Unifies long-range S&OP with multi-plant S&OE execution in one model built for complex discrete industries like semiconductor, medical, industrial, automotive and ETO, CTO, MTO manufacturing.
Eyelit SIOPLiveMES · APS · SIOPCommitments flow down to Eyelit APS and MES
Demand PlanningSIOPSupply Chain PlanningSIOPInventory PlanningMEIOSales & Operations ExecutionS&OEToday’s manufacturers are forced to stitch together multiple disconnected systems for S&OP, S&OE, demand planning, and factory scheduling. The result: data latency, planning gaps, and missed commitments.
In many complex discrete industries like semiconductor and medical supply chains, what’s actually selling through to end customers is largely invisible. This causes revenue generating demand signals to be distorted and unseen distributor inventory building up in the channel. The end result is revenue projections that are unreliable.
S&OP Plans do not have the detail required to properly coordinate across plants and are only updated periodically. This results in the use of outdated information that is not sufficient to coordinate and communicate cross plant at execution time. In the end planners rely on spreadsheets to plan in a disconnected fashion.
Complex discrete supply chains span dozens of subcontractors that have different capacities, lead times, qualifications, and cost structures. The number of planning combinations grows exponentially. Humans with spreadsheets simply can’t keep up, and the result is poor use of existing inventory, contracted capacity, and product substitution alternatives.
Each order can carry unique requirements: product specs, approved suppliers, quality grades, country-of-origin rules, regulatory certifications, and alternative acceptable configurations. Standard planning systems do not have an efficient way to plan in this situation, forcing planners to police them manually or create an explosion of part numbers.
Sales commits delivery dates without visibility into real-time full supply chain materials and capacity availability — eroding customer trust.
Reduce the risk of stockouts that waste capital and disrupt production. Make smarter decisions with data-driven visibility across your supply chain.
Identify bottlenecks with production capacity, machine availability, and inventory utilization before there are impacts to customers.
Create accurate, buildable production plans that meet customer commitments
Eliminate manual process and streamline allocation across multiple production sites.
Align throughput and capacity to meet promised delivery dates. Increase operational efficiency while achieving OTIF targets.
Aligns demand, supply, capacity, and financial plans across your organization through constrained optimization — with scenarios as the tool for exploring the uncertain. Because Eyelit S&OP and S&OE share the same model, the approved plan flows directly into execution without translation or data loss.
Demand planning that combines statistical models, sales insights, customer demand signals, and market intelligence into a single, aligned forecast. Machine learning evaluates the historical accuracy of each input and automatically weights contributions accordingly. Combined with distributor sell-through visibility and attribute-based forecasting for complex configured products, plans stay aligned with real market demand rather than assumptions.
Optimization-driven planning across manufacturing, distribution, replenishment, capacity, and materials within a single unified model. Advanced optimization simultaneously evaluates all feasible supply chain alternatives and automatically generates the best plan based on business objectives, constraints, and operational priorities.
Set scientifically calculated safety stock targets at every supply chain tier — raw material, WIP, sub-assembly, finished goods, and distributor — using multi-echelon inventory optimization (MEIO) to minimize total pipeline cost while meeting service level objectives.
Sales & Operations Execution (S&OE) orchestrates the supply chain in real time, continuously re-planning and re-scheduling orders at a detailed level, automatically responding to changing conditions throughout the day. This ensures commitments remain on track and operations stay aligned when disruptions occur.
An industry-leading approach to planning complex ETO, ATO, CTO, MTO, and MTS environments with customer-specific specs. 3rd Generation combines ABP with Optimization and AI enablement.
Classical order promising replaced by Attribute Based Planning combined with AI. Customer-specific attributes defined per demand are propagated through the entire supply chain and continuously refined by AI — enabling intelligent, constraint-aware commitments that adapt with every order.
Embedded AI agents for schedule health monitoring, exception management, capacity alerts, what-if automation, and orchestrate the response across SIOP, APS, and MES. Prescriptive guidance bridges the gap between novice and expert planners.
That shared model is the foundation of closed-loop production orchestration. Commitments flow down to Eyelit APS and MES, and execution reality flows back up. Your long-range sales and operations plan and your day-to-day execution run on the same data model — no synchronization, no data translation, no lag. When supply conditions change on the shop floor, the plan updates automatically. Planners and operators always work from a single version of the truth.
Manage distributor channel inventory with visibility into what’s selling through to end customers — not just what was sold in. Early warning signals for increasing or decreasing sell-through prevent channel stuffing, reduce inventory risk in the distribution chain, and support more accurate revenue projections.
Scientifically calculated safety stock targets at every tier using stochastic models that minimize total pipeline cost while meeting customer service level objectives. Inventory is positioned where it protects service most efficiently, not where it accumulates by default.
3rd Generation ABP extends attribute-based planning across the entire production network—upstream and downstream, with no practical limit on BOM depth or complexity—and applies it to all planning objects, including processes and resources.
The only thing that changes is who’s holding the wheel. Same tools, same governance, deployed to match the task at hand.
“Sits next to the operator. Suggests, drafts, recommends, and executes on request. The user stays in charge at every step.”
You act on the agent’s suggestions. It drafts, you decide.
“Given a goal, not a script. Plans, executes, and escalates by exception. Reports to a human manager.”
The agent acts on its own and escalates exceptions to you.
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