Self-Service Vs Auto-Resolution – How Are These Different?

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Self-Service Vs Auto-Resolution – How Are These Different?
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Balancing Self Service with Auto-Resolution

IT infrastructure management has never gained such heightened proportions as it has in the Post-Covid world. Global remote working scenarios resorted to more than experimentations as the intensifying pressure on IT infrastructure to sync with ‘virtual’ management of employees, customers, and allied services demanded more streamlining of tools and efficiencies.

Building an interactive and robust digital infrastructure for both internal and external customers, a trend underway many years ago is now becoming the ‘new normal’. As reports get churned out on the feasibility and ‘must-have’ models on more responsive/automated IT service Service Desk, the buzz word is to get quick help or self-help when one needs it!

Self-service or Auto-resolution?

Self-service is an older construct that did not have the benefit of the latest technologies. However, Auto-resolution, the buzz-word today; leverages the latest technology in overcoming the main issues associated with self-service in achieving the tangible ‘Shift-left’.

While there are many implications and aspects of the new AI-powered Service Desk – let us focus on the key aspect of “Self-service” v/s “Auto-resolutions”.

An understanding of the broader perspective of the employee service Desk is therefore inevitable as it is at the cusp of a big revolution. This has been enabled by the timely confluence along with the advancement of multiple technologies such as:

  • Artificial Intelligence (AI) and the advancements in its natural language processing capabilities

  • Simplified process orchestration

  • Collaboration tools like MS Teams.

Self Service

In layman's terms, Self-service can be easily defined and most of us intuitively know this. Self-service implies offering employees’ tools and information to n find answers to their questions and have a better experience”.

In this context of self-service, the ‘employee’ or the ‘user’ is responsible for the following three primary actions:

  • Identifying their issues

  • Finding the right tool/information

  • Using the right tool/information to solve the problem

In the context of Service Desk, the following would qualify as examples of business-related self-service:

  • Password reset facility

  • Automated software installs

  • FAQs that will help employees perform self-service

Self-service challenges:

All of us in the service desk function have tried to initiate a “Self-service” initiative for the organization to “Shift left” at some point in time.

Undoubtedly, experience relies on integrating self-service portals as part of any Service Desk that offers greater benefits of providing self-help - whether it be resetting of passwords, resolving a printer issue, or unlocking an account - these offer assistance and guidance. In the context of IT, a Service Desk enables the business to a quicker turnaround of customer service efficiently.

But, many of these initiatives do not reach the level of success to create a significant difference and Why? According to a 2017-SDI study, the following obstacles disrupted these initiatives (parameters) from becoming successful.

While there are many ways to interpret any data, as per our assessment, there are two core themes as to why adopting self-service has failed and this is hidden in the above data representation.

The embedded anomalies:

  • Access: Despite the best of self-service tools available, if employees cannot find those, what good would those tools do? Who would benefit from them?

  • Handholding: We need handholding and it is that simple. We need help to be catered to us. Sometimes, we need “human expertise in the loop” or as a backup. Most previous self-service initiatives lacked the ability to provide this.

So, how is Auto-resolution different?

Companies are gradually incorporating the new wave of automated Helpdesk operations. The Auto-resolution construct is primarily based on the concept of a Virtual Assistant. There are 3 aspects that impact the Auto-resolution scenario.

Auto-Resolution works on a smart AI platform that:

  • Understands the issue and identifies the problem.

  • Finds the right follow-up steps needed to resolve the issue/issues.

  • Perform the necessary steps in closing the issue

  • Enable intervention of human experts (Subject matter experts)to resolve the issue/issues

The user is provided with the right level of handholding by the smart/digital platform and is guided effortlessly towards a resolution. Common evidence is seen in examples that are integral to business-related operations, such as with Smart Platforms:

  • Helping users to create a new ‘Team’s’ channel.

  • Giving access to the marketing database after mobilizing necessary approvals.

  • Resetting of password via chat mode (chat center or a bot )

  • Escalating a difficult application issue to L3 level expert.

Auto -resolution as the key:

Auto-resolution using AI is the new construct of a modern Service Desk. In this construct, users feel that they have real-time assistance and have to do less to get an issue resolved – and Service Desk Managers can focus their resources on their key priorities.

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