I lss reduction%20in%20aht%2713 final

Proprietary and ConfidentialJuly 30, 2014 - 1 -
Reduction in Average handle Time
(AHT) for Service desk project
Name & Employee ID of the Team Members:
Pavithra Dhanabal , Love Gaur , Jayaraju Wundri Gundra & Pallavi Panda.
Project ID:102988
Account Name: RBC
Executing BU: IMS
Project Start Date: March 2013
iEvolve iLSS Green Belt Project Case Study

Business Case

Business Case
 Description: iGATE technical Help desk provides services for an esteemed client. The different Business Units (BU) for the
client are classified into different client base .Each stream has pre-defined skill sets where the calls are routed (Appendix
A).Stream 1 consists of callers from the client base Branch who directly impact the revenue for RBC. 26.5% of the
transactions are carried out in Stream 1 .Hence reducing the Average handle Time (AHT) for Stream 1 Business unit will
have a positive feedback on the Help Desk.
 Specific problem Statement: In reference to the graph below , there were multiple related SLA (Appendix B) that were
impacted when there were peaks in Stream1 AHT. Hence reducing the AHT of Stream 1 by optimizing the processes in
Stream 1 call handling will influence the overall AHT .
Note: Branch client base will be referred as Stream 1 in this presentation.
Impact : Focus on identifying the right AHT and identifying processes that will impact the AHT for Stream 1. There is also an
impact to the overall Gross margin for iGATE.
Month
Actual
FTE
GOS
Stream 1
Calls
Answered
Oct-12 36 71.37% 12997
Nov-12 32 72.03% 12198
Dec-12 37 84.11% 10442
Jan-13 32 89.96% 13838
Feb-13 30 79.01% 12922
Mar-13 35 84.54% 13440
978
837
806 812 811
784
4 4
1
0
2
1
0
1
1
2
2
3
3
4
4
5
600
650
700
750
800
850
900
950
1000
Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13
Old Batch Target AHT SLA Missed

Define

Project Charter
Project Name : Reduction in Average handle Time (AHT) for a Service desk project Date: 01-March-13
Project Objective To reduce the Average handle Time for Stream 1 from 784 seconds to 700 seconds by 31-Oct-2013.This
will have a positive impact on the overall AHT of the service desk facilitating us to meet the multiple
other SLA incorporated along with it.
Expected Annualized Savings (USD) $13,608.00( cost savings on account of reduction of FTE )
Project Scope In Scope: AHT for Stream 1
 Out of Scope: AHT of other Streams (Stream 2, DBI & Dexia).
 Other tiers in TSC (Incident Management team )
 Stream 1 transition team is excluded from this as they have a transition phase of 4 weeks since the
date they go live.
Project Schedule Team Members and other Resources
Project Identification 01-March-2013 Champion Mudit Chowdhry
Define 01-March-2013 MBB Manish Mehta
Measure 15-April-2013 BB Pearl J. Pereira
Analyze 28-June-2013 GB Pallavi Panda
Improve / Design 30-July-2013 GB Pavithra Dhanabal
Control / Verify 31-Oct-2013 GB Love Gaur
Close 31-Oct-2013 GB Jayaraju Wundri Gundra
Team members Viswanath Ravindran.
Other Resources: Transactional Quality team, Analyst from Stream 1,2 and 5.
D M A I C

Details of Saving Estimation
 Savings to the Project can be directly related to Grade Of Service (GOS) which is an SLA and directly related to the FTE required to
handle the volume.
 As indicated in the graph below, we will be able to save 6 resources by reducing the AHT by 84 sec
 Savings for 6 FTE is 6(FTE)* 9(working hrs.)*21(Working days)*12(months)*5.6 (cost/hr offshore)= $13,608.00
Other benefits:
 Resource Optimization
 Customer Satisfaction as resolution is faster
Actual AHT 784
Proposed AHT 700
Reduction in AHT 784-700= 84 sec
Reduction in AHT by 15 sec = Reduction in 1 FTE
Total FTE Saved Reduction in AHT / Reduction in AHT per FTE = 6 FTE
D M A I C

Project CTQs
Key Questions
Which customer name/ groups are the primary focus for this project?
Ans. Stream 1 Line of Business encompassing the Branch and Mobile users.
Which CTQ (s) will be the primary focus for this project?
Ans. Average handled time on call with Branch users.
D M A I C
Customer Name/
Group
VOC Gathering
Method
Key VOCs CTQ
Define the measure – How exactly the CTQ will be
measured
Royal bank of Canada
as a Customer &
Internal
Management.
Project Review
Meeting.
TSC Agents unable to resolve
issue quickly.
Average Handle
Time.
AHT is measured in seconds. Avaya report will provide
the details of Average handle Time daily and will
measure it as Grade Of Service (GOS). The Work Force
Management (WFM) team will forecast the manpower
requirement on the basis of the AHT trending with the
current and past AHT details.
AHT is calculated as SUM PRODUCT(AHT, No. of
calls)/SUM(No. of calls)

