SlideShare a Scribd company logo
1 of 14
Performance
Measurements for
WFM Processes
Debra Phillips,
Convergys, Global Consulting
Services
March 27, 2008
2© 2007 Convergys Corporation. All rights reserved.
Speaker Bio
Debra Phillips
 Extensive experience in strategic and operational functions of
Workforce Management in the Contact Center environment,
covering scheduling, forecasting, budgeting, and intraday
management process design, implementation, and operations.
Design and operational experience with IEX TotalView, Aspect
eWFM, and Avaya Call Routing, in multi-contact type and multi-
skilled agent environments.
 Earliest experience with software - Manpower Planning System
(TCS) 1.13.x (1991) Attended First TCS Group Conference
 Email - debra.l.phillips@convergys.com
3© 2007 Convergys Corporation. All rights reserved.
Agenda
Key Performance Measures for Best Practices through
end to end process
Key Metric Definition for Forecasting, Scheduling
How to calculate Metrics
 IEX TotalView
 Aspect eWFM
 Manual Template
Sample Baselines and Benchmarks
Convergys Best Practice Findings
4© 2007 Convergys Corporation. All rights reserved.
 The three major components of the end-to-end process are strongly
interconnected, yet each step has distinct deliverables that must be
managed separately.
 The performance of each step greatly impacts the end result of the
entire process.
Scheduling
• Optimized Shift Mix
• Completed/Filled
Schedules
Load Balancing
• Intra-Day Alerts
• Post-Day Performance
Reports
Key Performance Measures
• Schedule Quality Index
• Schedule Adherence
Index
Key Performance Measures
• Average Absolute
Value Variance
Key Performance Measures
• Agent Adherence
• Average Handle Time
• Cost per Call
• Service Level
• Occupancy
• Availability
• Average
Speed of
Answer
End-to-End
Performance
Measurements
Forecasting
Forecasts:
• Long-Term: 12-18 Month
(Monthly)
• Intermediate: 2-3 Month
(Interval)
• Schedule: 45 Day (Interval)
End-to-end process improvement increases process transparency
and accountability in driving toward efficiency
Key operational metrics measuring process efficiency &
effectiveness form the basis of analysis
5© 2007 Convergys Corporation. All rights reserved.
Forecasting Measure – Average Absolute Value Variance
(AAVV)
Concept - Measure of how closely the staff requirements,
call volume, and AHT forecasts created match actuals.
Calculating Absolute Value Variance by Interval from a
locked forecast at a pre determined timeframe.
Schedules are generated against interval forecast
requirements.
Generally using a forecast in a WFM tool.
Calculate for Volume Offered and AHT
Calculation:
 (Sum Total of Forecast (Volume) – Sum Total Absolute Variance
(Volume)) / Sum Total Forecast Volume
6© 2007 Convergys Corporation. All rights reserved.
AAVV
IEX Total View
 Capture Volume and AHT from
Intraday Performance screen
(IDP)
 Contact Types (CT) or Multi-
Contact Types
 Easy Export into excel
 Calculate for a Weekly period
Aspect eWFM
 Capture Volume and AHT from
Intraday screen - Customize
Tab
 Parent Forecast Groups (FG)
 Easy Export into excel
 Calculate for a Weekly Period
7© 2007 Convergys Corporation. All rights reserved.
AAVV - Baselines and Benchmarks - sample
AVV
Day FRCST CO FRCST% FRCST% Sum Diff
11/1 23,054 23,398 101.49% 92.33% 1794
11/2 22,921 22,519 98.25% 88.02% 2698
11/3 22,197 20,983 94.53% 87.65% 2591
11/4 14,640 13,450 91.87% 82.26% 2386
11/5 5,999 6,273 104.57% 87.29% 797
11/6 25,812 23,856 92.42% 88.21% 2812
11/7 23,710 23,200 97.85% 91.54% 1962
11/8 22,398 23,494 104.89% 92.56% 1747
11/9 21,011 21,785 103.68% 92.78% 1572
11/10 19,796 20,884 105.50% 87.64% 2581
11/11 13,605 13,603 99.99% 89.74% 1395
11/26 6,076 5,575 91.75% 82.91% 953
11/27 24,465 22,901 93.61% 90.52% 2172
11/28 22,959 20,631 89.86% 87.31% 2619
11/29 22,787 21,166 92.89% 90.72% 1964
11/30 21,784 21,663 99.44% 92.78% 1563
Metrics 572,892 552,651 96.47% 87.12% 73,788
All Res-Bili
10% Difference during Intervals
100 % Accuracy by end of Day
8© 2007 Convergys Corporation. All rights reserved.
AAVV - Baselines and Benchmarks - sample
DSG Interval Forecast Variance - May15th through May 21st
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
12:00
AM5:00
AM
10:00
AM3:00
PM8:00
PM1:00
AM6:00
AM
11:00
AM4:00
PM9:00
