Retail Planning & Category Management FAQs

Assortment tools help retailers decide the optimal product mix by store/channel, season, and customer segment, using historical sales, attributes, localization, and clustering. Planners simulate scenarios, align with merchandise plans, and balance breadth vs. depth to hit sales and margin goals while avoiding over/understocks. Modern suites support store profiling and dynamic clustering to tailor assortments to local demand.

Allocation and replenishment are complementary. Allocation decides the initial push of how much of each item goes to which stores/DCs based on plan, capacity, and expected demand. Replenishment is the ongoing pull that keeps shelves in stock, setting service targets, EOQs, review cycles, and vendor/carton constraints by item-store. Modern solutions handle lifecycles (intro, active, markdown), promotions, and multi-echelon logic that reduces safety stock across DCs and stores. Done together, they lift availability, sell-through, and working-capital efficiency.

Allocation assigns initial quantities to stores/channels based on expected demand (sales history, demographics, store size), while replenishment restocks items automatically as they sell to keep availability high, and markdowns low. Best-in-class systems automate forecasts, generate orders, and tune models by product lifecycle and seasonality to improve sell-through and margins.

Buyer refers to the buyer/planner workflows inside Assortment Planning. The solution connects financial targets, product attributes, and localized demand so buyers can move faster, collaborate with merchants and space teams, and make every assortment decision count. It automates decision points, streamlines cross-functional work, and ties choices to financial and operational outcomes, so buyers can localize, simulate, and execute assortments that protect margin while meeting customer expectations.

CKB is the centralized database behind Space & Category Management. It stores and governs category data planograms, hierarchies, products, and fixtures and secures access by roles so teams can build, publish, and reuse planograms and floor plans consistently across stores. Blue Yonder guidance shows how users categorize products, manage roles/permissions, and perform bulk operations like exporting projects from CKB, confirming its role as the source of truth for space planning content.

CKB Database Replication supports controlled movement/refresh of the CKB store (e. g., between dev/test/prod or regional instances) so Space/Floor Planning users work with the right versions at scale. Blue Yonder admin articles highlight version alignment between Space Planning and the CKB database, batch processing services that publish content, and the permissions needed for automation illustrating the safeguards involved when replicating or updating CKB across environments.

Dynamic Allocation continuously senses demand and inventory signals to place the right product, size, and quantity where it will sell, combining push/pull approaches, and adjusting as trends emerge. Blue Yonder's Allocation & Replenishment describes AI/ML-driven plans, lifecycle handling, and unified workbenches; support content shows Dynamic Allocation, even purchasing for new products without a forecast, and a Blue Yonder credential confirms a dedicated product/skill track.

Enterprise Planning (part of Merchandising) provides the foundational item/vendor/cost/pricing and planning data that synchronizes operations across departments and channels. Blue Yonder positions merchandising as the system of record that drives revenue with accurate, real-time, actionable data; related resources on merchandise financial planning explain how modern planning links strategic targets to execution. Together, they improve inventory control, support expansion, and tie plans to measurable outcomes.

Server Edition denotes an enterprise-grade deployment of the merchandising/enterprise planning, centralizing master data and planning logic for scale, governance, and performance. The merchandising overview emphasizes synchronized, real-time data across the enterprise to reach sales goals, optimize inventory investment, and support corporate initiatives' requirements for a server-based, multi-user planning backbone.

Floor Planning turns macro-space strategy into executable store layouts and drives ROI from every square foot. The Space Management page highlights creating localized floor plans, optimizing space allocation, and automating planogram generation; case studies show transformation through better layouts and shelf allocations. A solution brief underscores AI/data-science-assisted generation of ready-to-implement floor plans to speed cycles and improve consistency.

Floor Planning Plus expands Floor Planning with advanced visualization and workflow options used by teams to coordinate with Space Planning and Planogram Generator. Blue Yonder success content references Floor Planning Plus alongside planogram libraries, DXF export, and 3D visualization, showing richer editing, publishing, and collaboration features that help large organizations scale macro-space changes faster and with better control.

