How to calculate the business benefits of AIOps for your organization?

AIOps or Artificial Intelligence for IT operations is gaining more organizations’ attention as it helps in shifting ITOps from reactive to predictive. AIOps is becoming a need for businesses that manage complex IT environments. The ROI that you can achieve by implementing AIOps is comparatively high, but how you apply it to the business scenarios matter the most.

Based on the research conducted on fortune 2000 companies to understand how it can impact the IT environment, below are the five key areas which get benefited by AIOps.

Five key areas which drive most of the benefits by AIOps:

  • Improvement in IT productivity by reducing MTTR
  • Prevent outages by predicting P1 incidents
  • Automate manual and repetitive tasks
  • Enhance employees output by optimizing the capacity of IT teams
  • Reduce the usage of multiple on-premise solutions and outsourcing costs

By identifying where AIOps contribute the most to the ITOps, you can easily calculate the benefits. Based on the research conducted on digitally transformed organizations that have implemented ITSM and other digital monitoring tools with the following characteristics:

  • Employees around 1,500
  • 1,500 incidents for a month
  • About 4,000 server either virtual or physical
  • About 600 IT practitioners

With the above metrics, we can base our ROI calculation of AIOps. Below are some of the examples that can be applied to calculate the organization’s productivity.

  • Monthly incident volume
  • Percentage of incidents resolved due to log analysis
  • Estimated hours spent to resolve a single incident before AIOps implementation
  • Percentage of issue reduction effort due to AIOps
  • The efficiency of the IT incident process
  • Cost of false alerts

Consult with infrastructure automation experts to calculate ROI for your IT specifications.

 

Below are the business benefits of AIOps

  • Highly scalable: AIOps establish connections between the siloed data to provide actionable business insights.
  • Quick and effective data processing: Humans cannot process a huge volume of data, but AIOps can. The smart algorithms powered by ML and big data can derive insights from raw data sets.
  • Good decision making: AIOps leverage various algorithms like predictive data analysis, pattern matching, historical data analysis, and others. Thus AIOps can deliver data-driven responses to all incidents.
  • Effective digital transformation: AIOps help in detecting and reacting events in real-time by providing greater control over the business applications and IT infrastructure.
  • Effective business outcomes: AIOps increase the human capacity and puts the enterprise at the forefront of the technology revolution and continue to prove its worth in IT operations.            

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