SIPOC & High Level Process Map
HIGH LEVEL PROCESS MAP :
Suppliers Inputs Process Outputs Customers
RBC
Employees
Incoming Call through
Avaya.
Process description: Process of taking call. Closing the call and
forecasting the resource requirement
The call duration
recorded in
the Avaya
Report.
RBC Employees
Process Map:
Please refer :Slide 10
D M A I C

High level Process Map of TSC Call Flow
HIGH LEVEL PROCESS MAP ON CALL FLOW
Start
Call opening
Paraphrase the issue
Ownership
Problem Determination
Verification
Required
Search for PRP in KB
Issue
resolved
Escalate ticket
Problem Gathering
Supported
Issue
Perform Logical Troublshooting step
NO
YES
YES
NO
Direct the user to the
concerned department
RBC Application?
YES
NO
NO
YES
Verification Procedure
End of call
D M A I C

Measure

Performance Standards for the project
Clarify Data CTQ Performance standards
Clarify Data CTQ Performance Standards
CTQ Measure Data Type
CTQ Performance Characteristics
Segmentation Factors (Xs)
LSL USL Target Allowable DPMO
Average
handle Time
Continuous NA NA 700 secs NA
•Month Wise
•Day Wise
•LOB Wise
•Shift wise
•Skillset Wise
•Application Wise
•Training Batch wise
•Team Wise
•Interval & Day Wise
•Resource Skills Level
D M A I C

Data Collection Plan
Data Collection Plan
Define What to
measure
Define How to measure
Who will do
it
Sampling Plan (if applicable)
CTQ Measure
Measurement or test
method
Data Collection
Method
Person (s)
assigned
What
Where/
Who
How
Many
When
Average Handle
Time
Take data from the
Avaya CMS portal for
Skill sets Branch &
Branch Mobile and
compute the AHT for
Stream 1
Automated
through the
Avaya CMS
Love Gaur NA NA NA NA
Findings during review of the data collection plan:
1. The Avaya CMS tool used to retrieve AHT for agents in the Stream 1 skill does not have the ability to provide individual transaction wise
AHT for the transactions recorded under both the Branch and Branch Mobile Skill set.
Recommendation:
 The True AHT for the individual transactions can be obtained in 2 steps:
 The AHT of Top issues identified can be obtained by identifying the Transaction from the HP SM7 tool.
 Based on the Open time of the transaction from HPSM, a search has to be run in VERINT to obtain the actual AHT of that transaction
D M A I C

Data Collection/ Checksheet
Data collection template is automated through Avaya CMS portal.
Sample Data collected for the period Oct ‘12–March’13
Sample Data to be used for project
D M A I C

New batch Impact on Stream 1 AHT
Inference:
 The AHT of the Stream 1 transition team has a huge impact on the overall Stream 1 AHT. The graph above depicts the same.
Analysts who get trained in Stream 1 will be in learning phase for the first 4 weeks and it is expected from them to have high AHT.
Their AHT will impact the overall AHT, hence excluding it from the AHT analysis.
1000
863
812 812 811
788 775
978 837 806 812 811 784 749
1223
976
893
817
871
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
4.00%
600
700
800
900
1000
1100
1200
1300
Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13
Overall Old Batch New Batch Impact
D M A I C

Measurement System Analysis (MSA)
D M A I C
 Data Collection through Avaya CMS
 All the calls are recorded in the Avaya CMS. This data is
downloaded in an excel format and Siebel reports.
 Data is collected for different segmentations as mentioned in
previous slide .
 Accuracy Check
• The Avaya CMS tool that provides the data need not be tested as
this tool is provided by Avaya and pulls the call details real time.
• There is a very high confidence level on the tools accuracy
considering the usage and analysis done on the data.
• The tool could also not be tested due to the sensitive nature of
customers business.
Key Questions
Q. How will you ensure the data
being collected is accurate and
unbiased?
The tool allows for automated
report generation. Hence there is
no scope for bias.
Q. What are the areas of possible
bias or system errors?
None.
Q. Have the Reproducibility &
Repeatability aspects of the data
collection process been assessed?
Yes, the portal has been tested by
both MIS members and the test
result provides identical data set.
Q. Are data collectors properly
trained?
Yes, The MIS team member
responsible for gathering data has
been trained and equipped well
with Avaya CMS tool.

