% revenue growth with only 2% increase in stock
Companies like Amazon, Walmart, Alibaba, and Zara are leading the path in the use of technology and advanced analytics in managing supply chains. Artificial Intelligence
Automatically identify slow-moving items and evaluate sales potentials across channel/stores
Automatically identify slow-moving items and evaluate sales potentials across channel/stores
Track the recommendations’ acceptance rates, store order execution rates, and sales conversion and adapt the model accordingly
Maximize profitability subject to operational constraints, shipping & handling costs
Track the recommendations’ acceptance rates, store order execution rates, and sales conversion and adapt the model accordingly
Maximize profitability subject to operational constraints, shipping & handling costs
Summary view and visualization for recommendation and approval visibility for quick reference
Advanced analytics used in recommending store transfers at SKU, Option, Style, or Category Level
Actionable recommendations by store managers and ERP data integration
Tracking and reporting the transfer KPIs:
Realized transfer rate
Sales conversion
Category comparison
Configurable and Executive Dashboard reports with graphics, pivot tables
and drill downs
Performance tracking and financial visibility to assess the outcomes of transfer decisions