Solutions
Sales, Inventory and Operations Planning
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.
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Supply chain planning is broken — and it’s costing you
The distributor channel hides true demand
Disconnected S&OP and execution systems
Subcontractor networks and combinatorial complexity
Customer-specific constraints and configuration complexity
Slow, inaccurate order promising
Differentiating Capabilities
- 01
Unified S&OP + S&OE in a Single Model
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.
Read more → - 02
Sell-In / Sell-Through Demand Planning
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.
Read more → - 03
Multi-Echelon Inventory Optimization (MEIO)
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.
Read more → - 04
3rd Gen Attribute Based Planning (ABP)
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.
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Checking hold reason, then capacity, then the customer commit
- ✓mes.lot.getStatus(4471)MES
- ✓mes.hold.list(4471)MES
- ✓aps.schedule.simulate(Etch-02)APS
- ✓siop.commit.check(88-102)SIOP
Only quality-gated runs are kept, so the agent gets more consistent over time.
Differentiating Capabilities
-
01
Unified S&OP + S&OE in a Single Model
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.
Read more → -
02
Sell-In / Sell-Through Demand Planning
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.
Read more → -
03
Multi-Echelon Inventory Optimization (MEIO)
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.
Read more → -
04
3rd Gen Attribute Based Planning (ABP)
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.
Read more →
Checking hold reason, then capacity, then the customer commit
- ✓ mes.lot.getStatus(4471) MES
- ✓ mes.hold.list(4471) MES
- ✓ aps.schedule.simulate(Etch-02) APS
- ✓ siop.commit.check(88-102) SIOP
Only quality-gated runs are kept, so the agent gets more consistent over time.
Key Solutions
Sales & Operations Planning (S&OP)
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
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.
Supply Chain Planning
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.
Inventory Planning
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)
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.
Attribute Based Planning – 3rd Generation
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.
AI-Driven ATP / CTP
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.
Agent EyeQ – Electronic Employee
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.
Real Results with the right SIOP
Minimize costly shortages or excess inventory
Reduce the risk of stockouts that waste capital and disrupt production. Make smarter decisions with data-driven visibility across your supply chain.
Gain new visibility into production capacity and inventory usage
Identify bottlenecks with production capacity, machine availability, and inventory utilization before there are impacts to customers.
Capable to Promise (CTP)
Create accurate, buildable production plans that meet customer commitments
Simplify allocation planning for equitable inventory distribution
Eliminate manual process and streamline allocation across multiple production sites.
Optimize lead times for best on time in full (OTIF) performance
Align throughput and capacity to meet promised delivery dates. Increase operational efficiency while achieving OTIF targets.
Business Support as a Service (BSaaS)
A SIOP process that runs every month, not just the first one.
Embedded engineers
- Design your SIOP cadence, roles, and decision points with your leadership team
- Configure demand, supply, inventory, and financial views in Eyelit SIOP, connected to ERP and Eyelit APS
- Build the scenarios your executives actually ask about, from capacity investments to supplier risk to demand swings
Ongoing operational support
- Prepare data and run monthly demand and supply reviews ahead of each executive meeting
- Produce the scenario analysis, KPI packs, and executive dashboards your team presents
- Keep forecasts, inventory targets, and planning parameters current as the business changes
Same system. Different jobs.
The only thing that changes is who’s holding the wheel. Same tools, same governance, deployed to match the task at hand.
Helps you do your job better
Sits next to the operator. Suggests, drafts, recommends, and executes on request. The user stays in charge at every step.
- Drafts dispositions, RCAs, and schedule changes for review
- Surfaces relevant operational data on demand — no dashboards to build
- Walks junior engineers through unfamiliar tasks
- Accelerates routine work for experienced operators
Who’s holding the wheel
You act on the agent’s suggestions. It drafts, you decide.
Real Insights and Real Results
Case studies and practical outcomes from complex manufacturing operations.
Case Study8 steps to improve plant performance
According to the Office for National Statistics (ONS), output per worker in the UK fell by 0.1 per cent in the first quarter of 2026 compared with a…
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Case Study6 Essential KPIs for Manufacturing Performance
Depending on the systems and processes you have in place on your factory floor, you may face one of two problems; either you don’t know which key performance…
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Case StudyWhy Are You Still Using Spreadsheets for Production Planning & Scheduling?