Data Analysis- Capability Baselining
• Baseline: Zst = -2.03 Zlt -3.53
• Targeted Z = -2
For Continuous Data
USL LSL Sample Mean Sample Std. Dev ZST ZLT
700.00 849.00 73.41 -2.03 -3.53
Z VALUE CALCULATOR
E nt er t he U p p er
S p ec. Li mi t her e
E nt er t he Lo w er
E nt er t he cal cul at ed
S amp l e M ean her e E nt er t he cal cul at ed
S amp l e S t d . D ev. her e
D M A I C

Analyze

Normality test for AHT before the project
850840830820810800790780
99
95
90
80
70
60
50
40
30
20
10
5
1
Before
Percent
Mean 816.5
StDev 13.88
N 4
AD 0.531
P-Value 0.065
Normality test for AHT before the project
Normal
Inference: The analysis of the AHT before the project shows that it is normal as the P>0.05.
D M A I C

Analysis on High Call Drivers – JFM ‘13
Top SCIMS 2 to 8 mins 8 to 12 Mins 12 to 20 mins 20 to 30 mins More Than 30 Mins Total of Stream 1 Calls
DESKTOPLAPTOP 15.45% 17.65% 17.43% 18.19% 20.66% 16.85%
SOFTWARE 55.49% 55.43% 54.08% 48.75% 48.35% 54.00%
SYSTEM ACCESS 16.10% 16.63% 14.65% 12.50% 16.12% 15.56%
WINDOW SETTINGS 11.64% 8.10% 7.94% 5.31% 3.10% 8.88%
APPS_BRANCH SALES PLATFORM 4.34% 6.96% 7.09% 4.60% 10.33% 5.81%
NONE 98.68% 99.45% 98.57% 99.38% 94.63% 98.45%
FREEZING 1.32% 0.55% 1.43% 0.62% 5.37% 1.55%
HARDWARE DESKTOP 4.44% 5.56% 6.03% 6.85% 6.02% 5.30%
MSR 72.70% 66.20% 66.11% 66.80% 56.74% 68.04%
CIT 13.84% 18.98% 18.53% 18.67% 22.70% 17.17%
MONITOR 8.02% 8.33% 9.89% 7.47% 9.22% 8.54%
PRINTING SOFTWARE 3.41% 4.25% 4.08% 5.03% 3.76% 3.88%
NONE 69.81% 71.82% 76.64% 75.14% 82.95% 73.09%
FAX 27.32% 24.85% 19.00% 21.47% 13.64% 23.53%
MFU 2.87% 3.33% 4.05% 3.39% 3.41% 3.31%
INSTALLATION 0.00% 0.00% 0.31% 0.00% 0.00% 0.07%
HARDWARE PRINTERS 2.40% 4.17% 4.73% 6.51% 6.32% 3.83%
MFP 36.93% 34.57% 32.26% 30.13% 46.62% 35.17%
NONE 23.74% 21.91% 21.77% 18.34% 14.86% 21.14%
RECEIPT 15.83% 18.21% 21.77% 30.13% 14.19% 19.87%
PASSBOOK 16.79% 19.14% 20.16% 17.47% 17.57% 18.32%
LASER 6.47% 6.17% 3.76% 3.49% 4.73% 5.10%
INKJET 0.24% 0.00% 0.27% 0.44% 2.03% 0.40%
PRINTING INSTALLATION 3.75% 4.09% 3.19% 2.73% 1.66% 3.49%
NONE 99.54% 99.06% 98.80% 96.88% 94.87% 98.97%
HP 3052 DRIVER 0.46% 0.94% 1.20% 3.13% 5.13% 1.03%
Total 33.80% 42.68% 42.55% 43.90% 48.74% 39.16%
Inference:
 The table above indicates the high AHT contributors based on the number of calls recorded in HP SM7. By focusing on the above call
categories, we are catering solutions to 39% of the overall call volumes handled in Stream 1. (Complete set of call distribution is attached in the
file beside).
 The purpose of analysis is to identify the count of long calls contributing from the high call drivers and hence it has been categorized under
different time intervals for us to focus on opportunity areas
Perception based Analysis to be performed to identify the cause for the high AHT in the above call categories is included in the Slide 21.
D M A I C

Prioritizing causes perception based:
Fish Bone Analysis
Action Plan from the Fish Bone Analysis:
 Some of the solutions which are easy fix are in the next slide
 Solution for the cause which have a border has already been reviewed and relevant solutions identified.
 There are other solutions which require further analysis are to be take up as individual action items in the upcoming slides.
D M A I C

