In the past year and a half, TransUnion’s IT staff has collaborated with its data science team to develop advanced machine learning algorithms to spot performance issues and predict outages, allowing the IT team to troubleshoot and remediate before downtime occurs.
They used Machine Learning Toolkit from Splunk to develop the models, and over time they’ve gone from predicting outages one hour in advance to six hours in advance.
“We are using hundreds of millions of events as a training data set to look for minute fluctuations in application and systems health, and when the model sees those fluctuations, we can alert the appropriate teams,” Bailey says. “Instead of having a full-blown outage, we can take action much earlier, so it becomes a business-as-usual exercise instead of a fire drill.”
It’s a highly predictive model that can even tell IT administrators what days of the week and during which hours the company is most likely to encounter a problem, Dhar says. TransUnion has successfully implemented it in some business systems and is currently rolling it out across the enterprise, he says.
How Machine Learning Can Power Smarter Marketing
While AI is a powerful ally for ensuring continuity in IT operations, its analytical power can be harnessed to inform decision-making within every part of a business. Recognizing the potential, TransUnion is expanding its AI program beyond outages — building machine learning algorithms to deliver more business and operational insight to every business unit. “Anywhere we can bring value, we are looking to do it,” Dhar says.
Smaller companies are taking advantage of AI too. Apparel manufacturer Buffalo Jeans wanted to boost its online sales, so in 2016, it deployed several AI-powered IBM marketing applications to better understand its customers and send more relevant, highly targeted email marketing offers to them.