Supply Chain Optimization Software

A fresh paper from #MIT & #Microsoft introduces the 4I framework that links #AI with #mathematical_optimization to make rigorous planning explainable, interactive, and responsive, with a real Microsoft cloud supply chain case. Without needing a PhD in math! GenAI is making complex math optimization easier for everyone. A new 4I framework shows how AI can explain supply chain plans, answer tough “what if” questions, and adapt to sudden changes. Tested in Microsoft’s cloud supply chain, it proved powerful. For professionals, this means clearer decisions, faster scenario testing, and smarter planning. 🔎 Insight: LLM agents unify siloed data into a picture of operations. Planners ask for state now in natural language. The system reports inventory, backlogs, anomalies, and freshness, building trust before optimizing. 🧩 Interpretability: Models are explained in plain language. The assistant surfaces binding constraints, trade offs, and assumptions, then answers why not questions with costs and feasibility reasons. Black box becomes glass box. 🗺️ Interactivity: Scenario analysis turns conversational. Users propose shocks and tweaks, the agent edits parameters and constraints, runs solvers or heuristics, compares outcomes, and highlights Pareto trade offs across cost and service. ♻️ Improvisation: Change is expected. Agents monitor events, detect drift, update constraints, re optimize, and log impacts for cost and service. Users approve changes with audit trails, keeping plans aligned with reality.

After 100+ conversations with VPs of Supply Chain, one thing is clear: data isn’t the bottleneck - action is. Today’s ERPs, TMS, and supplier portals wait to be fed clean data and struggle with exceptions. What executives really want is software for their supply chain execution that handles the messy reality, takes appropriate action before problems happen, and adapts to how teams already work today. These 3 quotes summarize common frustrations: 1. “Our suppliers keep missing promised dates and we only catch it when it’s too late.” 2. “Transit times are erratic. We’ve manually added a fixed 25 days to buffer our inbound.” 3. “$20K of materials are sitting idle because we’re waiting on two parts that now have to be flown in.” So I decided to build it. Introducing Glacis, An end-to-end supply chain execution platform that helps: → Increase OTIF → Lower cost → Reduced working capital Across order intake, procurement, logistics and fulfilment teams. It’s implemented in weeks (not quarters) and requires minimal IT support. The results are already real: - A $20B automotive supplier improved OTIF by 4% within weeks by streamlining inbound logistics. - An $8B CPG business lowered sourcing costs and improved supplier performance by proactively managing promised dates. We’ve been fortunate to be advised by industry veterans who’ve shaped some of the most complex supply chains in the world, to name a few: - Pietro D'Arpa - former VP Supply Chain at P&G - Andrew Downard - CSCO at Dart Container - José Enrique Medina, NACD.DC, MBA - VP Global Supply Chain at MKS Instruments Happy to connect, If this sounds relevant to your organization.

🔍 Model Configuration Comparison: IBP | Kinaxis | Blue Yonder | o9 | OMP When it comes to choosing the right supply chain planning tool, the real game is in how flexibly and efficiently you can configure the model to your business. Here’s a high-level comparison of modeling and configuration across 5 leading planning platforms: 🧱 Architecture & Modeling • IBP: Modular planning area + key figures + Planning operators , Versions • Kinaxis: Real-time single data model • Blue Yonder: Hierarchical control tower • o9: Graph-based “digital brain” • OMP: Config sets + solver-driven templates 📊 Master Data Setup • IBP: Master Data Types with reuse logic • Kinaxis: Flat SDB tables with Excel-like views • Blue Yonder: Table-based, optimized for retail • o9: Node-relationship models • OMP: Predefined entities with structured loads ⚙️ Planning Logic Configuration • IBP: Time series or, Order based Keyfigures , Planning levels , Aggregation/ Disaggregation, Planning operators & Planning views. • Kinaxis: Built-in sheets & logic blocks • Blue Yonder: ML + rules-based logic • o9: AI models + scenario scripting • OMP: Solver logic with deep optimization 📈 Scenario Planning & UI • IBP: Excel UI, batch versioning • Kinaxis: Real-time, interactive simulations • Blue Yonder: Limited scenarios, intuitive UI • o9: Custom dashboards, graph simulation • OMP: Traditional UI, strong solver-based views 👨💻 Whether you’re running S&OP, demand/supply planning, or inventory optimization, the right choice depends on: • Industry complexity • Real-time decision needs • Data governance readiness • Optimization depth 📌 Save this for your next tool evaluation or POC session! 💬 Which one do you use or wish to evaluate ? Let’s exchange ideas. #SAPIBP #Kinaxis #BlueYonder #o9Solutions #OMP #SupplyChainPlanning #DigitalSupplyChain #SaaS #AIinPlanning #SCM #TechComparison #PlanningTools #LinkedInLearning Stefanini Group Stefanini North America and APAC Stefanini Brasil Stefanini EMEA Sandy Sankara Easwara Dhananjay Karanam Bala Upadhyayula Santosh Chavan satish mallina Veerabhadra Rao Kakarapalli

