A global building-solutions company used Pearstop to unify asset data and predict failures, reducing maintenance costs by 20 % and improving service margins by up to 9 %.
“We’ve gone from reacting to predicting — and our clients feel the difference.” — Digital Transformation Lead, Global Building-Solutions Company
Be a winner – Roger Federer playing tennis. Copyright New York Times.
Once data is clean and connected, the real value emerges. Pearstop enables large technical-services providers to shift from reactive maintenance to predictive, data-driven asset management.
A multinational building-solutions company (>$1 billion revenue) operated across five regions with inconsistent asset data.
Asset Managers and Digital Transformation teams couldn’t identify recurring failures or predict replacement cycles.
The Commercial Director wanted to monetise data-based insights but lacked confidence in the numbers.
Pearstop unified datasets from multiple systems, linking asset types, maintenance histories, and fault records.
It identified high-failure models, suggested replacement timelines, and visualised reliability trends per site — all through one dashboard.
The project turned passive data into a live decision system, guiding both maintenance and client strategy.
20% reduction in maintenance costs through predictive scheduling and improved asset reliability.