Demand Planning Software

ℹ️ Gartner Publishes Market Guide for Analytics and Decision-Making Platforms for Supply Chain The analytics and decision-making platform (ADM) market is evolving, but it remains highly fragmented. Supply chain technology leaders should use this guide to navigate the market environment and inform a cohesive technology roadmap for adopting supply-chain-specific ADM platform capabilities. OUR KEY FINDINGS 🔵 Line of business teams are looking to speed up cross-functional decision making with near-real-time insights and unstructured content to quickly react to and prevent disruptions, allowing them to enhance the quality of decisions. 🔵 Leaders now recognize that supply-chain-focused analytics and decision-making (ADM) platforms are enablers of flexibility and quicker time to value when dealing with a deluge of data. 🔵 ADM platforms for supply chain management (SCM) help leaders achieve connected, contextual, continuous and compliant decisions. Leveraging composite AI — the combined application (or fusion) of different #AITechniques — within a platform improves the platform’s learning efficiency and broadens its level of knowledge representations and AI abstraction mechanisms and provides a platform to solve a wider range of supply chain problems effectively. 🔵 Vying for a bigger share of the #SupplyChain ADM platforms market, vendors are repositioning their solutions to provide a broader range of capabilities. This has resulted in all-encompassing platforms with preconfigured use case templates and blueprints, as well as a development environment that supports analytics and #AI techniques specialized for supply chain functions. OUR RECOMMENDATIONS 🔵 Create a roadmap for adopting ADM platforms for SCM by using Gartner’s Technology Adoption Roadmap for #Data and #Analytics. 🔵 Optimize solution effectiveness and implementation efficiency, and maximize business value, by carefully choosing a buy, build or partner model for #DecisionSupport, #DecisionAugmentation, and eventually, responsible and safe #DecisionAutomation. 🔵 Build trust in autogenerated recommendations from ADM platforms by ensuring #explainability of their insights and investing in data quality. Establish realistic expectations about limitations (such as #hallucinations) and embrace the needs of multiple user personas by fostering user #collaboration, #composability or automated #insights. 🔵 Mitigate the risks of functional duplication by defining, communicating and enforcing strict governance policies. Select and align success #metrics and #KPIs across #decisions. Gartner clients subscribed to our Supply Chain Technology Strategy and Selection practices can login and read: "Market Guide for Analytics and Decision-Making Platforms for Supply Chain" [Published 14 January 2025 | G00798281] led by Christian Titze, Leonard Ammerer and myself (David Pidsley): https://lnkd.in/eW8dbTBt 🥳 Congratulations to the representative vendors featured

Congratulations, You’re the new Chief Supply Chain Officer — here’s how to choose the right technology partner. Now the real fun starts. You need to choose your supply chain technology partner, and the market is overflowing with options. Recently Supply Chain Digital published a solid overview of the main players. They listed solutions like Kinaxis, Blue Yonder, SAP SCM, Oracle, o9 Solutions, Inc., e2open, RELEX Solutions, OMP, Logility, Anaplan and project44. https://lnkd.in/dyYeDP24 All of them look impressive, but the trick is simple: the best tool is the one that fits your business reality, not the one with the loudest marketing. If I were choosing today, I would start with a very practical approach. Step 1: Understand your industry logic. If you are in pharma, for example, it makes sense to look closer at Kinaxis because companies like Sanofi and Merck already use it. If you are a retailer with strong fresh or perishable operations, RELEX might be more relevant. If you are deep into SAP, you will naturally lean toward SAP SCM. Step 2: Be honest about your digital maturity. If your teams still plan in Excel, you need a platform that can lift you step by step, not overwhelm you. Step 3: Look at real use cases. Who uses the tool today, what results they get, and whether these results actually look like something you need. Step 4: Check integration. A strong partner must connect with your ERP, your planning process and your data reality. If this does not work smoothly, nothing else matters. Step 5: Test scenarios. A good platform must help you see risks before they hit you. Scenario modeling is not a luxury anymore, it is survival. Step 6 (Very important!!!): Look at people. You are not buying software. You are choosing a partner who will stay with you through your transformation. Choosing the right solution is not about chasing the most advanced AI. It is about choosing what will solve your problems with the least amount of noise. If you are stepping into this role now, this is one of the first decisions that will define your next two to three years. Make it a thoughtful one.