⚙️ Planning without constraints is just theory. Advanced Planning & Scheduling (APS) brings planning closer to real-world execution. Traditional systems often assume unlimited capacity — but factories, machines, labor, and transport all have limits. APS is designed to plan with reality in mind. Here’s what APS really does 👇 🧠 What is APS? A constraint-based optimization and simulation system that enables real-time, finite-capacity planning and decision support across the supply chain. 🔍 Core Capabilities ⚖️ Optimization Balances cost, service levels, capacity, inventory, and profitability. 🔮 Simulation (What-If Analysis) Tests scenarios like demand spikes, supplier delays, or capacity reductions before decisions are made. 🏭 Finite Capacity Scheduling Plans using actual machine, labor, and shift constraints. 🧩 Multi-Constraint Planning Simultaneously considers materials, lead times, transport, and operational rules. 📊 APS vs Traditional MRP MRP → Assumes infinite capacity & reacts after issues occur APS → Considers real constraints & enables proactive decisions 🧠 Simple Memory Framework MRP plans materials → ERP executes transactions → APS optimizes decisions Modern supply chains don’t just plan orders — they simulate outcomes before execution. Is your planning system reactive or predictive? #SupplyChain #APS #ProductionPlanning #SupplyChainPlanning #MRP #ERP #Manufacturing #OperationsManagement #DigitalSupplyChain #Industry40 #DecisionSupport #SupplyChainManagement

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.

⛓️ Modern supply chains are a web of complex decisions that require powerful mathematical optimization tools for everything from inventory levels to logistics. With AI agents, your supply chain analysts can easily access these optimizations for better day-to-day decision-making. Here's how it works with the Mosaic AI Agent Framework: 1. 🧑💼 A supply chain manager asks a complex question in plain language, like, "What’s the impact if our top supplier is delayed by four weeks, and what actions should we take?" 2. 🤖 The AI agent understands the user's intent and recognizes that this requires a specific optimization model. 3. 🎛️ The agent autonomously calls the correct tool with the right parameters, running a simulation to calculate the impact and identify mitigation strategies. It then translates the model's complex output back into a clear, actionable recommendation for the manager.

𝐘𝐨𝐮𝐫 𝐒𝐀𝐏 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐢𝐧𝐠, 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭𝐚𝐭𝐢𝐨𝐧 & 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬 𝐦𝐨𝐝𝐮𝐥𝐞𝐬 𝐬𝐡𝐨𝐮𝐥𝐝 𝐛𝐞 𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐬𝐢𝐠𝐧𝐢𝐟𝐢𝐜𝐚𝐧𝐭 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐠𝐚𝐢𝐧𝐬 𝐚𝐧𝐝 𝐜𝐨𝐬𝐭 𝐬𝐚𝐯𝐢𝐧𝐠𝐬. But for many organizations? They're underutilized assets within your ERP system. While discussions are around new AI tools, the most impactful supply chain optimization tools might already be at your fingertips. Many logistics teams I consult with use these modules just as data entry with: ↳ Lack of integrated processes. ↳ Absence of standardized workflows. ↳ Minimal automation. Consider this scenario that's reshaping operations for forward-thinking supply chain leaders: → Optimizing 25 high-volume shipping lanes with SAP TM can lead to substantial freight cost reductions. → Implementing SAP EWM across warehouses enhances inventory accuracy and order fulfillment speed. → Integrating smart labor management systems can boost productivity by over 15% without increasing headcount. When these systems are fully leveraged: → You're looking at potential annual savings exceeding $1.5 million, just from enhanced operational efficiency. The gap between average operations and top-tier performance isn't about adopting the latest tech; it's about effectively utilizing existing tools. If your warehouse and transportation operations aren't optimized daily... You're leaving substantial value on the table.

