Blue Yonder FAQ: AI-Driven Supply Chain, Planning & Fulfillment Answers

AI-driven financial forecasting uses machine learning to analyze large volumes of structured data (e.g., sales transactions, SKU-level demand) and unstructured inputs (macroeconomic indicators, supplier news, social sentiment) to predict revenue, margin, and cash flow more precisely. It continuously refines forecasts as real-time data flows in, improving timeliness. Finance and merchandise planning teams use these forecasts to set open-to-buy budgets, prices, and buy quantities with confidence while still applying human judgment to reconcile AI insights with business context. Success depends on high-quality data, cross-functional adoption, and continuous bias monitoring.

Blue Yonder Fulfillment combines real-time inventory visibility and order orchestration microservices to ensure the right product reaches the right customer through the optimal channel. Its Inventory service shows available to promise quantities at the enterprise and location level, while Commits calculates feasible delivery options, and Order Services then orchestrates the entire order lifecycle, sending proactive alerts if exceptions occur. Retailers and omnichannel planners use Fulfillment alongside Replenishment to maintain optimal stock and flow, boosting on-time/in-full metrics and reducing costly split shipments. It requires integration across channels and accurate inventory data to perform effectively.

Blue Yonder Merchandise Financial Forecasting is an AI-enhanced module that unifies top-down, middle-out, and bottom-up financial plans, keeping them synchronized with allocation and replenishment. It provides hierarchical planning and attribute analysis, letting merchants drill into categories, attributes, and channels while still maintaining a consistent overall plan. Automated reconciliation across hierarchies reduces manual rework and ensures that sales, margin, and inventory targets remain aligned. Users can model scenarios, collaborate across merchandising and finance teams, and adjust plans as demand signals or promotions change, improving cost control and revenue outcomes.

This service delivers cold start demand forecasts for new product introductions (NPIs) by using attribute-based demand modeling. When a product has little or no history, AI identifies look-alike items based on attributes such as category, size, color, and market factors, then clusters them to estimate a baseline. As early sales arrive, the model learns quickly to correct bias and forecast. Category managers and supply planners use these forecasts to plan inventory, pricing, and marketing for NPIs, reducing the risk of stockouts or overstock. It requires accurate attribute data and careful selection of comparable items.

Autonomous Delivery Date is a machine learning microservice that predicts reliable promised delivery dates for every order. It learns from supplier lead times, carrier service levels, cutoff times, network congestion, and historical performance to balance speed against cost. By combining order-to-shipment time and distance, it reduces the gap between promised and actual delivery dates, improving customer satisfaction. Retailers and e-commerce teams use it to compete with anytime/anywhere expectations without overpromising. Accurate carrier data and integration with order management systems are prerequisites for optimal results.

This AI microservice dynamically sets channel-specific safety stock by SKU and node. It continuously analyzes real-time demand signals, volatility, lead-time variability, and service targets to adjust buffers upward or downward. The result is a more adaptive stock policy that mitigates supply risk while avoiding excess. Planners use it alongside inventory optimization to improve fill rates, reduce carrying costs, and free working capital. Strong integration and data quality monitoring prevent overreaction to outliers.

Blue Yonders Markdown Predictor recommends when and how deeply to mark down products to achieve sell-through and margin goals. It analyzes factors such as current and future demand, inventory levels, seasonality, product attributes, and price. By analyzing large amounts of data across regions, climates, and stores, the AI recommends targeted markdowns that maximize margins and minimize excess inventory. Merchandisers and pricing managers use it to reduce manual guesswork and quickly test scenarios. Successful deployment depends on high-quality demand data and the ability to act on insights across channels.

Predictive analytics uses statistical and machine learning techniques to uncover patterns in historical and real-time data and project future outcomes. By examining correlations between variables, these models forecast demand, identify churn risks, optimize pricing, and guide inventory. It is used across operations, marketing, finance, and supply chain to improve planning and execution. Predictive analytics differs from basic reporting in that it proactively estimates what will happen and suggests actions rather than simply describing the past. Effectiveness depends on quality data, appropriate algorithms, and continuous validation to avoid overfitting or unintended bias.

Multi-enterprise collaboration services enable real-time coordination of planning, forecasting, execution, and compliance across multiple companies in a supply chain network. They provide a shared data environment where manufacturers, suppliers, carriers, and retailers can exchange orders, forecasts, and inventory positions in real-time. Operating on a single source of truth with AI-powered insights, partners can jointly respond to demand changes, allocate constrained supply, and manage exceptions. Collaboration services also govern regulatory and contractual compliance across jurisdictions. They improve resilience and agility but depend on trust, aligned incentives, and rigorous data governance among participants.

Multi-Enterprise Supply Chain Network Platforms provide the underlying technology to orchestrate supply chains across multiple independent enterprises. Built on a single network and data model, they allow companies to manage orders, inventory, transportation, and capacity across all trading partners. Blue Yonder's platform combines a multi-tier network with AI assistants and predictions to deliver real-time visibility and decision-making. Customers can compose new workflows, add capabilities, and integrate external applications quickly, giving them the agility to respond to disruptions or growth. These platforms improve forecast accuracy, reduce cycle times, and enable closed-loop execution, but they require deep integration and cooperation among network participants.

Network Planning models and optimizes the structure of your supply network where to locate factories, distribution centers, and stock points; what size they should be; and how to route products. Gartner defines network design as optimizing the location and function of supply, manufacturing, and distribution facilities, and using analytics to determine the best configuration. Advanced multiechelon inventory optimization builds strategies across multiple stages to meet demand while minimizing working capital and logistics cost. Such tools consistently deliver high returns, reducing total inventory by 10-30% while maintaining or improving service. Network Planning supports strategic and tactical decisions so companies can adapt as demand patterns shift.

Network Resilience ensures the supply chain can anticipate, absorb, and recover from disruptions. Resilience blends robustness handling unexpected events and agility adapting quickly. Risk management identifies potential threats and implements strategies such as diversified sourcing, real-time monitoring, and contingency plans to mitigate them. Vendor compliance programs contribute by enforcing quality standards, improving transparency, and reducing risk. Pairing these practices with scenario driven planning and multiechelon inventory buffers helps networks maintain service during shocks and accelerate recovery.

Network Stock Management balances inventory across all tiers and nodes of a supply chain so the right product is available at the right place and time. Using multi-echelon optimization, it simultaneously determines optimal stock levels across suppliers, plants, distribution centers, and stores, minimizing working capital while meeting service. AI-driven dynamic safety stock algorithms continuously adjust buffers based on demand volatility, supplier reliability, and lead time variability, mitigating risk and reducing excess. Companies deploying multi-echelon solutions routinely achieve 10-30% reductions in total inventory while maintaining or improving service. Success depends on clean, real-time data and coordinated planning across functions.

Stockout Predictor is an AI microservice that flags imminent out of stocks before they occur. It learns from real-time demand, inventory positions, lead times, supplier/carrier reliability, and event signals (promotions, weather) to estimate the probability and timing of stockouts at SKU allocation. It then recommends preventive actions to expedite, substitute, reallocate, adjust order quantities so planners protect service without overbuying. Clear thresholds, bias monitoring, and good master data are key to reliable alerts and adoption.

Supply Chain Strategist is a network design and scenario planning tool that creates a digital twin of a company's supply network. Gartner defines network design as optimizing the location and function of supply, manufacturing, and distribution facilities, and determining transport lanes and modes to support. Strategist allows users to model different configurations, evaluate costs, lead times, and carbon footprints, and choose the best design for strategic or tactical horizons. It incorporates multi-echelon inventory optimization to balance upstream and downstream stock and routinely yields 10-30% inventory reductions with improved service. Effective use requires good data and cross-functional collaboration.

Logistics Telematics applies telematics technology to track and manage vehicles, trailers, and assets in the transportation network. It leverages GPS, onboard diagnostics, and wireless networks to collect and transmit real-time data on location, speed, and equipment health. The telematics device sends this data via a wireless network to a server, where it is accessed by dispatchers for routing, dispatch, and performance management. Fleets use telematics to enhance operational efficiency, reduce idling, and comply with regulations such as electronic logging device (ELD) mandates. Benefits include visibility into vehicle and asset locations, predictive maintenance alerts, and improved driver performance.

Logistics Visibility provides an end-to-end, real-time view of shipments and inventory across the supply chain. Without real-time data and crosscompany collaboration, companies have little visibility into inbound freight, causing delays. A transparent supply chain shows where shipments are in transit, in warehouses, or at distribution centers and where they will be next, unlocking significant business value. Mapping the entire lifecycle and knowing where everything is enables better strategic planning and improves command over inventory, reducing cashtocash cycles as shipment timing becomes predictable. Logistics visibility also enhances collaboration, reduces detention costs, and supports sustainability initiatives.

Multi-echelon inventory management (MEIM) optimizes stock across every tier of the supply chain from suppliers to plants, distribution centers, and stores. Instead of setting safety stock independently at each node, MEIM looks at the entire network so inventory can be pooled and positioned. By aligning buffer stocks across echelons, companies reduce excess inventory, improve service levels, and build resilience; research shows MEIM can cut inventory costs by up to 25% and increase service levels 5-10%. Industries with high demand variability use MEIM to reduce holding costs and mitigate disruptions, but success depends on accurate demand signals and coordination across functions.

Network design is the strategic process of deciding where to locate factories, distribution centers, and stock points, and how goods should move through them. It balances transportation costs, facility investments, inventory levels, service requirements, and sustainability. A well designed network streamlines operations and improves customer satisfaction; a poor one leads to high costs and inefficiencies. Planners use scenario modeling to evaluate different configurations and to answer questions such as whether to open new sites, consolidate warehouses, or change transport modes. The goal is a scalable, resilient network that aligns with business strategy and demand patterns.

Network optimization applies advanced analytics to design and manage supply chains in the most efficient, cost-effective way. It determines the optimal number, size, and location of warehouses, distribution centers, and production facilities, selects the best transportation modes and routes, and sets inventory levels that meet service targets while minimizing costs. By evaluating transportation, facility, and inventory decisions simultaneously, optimization reduces operating costs, improves service, and enhances overall performance. Organizations use it to compare scenarios, such as near shoring versus off shoring, and to reconfigure networks in response to market changes. Effective optimization requires reliable data and the ability to model complex trade-offs.

