Clients, whether Internal or External, expect their products and services to be available when they need them. Any disruptions in the form of unplanned interruptions or degraded performance, can have a significant impact in the ability of the Users to conduct their business and have a negative impact on the business performance in the form of impacted revenues, profits, and customer/employee satisfaction. The Client Experience Analysis process aims to establish a mechanism where data can be harvested to identify factors that have both a positive and negative impact on the Client Experience.
The Objective of The Process:
The Objective of the Client Experience Analysis process is to understand, manage, and improve the overall client experience by maintaining focus on the top six areas that provide the greatest insights: 1 – Customer Satisfaction, 2 – Customer Escalations, 3 – First Call Resolution rates at the Service Desk, 4 - Ticket Backlogs, 5 - MTTR, and 6 - Employee Experience.
Understand all elements are the Customer Satisfaction surveys are comprised of 1 – Incoming Volumes, Surveys Sent, Surveys Received, Comments of Satisfied Users, Comments of Unsatisfied Users, Personas of the Users, Personas Of the Technical Teams, Types of issues contributing to Sat/Dissat surveys, etc.
Understand all the escalations from a quantitative and qualitative standpoint.
Understand the Service Desk efficiency rates
Understand the impact of Response/Resolve Times (MTTR) on Customer Satisfaction
Understand the impact of Ticket Backlogs on Customer Satisfaction
Understand the impact of Employee Experience on Customer Satisfaction
Sample List of Benefits:
Improved survey response rates
Improved satisfaction scores and reduced dissatisfied scores
Reduced escalations
Improved response/resolve times to escalations
Improve First Time Fix rates at the service desk
Improved Employee Experience
Sample List of Observations:
Impact of Backlog on CSAT scores
Lower survey return rates
Lack of responsiveness from the Technical Teams to dissatisfied comments
Lack of actions being taken from the Technical Teams to address chronic reasons for dissatisfied surveys
Delayed response to escalations
Lack of action on escalations
Lack of understanding and addressing of chronic issues contributing to the escalations
Lack of process compliance at the Service Desk leading to missed First Time Fix opportunities
Issues with Skills at the Service Desk
Issues with Knowledge Management at the Service Desk
Issues with Quality Management at the Service Desk
Issues with Service Desk Line Management systems
Sample List of Areas to Probe (Customer Satisfaction):
What is the monthly incident volume? PBA
What is the monthly survey count (sent)? PBA
What is the monthly survey count (received)? PBA
What is the industry baseline for surveys received?
What percentage do surveys represent of the total volume?
What is the monthly breakdown of Sat and Dissat surveys? PBA
How many dissats have comments?
What is the quality of the dissat comments?
Conduct sensitivity analysis of the dissat comments to detect any signals.
Plot the dissats across a PBA time series and see if any patterns exist?
Are the dissats confined to a time of hour
Are the dissats confined to a time of day
Are the dissats confined to a day of the week
Are the dissats confined to a week of the month
Are the dissats confined to a time of quarter
Are the dissats confined to a month of the year
Check if the dissats are for the survey sent or is the user referring to something else. Waiver.
Check if the dissats are for child tickets. Waiver.
What RCA categories do the dissats fall into? PARETO
Which towers are generating the dissats and what are the dissat categories?
Which assignment groups are generating the dissats and what are the dissat categories?
Which agents are generating the dissats and what are the dissat categories?
What types of tickets (Category/Subcategory/Requested Item) are generating the dissats?
Which users/business units/organization/location/country are generating the dissats?
Which type of users (Standard/VIP) are generating dissats?
What percentage do escalations represent of the total volume?
What is the monthly breakdown of Uplift and Overdue escalations?
How many escalations have comments?
What is the quality of the escalation comments?
Conduct sensitivity analysis of the escalation comments to detect any signals.
Plot the escalations across a PBA time series and see if any patterns exist?
Are the escalations confined to a time of hour
Are the escalations confined to a time of day
Are the escalations confined to a day of the week
Are the escalations confined to a week of the month
Are the escalations confined to a time of quarter
Are the escalations confined to a month of the year
What RCA categories do the escalations fall into? PARETO
Which towers are generating the escalations and what are the escalations categories?
