Service Express’ OnDeck™ Uses Machine Learning to Predict Data Center Hardware Failures
March 5, 2019
Grand Rapids, MI –
Service Express, a leading third-party maintenance (TPM) provider, has debuted OnDeck™, their proprietary parts sparing system. With OnDeck Predictive Sparing, Service Express identifies and stocks the parts needed for repairs, resulting in more uptime for their customers’ data centers.
OnDeck uses a comprehensive algorithm built on machine learning to identify all usage trends from over a decade of parts data. Updates run in real time, so changes in parts usage are identified immediately. The system responds by making transfers, setting new reorder points, or adjusting local inventory so customers have the part they need before they actually need it.
Using this system, Service Express maintains a 94% first-trip repair rate and ensures that every part needed is stocked in local offices before equipment fails.
“OnDeck Predictive Sparing allows us to be proactive about our support instead of reacting to every data center outage,” says Service Express Chief Technology Officer and OnDeck creator Jake Blough. “Being able to predict future data center failure scenarios gives our customers confidence that we’ll have the right part available when they need it no matter what time or day that is.”
To set customers up for success, Service Express engineers complete a full equipment audit for every new data center, collecting the configuration information to connect to OnDeck. The system runs 24/7/365 for the most up-to-date view of parts usage by the server, storage and network equipment of the primary OEM brands, such as HPE, IBM, Dell EMC and more.
With the effectiveness of this predictive sparing model, Service Express is able to pass savings to customers with better service.
For more information on how Service Express takes the guesswork from parts usage and sparing with OnDeck Predictive Sparing, visit serviceexpress.com/why-service-express/partsedge/ondeck/.