Johannesburg, 15 Aug 2022
Spare a thought for the IT pro. It's convenient to say that technology is not only IT's problem, and on matters such as business buy-in and strategic alignment, that is absolutely the case. But technology performance, availability and troubleshooting are IT's problem. This dynamic reached a new level with digital transformation, and it's now setting an even higher mark as organisations figure out how to establish hybrid workplaces. These changes have knock-on effects that suck up IT resources and, if not addressed timeously, reduce employees' effectiveness.
There is no shortage of such disruptive experiences. A slow application or faulty laptop frequently gets in the way of flow and productivity. Routine IT tasks, such as configurations, patching or password reset, can significantly interrupt and hamper a productive workplace. And when these things happen, most people turn to IT for resolution.
Today's IT professionals are highly valuable contributors to their organisation's success. They establish and maintain the digital means that let companies operate faster, smarter and more efficiently. But as integrated digital systems become more elaborate, support requirements heap onto the shoulders of IT teams. Every support ticket requires some attention, yet doing so is not an effective use of IT professionals' time. And time lost on support calls means less focus on digital capabilities that make modern companies competitive.
AIOps is becoming a popular remedy for this situation, says Muhammed Omar, RSA Country Manager for ServiceNow: "AIOps is basically machine learning applied to the IT operations environment. You tend to get hundreds if not thousands of alerts a day. But do you know which ones are the most critical events that are going to have the highest business impact to your customers and employees – and that you need to prioritise? AIOps helps the business to really understand all the noise coming from events and logs, predict anomalies and identify root cause."
Self-healing IT
The appeal doesn't just end with managing alerts. Artificial intelligence and machine learning can help companies develop a concept called self-healing IT – remediating IT issues without human intervention. Self-healing IT stands on several building blocks, such as modernisation, automation and optimisation. Using AIOps, companies design and nurture a platform for a self-healing IT environment.
AIOps and self-healing IT have become very popular thanks to cloud-based service and process management platforms. Gartner estimates that 30% of large enterprises will use AIOps platforms this year. IDC predicts that an overwhelming 90% of large companies will use AIOps platforms within the next four years.
Omar isn't surprised that cloud-powered service platforms are at the heart of this revolution. They offer considerable advantages over traditional and legacy service applications: "The greatest difference is that past applications were fit for purpose, whereas a platform can serve many different purposes out of one instance, especially when you use integration and automation. They can standardise data into one format and source. This brings areas together that usually have their own data and reporting standards, such as service management and IT operations management. And if you're using a cloud platform, you can expect minor and major feature upgrades as part of your subscription. You don't have to pay for new features, even advanced ones like AI, and you don't have to run capex projects to bring in applications with fit for purpose features."
Three steps to effective AIOps
Service operations management platforms open the doors for new machine learning automation opportunities that self-learns when exposed to different service scenarios. For example, predictive intelligence can determine that Outlook-related errors should auto route and assign to the desktop support team, saving significant time and costs.
Since the leading platforms have established templates for common AI workflows, it doesn't take much to get started with AIOps and self-healing features. To get results fast and maintain their impact, Omar suggests three core stages.
First, consolidate your service management and IT operations processes, technology and data into a single platform: “That’s prerogative number one. You need to get the data in a single place and ensure the data is of a good quality. You can put all the AI and machine learning that you want on top of that data, but you’re not going to get true insights if your data is not of a good standard.”
Automation is second, and this is where the action happens – using AI-based automation, empowering employees with intuitive self-service, automating common requests to free up inundated agents and proactively preventing service issues. Start by getting the right work to the right teams faster with AI-fuelled incident routing, reducing manual triage effort and delays. Then use AI to push relevant content – such as knowledge base articles and similar incidents — to a single workspace, providing automated insights that help agents resolve issues faster and more accurately.
Once you have a solid foundation of data and processes, then the third phase is optimisation: "How do you improve the processes? How do you provide closed loop feedback? And how do you ensure that there's improvement within the organisation to deliver more with less and more effective processes?"
Using AI and machine learning to automate service and operations management reduces complexity and its reliance on human intervention. Best-of-breed service management platforms – those that use the cloud, standardise data, continually roll-out new features and provide comprehensive closed reporting loops – are making it much easier to build self-healing IT.
"Companies are not scared of AI and machine learning," says Omar. "The intent is to adopt AI and machine learning as much as possible to get to a point of hyper automation. But where many are stuck is where to start? What is the journey to maximise the capabilities of AI and machine learning? What are the quick wins and use cases that we could adopt to make things quicker, faster, more efficient and automate more? Platforms help answer those questions in a big way."
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