Low Hanging Fruits
Impact of the implemented solutions:
Since the time of the start of the project in March 2013 till June 2013. The above solutions has helped the project team to be able to reduce the AHT.
 The AHT for Stream 1 to be closely monitored for further progress.
S.N
o
Low Hanging Fruit (Solution) Impacted Cause Implementation
date
Status
1
2
3
4
5
6
Real Time Monitoring
a. Calls above 600secs to be addressed by TL/SME by
supporting the agents on live calls.
b. TL’s watching over the queue closely.
Review of Long calls
a. Previous day calls over 1800 sec are shared with TL’s to
be reviewed and find opportunity areas
b. Top 5 reasons for the long calls are identified and the
agents are coached.
Access for WJA granted for all TL / SME / QA to support
agents:
All support staff to include the access for WJA which has a
very high dependency on calls.(Printer calls where the
agent have to ping L2 to get it fixed)
Timely Feedback & Tracking:
A new feedback tracking mechanism in place as timely
feedback has impact on the agent’s performance /
Knowledge level increasing AHT.
Training and coaching:
More real time scenarios covered in Training to help them
probe better on calls
Agents Opportunity
Agents fail to learn new updates and applications from KB.
Addresses opportunities towards Agents Opportunity
where unnecessary step / Unable to find the PRP.
Addresses continuous feedback opportunity noticed.
This also will serve as a feedback to the Training
team which can accordingly make changes in
Training. (To be part of the Control measure)
Address the issues under the category Process where
it requires L1 to seek L2 help to fix in the call. After
the access is distributed L1 can now approach to all
support staff.
This addresses issues under category Training &
Coaching. All Feedback and coaching is now
centralized.
This addresses the category Training and coaching.
Training plan is now updated to have more mock
calls and mock ticket creation. Also MOCK call is
now a part of final assessment to ensure agents are
probing well on calls
All the new updates and changes in processes are
cascaded in the daily team huddle to ensure that
agents are up to date on critical process
01-Apr-2013
01-Apr-2013
01-May-2013
10-Apr-2013
17-Apr-2013
13-May-2013
Complete
Complete
Complete
Complete
Complete
Complete
D M A I C

Prioritising Causes – CI Matrix
D M A I C
HILC HIHC LIHC LILC
Process-Issue isolation between
hardware and software takes long time
where user's intervention was
required.
More real time scenarios
covered in Training to help them
probe better on calls
Change requests to update KM are
not been addressed timely
Clients insists agent to stay on call till the issue is resolved
Agents Opportunity - Agents
failed to check Outage ticket
/communication email & Show
related
Agents fail to multitask document
and Troubleshoot) during calls and
hence do not close the call on time.
New issues comes up which does not have any PRP and
Procedures
Agent s lack navigational fluency
Agents do not attempt to learn new
applications
Issue isolation/Escalation metrics requires OCC /Service
Provider's intervention.
Agents Opportunity -
unnecessary reboots tried
Not all solutions are migrated from
RA to KM
Tools/KB - Change Requests not being addressed properly.
Agents Opportunity - Agents
spend a lot of time in incorrect /
irrelevant probing
Due to high call volume SME are not
able to provide floor support as they
are logged in
Users do not have a phone nearby systems
Agents Opportunity-agents fail to
learn from KB.
L2 wants to ensure that all the
troubleshooting under the scope of
TSC(L1) is performed before
escalating to PMT
Slow tools e.g. DRA,TSC PRO and tools have an inefficient
search method-TSC PRO
No tracking mechanism to monitor
timely feedbacks
Multiple issues on same call
L2 are not readily available to take
up the master ticket
PRPs not available in a single location
L2 Ticket update procedure takes a
long time.
Agents wants to resolve the issue faster and come out of
the call and hence they opt for remote assistance even
before probing and understanding the issue
No access for software like WJA and hence have to depend
on L2
Remote assistance tools fails while taking control and
navigating users takes a long time

Call Audit Template Analysis
Need for AHT template
The template was designed to quantify the impact of all the major causes from the cause & effect analysis that
are listed in the slide 25.
The many categories that were listed in the perception Analysis did not have supporting data available. To
gather the relevant data an exhaustive set of checklist was created to be observed in calls.
Sample of the total calls from JFM were gathered to be analyzed.
To gain clarity, calls of different intervals of the high call drivers were monitored by the team and inference of
the same will be updated in the attached template.
D M A I C

Solutions from the Call Audit Template (Phase 1)
Inference:
 The complete set of inferences and solutions are attached in the sheet for reference.
 These solutions are to be applied in the Improve phase and followed for the Pilot Group members.
 The detailed set of solutions are attached in the file.
D M A I C

