Stanford / MIT Benchmarking IT Help Desk

Transcription

1 Stanford / MIT Benchmarking IT Help Desk Final Presentation November 13, 2002

2 Agenda Project Goals Help Desk Benchmarking Goals & benchmark metrics Initial data comparisons Findings & hypotheses Quick wins and lessons Tools and timelines to get there Benchmarking as a Methodology 2

3 Benchmarking Project Goals Help Desk Specific Enable comparisons between institutions Develop ongoing management tool» Determine metrics» Develop initial comparisons & findings» Identify tools needed, future plans Benchmarking in Higher Education Enable comparisons among schools and industry Develop methodology Provide a test-case Develop strategy to expand See additional context in Appendix 1 Project History & Goals 3

4 Benchmarks must tie to management goals 1. Support client needs with quality service 2. Be responsive 3. Be cost effective 4. Provide appropriate level of investment 5. Develop effective, mature processes 6. Maintain high-performing, competent team 7. Support rollout of new systems 4

5 Goals must tie to specific metrics Invest Appropriately Be Cost Effective % of budget Cost per case by topic Clients served/fte Total costs by topic Cases by media, including self-help Support Customer Needs with High Quality Service Annual customer survey Spot-surveys on selected transactions Be Responsive Elapsed time per case Call abandonment Hold time Time to answer Support Rollout of New Systems Case volume by topic 3 months before and after launch Minutes per case Develop High Performing, Competent Teams Employee satisfactn survey Individual perf. metrics Team performance metrics Training $$ / FTE % Help Desk certification Case volume compared to staff skills mix Develop Effective, Mature Processes # of contacts vs. # of days to resolve Origin of Help Desk cases See Appendix 6 for discussion of specific data elements to calculate benchmarks 5

6 Caveat: Best benchmarking is yet to come Problems with historical data Assumptions Extrapolations Simply missing some data Similar but very different operations Common metrics going forward Don t t focus too heavily on current data; look to future! 6

7 Context for Comparison: Help Desk Operations Organization Structure Location Offices Staffing ACD Tool Media MIT Consolidated + unquantified support in acad. depts. Single unit; junior/senior mixed; informal limit 15 min Single, separate location Cubes + call center 2-4 hour blocks; many stdts 4 phone numbers Home-grown Java Heavy 50%+ Stanford Distributed support model across ITSS Tier 1 & 2 (10 min limit Tier 1) Multiple, distributed Individual offices Full-time assignments 1 published #, then phone tree Customized Remedy Heavy Web-form See more details in Appendix 3. How Each Help Desk Works 7

8 Context for Comparison: FY 02 Sizing Demographics MIT Stanford Variance Faculty & Staff 9,230 10,792 17% Students 10,204 14,173 39% Total Population 19,434 24,965 28% University Consolidated Budget $1,535,949 $1,937,900 26% IT Department Information Annual Base Budget $x $x 1 83% Full Time Staff (FTE) % Help Desk Information With Students No Students Annual Base Budget $x $x 2 5% Full Time Staff (FTE) % Tickets Processed 43,553 56, % 1 Includes providing telecommunications for Stanford s hospital 2 Does not include Student Help Desk due to no tracking/ticketing system. Approximate increase with students would be +$275K and +5 or 6 FTEs. 8

9 Gauging investment and effectiveness MIT Stanford Variance IT Dept Budget / University Budget 2.9% 4.2% Help Desk Budget / IT Budget 4.2% 2.3% Tickets / School Population % Population per HD Employee 712 1, % Tickets / Help Desk FTE 1,595 3,017 89% Help Desk Budget / Ticket $41.83 $ % 1 This ratio s meaningfulness is affected because it does not include Student Help Desk numbers due to no tracking/ticketing system. 9

10 Goal: Be cost effective $200 $180 $160 Cost per Ticket $140 $120 MIT Stanford $100 $80 $60 $40 $20 $0 Accounts Backup Business Apps Business Func Cluster Connectivity Courseware Hardware OS Software Other Printing Desk Software Security/Virus Web See supporting data in Appendix 9

11 Goal: Be cost effective $480,000 $400,000 Total Annual Cost by Help Desk Topic Annual Cost $320,000 $240,000 $160,000 MIT Stanford $80,000 $0 Accounts Backup Business Apps Business Func Cluster Connectivity Courseware Hardware OS Software Other Printing Desk Software Security/Virus Web See supporting data in Appendix 9 11

12 Goal: Be cost effective Cases & Complexitys MIT First Contact Helpdesks Estimated Complexity of Case Accts/ID's/Auth Backup Bus App Suppt Bus. Functions Cluster Connectivity Courseware Hardware OS Software Other Printing Productivity SW Security/Virus Web See supporting data in Appendix 9 12

13 Goal: Be cost effective Stanford Helpdesks: Tier Where Resolved Cases & Complexity Other Level 2 Level 1 0 Accts/ID's/Auth Backup Bus App Suppt Bus. Functions Cluster Connectivity Courseware Hardware OS Software Other Printing Productivity SW Security/Virus Web See supporting data in Appendix 9 13