PM2:00
AM7:00
AM
12:00
PM5:00
PM
10:00
PM3:00
AM8:00
AM1:00
PM6:00
PM
11:00
PM4:00
AM9:00
AM2:00
PM7:00
PM
12:00
AM5:00
AM
10:00
AM3:00
PM8:00
PM1:00
AM6:00
AM
11:00
AM4:00
PM9:00
PM
PercentForecastVariance
Best Practice Range
9© 2007 Convergys Corporation. All rights reserved.
Scheduling Measure – Schedule Quality Index (SQI)
 Concept - Measure of how closely the schedules created match the
forecasted needs.
 Calculating Absolute Value Variance by Interval from a locked
planned forecast requirements at a pre determined timeframe for
schedule generation.
 Schedules are generated against interval forecast requirements plus
shrinkage or schedule overhead.
 Generally using schedules to planned forecast requirements in a
WFM tool. Static or Flex.
 Calculate for Schedules to be released to agent population.
 Calculation:
 (Sum Total of Forecast Reqs) – Sum Total Absolute Variance
Schedules to Fore)) / Sum Total Forecast Reqs
10© 2007 Convergys Corporation. All rights reserved.
SQI
IEX TotalView
 Utilize Performance
Analysis Report
From: 02/23/08 IEX TotalView 02/27/08
To: 02/29/08 MTS-ttlv 16:48
Shift: 0 All Day Performance Analysis
Management Unit: 302 Wireless - Cust Srv Page: 8
CT: 302 Wireless - Cust Srv
Date: Tuesday, 02/26/08
Sched ---------Weekly Plan------ -----Schedule---- -------Adherence------- --Seat Limits ( 0/9999)--
Time Open Req. Diff. O/U Req. O/U Est. O/U Dev. Occupied O/U Min Vacant
22:30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00
23:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00
23:30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00
Avgs: 10.00 11.06 0.57 1.06 11.06 1.06 9.90 1.17 5% 10.62 10.62 9988.38
Summary:
Forecasted Hours Required : 265.55 Schedule Open Hours : 240.08
Overhead Hours : 0.00 Schedule Hours Under : 30.07
Total Hours : 265.55 Schedule Hours Over : 4.60
Agents Scheduled: 50
For Req = 265.55
Tot Abs Var = 34.67
Diff = 230.88
SQI = 86.94 %
11© 2007 Convergys Corporation. All rights reserved.
SQI
Aspect eWFM
 Scheduling Runs – Staffing Basis to create new shifts or Test
current schedules.
 Schedule Efficiency in FTE Summary = Schedule Quality Index
(SQI)
Schedule Efficiency 85.54
Scheduled FTE 310.00
Schedule Inflexibility 5.14
SG-CSCW
FTE Summary
Required FTE 294.06
12© 2007 Convergys Corporation. All rights reserved.
SQI – Sample Worksheet
Sunday Monday Tuesday WednesdayThursday Friday Saturday WEEK
Date 11/05/06 11/06/06 11/07/06 11/08/06 11/09/06 11/10/06 11/11/06 TOTAL
Pulled Thursday 10/26/2006 - Schedules released
Summary:
Forecast Hours Required 310.90 1429.41 1312.62 1277.70 1214.19 1163.95 778.86 7487.63
Overhead Hours 102.60 468.95 430.68 419.09 398.37 381.85 255.43 2456.97
Total Hours 413.50 1898.36 1743.30 1696.79 1612.56 1545.80 1034.29 9944.60
Schedule Open Hours 453.75 1862.50 1795.75 1801.75 1676.00 1597.25 1106.25 10293.25
Schedule Hours Under 4.26 91.96 43.13 40.81 46.31 44.59 28.79 299.85
Schedule Hours Over 44.51 56.09 95.57 145.76 109.74 96.04 101.09 648.80
Agents 66 305 290 283 271 267 156
Schedule Quality Index
Z = TH - ( SHU +SHO) 364.73 1750.31 1604.6 1510.22 1456.51 1405.17 904.41 8995.95
ABS(Z) / TH 88.2% 92.2% 92.0% 89.0% 90.3% 90.9% 87.4% 90.5%
13© 2007 Convergys Corporation. All rights reserved.
SQI – Baseline and Benchmark - sample
RC2 Schedule Quality Index
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
8/20/2006
8/27/2006
9/3/2006
9/10/2006
9/17/2006
9/24/2006
10/1/2006
10/8/200610/15/200610/22/200610/29/2006
11/5/200611/12/200611/19/200611/26/2006
12/3/200612/10/200612/17/200612/24/2006
IEX Implementation Timeline
Percent
RES REPAIR Linear (RES REPAIR)
14© 2007 Convergys Corporation. All rights reserved.
Best Practice Findings - notes
 SQI can be used as a qualitative evaluation of schedule mixes with
shift types and work rules.
 SQI must include Shrinkage/Schedule Overhead
 Be Flexible with Tool settings to achieve desired results.
 Don’t get hung up on numbers. Baseline yours and establish
continuous feedback loop for improvement.
 SQI – Best Practice - 95 %
 AVV – Best Practice - 90-95%
 Other Measures
 Staffing Adherence Index (SAI) -
Measure of how closely agents were staffed into the assigned schedules.
 Aggregate Schedule Adherence -
Measure of how closely agents/centers followed the plan net staff plan.

