Haver & Boecker: AI-Powered Spare Parts Planning for 20,000 SKUs, Service-Driven

PartsOS Planning

Haver & Boecker: AI-Powered Spare Parts Planning for 20,000 SKUs, Service-Driven

How the global machinery manufacturer is moving from reactive, manual inventory planning to AI-based purchase recommendations with PartsOS Planning — to elevate its service level.

Who is Haver & Boecker?

HAVER & BOECKER is a tradition-rich, family-run industrial company headquartered in Oelde (Westphalia, Germany), founded in 1887. Today, it ranks among the world's leading technology providers in wire mesh and machinery manufacturing, with subsidiaries across the globe. HAVER & BOECKER unites two core business areas under one roof:

🔹 Wire Weaving Division

🔹 Machinery Division

Within the Machinery Division, HAVER & BOECKER develops equipment for the filling, packaging, and logistics of bulk materials (e.g. cement, building materials, chemicals, food). These include filling machines, weighing and dosing systems, and complete packaging lines.

A critical part of this business: spare parts and service.

High machine availability: Spare parts are essential to prevent downtime and quickly restore production processes.

Long life cycles: Industrial equipment often runs for many years — reliable spare parts supply secures long-term operation.

Original parts & quality: Precise original spare parts ensure optimal performance, safety, and efficiency.

That makes spare parts supply a business foundation — for Haver & Boecker and for every one of their customers worldwide. Due to the high share of special-purpose machines and their long operational lifetimes, the spare parts portfolio is exceptionally broad: over 20,000 distinct items have been sold as spare parts over the past three years.

The Starting Point

Disposition across the entire portfolio runs on automated but rigid rules. Every item — spare part or production part — is treated the same way. There's no spare-parts-specific focus and no differentiated forecasting logic. Currently selected items are planned with the same method: a slightly adjusted average of consumption over the past 12 months.

In practice, this meant:

🔹 Reactive forecasts: Stock levels were based on the past 12 months of consumption.

🔹 20,000 SKUs, high complexity: A special-machine portfolio doesn't lend itself to standardization. Stocking decisions get made in bulk or have to be adjusted by hand — eating up coordination time.

🔹 Rigid disposition rules: Led to frequent small orders with process costs of around €100 per transaction.

🔹 Stock-out situations: Critical spare parts repeatedly missing, stretching lead times and causing delivery delays.

🔹 Limited stock range and shipping times: Customers unhappy with delivery times, leading to lost sales — particularly on marketable items.

The result: a planning team forced to chase critical spare parts and constantly battle backlogs and stock-outs.

Why PartsCloud

Before the decision, Haver & Boecker deliberately weighed three alternatives:

  • Wait for SAP S/4HANA

    and operate manually in the meantime

  • Build a custom solution

    with all the internal development resources that ties up

  • Evaluate competing solutions

    in the spare parts space

PartsCloud won on three criteria:

  • AI- and ML-based planning, not 12-month logic

    AI- and ML-based planning, not 12-month logic

    PartsOS Planning analyzes more than just the past. It detects seasonality, peaks, lifecycles, and consumption patterns — and incorporates Haver & Boecker's specific machine knowledge. Reactive planning becomes proactive, data-driven planning.

  • Integration, not replacement

    Integration, not replacement

    PartsOS Planning works as a standalone AI tool that complements the existing SAP setup. That keeps effort and IT risk low — and brings a speed that an S/4HANA migration can't match.

  • Direct impact on every pain point at once

    Direct impact on every pain point at once

    Service level up, process costs down, scrap down — and inventory built up exactly where it's missing today. Demand-based, not blanket. At the center: service level. It's Haver & Boecker's most important lever and the central target metric of the business case.

The Setup

The pilot started with 150 material numbers as initial scope.

The next step: a gradual expansion toward roughly 10% of the SKU portfolio — about 2,000 items — being loaded into PartsOS Planning and analyzed. In this phase, purchase requests are still deliberately handled manually by the planning team rather than triggered automatically.

Since calendar week 22, Haver & Boecker has been using PartsOS Planning specifically for the most critical items — the spare parts that repeatedly arrived late or were unavailable in the past.

Running in parallel:

🔹 Data integration via structured Excel uploads as a pragmatic starting point ahead of a deeper SAP integration

🔹 Regular alignment meetings between the Haver & Boecker and PartsCloud teams to calibrate purchase recommendations and address edge cases

🔹 A fundamental internal shift in the planning team: moving from rigid rules toward service-level-driven stocking. This is deliberately not just a tool topic — it's a mindset shift Haver & Boecker is actively driving.

What the Business Case shows

Before the pilot, PartsCloud and Haver & Boecker built a detailed business case together. The dimensions at full rollout:

15%

higher availability

< 6 months

payback period including peak phase

up to 1 Mio. €

ROI-amount per year

What's Next

🔹 Validation of the business case projections through the remainder of the pilot phase

🔹 Gradual expansion beyond the initial 150 items — full scaling is tied to automated SAP integration of purchase recommendations

🔹 Deeper SAP integration — ideally with automated export of purchase recommendations to eliminate manual handoffs

🔹 Expansion to additional planning areas beyond the initial setup

🔹 Internal service-level discussion: higher stocking at strategic points as a deliberate investment in delivery capability

🔹 Handling of dual-use consumption: many items are needed both as spare parts and for new machines. PartsOS Planning needs to cleanly differentiate and reflect this in its forecasting logic.

The pace is set. Service means delivering. That's exactly what Haver & Boecker is now equipped to do — a little better, every day.

"Our goal is to provide our customers with the right spare part exactly when it is needed. Our previous planning processes could not consistently meet this requirement, particularly for critical parts. Furthermore, the high level of complexity involved in custom machinery manufacturing demands flexible rather than rigid planning approaches. With PartsOS Planning, we are transforming our inventory management into a data-driven, dynamic control system that is consistently aligned with service levels and places a much stronger emphasis on spare parts operations."

Hannes Malczewski

Interim Head of Spare Parts Shipping & Project Coordination

FAQs

  • What does Haver & Boecker use from PartsCloud?

    Haver & Boecker uses PartsOS Planning — PartsCloud's AI-based spare parts planning solution. The ongoing pilot currently covers 150 material numbers; the planned scaling targets ~10% of the SKU portfolio (about 2,000 items).

  • How does PartsOS Planning integrate with Haver & Boecker's SAP environment?

    During the pilot, via structured Excel uploads (data export from SAP, upload to PartsOS Planning, transfer of purchase recommendations back into SAP). A deeper, automated integration is planned and necessary as the next step.

  • What alternatives did Haver & Boecker evaluate?

    SAP S/4HANA as a future option, a custom in-house build, and other providers in the spare parts space. PartsCloud won because of its AI-based planning, fast integration with the existing SAP setup, and direct impact on every relevant pain point.

  • How fast is time-to-value?

    First purchase recommendations run early in the pilot phase. Initial data load of 9 files takes about 1.5 hours. Scaling and integration proceed iteratively.

More Customer Stories

Find out how other industrial companies have transformed their spare parts planning with PartsCloud.

Coperion

How Coperion used PartsOS Planning to virtually eliminate impending stockouts on critical components, increase parts availability by over 15%, and achieve full ROI within just three months.

EUCO Rail AG

How EUCO Rail is transitioning, together with PartsCloud, from reactive, spreadsheet-based planning to proactive, AI-powered spare parts management, ensuring critical components are reliably available across all locations.