Merchandise & Assortment
Merchandise planning and customer-centric assortments have always been core to retail performance—but the operating model most retailers still use is no longer fit for purpose. Shorter lifecycles, omnichannel demand, and faster competitive cycles have turned “seasonal planning” into a continuous discipline. And when analytics sits outside execution, teams spend more time reconciling spreadsheets and explaining variance than improving outcomes.
Dataviva’s Merchandise & Assortment suite closes the loop between strategy and day-to-day action. We combine advanced analytics and ML (including attribute-driven forecasting for new items, assortment recommendations, size profiling, and optimization) with an execution-connected workflow—so assortment intent becomes buy quantities, allocation, and replenishment actions that are measurable, governable, and continuously updated as demand signals change.
We then go a step further and fully integrate Order Planning & Execution on the same platform, removing silos and reducing duplication and manual work.
50%
Reduce Decision Time
25%
Reduce Overstocks
5%
Increase Sales
5%
Increase Margin
Applications
Merchandise Financial Planning
Financial planning must keep pace with faster assortment cycles and omnichannel complexity. Dataviva provides a flexible, easy-to-use workflow to produce rolling merchandise financial plans across all active points of commerce—without relying on slow batch updates and manual consolidation. Because the platform connects planning with execution-facing processes, enterprise goals and guardrails flow consistently into downstream decisioning—supporting alignment across assortment, supply chain, and pricing workstreams. Teams spend less time reconciling plan vs. actual and more time steering performance while there is still time to change outcomes.
Assortment Planning
Assortment planning should be a customer-focused, end-to-end process—not a sequence of disconnected analyses. Dataviva provides a visual workflow that combines store clustering and attribute-level assortment analysis to build a clear assortment strategy and generate automated recommendations for the right breadth and depth across channels and locations. Crucially, assortment plans do not stop at “recommendations.” Dataviva converts intent into operational action by sending buy quantities and distribution plans directly into purchase order and allocation processes—so localized assortments are delivered in stores and channels with less rework and fewer late-cycle escalations.
Order Planning & Execution
Purchase orders are where planning meets financial terms and operational constraints. Dataviva converts replenishment plans into optimized purchase order recommendations that respect vendor agreements and constraints—such as volume-based pricing tiers and negotiated terms—while also producing efficient delivery plans that account for order and truck constraints. This reduces manual rework between planners and buyers, improves buying ROI, and accelerates the time from decision to executable purchase orders—without losing governance or auditability.
Assortment Optimization
When demand is volatile and space is constrained, assortment planning needs optimization—not manual compromise. Dataviva builds an optimized assortment matrix using assortment strategy and tactics, plus predicted new-item performance from attribute-driven demand intelligence. Optimization accounts for real-world constraints—such as cannibalization/halo effects, space constraints, market signals, and assortment rules—so recommendations are feasible and aligned to business goals. And because the platform is live, assortments can be refined as performance data arrives—without forcing teams into spreadsheet-driven re-plans.
Allocation Planning & Execution
Allocation is where retail strategy becomes reality. Dataviva allocates at SKU level across channels and locations using demand intelligence, assortment intent, and item/location rules, and then keeps allocation current as new signals emerge through the selling cycle. For categories that rely on prepacks, Dataviva accelerates decisions by automating recommendations and determining optimal prepack configurations aligned to warehouse and store requirements. Allocation works as part of the live flow with replenishment—so teams spend less time reconciling and more time improving availability and sell-through.
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.
Store Clustering
Localization fails when store groups are defined by static heuristics or outdated segmentation. Dataviva automatically builds store clusters using combinations of criteria—including KPIs (sales, profitability, flow), item/store attributes, and space constraints—so clustering reflects how stores actually behave. Clusters become an operational tool: they inform localized assortments, distribution strategies, and buy decisions at scale—so planners can move faster without defaulting to one-size-fits-all ranges. The result is fewer manual iterations and assortments that better match customer demand across formats and regions.