More Related Content

What's hot

Workday training for_employees
Workday training for_employeesWorkday training for_employees
Workday training for_employeesbgadicha
 
Deep Learning Technical Pitch Deck
Deep Learning Technical Pitch DeckDeep Learning Technical Pitch Deck
Deep Learning Technical Pitch DeckNicholas Vossburg
 
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...Power BI Interview Questions and Answers | Power BI Certification | Power BI ...
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...Edureka!
 
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15BizLibrary
 
How RPA Technology is Automating HR to Save Time & Increase Productivity
How RPA Technology is Automating HR to Save Time & Increase ProductivityHow RPA Technology is Automating HR to Save Time & Increase Productivity
How RPA Technology is Automating HR to Save Time & Increase ProductivityUiPath
 
Oracle Service Cloud overview
Oracle Service Cloud overviewOracle Service Cloud overview
Oracle Service Cloud overviewBang Ta
 
Workforce forecasting & planning Introduction for recruiters - Workshop summary
Workforce forecasting & planning Introduction for recruiters - Workshop summaryWorkforce forecasting & planning Introduction for recruiters - Workshop summary
Workforce forecasting & planning Introduction for recruiters - Workshop summaryAlexander Crépin
 
Building a Center of Excellence for your Salesforce crm team
Building a Center of Excellence for your Salesforce crm teamBuilding a Center of Excellence for your Salesforce crm team
Building a Center of Excellence for your Salesforce crm teamBuyan Thyagarajan
 
PowerPivot and PowerQuery
PowerPivot and PowerQueryPowerPivot and PowerQuery
PowerPivot and PowerQueryin4400
 
Power BI Full Course | Power BI Tutorial for Beginners | Edureka
Power BI Full Course | Power BI Tutorial for Beginners | EdurekaPower BI Full Course | Power BI Tutorial for Beginners | Edureka
Power BI Full Course | Power BI Tutorial for Beginners | EdurekaEdureka!
 
