In the world of service management, analytics will continue to be a driving force in decision-making in 2020. Artificial intelligence (AI), automation, and analytics are redefining the way IT service management (ITSM) is done and the role it plays in a business. In its Predictions 2020 report, Forrester wrote of automation and AI as moving “deeper into the organization, closer to the customer, and, more profoundly, into the very makeup and operations of the company.”
In fact, Forrester predicts that in 2020, CIOs will look within their own organization for efficiency gains, automating 10% of their IT tasks that are highly standardized and repetitive. As IT team members are freed from mundane work, CIOs will prepare them for more complex and business-focused tasks.
In this article, I’ll look specifically at how not just analytics, but predictive analytics will continue to grow in importance, impacting ITSM and how organizations conduct business.Here @a_sahai takes a look at how not just analytics, but predictive analytics will continue to grow in importance, impacting #ITSM & how organizations conduct business. Click To Tweet
Not Just Big Data, But Massive Data
In 2017, it was estimated that by this year, 2020, 1.7 megabytes of data would be created every second for every person on earth. Currently, over 2.5 quintillion bytes of data are created every single day. That’s not just big data – it’s massive data. However impressive these figures may be, though, they don’t guarantee value.
The full power of data is often underused because humans alone cannot possibly manage or fully make use of the massive amounts of data being generated every day. According to Forrester’s 2020 Predictions report, “While interest in big data has waned over the last couple years, enterprise data strategy continues to be a top initiative for executives. It’s critical in unlocking a firm’s digital transformation — and necessary to take advantage of AI and machine learning. 2020 will be a wake-up year for many firms, as the total cost of getting data wrong will become apparent.”In 2017, it was estimated that by 2020, 1.7 megabytes of data would be created every second for every person on earth. Currently, over 2.5 quintillion bytes of data are created every single day! Click To Tweet
Coupling Analytics with Automation
Because “getting it wrong” can be so expensive for companies, predictive analytics in particular is becoming more appealing. Analytics in general and predictive analytics in specific may use statistics, AI, data mining, and other techniques to predict future outcomes. This enables organizations to effectively interpret their mounds of data and make more informed business decisions. It’s no wonder, then, that the adoption of predictive analytics is growing. In 2018, the global market was projected to reach about $10.95 billion by 2022, growing at a CAGR of around 21% between 2016 and 2022.
Automation and AI/analytics are complementary – one provides insights, and the other delivers action. An April 2019 report by EMA, focused on AI/analytics in ITSM, found that 84% of respondents said the combination of automation and AI/analytics was a high-to-extremely high priority. And organizations that allowed automated actions to be driven directly from AI/analytics insights reported such benefits as savings across all of IT, improved IT Ops efficiency, and faster incident and problem resolution.
This new focus is really about how organizations can do more with the data that’s already in their ITSM and IT operations systems and how they can use it to aid in decision-making, in terms of associating the data as well as basic inferencing and predicting. For instance, one of the holy grails of ITSM is automated resolution of incidents. Though the industry may not be completely ready for it yet, the process can be aided by AI such that human decision-making is better informed.With predictive analytics, organizations can begin to make short-, mid-, and long-term goals with greater insight, says @A_sahai #AI #Automation Click To Tweet
With predictive analytics, organizations can begin to make short-, mid-, and long-term goals with greater insight. When it comes to decisions about business processes, they can use this insight to determine which ones to automate. For instance, an organization could automate some of the work in the service desk and the network operations center (NOC), which will reduce operations costs. This approach is applicable to enterprise service management, mobility, IT Ops, and, of course, ITSM.
The Name of the Game: Predictive Analytics
As companies compete for market share in the digital landscape, business speeds up and the data avalanche grows exponentially. This data holds enormous potential for greater efficiency, higher customer satisfaction, and more informed decisions that drive business goals. However, much of the data that organizations currently have is going unused because there’s just too much of it and too few trained data analysts to mine its riches.
Predictive analytics is growing in popularity as a way to wrangle all that data into usable forms that improve business processes and decision-making. In combination with automation, predictive analytics helps to usher in a new era of greater productivity and possibility in ITSM and other IT management areas.