Free Desktop Support Training Series | What You Need to Know About Desktop Support KPIs

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Cause and Effect
What You Need to Know About Desktop Support KPI’s
Session #408: April 18, 2013 Jeff Rumburg, Managing Partner, MetricNet LLC

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Observations From 25 Years of Desktop Support Data
More than 900 Desktop Support Benchmarks
Global Database
25+ Key Performance Indicators
Nearly 60 Industry Best Practices
1

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Characteristics of World-Class Desktop Support
 Desktop Support consistently exceeds customer expectations
 Result is high levels of customer satisfaction
 MTTR is below average for Incidents and Service Requests
 Costs are managed at or below industry average levels
 Cost per Ticket, per Incident, and per Service Request is below average
 Minimizes Total Cost of Ownership (TCO)
 Desktop Support follows industry best practices
 Industry best practices are defined and documented
 Desktop Support follows industry best practices
 Every transaction adds value
 A positive customer experience
 Drives a positive view of IT overall
© 2013 MetricNet, LLC, www.metricnet.com

Tickets, Incidents, and Service Requests
Incident Volume + Service Request Volume = Ticket Volume
Tickets
Incidents Service Requests
 Unplanned work that
requires a physical
touch to a device
 Hardware break/fix
 Device failure
 Connectivity failure
 Planned work that
requires a physical touch
to one or more devices
 Move/Add/Change
 Hardware or software
upgrade
 Device refresh
 Device set-up
© 2013 MetricNet, LLC, www.metricnet.com 3

The Premise Behind Desktop Support KPI’s
We’ve all heard the expression…
“If you’re not measuring it,
you’re not managing it!”
But there’s more to the story…Lots more!

Two Paradigms for Desktop Support KPI’s
The Historical Approach The Holistic Approach
Measurement
(75%)
Analysis
(15%)
Prescription
(7.5%)
Action
(2.5%)
Measurement
(5%)
Analysis
(20%)
Prescription
(30%)
Action
(45%)
IncreasingValue!

6
4
3
2
1
Customer
Enthusiasm
An Industry MegaTrend: The Holistic Use of KPI’s
Measure
Diagnose
Prescribe
Implement
Model
Component Description
1. Measure
Measure help
desk
performance on
an ongoing basis
2. Diagnose
Benchmark
performance and
conduct a gap
analysis
3. Prescribe
Define actions to
close the gap
4. Implement
Implement your
action plan and
improve
performance

The Most Common Desktop Support KPI’s
 Cost per Ticket
 Cost per Incident
 Cost per Service Request
Cost Productivity
Service Level
Quality
Ticket Handling
Technician Average Incident Response
Time (min)
 % of Incidents Resolved in
24 Hours
 Mean Time to Resolve
Incidents (hours)
 Mean Time to Complete
Service Requests (days)
 Technician Utilization
 Tickets per Technician-
Month
 Incidents per Technician-
Month
 Service Requests per
Technician-Month
 Ratio of Technicians to
Total Headcount
 Customer Satisfaction
 First Contact Resolution Rate
(Incidents
 % Resolved Level 1 Capable
 % of Tickets Re-opened
 Technician Satisfaction
 New Technician Training
Hours
 Annual Technician Training
Hours
 Annual Technician Turnover
 Technician Absenteeism
 Technician Tenure (months)
 Technician Schedule
Adherence
 Average Incident Work
Time (min)
 Average Service Request
Work Time (min)
 Average Travel Time per
Ticket (min)
And there are hundreds more!!
Workload
 Tickets per Seat per Month
 Incidents per Seat per
Month
 Service Requests per Seat
per Month
 Incidents as a % of Total
Ticket Volume