Solutions from the Call Audit Template (Phase 2)
Note: All Solutions here are dependent on RBC ESD team
S.No Solution Set Impacted Cause Implementation date Status
1
2
3
4
List of Applications where the agents can drop
out of calls.
An exhaustive set of analysis was completed to
identify the set of applications where the agents
can perform the required troubleshooting and
can drop out of the existing call. (Slide 28)
Issues related to Knowledge Base.
a. A set of pending change request that has an
impact to agents call were gathered / identified.
b. A set of solutions are identified which were
available in Right Answers are not moved to KM
now. Details are in (Slide 29)
New Application On-Boarding
Delay in Notifying TSC on new applications (A
formal process of new Application On-Boarding -
in progress) (Slide 30)
Remote Assistance Failures
a. A detailed analysis was performed (Slide 31) to
understand the impact of Remote Assistance
failure on calls.
b. Verbatim guidance to agents are provided by
the CEF team when RA fails
c. Change implemented in QA scorecard to
evaluate agents if RA is used appropriately.
Addresses opportunities towards
Category Others – Client
insisting to stay on call.
Category - Tools/Knowledge
Base
Category Training/Coaching
Category - Tools/Knowledge
Base
16-Jul-2013
27-08-2013
09-08-2013
Item a – 01-July-2013
Item b – 22-Jul-2013
Item c – the score were
changed on the 05-Jul-2013.
Complete
Complete
Complete
Complete
Note: All Solutions here are dependent on RBC ESD team
D M A I C

1. Applications where the agents can educate and
Drop out
Inference:
 The above mentioned scenarios/problem isolation takes a long time where an agent stays on call unnecessarily when the
final step to either resolve the issue or isolate the problem takes a long time.
 The information has to been cascaded to the agents to provide proper instructions/solutions and drop off from the call with
user’s consent.
D M A I C
Find the List of applications Issues where agents can come out of calls
Microsoft Product installation
Sales Platform installation
Service platform Installation
CCU Re-entry
Try the application on other computer
Try the hardware on other computer
PRP which requires a Reboot and if that would definitely fix the issue (RBIS Trigger file/ZPR0)

2. Impact of Knowledge Base updates on
agents Calls
Change Request is a portal where we submit requests to update/create KB articles.
It was observed that lack of KB leads to increase in resolution time, consequently TSC QA team had submitted many CRs and it had
not been closed on time. To mitigate this gap, we followed up with RBC ESD team to have a process in place
 TSC QA team followed up with the RBC ESD team to update the Knowledge base. A glance of pending change requests with priority:
D M A I C
Request Status High Low Medium
In Progress 2 4 2
Initial Submission 0 0 5
Under Review 12 13 25
Grand Total 14 17 32
The complete set of Change requests pending is as below:

3. New Application On-Boarding
 One of the key aspects of a service desk is to have a clear ownership, accountability defined for new on
boarding applications which will help us to provide seamless support to our clients with all the facts and
data readily available which can be used for analysis, investigations and for the preparations of knowledge
parks and PRP’s
 With introduction of new applications TSC has always encountered a spike in terms of AHT and FCR due to
lack of KB articles and PRPs.
Solutions introduced:
1. Governed by I&I team,
2. Knowledge base tracking: Quality team
3. AHT and trend analysis: Team leader
4. Tracking unknown issues & creating PRP: L2
D M A I C

4. Analysis on Time taken during the use of Remote
Assistance Impacting AHT
 The use of Remote assistance tool on a call follows procedure shown.
 There are 2 scenarios that an agent encounters on a regular basis:
– RA needed and it was a success
– RA needed and it fails and agents would have to resort to navigate the
caller for resolution / escalate to next level.
 With a sample observation of 25 calls it takes 73.16 secs to take
control.
 With a sample observation of 10 calls where RA fails it takes 152.8
secs to confirm RA failed. It also takes another 952.9 secs to navigate
the caller to a point of resolution / escalation.
Inference:
 17% of calls did not require Remote assistance and an
agent spends 109secs/call trying to take control instead
of navigating the user and utilising the time.
 It was observed in 5% of the calls-the problem with RA
appeared after 127seconds in the call. On these calls
while trying to fix the RA error 421 seconds/call was
consumed but only 1% of RA issue was resolved.
D M A I C