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas Dussurget
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas DussurgetHow to Implement SLAs and Metrics in JIRA Service Desk - Lucas Dussurget
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas DussurgetAtlassian
 
Agile_Jira_Presentation_1.pptx
Agile_Jira_Presentation_1.pptxAgile_Jira_Presentation_1.pptx
Agile_Jira_Presentation_1.pptxknowworld
 
Oracle Planning and Budgeting Cloud Service
Oracle Planning and Budgeting Cloud ServiceOracle Planning and Budgeting Cloud Service
Oracle Planning and Budgeting Cloud ServiceDatavail
 
SOA in Financial Services
SOA in Financial ServicesSOA in Financial Services
SOA in Financial ServicesMike Walker
 
Power BI Reporting & Project Online
Power BI Reporting & Project OnlinePower BI Reporting & Project Online
Power BI Reporting & Project OnlineHari Thapliyal
 
SAP Sapsuccessfactors Introduction
SAP Sapsuccessfactors  Introduction SAP Sapsuccessfactors  Introduction
SAP Sapsuccessfactors Introduction Sap HCM
 

What's hot (20)

Workday training for_employees
Workday training for_employeesWorkday training for_employees
Workday training for_employees
 
Deep Learning Technical Pitch Deck
Deep Learning Technical Pitch DeckDeep Learning Technical Pitch Deck
Deep Learning Technical Pitch Deck
 
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...Power BI Interview Questions and Answers | Power BI Certification | Power BI ...
Power BI Interview Questions and Answers | Power BI Certification | Power BI ...
 
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15
How to Measure the Impact of Employee Soft Skills Training | Webinar 02.17.15
 
Jira
JiraJira
Jira
 
How RPA Technology is Automating HR to Save Time & Increase Productivity
How RPA Technology is Automating HR to Save Time & Increase ProductivityHow RPA Technology is Automating HR to Save Time & Increase Productivity
How RPA Technology is Automating HR to Save Time & Increase Productivity
 
Oracle Service Cloud overview
Oracle Service Cloud overviewOracle Service Cloud overview
Oracle Service Cloud overview
 
Oracle EPM/BI Overview
Oracle EPM/BI OverviewOracle EPM/BI Overview
Oracle EPM/BI Overview
 
Workforce forecasting & planning Introduction for recruiters - Workshop summary
Workforce forecasting & planning Introduction for recruiters - Workshop summaryWorkforce forecasting & planning Introduction for recruiters - Workshop summary
Workforce forecasting & planning Introduction for recruiters - Workshop summary
 
Building a Center of Excellence for your Salesforce crm team
Building a Center of Excellence for your Salesforce crm teamBuilding a Center of Excellence for your Salesforce crm team
Building a Center of Excellence for your Salesforce crm team
 
PowerPivot and PowerQuery
PowerPivot and PowerQueryPowerPivot and PowerQuery
PowerPivot and PowerQuery
 
Power BI Full Course | Power BI Tutorial for Beginners | Edureka
Power BI Full Course | Power BI Tutorial for Beginners | EdurekaPower BI Full Course | Power BI Tutorial for Beginners | Edureka
Power BI Full Course | Power BI Tutorial for Beginners | Edureka
 
Power BI Overview
Power BI Overview Power BI Overview
Power BI Overview
 
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas Dussurget
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas DussurgetHow to Implement SLAs and Metrics in JIRA Service Desk - Lucas Dussurget
How to Implement SLAs and Metrics in JIRA Service Desk - Lucas Dussurget
 
Quality Engineering in the New
Quality Engineering in the New Quality Engineering in the New
Quality Engineering in the New
 
Agile_Jira_Presentation_1.pptx
Agile_Jira_Presentation_1.pptxAgile_Jira_Presentation_1.pptx
Agile_Jira_Presentation_1.pptx
 
Oracle Planning and Budgeting Cloud Service
Oracle Planning and Budgeting Cloud ServiceOracle Planning and Budgeting Cloud Service
Oracle Planning and Budgeting Cloud Service
 
SOA in Financial Services
SOA in Financial ServicesSOA in Financial Services
SOA in Financial Services
 
Power BI Reporting & Project Online
Power BI Reporting & Project OnlinePower BI Reporting & Project Online
Power BI Reporting & Project Online
 
SAP Sapsuccessfactors Introduction
SAP Sapsuccessfactors  Introduction SAP Sapsuccessfactors  Introduction
SAP Sapsuccessfactors Introduction
 

