Reducing AHT

By: Subhash Mandal Dated 30 Nov 2012
REDUCING AHT – BUSINESS CREDIT SERVICES

VOICE OF THE CUSTOMER - VOC
2
d
DEFINE
Customer Comments Critical to Quality-CTQ’s
John McCune : CFO-GE
Health Care
The client was unhappy due to missing
SLA target in last two quarters set by
them.
Current AHT of process-BCS is at
405 seconds.
End Customers-General
Electric.
The agents were unable to understand
customer’s problems at first go which
took them longer to reciprocate &
resolve their queries.
Need to meet the desired AHT
target which is 300 seconds per
call.
Process Owner-AVP
BCS has unable to meet the SLA target
of AHT last quarter.
AHT = 300 Seconds per call

PROJECT CHARTER
Business case:
Genpact is the leading outsourcing firm with clients from across
the globe. GE HealthCare - Business Credit Service (GE-HC : BCS)
is one of the prominent client for Genpact for over 5 years.
GE-BCS caters to end customer’s queries, concerns and requests.
The process is unable to meet the AHT target for this quarter
resulting to customer dissatisfaction. If the same persist
consecutively for three quarters, the client might take away the
business. Hence, lies the opportunity to satisfy the customer and
increase company revenue.
Team:
 Sponsor-Kunal Giri
 MBB-Naresh Rao
 Champion-Alka Shukla
 Process owner-Gunjit Narang
 BB-Jatin Sharma
 GB-Jasjot Masuta
 Team member-Subhash Mandal
Problem Statement:
AHT of the process-BCS was 405 seconds resulting to miss
service-level in last quarter. 46.61% agents were below the target
AHT of 300 seconds.
This AHT target will improve the business delivery and eventually
enhance opportunity to earn more revenue to the company.
Client might pull back the business if the AHT target is
not met in the next quarter.
Goal Statement:
To improve AHT of the process to 300
seconds by the 30th
November 2012, without
impacting the quality.
In Scope: The BCS-collections and customer service
team in Gurgaon, Delhi & Hyderabad.
Out Scope: Other GE processes.
Milestones Target Date Actual date
D 30/Nov/2012 30/Dec/2012
M 31/Jan/2013 28/Feb/2013
A 31/Mar/2013 30/Apr/2013
I 31/May/2013 30/Jun/2013
C 31/Jul/2013 31/Aug/2013
d
DEFINE

ARMI
Key Stakeholders ARMI Worksheet
Define Measure Analyze Improve Control
Stakeholders—AM Tyagrajan I I I I I
Sponsor-Kunal Giri I I I I I
Champion-Alka Shukla I & A I & A I & A I & A I & A
MBB-Naresh Rao A & I A & I A & I A & I A & I
BB-Jatin Sharma I & R I & R I & R I & R I & R
Process Manager-Gunjit Narang I & M I & M I & M I & M I & M
GB-Jasjot Masuta R & M R & M R & M R & M R & M
Team Members-Subhash Mandal M M M M M
A – Approval of team decisions I.e., sponsor, business leader, MBB.
R – Resource to the team, one whose expertise, skills, may be needed on an ad-hoc basis.
M – Member of team – whose expertise will be needed on a regular basis.
I – Interested party, one who will need to be kept informed on direction, findings.
Communication Plan
Information Or Activity Target Audience Information Channel Who When
Project Status Leadership E-mails Gunjit Narang/
Alka Shukla/Naresh Rao
BI-Weekly
Tollgate Review MBB, Black-belt, GB &
Champion
E-mails and/or Meetings Naresh Rao, Jatin Sharma,
Jasjot Masuta & Alka Shukla
As per Project Plan
Project Deliverables or Activities Members Emails and/or Meetings Weekly
d
DEFINE