Controllable vs. Non-Controllable KPI’s
Causal
Factors
Drivers
 Cost and Quality are the Macro Measures
 The Macro Measures tell the story of your
performance
 They are good for communicating the
performance of Desktop Support
 But you cannot control them directly
 Workload metrics are driven by Causal Factors
 The Causal Factors define the volume and mix
of work performed by Desktop Support
 Desktop Support has very little control over the
Causal Factors
 They are a function of your IT environment
 Productivity, Service Level, Technician, and Ticket
Handling are the underlying drivers of performance
 These are the metrics that drive your performance
 You can control these metrics directly
 It is through these metrics that you can influence the
Macro Measures, and improve your performance

Causal Factors: The Workload Drivers
Causal
Factors
Drivers
 Causal Factors include:
 Device count and mix
 Mix of desktop vs. laptop
computers
 Number of mobile devices
 Average age of devices
 Standardization of desktop
environment
 User population density
 High rise vs. campus vs. field
 User work location
 Office vs. home vs. field
 And numerous other factors…

The Most Common Desktop Support KPI’s
 Cost per Ticket
 Cost per Incident
 Cost per Service Request
Cost Productivity
Service Level
Quality
Ticket Handling
Technician Average Incident Response
Time (min)
 % of Incidents Resolved in
24 Hours
 Mean Time to Resolve
Incidents (hours)
 Mean Time to Complete
Service Requests (days)
 Tickets per Technician-
Month
 Incidents per Technician-
Month
 Service Requests per
Technician-Month
 Ratio of Technicians to
Total Headcount
 First Contact Resolution Rate
(Incidents
 % Resolved Level 1 Capable
 % of Tickets Re-opened
 Technician Satisfaction
 New Technician Training
Hours
 Annual Technician Training
Hours
 Annual Technician Turnover
 Technician Absenteeism
 Technician Tenure (months)
 Technician Schedule
Adherence
 Average Incident Work
Time (min)
 Average Service Request
Work Time (min)
 Average Travel Time per
Ticket (min)
And there are hundreds more!!
Workload
 Tickets per Seat per Month
 Incidents per Seat per
Month
 Service Requests per Seat
per Month
 Incidents as a % of Total
Ticket Volume

Desktop Support KPI’s: Which Ones Really Matter?
 Cost per TicketCost
Productivity
Quality
Call Handling
 Customer satisfaction
 First contact resolution rate (incidents)
Technician  Technician Job Satisfaction
Aggregate  Balanced scorecard
TCO  % Resolved Level 1 Capable
Service Level  Mean Time to Resolve

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Benchmarking Case Study:
Optimizing Desktop Support Performance

Your Desktop
Support Performance
Performance of
Benchmarking Peer
Group
Determine How
Best in Class
Achieve Superiority
Adopt Selected
Practices of
Best in Class
Build a Sustainable
Competitive
Advantage
The ultimate
objective of
benchmarking
COMPARE
The Benchmarking Methodology
Read MetricNet’s whitepaper on Desktop Support Benchmarking. Go to www.metricnet.com to download your copy!

Cost per Ticket HigherLower
Higher
AFTER BENCHMARKING
STARTING POINT: BEFORE
BENCHMARKING
BEST-IN-CLASS
PERFORMANCE CURVE
AVERAGE PERFORMANCE CURVE
The Goal of Benchmarking
CustomerSatisfaction