Improve

Solution set 1- Impact on AHT
S.No Issue Solutions
Implementation
month
IMPACT
1
Real Time Monitoring a. Calls above 600secs to be addressed by TL/SME by
supporting the agents on live calls.
APR'13
After implementing all the
actions plans for the
Quick fixes the AHT
reduced by 15 sec/month.
b. TL’s watching over the queue closely.
2
Review of Long calls a. Previous day calls over 1800 sec are shared with
TL’s to be reviewed
APR'13
b. Top 5 reasons for the long calls are identified and
the agents are coached.
3
Access for WJA granted for all TL / SME /
QA to support agents:
All support staff to include the access for QJA which
has a very high dependency on calls. MAY'13
4
Timely Feedback & Tracking: A new feedback tracking mechanism in place as
timely feedback has impact on the agent’s
performance / Knowledge level increasing AHT.
APR'13
5
Training and coaching:
More real time scenarios covered in
Training to help them probe better on
calls
This addresses the category Training and coaching.
Training plan is now updated to have more mock
calls and mock ticket creation. Also MOCK call is now
a part of final assessment to ensure agents are
probing well on calls
APR'13
6
Agents Opportunity
Agents fail to learn new updates and
applications from KB.
All the new updates and changes in processes are
cascaded in the daily team huddle to ensure that
agents are up to date on critical process
MAY'13
D M A I C

Solution set 2- Impact on AHT
D M A I C
Solutions from Call Audit Template
S.No Issue Solutions Implementation date Impact
1
Agents Opportunity - Agents failed to
check master ticket & Show related
To modify the Call Opening to include "To
Check the previous call records" JULY'13
Along with tracking the
solutions from the Low
hanging Fruit + After
implementing solutions
and tracking the changes
from the solution set
there is a reduction in
AHT which can be
looked in 2 ways:
Overall AHT(New
agents+Old agents)
reduced by 52 seconds.
AHT of the old agents is
reduced by 69 sec
2
Agents Opportunity - Agents spend a lot
of time in incorrect / irrelevant probing
For the top call generators-probing
questions set to be prepared.
JULY'13
3
Process-Issue isolation between
hardware and software takes long time.
Create issue isolation questions for the top
call generators.
4
Agents Opportunity - unnecessary
reboots tried
Agents to be coached on when reboots are
necessary JULY'13
5
Process-No access to Software's like
WJA and hence agents depends on L2.
Access has been given for TLs and SME for
the WJA software
MAY'13
6
Tools/KB-Agents spend time to search
PRPs in multiple locations
Discussed with the ESD team to move
PRP's to one KB - KM JULY'13
7
Agents opportunity - Agents fail to
multitask/document and Troubleshoot
during calls because agents get
distracted by MOC chats and emails
which are irrelevant on the call.
The calls audited by the QA are tracked
with this information to ensure agents are
not involved in email and chat sessions. AUGUST'13
8
Agents Opportunity - Agents wants to
resolve faster and without probing they
use RA.
Tracking mechanism in place to verify the
appropriate usage of RA JULY'13
9
Tools/KB-Agents spend time to search
PRPs in multiple locations
Discussed with ESD team to have a
centralized KB which has the links to all the
PRPs/Knowledge article.
JULY'13

Process changes
 Change Requests :For any updates to be made on Knowledge base change requests (CR)
should be submitted for approval from RBC. There was a delay in getting PRP/Process
updated in TSC Pro as there was no turn around time for the CRs submitted. After discussion
with the ESD team, RBC came up with the SLA (Based on impact and Urgency) for all change
requests submitted. ESD I&I Priority and SLA def.docx
CR SLA Targets:-
Acknowledgement of the request :
High: 2 Hours – Requires additional Email to ESD I&I advising why this is a high priority (To ensure we have a process in
place for future calls)
Medium/Low: 1 Business Day
Completion of request:
High: 1 Business day when all requirements have been met & appropriate information provided
Medium: 2-10 business days based on information provided
Low: 5-20 business days based on information provided
D M A I C

AHT Trend in the improvement phase
D M A I C
978
837
806 812 811
784
749 760
712 700 696 692
4 4
1
0
2
1
0 0 0
0 0
0
0
1
2
3
4
5
600
650
700
750
800
850
900
950
1000
AHT Stream1 Target SLA Missed
Along with tracking the solutions from the Low hanging Fruit + After implementing solutions and tracking the changes there is a reduction in
AHT which can be looked in 2 ways:
 AHT of the old agents is reduced by 69 sec
NOTE : The graph above shows the reduction in AHT post implementation of solutions listed in slide 33,34 & 35
1000
863
812 812 811 788 775 760
734 722 712 708
978 837 806 812 811 784 749 760 712 700 696 692
600
700
800
900
1000
1100
Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13
AHT(sec)
Overall Old Batch
Since iLSS