I've been working with supply chain planning for 17 years and since 2021 with OMP and Kinaxis. Here's what changed in the Gartner Magic Quadrant from 2021 to 2025. THE CONSISTENT LEADERS: - Kinaxis – 11 consecutive years as Leader - OMP – 10 consecutive years, highest "Ability to Execute" - Blue Yonder, SAP, Oracle – maintained positions THE BREAKTHROUGH STORIES: - o9 Solutions – went from rising player to Leader, now $3.7B valuation with 37% YoY growth - RELEX – jumped from Niche Player (2022) to Leader (2025) in just 3 years WHO DISAPPEARED: e2open dropped from Leaders. Multiple smaller vendors (Adexa, GAINSystems, Quintiq, Syncron) no longer in the report. WHAT CHANGED TECHNOLOGY-WISE: 2021: Cloud migration, basic ML 2025: GenAI/Agentic AI mandatory, real-time planning, cloud-native architecture KEY TAKEAWAY: The gap between Leaders and the rest widened dramatically. The bar for "table stakes" went from cloud capability to AI-powered autonomous planning in just 4 years. If you're evaluating platforms now: → Safe bets: Kinaxis, OMP (proven over 10+ years) → Fast innovators: o9, RELEX (aggressive R&D) → Suite plays: SAP, Oracle (if ERP-centric) The market consolidated. Fewer viable options, but Leaders are stronger than ever. Thoughts? What's your experience with these platforms? ♻️ Repost to show someone how APS is progressing overtime. 🔔 Follow Sergey Masyagin for insights on Supply Chain Automation & AI. #SupplyChain #Kinaxis #SupplyChainPlanning #Gartner #APS #SCM

🔍 Forecasting in IBP vs Kinaxis vs OMP vs Relex vs Blue Yonder In today’s dynamic supply chains, accurate forecasting is essential for agility, efficiency, and resilience. Here’s how the top platforms stack up: Via 📊 SAP IBP • Uses time-series, AI/ML models via the Predictive Analytics Library (PAL) • Integrates forecasting into end-to-end S&OP, inventory, and demand planning • Real-time insights with SAP HANA for large volumes and collaborative planning ⚡ Kinaxis RapidResponse • Enables concurrent planning: forecast changes trigger real-time supply impact • Supports ML, causal forecasting, and demand sensing • Ideal for fast-moving, highly responsive supply chain environments 🏗️ OMP • Strong in multi-echelon and hierarchical forecasting • Forecasting is tightly integrated with finite capacity planning • Suited for complex manufacturing networks needing synchronized demand-supply logic 🛒 Relex Solutions • Designed for retail/FMCG, with store- and SKU-level forecasting • Uses AI/ML for promotions, weather, seasonality, and life-cycle forecasts • Automates replenishment and forecasting with strong daily granularity 🤖 Blue Yonder • Powered by Luminate AI/ML platform with probabilistic forecasting • Great for demand classification, demand sensing, and omni-channel retail • Strength lies in prescriptive recommendations and event-driven planning ✅ Quick Comparison: • IBP → Best for integrated enterprise planning (SAP users) • Kinaxis → Best for agility & real-time scenario planning • OMP → Best for manufacturing complexity and constraint-based planning • Relex → Best for retail-level granularity and automation • Blue Yonder → Best for AI-first, omni-channel retail and supply. 📌 Forecasting isn’t one-size-fits-all. Choosing the right platform depends on your industry, complexity, and decision velocity. Let’s connect if you’re evaluating tools or planning a digital supply chain transformation! #Forecasting #SupplyChainPlanning #SAPIBP #Kinaxis #OMP #Relex #BlueYonder #DemandPlanning #RetailTech #AIinSupplyChain #SOP #SupplyChainTransformation #Concurrengplanning 💬 👇🏻For queries on digital transformation using SAP IBP, Kinaxis, OMP, or Blue Yonder — feel free to reach out or drop a message. Let’s explore how the right tool can accelerate your supply chain journey. 🚀 Stefanini Group Stefanini North America and APAC Stefanini Brasil Stefanini EMEA Sandy Sankara Bala Upadhyayula Easwara Dhananjay Karanam Veerabhadra Rao Kakarapalli satish mallina Santosh Chavan Chaitanya Josyula

