All Dataleo news, jobs, analyses and tutorials around S&OP in Supply Chain and Operations.
The role is relevant to planning operating-model design, decision rights, technology implementation and measurable process outcomes.
The role is relevant because it connects SAP IBP, S&OP, demand, inventory and supply planning with governed decision processes.
This job is a useful signal for Supply Chain Planning because it focuses less on system implementation alone and more on the operational end-user layer of SAP IBP. The role sits where planning tools, recurring routines and business decisions meet.
For planning leaders, the interesting point is governance of the weekly and monthly decision cycle: which alerts matter, which KPIs trigger escalation, who owns the short-term response plan, and how planning data becomes trusted enough to support S&OE and S&OP decisions consistently.
MediumMediumHighMediumHighMediumA 2026 study conducted by Incisiv with Anaplan examines responsiveness, planning technology, AI infrastructure and the financial impact of delayed decision-making. It frames planning latency as a hidden cost that can erode margins.
LowSKU Science remains a useful Radar signal for lightweight demand planning and S&OP, especially for SMB, e-commerce and retail teams that need structure without a large enterprise planning suite.
The practical relevance is Demand Planning, SKU-level forecasting, inventory planning and planning analytics. For smaller teams, the first AI-enabled planning step is often not agentic automation, but replacing fragile spreadsheets with repeatable forecast review and decision routines.
More details are available on the SKU Science website.
This product signal matters because Supply Chain AI adoption also happens in small and mid-sized companies. SKU Science should be tracked where accessible planning tools help teams build forecast discipline, planning ownership and Planning Governance.
MediumColibri S&OP is positioning AI Agents inside supply chain planning workflows covering demand planning, supply planning, strategic planning, safety stock optimization and constrained plan optimization.
This is relevant for mid-market and local planning teams because it shows how agentic planning ideas are moving beyond global mega-suites. The practical question is how S&OP teams use agents to accelerate scenarios and exceptions while keeping human ownership of planning decisions.
More details are available on the Colibri S&OP website.
This product signal matters because Agentic AI in planning is not only a large-enterprise trend. Colibri S&OP should be tracked where AI helps business users structure demand, supply and scenario decisions inside a governed Planning Governance process.
HighA new wave of Supply Chain AI experimentation is emerging across the planning community. Inspired by initiatives such as Knut Alicke’s AI-assisted S&OP application, supply chain professionals are increasingly using vibe coding tools to build operational applications without traditional software development teams.
What started as isolated experiments is becoming a broader movement. Examples now span S&OP, demand planning, inventory management, scenario modeling, supplier risk monitoring and planner copilots. Recent community examples include AI-generated planning applications shared by practitioners such as Mahmoud Moursy, alongside other public discussions around IBP engines, manufacturing dashboards and supply-chain planning automation.
The emergence of these tools creates a new layer between Excel and enterprise APS platforms. Rather than replacing established planning solutions, these lightweight applications allow domain experts to rapidly test ideas, automate workflows and address local planning challenges that may never justify a large transformation project.
However, the opportunity comes with significant risks. As more planners become application builders, organizations must address AI governance, data quality, model transparency, business ownership, security, auditability and integration with enterprise systems. Without controls, companies risk creating a new generation of planning silos and shadow applications powered by AI rather than spreadsheets.
The most important signal is not that planners can now build software. It is that the economics of solution creation have changed. A planner with deep business expertise and access to modern AI tools can now prototype a functional Supply Chain Planning solution faster than many traditional software projects can complete requirements gathering.
For leaders, the question is no longer whether employees will build AI-powered planning applications. They already are. The strategic question becomes how to govern them through version control, testing standards, approval workflows, data lineage, user permissions, documentation and lifecycle management.
This points to the emergence of a middle layer between Excel and enterprise ERP or APS environments. It can accelerate controlled prototyping, but it also creates operational risk when business logic, data flows and decision ownership are not explicit.
The Dataleo team is currently working on a practical framework to help companies evaluate, govern, industrialize and scale vibe-coded Supply Chain AI applications. More details will be shared soon.
HighFourKites has enhanced Inventory Twin to connect S&OP decisions with real operational inventory conditions. The update is designed to help teams identify gaps between planned inventory positions and execution reality across the network.
LowLisa Anderson was named among the Top 50 Manufacturing Thought Leaders for 2026, recognizing her work across manufacturing, ERP, S&OP, resilience and operational transformation.
MediumBoard and Microsoft highlighted agentic AI capabilities for enterprise planning. The signal for supply chain teams is that planning platforms are increasingly embedding AI agents into workflows that connect finance, operations and performance management.
For S&OP and IBP teams, the practical value is faster scenario support, insight generation and cross-functional planning alignment. The risk is that agents must be governed so that planning assumptions, approval workflows and Human-in-the-Loop controls remain visible.
This matters because Agentic AI is moving into planning platforms that influence enterprise decisions. Board users should evaluate agentic capabilities through governance, scenario ownership and decision traceability, not only productivity gains.
LowArkieva published practical supply chain planning content that frames AI as a way to improve forecasting, inventory decisions and planning collaboration rather than replace planners outright. The signal is useful because many mid-market planning teams still need process maturity before advanced automation.
For Demand Planning, inventory and S&OP teams, Arkieva’s relevance is pragmatic: better forecast discipline, structured exceptions, supply-demand balancing and planning routines. This connects Planning Governance with realistic AI adoption.
Arkieva is a useful Radar signal because not every company is ready for autonomous agents. Many need a reliable planning layer first, with clear owners, calendars, exception rules and human review before scaling Supply Chain AI.
MediumGanacos announced its participation in Supply Chain Event 2025 in Paris, where it planned a joint session with Carrefour on the retailer’s unified and collaborative private-label S&OP model.
The session was presented by Carrefour planning leaders Manuella Maignan Pierson and Juliette de Brisson, connecting demand and supply planning with private-label growth, supplier coordination and shared planning data.
The relevant signal is not the event presence itself, but the operating model behind the case. A unified S&OP process requires authoritative data, clear ownership of assumptions and controlled movement from commercial forecasts into supply and supplier decisions.
Leaders should assess whether the planning layer remains a lightweight collaborative environment or becomes sufficiently critical to require deeper integration with ERP, APS and supplier workflows.
MediumIntuiflow detailed its integration with SKU Science, adding demand-planning capabilities to a platform spanning S&OP, material planning, scheduling and execution.
MediumKomugi participated in Global Industrie 2025 in Lyon, where co-founder Xavier Feltin joined a roundtable on S&OP best practices and benefits for industrial organizations.
The event connected Komugi’s workload-capacity planning positioning with broader discussions on smart manufacturing, industrial AI and Industry 5.0.
The operational relevance is the link between strategic S&OP choices and executable capacity plans. Manufacturers need traceable assumptions, realistic bottleneck data and named ownership before scenarios are translated into production or investment decisions.
MediumIn 2020, Jean-François Nordmann joined o9 Solutions to help develop the French market. His role covered market opening, qualification of planning needs and discussions with Supply Chain, IT and transformation leaders around integrated planning.
The move reflected growing French interest in Supply Chain Planning, S&OP, IBP and APS platforms able to connect business planning with enterprise data and execution processes.
Planning collaboration creates value when it preserves assumptions, alternatives, owners and outcomes behind decisions.
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Moving planners from manual reporting toward interpretation and strategic influence
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Fast Company argues that AI is accelerating insight generation while many organizations still rely on monthly S&OP cycles and fragmented decision workflows.
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