The Automation imperative – “Do More from Less”
COVID-19 has contributed to the slowing down / contracting of all major economies and businesses. In such a business climate, organizations are focusing their efforts on improving bottom line performance. All support functions, especially internal IT function, are expected to reduce costs, drive-up productivity, and efficiency. In short, the name of the game is “Do More from Less”.
Automation opportunities in IT
Hyper-automation (or automation across all tasks/processes within an organization) is one of the top technology trends influencing business strategies world over. Businesses are increasingly looking at automating processes that are standardized, repeatable, rules driven and manually intensive. Many back-office operations in the enterprise functions of HR, Finance and IT across industry verticals are ripe candidates for automation.
CIOs have been at the forefront of leveraging IT tools to manage various aspects of IT service management. ITSM tools like Manage Engine, Service Now and more have helped the IT service desk to manage and track all the service tickets in a systematically. This has also brought in some productivity gains by ensuring prioritization of tickets, allocating tickets to service desk members based on skill and availability, tracking and reporting SLAs and more. However, they have not done much to automate the ticket’s resolution – which are still performed manually.
One of the high impact automation ideas in IT end-user support is to automate the L1 ticket resolution end-to-end for IT service desks. This solution, Intelligent Service Desk, is built by interconnecting three tools –
- Chatbots that are trained in L1 ticket related intents and utterances that will provide either self-help related solutions to end-users or trigger BOTs/scripts to automate the ticket resolution
- ITSM tools that have configured service catalogs, CMDB, incident/service management SOPs etc. to manage all the L1-L3 IT service support and
- RPA tools that can perform the necessary workflows for executing standardize, repeatable rule-based service resolutions that involve other IT systems in the organization
As an illustration, a typical password reset would have taken > 8 minutes for a traditional service desk to resolve, would now take < 2 minutes for an intelligent service desk to resolve.
Using Intelligent Service Desk, password reset requests resolved immediately with better user experience.
The use cases for L1 service/incidents requests are many and listed in the chart below.
Happiest Minds’ approach to automation
At Happiest Minds, we follow a standard 3 step approach to implement automation.
e.g., implementing the Intelligent Service Desk would comprise the following three steps –
- Opportunity assessment – To assess the current ITSM landscape – tools, processes platforms and others. – in the organization and identify the automation potential. The deliverable would typically include identifying the L1 tickets that are automatable and the implementation roadmap.
- PoC solution build-out – To set up solution’s components– chatbot, ITSM tool and RPA tool and test out the automation for two L1 ticket use cases.
- Expand Solution use cases – To extend the PoC solution to a production environment and continuously develop and implement additional L1 use cases.
By implementing such an Intelligent Service Desk, organizations are expected to improve their end-user experience, improve service desk staff productivity, and enhance the IT service desk efficiency by at least 20%. With this, CIOs can quickly achieve the strategic objectives of “Doing More from Less” in their IT end-user support setup.
Senior Vice President and Head of CoE, Digital Process Automation at Happiest Minds Technologies, comes with over 23+ years of experience across Business Consulting, Analytics and Automation. He has worked as a consultant in Operations Transformation, IT Strategy, Outsourcing and has led the Global Analytics capability in the areas like Risk Analytics, Marketing Analytics and Supply Chain Analytics.
Sundar studied Computer Science & Engineering at IIT Delhi and is a gold medalist in Marketing & Finance from XLRI Jamshedpur.