Legacy data foundations fragment and can stall when moving from human click-rates to autonomous execution. True Systems of Action demand zero operational drag. How do you scale data architectures when software agents suddenly start triggering millions of real-time transactions? Look at how Manhattan Associates modernized their supply chain platform using Cloud SQL and BigQuery: 🔹 Massive scalability: Processing over 1 billion daily API calls with average sub-150ms latency. 🔹 Operational efficiency: Dynamically absorbing hundreds of thousands of monthly auto-scaling events. 🔹 AI-driven innovation: Running specialized AI agents to coordinate real-time warehouse and retail operations. By reducing system latency and providing real-time AI insights, the platform removes the "operational drag" that can lead to frustration. For employees, this means having a reliable tool that accurately predicts inventory needs and optimizes labor schedules in seconds, allowing them to serve customers rather than managing data silos. Exceptional architectural engineering by the team at Manhattan Associates! 👉 Read the case study: https://bit.ly/4dOM7AO

SAP is advancing the art of supply-chain orchestration by combining its business-network platform with generative and agentic AI. Organizations are now able to extend visibility across multi-tier networks and, more importantly, act on those insights through automation and intelligence embedded in the workflow. At the core of this change: a new solution called SAP Supply Chain Orchestration (targeted for the first half of 2026), built on SAP Business Technology Platform and leveraging data from the SAP Business Data Cloud and the SAP Business Network. It uses AI to detect issues several tiers deep in a supply chain, proactively warn stakeholders, and trigger prioritized actions across procurement, manufacturing, logistics, and planning. For practitioners like us, the implication is that supply chains must orchestrate rather than simply observe. With networked data, intelligent agents, and action-ready workflows, the chain becomes a live, adaptive system instead of a series of handoffs. If you're working on supply-chain resilience, this is a moment worth paying attention to.

🔗 If you’re managing complex supply chains, you know the Data Gap. You have the data, but by the time a data scientist builds a dashboard to explain a disruption, the ship has already sailed (sometimes literally). Databricks has closed that gap with Agentic Analytics within AI/BI. Here are the two recently launched capabilities for supply chain leaders: 1/ Rapid Root-Cause Analysis (via Genie Research) ❓ Standard BI tells you what happened (e.g., "Shipping costs are up 15%"). ✨ AI Research agent: Instead of a single query, Genie Research creates a multi-step plan. It reasons through your data, executes multiple SQL queries, and iterates until it finds the smoking gun. 💡🔗 Supply Chain Value: Ask, "Why did our East Coast fulfillment lag last week?" and get a full report—complete with visualizations and citations—identifying the specific carrier delays and inventory shortages responsible. 2\ Accelerated Visibility (via Agentic Authoring) ❓ Waiting weeks for a new KPI dashboard is a thing of the past. ✨ Natural Language to Layout: You can now describe a dashboard in plain English. The agent searches your Unity Catalog for the right tables, creates the datasets, generates the charts, and organizes the layout. 💡🔗 Consistency at Scale: It builds reusable semantic definitions. This means "Lead Time" is calculated the same way across your entire organization, eliminating the tribal knowledge that often leads to conflicting reports.