SIPOC
Supplier Input Process Output Customer
AVAYA Software and
networking.
AVAYA software and
call-master.
Customer’s call pops-
up and received.
Answering call with
greeting & agent’s
introduction.
GE LESCO credit
account holder.
AVAYA Software and
networking.
Call master Listening to
customer’s query.
Provide necessary
information as
customer’s
requirement.
GE LESCO credit
account holder.
Human Resource Agent and call script. Probing, in case of
any doubt.
Helps customer with
necessary information
GE LESCO credit
account holder
SOP
Process flow.
Information and/or
documents.
Resolve customer’s
query with needed
information .
Satisfied & happy
customer.
GE LESCO credit
account holder
Caller & company. Query, concerns and
updates received
from customer. GUI
to update.
Documentation of
conversation.
Update & save
conversation
summary & provide
ticket no. if any.
GE LESCO credit
account holder
Call Master. End call with proper
verbatim.
Customer’s
satisfaction with
needed information
GE LESCO credit
account holder
d
DEFINE

6
d
DEFINE PROCESS MAP - FLOW CHART
START
Is the call for any
specific collector /
account-manager?
NO
YES
Account-manager/collector answers
call with proper greeting &
investigates into customer’s query.
Could customer’s
query be resolved
at his end?
Customer service agent answers call
with proper greeting & investigates
into customer’s query.
Is
collector/account-
manager able to
resolve customer's
query/request?
YES
query/request
Update the conversation's gist &
provide ticket no., if needed.
END
Is the special
handling
team/supervisor able
to resolve customer's
query/request?
NORoute call to special handling
team/supervisor to take care.
NO
YES
Route the call to grievance
handling team at different
location.
Grievance handling team addresses
customer’s issue & provides resolution.
Gives a TAT in case future follow-up.
NO
YES
query/request
Customer calls in requesting
for key-code, account details,
invoice/statement copy, making
payment on account etc.
End the call with proper
greeting & verbatim.

DATA COLLECTION PLAN
KPI Operational Definition Defect Def Performance Std
Specification Limit
Opportunity
LSL USL
AHT
The total time taken by an agent
including Talk-time/Hold time/After
Call Work time against total no. of
calls taken, expressed in seconds, in
a month.
Any call duration
exceeding 300 sec
will be considered a
defect.
300 Sec NA 300 Sec Monthly AHT
KPI Data Type
Data Items
Needed
Formula to be
used
Unit
Sec
Plan to
sample
What
Database or
Container
will be used
to record
this data?
Is this an
existing
database
or new?
If new,
When will
the
database
be ready
for use?
When is the
planned
start date
for data
collection?
AHT Continuous
AHT, Talk
time, Hold
time, ACW,
No. Of calls
taken
AHT=(Talk
time+Hold
time+After call
work time)/The
no. of calls
taken
Seconds MS Excel Existing NA NA
July 11’ to
Dec 11’
m
MEASURE

8
IMR CHART : PRE IMPROVEMENT
There are special cause variations so the process was statistically out of control.
m
MEASURE

MSA - GAGE R&R ANOVA
Gage R&R
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 4031.4 6.89
Repeatability 3847.0 6.58
Reproducibility 184.4 0.32
Operator 184.4 0.32
Part-To-Part 54472.1 93.11
Total Variation 58503.6 100.00
Process tolerance = 1
Study Var %Tolerance
Source StdDev (SD) (6 * SD) (SV/Toler)
Total Gage R&R 63.494 380.96 38096.10
Repeatability 62.024 372.15 37214.63
Reproducibility 13.579 81.48 8147.64
Operator 13.579 81.48 8147.64
Part-To-Part 233.393 1400.36 140035.60
Total Variation 241.875 1451.25 145125.06
Number of Distinct Categories = 5
As all the Rules for Gage R & R ANOVA
method are satisfied by the data, so we
can take this data for further Analysis
m
MEASURE
3 Rules of GageR&R :
1)GageR&R as a percentage of contribution towards total variation
should be smaller that part-to-part variation.
2)GageR&R as a percentage of tolerance towards total variation:
a) Accept, if less than 10%
b) May accept with caution if between 10-30%
c) Reject if greater than 30%
3)No. of distinct categories should be equal to or greater than 4