14 Goal: Support rollout of new systems 7,000 Impact: New Business Applications 6,000 Number of Trouble Tickets 5,000 4,000 3,000 2,000 Kronos/HR People Soft Jan. Axess Probs. March HR Salary Setting May ITSS Help Desk Level 1 ITSS Help Desk Level 2 Legacy Applications Rollout New Applications 1,000 - Total Help Tickets A S O N D J F M A M J J 12 Months FY02 Some rollout application tickets included in HDLevels 1 & 2. See supporting data in Appendix 9 (Stanford data only). 14

15 Preliminary data offers initial observations Implementation choices affect Help Desk costs MIT» » Connectivity to desktop» Security, Kerberos Stanford» Accounts, authentications» Business apps Time is money. Topics are expensive when they are complex, must escalate, or relate to unique applications Specialists are required more frequently for unique, proprietary issues System rollouts create overall spikes and some dips in specific areas 15

16 Initial observations Student employees» MIT Help Desk employs more students at a lower overall budget» More FTEs but difficult now to gauge overall effectiveness of using students Structured tiers:» Using structured tiers may support a greater number of cases» Resolving at Tier 1 significantly reduces costs» You can either tier the work through process choices, or can tier the staff to handle only certain types of work Media of case submission may affect costs» Web submission may support greater number of cases/fte 16

17 Goal: Be responsive Responsiveness to Phone Calls Stanford Tier 1 only Jan-Aug 02 MIT- All desks Jul 01 Jun 02 Average Speed to Answer (seconds) Abandon Rate % 17% 13% Time before Caller Abandons (seconds) Average Call Length (seconds) 252 (4.2 min) 415 (6.9 min) Time between Calls (for staffer) 4.9 min Average # of Calls Monthly HDI Industry Comparisons % 5 min. Speed to Answer = Time a call waited before being answered by a person. Abandon rate = % of calls where customer hung up; includes callers that hung up after reaching voice mail. Call Length = Time from when a call is answered to when it is released. Time between Calls = Time between calls that an ACD agent handles. Agent closes out ticket before getting back in queue to receive calls. 17

18 Goal: Support customers with high quality service Customer satisfaction appears comparable across institutions. MIT Computing Help Desk (All Levels) and Stanford Help Desk (Level 1) "Snapshot" Surveys after Recently Closed Cases Annualized Average Timeliness of Response 5.0 Quality of Resolution 5 Point Likert Scale Courtesy and Professionalism Technical Competence Overall Satisfaction 0.0 MIT 2001 SU 2002 Improvement efforts do bear fruit as shown in MIT s two annual survey results. Likert Scale MIT Computing Help Desk (All Levels) from IS Annual Customer Satisfaction Surveys Timeliness of Response Quality of Resolution Courtesy and Professionalism Technical Competence Overall Satisfaction Ability to Get Through Turnaround Time See supporting data in Appendix 5 18

19 Goal: Develop effective, mature processes The vast majority of cases are resolved quickly. Help Desk Overall Time to Close Cases -- Help Desk Case neglected or Customer unresponsive % % % 80.00% 70.00% Days to Close Cases % 50.00% 40.00% 30.00% n of Interactions % 9.23% 10.95% 4.09% 3.40% 2.35% More 20.00% 10.00%.00% Desirable Days 19

20 Goal: Maintain high-performing, competent team Individual performance can vary greatly; must consider Hawthorne effect Managers D Staff Member C (75%) Staff Member A Stanford IT Help Desk (Level 2) Hours Logged FY02 Staff Member I 461 Staff Member E (55%) 532 Staff Member B Staff Member H (80%) Staff Member G Staff Member F

21 Goal: Maintain high-performing, competent team More team or employee-related metrics are desirable but need more high level discussion Employee satisfaction survey Customer satisfaction tied to individual service providers Individual performance metrics MIT already tracks by team Stanford tracks by individual Help Desk Certifications Behavioral and/or technical competencies 21

22 Initial performance data also yields some Customer satisfaction observations» Appears comparable across both institutions» Improvements efforts did increase satisfaction over 2 years (MIT) Process effectiveness» Better categorization, identification of the work may help with faster escalation. Get to the right place faster.» Vast majority are resolved quickly Employee performance» Can vary significantly among individuals» Metrics do affect behavior (Stanford) 22

23 The data also raise good questions Processes Which cases should be escalated more quickly? Should you tier the work or the organization? organization? How does web-submission affect cost? Staffing Is student employment effective? What additional training should tier 1 1 receive? How should each institution use employee performance data? Support intensive systems Should support intensive systems be replaced? How can we help with new system design to minimize Help Desk requirements? Investments to improve efficiencies Which tools should we acquire to improve performance? 23

24 Quick Wins for Implementation MIT Stanford Tracking Track tickets at student-staffed Unix desk Track internal hand-offs or tiers/escalations explicitly Standardize work reporting categories Track type of media for each case Consolidate reporting functions into one ticket system Examine excess ticket counts in specific categories In Place Quick Win Quick Win In Place Quick Win Quick Win Quick Win In Place Quick Win Quick Win In Place Quick Win Customer feedback Initiate or increase transaction-based spot surveys Quick Win Quick Win Proactively use data Generate & review weekly metric reports Generate weekly standards for tickets processed or time spent and use as part of individual performance management Quick Win Not quick Quick Win Quick Win Reconfigure Space Reconfigure space and move staff to allow for more efficiencies and collaboration In Place Quick Win 24