Floorplan Generator automates macro-space design so you can produce store-specific layouts in minutes, not weeks. Using AI and rules, it assembles fixtures and departments into ready-to-implement floor plans while honoring space, adjacency, and capacity constraints, dramatically speeding up resets and improving consistency across locations. Blue Yonder. It pairs with Space & Category solutions to push updated planograms and assortments downstream without manual rework.

Blue Yonder's retail forecasting (Cognitive Demand Planning) blends AI/ML with autonomous scenario planning to deliver faster, more accurate forecasts, and a better planner experience. The platforms' demand-planning engine also touts measurable accuracy gains by combining patented algorithms with machine learning and feature engineering. These capabilities help retailers improve on-shelf availability, reduce waste, and adapt quickly to market shifts.

Intelligent Allocation uses AI to steer inventory to the most profitable and service-friendly nodes, continuously rebalancing as demand and constraints change. It supports flexible allocation rules, lifecycle strategies, and a consolidated inventory view to boost sell-through while reducing markdowns. Case materials highlight how Blue Yonder's AI-based order/fulfillment stack underpins fast customer promises and efficient inventory movement across networks.

MFP connects pre-, in-, and end-of-season financial planning into one flow, leveraging predictive analytics and (in newer releases) generative AI to improve accuracy and speed of decisions. Blue Yonder guidance emphasizes a connected approach linking MFP, demand, assortment, and allocation so plans stay synchronized as conditions shift. The result: tighter control of sales, margin, and inventory investment across categories and channels.

Mobile Store Operations equips associates with an app that drives real-time pick, pack, hand-off, and ship workflows, turning stores into efficient fulfillment nodes. It surfaces tasks, locations, and quantities to increase accuracy and speed, and uses store inventory to fulfill online orders and avoid markdowns. Managers gain visibility to balance service, labor, and capacity during peaks.

Performance Analysis refers to the analytics advances delivered in recent releases, AI-assisted, on-the-go issue resolution, richer scenario planning, and real-time alignment of demand, supply, and financial plans on a common platform. The 1H 2025 release highlights agentic AI and a modern UX to accelerate analysis and decision-making across planning and execution.

Planogram Generator Client modernizes how planograms are created and managed on the desktop. Blue Yonder's Space Planning resources emphasize moving from generic to store-specific planograms and streamlining authoring so teams can scale localized assortments and layouts with far less manual effort. It complements Space Management's clustering and automation to increase efficiency and planogram quality.

Planogram Generator Enterprise adds centralized governance and publishing at standardizing templates, rules, and data pipelines so large retailers can roll out planograms consistently across banners and regions. The program focuses on eliminating generic planograms and enabling store-specific, data-driven layouts that are easier to govern and update enterprise-wide, with Space Management automation improving throughput and operational efficiency.

Replenishment for Retail balances availability and margin by automating when, where, and how much to replenish across stores/DCs. It uses item-/store-level demand sensing, service-level targets, lead-time variability, and vendor/carton constraints to calculate economically optimal orders. Lifecycle, and seasonality logic (new, active, markdown) protect sell-through, while exception workflows flag supply risk, and promotion spikes. For grocery/fresh, min-shelf rules, waste limits, and day-of-week delivery calendars maintain freshness. Optional clustering and multi-echelon policies reduce safety stock while keeping on-shelf availability high.

Shopper Insights turns transaction, loyalty, traffic, and market data into space and category actions. It surfaces decision trees, item affinities, and demand transference so merchants and space planners know which SKUs truly drive the basket. Store/cluster-level analytics reveal local preferences and trip missions; heatmaps and KPI panels quantify shelf productivity (e. g, sales per facing, eye-level gain). The output links directly to planograms and floor plans, enabling evidence-based facings, adjacencies, and localization that lift conversion and reduce space waste.

Size Scaling optimizes the size curve by store/cluster so apparel and footwear assortments match local fit and demand. It mines sell-through, returns, and substitution patterns to build predictive curves, then translates them into buy, allocation, and replenishment quantities, accounting for vendor pre-packs, minimums, and omnichannel reservations. During the season, it rebalances the mix (e. g., protects popular sizes, slow buys on long-tail sizes) to reduce stockouts, stray inventory, and markdowns. Results: higher full-price sell-through and fewer size breaks on the shelf.