Benchmarking Data Summary
Average Min Max
Cost per Ticket $81 $68 $55 $117
Cost per Incident $57 $45 $34 $85
Cost per Service Request $144 $128 $107 $196
Customer Satisfaction 71% 81% 71% 89%
First Contact Resolution Rate (Incidents) 49% 55% 44% 82%
% Resolved Level 1 Capable 9% 17% 4% 23%
% of Tickets Re-opened 2.0% 6.0% 1.0% 8.0%
Technician Utilization 46% 54% 36% 84%
Tickets per Technician per Month 65 81 58 93
Incidents per Technician per Month 81 100 72 131
Service Requests per Technician per Month 42 53 35 71
Ratio of Technicians to Total Headcount 73% 84% 69% 88%
Average Incident Response Time (hours) 9.1 6.3 4.2 12.1
% of Incidents Resolved in 24 Hours 33% 51% 33% 62%
Mean Time to Resolve Incidents (days) 2.6 1.9 0.7 4.3
Mean Time to Complete Service Requests (days) 12.7 7.4 4.6 12.7
Technician Satisfaction 71% 84% 66% 87%
New Technician Training Hours 10 46 10 80
Annual Technician Training Hours 0 21 0 28
Annual Technician Turnover 53% 24% 8% 53%
Technician Absenteeism 19% 14% 9% 22%
Technician Tenure (months) 11 47 11 64
Technician Schedule Adherence 64% 87% 64% 91%
Average Incident Work Time (min) 65 49 38 77
Average Service Request Work Time (min) 119 94 80 110
Average Travel Time per Ticket (min) 18 23 12 49
Tickets per Seat per Month 0.79 0.90 0.70 1.68
Incidents per Seat per Month 0.57 0.65 0.5 1.2
Service Requests per Seat per Month 0.22 0.25 0.2 0.48
Incidents as a % of Total Ticket Volume 72% 72% 71% 71%
Deskside Support KPI's Peer GroupYour
Performance
Productivity
Workload
Cost
Quality
Metric Type
Service Level
Technician
Ticket Handling

The Two Foundation Metrics: Cost and Customer Satisfaction
Cost per Ticket Customer Satisfaction

Cost and Quality: Nothing Else Matters!
Lower Cost
Cost per Ticket (Efficiency)
(Effectiveness)
Top Quartile
Efficient and Effective
Lower Quartile
Middle Quartiles
Effective but not Efficient
Middle Quartiles
Efficient but not Effective
World-Class
Desktop
Support
Peer Group
Higher Cost
Lower
Quality
Higher
Quality

Technician Utilization: The Key Driver of Cost
Technician
Utilization

$0
$50
$100
$150
$200
$250
$300
30% 40% 50% 60% 70% 80% 90%
Techncian Utilization
CostperTicket
Technician Utilization vs. Cost per Ticket

Desktop Support Technician Utilization Defined
Technician
Utilization
((Average number of Incidents handled by a technician in a month) X (Average Incident Work Time) +
(Average number of Service Requests handled by a technician in a month) X (Average Service Request Work Time) +
(Average number Tickets handled by a technician in a month) X (Average Travel Time per Ticket))
(Average number of days worked in a month) X (Number of work hours in a day) X (60 minutes/hr)
 Technician Utilization is a measure of technician work and travel time, divided by
total time at work during the month
 It takes into account both incidents and service requests handled by the
technicians
 But it does not make adjustments for sick days, holidays, training time, project
time, or idle time
=

Example: Desktop Support Technician Utilization
 Incidents per Technician per Month = 60
 Service Requests per Technician per Month = 24
 Average Tickets per Technician per Month = 84
 Average Incident Work Time = 32 minutes
 Average Service Request Work Time = 59 minutes
 Average Travel Time per Ticket = 41 minutes
Technician
Utilization
((Average number of Incidents handled by a technician in a month) X (Average Incident Work Time) +
(Average number of Service Requests handled by a technician in a month) X (Average Service Request Work Time) +
(Average number Tickets handled by a technician in a month) X (Average Travel Time per Ticket))
(Average number of days worked in a month) X (Number of work hours in a day) X (60 minutes/hr)
=
Technician
Utilization
((60 Incidents per Month) X (32 minutes) + (24 Service Requests per Month) X (59 minutes) +
(84 Tickets per Month) X (41 minutes))
(21.5 working days per month) X (7.5 work hours per day) X (60 minutes/hr)
= =
70%
Technician
Utilization

The Drivers of Customer Satisfaction
Technician
Utilization
FCR
(Incidents)
Technician
Satisfaction
SL’s
MTTR

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
30% 40% 50% 60% 70% 80% 90% 100%
Technician Satisfaction
Technician Satisfaction vs. Customer Satisfaction