Improve
Confirming Improvements

Story on the Pilot Implementation:
 We have identified agents from Stream 1 group of all Types basis the performance. There were 10 agents selected
which is 25% of the population from Stream 1. The agents are availble in the attached sheet indicating the progress.
 These agents were briefed on the project and set the expectation on their roles as team members.
 The group of agents were coached on all the best practices based on the earlier analysis. The items from the
solutions set were implemented by them as “Things to do” on Stream 1 Calls.
 There was a constant meeting and session with the team to re-iterate the “Things to do” on calls. Challenges were
posted by the agents during these contact sessions.
 All the observations and feedbacks were shared for all the high call drivers.
 Reviews were held constantly to discuss on the AHT results.Their AHT was tracked on a daily/weekly basis to gauge
the improvement.
Success criteria for the Pilot Plan and the success rate for the Pilot Team:
 The detailed success criteria and the results is attached in the Slide.
 The AHT scores achieved for the Pilot Team is attached in the Slide
Implementation Plan
D M A I C

Normality test for AHT after the
project
825800775750725700675650
99
95
90
80
70
60
50
40
30
20
10
5
1
After
Percent
Mean 727.6
StDev 36.37
N 7
AD 0.422
P-Value 0.225
Normality test for AHT after the project
Normal
Inference :
A Normality plot was drawn for AHT after the AHT project to identify the kind of Hypothesis we should
use. P>0.05 which means the data is normal post implementation of the ideas from the project.
D M A I C

Statistical confirmation using 2 Sample
t test
Interpreting the Results
Ho: States that there exists no
difference in the data samples or
may be due to chance
Ha: States that there exists a
difference between the data
samples and the difference is true
and on chance
From the statistical analysis in the
figure p=0.00.
Since p<0.05, we accept alternate
hypothesis(Ho) where there is a
difference in the mean.
D M A I C

Targeted Z value Vs. Current Z value
• Targeted Z = -2 (Slide 17)
• Current Z = -2
USL LSL Sample Mean Sample Std. Dev ZST ZLT
700.00 728.00 36.40 -0.77 -2.27
E nt er t he U p p er
E nt er t he Lo w er
E nt er t he cal cul at ed
S amp l e M ean her e E nt er t he cal cul at ed
S amp l e S t d . D ev. her e
D M A I C

Achievements
S.N. Parameters Before Target After
1
Z value ( Zst) -2.03 -0.77 -0.77
2
Cpk NA NA NA
3
Average Handle Time for
Stream 1
811 700 700
4
Annualized Financial
Savings/Benefits (USD $)
NA $13,608.00
D M A I C

Control

Control Plan & Control mechanism
D M A I C
Control Suggested Action Plan Indicator Who When
Periodic Process Capability Study
Bi-Monthly checks for the process
capability to be conducted for the
different applications in Stream 1
To measure the volumes of the different Stream
1 application wise transactions handled.
Increase in AHT
Addition of New support
Process.
QA Team &
MIS
Bi-
Monthly
Monthly checks for the process
capability to be conducted on the FTE
for Stream 1
MIS team along with the support of the WFM
team to perform check on the FTE requirements
to handle Stream 1 volumes not only from the
historical call volumes but also the considering
the current Stream 1 call volumes.
Miss in GOS for Stream 1
Increase in stream 1 call
volume
Increase in AHT for
Stream1
WFM & MIS Monthly
Long call Analysis with the active queue
monitoring.
Ops team to perform active queue monitoring
with checkpoints on the agents productivity
report.
Ops team to communicate with the Support
team and the ESD team to showcase the
increasing AHT on specific applications.
Increase in AHT on
specific call category in
Stream 1.
Ops & QA
team
Daily
Changes to Process / Checklist
New Application On-Boarding
procedure to be formally signed off
with an understanding between iGATE
and RBC.
To measure the AHT for all New Applications On-
boarding. The High AHT contributions to be further
analyzed for Verification and Validations.
Increase in AHT for New
support Process.
QA team &
ESD RBC
New
Applicati
on Sign
OFF
TSC Support Tools & TSC Knowledge
Base
Changes to support tools to go through a formal
New application On-boarding process. Impact on
AHT for the new tools to be verified.
A new Volume Stream Mapping procedure to be
performed for all new Support Tools and KB
changes to identify the AHT impact
Introduction of new
Support Tool
QA team &
ESD RBC
New
Applicati
on Sign
OFF
Any new problem issue PRP's to be
validated for duration to implement
on calls
New PRP's to go through a procedure to decide the
cut-off for PRP time. Any PRP which are greater
than >700 secs to verified.
New PRP's taking a long
time
QA team &
ESD RBC
New PRP
Sign OFF

Mistake Proofing
D M A I C
OBSERVATIONS ACTIONS
Tools/ KB-Agents spend time to
search PRPs in multiple locations
New and existing applications PRP's to
be avialble in one KB - KM
Agents failed to check master
ticket & Show related
The Call Opening statement has been
modified "To Check the previous call
records"
Know ledge Base not updated
Change Request SLA in place for the
new solutions/ process related changes
to be updated in the KB.