Slow-mover logic is built for intermittent demand. Instead of standard time-series, it uses approaches suited to sparse sales (e. g., Croston-style, Bayesian pooling), blends signals across stores/clusters, and considers substitutes to avoid false stockouts. Policies emphasize longer review cycles, economic order quantities, and service targets that balance availability vs. carrying cost. Alerts trigger rationalization or vendor negotiation when long-tail items underperform. Net effect: fewer dead-stock traps, better parts/long-tail service, and lower working capital.

Space Automation Professional industrializes planogram ops. Teams codify rules (facings, adjacencies, fixtures, compliance), schedule batch generation, and mass-publish store-specific planograms without manual touches. Data validation catches broken items/fixtures early; QA checks confirm assortment and safety/compliance rules before release. Integrated workflows push results to floor planning and store execution, while dashboards track throughput, and issue resolution category resets happen faster, with fewer errors, at true enterprise scale.

Space Planning is the desktop workbench for creating high-quality planograms. It supports precise fixture modeling, rules-based placement, performance analytics (e. g., sales/GM per facing), and store-specific variants, all tied to product and pack hierarchies. Planners simulate facings and adjacencies, then publish compliant planograms to downstream systems and store mobile apps. The result is faster resets, better shelf productivity, and tighter alignment between category strategy and execution.

Space Planning Plus extends the core with advanced authoring and collaboration-rich libraries, batch ops, and visualization to speed large programs. Teams standardize templates and rules, coordinate with Floor Planning and Planogram Generator, and manage approvals at scale. It's purpose-built for enterprises rolling out thousands of localized planograms while maintaining governance, version control, and performance KPIs across banners and regions.

Space Planning Web brings lightweight, browser-based planogram review and editing to the business. Merchandising and field teams can view store-specific layouts, make controlled tweaks, annotate issues, and approve or reject proposals without desktop installs. Tighter loop-times (review fix, publish) keep assortments and compliance current, while governance ensures only permitted edits go live. It complements the desktop client and automation services for an end-to-end, modern space workflow.

Store Insights translates sales, traffic, loyalty, and market data into store-level actions for merchants and space teams. It reveals which categories, SKUs, and facings truly drive baskets; highlights localization opportunities by cluster; and pinpoints underperforming space using KPIs like sales/GM per facing and attachment rate. Findings flow straight into planograms and floor plans, so you can tune adjacencies, facings, and assortments quickly and measure impact over time.

Strategic Assortment aligns your product mix with financial targets and customer demand by season, channel, and store/cluster. Planners model what-if scenarios, balance breadth vs. depth, and localize for demographics and missions, then connect plans to allocation and replenishment so choices show up on shelves fast. The result is higher conversion, margin, fewer stockouts/markdowns, and a clear, auditable link from strategy to shelf.

Strategic Space sets the macro-space strategy, how much floor and fixture capacity each department and category should get by format, season, and cluster. It blends performance analytics with role-based guardrails (destination, routine, convenience) and customer journeys to guide adjacencies and traffic flow. Targets then drive floor-planning and automated planogram generation, keeping space, assortment, and financial plans in sync.

Floor Planning converts macro-space strategy into executable, store-specific layouts. Using rules and AI, planners place departments, aisles, and fixtures to meet capacity, adjacency, and safety constraints, then publish designs for space and store-operations teams. Tight integration with planogram generation speeds resets, while analytics quantify sales/GM per square foot so you can iterate layouts that grow revenue and reduce wasted space.

Merchandise Financial Planning (MFP) links top-down targets and open-to-buy with bottom-up category and assortment plans. It sets sales, margin, receipt, and inventory guardrails; simulates scenarios (price, promo, mix) before committing; and continuously reconciles plans in-season as trends change. With MFP aligned to demand, allocation, and space, retailers reduce risk, protect cash, and hit KPIs with fewer last-minute course corrections.