STABILITY - RUN CHART
As P-value for Mixture, Cluster, Trend & Oscillation are greater than 0.05,
the Data is STABLE.
m
MEASURE

11
PROCESS CAPABILITY
m
MEASURE
As the Process is working at a sigma level of 1.4 and the DPMO is 537,615.
So, there is a great opportunity for Improvement in the process
Z-Value
Mean 405.65
Std. Dev. 273.23
USL 300
DPMO 537,614.68
SIGMA LEVEL 1.4

CAUSE & EFFECT DIAGRAM
a
ANALYSE

13
a
ANALYSE POTENTIAL Xs
Sr. no. Potential X Description Data type Test to be done
1 Trainer
A person, assigned to train & teach people about the new
job which they will be doing after the learning completes.
Data type Mood’s Median Test
2
Process
knowledge
Overall knowledge of the process functionality, job
description, conduct & other vital information needed to
work efficiently and effectively.
Discrete
Mann Whitney Test
3 Shift-timing
The time when an agent logs in & starts his shift till he logs
off.
Discrete
Mood’s Median Test
4 Gender Whether an agent is a male OR female.
Discrete
Mann Whitney Test
5 Location Place from where the calls being taken
Discrete
Mann Whitney Test
6 Age Age of the agent in years
Continuous
Regression test
7 Tenure Duration of the agent being in the company.
Continuous
Regression test
8 Education Academic background and qualification of agent
Discrete
Mood’s Median Test
9 Marital status Whether the agent is married OR unmarried.
Discrete
Mann Whitney Test
10
Communication
mode
Language in which the agent communicates with
Its customers, i.e., English or Hindi
Discrete
Mann Whitney Test
11
Process
complexity
The critical level of the process, i.e., P-I, P-II or P-III.
Discrete
Mann Whitney Test

AHT vs TRAINER - MOOD’S MEDIAN TEST
14
Mood Median Test: Project Y versus Trainer
Mood median test for Project Y
Chi-Square = 53.57 DF = 5 P = 0.000
Individual 95.0% CIs
Trainer N<= N> Median Q3-Q1 +---------+---------
+---------+------
Amit 56 32 247 367 (--*-----)
Atul 56 20 194 247 (--*-)
Daniel 69 49 270 459 (---*----)
Rashid 21 43 535 517 (-------*------)
Ruby 42 91 494 454 (------*------)
Sonia 29 37 435 359 (--------*----)
+---------+---------+---------+------
150 300 450 600
Overall median = 336
As P-value < 0.05,
the median of
trainers are
significantly
not-equal to each
other. Hence, we
will do further
analysis on trainers.`
a
ANALYSE

15
AHT BOX PLOT : TRAINER
Agents trained
under Atul have the
least AHT & agents
trained under
Rashid have highest
AHT. Hence, we’ll
further break down
this to Trainers in
Different Locations.
a
ANALYSE

16
AHT BOX PLOT :TRAINERS IN DIFFERENT LOCATIONS
Trainees trained
under Rashid at C5
have better AHT.
Trainees under
Sonia have better
AHT at C6. Amit’s
trainees have better
AHT at C6 vs C5.
Hence, we’ll further
break down this to
Trainers in Different
Locations.
a
ANALYSE

17
AHT BOX PLOT:TRAINERS IN PROCESS COMPLEXITY
Amit : Trainees in L2
have lesser AHT vs
trainees in L1.
Rashid : Trainees in
L1 have lesser AHT
vs trainees in L2.
Atul and Daniel both
have more than 50
% trainees meeting
the AHT target of
300 seconds.
a
ANALYSE

18
Atul : More than
75% of male
trainees are meeting
the AHT target of
300 Seconds.
Daniel : Female
trainees have lesser
AHT vs male
trainees.
AHT BOX-PLOT:TRAINERS WITH DIFFERENT GENDERS
a
ANALYSE

