Advanced Real World Help Desk with System Center 2012 SP1 Service ManagerKristina AshmentSr. Program ManagerMicrosoft

Doug HiteOperations EngineerMicrosoft

SD-B316

Who are we? Cloud & Datacenter Management

(STB) Server & Tools Business (CDM) Cloud & Datacenter

Management

Tier 1 & Monitoring Team supporting over 10,000 Servers

Call Centers in Redmond & Hyderabad

Two Help Desks: Infrastructure Requests/Team (IR)

Service Requests/Applications Team (SR)

microsoft.com – MSDN - TechNet WindowsUpdate - Windows

Intune

TIER 1 24x7 Helpdesk

TIER 2 & 3 Engineering Team

Operations Manager

Service Manager

Config Manager

CU

BE

SITES MONITORED BY CDM

Session Objectives And Takeaways

Discuss challenges facing IT Operations & Call Centers that use

Operations Manager & Service Manager

Key takeaways:

Leverage out of the box System Center reporting and how to build complex reporting scenarios Using Service Manager 2012, Operations Manager & Configuration Manager data to improved

your business

STAFFING LEVELS

ENGINEERING COSTS

COST PER TICKET/ALERT

MEASURE SLA PLANNING & FORECAST

MONITORING COSTS

• Who are the Top Performers?

• What is the cost by Analyst, Shift or Location?

• Who is driving down (or up) your SLA Commitments?

EMPLOYEEPERFORMAN

CE

• What is the cost of each System or Server?

• What is the growth rate?• Cost by Business Group?

FORECAST &CAPACITY PLANNING

Problems to solve

• Service Level Agreement commitments being met?

• Area’s for improvement?

• Problem Management

SLACOMPLIANCE

• Engineering Staffing Level’s

• Fewer Alerts/Small DB’s• Escalations cost

time/money

COSTSAVINGS

CUBE – Metrics Defined

INFRASTRUCTURE HELPDESK (IR)

(IR) Infrastructure Request:IR Driver: Operations Manager Alerts

APPLICATION HELPDESK (SR)

(SR) Service Requests:SR Driver: Email & Phone Calls

TOTAL IR/SRESCALATED IN SLA (TTE IN/SLA) ESCALATED OUT of SLA (ESC OUT/SLA)

FIRST TOUCH RESOLUTION (FTR)Closed In SLA (% FTR In SLA) Closed Out SLA (% FTR Out/SLA)

ACTIONABLE (Worked/Billed) NON-ACTIONABLE (Not Worked or Billed)

AVG Time To ESC IN SLA (AVG TTE IN/SLA)AVG Time ESC Out of SLA (AVG TTE

OUT/SLA)AVG Time To Closed IN SLA (AVG TTC IN/SLA)

AVG Time Closed Out SLA (AVG TTC OUT/SLA)

Help Desk Tier 1

Measuring Team Performance Adding “Assigned To” shows

individual metrics

Volumes worked, In/Out of SLA FTR (First Touch Resolution) & TTE (Time to Escalate)

Building on the Core Metrics Add additional SM Queue’s to measure

Tier 1Tier 3 SLA impact?

Add Cost to Tier 2 & 3 shows the financial impact for staffing.

Supported Business Units

How SM data shows the cost of their team:

By Org, Property, SE or Server, the top Alert Generators Cost of the services by Organization, Property, Server & Engineer Growth Projections, what are the past volumes telling us about our current

business?

Problem Management Reports to T2/T3 have significantly reduced total Alert Volumes from SCOM SCOM Management Pack clean underway, Engineers have a better sense of

their systems

Operations Manager: Fine-Tuning (MP-IR Report)

How SM Cube improves OMAdding OM MP data makes for easy fine-tuning; What MP’s (Management Pack) are noisy, which

one’s to address first

Pulling in the OM data aligned with SM IR’s; No more hunting for an MP monitor to adjust.

