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Seasonal Line Planning for Wholesale

Wholesale-seasonal-line-planning

Forecast demand for new products and collections 

PartnerLinQ's Seasonal Line Planning (SLP) is the engine that drives confident investment in new products, styles, and collections for wholesale success. By mastering the challenge of forecasting products that lack historical demand signals, we provide brands with high-fidelity projections needed to secure key sell-in volumes with customers and minimize risk. 

PartnerLinQ provides complete ecosystem that delivers on this vision through four core capability pillars:

End-to-End-Connectivity

End-to-End
Connectivity

Seamlessly link SKU-level forecasts, commercial goals, and material requirements across the B2B planning lifecycle. 


Granular-Control-Towers

Unified Data
Model

NPI product attributes, historical analog data, and forecast inputs reside on a single platform, eliminating the "siloed financial vs operational planning" challenge. 

Agentic-AI-Services

AI-Driven
Intelligence

Leverage ML for attribute-based product matching and running sell-in volume simulations to reduce risk in new product investments. 

The-Composable-Enterprise

Composability & Flexibility

The modular architecture allows the solution to be easily configured to incorporate external data signals and new forecasting models specific to seasonal lines. 

Features & Capabilities

PartnerLinQ provides the advanced predictive capabilities and scenario tools required to accurately forecast, model, and commit to new line performance in the wholesale environment. 

  • Attribute-Based Matching: Utilizes AI/ML models to identify and match new styles/SKUs to similar SKUs or past seasons based on detailed attributes (e.g., fabric, color, silhouette, price point). 

  • Trend & Promotional Modeling: Tools to incorporate promotional or trend-driven adjustments to forecasts, capturing market excitement, and competitive shifts. 

  • Analog Forecasting: Generate initial demand forecasts for NPIs by leveraging the performance history of similar products (analog forecasting), filling the demand signal gap. 

Business-Process
  • Sell-In Simulation: Ability to simulate sell-in volumes by customer or region based on the product forecast, ensuring alignment with sales strategy. 

  • Commitment Validation: Validate that the total simulated sell-in volume adheres to the financial guardrails and inventory constraints set in MFP. 

  • Lifecycle Management: Manage the phase-in/phase-out lifecycle of new products alongside existing core items. 

Business-Process
  • Forecast Accuracy: Continuously monitor the NPI Forecast Accuracy % against actual initial orders and subsequent sales. 

  • Bias Management: Analyze Forecast Bias % to identify systematic over- or under-forecasting tendencies and refine AI models. 

  • Performance vs. Projections: Track Projected Units/Sales vs Actual to quickly identify forecasting errors and apply corrective action. 

Business-Process

Technology

A solution's technology vision must align with your organization’s future aspirations. PartnerLinQ’s modern, composable architecture ensures a planning solution that is not only powerful today but will scale to meet your evolving needs. 

  • Cloud-Native & Multi-Cloud Architecture: Our scalable, cloud-native architecture is built for demand planning cycles, ensuring fast processing and seamless performance. We support multi-cloud environments, providing the flexibility to align with your organization’s cloud strategy. 

  • Composability: Built on an API-first and microservices architecture, our platform provides the extensibility and flexibility to adapt to your unique needs, helping you achieve a truly composable enterprise. 

Business-Process
  • Intelligent Data Applications Framework: Our framework allows you to easily onboard and enrich external data sets and factors with AI-based predictions, creating a richer input signal for your demand planning process and accelerating the evolution of your digital intelligence with ease. 

  • Trading Partner Network: Our native integration with your trading partner network allows for real-time data capture, ensuring your plans are always informed by the most current market signals. 

  • Seamless Data Flow: Our bi-directional integration capabilities with ERP, POS, Online Commerce, and WMS systems ensure a continuous flow of demand data for a single source of truth. 

  • Extensive Prebuilt Adapters: We offer prebuilt, composable integration adapters for over 80 enterprise application platforms, including SAP, Oracle, Microsoft Dynamics 365, Microsoft Dynamics Business Central, Manhattan Active Omni and Salesforce.  

Business-Process
  • Custom Algorithm & Model Development: The platform provides a unified environment for in-house development of custom algorithms and models, giving your teams the tools to continuously evolve the solution. 

  • Industry Knowledge Graph and Data Models: ParnterLinQ’s industry data models and supply chain knowledge graph instantly enable out of the box reporting, search and planning capabilities to a whole new level of sophistication and extensibility. 

  • Third-Party Analytic Integration: Easily integrate third-party analytics and leverage public APIs to expand the planning models and connect with external data sources. 

Business-Process

User Experience

SLP's user experience centers on visual comparison, easy adjustment, and generative AI guidance to build confidence in every seasonal launch commitment. 