Which assignment groups are generating the escalations and what are the escalations categories?
Which agents are generating the escalations and what are the escalations categories?
What types of tickets (Category/Subcategory/Requested Item) are generating the escalations?
Which users/business units/organization/location/country are generating the escalations?
Which type of users (Standard/VIP) are generating escalations?
Sample List of Areas to Probe (MTTR):
https://www.jnanaipc.com/blogs/mttr
Collect and review the MTTR YTD performance with Opened and Resolved/Closed flow rates
Identify any patterns, signals, anomalies
Identify if there are issues with MIO skills, capability, and capacity
Identify if there are issues with response times
Identify if there are issues with restoration times
Identify if there are issues with coordination on MIO bridge calls
Identify if there are skills and capabilities issues
Identify if there are capacity issue
Identify if there are issues with vendor engagement
Identify if there are issues with L2/L3 engagement
Identify if there are issues with recovery procedures
Identify which teams have contributed to higher MTTR
Identify which agents are contributing to higher MTTR
Identify which Applications/Infra components are contributing to MTTR
Identify via a time series analysis of MTTR varies by time of day, day of week, week of the month, month of the year
Identify if MTTR is impacted if issues span multiple teams
Identify if MTTR varies on repeat/chronic issues
Identify if there are issues with monitoring and alerting
Identify if there are issues with event management
Sample List of Areas to Probe (Ticket Backlogs):
https://www.jnanaipc.com/blogs/ticket-backlogs
Compare overall Backlog count to the Healthy Backlog target that has been set and determine if the current backlog is healthy or unhealthy? To determine the healthy target, factor in, incoming volumes, resolution SLAs, typical SLA hold usage, 3 strike policy, etc.
Compare current backlog to previous week backlog count and determine % increase/decrease.
Explain the root cause of any variance.
Have overall counts changed?
Have counts in various buckets changed due to work being done or lack of work and tickets are shifting to the right? (30 days to 60 days to 120 days, etc.)
Review distribution of aging tickets across a by-week timeline to identify severely aged tickets. Explain the aged tickets.
Review aged tickets by Incident State and Days Aging and compare current week against previous week to identify shifts in age groups.
Review aged tickets by Incident State and Days Aging to identify the distribution of aged tickets by state and days aging. Identify oldest groups and explain why.
Review aged tickets by Incident State and Last Update date (by week) to identify which tickets have not been updated in a timely manner.
Review aged tickets by Incident State, Days Aging and Escalation Type to identify if Users are escalation aged tickets.
Review aged tickets by Incident State Reason and Days Aging to identify reasons for why backlog tickets are on SLA Hold.
Review aged tickets by category and days aging to identify and anomalies. Drill down by looking at short description.
Review aged tickets by subcategory and days aging to identify and anomalies. Drill down by looking at short description.
Review aged tickets by contact type and days aging to identify and anomalies. Drill down by looking at short description.
Review aged tickets by Assigned To and days aging to identify and anomalies. Drill down by looking at short description.
Review aged tickets by Assignment group and days aging to identify and anomalies. Drill down by looking at short description.
Review skills and training management program which includes skill gap analysis at regular intervals
Review the knowledgebase and ensure there is a knowledge management program in place to provide current and accurate information
Review the total quality management program to ensure that calls, tickets, surveys and other sources of work are being looked at to improve the overall quality.
Review the service performance management program. Specifically, the reporting and measurements system to track and trend the team's performance.
Review the service performance management program. Specifically, the analytics and optimization system to ensure insights are being harvested from their performance and recommendations are being made to drive improvement.
Review the continual service improvement program. Ensure all observations and findings are being tracked in the CSI register and improvement is being made.
Review employee engagement, enablement, and empowerment systems. Specifically, implement an awards and recognition program. Having engaged and connected employees will contribute to the FCR results.
Sample List of Areas to Probe (Employee Experience):