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Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Slide 1 Desktop Metrics: What Should We Measure?

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Presentation on theme: "Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Slide 1 Desktop Metrics: What Should We Measure?"— Presentation transcript:

1 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Slide 1 Desktop Metrics: What Should We Measure? John McDermon Group Leader DCS-2 Departmental Computing Services Division LA-UR

2 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Three questions What behavior do you want to promote? What story do you want to tell? Who do you want to tell this story to? Slide 2

3 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Behavior You dont get what you want, you get what you measure 1 Beware of unintended consequences 3 traditional vectors Better Quality, Accuracy, Efficacy defects, repeats Faster Timeliness, Efficiency response time, resolution time Cheaper Total cost, Cost per unit define costs, define units Where does quantity fall? Slide 3 1.

4 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Story Purpose Inform Explain Persuade Timeframe Past Once upon a time… Present Real time – dashboard, HUD Future Gaze into our crystal ball… Slide 4

5 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Audience Customers Upper management Internal management Competitors Peers Critics Others? Slide 5

6 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Other things to consider Leading or Lagging Trends or Spot values Cost and difficulty of acquiring data What data are you collecting now? What are your current systems capable of? Frequency Slide 6

7 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Discussion Example 1: Faster Explain about future Customers Example 2: Cheaper Persuade about past Upper management Example 3: Better Inform about present Peers Slide 7

8 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D LANL Environment 12,000 employees all types, including students 40+ square miles 30,000 network devices 15,000 fingerprint as WIN 6,000 other Operating Systems + printers, switches, etc. 3,000 standalone systems Slide 8

9 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Departmental Computing Services 5 Groups 280 staff 1 Central Services Group 30 staff 4 Field Groups 250 staff Support over 80% of LANL Departmental Computing assets Includes: Standards, Tools & Services Call center Electronic Software Distribution (ESD) Departmental servers and services Does not include: Network or Phones Enterprise application development or operations Slide 9

10 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Volume of work Slide 10 FY08 120,132 FY09 68,042 FY07 116,805 FY06 112,060 FY05 78,483 FY04 69,230

11 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Service Level Agreement High – 80% resolved in 4 work hours Medium – 80% resolved in 3 work days (24 work hrs) Slide 11

12 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY08 High (4 hrs) Slide 12

13 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY08 Medium (3 days) Slide 13

14 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY09 High (4 hrs) Slide 14

15 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY09 Medium (3 days) Slide 15

16 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Workload Tracking Tickets Created Tickets Closed Tickets in Queue Slide 16

17 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY07 Ticket Queue Slide 17

18 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY08 Ticket Queue Slide 18

19 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY09 Ticket Queue Slide 19

20 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D FY07 – FY09 Ticket Queue Slide 20

21 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Attempt to show age of queue Slide 21

22 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Customer Satisfaction Every ticket closed generates a survey 3 vectors Promptness How satisfied were you with the promptness and efficiency of our desktop support service? Accuracy How satisfied are you that your request was completed accurately without creating other problems? Professionalism How satisfied are you with the courtesy, knowledge and experience of our staff? 5 point scale (-2 to +2) Very Dissatisfied = -2, Neutral = 0, Very Satisfied = 2 Slide 22

23 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Survey Response Rate Slide 23

24 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Survey Scores Slide 24

25 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Research: quantifying an environment Assertion: Complexity increases cost of support Examples of complexity Number of systems Number of operating systems and versions Number of applications and versions Classified (complexity of security plan) Servers, dual boot, etc. Method of access (network vs. stand alone) How to quantify complexity? Could these be variables in linear equation? Slide 25

26 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Harvey Mudd Clinic A MULTI-CRITERIA OPTIMIZATION MODEL FOR TRADE-OFFS BETWEEN SERVICES AND COSTS IN COMPUTER SUPPORT SERVICES This project shall deliver a decision analysis model that relates the cost of support to the types of services available. It will include a multi-criteria optimization model for making trade-offs between level of service provided and costs of that service. The cost of support will be modeled as a function of actual costs (e.g. salaries, cost of systems, cost of equipment, software, etc) and time costs (actual costs in the form of FTE's required to support a given environment, but also including training and professional development costs). The model will permit comparisons amongst different environments so that choices between technologies and level of support can be made by the users. Slide 26

27 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Harvey Mudd Clinic (cont.) To estimate the number of technicians required at each skill level, we anticipate developing a multi-class queueing model where each "server" (technician) is capable of serving different classes of customers based on their skill set. Statistical analysis will be required to estimate the distribution of the time between service requests of each type (e.g. the arrival rate and inter-arrival time distribution) and the distribution of service times; these would be the inputs to the queueing model. Queueing theory as well as computer simulations will be used to estimate the correct number of technicians at each skill level. This queueing model in turn will provide a simple "rule-of-thumb" metric relating environment "complexity" and number of technicians. This metric will be obtained by fitting a statistical model to the results of the queueing simulation to infer which factors have the greatest impact on number of FTE's required. Slide 27

28 Operated by Los Alamos National Security, LLC for the U.S. Department of Energys NNSA U N C L A S S I F I E D Questions? Contact: John McDermon Slide 28


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