Planning Data Infrastructure provides the governed foundation product, vendor, cost/price, attributes, hierarchies, calendars, and location structures used across planning apps. It standardizes master data and pipelines, ensures version control, and exposes trusted datasets to assortment, space, allocation, and financial planning. With a single data backbone, planners work faster, reconcile less, and push decisions to execution systems without rework.

Replenishment Planning defines the policies that keep shelves in stock at the lowest total cost. It sets service targets, review cycles, order quantities, and vendor/carton constraints by item-store; models lead-time variability and seasonality; and connects to allocation and execution so orders flow automatically. Multi-echelon logic reduces safety stock across DCs and stores, raising availability while freeing working capital.

Retail analytics turns raw sales, inventory, customer, space, market data into decisions that lift revenue and margin. Typical use cases: demand forecasting, price/promo optimization, localization, and space productivity. In category, and space workflows, analytics surface decision trees, item affinities, and sales/GM per facing so teams can re-plan assortments, facings, and adjacencies with confidence. Tightly linking insights to planogram and floor-planning tools shortens the loop from see to do.

Retail demand forecasting estimates future sales by item, store/cluster, and channel so you can buy, allocate, price, and staff with confidence. Modern approaches blend machine learning with causal signals (promotions, price, seasonality, holidays, weather, local events) and handle edge cases like new items (analogs) and intermittently-selling SKUs. Good systems produce probabilistic forecasts (not just a single number), expose accuracy and bias KPIs, and let planners run scenarios (what-if price drops 10%?). The payoff: fewer stockouts/markdowns, tighter OTB, and faster reaction to demand changes.

Retail Performance Analytics turns planning and execution data into role-based insights. Think interactive dashboards that connect demand, space, inventory, price/promo, labor, and fulfillment metrics, with drill-through from corporate to store/SKU. Planners and operators get anomaly alerts, root-cause trails (e. g., promo uplift lagged by out-of-stocks), and guided next actions. Because it sits on common data, everyone debates decisions, numbers, accelerating line reviews, space resets, and in-season re-plans. Result: faster decisions, higher availability, better margins.

Retail Planning connects strategy to shelf across financial planning, merchandising, assortment, price/promo, allocation, replenishment, and space. Teams set targets (sales, margin, inventory), simulate scenarios, then translate the plan into localized assortments and space while staying aligned to OTB and capacity constraints. A connected platform keeps plans synchronized as trends shift, feeds execution systems (OMS/WMS/LMS), and returns performance signals for continuous re-planning. The outcome is fewer fire drills and a measurable link from every decision to financial results.

Allocation and replenishment are complementary. Allocation decides the initial push of how much of each item goes to which stores/DCs based on plan, capacity, and expected demand. Replenishment is the ongoing pull that keeps shelves in stock, setting service targets, EOQs, review cycles, and vendor/carton constraints by item-store. Modern solutions handle lifecycles (intro, active, markdown), promotions, and multi-echelon logic that reduces safety stock across DCs and stores. Done together, they lift availability, sell-through, and working-capital efficiency.

Size Scaling tunes size curves by store/cluster so the buy, allocation, and replenishment mix matches local demand for apparel/footwear. It mines sell-through, returns, and substitution patterns to predict the right ratio (e. g., more M/L in urban formats, more XL in suburban), then respects vendor pre-packs and minimums. In-season, it adapts curves as signals change to prevent size breaks, cut stray inventory, and protect full-price sell-through.

Space Planning is the desktop workbench for high-quality planograms. Planners model fixtures precisely, apply rules for facings/adjacencies, analyze shelf productivity (sales/GM per facing), and generate store-specific variants at scale. Tight ties to assortment, allocation, and floor planning ensure what's on the shelf matches the plan and physical constraints. Publishing workflows and store feedback loops shorten resets and improve compliance.

EKB is the governed content backbone for space/category operations, your single source of truth for products, attributes, hierarchies, fixtures, templates, and planogram assets. It centralizes permissions, versioning, and data validation; supports bulk operations; and feeds downstream tools (Floor Planning, Planogram/Space Automation, store execution). With consistent, auditably correct content, teams can scale localized planograms and maintain compliance across banners and regions.