(Reading time: 6 - 11 minutes)

Quality - Using Voice of Customer (VOC) Analysis for improving Service Desk Process Efficiency

Voice of the Customer

Voice of the Customer (VOC)

VOC is a term used in Service Desk processes for capturing the customer feedback, expectations and preferences.

Employees in Service Desk processes directly engage with customers either over Phone, chat or email. VOC data for Service Desk processes are typically collected using customer surveys. The survey responses often hold a wealth of information in terms of suggestions and complaints under the comments or feedback section. These typically include key information around areas such as:

  • Unresolved Issues
    • Sample VOC: “The issue is closed, but the poorly written error message which prompted my opening in the first place isn't fixed and isn't likely to be fixed”.
    • Sample VOC: “I cannot believe this request was closed without resolution”.
  • Missing user confirmation on resolution
    • Sample VOC: “Two weeks of having requests for an update denied, and then agent closes the case with no response provided, or justification for closing”.
  • Premature closure of interaction
    • Sample VOC: “Service Request was closed because they did not hear from me between 9:30PM and 6AM”.
  • Asking repeatedly for same information
    • Sample VOC: “I was asked the same questions several times, even after providing answers and screenshots. It took over 2 weeks to get something resolved that could have been fixed in 1 day if the right analyst with the right knowledge addressed it”.

The above list grows as more VOC data is collected.

VOC Analysis is a technique that produces a detailed set of customers’ actual needs; analysis of VOC data results in a prioritized list of issues/ problems that need to be worked upon through specific targeted actions in order to improve customer satisfaction and process efficiency.

Let us look at a simple approach to carry out the VOC analysis of a Service Desk process

Step 1: Data Collection

– Collecting and filtering the VOC data:

  1. Retrieve a minimum of 3 months of all closed interactions data
  2. Collect all interactions where survey was sent
  3. Filter out the interactions where customer wrote suggestions or complaint in the comment and feedback section 

Step 2: Data Mining

– An analytical process designed to explore data in search of consistent observations and/or relationship between iterations, and then validate the findings by applying the detected observations. Following are the key categories along which the customer comments/ feedback are analyzed and bucketed as part of VOC analysis:

VOC analysis of Service Desk

Communication

Gaps

Technical

Gaps

Process

Gaps

Process Adherence

Gaps

Environment

Issues

People

Issues

Timely communication

Knowledge base (KB)

Process does not exist

Process exists but not followed

Product Issue

Human Errors

Quality of communication

Tacit knowledge

Process is inadequately defined

Inconsistencies in following the process

Tools Issue

Wrong inherited practices

Issue Comprehension

Non-uniform knowledge levels

 

 

External Factors

 

Missing user communication

Technical/Functional/Domain knowledge

 

 

 

 

 Detailed description of each category

Category I: Communication Gaps

Subcategory 1: Lack of timely communication: Failing to communicate to the updates to the user on a prior agreed timeline

Subcategory 2: Low quality of communication sent by service desk: Failing to communicate the latest update to the user or failing to communicate ineffectively (with spelling and grammatical errors)

Subcategory 3: Unable to comprehend user communication: Unable to understand user’s response

Subcategory 4: Missing user communication: Failing to reply to all questions/queries asked by user

Category II: Technical Gaps

Subcategory 1: Lack of knowledge base: Non-availability of a knowledge base article to help the team members in resolving/triaging an issue

Subcategory 2: Lack of Tacit knowledge: Process knowledge that is difficult to transfer to another person by means of documenting it or verbally telling it

Subcategory 3: Non-uniform knowledge levels: Inconsistency in resolving/triaging (using different approaches to resolve/triage) an issue by team members

Subcategory 4: Lack of technical/functional/domain knowledge: Lack of domain or techno-functional knowledge among team members

Category III: Process Gaps

Subcategory 1: Process does not exist: Process has not been defined for any particular state

Subcategory 2: Process is inadequately defined: Process has been defined but without considering all parameters

Category IV: Process Adherence Gaps

Subcategory 1: Process exists but not followed: Failure to follow an existing process by all team members

Subcategory 2: Inconsistencies in following the process: Failure to follow the existing process by some of the team members

Category V: Environment Issues

Subcategory 1: Product Issue – Issues with the product which is being supported by Service Desk

Subcategory 2: Tools Issue – Issues with tools with assist the Service Desk team to resolve the customer issues

Subcategory 3: External factors – Any external environmental factor contributing to the issue

Category VI: People Issues

Subcategory 1: Human Errors – Inadvertent misses by team members

Subcategory 2: Wrong inherited practices – Wrong practices carried over from another vendor/team/employee

Each VOC data sample now needs to be analyzed along the above mentioned categories and sub-categories. A single interaction could have multiple gaps because of which it led to customer dissatisfaction. In VOC analysis, we try to identify all possible gaps for a single interaction to build up a prioritized list.

Step 3: Data Modeling

– The analyzed data is collated in a structured format (based on the above mentioned categories) and used as the base information for assessing and designing a solution component (and related action items)for each actionable factor.

  1. Sum the occurrence of each issue
  2. Calculate the percentage of occurrence of each issue
  3. Rank each issue in order of their occurrence (Highest to Lowest)
  4. Look to develop the solution component of the most frequently occurring issues   first going up till the least frequently occurring issue 

Step 4: Developing Solution Component

– Once VOC analysis is completed, a prioritized list of gaps will be obtained to work upon and develop solution component for each of the identified gaps.

  1. Brainstorm and develop the solution component for each of the identified gap
  2. Identify the owner of each gap
  3. Identify the measurement guideline for each gap
  4. Identify the goal to reach
  5. Identify the control measure that will be put in place to plug all identified gaps
  6. Develop a Monitoring and Tracking mechanism and report the status of a pre-decided frequency (weekly or monthly) 

Similar articles

Chillzee Tag Cloud

About Chillzee

Chillzee.com is an entrepreneurship portal.

The site provides informative topics on Organizational and Strategic needs.