Supply chain risk management (SCRM) is the process of identifying, assessing, mitigating, and monitoring risks that could disrupt supply chains, such as natural disasters, supplier failures, cyberattacks, or demand shocks. Effective SCRM considers internal and external risks across all tiers; disruptions anywhere in a multitier supply chain can trigger ripple effects on production. Managers use tools like risk heat maps, scenario planning, dual sourcing, and inventory buffers to reduce impact. Proactive SCRM helps companies avoid slowdowns, protect revenue, and ensure regulatory compliance. Success requires cross-functional coordination, up to date data, and continuous monitoring.

Supply chain traceability is the ability to track and record the provenance of materials, components, and subassemblies through every stage of production and distribution. BSR defines it as tracking the journey of products and their inputs from origin to end. Effective traceability requires documenting the chain of custody, transportation, and warehousing records to provide a complete history from raw material to finished product. This information enables companies to ensure regulatory compliance, conduct targeted recalls, verify ethical sourcing, and support sustainability claims. Traceability goes beyond visibility by proving where and how a product was made. Building it requires standard data formats, interoperable systems, and cooperation across the supply chain.

Stockout Predictor is an AI microservice that flags imminent out of stocks before they occur. It learns from real-time demand, inventory positions, lead times, supplier/carrier reliability, and event signals (promotions, weather) to estimate the probability and timing of stockouts at SKU allocation. It then recommends preventive actions to expedite, substitute, reallocate, adjust order quantities a"so planners protect service without overbuying. Clear thresholds, bias monitoring, and good master data are key to reliable alerts and adoption.

The Network Foundation is a multi-enterprise, real-time platform that connects all trading partners on a single network. Traditional control towers built on loosely coupled systems struggle because data sits in silos and batch updates create delays. A network-based foundation overcomes this by letting every supplier, carrier, and customer share the same real-time data through community-wide master data management. This many-to-many network delivers real-time visibility and agility across the supply chain and speeds partner onboarding. It serves as the base for network control towers, collaboration, and autonomous agents that optimize inventory, transportation, and execution across the enterprise.

Shared planning services (calendars, hierarchies, workflows) that speed implementation and keep apps in sync. 

Billing and revenue management tools automate the capture, rating, invoicing, and revenue recognition of logistics and value added services. They record every chargeable activity—handling, storage, and transportation—and generate invoices automatically, significantly reducing manual workload. These systems support customized billing profiles and provide detailed charge breakdowns, improving transparency and reducing disputes. By offering real-time visibility into billing status, they accelerate cash collection and ensure compliance with complex regulations. Finance teams use them to prevent revenue leakage and adapt pricing as new services are introduced, but accurate billing requires reliable operational data and strong integration.

Blue Yonder's Customer Success and Support Services help organizations adopt the platform and continuously realize value. Dedicated teams handle onboarding, product training, and proactive health checks, while Technical Account Managers learn customers' workflows, script solutions to common issues, and translate business needs into technical solutions. Customers gain access to knowledge bases and experts for troubleshooting, upgrades, and roadmap guidance. This support is critical for adoption; studies show that only about 35% of supply chain professionals feel they leverage most of their tools' capabilities and usability, and training drives success. Ongoing engagement and a culture of continuous learning are key to maximizing ROI.

Blue Yonder Data Management Services clean, standardize, and synchronize data across ERPs, WMS, TMS, and partner systems to create a single source of truth. They integrate master data, enforce governance rules, and update changes in near real-time. With centralized and cleansed data, companies can unlock real-time analytics and AI-driven decision-making, substantially reducing delays and improving inventory accuracy. Implementing this single source of truth requires robust integration, sustained data quality initiatives, and strong data stewardship. With high-quality data, planners and operators make faster, more informed decisions.

Regional Technical Account Manager (TAM) services provide named experts who act as trusted advisors throughout the product lifecycle. These TAMs understand customers' technical setups and workflows, provide tailored training and optimization guidance, and help resolve issues before they affect operations. They monitor common support questions, create scripts to address recurring problems, and coordinate escalations, upgrades, and compliance with service-level agreements. By acting as a bridge between business and technical teams, TAMs help customers extract maximum value from their solutions and ensure consistent adoption across regions and teams. Their effectiveness depends on strong communication, regional knowledge, and close collaboration with customer teams.

Trading Partner Network Services enable real-time collaboration and visibility across all tiers of a supply chain network. After Blue Yonder's acquisition of One Network Enterprises, customers can collaborate with suppliers, carriers, and distributors on a single multi-enterprise platform. The network provides a single source of truth enhanced by AI assistants and predictions, so participants can see inventory and goods movement upstream and downstream, and act before disruptions. It supports flexible management of capacity, inventory, and transportation, and its composable architecture lets customers add new capabilities. Successful participation requires data quality, integration with partner systems, and alignment of processes across organizations.

Integration platforms are technology layers that connect disparate supply chain systems, legacy and modern, into a cohesive ecosystem. They provide agnostic connectors to quickly integrate TMS, WMS, ERP, and partner systems without brittle, point-to-point connections. A supply chain integration platform centralizes data and processes, enabling real-time transfer of orders, inventory, and shipment information; it also supports cloud-to-cloud, hybrid, and B2B integrations, and offers pre-built connectors and low-code. Benefits include improved transparency, faster deployment, reduced operational costs, and scalability. However, integration projects often face challenges such as incompatible data formats and poor data quality. About 65% of projects fail due to these issues, so successful implementations require robust data governance and quality.

Platform extensibility services let customers add new modules, logic, or UI elements to the Blue Yonder platform without a disruptive rebuild. In software engineering, extensibility means a system can absorb new features or modifications without reconstructing its core. By making the underlying data model and APIs open and upgrade-safe, developers can integrate niche workflows, custom analytics, or partner applications while still receiving updates. Extensibility lengthens the platform's life, lowers total cost of ownership, and empowers teams to innovate safely and rapidly.

Blue Yonder Billing Management automates the capture, rating, and invoicing of logistics and value-added services so companies can bill accurately and quickly. Modern billing systems automatically generate invoices, reduce manual tasks, and provide real-time visibility into billing. They record every chargeable activity, support customized billing profiles, and produce detailed reports. Accurate, timely billing improves cash flow, reduces disputes, and ensures compliance with complex customer regulations. Finance teams use this service to turn operational events into revenue while adapting to new service offerings.

Chain of Custody provides end-to-end tracking of high-value or regulated products across the entire supply chain. A robust chain of custody solution documents who has what and records the movement of goods through every step. It supports complex serial, IoT, or hybrid tracking with capabilities to split, mix, or relabel. Transparency discourages theft and enables targeted recalls; knowing a product's origin and history helps identify and fix issues. Companies use Chain of Custody to ensure compliance, protect brand integrity, and give customers confidence about product provenance.

Blue Yonder Connect is the integration layer that links Blue Yonder applications with enterprise systems and trading partners. It creates a single source of truth by synchronizing data from ERPs, WMS, TMS, and external systems. Real-time integration helps overcome the 65% failure rate of projects caused by incompatible data formats and poor data. Connect provides low-code tools, APIs, and pre-built adapters so IT teams can build data pipelines across cloud, hybrid, and on-premises environments; a large connector library and REST API support enable both technical and non-technical users to automate flows.

This adapter synchronizes Blue Yonder solutions with SAP S/4HANA, ensuring that orders, inventory, and financial data flow seamlessly between the ERP and supply chain applications. It uses standardized communication protocols such as REST, OData, and IDoc to exchange data across on-premises and cloud environments. Prebuilt connectors and visual interfaces simplify integration and support both real-time and asynchronous patterns. SAP connectors bridge legacy ECC systems and S/4HANA Cloud, providing secure, auditable transactions and strong performance. The adapter reduces manual data entry, preserves data integrity, and accelerates order-to-cash cycles.

The Additional Instance option provides customers with a sandbox environment, an isolated space where integrations, configurations, and updates can be tested without impacting production. This instance mirrors production but remains separate, enabling safe testing of new connectors, custom logic, or training scenarios. It helps prevent unintended disruptions, especially when integrating third-party services or custom integrations. Access controls and monitoring guardrails keep the sandbox isolated and governed.

The API & Expansion Pack adds a large library of pre-built connectors, templates, and REST APIs to Blue Yonder Connect. Integration platforms show how a massive connector library with 200+ native integrations and REST API support enables users to build pipelines across SaaS apps, databases, and cloud warehouses without heavy coding. Similarly, the Expansion Pack gives Blue Yonder customers more adapters for EDI and API integrations, plus low-code tools to design custom flows. Users can create new APIs or connect to external ones via point-and-click interfaces, speeding deployment and reducing reliance on specialized developers.

The Enterprise edition is designed for complex, large-scale integrations. It includes enterprise-grade API management, data governance, and support for on-premises, cloud, and hybrid deployments. As seen in integration platforms like Jitterbit and Dell Boomi, enterprise solutions offer API creation and management, pre-built templates, and connectors, and support both real-time and batch processing. They come with extensive connector libraries, drag-and-drop interfaces, and robust workflow orchestration to handle high volumes and diverse data sources. The Enterprise edition also emphasizes security, monitoring, and service level commitments for mission-critical supply chain operations.

The Extension option adds advanced API creation and customization capabilities. Users can build new APIs or extend existing ones via point-and-click interfaces and pre-built templates. This allows tailored integration flows, such as new event triggers, complex transformations, or third-party adapters, without modifying the core platform. A modular, plug-in architecture supports additional connectors and provides real-time monitoring, execution logs, and alerting. By extending the integration layer, enterprises can innovate quickly, connect niche applications, and maintain upgrade-safe customizations.