25 of Help Desk Benchmarking Software or Hardware Investments Customer feedback Management High Performing Team Scope Remedy changes needed for bmarking; ; engage consultant Casetracker to allow consultant to track touch minutes per case and escalations (tiers) both within and outside HD Knowledge Management system Pilot use to help HD staff retrieve standard answers Evaluate usefulness of client use (self-help) ACD call-board to display calls waiting in queue Create dashboard reports and process for regular reporting Self-serve password reset tools Collaborate on annual customer survey Define process for using customer survey responses Create cross-functional ITSS team for Delphi rollout Institute regular review of metrics with finance Create Help Desk Standard Oprtng Procdrs & Handbk Solicit employee feedback for process and job improvement Track % of HD Certifications and training $ per employee MIT In Place Long Term In Place In Place Long Term Stanford 25

26 Cost to Implement Metrics Software or Hardware Investments Remedy consultant to program changes Casetracker consultant Knowledge Management system Pilot use to help HD staff Evaluate use of client self-serve ACD call-board to display queued calls Self-serve password reset tools Joint customer satisfaction survey Creation of Standard Operating Procedures Self Creation of Dashboard Next 6 months MIT Stanford $ 75K $ 60K $ 300K $300K $ 15K $ 60K $10K $10K $32K $15K 26

27 Stanford: Help Desk Dashboard MONTHLY Cases by Media Calls Walk-In Self-Help TO BE DEVELOPED Customer Satisfaction - Spot Ticket Surveys IT Help Desk Tech Support Student J F M A M J J A S O N D 0 Courtesy Tech Knowledge Overall Satis 3,400 3,200 3,000 2,800 2,600 2,400 2,200 2,000 1,800 1,600 1,400 1,200 1, Level 1 Help Desk # of Tickets Created by Employee F M A M J J A S Avg Another Metric Call Length (Tier 2) Phone-In Statistics Abandon Time to Answer Hold Time Actual Goal Problems by Cause - Tier 1 -- for Month of XXXXX Current Previous % Problem Resolution 100% 80% 60% 40% 20% Tier 3 Tier 2 Tier 1 Account ID Authority Bus App Cluster Securty/Virus Connectvty Data Backup Other HW Print SW - OS SW -Personal Web Telecom 0% 27

28 MIT: Help Desk Dashboard MONTHLY MIT First Contact Helpdesks MIT First Contact Help Desks Cases By Method % 50% Cases / Complexity Accounts/ID's/Authority Backup Business Application Support Business Functions Cluster Connectivity Courseware Hardware OS Software Other Printing Productivity Software Security/Virus Web Specialist (Tier 2) Simple (Tier 1) Referral (Tier 3) 40% 30% 20% 10% 0% Jan- Feb- Mar- Apr- May- Jun- 02 TO BE DEVELOPED Customer Satisfaction - Spot Ticket Surveys Courtesy Tech Overall Satis Knowledge IT Help Desk Tech Support Student 02 Jul-02 Aug- Sep- Messages 02 ( , Web) Interactive (Voice, Char) In-Person (Walk In, Site Visit) Internal (Transfers, Referrals) MIT First Contact Helpdesks Interactive Communications (Phone, Chat) Answered % MIT First Contact Helpdesks Message Communications ( , Web Requests) Time to Close Cases Call Length (specialist) (0-600) Call Length (simple) (0-600) Phone Time to Answer (0-60) Hold Time (0-60) Notes: 1) The MIT ACD currently does not collect hold time. 2) Times are in seconds 3) MIT currently cannot distinguish specialist from simple calls; actual is average Actual Goal Time between exchanges (specialist) (0-6000) Number of exchanges (specialist) (0-6) Answered% Time between exchanges (simple) (0-600) Time to first response (0-600) Number of exchanges (simple) (0-6) Notes: This is a sample dashboard showing metrics to be delivered on a monthly basis pending some tool improvements. 1. The Cases by Complexity graph shows real ticket counts and categorizations. Complexity is currently estimated based on time-to-resolve. 2. We do not currently have complete Helpdesk Interactive Communications data such as time to first response. This graph is a placeholder. 3. Cases by Method shows additional data. The graph breaks out and web requests. Ultimately we want to consolidate this data into the categories shown in the graph s legend. Actual Goal Cases % 90.00% % % % 60.00% % % % %9.23% 10.95% 20.00% %3.40%2.35% 10.00% 0.00% More Days 28

29 Next Steps for MIT/Stanford Help Desk Benchmarking Months: D J F M A M J J A S Implement selected metrics (dashboard) and quick wins Track common metrics; re-evaluate Begin software modifications Implement Knowledge Management system and ACD call board Implement customer spot surveys; then annual customer survey (?) Implement management, oprtns changes Consider inviting others to benchmark Ongoing Ongoing Annual? = On-site visits 29