Similar to Performance Measurements for WFM Processes - Convergys

18 Apr 2015 NWFSC PMI presentation v7
18 Apr 2015 NWFSC PMI presentation v718 Apr 2015 NWFSC PMI presentation v7
18 Apr 2015 NWFSC PMI presentation v7Michael Cary
 
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing Industry
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing IndustryOverall Equipment Efficiency - A Next-Gen KPI for the Manufacturing Industry
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing IndustryInfoStream Solutions
 
161025_Acheivments and Projects
161025_Acheivments and Projects161025_Acheivments and Projects
161025_Acheivments and ProjectsMohamed Roushdy
 
Dynamic task scheduling on multicore automotive ec us
Dynamic task scheduling on multicore automotive ec usDynamic task scheduling on multicore automotive ec us
Dynamic task scheduling on multicore automotive ec usVLSICS Design
 
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSDYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSVLSICS Design
 
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSDYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSVLSICS Design
 
Cs 568 Spring 10 Lecture 5 Estimation
Cs 568 Spring 10  Lecture 5 EstimationCs 568 Spring 10  Lecture 5 Estimation
Cs 568 Spring 10 Lecture 5 EstimationLawrence Bernstein
 
Finalising FRS for ERP of S&T deptt in Indian Railways
Finalising FRS for ERP of  S&T deptt in Indian RailwaysFinalising FRS for ERP of  S&T deptt in Indian Railways
Finalising FRS for ERP of S&T deptt in Indian RailwaysIndian Railways
 
OTS - Everything you wanted to know but didn't ask
OTS - Everything you wanted to know but didn't askOTS - Everything you wanted to know but didn't ask
OTS - Everything you wanted to know but didn't askJeff Hackney
 
Forecasting Capacity Issues in Stateful Systems: A Proactive Approach
Forecasting Capacity Issues in Stateful Systems: A Proactive ApproachForecasting Capacity Issues in Stateful Systems: A Proactive Approach
Forecasting Capacity Issues in Stateful Systems: A Proactive ApproachIRJET Journal
 
EXTENT-2016: Test Automation and Agile Testing
EXTENT-2016: Test Automation and Agile TestingEXTENT-2016: Test Automation and Agile Testing
EXTENT-2016: Test Automation and Agile TestingIosif Itkin
 
Value add: Single User Performance Testing (http://managingperformancetesting...
Value add: Single User Performance Testing (http://managingperformancetesting...Value add: Single User Performance Testing (http://managingperformancetesting...
Value add: Single User Performance Testing (http://managingperformancetesting...akbollinger
 
Mellor Consulting Group approach toward a BKM OEE deployment
Mellor Consulting Group approach toward a BKM OEE deployment Mellor Consulting Group approach toward a BKM OEE deployment
Mellor Consulting Group approach toward a BKM OEE deployment Mellor Consulting Group
 
Factory talk
Factory talkFactory talk
Factory talkJohn H
 
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...gerogepatton
 
E g innovations
E g innovationsE g innovations
E g innovationsdvmug1
 
eG Innovations, How to.. VDI Performance
eG Innovations, How to.. VDI PerformanceeG Innovations, How to.. VDI Performance
eG Innovations, How to.. VDI Performancesubtitle
 
Earned schedule - concept and technique
Earned schedule - concept and techniqueEarned schedule - concept and technique
Earned schedule - concept and techniqueSanjeevaniSathe
 

Similar to Performance Measurements for WFM Processes - Convergys (20)

18 Apr 2015 NWFSC PMI presentation v7
18 Apr 2015 NWFSC PMI presentation v718 Apr 2015 NWFSC PMI presentation v7
18 Apr 2015 NWFSC PMI presentation v7
 
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing Industry
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing IndustryOverall Equipment Efficiency - A Next-Gen KPI for the Manufacturing Industry
Overall Equipment Efficiency - A Next-Gen KPI for the Manufacturing Industry
 
161025_Acheivments and Projects
161025_Acheivments and Projects161025_Acheivments and Projects
161025_Acheivments and Projects
 
Dynamic task scheduling on multicore automotive ec us
Dynamic task scheduling on multicore automotive ec usDynamic task scheduling on multicore automotive ec us
Dynamic task scheduling on multicore automotive ec us
 
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSDYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
 
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUSDYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
DYNAMIC TASK SCHEDULING ON MULTICORE AUTOMOTIVE ECUS
 
