Automate And Optimise – Don’t Stagnate And Minimise
There is much current debate around how the working world has changed so radically in the last few months, with various opinions on what this means for the future. Of course, we have actually been discussing this for some time, particularly in the light of technology developments – like AI and robotics – as well as changes in how we work – using agile and other ‘new’ enlightened approaches.
The consensus of course is that things will never be the same again – we won’t go back to the way we were before. I agree totally – we are constantly evolving in how we work and how we use technology. The global crisis has certainly accelerated a lot of changes quickly, and at the same time opened up the debate about the value of change. We should always be looking at how to improve, progress, and deliver new things, and get better, faster, cheaper at delivering BAU – business as usual.
In the world of IT support, service management, and service delivery, there are many opportunities available using automation and AI (Artificial Intelligence). AI does not imply ‘real’ intelligence, like our human brainpower. There are some things that technology can deliver better than we can, although the majority of our intelligence will still take many years to replicate. There are many great opportunities to remove repetitive, error-prone, and thankless tasks from human delivery – to then free up people to do more creative, interesting and ‘real intelligence’-based work.
We should view these now as massive shift-changing opportunities to develop using AI, much more than just enabling people to work from home or to work remotely.
Automation and AI provide us with the keys to a whole new world of work. One of the 7 ITIL4 Guiding Principles is ‘Optimise and Automate’– a clear mandate to improve and use automation to support optimisation and CSI wherever possible.
Let’s take a look at areas where AI can support and improve how we deliver IT Services.
AI and Automation – Opportunities.
Here some core ITSM areas where AI can provide value to ITSM delivery:
1. Knowledge Management
Organisations often maintain large amounts of unstructured data – AI can use machine learning and natural language processing to identify patterns and drive some insights from this to auto-create knowledge articles – for IT people or to customers through self-service.
2. Service Desk
AI system can provide a number of automated responses and interactions using natural language processing – either to resolve simple issues automatically, or quickly triage and escalate more complex issues. This can be cost-effective as well as a fast and efficient way to manage standard transactions – it can also be provided 24×7.
3. Incident Management
AI can be used to manage and speed up the process of categorization, prioritization, and escalation – triage. AI can also recognise commonly occurring incidents through pattern recognition and raise a problem or major incident before this may be raised by a person. In large organisations AI is also useful as part of the optimization of teams and shifts to provide flexible support.
4. Request Fulfilment
AI is really useful to provide 24 x 7 simple fulfillment of simple requests – password resets, software distribution, simple configuration changes. AI also helps to automate workflow, approvals, and fulfillment of a variety of requests.
5. Problem Management
With machine learning and data analysis, AI can analyze patterns, identify and categorise future problems and escalate issues and alerts to people automatically. AI systems can also applying relevant fixes and automate workarounds and carry out automated impact and dependency analysis across systems.
6. Reporting and data analytics
Predictive analytics can be used by organizations to improve management decision-making, using data modeling, machine learning as well as existing data modeling methods. Applying intelligent analytics across all channels of support helps to drive a holistic approach to service improvement.
AI and Automation – the challenges
First and foremost – be clear on the goals and expected outcomes of any planned automation that can deliver a lot of benefits, but these may not be realised if there is a lack of clarity on what you are trying to achieve. Set out clear targets for what the automation will deliver to the operation and your business users.
It’s also vital to communicate and consult with your users/customers on this – certainly well before launching any major change to service. If it goes wrong in the short term, you need people on board. It may also work but need to be sold to users before they are hit with it. Testing is key – don’t skimp on it.
Data and process readiness preparation are also essential – i.e. its important to ensure that any data or processes that are being automated are accurate and relevant. There’s no point in automating broken processes or inaccurate systems.
A big challenge is also around people – people need to feel comfortable and confident that the technology is not simply going to replace them – organisational change management is needed to support them. They also need to learn new skills around how to make AI work. Business leaders and decision-makers also need to be clear on the value proposition of what AI will bring, and what is involved in terms of investment in funds and human resources to make this work.
let’s optimise and automate what we do as much as possible – in reality using technology to deliver really effective CSI. Stagnation is not an option and recent events have proved that the world can change very quickly – if we view this through a minimised lens and resist automation, we will not be able to compete and cope effectively and efficiently with further change.
I’m looking forward to presenting more on this topic and discussing these ideas with an industry panel on 11th August. SAVE YOUR SEAT!
Blog cover design by Shriram Sivakumar
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