Transform your supply chain with intelligent, data-driven network planning.
Keeping critical machinery running requires a flawless parts network, but manual tracking makes this nearly impossible. Most asset-heavy companies struggle with a brutal choice: overspend millions on safety stock, or risk catastrophic downtime when a unique component isn't available.
Servigistics eliminates this gamble by automating your inventory planning. It is designed from the ground up for environments where equipment failure is not an option, allowing you to hit your strict service metrics without locking up vital working capital in dusty warehouse inventory.
Generic ERP tools and basic spreadsheets are built for predictable, forward-moving production lines - not the erratic, unpredictable world of maintenance and repairs. They rely on past sales averages, which leaves your planners completely blindsided when emergency shortages hit your local depots.
This platform completely changes how you look at supply chains. By running your operations through advanced data science and machine learning, it builds a dynamic digital map of your global parts network. This connects your central distribution centers with remote stocking points so you can stop reacting to crises and start preventing them.
Spare parts are notoriously difficult to predict because some components might sit on a shelf for months before a sudden spike occurs. Servigistics uses machine learning to look deeper than basic history, analysing equipment age, operating environments, and actual wear metrics to deliver highly accurate forecasts.
Instead of treating every warehouse like an isolated island, the platform manages your entire logistics footprint simultaneously. This multi-tiered strategy calculates exactly where to place stock globally to guarantee high availability while keeping handling costs and emergency courier fees as low as possible.
You can take the guesswork out of planning by feeding real-world asset data directly into your parts network. By tracking how many hours machines are actually running in the field, your team can spot upcoming maintenance waves early and position the right components long before an engineer is dispatched.
Parts requirements change dramatically from the moment a new machine is launched to decades later when it becomes legacy hardware. Servigistics simplifies this transition by analysing engineering updates, supersessions, and final-buy contracts so you can meet long-term agreements without over-purchasing.
Modern industrial businesses need to turn expensive logistics headaches into a clear financial advantage. Servigistics gives you the visibility needed to maximise asset uptime, improve service margins, and gain total clarity across your entire global parts footprint.
Standard business applications fall short when a single missing component can stall a client's multi-million-pound operation. Servigistics is engineered precisely for complex sectors like aerospace, defense, heavy manufacturing, and medical technology. It easily scales across massive dealer networks, giving you complete control over your investments.
When your parts availability matches up perfectly with your engineering schedules, your entire business runs better. Having the correct components ready for your technicians instantly boosts first-time fix success, slashes costly part backorders, and drives down the total cost to serve your clients.
ERP systems are great for manufacturing new products, but they struggle with the volatile, non-linear demand of repair parts. Servigistics uses specialised algorithms built specifically to handle the unpredictable nature of the aftermarket.
It is widely adopted in capital-intensive fields where equipment downtime causes severe financial or operational damage. Key sectors include aerospace, automotive, heavy machinery, high-tech, medical devices, and power utilities.
By looking at your entire network together rather than checking individual warehouses separately. It figures out the most strategic locations to hold stock, ensuring high service levels without requiring you to buy safety stock for every single branch.
Yes. The platform integrates with IoT networks to monitor real-world machine usage and operational data, allowing you to transition toward a predictive parts model based on actual equipment health.