Cs 568 Spring 10 Lecture 5 Estimation
Cs 568 Spring 10  Lecture 5 EstimationCs 568 Spring 10  Lecture 5 Estimation
Cs 568 Spring 10 Lecture 5 Estimation
 
Finalising FRS for ERP of S&T deptt in Indian Railways
Finalising FRS for ERP of  S&T deptt in Indian RailwaysFinalising FRS for ERP of  S&T deptt in Indian Railways
Finalising FRS for ERP of S&T deptt in Indian Railways
 
OTS - Everything you wanted to know but didn't ask
OTS - Everything you wanted to know but didn't askOTS - Everything you wanted to know but didn't ask
OTS - Everything you wanted to know but didn't ask
 
Forecasting Capacity Issues in Stateful Systems: A Proactive Approach
Forecasting Capacity Issues in Stateful Systems: A Proactive ApproachForecasting Capacity Issues in Stateful Systems: A Proactive Approach
Forecasting Capacity Issues in Stateful Systems: A Proactive Approach
 
EXTENT-2016: Test Automation and Agile Testing
EXTENT-2016: Test Automation and Agile TestingEXTENT-2016: Test Automation and Agile Testing
EXTENT-2016: Test Automation and Agile Testing
 
Value add: Single User Performance Testing (http://managingperformancetesting...
Value add: Single User Performance Testing (http://managingperformancetesting...Value add: Single User Performance Testing (http://managingperformancetesting...
Value add: Single User Performance Testing (http://managingperformancetesting...
 
Mellor Consulting Group approach toward a BKM OEE deployment
Mellor Consulting Group approach toward a BKM OEE deployment Mellor Consulting Group approach toward a BKM OEE deployment
Mellor Consulting Group approach toward a BKM OEE deployment
 
Factory talk
Factory talkFactory talk
Factory talk
 
7 2prevent main
7 2prevent main7 2prevent main
7 2prevent main
 
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...
Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Constructi...
 
Earned Value Management - Foundation
Earned Value Management - FoundationEarned Value Management - Foundation
Earned Value Management - Foundation
 
E g innovations
E g innovationsE g innovations
E g innovations
 
eG Innovations, How to.. VDI Performance
eG Innovations, How to.. VDI PerformanceeG Innovations, How to.. VDI Performance
eG Innovations, How to.. VDI Performance
 
Earned schedule - concept and technique
Earned schedule - concept and techniqueEarned schedule - concept and technique
Earned schedule - concept and technique
 