Are you still spending time on spreadsheets adjusting production plans and schedules? If so, you are not alone.
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Case StudyHow to turn small batch manufacturing from problem to opportunity
James Womack, author of the best-selling business classic text ‘Lean Thinking’, tells the story of how he challenged his children to an envelope-stuffing competition.
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Case StudyIndustry 4.0: don’t get left behind
Industry 4.0, smart manufacturing, big data, IoT, advanced manufacturing intelligence… you’ve heard all the buzzwords, but what do they really mean, and what’s their relevance to your manufacturing…
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Case StudyRevenue per full-time employee – why it’s a waste of your time…
Revenue per full-time employee – why it’s a waste of your time… The chances are that the way you measure the productivity of your workforce is to calculate…
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Case StudyFive must-have features for your next shop floor data collection system
Investing in any new system for your business can have far-reaching consequences. Apart from the direct costs involved, you will be conscious of the time and resources…
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Case StudyPlanning and Scheduling – A Key Enabler of Industry 4.0 Transformation
Industry 4.0 envisages a flexible network of connected Cyber Physical Systems (CPS), working autonomously and self-optimizing performance across the network.
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Case StudyThe Digital Twin’s Role in the Production Environment
A digital twin is a digital representation of a real-world entity that contains both the structure and the dynamics of the real-world entity. It is connected to its…
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Case StudyIndustry 4.0 Implementation and Strategy
Today most production managers are participating in a race, whether they know it or not. It's the race to adopt and implement new manufacturing systems and technologies.
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Case StudyMulti-Stage Scheduling
In the automotive industry, the entire supply chain is driven by the assembly line sequence. Links within the chain are relied upon to produce and deliver parts on…
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Case StudyHow to Prepare for Supply Chain Automation & Stay Competitive
Market forces and technological advancements continue to accelerate the already unprecedented levels of information and product exchange around the world.
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Case StudySupercharging the Digital Twin with Planning & Scheduling 4.0
The digital twin is a powerful Industry 4.0 capability that is transforming manufacturing operations.
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Case StudyMulti-Zone Sequencing
Eyelit Technologies MLS, versions 7.0 and beyond introduce multi-zone production sequencing, a new approach to optimization which can benefit plants with the need to generate a sequence for…
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Case StudyHow Can Manufacturers Become More Sustainable
The Automotive Industry Action Group (AIAG) is hosting a Virtual Corporate Responsibility Summit on April 28. Leading automotive manufacturers will come together to discuss production planning and scheduling,…
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Case StudyStabilize Your Supply Chain
Optessa Founder and CEO Ashok Erramilli discusses the power of data-driven analytics and the importance of achieving balance and stability in production management.
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Case Study5 COMPONENTS OF PRODUCTION SCHEDULING
Production Scheduling is "used in a manufacturing process to allocate plant and machinery resources, plan human resources, plan production processes and purchase materials". What are the components of…
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Case StudyEyelit’s Integrated Manufacturing System (MES) Selected and Deployed by WD Lab Grown Diamonds
TORONTO—(BUSINESS WIRE)—Eyelit, a manufacturing software provider for visibility, control, and coordination of manufacturing operations, announced today that WD Lab Grown Diamonds
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Case StudyEnterprise Production Scheduling Solutions
Enterprise manufacturers need manufacturing scheduling software that can simultaneously simplify the complexity of the detailed scheduling process, boost the efficiency of the production process, and ensure on-time production…
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Case StudyModern CTO Podcast | Episode #284 | Erwin Paes
Erwin Paes spoke with Modern CTO Podcast host Joel Beasley on the intricacies of planning and scheduling in manufacturing, how Optessa's greatest strength is their people, and the…
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Avoid another year of decisions made in silos, alerts with no explanation, and your best people buried in dashboards instead of strategic work. See Agent EyeQ reason, act, and deliver outcomes across your manufacturing platform, in a live demo tailored to your environment.