This adapter synchronizes Blue Yonder solutions with SAP S/4HANA, ensuring that orders, inventory, and financial data flow seamlessly between the ERP and supply chain applications. It uses standardized communication protocols such as REST, OData, and IDoc to exchange data across on-premises and cloud. pre-built connectors and visual interfaces simplify integration and allow real-time and asynchronous. SAP connectors bridge legacy ECC systems and S/4HANA Cloud, providing secure, auditable transactions and performance. The

This connector integrates Blue Yonder with SAP HANA, SAP's in-memory database platform. It uses standard interfaces such as REST, OData, and RFC to exchange data in real-time. Prebuilt connectors and visual mapping tools simplify integration and support both real-time and asynchronous patterns. The connector bridges on-premises SAP systems and SAP HANA Cloud, ensuring continuous data access and secure, auditable transactions, while monitoring and alerting provide visibility into integration health. This helps companies synchronize orders, forecasts, and inventory across Blue Yonder and SAP environments.

The Standard edition is the core integration layer that connects Blue Yonder applications to ERPs, WMS, TMS, and other systems. It provides lowcode/nocode automation, a large library of ready-made connectors, and REST API support so business users can build data pipelines without heavy programming. Prebuilt templates accelerate implementation and reduce rework. Security features such as role-based access, encryption, and audit logging protect data, while real-time and batch integration keep master data, orders, and inventory synchronized across on-premises and cloud environments enabling a single source of truth and consistent planning.

Blue Yonder Monitor tracks the health of integration processes and supply chain transactions in real-time. It provides dashboards, execution logs, and alerting so users can spot bottlenecks, delays, or failures. Logs record each transaction, and support root cause analysis, while notifications trigger when service level thresholds are breached. Monitoring also captures system performance and usage metrics, helping teams optimize resource allocation and maintain compliance. This proactive oversight reduces downtime, accelerates troubleshooting, and ensures data flows remain reliable.

Multi-Dimensional Monitoring extends basic monitoring by correlating events across multiple data domains, orders, shipments, inventory, carriers, and vendors to provide deeper insights. It aggregates and visualizes metrics to reveal patterns and anomalies across the network and leverages real-time monitoring and alerting tools to detect deviations. Enhanced transparency allows stakeholders to trace issues back to their origin and coordinate corrective action. This holistic view helps prevent cascading failures, improves decision-making, and drives continuous improvement across the supply chain.

Network Telematics uses telecommunications and information processing technologies to collect and transmit location, speed, and diagnostic data from vehicles. GPS receivers, onboard sensors, and wireless networks send data to a central service, where fleet managers monitor routes and dispatch. As telematics adoption grows due to business demand and regulatory mandates, fleets use this data to improve efficiency and sustainability reducing idling, ensuring compliance, and optimizing routes. Benefits include real-time shipment visibility, proactive maintenance alerts, and enhanced driver performance. Blue Yonder integrates telematics feeds to provide accurate ETAs and support event driven orchestration across the network.

Supply Chain Foundation Base is the common data and integration layer that underpins Blue Yonder's planning and execution solutions. It consolidates master data from ERPs, WMS, TMS, and partner systems into a single source of truth, synchronizing updates across applications in real-time. Eliminating data silos ensures consistent, accurate, and up-to-date information for analytics and decision-making. Establishing such a foundation requires robust integration, data governance, and appropriate controls. Once in place, the foundation enables advanced analytics, AI models, and composable apps to operate on clean data, reducing latency and improving collaboration across the enterprise.

Data Management and Analytics unify, cleanse, and govern supply chain data to support descriptive, predictive, and prescriptive insights. By integrating data from disparate systems and creating a single source of truth, organizations eliminate silos and ensure consistent, up-to-date information. Real-time synchronization improves visibility, reducing delays by up to 58% and increasing inventory accuracy by 30%. Analytics teams then use this trusted data to build dashboards, generate forecasts, and optimize decisions. Implementing such capabilities requires robust integration, data quality programs, and security.

An Integration Platform as a Service (iPaaS) is a cloud based platform that connects disparate applications, data sources, and trading partners. It centralizes data and processes to provide a real-time view of the supply chain and supports cloud-to-cloud, hybrid, and B2B integrations. iPaaS offerings include prebuilt connectors, lowcode API builders, and mapping tools that make it easy to connect ERPs, WMS, TMS, and partner systems without extensive development. They improve transparency, reduce operational costs, and accelerate deployment by offering reusable components and managed security. Blue Yonder's iPaaS foundation enables composable applications and rapid onboarding of new partners.

Supply chain monitoring and alerting uses a control tower to aggregate data, provide real-time visibility, and send actionable alerts across procurement, manufacturing, transportation, and fulfillment. Control tower software integrates information from multiple systems and gives users up to date views of inventory, shipments, and orders. It tracks shipments in real-time and triggers alerts if routes deviate, inventory drops below thresholds, or production issues occur. Advanced analytics, dashboards, and collaboration tools help teams diagnose issues and coordinate responses. Effective monitoring depends on integrated data, clear escalation rules, and the ability to prioritize alerts to avoid overload.

Supply chain platform infrastructure refers to the digital and physical foundation that supports real-time, responsive supply chains. Cloud-based inventory systems, real-time data platforms, edge computing, and scalable hosting architectures are essential to share updates instantly and run predictive analytics. Without robust infrastructure, data pipelines lag, and predictive models cannot operate. Modern platforms require open APIs for integration and must be built for scalability and resilience with redundancy, proactive monitoring, cybersecurity, and disaster recovery capabilities to avoid costly blind spots. Good infrastructure allows companies to connect partners quickly, support composable applications, and adapt to growth or disruptions.

The Blue Yonder Platform is a composable, open architecture that provides building blocks for end-to-end supply chain solutions. Like other modern supply chain platforms, it offers an open, collaborative foundation for data and process orchestration, with hundreds of connectors that harmonize information across ERP, WMS, TMS, and partner systems. Customers can use lowcode tools to build custom workflows, dashboards, and microservices without rewriting core code. Composable architecture means you can plug in best-of-breed modules demand planning, order management, and AI agents while reusing a unified data model. This reduces integration costs, enables rapid innovation, and supports a thriving partner ecosystem.

The Platform Expansion Pack adds specialized microservices, connectors, and API capabilities to the base platform. Rather than forcing a monolithic system, it lets you integrate best-of-breed solutions into your existing ERP or planning backbone to address specific needs. New adapters for EDI/API integration, advanced analytics modules, and prebuilt process templates extend functionality without rearchitecting core systems. The result is a more responsive, efficient supply chain that can adapt quickly to changing requirements.

The Supply Chain Foundation Snapshot Service creates a read-only, point-in-time copy of your environment for testing and training. A snapshot is a point-in-time copy of data capturing its current state; it preserves the exact configuration of applications, data, and settings so teams can safely trial upgrades or new integrations without risking production. Snapshots are space-efficient and support quick development, but they are best for short-term development or rinse and repeat. In supply chain contexts, snapshots allow IT teams to reproduce the foundation for user training, troubleshoot issues, and validate configuration changes before deployment.

The Supply Chain Planning Foundation unifies the data models and core services that drive demand forecasting, supply planning, inventory optimization, and sales & operations planning. Supply chain planning optimizes the manufacturing and delivery of goods from raw materials to customers and encompasses functions such as demand forecasting, inventory management, response and supply planning, and S&OP. Integrated planning platforms centralize data to deliver a single, unified view and support advanced analytics and AI so planners can adjust dynamically and collaborate across teams. Unified planning foundations eliminate manual consolidation, improve forecast accuracy, and accelerate scenario modeling for smarter what-ifs and decisions.

A supply chain SaaS platform delivers planning, execution, and analytics capabilities via the cloud. SaaS solutions are accessed over the internet on a subscription basis, so there's no software to install. For supply chain teams, SaaS platforms unify procurement, logistics, and inventory management into a single system that scales as the business grows. Benefits include lower upfront costs, rapid deployment, continuous updates handled by the provider, and real-time collaboration. Built-in analytics and AI help companies monitor KPIs, predict demand, and respond quickly to disruptions.

Edge technology processes data close to the source on sensors or local gateways instead of sending everything to a distant data center. By moving computing power nearer to where data is generated, edge computing cuts latency from tens of milliseconds to a few milliseconds, reduces network traffic by 70 €"90%, and allows autonomous decision making. A layered architecture collects data on end devices, processes it on edge nodes, and uses the cloud for longer term storage. In supply chains, edge technology powers real-time tasks such as automated receiving, damage detection, and predictive maintenance, even in environments with poor connectivity.

Blue Yonder Order Services is a microservices-based layer that coordinates order capture, promising, and fulfillment across channels. A composable architecture with more than 40 independent microservices enables rapid time-to-market and high scalability, processing thousands of transactions per second. Key microservices include real-time inventory availability, order orchestration, and fulfillment execution; machine learning models provide adaptive fulfillment, and warehousing options (curbside pickup, BOPIS, same-day delivery), and deliver insights to reduce costs and improve customer experience. Businesses can start with the capabilities they need and expand later, integrating via APIs for personalized experiences.

Commerce Insights & Actions uses real-time analytics to understand customer behavior and optimize pricing, promotions, and assortment across channels. real-time e-commerce analytics provide immediate feedback on metrics such as customer behavior, orders, and product performance, enabling businesses to adjust marketing and pricing strategies as events unfold. Digital platforms combine operational data and experience data from web, mobile, social, and IoT sources to create a 360-degree view of each customer. AI and machine learning identify patterns, predict demand, and personalize offers, so retailers can deliver the right product at the right time while avoiding overdiscounting and stockouts.

Customer Order Visibility provides end-to-end visibility of every order from capture through fulfillment. Without real-time data and cross-company collaboration, companies have little insight into inbound freight, causing delays. A transparent supply chain allows you to see where shipments are in transit, at warehouses, or in distribution centers, and plan accordingly. real-time visibility improves execution, reduces detention and demurrage fees, optimizes lanes and lead times, and increases collaboration with suppliers. Knowing when shipments change custody gives better command over inventory and accelerates cash.