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
30% 40% 50% 60% 70% 80% 90%
First Contact Resolution Rate (Incidents)
Incident FCR vs. Customer Satisfaction

Incident MTTR vs. Customer Satisfaction
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
Incident MTTR (days)

The Drivers of Technician Satisfaction
Technician
Utilization
FCR
(Incidents)
Technician
Satisfaction
SL’s
MTTR
Service
Levels: MTTR
Coaching Career Path Training Hours

New Technician Training Hours vs. Technician Job Satisfaction
20%
30%
40%
50%
60%
70%
80%
90%
100%
0.0 50.0 100.0 150.0 200.0 250.0
New Technician Training Hours
TechnicianSatisfaction

Annual Training Hours vs. Technician Job Satisfaction
40%
50%
60%
70%
80%
90%
100%
0 20 40 60 80 100 120 140
Annual Technician Training Hours
TechnicianSatisfaction

Technician Experience vs. Incident FCR
20%
30%
40%
50%
60%
70%
80%
90%
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0
Technician Time on Job (months)
IncidentFCR

Measuring Defects: % Resolved Level 1 Capable
Technician
Utilization
FCR
(Incidents)
Technician
Satisfaction
SL’s
MTTR
Service
Levels: MTTR
% Resolved
Level 1
Capable

Cost of Resolution: North American Averages
Support Level Cost per Ticket
Vendor
Level 2: Desktop Support
Field Support
Level 3 IT
(apps, networking, NOC, etc.)
Level 1: Service Desk
$471
$196
$85
$62
$22

A Summary of the Major KPI Correlations
Technician
Utilization
FCR
(Incidents)
Technician
Satisfaction
SL’s
MTTR
Work/
Travel Time
Techs/
Total FTE’s
Absenteeism/
Turnover
% Resolved
Level 1
Capable
Scheduling
Efficiency
Service
Levels: MTTR

Benchmarking Case Study: The Diagnosis
Average Min Max
Cost per Ticket $81 $68 $55 $117
Cost per Incident $57 $45 $34 $85
Cost per Service Request $144 $128 $107 $196
Customer Satisfaction 71% 81% 71% 89%
First Contact Resolution Rate (Incidents) 49% 55% 44% 82%
% Resolved Level 1 Capable 9% 17% 4% 23%
% of Tickets Re-opened 2.0% 6.0% 1.0% 8.0%
Technician Utilization 46% 54% 36% 84%
Tickets per Technician per Month 65 81 58 93
Incidents per Technician per Month 81 100 72 131
Service Requests per Technician per Month 42 53 35 71
Ratio of Technicians to Total Headcount 73% 84% 69% 88%
Average Incident Response Time (hours) 9.1 6.3 4.2 12.1
% of Incidents Resolved in 24 Hours 33% 51% 33% 62%
Mean Time to Resolve Incidents (days) 2.6 1.9 0.7 4.3
Mean Time to Complete Service Requests (days) 12.7 7.4 4.6 12.7
Technician Satisfaction 71% 84% 66% 87%
New Technician Training Hours 10 46 10 80
Annual Technician Training Hours 0 21 0 28
Annual Technician Turnover 53% 24% 8% 53%
Technician Absenteeism 19% 14% 9% 22%
Technician Tenure (months) 11 47 11 64
Technician Schedule Adherence 64% 87% 64% 91%
Average Incident Work Time (min) 65 49 38 77
Average Service Request Work Time (min) 119 94 80 110
Average Travel Time per Ticket (min) 18 23 12 49
Tickets per Seat per Month 0.79 0.90 0.70 1.68
Incidents per Seat per Month 0.57 0.65 0.5 1.2
Service Requests per Seat per Month 0.22 0.25 0.2 0.48
Incidents as a % of Total Ticket Volume 72% 72% 71% 71%
Deskside Support KPI's Peer GroupYour
Performance
Productivity
Workload
Cost
Quality
Metric Type
Service Level
Technician
Ticket Handling

