Scenario 1 - Chris is having a rather unpleasant day at work. He needs to complete some important assignments, but his computer is running slow. Chris decides to call the service desk team. Once connected, he nervously navigates the rambling IVR system.
Scenario 2 – Julie is facing similar issues with her laptop. To address these issues, she accesses her organization’s unified portal powered by Natural Language Processing (NLP) and Artificial Intelligence (AI).
Integrated with Active Directory (AD), a chatbot recognizes Julie’s login and greets her once she logs in. The chatbot is also aware of the devices and applications she uses. Julie types her grievance in the chat interface as the conversation begins – “My computer is running...”
The chatbot’s AI and NLP algorithms immediately identify her complete sentence – "My computer is running slow”, and run the following checks and analysis:
- End-user experience monitoring tool
- Computer performance data
- End-user score
Once the analysis is complete, the chatbot diagnoses the problem and provides recommended actions. For Julie’s issue, the chatbot identifies and recommends cleaning up the disk space as a remedial action. The chatbot asks Julie if she’d want the bot to delete all the temporary files or help Julie in taking the steps to accomplish the task.
Additionally, as Julie requires IT peripheral devices, the chatbot places an order after providing her with options relevant to her work and profile. The chatbot then logs the delivery address, provides an estimated time of arrival (ETA) for the order, and furnishes a ticket for the order placed.
In the 2nd scenario, the chatbot is taking action. Depending on the use case and application, the bot is integrated with various enterprise systems and can accomplish multiple tasks ranging from applications for ordering computers and peripherals and booking meeting rooms to sending reminders for purchase orders.
The 2nd scenario has two key takeaways:
- The servicing of end-users in the digital age demands an approach rooted in technology (mainly automation and AI).
- Consumers' expectations are constantly evolving – customers are now seeking a phenomenal digital experience that includes recommendations and solutions at the click of a button.
Demand for a redesigned service desk model
Enterprises have grown exponentially, and so have the end-user expectations of customers in a B2C scenario and employees in a B2B scenario. Post pandemic, it is crucial for enterprises and organizations to transform the service desk, given that disruptions force organizations to revert to a hybrid model of working. Service desks should no longer be viewed as support functions — in the event of disruptions across services, they are the first line of contact between the employee and customer, and the organization.
Reimagined service desk model
Intelligent knowledge-based repository
Every time a familiar query arises, Service desk agents spend time trying to retrieve the resolution. And even if the problem remains the same, its resolution may differ every time depending on the situation. As a new generation of employees is more likely to carry out self-service regarding routine IT issues, creating an intelligent knowledge repository would reduce the need for repetitive and resolvable service desk tickets.
Social and collaborative peer support
It is imperative that the service desk is integrated across enterprise social media platforms. Peer support is the most frequently used support across B2C and B2B channels. For example, customers first read reviews and then study the features of a product before buying it. Similarly, employees first connect with peers for resolutions and then with the service desks. Hence, the social platform should integrate chatbots and service-desk agents, as it would decrease the resolution time for tickets from days to a few hours.
Catering to hybrid work with the cloud
Hybrid work with work-from-home is the new norm across organizations — employees could be at home, in the office, or at a remote location. Similarly, service desk agents may need to work from home in case of an emergency or lockdown to meet shifting location expectations, improve productivity, and foster innovation.
Businesses also need to deploy service desks in the cloud and establish multiple communication channels. For example, the service desk on the cloud would enable employees to register their tickets with a one-touch service on the smartphone. At the same time, agents would receive cloud and mobile-based service desk tickets on the go. In addition, the cloud and mobile set-up would provide ready maintenance and resolutions across the help desk from anywhere.
Evolution of XLAs
To facilitate holistic change across service desks, including change within service desk agents, the service level agreement (SLAs) of service desks need to be reimagined and replaced with experience level agreements (XLAs). XLAs focus on what is most important to the end-user or end-user-centric metrics that focus on the user satisfaction.
SLAs focus on operations, volume of tickets addressed, and overall resolution output. With these new metrics, agents would be more focused on the quality of support, the resolution, and ultimately, how the resolution impacts the employee or end-user.
Intelligent service desk (AI, Predictive Analytics, and automation)
The transition of the service desk to AI and automation needs to be accelerated. Service desk organizations will be able to provide predictive resolutions by identifying workforce needs, studying device issues, and analyzing data.
AI-powered predictive intelligent algorithms installed across systems would provide intelligent recommendations before the occurrence of the issue. Predictive support could be pushed to employees and end-users through human agents at regular intervals – and would be a proactive intervention. AI would reduce the service desk response time from a few hours to a few minutes, or in no time, in case of preemptive resolutions, and provide almost 24/7 support to service issues.
Implementation of a service desk covering the features of a reimagined service desk model would bring about incremental change to the current help desk set-up. This implementation, in the long run, would facilitate change across numerous channels by driving:
- One-click actions or responses
- Consistent responses to similar queries
- Removal of language and location barriers to resolving issues
- Reduction of high-wait time
An incremental approach to this transformation would address capital constraints while implementing and overhauling the service desk. As a result, the reimagined service desk of the future would soon be a reality rather than a pipe dream.