Technical Challenges

Usability Not enough granular history data Incident doesn’t easily map to what

generated it? Custom calculations

What We Built

Tables

Udf’s

JobsOperations Manager DB

Tables

DWDataMart Database

Views

Service Manager DB

Tables

ETL

MPSD_DataMart Databasedbo Schema

ETL

Select From

Tables

Stage Schema

Views

Tables

Audit Schema

Designed for usability from the start

Create business specific views Benefited usability of resulting cube

Collapse 160 views into 72

Re-use the Service Manager DW where possible

Eliminates the need to move data Assumes SCSM DW is accurate Allows for SCSM to change the tables without impacting cube processing

Demo

How it works?

Getting OpsMgr Alert data

Setup Auditin

g

Retrieve Server List

• Stage_Alert• Stage_BaseManagedEnt

iity• Stage_ManagedType• Stage_ManagementPac

k• Stage_Monitor• Stage_Rules

Correlating Alert to incident

Factless* fact table with Service Manager incidentdim view to get Incident key

Managed Entity

Incident

Mgmt Pack

Monitor Rule Alert

What we get in our cube

Control the calculations Split out by Support Tier Assist in troubleshooting and

maintenance

Control the grain Cube grain in Incident or Service

request Provide drill through into incident

details

TOTAL IR/SRESCALATED IN SLA (TTE IN/SLA) ESCALATED OUT of SLA (ESC OUT/SLA)

FIRST TOUCH RESOLUTION (FTR)

Closed In SLA (% FTR In SLA) Closed Out SLA (% FTR Out/SLA)

ACTIONABLE (Worked/Billed) NON-ACTIONABLE (Not Worked or Billed)

AVG Time To ESC IN SLA (AVG TTE IN/SLA)AVG Time ESC Out of SLA (AVG TTE

OUT/SLA)AVG Time To Closed IN SLA (AVG TTC

IN/SLA)AVG Time Closed Out SLA (AVG TTC

OUT/SLA)

DIMENSIONS

IncidentsCurrent Tier

QueueCurrent ClassificationIncident Alert

Source

Status

Product

Tier 1 Analyst

Escalation State

MEASURES

Total Time in Minutes

AVE TTE

Incident Count

TTC

TTEAlert Count

Incident

Request

…

Lessons learned – Building the Cube

Separate cubes for IRs and SRs No dependencies between work item typesBetter allocation of resources

Split ETLS into 2 one for IR and SR jobs SR job finishes in under a minute runs every hour and provide near real

time data from CUBE

Write more ETLs to protect against changes in SM

JULY AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JULY AUG SEPT OCT NOV DEC0

10000

20000

30000

40000

50000

60000

48215

52124

4602447774

41087

38042

42004

34024

2987028705

30316

21957

1542514862 13492 14087 1479812123

6307 5740 5194 5786 6771 4567 5479 6393 5192 5601 6601 7042 63007406 7950 7875 7783 6972

33%

46% 45%

66%

58%

45% 46%49%

54% 54%

68%60%

78% 76%

84% 86%81%

87%

Help Desk Improvements

Goal 80%

CUBE Version 1 CUBE Version 2

WORKED IR’S

TOTAL IR’S IN - SLA COST

$135K

$122K

$118K

Forecast & Capacity Planning

Building on our OM & SM CUBE, we will add Configuration Manager data:

What is the cost of an ‘old’ physical server vs. a new Azure VM? What does the Monitoring footprint look like, where do we need new management

servers?

What we look at in the CUBE for Planning:

What hardware (property) is creating the most work in T1? And measure those alerts across all Tiers.

What does the growing data volumes tell us and what is the cost to manage these volumes?

Adding CM data will give us a complete picture of our Hosting & Engineering Cost & Performance.

Building on the Cube - VNext

Core requirements met!

Expand the reports by adding in other systems.

SERVICE MANAGER

OPERATIONS MANAGER

CONFIGURATION MANGER

Service Level Agreements

Employee Performance Cost Analysis by

Employee Problem Management

Top MP IR Generators Cost of the OM

System Alerts by OM System Forecast & Planning

HW Specific Reports Cost of Physicals vs.

VM’s What HW costs to run Forecast & Planning

Key takeaways

What advice we offer for those preparing to do a similar exercise

Things we learned the hard way and wish we knew upfront

QUESTIONS

Evaluation

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© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.