Desktop KPI’s: Which Ones Really Matter?
 Cost per TicketCost
Productivity
Quality
Call Handling
 Customer satisfaction
 First contact resolution rate (incidents)
Technician  Technician Satisfaction
Aggregate  Balanced scorecard
TCO  % Resolved Level 1 Capable
Service Level  Mean Time to Resolve

Aggregate Metrics: The Balanced Scorecard
Step 1
Eight critical
performance
metrics have been
selected for the
scorecard
Step 2
Each metric has been
weighted according to its
relative importance
Step 3
For each performance metric,
the highest and lowest
performance levels in the
benchmark are recorded
Step 4
Your actual
performance for
each metric is
recorded in this
column
Step 5
Your score for each
metric is then
calculated: (worst case
– actual performance) /
(worst case – best
case) X 100
Step 6
Your balanced score for each
metric is calculated: metric
score X weighting
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Worst Case Best Case
Cost per Incident 15.0% $312.00 $19.00 $48.00 90.1% 13.5%
Cost per Service Request 15.0% $556.00 $41.00 $113.00 86.0% 12.9%
Customer Satisfaction 25.0% 67.0% 94.0% 83.0% 59.3% 14.8%
Technician Utilization 15.0% 36.0% 84.0% 59.0% 47.9% 7.2%
First Contact Resolution Rate (incidents) 15.0% 38.0% 84.0% 61.0% 50.0% 7.5%
% of Incidents Resolved in 24 Hours 5.0% 19.0% 71.0% 58.0% 75.0% 3.8%
Mean Time to Complete Service Requests (days) 5.0% 18.4 1.8 5.8 75.9% 3.8%
Technician Satisfaction 5.0% 59.0% 93.0% 84.0% 73.5% 3.7%
Total 100.0% N/A N/A N/A N/A 67.1%
Balanced
Score
Your Actual
Performance
Metric
Score
Performance RangeMetric
WeightingPerformance Metric

Desktop Support Balanced Scorecard Benchmark
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
DesktopSupportBalancedScores
High 86.2%
Average ----- 51.9%
Median 50.1%
Low 16.0%
Your Score 67.1%
Desktop Support Balanced Scores
Key Statistics

Desktop Support Scorecard Trend
40%
45%
50%
55%
60%
65%
70%
75%
80%
85%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
DesktopSupportBalancedScore
12 Month Average Monthly Score

Establishing Performance Targets
Achieving the performance targets recommended above will improve the Desktop Support
Balanced Score from 67.1% to 85.6%.
Desktop Support Metric
Current
Performance
Performance
Target
Cost per Incident $48.00 $42.50
Cost per Service Request $113.00 $98.00
Customer Satisfaction 83.0% 90.0%
Technician Utilization 59.0% 65.0%
Incident First Contact Resolution 61.0% 70.0%
% of Incidents Resolved in 24 Hours 58.0% 70.0%
Mean Time to Complete Service Requests (days) 5.8 3.5
Technician Satisfaction 84.0% 90.0%
Desktop Support Balanced Score 67.1 85.6
% %

Driving Individual Accountability: The Technician Scorecard
Step 1
Eight critical
performance
metrics have been
selected for the
scorecard
Step 2
Each metric has been
weighted according to its
relative importance
Step 3
For each performance metric,
the highest and lowest
performance levels in the
benchmark are recorded
Step 4
Your actual
performance for
each metric is
recorded in this
column
Step 5
Your score for each
metric is then
calculated: (worst case
– actual performance) /
(worst case –best case)
X 100
Step 6
Your balanced score for each
metric is calculated: metric
score X weighting
39
Worst Case Best Case
Customer Satisfaction 20.0% 67.0% 94.0% 83.0% 59.3% 11.9%
First Contact Resolution Rate (Incidents) 20.0% 38.0% 84.0% 61.0% 50.0% 10.0%
Incidents Closed this Month 15.0% 19.9 76.9 59.8 69.9% 10.5%
Service Requests Closed This Month 15.0% 15.6 42.2 28.5 48.6% 7.3%
Unplanned Absenteeism 7.5% 0.0% 22.0% 19.0% 86.4% 6.5%
Teamwork 7.5% 0.0 5.0 3.5 69.9% 5.2%
Initiative 7.5% 0.0 5.0 5.0 100.0% 7.5%
Mentoring 7.5% 0.0 5.0 4.5 90.0% 6.7%
Total 100.0% N/A N/A N/A N/A 43.7%
Balanced
Score
Your Actual
Performance
Metric
Score
Performance RangeMetric
WeightingPerformance Metric

