Retail success depends on plans that connect across functions. Intelligent financial planning replaces sequential handoffs with unified decisioning. Pre-season budgets inform assortment choices. Pricing strategies protect margin targets. Open-to-Buy decisions align with inventory flow. Built on interoperable solutions and agentic intelligence, retailers forecast with precision, model scenarios in real time, and synchronize finance and merchandising on a single platform. Decisions optimize for business outcomes, not functional silos.
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AI analyzes 100+ demand signals (market trends, shopper behavior, weather patterns, competitive pricing) to deliver continuously refined forecasts. Models adapt as conditions change, giving retailers the insight needed to set realistic preseason budgets, adjust in-season plans, and allocate inventory intelligently across channels and categories.
Agentic intelligence
AI agents identify variances before they impact performance by flagging categories trending off-plan, margin pressures emerging or inventory imbalances developing. The system surfaces top and bottom performers with contextual insights, freeing planning teams to focus on strategic responses rather than hunting through data for problems. Agents handle the analysis, planners make the calls.
Scenario agility
Lever-based scenario planning lets retailers model what-if strategies rapidly. Adjust sales assumptions, pricing, promotions, or inventory levels to see the impact on margin and cash flow before committing capital. Compare scenarios side-by-side. Stress-test preseason budgets. Evaluate markdown timing and promotional effectiveness. Make confident decisions with full visibility into profitability impact.
Unified planning
Financial plans interoperate with downstream merchandising systems. Sales targets, inventory budgets, Open-to-Buy, and margin goals flow to assortment, allocation, and replenishment teams in real time. Finance and merchandising work from synchronized data on a unified platform, eliminating manual reconciliation. Functions optimize for business outcomes, not in isolation.
Solutions
Solutions for successful retail financial planning
Turn financial targets into buying decisions
Translate revenue and margin targets into actionable merchandise plans with real-time Open-to-Buy tracking and scenario modeling. MFP connects financial planning with inventory decisions, eliminating reconciliation lag between finance expectations and merchandising execution through unified decisioning across teams.
Deliver the right value to customers while protecting margins
Support your financial plans with optimized price and promotions. Leverage AI, machine learning (ML), and advanced analytics to create data-driven price plans that continuously balance inventory and demand to increase sell-through, reduce waste and protect margins.
Intelligence that guides every decision
AI analyzes demand signals, detects performance variances and recommends actions across the planning cycle. ML continuously refines forecasts, identifies margin risks, suggests scenario adjustments, and surfaces exceptions requiring attention. Teams get intelligence that supports better decisions, not just more data to analyze.
Financial planning solutions run on a unified data cloud that connects planning, execution and operational systems without custom integrations. Embedded AI and a shared data model provide real-time synchronization across merchandise planning, pricing strategies and supply chain decisions through interoperable workflows.
Advisory and implementation services accelerate financial planning and pricing transformation, from initial configuration through ongoing optimization. Retail experts guide teams through process redesign, change management, and continuous performance improvement to maximize ROI and drive adoption across finance, merchandising, and pricing teams.
Cogntive financial planning automates the analysis of financial targets, demand forecasts, and Open-to-Buy budgets across categories and channels. Work that takes weeks in spreadsheets. AI continuously monitors performance against plan, surfaces variances before they impact results and recommends adjustments based on real-time data. Teams spend less time reconciling versions and hunting for errors, more time making strategic decisions about where to invest capital and how to protect margins.
Modern financial planning solutions should offer AI-driven forecasting that analyzes multiple demand signals, scenario modeling that shows financial impacts before you commit capital and exception management that alerts teams to variances early. Look for interoperable workflows that connect financial plans with assortment, allocation and pricing decisions—eliminating manual data transfers between systems. The platform should provide unified decisioning across finance and merchandising, not just financial reporting in isolation.
Financial planning supports mid-season adjustments without rebuilding entire plans. When market conditions shift or performance trends off-target, teams can model new scenarios, evaluate margin impacts, and adjust Open-to-Buy allocations in real time. AI continuously refines forecasts based on actual sales, flagging categories that need attention and recommending reallocation strategies. This transforms financial planning from a periodic exercise into an ongoing capability that responds to business reality.
Because they are built on a unified platform that shares data foundations with assortment planning, and allocation and replenishment. Financial targets flow directly to downstream systems. When you update revenue goals or adjust Open-to-Buy budgets, assortment planners see changes immediately. This interoperability eliminates reconciliation gaps between what finance expects and what merchandising executes, ensuring teams work from synchronized data and optimize for business outcomes, not functional silos.
Most retailers see results within the first planning cycle. Common early wins include 20%-50% improved forecast accuracy, reduced planning cycle time from weeks to days and lower labor costs through automated exception management. Retailers report better inventory control that reduces markdowns, improved margin performance through scenario planning, and stronger alignment between finance and merchandising teams that eliminates reconciliation delays and accelerates decision-making.
