How a Semantic Analytics Solution Can Improve IT Operations

By: Redha Bournas|Co-written by: Sandipan Dutta - Leave a comment

Maintaining a healthy IT operations environment, reducing operational costs and improving customer satisfaction are the fundamental priorities of IT managers responsible for delivery and operations. That’s why it’s critical for organizations to gain a deeper understanding of the pervasive issues that are potentially disrupting the stability of their IT environment and leading to increased operational costs.

In the IT operations environment, the life cycles of incident, problem and change tickets, as well as work requests, are managed through a service desk tool. The categorical and unstructured fields of service desk tickets contain detailed information about the reported issues, their resolutions, agent assignments, assets impacted by the problem and other data points.

If organizations can correctly analyze and correlate this information, it can provide them valuable insights about the most pervasive issues, their causes and the emerging trends. It can also reveal the work efficiency of service desk agents, as well as other data that can help improve the stability and reduce the cost of service desk operations.

How a Semantics-Based Solution Can Help

Historically, traditional analytics tools that analyze the structured or categorical fields of tickets have been unable to provide a deep understanding of IT environment issues, mainly due to insufficient ticket categorization and a lack of robust information. However, unstructured fields of the tickets — such as incident description, resolution description and comments — contain pertinent and more detailed information about the prevailing issues and their root causes.

A large portion of business-relevant information originates in unstructured form, primarily as text. This is where a semantics-based text analytics solution can make a significant difference: It can analyze the unstructured, descriptive text of the tickets and derive useful insights. By using efficient text analytics algorithms, a semantic analytics solution can shed valuable light on the most pervasive issues, their contributing causes and other aspects of IT operations.

By continually deploying this tool and implementing actions based on its insights, organizations can reduce operational costs and maintain a healthy IT environment. A semantic analytics solution can also analyze data from customer satisfaction surveys and social media platforms that contain customers’ or end users’ comments. By correlating these sentiments with prevailing issues in the IT environment, companies can better understand how to improve customer satisfaction.

Key Benefits for IT Operations

Some of the primary benefits of using a semantic analytics solution for the service desk environment include:

  • Deriving actionable insights about the most pervasive issues, so the organization can take preventative actions to reduce the number of help desk tickets and improve resolution times.
  • Correlating incident and change tickets in order to detect emerging trends due to erroneous changes.
  • Predictive analytics that can identify the best-skilled agents to resolve first-time call failures and attain service-level agreement targets by selective reprioritization of incident tickets.
  • Identifying the entities — such as servers, devices, printers, applications and other configuration items — that are most frequently extracted from the unstructured text.
  • Eliminating unproductive work by diagnosing infrastructure events that are either false positives or related to the same root cause.
  • Improving customer satisfaction and eliminating any future causes of user frustration by analyzing social media and customer survey data.

Using state-of-the-art research and development work from the combined efforts of IBM Research Labs in Zurich, Yorktown and India, IBM is making strides in developing and offering an effective semantic IT operations analytics solution to its clients in order to optimize the health of their IT environments. To join the conversation about this new tool, connect with Dr. Redha Bournas and Sandipan Dutta.

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About The Author

Redha Bournas

E2E Analytics Solution Architect & Analytics Optimization Lead - PhD; Master Inventor, IBM Global Technology Services

Redha Bournas is an Analytics architect in GTS involved in numerous client engagements with key focus on semantic (unstructured text) analytics, a key ingredient for data feeds into Watson cognitive systems. Prior to his current role, Redha was a Simulation architect in GTS for three years optimizing the staffing levels of ticketing system pools worldwide in order to reduce IBM Help Desk operational costs.