In supply chain, one shift can impact everything. That’s why smart teams don’t guess. They simulate. Demand changes fast, VIP orders, supply shortages, urgent requests. Re-prioritizing without testing can cause more harm than help. That’s where Backorder Processing Simulation (BOP) in SAP S/4HANA aATP comes in. Here’s How BOP Simulation Helps You Make Smarter Supply Chain Decisions: What it is ↳ A risk-free “what-if” tool ↳ Re-prioritize orders without affecting live data Why it matters ↳ Changing one order affects many ↳ Simulation shows impact before you act How it works ↳ Select criteria: customers, materials, dates ↳ Apply a strategy (WIN, FILL, REDUCE) ↳ Run simulation + analyze shifts Use case examples 🔹 Product shortage? → See how top customers get impacted 🔹 Big order just arrived? → Test fulfillment without hurting commitments 🔹 Updating ATP logic? → Avoid disruptions before going live Key benefits ↳ Faster decisions ↳ Smarter order fulfillment ↳ Stronger customer trust ↳ Optimized inventory Backorder Processing Simulation isn’t just a fallback. It’s how leaders plan ahead, without the guesswork. Are you using simulation to shape smarter supply chain moves? #SAP #S4HANA #aATP #SupplyChain #BackorderProcessing #SAPTips #LogisticsOptimization

☁️💻 Top 10 Logistics & Supply Chain Management SaaS Products — with Market Share Insights The global Supply Chain Management (SCM) software market is growing rapidly, driven by cloud adoption, AI, real-time visibility, and end-to-end digitalization. While hundreds of tools exist, the top 10 SCM SaaS players control ~43% of the global market. Here’s a clear snapshot of who leads and why 👇 🔹 1. SAP (SAP IBP / SAP SCM) 📊 ~12.2% market share The undisputed leader. Strong in demand planning, S&OP, inventory optimization, and enterprise-wide integration. 🔹 2. Oracle SCM Cloud 📊 ~7–8% A complete cloud SCM suite covering procurement, logistics, manufacturing, and fulfillment. 🔹 3. Blue Yonder (Luminate Platform) 📊 ~5–6% AI-driven planning, forecasting, WMS, and TMS—very strong in retail and complex supply chains. 🔹 4. E2open 📊 ~4–5% End-to-end connected supply chain with strong collaboration, planning, and execution capabilities. 🔹 5. Infor (Infor Nexus) 📊 ~3–4% Cloud-native supply chain network focused on global trade, visibility, and supplier collaboration. 🔹 6. Coupa (Supply Chain Design & Planning) 📊 ~2.5–3.5% Combines spend management with supply chain planning and optimization. 🔹 7. Manhattan Associates 📊 ~2.5–3% Best-in-class WMS, TMS, and omnichannel fulfillment solutions. 🔹 8. Kinaxis (RapidResponse) 📊 ~2–2.5% Leader in real-time planning, scenario modeling, and supply chain resilience. 🔹 9. Epicor SCM 📊 ~1.5–2.5% Strong mid-market SCM solutions for manufacturing and distribution. 🔹 10. project44 / FourKites 📊 ~1–2% (visibility niche) Specialized leaders in real-time shipment tracking and logistics visibility. 📌 Key takeaway: ✔️ The SCM SaaS market is dominated by a few giants, while the rest is highly fragmented ✔️ Enterprises now use multiple SaaS tools together (Planning + Execution + Visibility) ✔️ Cloud, AI, and real-time data are no longer optional—they’re mandatory 💬 Question for you: Which SCM SaaS platform are you using today—and why? #Logistics #SupplyChainManagement #SCMSoftware #SaaS #DigitalSupplyChain #LogisticsGuide #SupplyChainTech