Monthly Technician Performance Postings
Sep'10 Aug '10 Jul '10 Jun '10 May '10 Apr '10
11 95.8% 98.0% 97.1% 95.7% 98.3% 97.3% 97.0%
32 92.8% 92.1% 90.3% 89.3% 84.6% 92.2% 90.2%
21 91.5% 88.5% 83.2% 94.0% 93.7% 93.5% 90.7%
35 91.0% 86.8% 85.2% 78.5% 80.5% 68.2% 81.7%
14 89.5% 89.1% 90.0% 90.1% 92.3% 92.1% 90.5%
26 83.8% 84.4% 90.2% 86.5% 77.8% 63.9% 81.1%
25 83.0% 73.6% 81.9% 72.1% 84.8% 87.9% 80.5%
15 70.4% 66.6% 53.3% 56.3% 56.6% 39.0% 57.0%
20 64.9% 66.5% 70.1% 56.9% 40.9% 72.7% 62.0%
31 62.3% 47.4% 22.7% 38.4% 26.0% 93.0% 48.3%
16 61.0% 62.8% 54.5% 45.9% 41.7% 62.7% 54.8%
17 57.9% 42.1% 32.3% 71.6% 60.3% 60.3% 54.1%
33 56.8% 75.5% 64.8% 80.3% 79.7% 73.5% 71.8%
13 52.2% 34.9% 61.0% 52.8% 58.9% 48.7% 51.4%
24 48.9% 66.7% 86.9% 87.7% 83.6% 74.5% 74.7%
28 46.4% 45.5% 19.3% 40.3% 28.8% 32.4% 35.4%
27 43.7% 26.5% 31.5% 24.3% 22.2% 17.2% 27.6%
19 41.5% 28.4% 50.1% 48.1% 71.1% 81.0% 53.4%
23 39.1% 52.3% 57.1% 86.4% 87.7% 88.9% 68.6%
22 36.8% 18.7% 19.3% 52.9% 66.4% 64.3% 43.1%
12 36.6% 43.2% 33.1% 65.7% 69.0% 86.0% 55.6%
30 36.3% 22.6% 23.5% 85.8% 81.5% 70.3% 53.3%
29 34.1% 44.9% 50.2% 28.3% 48.9% 36.9% 40.5%
34 33.4% 37.9% 23.1% 21.7% 29.7% 22.6% 28.0%
18 32.6% 68.4% 80.4% 88.4% 83.8% 91.6% 74.2%
Monthly Average 59.3% 58.5% 58.0% 65.5% 66.0% 68.4% 62.6%
Technician
Number
Monthly Scorecard Performance Six Month
Average

The Big Picture on Desktop Support KPI’s
41

84%
47%
31% 29%
22%
19%
8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Service Desk Desktop
Support
Network
Outages
VPN Training Enterprise
Applications
Desktop
Software
Factors Contributing to IT Customer Satisfaction
%SayingVeryImportant
 n = 1,044
 Global large cap companies
 Survey type: multiple choice
 3 responses allowed per survey
 84% cited the service desk as a very important factor in their overall satisfaction with corporate IT
 47% cited desktop support as a very important factor in their overall satisfaction with corporate IT
Because Desktop Support is a Major Driver of Customer Satisfaction