Performance Measurements for WFM Processes - Convergys

  • 1. Performance Measurements for WFM Processes Debra Phillips, Convergys, Global Consulting Services March 27, 2008
  • 2. 2© 2007 Convergys Corporation. All rights reserved. Speaker Bio Debra Phillips  Extensive experience in strategic and operational functions of Workforce Management in the Contact Center environment, covering scheduling, forecasting, budgeting, and intraday management process design, implementation, and operations. Design and operational experience with IEX TotalView, Aspect eWFM, and Avaya Call Routing, in multi-contact type and multi- skilled agent environments.  Earliest experience with software - Manpower Planning System (TCS) 1.13.x (1991) Attended First TCS Group Conference  Email - debra.l.phillips@convergys.com
  • 3. 3© 2007 Convergys Corporation. All rights reserved. Agenda Key Performance Measures for Best Practices through end to end process Key Metric Definition for Forecasting, Scheduling How to calculate Metrics  IEX TotalView  Aspect eWFM  Manual Template Sample Baselines and Benchmarks Convergys Best Practice Findings
  • 4. 4© 2007 Convergys Corporation. All rights reserved.  The three major components of the end-to-end process are strongly interconnected, yet each step has distinct deliverables that must be managed separately.  The performance of each step greatly impacts the end result of the entire process. Scheduling • Optimized Shift Mix • Completed/Filled Schedules Load Balancing • Intra-Day Alerts • Post-Day Performance Reports Key Performance Measures • Schedule Quality Index • Schedule Adherence Index Key Performance Measures • Average Absolute Value Variance Key Performance Measures • Agent Adherence • Average Handle Time • Cost per Call • Service Level • Occupancy • Availability • Average Speed of Answer End-to-End Performance Measurements Forecasting Forecasts: • Long-Term: 12-18 Month (Monthly) • Intermediate: 2-3 Month (Interval) • Schedule: 45 Day (Interval) End-to-end process improvement increases process transparency and accountability in driving toward efficiency Key operational metrics measuring process efficiency & effectiveness form the basis of analysis
  • 5. 5© 2007 Convergys Corporation. All rights reserved. Forecasting Measure – Average Absolute Value Variance (AAVV) Concept - Measure of how closely the staff requirements, call volume, and AHT forecasts created match actuals. Calculating Absolute Value Variance by Interval from a locked forecast at a pre determined timeframe. Schedules are generated against interval forecast requirements. Generally using a forecast in a WFM tool. Calculate for Volume Offered and AHT Calculation:  (Sum Total of Forecast (Volume) – Sum Total Absolute Variance (Volume)) / Sum Total Forecast Volume
  • 6. 6© 2007 Convergys Corporation. All rights reserved. AAVV IEX Total View  Capture Volume and AHT from Intraday Performance screen (IDP)  Contact Types (CT) or Multi- Contact Types  Easy Export into excel  Calculate for a Weekly period Aspect eWFM  Capture Volume and AHT from Intraday screen - Customize Tab  Parent Forecast Groups (FG)  Easy Export into excel  Calculate for a Weekly Period
  • 7. 7© 2007 Convergys Corporation. All rights reserved. AAVV - Baselines and Benchmarks - sample AVV Day FRCST CO FRCST% FRCST% Sum Diff 11/1 23,054 23,398 101.49% 92.33% 1794 11/2 22,921 22,519 98.25% 88.02% 2698 11/3 22,197 20,983 94.53% 87.65% 2591 11/4 14,640 13,450 91.87% 82.26% 2386 11/5 5,999 6,273 104.57% 87.29% 797 11/6 25,812 23,856 92.42% 88.21% 2812 11/7 23,710 23,200 97.85% 91.54% 1962 11/8 22,398 23,494 104.89% 92.56% 1747 11/9 21,011 21,785 103.68% 92.78% 1572 11/10 19,796 20,884 105.50% 87.64% 2581 11/11 13,605 13,603 99.99% 89.74% 1395 11/26 6,076 5,575 91.75% 82.91% 953 11/27 24,465 22,901 93.61% 90.52% 2172 11/28 22,959 20,631 89.86% 87.31% 2619 11/29 22,787 21,166 92.89% 90.72% 1964 11/30 21,784 21,663 99.44% 92.78% 1563 Metrics 572,892 552,651 96.47% 87.12% 73,788 All Res-Bili 10% Difference during Intervals 100 % Accuracy by end of Day
  • 8. 8© 2007 Convergys Corporation. All rights reserved. AAVV - Baselines and Benchmarks - sample DSG Interval Forecast Variance - May15th through May 21st 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 12:00 AM5:00 AM 10:00 AM3:00 PM8:00 PM1:00 AM6:00 AM 11:00 AM4:00 PM9:00 PM2:00 AM7:00 AM 12:00 PM5:00 PM 10:00 PM3:00 AM8:00 AM1:00 PM6:00 PM 11:00 PM4:00 AM9:00 AM2:00 PM7:00 PM 12:00 AM5:00 AM 10:00 AM3:00 PM8:00 PM1:00 AM6:00 AM 11:00 AM4:00 PM9:00 PM PercentForecastVariance Best Practice Range
