Demand Forecasting
Demand Forecasting fails when the world changes faster than batch cycles and manual processes can react. Dataviva was built for the difficult scenarios — launches, promotions, re-ranging, sparse history, and short lifecycles — using a demand-pattern recognition approach that selects the right method per item, location, and channel regardless of their sales history or lack thereof.
Most importantly, forecasts are not “reports.” In Dataviva they are a live input to operational decisions—so allocations, replenishment, ordering, and promotions can be updated as soon as new signals arrive. Your data science team can extend Dataviva platform with your own methods, and the forecasting engine can be exposed to your landscape as a service.
50%
Reduce Decision Time
25%
Reduce Overstocks
5%
Increase Sales
5%
Increase Margin
Applications
New Product Forecasting
New product introductions and assortment changes should not trigger weeks of manual work, guesswork, and post-launch firefighting. Dataviva New Product Forecasting produces reliable, bottom-up forecasts for brand-new items, new stores, and new channels—even when history is sparse, noisy, or non-existent. Because Dataviva connects insight to action, new-item forecasts immediately drive assortment decisions, purchasing, initial allocation, and fulfillment —so launch plans are not just created, but actually delivered and continuously corrected as real demand signals emerge
Promotion Planning
Promotions break conventional forecasting because they distort demand, create second-order effects, and require frequent mid-flight adjustments—often across multiple teams and systems. Dataviva isolates true promotion impact, models halo and cannibalization effects, and forecasts promotional demand accurately even for promotions you have never run before. Most importantly, promotions are managed as a live loop: Dataviva’s real-time platform continuously monitors performance and supports rapid course-correction—so promotion plans translate into immediate changes in pricing and inventory flows where needed, reducing manual effort and preventing avoidable stockouts/overstocks while the event is still running.
Automated Size Curves
Size profiling is foundational for fashion planning and execution, but it is often manual, error-prone, and updated too infrequently to keep up with changing demand. Dataviva automates size curves end-to-end: cleansing “messy” data, identifying size ranges and sub-ranges, and generating robust size curves that reflect store- and channel-specific behavior. Because Dataviva closes the gap between planning and execution, size curves are not static reference data—they directly improve buying, allocation, replenishment, and assortment execution across the lifecycle, reducing manual maintenance and preventing size-driven availability issues before they become escalations.