Detailed Scheduling generates precise production schedules and allocates resources across factories or lines. In production planning, detailed scheduling involves creating a comprehensive timeline and sequence of tasks, considering equipment availability, setup times, and dependencies to ensure smooth production. Resource allocation assigns labor and machines to jobs, balancing workloads to maximize utilization and minimize idle time. By optimizing sequences and reacting to real-time constraints, Blue Yonder's scheduler reduces bottlenecks, improves throughput, and aligns manufacturing with changing demand. Integrated with planning and execution systems, it updates schedules as conditions change, providing a feasible plan that operations can trust.

Dynamic segmentation continuously groups customers, products, or demand profiles based on real-time behaviors and context. Unlike static segmentation, which relies on fixed attributes, dynamic segmentation adapts to changing patterns using advanced analytics, and by analyzing purchase history, preferences, and external signals, the system identifies segments that evolve as customer behavior or market conditions shift. This allows businesses to tailor pricing, promotions, allocation, and supply strategies for each segment, improving satisfaction. Supply chain planning, dynamic segmentation can also classify items by demand variability or lead times to optimize inventory and service levels.

The Fulfillment Sourcing Simulator is a scenario planning tool that uses a digital twin of your supply chain to test sourcing and fulfillment strategies before making changes. A digital twin is a virtual replica of the physical supply chain that uses real-time data and simulation to improve visibility, predict issues, and optimize. It lets professionals subject their network to disruptions or demand shifts to see the effects and identify potential. Digital twins integrate IoT sensors, ERP, business intelligence, and AI to provide a data-driven view of. By experimenting with sourcing rules, lead times, and logistics options, companies can select the best strategy without risking service or costs.

Intelligent Rebalancer is a cloud-native microservice that reallocates inventory across the network in near real-time. It uses AI/ML and an optimization engine to evaluate cost, service levels, margins, and sustainability, then issues recommendations. The microservice runs continuously during execution to correct course when disruptions occur, complementing your planning system and integrating with ERPs. It can be deployed on its own, or with other microservices, and connects to third-party systems to provide rapid, profitable reallocation.

Inventory optimization balances stock levels to meet customer needs while minimizing cost. It analyzes historical sales and demand signals to set reorder points and orders. Unlike basic inventory management, optimization actively adjusts stocking policies to maintain service levels and avoid overstock/understock. Modern solutions use AI to sense supply chain disruptions and demand volatility, enabling agile responses in real-time. The goal is to free working capital, reduce carrying costs, and improve fill rates across the entire network.

Inventory segmentation allocates stock based on predefined criteria such as customer groups, channels, or fulfillment methods, ensuring the right inventory is reserved for the right demand. In manufacturing, AI and real-time analytics further classify inventory by demand patterns, profitability, and service level. This allows planners to apply different strategies for fast moving versus longtail items, simulate the impact of classification changes, and balance priorities among channels and customers. Effective segmentation protects revenue, improves service and forecasting, and gives manufacturers the agility to reallocate stock when conditions change.

Order collaboration enables buyers, suppliers, and logistics partners to work from a single, shared view of purchase orders. Studies show that 77% of companies invest in deeper supplier relationships because poor collaboration leads to disruptions, higher inventory, and lost revenue. PO collaboration tools allow all parties to confirm forecasts, align production schedules, and react to exceptions quickly. For make-to-stock, configure-to-order, and make-to-order strategies, collaboration means sharing demand signals, coordinating capacity, and ensuring materials arrive when needed. Better communication improves on-time delivery, reduces expediting costs, and builds trust across the supply chain.

Order Optimization applies AI-powered sourcing and simulation to decide which inventory to allocate for each order, balancing delivery speed, cost, and margins. Blue Yonder's solution provides accurate real-time availability and personalized fulfillment. Machine learning models predict the cost, location, and speed trade-offs of different fulfillment options, enabling retailers to lower service costs while still meeting. It prevents stockouts and delays by selecting the best node for each order and allocating labor and delivery resources. The result is improved customer satisfaction, optimized inventory utilization, and better ROI.

Order Promiser ensures that every commitment you make to customers can be kept. It provides accurate delivery dates based on real-time inventory, capacity, and transportation constraints, and offers personalized, market-based fulfillment. By avoiding stockouts and processing delays, it delivers on promises and maintains customer loyalty. Smart resource allocation optimizes labor and transportation resources to execute on. Integrated dashboards and AI-driven insights help planners simulate fulfillment options and choose the most profitable.

Order Sequencing defines the order in which production or fulfillment tasks are executed to maximize reliability and efficiency. In production, scheduling software determines the sequence and timing of tasks to best use available resources and meet delivery deadlines. It considers material availability, ship dates, and constraints such as allergens, packaging, or sequencing plans. It allocates work to specific work centers and times, minimizing idle time, reducing work-in-progress inventory, and ensuring production stability. Consistent sequencing helps manufacturers and fulfillment centers meet service targets while coping with changes in demand and capacity.

Order Slotting & Scheduling assigns orders to specific time slots and resources to ensure on-time delivery. It optimizes fulfillment by considering delivery deadlines, transportation, and warehouse capacity and resources. Advanced systems use real-time data integration, predictive analytics, and automation to adjust slotting and scheduling. These capabilities can be standalone or integrated into a TMS or WMS; they improve reliability, reduce failed deliveries, and increase customer satisfaction. Data-driven planning and continual adjustment help identify bottlenecks and allocate resources efficiently, making it easier to meet delivery.

Blue Yonder's Store Execution app digitizes core in-store inventory work so associates can keep on-hand records accurate in real-time. On a mobile device, they can scan, look up items, receive deliveries, perform cycle counts, and make inventory adjustments offline, feeding a single source of truth that supports omnichannel promises and faster, error-free store operations.

Collaborative order management connects buyers, suppliers, and logistics providers on a shared platform so everyone works from the same purchase-order data. Blue Yonder's network (via One Network) unifies supply-side and demand-side order orchestration, inventory planning, and logistics planning, with embedded business intelligence and real-time exception. Solutions like TPSynergy extend your ERP to external partners so purchase orders and changes sync automatically to a collaboration portal, giving suppliers complete visibility and preventing errors. Alerts and closed-loop acknowledgements improve reliability, and notify partners of, leading to fewer disruptions and faster cycle times.

Commerce fulfillment is the end-to-end process of getting online orders from your store to the customer. In an e-commerce context, it includes receiving bulk goods, storing SKUs in a warehouse, picking and packing orders, printing shipping labels, shipping them, and handling returns. Integration between your online storefront and warehouse management system ensures orders flow instantly into the warehouse, generating pick lists and shipping documents. Efficient fulfillment reduces late deliveries and errors so you meet customer promises at scale while controlling costs.

Inventory optimization aims to hold just enough stock to meet customer demand without tying up excess cash. It uses historical sales and demand signals to set reorder points. Unlike basic inventory management, optimization continuously adjusts stocking policies to maintain high service levels while avoiding overstock. Modern solutions incorporate AI to sense disruptions and demand volatility, enabling agile adjustments and real-time visibility across the supply chain. The result is freed working capital, lower carrying costs, and higher fill rates.

Inventory visibility is the ability to monitor stock levels in real-time and know where each SKU resides across warehouses, fulfillment centers, and in transit. With accurate visibility, companies can reduce stockouts and improve allocation of resources across channels. real-time inventory data supports omnichannel operations, ensuring products are accounted for on every channel and preventing the embarrassment of selling items that aren't actually in stock. Visibility is the foundation for resilient, responsive supply chains and happier customers.

Order management covers the end-to-end process of receiving, processing, fulfilling, and tracking customer orders. In supply chain management, it begins with order capture, continues through inventory checks, order processing, and picking/packing, and ends when the customer receives the order. Effective order management ensures timely, accurate deliveries and includes customer service functions like handling returns. By consolidating orders across channels and providing real-time tracking, order management systems boost customer satisfaction, enhance inventory visibility, and streamline operations.

Blue Yonder's Robotics Hub is a vendor-agnostic platform that connects all your warehouse robotics and automation systems to your WMS. It accelerates the onboarding of multiple robotics vendors and improves visibility across automation solutions without locking you into one provider. Standard APIs simplify integration; a real-time dashboard provides centralized visibility across robots; dynamic workflows coordinate outbound fulfillment and replenishment; and alerting enables proactive responses to exceptions. By providing a single view, Robotics Hub increases utilization, offers operational flexibility, and speeds time to value.

Order management software streamlines the entire order lifecycle from order receipt through fulfillment and tracking. It consolidates orders across multiple channels and helps businesses manage and fulfill them efficiently, ensuring timely deliveries and boosting customer satisfaction. Essential features include real-time inventory tracking and sales order processing, integration with e-commerce platforms, and financial and customer data management. By automating these processes and providing insights, order management software minimizes errors, shortens fulfillment cycles, and enhances the customer experience.

Production scheduling creates a detailed timetable for manufacturing tasks and allocates resources accordingly. It develops a comprehensive production timeline and sequence of activities to ensure smooth. Scheduling assigns tasks to workstations or production lines, taking into account equipment availability, setup times, and jobs. Resource allocation then determines the optimal distribution of labor and equipment to balance workloads and maximize productivity. The objective is to minimize idle time and bottlenecks, enabling manufacturers to meet delivery deadlines and adapt to changing demand.

Store inventory management involves ordering, storing, and using a retailer's stock of raw materials, components, and finished goods in a way that meets customer demand while keeping costs low. Effective systems ensure accurate tracking across locations and maintain optimal levels so stores don €TMt overstock or run out, improving profitability. Modern solutions use barcodes, RFID, and analytics to forecast demand, automate replenishment, and provide real-time visibility into each SKU's status, enabling quick decisions and reducing shrinkage.

Store operations execution turns merchandising, pricing, promotion, and space planning decisions into flawless in-store execution. AI-enabled tools align operations across omnichannel stores, improving demand forecasting and replenishment while reducing manual work. Digital platforms give associates task lists and planograms instead of paper guides, so teams know exactly what to do from receiving deliveries to updating prices. This approach directly impacts customer experience, inventory accuracy, and sales.

Commits is a cloud-native microservice that calculates accurate delivery options and timeframes (order by and get by promises) for every order. Integrated with the order management and inventory services, it analyzes real-time inventory, capacity, and logistics constraints to determine the best way to fulfill an order. A single workflow engine provides an enterprise view across all order states, with proactive monitoring, and this ensures customers receive transparent delivery promises and drives higher on-time delivery performance.