44
0
10
20
30
40
50
60
70
0 1 2 3 4 5
ProductiveHoursLostperEmployeeperYear
Because Quality of Support Drives End-User Productivity
1 (top) 2 3 4 (bottom)
Customer Satisfaction 93.5% 84.5% 76.1% 69.3%
First Contact Resolution Rate 90.1% 83.0% 72.7% 66.4%
Mean Time to Resolve (hours) 0.8 1.2 3.6 5.0
Customer Satisfaction 94.4% 89.2% 79.0% 71.7%
First Contact Resolution Rate 89.3% 85.6% 80.9% 74.5%
Mean Time to Resolve (hours) 2.9 4.8 9.4 12.3
Service Desk
Desktop Support
Performance Quartile
Support Function Key Performance Indicator
37.4 46.9Average Productive Hours Lost per Employee per Year 17.1 25.9
Performance Quartile n = 60

45
Support Level Cost per Ticket
Vendor
Level 2: Desktop Support
Field Support
Level 3 IT
(apps, networking, NOC, etc.)
Level 1: Service Desk
$471
$196
$85
$62
$22
Because Support Has an Opportunity to Minimize TCO

Some Final Thoughts on Desktop Support KPI’s
 When it comes to Desktop Support KPI’s, the 80/20 Rule applies
 Less really is more!
 Seven KPI’s, plus the Balanced Scorecard are all you need to holistically
measure and manage your Desktop Support organization
 Understand the cause-and-effect relationship between KPI’s
 This gives you the power to achieve desired outcomes in Desktop Support!
 Not all Desktop Support KPI’s are controllable
 Focus on the controllable KPI’s
 Effective application of Desktop Support KPI’s can help to reduce and
minimize Total Cost of Ownership for End-User Support, and drive high
levels of Customer Satisfaction for all of IT

47
Thank You!
Thank you for attending this session.
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48
Question and Answer

25 Years of Desktop Support Data
More than 900 Desktop Support Benchmarks
Global Database
25+ Key Performance Indicators
Nearly 60 Industry Best Practices

Benchmarking is MetricNet’s Core Business
Call Centers
Telecom
Information
Technology
Satisfaction
 Technical Support
 Customer Service
 Telemarketing/Telesales
 Collections
 Service Desk
 Desktop Support
 Field Support
 Price Benchmarking
 Employee Satisfaction

52
Your Presenter: Jeff Rumburg
Jeff Rumburg is a co-founder and Managing Partner at MetricNet,
LLC. Jeff is responsible for global strategy, product development,
and financial operations for the company. As a leading expert in
benchmarking and re-engineering, Mr. Rumburg authored a best
selling book on benchmarking, and has been retained as a
benchmarking expert by such well-known companies as American
Express, Hewlett-Packard, and GM. Prior to co-founding
MetricNet, Mr. Rumburg was president and founder of The Verity
Group, an international management consulting firm specializing in
IT benchmarking. While at Verity, Mr. Rumburg launched a number
of syndicated benchmarking services that provided low cost
benchmarks to more than 1,000 corporations worldwide.
Mr. Rumburg has also held a number of executive positions at META Group, and Gartner, Inc. As
a vice president at Gartner, Mr. Rumburg led a project team that reengineered Gartner's global
benchmarking product suite. And as vice president at META Group, Mr. Rumburg's career was
focused on business and product development for IT benchmarking. Mr. Rumburg's education
includes an M.B.A. from the Harvard Business School, an M.S. magna cum laude in Operations
Research from Stanford University, and a B.S. magna cum laude in Mechanical Engineering. He
is author of A Hands-On Guide to Competitive Benchmarking: The Path to Continuous Quality
and Productivity Improvement, and has taught graduate-level engineering and business courses.
Mr. Rumburg serves on the Strategic Advisory Board for HDI.

53
Cause and Effect
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