Approval & Appreciation
D M A I C
From: Chowdhry, Mudit (CWM-NR)
Sent: 2013, December, 05 7:46 AM
To: Dhanabal, Pavithra (CWM-NR); Ravindran, Viswanath (CWM-NR); Wundri Gundra, Jayaraju (CWM-
NR); Panda, Pallavi (CWM-NR); Gaur, Love Kumar (CWM-NR)
Subject: RE: PPT for iLSS AHT
This is approved and we should close this project now
…congratulations to all and very well done 
Thanks,
Mudit Chowdhry | Service Delivery Manager | Technology Support Center |T. 1-866-288-4517 |
Extension: 4158

Project Milestones
Plan Date Actual Date Sign-Off date Approver
Project
Identification 01-March-2013 01-March-2013 01-March-2013 Mudit Chowdhry
Define
01-April-2013 01-April-2013 01-April-2013
Mudit Chowdhry
Measure
28-June-2013 28-June-2013 28-June-2013
Mudit Chowdhry
Analyze
30-July-2013 30-July-2013 30-July-2013
Mudit Chowdhry
Improve /
Design 31-Sep-2013 31-Sep-2013 31-Sep-2013
Mudit Chowdhry
Control /
Verify 31-Sep-2013 31-Sep-2013 31-Sep-2013
Mudit Chowdhry

Learning's

Important lessons learned
 The process is very dynamic and the changes made are directly proportional to the
AHT of the calls. Hence TSC has to be always vigilant to ensure the process gap by
signing off before implementation.
 The Knowledge base is created/modified by RBC and the control over the same is
less. Hence a rigorous follow up is required to ensure it is up to date to reduce
process gaps.
 Analyses based on the data gathered and the causes deciphered out of the same
may not have just one fix but it could be inter-related with other factors like
scheduling(WFM)/Skillsets/call pattern/Call trend during peak
time/Outages/Training batch.

Reusability Areas
Some of the suggestion that are available that can be used as part of a Help Desk
Environment are as below:
 Live Queue Monitoring for incoming calls or tickets to the Help Desk, helps us to diagnoise
outages earlier and control the hight AHT on these issues.
 Master Access checklist for the complete HelpDesk across all layers of resources is helpful in
identifying the necessary support that is required reducing the dependancy on a single group.
 Managing Change Requests for all existing KB article in a tracker is essential. The tracker should
have the severity of the change request with a predefined SLA is essential to analyze the impact
of downtime.
 Formalized approach for On borading New Application into support is always recommened to
assess the impact of any new application being on-boarded. This also helps in better planning of
all related activities around the change. Failing to do this most likely results in scope creep in the
support project.

Project Summary-
4 Blocker

Analyze :
Tools used:
Cause and effect Diagram – Identification
Control IMPACT metrics-Prioritization
• Write Identified root cause
Identified high call drivers
Process gaps
Knowledge base inconsistency
Agent’s opportunity- Probing skills
 Tools inconsistency
Slide 22 & Slide 24
Improve:
• Actions Taken –
 Real time Queue monitoring
 Analysis on long calls
 Fixed process gaps for the high call drivers
 Fixed Knowledge base
 Identified inevitable scenarios
Applied all the ideas in the pilot team and this has shown a
considerable improvement and hence applied the same to all the
analysts.
Slide 33 & slide 34
Define & Measure :
• Business Case: The different Business Units (BU) for the client
are classified into different client base .Stream 1 consists of callers
from the client base Branch who directly impact the revenue for
RBC. 26.5% of the transactions are carried out in Stream 1 .Hence
reducing the Average handle Time (AHT) for Stream 1 Business
unit will have a positive feedback on the Help Desk
• .
• CTQ Base lined : AHT. Before the start of the project, the CTQ
was 784 sec
• Estimated Savings : $13,608.00(On account of FTE)
Results & Control :
• CTQ Achieved : The overall AHT has been reduced to 84 sec
for the Stream 1 client base.
• Actual Savings : $13,608.00(on account of FTE)
• Control Mechanism Deployed :
 Ensure to check the new PRP’s are checked to ensure it
does not contribute to the overall AHT.
 SLAs created for the CR’s to ensure the Knowledge
base is up to date.
 Monthly checks for the process capability to be
conducted on the FTE for Stream 1
Slide 48
To reduce the AHT of Service desk
Pavithra Dhanabal Love Gaur Kumar Jayaraju Wundri Gundra

THANK YOU !

I lss reduction%20in%20aht%2713 final

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