  • Side-by-Side Analog Comparison: Visually presents the new product's forecast alongside the historical performance of its analog SKU, building transparency and confidence in the projection. 

  • Rapid Iteration: Ability to replicate and copy master plans and rapidly apply dynamic recalculations to reflect changes in sales strategy or customer commitments. 

  • Simulation Sandbox: A dedicated environment to simulate sell-in volumes and apply top-down or bottom-up adjustments to NPI forecasts without impacting the master plan. 

Business-Process
  • Generative AI Explainability: GenAI provides narratives explaining why a new product was forecast at a certain volume (e.g., "Forecast based on a 90% attribute match to the X-style from last season, with a 15% upward adjustment due to current trend signals"). 

  • Exception-Based Management: The system automatically flags NPI forecasts that fall outside established risk thresholds (e.g., high Forecast Bias %), directing planners to manage by exception. 

Business-Process
Implementation-Advantage

Implementation Advantage

Our SLP implementation is focused on rapidly activating your historical data and product attribute libraries to deliver high-accuracy analog forecasting from the first season. 

  • Rapid Attribute Configuration: Fast setup and ingestion of detailed product attributes, which are the core inputs for attribute-based product matching and AI forecasting models. 

  • Expert Enablement: Training focuses on helping planners effectively apply and adjust promotional or trend-driven adjustments and interpret NPI forecast risks. 

  • Configurable Modeling: Quick configuration of the ML models used for NPI forecasting, allowing the brand to prioritize the most effective forecasting methods (e.g., volume weighting, clustering). 

  • Seamless Data Onboarding: Streamlined integration with Product Lifecycle Management (PLM) and ERP systems to onboard new product information and historical performance data for analog forecasting. 

End Result & Business Benefit

PartnerLinQ’s SLP for Wholesale solution directly translates market intuition into measurable performance, ensuring that seasonal launches drive profitability and sales confidence. 

  • Maximized Success Rate: Achieve a high NPI Forecast Accuracy %, ensuring inventory investment is precisely matched to customer demand. 

  • Increased Revenue: Maximize the Contribution of NPIs to Seasonal Sales % by confidently committing and selling-in the right volumes to key accounts. 

  • Protected Inventory: Significantly reduce the risks of overbuying or understocking new products, which protects Gross Margin % and limits liquidation costs. 

  • Wholesale Trust: Provides sales teams with data-backed forecasts and simulations, strengthening confidence in new collection commitments to key wholesale accounts. 

End-Result-Business-Benefit
Pricing-Model

Pricing Model

PartnerLinQ provides overall business value and industry-specific intelligent planning technology and solutions for both current and future needs. We offer a simplified pricing model that provides predictability and transparency, empowering your business to invest with confidence.  

  • Tiered, Usage-Based Pricing: Our model is simple and transparent. You only pay for the tier that matches your actual usage each month, so you are only ever paying for what you use.  

  • Unified & Transparent Cost: Our unified pricing covers all core capabilities—including integration, data processing, the planning applications, and the embedded AI—eliminating hidden costs.  

  • Simplified Total Cost of Ownership (TCO): By consolidating all key functions into a single, usage-based model, we eliminate the hidden costs of managing multiple vendors and disparate systems, ensuring your investment delivers both immediate and sustainable business value.  


PartnerLinQ gives you the precision, agility, and control to turn seasonal volatility into a competitive advantage.
Contact us to schedule a demo and see the difference.

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FAQs

The solution leverages AI/ML models and attribute-based product matching to perform analog forecasting. It matches the new product to similar SKUs or past seasons based on shared attributes (e.g., material, price) to create a data-backed initial demand projection. 

Sell-in simulation allows brands to model the expected order volumes by specific customer or region based on the NPI forecast. It is crucial because it validates the brand's ability to meet NPI commitments to key wholesale accounts before production begins. 

Success is measured by the predictive quality of the forecast and the resulting sales, including NPI Forecast Accuracy %, Sell-through % for New Products, and the overall Contribution of NPIs to Seasonal Sales %. 

Planners can easily incorporate promotional or trend-driven adjustments into the analog forecast. The AI also uses external trend data sets via the Intelligent Data Applications Framework to enrich the demand signal for new styles. 

By providing a quantified, data-driven forecast, SLP minimizes reliance on gut feeling. Tracking the Forecast Bias % and NPI Forecast Accuracy % ensures that buy plans are rigorously grounded in predictable demand, avoiding costly overstocking. 

How resilient and agile is your supply chain?

If you encounter unexpected disruptions, lack of automation, and changing consumer attitudes, you’re not alone.

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