Planning that adds up. Stock levels that are accurate.

For SCM and procurement teams who derive precise, SKU-accurate forecasts from their ERP data — without Excel workarounds or gut feeling.

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You know how forecasting works

But ERPs and manual order calculations hit their limits as soon as the product range grows or demand becomes more volatile.

  • Demand forecasting in Excel & ERP

    Weeks of work, error-prone, and no one really trusts the numbers.

  • Duplicate work without a shared data foundation

    Forecast and ordering decisions are based on different, unsynchronized figures.

  • Rarely the right level

    Inventory swings between overstock and stockout.

From disposition to strategic planning

Forecasting and procurement in one platform — no Excel insider knowledge and no weeks-long training. With PartsOS, your disposition works productively from day one

AI that knows your demand

Our ML models detect seasonality, lead-time variability, lifecycles, and sporadic demand patterns—delivering forecasts that stand up to S&OP scrutiny.

Forecasts that know your procurement logic

Lead times, MOQs, and supplier terms feed into the forecast — so it's immediately ready for procurement as soon as you transfer it into your ERP.

Scheduling without Excel know-how

Forecasts and order proposals in a single system. Lead times, MOQs, and supplier terms are automatically factored in—accept or reject with a single click.

Intuitive. Powerful.

Behind the clean interface are AI and machine learning models that incorporate every change into your forecasts.
The result: reliable foundations for every decision.

What Changes for You

KPIs that measurably improve instead of blocking each other.

  • Higher Forecast Accuracy

    Higher Forecast Accuracy

    Unlike traditional forecasts, seasonality, maintenance cycles, and special effects are factored in automatically. Customers report forecast accuracy improvements of 20–40%.

  • Lower inventory, more free working capital

    Lower inventory, more free working capital

    Optimized to your service level target - tailored per part, not averaged across the assortment. Inventory reductions of 15–25% are the rule, not the exception.

  • Demand planning as a repeatable process

    Demand planning as a repeatable process

    No hidden Excel knowledge that disappears when someone leaves. Your planning process becomes transparent, traceable, and transferable.

How the AI in PartsOS arrives at its forecast

For every single SKU, PartsOS tests over 100 forecasting models in backtesting and selects the most accurate one. With every new planning run, the forecast is further refined.

Our Forecasting Method

Over 100 forecasting models are tested per part in backtesting. The model with the lowest forecast error is selected and re-evaluated with every new planning run.

Our AI Approach

How PartsOS complements your ERP

Your ERP manages what is there. PartsOS plans what is needed next.

Your ERP

Task

Manages inventory, orders, and master data in one place.
+ Provides the demand forecast per SKU over 12 months.

Forecasting

Plans according to fixed, consistent rules.
+ Select the most suitable option from up to 100 models for each part, even for sporadic requirements.

Data basis

Works with your master and transaction data.
+ Additionally incorporates consumption patterns and other signals.

Up-to-dateness

Fixed logic, once set up.
+ Refines the forecast with each planning run.

Interplay

Order and book as usual.
+ Returns the released forecast to your ERP.

How it works

Three steps, clear responsibilities, no extensive onboarding.

  • Data comes in

    Data comes in

    Upload master data, consumption history, stock levels, and lead times from your ERP using a standard template. SAP, Dynamics, ProAlpha, ABAS, or custom systems - all common platforms are supported.

  • Smart Upload checks your data

    Smart Upload checks your data

    Our Smart Upload automatically checks your data sets for gaps and inconsistencies and gives you direct feedback like an assistant — for example, if more parts were delivered than your booked quota allows. Only afterward do you review the results together with our team and start your planning run for the quarter.

  • Review, approve and export forecasts

    Review, approve and export forecasts

    Per part: the demand forecast for the next 12 months, optimized for your service-level target. You go through the forecasts at your own pace, confirm what should be transferred into your procurement, and export the approved forecasts.

How customers use PartsOS

See how mechanical engineering companies, from Hymmen to Coperion to EUCO Rail, have used PartsOS to systematically improve their spare parts planning.

  • EUCO Rail AG

    Data-driven spare parts planning for maximum vehicle availability in rail transport

    Learn more

  • Coperion

    Intelligent spare parts planning for greater planning reliability and parts availability

    Learn more

  • Weinig AG

    AI-powered spare parts planning for a world market leader in woodworking machinery

    Learn more

  • Hymmen GmbH

    From manual planning to autonomous AI-driven spare parts management

    Learn more

FAQs from Supply Chain- and Procurement Teams

  • How does PartsOS integrate into our existing S&OP process?

    PartsOS integrates into any S&OP cycle—whether weekly, bi-weekly, or monthly. The forecast output can serve as a data basis for S&OP meetings without requiring you to change existing processes.

  • What forecast accuracy do customers typically achieve after 3-6 months?

    Most customers see a 20-40% improvement over their previous forecast level within the first six months. The range depends on data quality and assortment complexity.

  • How does PartsOS handle sporadic or volatile demand (lumpy demand)?

    Lumpy demand is the rule, not the exception, in spare parts. PartsOS uses models specifically designed for sporadic demand patterns and selects the right model per SKU - not a one-size-fits-all approach.

  • Can we input minimum order quantities (MOQ), safety stocks, and supplier terms?

    Yes. MOQs, safety stocks, service-level targets, and supplier prices per quantity tier are part of the standard input. PartsOS automatically factors them in when creating forecasts, so the forecast is immediately ready for procurement.

  • How does PartsOS handle lead time variability?

    Lead times are incorporated as a variable in the model. If you have historical lead time data, PartsOS learns from the variability and reflects it in the safety stock calculations.

  • Does PartsOS also create order suggestions, or does it stop at the forecast?

    PartsOS delivers the demand forecast per SKU — the basis for your procurement decision. What you order from it is decided and triggered as usual in your ERP or procurement system. This way, decision-making authority stays fully with your team.

  • How do we handle ABC or XYZ classifications?

    PartsOS automatically classifies SKUs by demand pattern and value contribution and adjusts the forecasting strategy per class.

Ready for predictable procurement?

Every business is different. What matters to us are your individual challenges. Let's talk about your untapped potential together.

Where does your spare parts planning stand today?

Four questions, two minutes. Afterwards, our team will provide an honest, personalized assessment, tailored to your specific situation.

Quick Check

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In 30 minutes, we'll walk through together what your trial phase looks like - scope, data setup, and start date - so that PartsOS works for your specific use case.

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