AI-powered data cleaning solution

Because clean, reliable data is the foundation for everything you want to achieve. Without it, you face duplicates, blind spots, and rising costs. With it, you gain visibility, control, and confidence in every decision. That’s why we built SPARROW to make spare parts data simple, accurate, and actionable. You get a single source of truth that helps your teams collaborate better, reduce waste, and plan strategically — all while keeping day-to-day operations running smoothly

Spare parts data is rarely clean from the start. You often face duplicates, inconsistent names, missing specifications, or non-standard classifications. These issues usually come from manual entry, different supplier inputs, or legacy systems — and over time they lead to confusion, excess stock, and frustration across teams. With SPARROW.Clean, you don’t need to fix this manually. The platform automatically detects duplicates, flags inconsistencies, and helps you build harmonised, structured data standards across plants and systems. The result: cleaner data, smoother collaboration, and more confident decisions.

In large manufacturing groups, spare parts data often lives in silos. Different ERPs, plants, and teams use their own naming conventions, part numbers, or classifications. The result? Duplicate parts, fragmented inventories, and no clear overview at group level. This makes it difficult to pool stock, reduce costs, or keep control of MRO spend. Without one source of truth, central teams are left managing complexity without real visibility. That’s exactly what the SPARROW Hub solves: it brings all spare parts data together into a single, reliable view across your network. (You can read more about cross-site strategies on our blog.)

Spare parts harmonisation means working with a single set of clean, standardised data across all your plants and systems. Instead of different names, codes, or categories for the same part, you get one clear version of the truth. This matters because it reduces redundancy, improves visibility, and makes it easier to buy smarter at group level. With harmonisation, you can consolidate suppliers, share critical spares across sites, and unlock real savings in your MRO operations. The SPARROW Hub gives you the structure and tools to make this possible — turning messy, disconnected data into a real strategic asset for your business.

When your spare parts data isn’t reliable, costs rise fast. Duplicate entries, unclear naming, or missing details make it hard to know what you already have — so teams often reorder “just in case.” The result is excess stock, tied-up working capital, and more emergency orders than you’d like. With clean, harmonised data, you can see real demand, optimise reorder policies, and remove duplicates. That way, you reduce waste, lower inventory costs, and keep your spare parts management lean and efficient.

Cleansing your spare parts data once is a good start — but it won’t keep things clean for long. New parts get added, specs change, and people come and go. That’s why keeping data quality high needs to be an ongoing process. With SPARROW.Clean, you don’t just fix your data today; you get tools to stop it from slipping back tomorrow. Built-in monitoring, alerts, and rule-based checks help you keep control, so your spare parts data stays reliable and supports your business in the long run.

Every big digital project depends on clean master data. Whether you’re moving to SAP S/4HANA, setting up predictive maintenance, or centralising procurement, unreliable spare parts data will follow you into new systems and weaken your investment. With SPARROW.Clean, you get a structured, scalable way to clean and harmonise your MRO data before you take the next step. It integrates with ERP and CMMS, giving you a solid, trusted foundation so every phase of your transformation delivers the value you expect.

All we need is an export of your spare parts master data — typically a spreadsheet or CSV from your ERP or CMMS. There's no need for manual cleanup or technical prep beforehand. SPARROW.Clean is designed to handle raw, messy data and work with it directly. During the onboarding, we help you identify duplicates, structure key fields, and apply standard naming conventions based on your business needs. It's a quick way to gain visibility into data quality and start improving it without a heavy lift.

Spare parts data is often messy — names differ, formats vary, and duplicates slip through. SPARROW.Clean uses smart algorithms to analyse descriptions, classifications, and metadata across your dataset, catching duplicates even when the naming looks completely different. For example, it can recognise that “Siemens 6ES7136-6BA00-0CA0” and “Siem 6ES7136 6BAOO OCAO” are the same part. You’ll see everything in a clear, visual interface that highlights duplicates, missing fields, and anomalies. From there, you can merge, clean, or flag records for review. And because it supports multilingual data, it works seamlessly across global teams with different naming conventions.

You’ll usually start seeing results in just 2 to 4 weeks. We recommend beginning with one site, system, or business unit so you can prove value quickly. From there, it’s easy to scale step by step across additional plants. Because SPARROW is modular and doesn’t require heavy IT involvement, your teams can move fast and stay focused. This structured rollout gives you quick wins early on, while also building the foundation for sustainable improvements in spare parts management.

No, SPARROW.Clean can be used as a standalone tool right from the start. You simply upload your spare parts master data, and the system gets to work. Integration with your ERP or CMMS can come later if desired, but it’s not required for cleansing, deduplication, or standardisation. This makes it ideal for fast pilots or for cleaning legacy systems ahead of a larger digital transformation.

SPARROW.Clean includes built-in governance tools to help you maintain data quality over time. These include duplicate prevention alerts, rule-based validation, and periodic checks to identify outdated or incomplete records. You can assign roles and responsibilities for approving new parts, enforcing naming standards, and ensuring data hygiene across sites. With SPARROW in place, spare parts cleansing becomes an embedded process — not just a one-time fix.