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BEST PRACTICES
Service Desk Metrics: Best Practices for Data Analysis and Reporting
• What is the average customer satisfaction
score for each period? How are we trending?
• What is my average number of tickets per
user per month? How does that compare to
the industry standard? Having lower-than-
average tickets per user per month could
indicate you provide excellent self-service
tools or that your users avoid calling the
helpdesk. Conversely, having higher-than-
average tickets could indicate system or
product improvement opportunities or a
world-class helpdesk that provides excellent
customer service.
• How many tickets are we resolving at first-
level support? How many are resolvable
at first-level support? What is our true
first-level resolution rate, and how does it
compare to others?
• What is our average number of hours
to resolve high-priority tickets? What is
acceptable, and how does that compare
to other firms? This can be measured for
each team and department separately,
and combined to be from the customer's
perspective.
Also include an event description, resolution
and closure. These free-text fields can be a critical
piece for data analysis. Tell a story and include the
proper keywords, but remain relevant and on-topic.
» When performing data analysis:
• Categorize the events into buckets using one
or more ticket classifications;
• Analyze the top categories to find the 20
percent of your tickets that cause 80 percent
of the problems;
• Review free-text fields for deeper dives;
• Design charts that tell a story of your data
analysis results; and
• Write an executive summary of the
results, including your assessment and
recommendations, and present your
findings to the business.
» Proper data analysis answers questions frequently
asked by your executives, such as:
• What are my top five issues?
• What are my top five requests?
• Who are my top 10 "frequent fliers"?
This includes customers with requests,
customers with issues and both combined.
• What are my top five applications/products/
services that generate the most incidents/
requests?
• Have we seen this issue in the past? If yes,
how oen? How do we normally resolve
it? This typically results in deploying a
patch that resolves a recurring problem,
rather than handling the same complaint
repeatedly.
PETER QUMSIYEH
Peter Qumsiyeh joined WilmerHale
in 2010 with the opening of the
firm's newest office in Dayton, Ohio.
Peter was immediately promoted
to a coordinator role, analyzing
data and designing metrics, while
quickly transitioning from an
individual contributor to a mentor
and team leader. After receiving his
Lean Six Sigma Black Belt, Peter
led top-priority projects across the
firm, empowering attorneys with
essential information and enhancing
the use of technology in law, all
while demonstrating exceptional
professionalism and outstanding
leadership. Contact him at peter.
qumsiyeh@wilmerhale.com.
MORE ONLINE!
Access the "Service Desk Metrics:
Best Practices for Data Analysis and
Reporting" webinar recording from
July 20 at www.iltanet.org/recordings