AHT vs PROCESS KNOWLEDGE-MANN WHITNEY TEST
19
Mann-Whitney Test and CI : Project Y_FAIL, Project Y_PASS
N Median
Project Y_FAIL 351 335.00
Project Y_PASS 194 358.00
Point estimate for ETA1-ETA2 is 7.00
95.0 Percent CI for ETA1-ETA2 is (-30.99,48.98) W = 96567.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6727
Hence, P-Value is 0.6727
The test is significant at 0.6727 (adjusted for ties)
As P-value >0.05, the
median of
Process-knowledge of
FAIL is significantly equal
to the median of
Process-knowledge of
PASS. Hence, no further
analysis needs to be
done.
a
ANALYSE

20
AHT vs SHIFT-TIMING : MOOD’S MEDIAN TEST
Mood Median Test: Project Y versus Shift
Chi-Square = 6.80 DF = 2 P = 0.033
Shift N<= N> Median Q3-Q1 +---------+---------+---------+------
Evening 129 110 297 483 (------*-------)
Morning 81 72 298 440 (------*-----------)
Night 63 90 429 441 (-------*--------)
+---------+---------+---------+------
240 320 400 480
As P-value < 0.05,
the median of AHT
in three different
shifts are
significantly
not-equal to each
other. Hence, we
will do further
analysis on
shift-timing.
a
ANALYSE

21
50% agents are
meeting AHT target in
Morning and Evening
shifts. Less than 50%
agents are meeting
AHT target of 300
seconds in Night shift.
AHT BOX-PLOT : SHIFT
a
ANALYSE

22
100% agents trained
by Atul in Evening
shift have AHT less
than 300 Sec & more
than 75% agents have
AHT less than 300 sec
in Night shift under
Rashid.
AHT BOX-PLOT : SHIFT WITH DIFFERENT TRAINERS
a
ANALYSE

23
AHT BOX-PLOT:SHIFT WITH PROCESS COMPLEXITIES
More than 50% agents
in L1, morning shift
and L2 evening shift
are meeting the AHT
target of 300 Seconds.
In L1, night shift only
25% are meeting AHT
target of 300 Seconds.
a
ANALYSE

24
AHT BOX-PLOT : SHIFT BY MALES & FEMALES
Females in evening
shift and Males in
morning shift are
meeting AHT target of
300 Seconds. In night
shift, neither males
nor the females are
meeting the AHT
target.
a
ANALYSE

25
AHT BOX-PLOT : SHIFT IN DIFFERENT LOCATIONS
More than 50% agents
at C6 evening and
morning shift are
meeting the AHT
target of 300 seconds.
And in night shift
more than 25% agents
are meeting the
target.
a
ANALYSE

26
AHT vs GENDER - MANN WHITNEY TEST
Mann-Whitney Test and CI: Project Y_F, Project Y_M
N Median
Project Y_F 234 334.50
Project Y_M 311 344.00
As P-value >0.05,
the median of
AHT of Males is
significantly equal to the
median of AHT of
Females. Hence, no
further analysis needs to
be done.
a
ANALYSE

27
AHT vs LOCATION - MANN WHITNEY TEST
Mann-Whitney Test and CI: Project Y_C5, Project Y_C6
N Median
Project Y_C5 303 363.00
Project Y_C6 242 299.00
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at
0.6688
median of
AHT of Location C5 is
median of
AHT of Location C6.
Hence, no further
done.
a
ANALYSE

28
AHT vs AGE - REGRESSION TEST
Regression Analysis: Project Y versus Age
The regression equation is
Project Y = 377 + 1.03 Age
Predictor Coef SE Coef T P
Constant 377.02 75.94 4.96 0.000
Age 1.025 2.686 0.38 0.703
S = 273.632 R-Sq = 0.0% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 10905 10905 0.15 0.703
Residual Error 543 40656738 74874
Total 544 40667643
As P-value >0.05, so
there is no impact of age
on AHT. Hence, no
be done.
a
ANALYSE