The Customer Order Assistant (COA) is an AI-driven assistant that automates tedious order management tasks. It handles repetitive activities like order acknowledgements and change management, freeing staff to focus on other tasks. COA analyzes inventory data, supplier performance, and lead times to recommend next best actions, while centralizing communications with suppliers, and this reduces manual workload, shortens cycle times, and improves decision-making as conditions change.

Inventory Service provides a real-time, unified view of stock across the enterprise and at individual locations. It delivers a single source of truth so teams can locate and reserve products accurately, avoiding overselling, and the microservice integrates with other order management and fulfillment functions, enabling real-time ATP (available to promise) calculations and more precise planning. Synchronizing inventory data across channels and systems supports omnichannel strategies and enhances customer experience.

Blue Yonder HR Scheduling uses AI-driven labor optimization to create store schedules that match business demand with employee skills and preferences. Modern workforce management solutions include modules for labor budgeting, demand forecasting, employee scheduling, and time & attendance; AI can instantly generate optimized schedules, improving productivity and offering employees more predictable shifts. The service helps retailers control labor costs, ensure compliance, and increase employee satisfaction by incorporating availability and fairness into the schedule.

Time & Attendance captures employee hours accurately and automatically, replacing manual timesheets. Automated tracking records time in real-time, simplifying payroll and reducing costs. It ensures employees are paid correctly, prevents overtime, and helps businesses comply with labor regulations by maintaining auditable records. By streamlining clock-in and clock-out processes, the system increases productivity and gives managers up-to-date visibility into staffing levels.

Warehouse Labor Management monitors and improves workforce productivity in distribution centers. These systems record standard times for tasks and compare them to actual performance, enabling objective measurement of throughput. Benefits include maximizing productivity, spotting improvement opportunities, planning staffing levels, increasing operator throughput, and ensuring optimal task execution. real-time dashboards analyze efficiency by operator, shift, or department, so managers can redistribute workloads and adjust incentives. This leads to higher utilization, reduced labor costs, and a safer, more efficient warehouse.

Labor management is the discipline (and software) for planning, measuring, and improving workforce performance, often by defining engineered standards, tracking task times, and surfacing real-time productivity insights. In warehouses, an LMS monitors activities and compares actuals to standards so leaders can coach, plan labor, and hit cost and service targets. Benefits include higher utilization, better accountability, and more accurate staffing during peaks. Think of it as the layer that optimizes people, complementing the WMS process control.

In-store food service needs daily production plans that translate demand forecasts into precise prep lists, recipes, and run schedules while enforcing food-safety controls. Modern fresh-production systems balance ingredient availability, yields, and dayparts to minimize shrink and keep cases full; they also help track temperatures, critical limits, and corrective actions under HACCP. Combining AI-based forecasting with digital checklists and monitoring reduces waste and ensures consistent quality and compliance across deli, bakery, and hot bars.

Warehouse Labor Management applies engineered standards and real-time analytics to maximize DC productivity. Teams establish fair, studied time standards, then compare actual performance to those baselines to identify coaching opportunities, allocate work, and forecast staffing. Done well, WLM reduces labor cost and turnover while improving throughput and on-time fulfillment, especially during promotions and seasonal spikes. It complements WMS by adding clear visibility into people-level KPIs and bottlenecks across receiving, picking, packing, and shipping.

Workforce Management (WFM) covers forecasting labor needs, budgeting, scheduling, time & attendance, compliance, and performance tracking. You have the right people, in the right place, at the right time. Modern WFM software automates these processes and reconciles schedules with skills, availability, and rules to improve service levels and cost control. Typical suites bundle analytics and self-service for managers and employees, boosting engagement and agility across stores and DCs.

Workforce Optimization (WFO) is a strategy and toolset that unifies scheduling, quality/performance management, training/coaching, and analytics to raise service quality while lowering operating costs. By aligning staffing to demand, monitoring outcomes, and closing skill gaps, WFO improves both employee effectiveness and customer experience across frontline operations (stores, contact centers, and fulfillment).

Workforce scheduling transforms demand forecasts and constraints (skills, labor laws, availability, preferences) into fair, compliant rosters. Advanced systems use rules and optimization to place the right associates on the right tasks, and shifts, cut overtime, and idle time, and adapt quickly to demand changes. Integrated scheduling + time/attendance also streamlines payroll accuracy and labor compliance.

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.

PUDO & CheckOut integrations connect returns and lastmile partners (stores, lockers, counters) with order and inventory systems to simplify buy-online-return-in-store (BORIS), dropoff, exchanges, and refunds. They orchestrate label creation, eligibility rules, fraud checks, disposition (return to shelf, DC, vendor), and refund triggers while updating ATP to resell quickly. For customers, it's fast and convenient; for retailers, it reduces reverse logistics cost and recovers inventory value sooner.

Returns Orchestration coordinates every step of the reverse-logistics journey across channels. A configurable rules engine validates eligibility, sets disposition (restock, refurbish, RTV, recycle), selects route (store, DC, vendor), and triggers refunds or exchanges. It generates labels/QRs, books carriers, updates ATP immediately to resell viable items, and flags fraud. Operational dashboards track SLAs, costs, and sustainability KPIs (e. g, miles avoided, landfill diversion). Net: faster refunds, lower reverse-logistics cost, and higher recovery value.

Advanced Scheduling builds fair, compliant store rosters that match demand by hour and department. It blends forecasts with constraints (skills, availability, labor laws, budgets), auto-generates optimal shifts, and re-optimizes intraday for call-outs or traffic spikes. Managers get what-if tools; associates get self-service swaps and preferences. Integrated time & attendance ensures payroll accuracy, while KPI views (service level, overtime, coverage gaps) keep labor aligned to sales and tasks.

DropOff Kiosk enables self service returns at stores, lockers, or partner locations. Shoppers scan a QR, print/attach a label (if needed), and deposit items in a designated bin. The kiosk validates policy, reason codes, and identity, then triggers instant or conditional refunds or exchanges. On the back end, it routes items to the right node, updates inventory reservations, and provides operations with volume, SLA, and exception reporting. Result: shorter queues, happier customers, and lower handling cost.

In-Store Returns Processing digitizes BORIS workflows end-to-end. Associates scan the order, verify eligibility, grade condition, and select disposition (return-to-shelf, quarantine, RTV, liquidation). The flow supports instant exchanges, partial returns, and fee rules; it posts refunds, restocks sellable items immediately, and captures photos/notes for disputes. Managers see compliance and recovery KPIs so they can coach and adjust processes, reducing queues while reclaiming more value from each return.

Pick Up Drop Off (PUDO) Processing orchestrates both customer pick-ups and returns at counters, lockers, or partner sites. It handles identity checks, appointment/slot management, multi-order batching, and real-time notifications. For drop-offs, it validates policies, prints labels/QRs, and books return routes; for pick-ups, it confirms payment and releases inventory. All events sync to OMS/WMS, so ATP, promise dates, and customer communications stay accurate.

Returns Initiation is where the customer (or agent) starts the process, web/app portal, chatbot, call center, or in-store. A policy engine checks windows, item types, and reasons; the system presents options (exchange, replacement, repair, refund) and methods (in-store, locker, mail-in), with dynamic fees where applicable. It creates RMAs/QRs and shipping labels, sets expectations (refund timing, restocking), and captures structured reason codes to feed upstream fixes in merchandising and quality.

Last-mile & Pickup Management coordinates BOPIS/curbside, ship-from-store, and same-day delivery. It selects the best node, slots pick windows, batches orders, and guides pick/pack/stage tasks on mobile. For pickup, it handles check-in and curbside handoff; for delivery, it rate-shops carriers, prints labels, shares ETAs, and provides proof-of-delivery. Managers track speed-to-ready, on-time pickup/delivery, and exceptions to keep promises while controlling cost.

Pick Up & Drop Off Processing provides a standardized, auditable counter/locker workflow for both directions. For pick-up, it validates identity, confirms payment/age-restricted rules, and completes handoff scans. For drop-off, it verifies return terms, prints labels/QRs, records condition notes, and routes items appropriately. The system posts real-time status to customer communications and inventory services, reducing queues, misplacements, and refund delays.

Returns Management orchestrates the full reverse-logistics flow across channels. It validates eligibility and policy, creates RMAs/QRs, labels, directs items to the right node (restock, refurbish/repair, RTV, recycle), and triggers refunds/exchanges. It also updates ATP quickly to resell salvageable items, captures reason codes for upstream fixes, and surfaces KPIs (cycle time, recovery value, fraud flags, sustainability metrics). The goal: faster refunds, lower handling and transport costs, and maximum value recovery without breaking customer trust.

A Logistics Control Tower is the command center for transportation and DC execution. It fuses real-time shipment, carrier, yard, and warehouse signals into one view, detects risks (delay, capacity, dwell), and recommends mitigations (reslot, reroute, retender). Playbooks coordinate teams and partners, while predictive ETAs and exception alerts keep promises on time. Scenario planning helps balance service, cost, and sustainability (e. g., mode swaps, consolidation). Net: fewer surprises, faster recovery, and better OTIF.

A Planning Control Tower connects demand, supply, inventory, and financial plans on a single data backbone. It continuously monitors plan vs. actuals, highlights KPI drift (service, margin, inventory), and guides rapid plan-monitor-respond loops. Planners can run what-ifs (price, promo, lead time, capacity), evaluate trade-offs, and align decisions across S&OP/S&OE, and IBP. By closing the loop between sensing and re-planning, it cuts fire drills and drives measurable, cross-functional outcomes.

This flavor of consensus planning handles intermittent, service-critical demand. It blends statistical baselines with service-level targets, seasonality, supersessions, and part substitution, bringing sales, ops, and finance together to agree on one number. Cluster pooling stabilizes sparse signals; policy levers set safety stock and reorder rules by criticality. The process reduces stockouts for long-tail parts, trims dead stock, and improves fill-rates without inflating working capital.

