Optimizing Service Delivery Through Analytics and ITSM. Rich Jaso VP, Unisys Global Managed Services

Transcription

1 Optimizing Service Delivery Through Analytics and ITSM Rich Jaso VP, Unisys Global Managed Services

2 Agenda Challenges Facing the Market in Optimizing IT Support ITSM Analytics Driving Operational Change in IT Service Delivery Model Implications Use data to highlight common inefficiencies, hidden costs and service problems 2012 Unisys Corporation. All rights reserved. 2

3 IT Support Optimization Challenges in a Changing Market 2012 Unisys Corporation. All rights reserved. 3

4 People Computing: Focus on the End User Consumer IT Is On-Fire The Experience Economy Experiences as a competitive advantage main barrier isn t tech (Frog Design, 2012) Social Enterprise 67% of companies now use social computing in the enterprise. (IDC 2012) Mobile Enterprise 61% increase in the use of mobility in the enterprise, 2011 to (Yankee Group, 2012) 2012 Unisys Corporation. All rights reserved. 4

5 Four Steps to Effectiveness Align IT-End User SERVICE FOCUS Improve IT Process PROCESS OPTIMIZATION Reorganize IT Maturing the IT Operating Model Business Alignment Reallocate Budgets 2012 Unisys Corporation. All rights reserved. 5

6 Today s Support Environment Growing Applications Portfolio Growing Complexity Number of Resolver Groups Consistency Gap Cost Pressure End user Demands 2012 Unisys Corporation. All rights reserved. 6

7 IT Support Market Trends Application Portfolio: Average Mid-Large Enterprise Applications Applications Hardware Devices 2000 Standardize on Laptop/Desktop 2012 Bring your own, laptop, desktop, PDA, etc Resolvers in Support Eco System 2000 Few, part time developers Service Desk Handle Times Mins Mins 2012 Unisys Corporation. All rights reserved. 7

8 The New Paradigm Anytime, anywhere connectivity My hardware, my stuff Customer drivers Expectation of service levels Proliferation of security threats More Devices Users Connectivity Complexity Colliding Forces Vulnerabilities Threats Risk More Reduced budgets Less time to respond Fewer staff Less margin for error Economic realities 2012 Unisys Corporation. All rights reserved. 8

9 IT Analytics Drives Operational Change 2012 Unisys Corporation. All rights reserved. 9

10 End User Focus 5 Satisfied 4,5 4 Annoyed 3,5 3 Aggravated 2,5 Helpless Desk 2 1,5 1 0,5 0 <10 mins minutes minutes >20 minutes User Satisfaction by Resolution Timeframe 2012 Unisys Corporation. All rights reserved. 10

11 Transformation to a New Model Service delivery Optimized service delivery Service management Traditional Support Model Resolution Optimization Support Model 2 Resolvers 0 Self Help Fractionalized No End-to-End View Disparate Supply Chain Incongruent goals 3 1 Help Desk Field Dispatch No incentives to drive issues down to a lower level/cost 0 Fasthelp 1 2 Help Desk Field 3 Dispatch Resolvers All Support levels linked with ITIL-based processes Shared mission to drive cost out of support supply chain Intensely focused on continuous improvement at each component and throughout entire delivery chain ITSM Analytics 2012 Unisys Corporation. All rights reserved. 11

12 Cost Per Resolution Daily Incident Handling Rates by Support Personnel Ideal Resolution Optimization Model Shift Left $$$$ Technicians in the Field (Dispatch, Level 3) Client Resolver Teams 4-6 $$$ Specialist Remote Resolution (SD, Level 2) Service Desk (SD, Level 1) $$ Chat $ Self-Help Automation (Level 0) Shift Left Philosophy, when successfully implemented not only achieves resolution optimization but also increases productivity, decreases time to resolve, reduces cost, and improves user satisfaction 2012 Unisys Corporation. All rights reserved. 12

13 The Challenge in Shifting Left 3 rd Party Resolver- 18% L1 38% * In House Resolver 30% L2 3% Field 11% Roadblock hit when Resolvers 50% of Incident Handling 2012 Unisys Corporation. All rights reserved. 13

14 Current State of the Industry 45% 40% 35% 30% 40% 35% 30% 25% 25% 20% 15% 10% 5% 20% 15% 10% 5% 0% <10 Mins Mins Mins 0% <24 hrs hrs hrs hrs Average Handling Time Service Desk Mean Time to Resolve by Resolver Groups Current execution in the industry falls well short of Best Practices and represents tremendous opportunity to improve user satisfaction, decrease cost, and increase productivity 2012 Unisys Corporation. All rights reserved. 14

15 ITSM is the Control System Service Views of the Business Services Catalog Service Portal Service Desk BIG DATA Service Reports ITSM Core Cloud Governance CMDB Control Charts Service Impact App Management Event Management 2012 Unisys Corporation. All rights reserved. 15

16 Resolved Service Desk Support Flow Full Control Over the End-to-End Process End user encounters question or problem End user resolves via self service portal? End user contacts Service Desk Phone Web-Submit Alert Resolved Service Desk L2 Service Desk Agent Service Desk performs initial triage based on incident type; may use remote takeover to resolve. If not successful, then Dispatch is required or escalation to resolver ITSM Proper resource is identified based on incident type, location, and SLA. Service Desk maintains visibility to, and management of, referred incidents Deskside Deskside Technician Hardware Dispatch Software Dispatch Resolver Groups Hardware Dispatch Software Dispatch End-to-end service management system used by all participating suppliers to record, classify, update, and track incidents and requests Fully integrated technology enables smooth handoff to problem and analytics processes Legend - Internal SEO Analysis Review of all incidents, problems looking at patterns, providing continuous improvement, and root cause analysis Defect Reduction Proactive Resolution Mean Time To Resolve CSAT - External Resolvers 2012 Unisys Corporation. All rights reserved. 16

17 Key Points Ask your Support Teams for: Service Desk Average Handle Times by Agent If the answer is greater than 10 minutes you have an improvement and cost reduction opportunity Resolver group mean time to resolve If MMTR is greater than 24 hours you have a significant opportunity for improvement Support ECO system focus should be managed end to end Analytics provides the engine for real time governance and continuous improvement o Day to Day operations o Service Management and Incident elimination Governance over the entire eco system in real time is the critical Success Factor Continuous improvement must span all support functions and optimization of work must be unrelenting o Reducing resolver support workload should improve development timelines A Robust ITSM System, with Appropriate Analytics, and Intense Governance are the Critical Success Factors in Ensuring Effectiveness 2012 Unisys Corporation. All rights reserved. 17

18 Thank You Unisys key contacts Geoffrey Hogerwaard Marc Tossaint Unisys Corporation. All rights reserved. 18