29
AHT vs TENURE - REGRESSION TEST
Regression Analysis: Project Y versus Tenure-Years
The regression equation is
Project Y = 405 + 0.06 Tenure-Years
Predictor Coef SE Coef T P
Constant 405.39 31.59 12.83 0.000
Tenure-Years 0.058 6.381 0.01 0.993
S = 273.668 R-Sq = 0.0% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 6 6 0.00 0.993
Residual Error 543 40667637 74894
Total 544 40667643
As P-value >0.05, so
there is no impact of
Tenure on AHT.
Hence, no further
done.
a
ANALYSE

30
AHT vs EDUCATION - MOOD’S MEDIAN TEST
Mood Median Test: Project Y versus Education
Chi-Square = 4.33 DF = 2 P = 0.114
Education N<= N> Median Q3-Q1
Graduate 80 102 389 471
Higher Secondary 99 83 297 478
Post-Graduate 94 87 319 463
Education --------+---------+---------+--------
Graduate (---------*-----------)
Higher Secondary (-------*----------)
Post-Graduate (--------*----------)
--------+---------+---------+--------
300 360 420
As P-value > 0.05,
the median of
Education in four
different cases are
significantly
equal to each other.
Hence, we will NOT
do any further
analysis on
education.
a
ANALYSE

31
AHT vs MARITAL STATUS - MANN WHITNEY TEST
median of
AHT of Married is
median of
AHT of Unmarried.
Hence, no further
done.
Mann-Whitney Test and CI: Project Y Married, Project Y Single
N Median
Project Y Married 227 330.00
Project Y Single 318 340.50
Point estimate for ETA1-ETA2 is -0.00
a
ANALYSE

32
AHT vs COMMUNICATION MODE-MANN WHITNEY TEST
median of
AHT of English
Communication is
median of
AHT of Hindi
Communication. Hence,
no further analysis needs
to be done.
Mann-Whitney Test and CI: Project Y English, Project Y Hindi
N Median
Project Y English 303 366.00
Project Y Hindi 242 317.50
Point estimate for ETA1 - ETA2 is 4.00
95.0 Percent CI for ETA1-ETA2 is (-33.00, 43.99)W = 83167.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at
0.8065
a
ANALYSE

33
AHT vs PROCESS COMPLEXITY-MANN WHITNEY TEST
median of
AHT of Complexity at L1
is significantly equal to
the median of
AHT of L2. Hence, no
be done.
Mann-Whitney Test and CI: Project Y_L1, Project Y_L2
N Median
Project Y_L1 241 355.00
Project Y_L2 304 319.00
Point estimate for ETA1-ETA2 is -11.00
`
a
ANALYSE

34
a
ANALYSE
VITAL Xs OUT OF POTENTIAL Xs
Sr. no. Potential X Test done P-Value Impact-Y/N
1 Trainer Mood's median 0.0000 YES
2 Process knowledge Mann Whitney 0.6727 NO
3 Shift timing Mood's median 0.0330 YES
4 Gender Mann Whitney 0.8749 NO
5 Location Mann Whitney 0.6688 NO
6 Age Regression 0.7030 NO
7 Tenure Regression 0.9930 NO
8 Education Mood's median 0.1140 NO
9 Marital status Mann Whitney 0.9813 NO
10 Communication mode Mann Whitney 0.8065 NO
11 Process Complexity Mann Whitney 0.5179 NO

35
a
ANALYSE
VITAL Xs
Based on analysis done on the Eleven POTENTIAL Xs, we found two VITAL Xs out of
all the POTENTIAL Xs which are:
1.Trainer
2.Shift-timings
We have some detailed results upon analysis of
these two VITAL Xs, which have been mentioned in
the next slide…