Automotive suppliers face OEM call-offs, program ramps/phase-outs, and strict service penalties. This template supports line-side stability by reconciling OEM schedules, EDI demand, and historical patterns into a single, consensus plan. It models tooling/capacity constraints, engineering changes, and supersession chains, and exposes scenario impacts to finance. The result is steadier schedules, fewer expedites, and tighter alignment with customer scorecards.

Consumer categories are promotion-and season-sensitive with short life cycles. This approach ingests POS/loyalty, price/promo calendars, media, and weather/events to build baselines and promotional uplifts, including cannibalization and halo effects. Planners align on one forecast, tune size/color/channel mixes, and track bias/accuracy. Outcome: better on-shelf availability during peaks, fewer markdowns, and a forecast everyone trusts from merchant to finance.

High tech faces rapid obsolescence, multi-tier channels, and volatile NPI ramps. This configuration models lifecycle curves, channel inventory (sell-in/sell-through), and configuration/options demand, then reconciles sales/marketing/finance inputs into one plan. It supports quick re-plans for constraint shifts or design changes and exposes risk to supply and S&OP. Benefits: fewer shortages on hot SKUs, lower E&O on fading ones, and tighter revenue predictability.

Blue Yonder Demand is the core demand-planning solution: ML-enhanced forecasting, demand sensing, causals, segmentation, and consensus workflows on a common data model. It supports new-item prediction, promo uplift, intermittent items, and probability distributions (not just a single number), with bias/accuracy governance, and what-if scenario planning. Connected to supply, inventory, and financial planning, it shortens the signal-to-action loop and improves service, margin, and cash.

Demand 360 unifies every meaningful signal: POS/loyalty, e-commerce, wholesale orders, price/promo, events, and external factors into an always-current view of demand. It pairs ML forecasting with explainable drivers and scenario planning so planners can see why demand is shifting, and how decisions (price, promo, mix) will impact sales, margin, and inventory. With probabilistic forecasts and bias/accuracy governance, teams align on one plan, react faster to volatility, and feed execution systems (allocation, replenishment, labor) with confidence.

Demand & Supply Planning connects forecasting with constrained supply planning on one model. It translates consensus demand into feasible supply plans that respect capacities, lead times, MOQ/case-pack rules, and network constraints, and continuously reconciles plan vs. actual as signals change. Planners run what-ifs (vendor delay, capacity shift, promo uplift) to evaluate trade-offs among service, cost, and cash. The outcome is higher availability, fewer expedites, and tighter working-capital control across plants, DCs, and stores.

Demand Capacity Management closes the gap between what customers want and what we can make/move. It monitors demand vs. finite capacities by line, supplier, and lane; flags overloads early; and suggests smoothing prebuilds, alternate lines, supplier shifts, or lead-time changes. Planners test scenarios (e. g, pull-ahead production, changeover strategy, or mix swaps) and publish the chosen plan for execution. The result is steadier schedules, fewer last-minute expedites, and service protection without runaway cost.

Demand Edge for Retail delivers low-latency, store-and channel-level demand sensing at scale. It ingests fast signals (POS, web traffic, basket shifts, local events), updates short-term forecasts frequently, and exposes explainable drivers so that merchants and replenishment can act immediately. By pushing fresh demand to allocation and store fulfillment, retailers cut stockouts during peaks, protect fresh/grocery waste targets, and adapt staffing and space more dynamically without waiting for weekly batch cycles.

Change Management Service ensures Demand Edge sticks. It guides rollout and governance (pilots, A/B tests, KPIs), tunes configurations by format/cluster, and trains planners and operators on new workflows. The service monitors bias/accuracy, explains driver shifts, and codifies playbooks (e. g., promo exceptions, event spikes). By pairing technology with adoption, retailers realize the promised gains of faster decisions, higher on-shelf availability, and lower waste across every region and banner.

Deployment Planning decides how much to push from plants to upstream DCs and downstream nodes to meet service and freshness goals at the lowest cost. For consumer goods, it accounts for promotions, seasonality, shelf-life, truck/carton economics, and DC/store capacity. Planners simulate allocations, prebuilds, and transfer strategies, then release feasible moves to transportation and warehousing. Benefits: higher on-shelf availability during peaks with fewer costly redistributions and markdowns.

High tech networks span multi-tier channels and short product lifecycles. Deployment Planning balances limited components and finished goods across regions and partners, modeling NPI ramps, step-downs, and E&O risk. It considers channel inventory (sell-in vs. sell-through), postponement options, and allocation fairness to protect launches while minimizing obsolescence. The result: better service on hot SKUs, faster channel turns, and less write-off as products transition.

For service-critical parts with intermittent demand, Distribution Planning sets stocking targets and deployment rules by node, balancing response time and working capital. It models supersessions/substitutes, vendor lead-time variability, and technician or route-truck needs. The system pools sparse signals across clusters, suggests rationalization where appropriate, and plans redeployments to avoid dead stock. Outcome: higher part fill rates, fewer emergency orders, and healthier inventory across branches and vans.

Dynamic Demand Response senses short-term demand shifts (POS, web, events, weather, promo changes) and rapidly adjusts near-term forecasts and plans. It pushes updated signals to allocation, replenishment, and labor so you react in hours, not weeks, protecting service while minimizing waste. Planners get explainable drivers and scenario levers (price, promo, mix) to choose the best response, then publish with auditability.

Enterprise Supply Planning turns the consensus demand plan into a feasible, cost-aware supply plan across plants, suppliers, DCs, and stores. It respects capacities, lead times, MOQs, changeovers, and shelf-life; simulates alternatives (prebuilds, supplier shifts, postponement); and continuously reconciles plan vs. actuals. The result is higher availability with fewer expedites and tighter working-capital control.

The deployment capability decides optimal flows from plants to upstream/downstream nodes to meet service and freshness targets at least cost. It plans push/pull moves by accounting for promotions, truck/carton economics, DC/store constraints, and shelf-life. Planners can scenario test prebuilds, transfers, and node priorities, then release executable moves to TMS/WMS.

The manufacturing capability converts demand into constrained production plans. It balances lines, changeovers, and materials availability; optimizes lot sizing and sequencing; and protects critical orders with rules/penalties. Planners simulate alternatives (lines, calendars, suppliers) to stabilize schedules and cut expediting. Plans publish to detailed scheduling and shop-floor execution.

Flow-Through Deployment plans cross-dock/flow-through strategies so goods bypass storage and move straight from inbound to outbound. It aligns supplier arrivals, DC capacities, and store slots, minimizing dwell and touches while meeting delivery windows. Ideal for fast-turn items, and fresh, it reduces handling cost, shortens lead time, and improves freshness/service.

Flowcasting propagates a single, store-level forecast upstream through the network so every node (store, DC plant/supplier) is synchronized to true demand. By anchoring on store need and time-phasing inventory, and orders back through the chain, it improves on-shelf availability, reduces bullwhip, and lowers inventory while protecting service.

IBP connects demand, supply, inventory, and financial plans on one cadence and data model. It monitors plan-vs-actuals, exposes KPI drift (service, margin, cash), and enables scenario trade-offs (price, promo, capacity, lead time) for executive decisions. The closed-loop process aligns functions around one set of numbers and accelerates response to risk and opportunity.

Manufacturing ABPP provides advanced planning for batch/process manufacturers to translate demand into material and capacity feasible production plans. It considers recipes/BOMs, yields, changeovers, and campaign rules; optimizes lot sizes and sequences; and synchronizes upstream materials with finite resources. Scenario tools help choose the best plan, then publish it for execution for reliable service at lower cost.

Manufacturing Planning for Consumer Industries converts volatile, promotion-driven demand into feasible production plans. It models recipes/BOMs, yields, allergens, shelf life, and changeovers, then optimizes lot sizes and sequencing to hit service and freshness targets at minimum cost. Planners can simulate promo spikes, supplier delays, or capacity moves (extra shifts, alternate lines) and choose the plan that protects OTIF while reducing waste. Plans flow to detailed scheduling and execution, keeping plants, DCs, and retailers synchronized.

For high tech, the planner must balance NPI ramps, short lifecycles, and tight component supply. This capability reconciles channel demand with constrained materials (long-lead chips), models multi-level BOMs and options, and weighs postponement, or alternate component strategies. Scenario planning exposes service/E&O trade-offs during launches and step-downs, helping planners protect hot SKUs while minimizing write-offs. The result: steadier build plans, fewer expedites, and better revenue predictability.

Network Asset Management plans and governs the constrained assets that determine supply performance across your network: production capacity, storage, lanes, tooling, and returnable containers. It provides visibility to current/future availability, reserves capacity against the plan, and highlights conflicts (overloads, dwell, imbalance). Planners can simulate re-allocation (alternate plants, lanes, or tooling) to meet service at the lowest cost, then publish the chosen flows to deployment, transportation, and warehouse execution.

Sales Planning aligns revenue targets with demand, supply, and finance on a shared cadence. Sales sets goals by customer/channel/region; planners reconcile the top-down plan with bottom-up demand and supply constraints; finance closes the loop with margin and cash impacts. What-if analyses (price, promo, mix) make trade-offs explicit before committing. The output: one plan the enterprise trusts, with accountable targets, and clear execution hand-offs.

Statistical Forecasting for Manufacturing produces robust baselines for parts and finished goods using proven methods (e. g., exponential smoothing, ARIMA, Croston-style for intermittent demand). It segments items by behavior (stable, seasonal, lumpy), auto-selects the best model, and rolls forecasts through multi-level BOMs to support MPS/MRP. Accuracy/bias governance and scenario tools help planners adjust for engineering changes, supplier risk, or program ramps, so production and procurement start from a credible signal.

This capability turns OEM schedules/call-offs and distributor demand into feasible supply plans that respect materials, capacity, tooling, and transportation constraints. It manages supersessions and engineering changes, supports JIT/JIS, and sequenced deliveries, and highlights risks early (line overloads, component shortages). Scenario planning weighs options, alternate lines, inventory buffers, and supplier shifts to protect service while cutting expedites and premium freight.