  • 9. 9© 2007 Convergys Corporation. All rights reserved. Scheduling Measure – Schedule Quality Index (SQI)  Concept - Measure of how closely the schedules created match the forecasted needs.  Calculating Absolute Value Variance by Interval from a locked planned forecast requirements at a pre determined timeframe for schedule generation.  Schedules are generated against interval forecast requirements plus shrinkage or schedule overhead.  Generally using schedules to planned forecast requirements in a WFM tool. Static or Flex.  Calculate for Schedules to be released to agent population.  Calculation:  (Sum Total of Forecast Reqs) – Sum Total Absolute Variance Schedules to Fore)) / Sum Total Forecast Reqs
  • 10. 10© 2007 Convergys Corporation. All rights reserved. SQI IEX TotalView  Utilize Performance Analysis Report From: 02/23/08 IEX TotalView 02/27/08 To: 02/29/08 MTS-ttlv 16:48 Shift: 0 All Day Performance Analysis Management Unit: 302 Wireless - Cust Srv Page: 8 CT: 302 Wireless - Cust Srv Date: Tuesday, 02/26/08 Sched ---------Weekly Plan------ -----Schedule---- -------Adherence------- --Seat Limits ( 0/9999)-- Time Open Req. Diff. O/U Req. O/U Est. O/U Dev. Occupied O/U Min Vacant 22:30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00 23:00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00 23:30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 * 0.00 0.00 9999.00 Avgs: 10.00 11.06 0.57 1.06 11.06 1.06 9.90 1.17 5% 10.62 10.62 9988.38 Summary: Forecasted Hours Required : 265.55 Schedule Open Hours : 240.08 Overhead Hours : 0.00 Schedule Hours Under : 30.07 Total Hours : 265.55 Schedule Hours Over : 4.60 Agents Scheduled: 50 For Req = 265.55 Tot Abs Var = 34.67 Diff = 230.88 SQI = 86.94 %
  • 11. 11© 2007 Convergys Corporation. All rights reserved. SQI Aspect eWFM  Scheduling Runs – Staffing Basis to create new shifts or Test current schedules.  Schedule Efficiency in FTE Summary = Schedule Quality Index (SQI) Schedule Efficiency 85.54 Scheduled FTE 310.00 Schedule Inflexibility 5.14 SG-CSCW FTE Summary Required FTE 294.06
  • 12. 12© 2007 Convergys Corporation. All rights reserved. SQI – Sample Worksheet Sunday Monday Tuesday WednesdayThursday Friday Saturday WEEK Date 11/05/06 11/06/06 11/07/06 11/08/06 11/09/06 11/10/06 11/11/06 TOTAL Pulled Thursday 10/26/2006 - Schedules released Summary: Forecast Hours Required 310.90 1429.41 1312.62 1277.70 1214.19 1163.95 778.86 7487.63 Overhead Hours 102.60 468.95 430.68 419.09 398.37 381.85 255.43 2456.97 Total Hours 413.50 1898.36 1743.30 1696.79 1612.56 1545.80 1034.29 9944.60 Schedule Open Hours 453.75 1862.50 1795.75 1801.75 1676.00 1597.25 1106.25 10293.25 Schedule Hours Under 4.26 91.96 43.13 40.81 46.31 44.59 28.79 299.85 Schedule Hours Over 44.51 56.09 95.57 145.76 109.74 96.04 101.09 648.80 Agents 66 305 290 283 271 267 156 Schedule Quality Index Z = TH - ( SHU +SHO) 364.73 1750.31 1604.6 1510.22 1456.51 1405.17 904.41 8995.95 ABS(Z) / TH 88.2% 92.2% 92.0% 89.0% 90.3% 90.9% 87.4% 90.5%
  • 13. 13© 2007 Convergys Corporation. All rights reserved. SQI – Baseline and Benchmark - sample RC2 Schedule Quality Index 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 8/20/2006 8/27/2006 9/3/2006 9/10/2006 9/17/2006 9/24/2006 10/1/2006 10/8/200610/15/200610/22/200610/29/2006 11/5/200611/12/200611/19/200611/26/2006 12/3/200612/10/200612/17/200612/24/2006 IEX Implementation Timeline Percent RES REPAIR Linear (RES REPAIR)
  • 14. 14© 2007 Convergys Corporation. All rights reserved. Best Practice Findings - notes  SQI can be used as a qualitative evaluation of schedule mixes with shift types and work rules.  SQI must include Shrinkage/Schedule Overhead  Be Flexible with Tool settings to achieve desired results.  Don’t get hung up on numbers. Baseline yours and establish continuous feedback loop for improvement.  SQI – Best Practice - 95 %  AVV – Best Practice - 90-95%  Other Measures  Staffing Adherence Index (SAI) - Measure of how closely agents were staffed into the assigned schedules.  Aggregate Schedule Adherence - Measure of how closely agents/centers followed the plan net staff plan.