36
 More than 50% candidates under Amit, Atul & Daniel are meeting the AHT target of 300 seconds
 Trainees trained under Rashid at C5 have better AHT.
 Trainees under Sonia have better AHT at C6. Amit’s trainees have better AHT at C6 vs C5
 Trainees in location L2 have lesser AHT vs trainees in L1 under trainer Amit
 Trainees in location L1 have lesser AHT vs trainees in L2 under Rashid
 Atul and Daniel both have more than 50% trainees meeting the AHT target of 300 seconds
 More than 75% of male trainees are meeting the AHT target of 300 Seconds under Atul and Female trainees have lesser AHT vs Male
trainees under Daniel
 In Morning & Evening shifts, 50% agents are meeting AHT target and in night shift less than 50% are meeting their target of 300 seconds
 In Evening shift, 100% agents are meeting their target under Atul & in night shift more than 75% agents are meeting AHT target of less
than 300 sec trained under Rashid
 More than 50% agents in L1, morning shift and L2 evening shift are meeting the AHT target of 300 Seconds. In L1, night-shift,
only 25% are meeting AHT target of 300 Seconds
 Females in evening shift and Males in morning shift are meeting the target. In night shift, neither males nor the females
are meeting the AHT target
 More than 50% agents at C6 evening and morning shift are meeting target. And in night shift more than 25% agents are
meeting the AHT target of 300 sec
IMPROVEMENT PLAN:BASED ON
ANALYSIS
i
IMPROVE

37
QUALITY FUNCTIONAL DEPLOYMENT
i
IMPROVE

38
i
IMPROVE
FMEA-RISK TREATMENT PLAN : TRAINER

CONTROL PLAN
c
CONTROL
Activities Responsibilities Frequency
Share Best Practices Training team Weekly
Train the Trainer Training team Quarterly
Trainers' monthly rating Training team Monthly
Performance based annual growth HR Team Annual
R n R HR Team Quarterly
Shift rotation Operations Monthly
Provide night allowance Operations Monthly
Provide pickup/drops for night shift Operations Daily
Games & fun activities in night shift HR Team Weekly
Enhance night allowance for future HR Team Weekly
Take pre approval for night allowance Operations Monthly
Make proper rostering to avoid transport delay. Transport team Daily
Reduce time to cancel transport in case of self arrangement Transport team Daily
Put guards mandatory in cabs with female agents. Security Daily
Encourage agents to self manage breaks. Operations Daily
Mandate split off with Sat or Sun. Operations Daily
Take pre approval for night contests Operations Quarterly

40
Before the project, more
than 50% of agents had
AHT above 300 seconds
whereas after the
project, AHT dropped
down to less than 300
seconds for over 75% of
the agents.
AHT BOX PLOT:PRE DATA vs POST DATA
c
CONTROL

41
GRAPHICAL SUMMARY: PRE DATA vs POST DATA
Post Project:
Mean:200.93 Median :209 StDev:102.4
Most of the
agents have
AHT less than
300 seconds
after the
project
c
CONTROL

BAR GRAPH: PRE DATA vs POST DATA
Mean
Pre Improvement:405.65
Post Improvement: 200.93
Median
Pre Improvement:336.00
Post Improvement:209.00
St. Dev
Pre Improvement: 273.42
Post Improvement: 102.44
c
CONTROL

43
SIGMA LEVEL & DPMO:PRE vs POST IMPROVEMENT
c
CONTROL
Pre Improvement Data Post Improvement Data
 No. of defects were 254 out of 545
opportunities
 DPMO was 466,055
 Sigma level was 1.6
 No. of defects are 118 out of 545
opportunities
 DPMO reduced to 216,514
 Sigma level went up to 2.3

44
Prior improvement, there were special cause variation so the process
was statistically out of control, however, post-improvement, there is
no special cause variation and the process is statistically in control.
IMR CHART : PRE vs POST IMPROVEMENT
c
CONTROL

45
c
CONTROL
LEADERSHIP APPRECIATION!

46
Thank you!
subhash.mandal09@gmail.com

Reducing AHT

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