Demand Planning creates a trustworthy forecast and consensus plan across sales, marketing, supply, and finance. It blends statistical/ML techniques with causal drivers (price, promo, events) and handles edge cases like new items and intermittent parts. Governance tracks accuracy and bias; scenario planning shows the impact of decisions before you commit. A stronger signal to supply, inventory, and deployment means fewer stockouts, fewer markdowns, and better cash performance.

Integrated Business Planning (IBP) synchronizes demand, supply, inventory, and financial plans on a common data model and cadence. It continuously monitors plan-vs-actuals, flags KPI drift, and enables executive trade-offs across service, cost, and cash using structured scenarios. By aligning functions to one set of numbers and closing the loop back to execution, IBP reduces firefighting and drives measurable, cross-functional outcomes.

S&OP is the monthly, cross-functional cadence that aligns demand, supply, inventory, and finance to one plan. Teams review a rolling horizon, reconcile gaps to targets, run scenarios (price, promo, mix, capacity, lead time), and escalate trade-offs for executive sign-off. A strong S&OP process links strategic goals to operational constraints, reduces last-minute expedites, and improves service, margin, and cash then hands an agreed plan to execution with clear owners and KPIs.

Asset Management governs the constrained assets that determine supply performance: production lines, storage, lanes, tooling, and returnable containers. It provides visibility to current/future capacity, reserves it against the plan, and flags conflicts (overloads, dwell, imbalance). Planners can simulate alternatives (alternate plants, carriers, lanes, or tooling) to meet service at the lowest cost, then publish the chosen flows to deployment, transportation, and warehouse execution.

Supply Chain Execution turns plans into movement: pick/pack/ship in DCs, transportation tendering, labeling, track-and-trace, and proof-of-delivery. It orchestrates orders across modes, and carriers, rate-shops, creates compliant documents, and manages exceptions in real-time. Tight feedback loops (status, ETA, events) keep ATP/promises accurate, and surface issues early so teams can re-slot, re-route, or re-tender before service slips.

Planning converts strategy into executable demand, supply, inventory, and deployment plans on a shared data model. Forecasts become feasible supply plans that respect capacities, lead times, MOQ/case-pack rules, and freshness; inventory policies set service targets and safety stock; deployment defines flows through the network. Connected planning shortens the sense-plan-act loop and delivers higher availability with lower working capital.

It's the governed foundation cloud, integration, security, and AI services that all planning apps share. A unified model (products, locations, calendars), high-throughput pipelines, event streaming, and open APIs keep data trusted and current. Built-in governance (lineage, quality, access control) plus ML/optimization services let you add new use cases without rebuilding plumbing, planners focus on decisions, not data wrangling.

Orchestration coordinates the flow of plans and signals across demand, supply, inventory, deployment, and financial planning. It ensures one set of numbers, triggers re-planning when events occur (demand spikes, delays), and manages exceptions with clear ownership and SLAs. Scenario services quantify service-cost-cash trade-offs so leaders choose deliberately, and execution systems get timely, feasible instructions.

Command Center is a real-time detect-decide-act layer that unifies visibility, risk detection, and guided actions across planning and execution. It fuses signals (demand, inventory, shipments, capacity), flags threats to KPIs, recommends mitigations, and can trigger workflows to resolve issues. Playbooks standardize responses, while dashboards track outcomes, so teams move from firefighting to proactive, measurable control.

Single-Tier Planning Orchestration applies the same governance and event-driven updates when you're optimizing within one echelon (e. g., a plant network or a retail DC network). It synchronizes demand signals, capacity, and material constraints, and deployment rules inside that tier, auto-triggering re-plans as conditions change. The result: faster decisions, fewer expedites, and consistent execution without adding multi-echelon complexity.

It's the capability to calculate and monitor greenhouse-gas emissions across your supply chain, typically at shipment, lane, mode, and facility levels. Activity data (miles, mode, fuel, weights) is mapped to emission factors to produce COe, with support for Scope 1/2/3 roll-ups, well-to-wheel vs. tank-to-wheel, and carrier-or fuel-specific factors. Dashboards surface hot spots; APIs feed planning so you can optimize mode, routing, and cost, not just cost. Compliance (e. g., audit trails, assumptions) and target tracking enable credible reporting and measurable reduction programs.

Sustainable logistics applies emissions and circularity lenses to everyday transportation and warehousing decisions. Tactically, you maximize cube and backhauls, favor lower-carbon modes (rail/intermodal), avoid empty miles, and design cross-dock/flow-through to cut dwell and energy. Strategically, you reshape the network (node placement, service zones), pilot alt-fuel/EV where it pencils, and optimize packaging to reduce mass and damage. The point isn't green at any cost, but quantified trade-offs, service, cost, and carbon, so the network gets cleaner and more resilient year over year.

A TMS plans, optimizes, executes, and settles freight. Planners build loads and routes (single/multi-stop, parcel/LTL/TL/intermodal), rate against contracts, spot, tender to carriers, and track shipments with live ETAs and exceptions. Appointment scheduling, dock/yield constraints, and driver-hour rules keep plans feasible. Freight audit & pay closes the loop. Strong TMS platforms add scenario modeling and analytics so you can continuously improve cost, service (OTIF), and sustainability on one control surface.

3-D Load Planning packs cartons/pallets into containers or trailers to maximize space utilization, while respecting reality: dimensions, weight, stackability, orientation, crush limits, axle balance, and stop-sequence (so the first stop is accessible). It supports mixed-SKU and mixed-pack patterns, vendor pack rules, and hazardous/temperature constraints. The outcome is fewer containers, fewer miles, and less product damage, plus plans that can be executed as-is on the dock.

It's the what-if and network-design workbench for transportation. Import historical moves and master data, then simulate alternate carriers, modes, consolidation rules, service levels, and node changes to quantify cost/service/carbon trade-offs before you roll them out. Use it for RFP prep, budget planning, contingency scenarios (port closures, fuel shocks), and continuous improvement (e. g., LTL multi-stop TL conversion). Insights flow back to the live TMS policies.

A collaboration layer that connects shippers, brokers, and carriers on shared workflows, capacity sharing, tender/accept, appointment scheduling, status/ETA events, documents, and scorecards in one network. API/EDI connectivity speeds onboarding; standardized milestones reduce noise; performance analytics drive fair carrier development. Result: faster acceptances, better coverage during peaks, and fewer exceptions without living in email threads.

Dynamic Price Discovery taps live carrier/market rates to complement contract tariffs, so you can compare real-time spot vs. contracted options and auto-select the best service-cost-carbon combination. It accounts for accessorials, transit promises, and capacity signals; can re-price when plans change; and writes the final buy rate to execution and settlement. Shippers cut tender rejects and expedite spend while keeping promised delivery windows.

Load Building creates feasible, cost-efficient loads across orders and stops. It consolidates LTL into multi-stop TL, enforces weight/volume/axle, and calendar constraints, and honors pickup/delivery windows, dwell, and driver hours. Rules can prioritize service (fewer touches, earlier windows) or cost (higher cube, mode shift). Plans are published for tendering and appointment scheduling, and the dock sees exactly what to stage and when.

A carbon-accounting workbench for transportation. It converts shipment activity (distance, mode, weight/volume, fuel type) into COe using recognized emission factors, then rolls results up by lane, mode, carrier, customer, and time period. Planners can compare route/mode options on cost and carbon, track progress against targets, and export audit-ready reports. With APIs feeding planning and execution, you can favor lower-carbon routings (e. g., rail/intermodal), right-size containers, and cut empty miles without flying blind on the trade-offs.

Transportation procurement is built into your TMS stack. Run RFPs and mini-bids, benchmark lanes, model award scenarios (single vs. multi-award, incumbents, caps), and push the final carrier matrix straight into planning and tendering. Lane health and compliance dashboards track acceptance, service, and cost drift; auto-reprice and spot options cover capacity gaps. Result: stronger coverage in peaks, fewer rejects/expedites, and a defensible audit trail from bid to execution.

A shared, network-wide appointment layer that coordinates pick-up/delivery times across shippers, carriers, and facilities. It exposes dock capacity, calendars, and rules; validates constraints (equipment, driver hours, yard dwell); and books/modifies slots automatically when plans change. Facilities smooth inbound/outbound waves, carriers cut detention, and planners see the ripple effects on loads and ETAs, so the yard, dock, and road stay in sync.

Multi-objective load/route optimization across modes and partners. It consolidates orders into feasible loads, sequences multi-stop tours, evaluates mode shifts, and assigns carriers while honoring windows, capacity, axle/weight, driver-hour, and service constraints. You can prioritize cost, OTIF, or carbon, and run what-ifs before releasing to tendering. Plans are published to appointments and execution so the dock knows exactly what to stage and when.

real-time shipment visibility from tender to proof-of-delivery. It normalizes carrier/telematics events, predicts ETA slippage, and triggers exception workflows (re-slot, re-route, re-tender) before service misses occur. Live status flows to customers and to planning (updating promises and ATP), while scorecards track dwell, on-time, damage, and claims. Where's my truck? calls; more proactive, measurable control.

ProfiTour is a route and tour planning for distribution fleets. It builds efficient daily tours with time windows and capacity constraints, sequences stops to minimize miles and service risk, and respects driver regulations and customer SLAs. Dispatch gets executable tours and turn-by-turn stop lists; operations can model territory changes, depot switches, or delivery calendars to raise service, and cut especially in dense, multi-stop networks.

A real-time, cloud-native layer that keeps plans and execution aligned. RTC ingests live events (status, traffic, weather, asset signals), re-optimizes loads/routes when conditions shift, and syncs changes to appointments, carriers, and customers. It centralizes detect-decide-act for transportation, so teams move from reactive firefighting to guided, measurable responses.

Transportation Analytics turns shipment, cost, carrier, appointment, and yard data into find-and-fix insights. Role-based dashboards expose lane hot spots, consolidation opportunities, acceptance gaps, and dwell drivers; modeling quantifies savings before rollout and verifies them after. Insights flow back into planning policies (mode shift, tender order, cube rules) so the network improves every cycle.

