How Machine Learning Can Transform IT Services?

What is Digital Labor?

You can’t ignore — Technologies like Cloud computing, Internet of Things, Big Data, Artificial Intelligence and Machine Learning are creating a new kind of labor system; called Digital Labor

With cognitive platforms available now, it is feasible for the machine to learn and understand the meaning of what’s going around. Every industry is disrupted by these emerging technologies, and more and more companies are experimenting with cognitive computing and automation platforms

There is no doubt that this is another industrial revolution. Many tasks we perform today will be taken up by Digital Labor.

How Machine Learning Can Transform IT Services?

Machine Learning can significantly transform IT services, but have some objectives before you hit the road -as Machine Learning is not some magic you apply and get benefits out of it.

  • Collect, analyze and predict information across the network, and use information to predict IT lag.
  • Reduce SLA violations by assigning tickets to SMEs who have handled similar tickets
  • Contextualize multiple issues and make most relevant operation staff see a list root causes and impacts and auto-initiate a virtual war room
  • Use ticket text classification to create a model and use sample to further train the model
  • Predict IT service delivery cost by predicting volume change and activities efforts
  • Balance resources, work flexibility and IT service performance
  • Knowledge article can be saved automatically
  • Make IT team to focus on workflow rather than individual alerts
  • Automated analysis of security data, understanding user behavior, giving them risk score and step-up their authentication based on sudden change in their behavior

Gartner says,

It’s time to take advantage of these technologies at the IT service desk to support the proactive, personal and dynamic needs of the digital workplace.

How Machine Learning Complements Your Current IT Tools?

Machine learning techniques can complement your current monitoring tools, providing root-cause analysis and real-time detection of any anomaly.

The volume of IT telemetry (events, alerts, traps, messages) can be huge and overwhelming. With the assistance of machine learning, however, your IT production operations staff can make immediate sense of the potentially thousands of events generated across the environment. The ability to quickly see the signal from the noise, as well as to understand how the events are all related to a couple of situations, is known as IT situational awareness — something that all IT teams are looking to improve upon. Source

Example 1:

Service Desk tools like Zendesk, Desk.com uses machine learning and semantic analysis to automatically tag incoming tickets so that you can deal with similar tickets in badges

Zendesk is one of the first customer service platforms implementing machine learning to natively auto-respond to customer tickets with relevant knowledge base articles, helping solve and deflect customer inquiries before they ever reach an agent.

Example 2:

Atlassian introduced smart graph to their JIRA Service Desk, a hybrid algorithm that combines keyword search and machine learning to provide better search results.

Smart graph does away with playing the guessing game. By optimizing real interactions and machine learning to translate between IT forms and common lingo — your customers are happy campers

But, Don’t Forget These:

Performance of such tools varies based on the machine learning algorithms used, ranking methods, quality of datasets and training models

Have some goals before you implement Machine Learning tools in your IT operations.

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