Cummins Helps Mines Avoid Expensive Downtime with Innovative Remote Monitoring
Accurate forecasts for
incoming alert volumes
incoming alert volumes
Assurance “immediate” alerts
are handled promptly
are handled promptly
A differentiated service for
tangible customer benefits
tangible customer benefits
Ability to help customers increase uptime,
saving one customer $600,000
saving one customer $600,000
At a Glance
Company Cummins
Industry Industrials
Region Global
Products Used Calabrio ONE Suite
About Cummins
Founded more than 100 years ago, Cummins Inc. creates the engine solutions people depend on. With 2020 sales of $19.8 billion and 14 consecutive years on Ethisphere World’s Most Ethical Companies list, more than 58,000 Cummins employees and thousands of dealers worldwide remain committed to powering a more prosperous world through education, environment and equality of opportunity.
Forecasting helps ensure enough agents are available to triage incoming alerts about truck engine issues
Challenge
In mining, engine failures can cost owners up to $1 million per day. Still, busy drivers often ignore engine system warnings until it’s too late, and the truck engine fails completely.
To help mining customers increase uptime and profitability, Cummins Inc. offers an innovative maintenance service that remotely monitors customer truck engines as they operate in-field. The service’s internal diagnostics proactively monitors each engine’s fault information and live engine data, then sends alerts to customer support agents who triage the data and identify those alerts requiring immediate intervention. In this way, customers can learn about and fix potential issues before they have a chance to erupt into major problems.
But ensuring all “Immediate” alerts would be handled properly and promptly proved to be a challenge. Cummins customer support leaders had to find an accurate way to forecast exactly how many agents needed to be available to receive and disposition alerts at any given time.
Solution
The remote monitoring team at Cummins paired the cloud-based Calabrio Workforce Management (WFM) with the company’s existing Cisco phone system, then deployed the integrated forecasting solution across more than 450 agents in two countries to start.
Now, planners use Calabrio to build accurate, unique forecasting models for each new customer site based upon a variety of both historical and real-time criteria. They can even customize their Calabrio forecasts according to nuances for each site—such as the number of alerts typically received for the particular engine types used there; the number of older, more problematic engines used there; or the customers geographic location.
Calabrio WFM gives us the powerful forecasting we need to ensure we always have enough agents on hand to review and process the critical alerts sent from the truck engines working at mining sites around the world.”
John Weippert –
Global Customer Support Systems Manager
Cummins
Result
With Calabrio, Cummins leaders can accurately forecast incoming alerts, so agents can fulfill the promise made by the company’s innovative remote monitoring service. And the results are incredibly tangible.
Thanks to remote monitoring, one customer site was finally able to diagnose an issue with a specific engine family that had caused problems for three years. This feat—combined with the pinpointing of a problem that would have cost much more to repair if it had been allowed to reach the point of complete failure—created a massive, positive ripple effect: the customer saved $600,000 and recouped 150 hours of downtime. Overall, Cummins reduced response time to all customers by nine minutes and were able to add more customers sites to their monitoring program without having to add more staff.
Cummins’ remote monitoring service proved so successful, its team of agents will now remotely monitor all customer mine sites around the world—24 hours per day, seven days per week, 365 days per year.
Listen to John Weippert from Cummins about “Forecasting for Gigantic Engines” on Calabrio’s Podcast here.
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