Transportation Manager is the core TMS control surface for planning, executing, and settling freight. Planners rate against contracts/spot, build multi-stop loads, and routes across parcel/LTL/TL/intermodal, tender to carriers, manage appointments, and track live ETAs/exceptions. Freight audit & pay closes the loop so accruals, invoices, and disputes reconcile off the same shipment truth. Embedded analytics and policies (mode shift, consolidation, service tiers) let you improve cost, OTIF, and sustainability continuously without bouncing between tools.

Transportation Mobile User puts driver and dock tasks on a phone/tablet: accept tenders, view stop-by-stop instructions, capture POD/photos, scan barcodes, and post real-time status/exception codes. GPS events feed ETAs and geofenced arrivals; document capture reduces disputes and accelerates settlement. For shippers and carriers, it shrinks " Where's my truck? noise, increases milestone compliance, and improves dock turns because everyone is working from the same live plan.

Transportation Modeler is your what-if and network design workbench. Import historical shipments and master data, then simulate alternate carriers, modes, consolidation rules, service levels, and node changes to quantify cost/service/carbon tradeoffs before rollout. Use it for RFP strategy, budget planning, contingency scenarios (port closures, fuel spikes), and continuous improvement (e. g., LTL-to-multi-stop-TL conversions). Validated policies flow back into live planning so savings are realized as modeled.

Transportation Modeling generalizes scenario capabilities across lanes and networks: test mode shifts, award strategies, delivery calendars, appointment rules, and cube policies; compare baseline vs. proposed on cost, OTIF, and COe; and publish chosen policies to production. It's the safe sandbox for changes you derisk decisions and verify ROI before they hit operations.

Transportation Optimization builds feasible, efficient loads and routes that respect real-world constraints: time windows, driver HOS, axle/weight, equipment, dwell, and customer SLAs. It consolidates orders, sequences multi-stop tours, evaluates mode changes, and balances objectives (cost, service, carbon). Results are published to tendering and appointment scheduling so the dock knows exactly what to stage and when reducing miles, touch points, and late deliveries.

Transportation Planner is the day-to-day cockpit for planners and dispatch. It surfaces suggested loads/tours, highlights exceptions, and capacity gaps, supports manual edits/locks, and releases plans to carriers with full visibility to downstream appointments and yard. Embedded KPIs (acceptance, OTIF risk, cube, cost/unit) guide prioritization; one-click what-ifs help resolve issues without leaving the screen.

This capability ties planning to time-bound reality, coordinating routes/loads with dock calendars, yard constraints, and carrier availability. It auto-books, or proposes appointment slots, rebalances waves to avoid congestion, and reschedules when upstream delays occur so service is protected with minimal expedites. The net: smoother yards, lower detention, and plans that actually execute.

Container Load Optimization (3-D load building) packs cartons/pallets into containers or trailers to maximize cube while respecting weight, stackability, orientation, crush limits, axle balance, and stop sequence. It generates pack diagrams that your dock can execute, lowering damage and touches. Fewer containers, fewer miles, and better on-time performance without trial-and-error on the floor.

DC Outbound Smoothing evens out the peaks and valleys on your dock by sequencing orders, waves, and carrier appointments so work is balanced by hour and door. It staggers pick/pack/replenishment, aligns yard moves, and trailer availability, and releases freight in a flow that fits labor and equipment limits. The payoff: shorter dwell, fewer congestion-driven delays, better carrier turns, and plans that actually execute under real constraints.

Freight Procurement manages full-cycle sourcing RFPs, mini-bids, and awards for contracted transportation. You benchmark lanes, model award scenarios (single vs. multi-award, incumbents, caps), and push the final matrix directly into planning. Compliance dashboards track acceptance, on-time, and cost drift; spot and reprice options close capacity gaps. Outcome: resilient coverage in peaks, fewer tender rejects, and provable savings from bid through execution.

Load Building consolidates orders into feasible, efficient loads. It honors cube/weight/axle limits, time windows, dwell, and equipment types while choosing multi-stop tours where it makes sense. Rules can optimize for cost (max cube, consolidate LTL to TL) or service (early deliveries, fewer touches). Loads are published to tendering and appointments, so the dock knows exactly what to stage and when.

Appointment Scheduling coordinates pick-up and delivery times among shippers, carriers and facilities. It exposes dock calendars, constraints, books, or rebooks slots automatically as plans change, and smooths inbound/outbound waves to reduce detention. Because its tied to planning and execution, changes propagate to ETAs, yard, and labor keeping doors, drivers, and freight in sync.

Route Optimization builds cost-and service-aware tours for multi-stop distribution. It sequences stops, assigns equipment, and respects time windows, driver HOS, capacity, and customer SLAs. You can balance multiple objectives (miles, OTIF, COe), test what-ifs (territory changes, depot moves), and republish new routes when conditions shift all from one planning surface.

Specialized TMS workflows handle freight with extra temperature-controlled, hazardous, oversized/overweight, or high-value. They add permit/escort logic, segregation, and cleaning rules, temp/condition monitoring, geofenced chains-of-custody, and stricter appointment controls. Planners choose compliant modes and equipment automatically, carriers get precise instructions, and audit trails prove that safety and regulatory requirements were met.

Transportation Analytics turns shipment, cost, carrier, appointment, and yard data into find-and-fix insights. Role-based dashboards expose lane hot spots, consolidation opportunities, acceptance gaps, and dwell drivers; modeling quantifies savings before rollout and verifies them after. Insights flow back into planning policies (mode shift, tender order, cube rules) so the network improves every cycle.

Transportation Optimization generates feasible load/route plans that minimize cost and risk while meeting service targets. It consolidates orders, evaluates mode shifts, sequences multi-stop tours, and enforces windows, driver hours, axle/weight, and equipment rules. Plans are published to tendering and appointment scheduling, reducing miles, touches, and late deliveries, giving operations executable instructions.

Transportation Planning turns orders into feasible, cost-effective load and route plans. Planners (or automation) select modes, and carriers, consolidate orders, build multi-stop tours, and respect windows, driver HOS, axle/weight, equipment, and service SLAs. Tight ties to appointment scheduling smooth dock waves; visibility and exception workflows keep ETAs and promises accurate. Scenario tools let you test consolidation and mode shifts before releasing to tendering, so operations execute the plan, not fight it.

This combines plan creation with algorithmic route/tour optimization. The system sequences stop, assign equipment, choose mode/carrier, and balance objectives (cost, OTIF, COe) while enforcing real-world constraints (windows, HOS, weight/volume, dwell). It re-optimizes when orders change, or delays hit, then republishes to appointments, and execution so the dock, and drivers stay in sync. Result: fewer miles, and touches, higher on-time performance, and resilient plans that adapt in-day.

Transportation Visibility gives a single, real-time view from tender to proof-of-delivery. It normalizes carrier/telematics events, predicts ETA slippage, and triggers guided actions (re-slot, re-route, re-tender) before service misses occur. Status flows to customers and back to planning/OMS to keep promises and ATP accurate. Scorecards track dwell, on-time, damage, and claims so you can improve lanes, carriers, and policies continuously.

Vehicle routing & scheduling (VRS) builds daily tours that meet time windows and capacity while minimizing cost and miles. It assigns orders to vehicles, sequences stops, and respects constraints like driver hours, service durations, equipment, and customer SLAs. Advanced VRS supports multi-depot, pickup/returns, and what-ifs (territory/depot changes), with re-optimization when exceptions occur. Net: tighter OTIF, fewer miles, and a plan the field can actually run.

Robotics Hub is a vendor-agnostic layer that connects multiple robot types to your WMS via standard APIs/events. The WMS publishes work (picks, replenishments, moves); Robotics Hub assigns tasks to the best robot fleet, monitors status in real-time, and handles exceptions and fallbacks. Because it centralizes onboarding and orchestration, you can mix vendors/technologies without custom point-to-point integrations, scaling automation faster with one control surface.

A WMS runs the DC: receiving, putaway, slotting, cycle counting, replenishment, picking, packing, shipping, and returns while enforcing lot/serial, temperature, and compliance rules. It orchestrates tasks across people, equipment, and zones, integrates with automation/robots, and provides inventory accuracy and traceability. With dashboards and alerts, managers balance waves/waveless flows, reduce dwell, touches, and improve throughput, service, and especially during peaks.

Dispatcher WMS is Blue Yonder's proven warehouse management system (the descendant of RedPrairie), built for complex, high-volume DCs. It provides rules-driven tasking across inbound, storage, replenishment, and outbound, supports RF/mobile workflows, and coordinates with labor and automation to maximize throughput and accuracy. Facilities use it to enforce compliance (lot/serial, temperature, QA), lower touches, and shrink, and deliver consistent service across multi-site networks.

Blue Yonder's VRS plans end-to-end distribution tours that hit customer windows at minimum cost. It consolidates orders, sequences stops, respects driver and equipment constraints, and can optimize for different objectives (miles, OTIF, COe). Intraday re-optimization adapts to changes (late picks, traffic, cancellations) and republishes to appointments and drivers. The outcome: predictable service, fewer miles and touches, and tours your network can actually execute.

Blue Yonder Warehouse Management runs end-to-end DC operations: receiving, putaway/slotting, cycle counting, replenishment, picking (wave, waveless, batch, zone), packing, shipping, and returns, while enforcing serial/lot, FEFO/FIFO, temperature, and compliance rules. It orchestrates labor and automation side-by-side, supports value added services (kitting, ticketing, labeling), and provides real-time inventory accuracy and traceability. role-based dashboards surface bottlenecks and KPIs (throughput, dwell, accuracy, UPH) so managers can rebalance work on the fly. Tight integration to robotics, transportation, and store/OMS keeps promises accurate during peaks without sacrificing control.

Warehouse automation uses machines, robotics, and software to move, store, pick, and pack goods with minimal manual touches. Examples include AMRs/AGVs, goods-to-person systems, AS/RS, conveyor/sortation, automated packing, and vision/voice-directed picking. The WMS provides the brain: it decides tasks and inventory, then dispatches work to people and robots via standard APIs, monitors progress, and handles exceptions. Benefits include higher throughput and accuracy, safer operations, fewer touches/miles, and better space utilization. The key is to start with data-driven bottlenecks and a scalable integration layer so you can mix vendors and expand over time.