Six Sigma Project- GB

SIX SIGMA PROJECT:
Lowering the Average Handling Time
Project by : Mr. Livanshu Kashyap

VOICE OF CUSTOMER-VOC
Customer Comments Critical to Quantity- CTQ’s
Vice President – Operations
Escalation received from the client.
Process hasn’t met AHT SLA of
2.5min/bill in Mar 15.
AHT target not met
Vice President - Marketing
Business with IBM is at stake because of
AHT SLA target not met. Huge penalty is
to be given to IBM.
AHT target not met
Gen. Manager -Operations
Penalty of $25 USD per failed bill will be
assessed since the process couldn’t
meet AHT Target in Mar 15.
AHT target not met
Manager- Operations
We are much concerned about the
revenue loss to our company till the
month of March.
AHT target not met

PROJECT CHARTER
Business Case Team
 ATIOS is one of the leading business processing outsourcing company
working for leader clients like IBM, ATI, Bharti, Vodafone etc. with branches in
Bangalore & Gurgaon.
 In March 2015, the revised AHT service-level agreement of 2.5 min/bill
failed.
 Its mandatory for both branches to get inline with revised AHT SLA targets
for business continuity & to avoid potential revenue loss.
Sponsor – Mr. Vishal Ghai BB- Mr. Robin Kaith
Champion- Mr. Mohinder GB- Mr. Livanshu Kashyap
MBB- Mr. Anand Sharma Team member- Mr. Babulal
Problem Statement Goal Statement
Analysis in March 2015, AHT report reveals:
Out of 3371 bills processed 62.87% i.e.2120 bills did not meet goal AHT.
Business continuity with IBM is at stake if process doesn’t meet AHT target
for 3 consecutive months.
By March 15 penalty to be paid is $22,000 USD by ATIOS. Every
subsequent month wherein process doesn’t meet client AHT target, then a
penalty of $25 USD per failed bill will be applicable
To achieve monthly AHT of 2.5min/bill for the entire process
by 31st July 2015.
In Scope: Bill Processing Team.
Out Scope: All other departments.
Milestones
Days
Define
Measure
Analyze
Improve
Control
Start Dates: 1-April
3-April
6-April
11-April
20-April
Days
2
3
5
10
10

RASIC
ACTIVITIES
Sponsor –
Vishal Ghai
Champion –
Mohinder
MBB – Anand
Sharma
BB – Robin
Kaith
GB – Livanshu
Kashyap
Team Member-
Babulal
Process Data I I , A I C S R
Project Charter I I , A I , C R S S
Roles and Responsibilities I I , A I R S S
Process Map I I , A I C S S
Data Collection Plan I I , A I , C R S S
Validate Measurement System I I , A I R S S
Graphical Summary I I , A I C R S
Cause and Effect Diagram I I , A I R S S
Data validation of Xs I I , A I , C R S S
Hypothesis Testing I I , A I , C R S S
Vital Xs (Root Causes) I I , A I , C R S S
Quality Function Deployment I I , A I , C R S S
Improvement Validation I I , A I , C R S S
Failure Modes & Effect Analysis I I , A I , C R S S
Control Plan I I , A I , C R S S
Control Chart I I , A I , C R S S
Cost Benefit Analysis I I , A I , C R S S
R – Responsible Solely and directly responsible for the activity.
A – Approve Reviews and assures that the activity is being done as per expectations.
S – Support Provides the necessary help and support to the owner.
I – Inform Is to be kept informed of the status/progress being made.
C – Consult Is to be consulted for this activity for inputs .

SIPOC
Customer
Order from
Customer
START
Bill
Acknowledge
Billing Deptt.
END
Allow or deny
bill
Process PO
for payment
Send Invoice
Place OrderBilling Deptt.
Computer
Input
Bill
Generation
Customer
Finance Deptt. Payment Report Management
A SIPOC is a High level view of a process.

COMMUNICATION PLAN
Activity Target Audience Mode Who Frequency Backup
Project Status
Project Sponsor,
Champion
Email Mr. Livanshu
Mon, Wed & Sat Mr. Robin
Tollgate Review
Champion, MBB, BB
& GB
Email Mr. Livanshu As per milestones Mr. Robin
Resource management Sponsor Email
Mr. Vishal
Ghai
As per requirement Mr. Mohinder
Activity assignment Team Members Email Mr. Livanshu As per requirement Mr. Robin
Daily meetings Required Personal Email Mr. Livanshu Daily Mr. Robin
Deliverables Team members Board Mr. Babulal Tuesday &Friday Mr. Robin
Complaints/ Feedback Champion, MBB, BB Email Mr. Robin As per requirement Mr. Livanshu

DATA COLLECTION PLAN
KPI/Y Operational Definition Defect Definition
Performance
Standard
Specification Limit
Opportunity
LSL USL
AHT
monthly
Total time taken from opening a bill till
closing a bill for all the bills processed
in a month/ Total no of bills processed
AHT greater than
2.5 min/bill for a
month
AHT less or equal to
2.5 min/bill for a
month
NA
2.5 min/bill
for month
Monthly
KPI Data Type
Data Items
Needed
Formula to be used Unit
Plan to collect Data
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
monthly
Continuous
Bill processing
time
Bills opening time + Bills
processing time + Hold/Wrap
Time + Bills closing time
Sec Excel Sheet Existing NA NA
1st
Mar 2015 –
31st
Mar 2015

MEASUREMENT SYSTEM VALIDATION
Measurement system used for AHT measurement : ASP* Net weaver (Software)
Working Principle:
 The time starts as we execute a dedicated T-code (VL01N) to start bill processing and calculate
AHT for the same the moment as we execute a dedicated T-code (ZSD102) for finalizing the bill.
 Its an automatic tool that is being sourced from a SAP server calibrated with GMT.
Issues that can cause failure Validation Result
Check if the SAP server is calibrated
with standard i.e. Greenwich Mean
Time?
The check is being done by SAP team pre-
installation & monthly on 1st of
each month that SAP Net weaver is calibrated
with standard.
Successful.
SAP Net weaver found calibrated
with standard.
The algorithm behind
SAP Net weaver is calculating accurate
Randomly 10 records are selected 10 times
and matched with their respective backhand
files.
Successful, SAP team found it calibrated
with their respective backhand files.
Attribute Agreement Analysis is also being done to validate & verify the measurement system.

CONTROL CHART – Levels of AHT
The I-MR Chart of AHT shows
that the process in not within
control limits and requires an
urgent attention.
Data points in chart
representation are all data
points from June 15 to Sep 15
i.e. 3371 data points.
Within limits- Green circles
Out of limits- Red squares

ATTRIBUTE AGREEMENT ANALYSIS
Within Appraisers
Assessment Agreement
Appraiser # Inspected # Matched Percent 95% CI
1 100 98 98.00 (92.96, 99.76)
2 100 99 99.00 (94.55, 99.97)
3 100 97 97.00 (91.48, 99.38)
# Matched: Appraiser agrees with him/herself across trials.
Each Appraiser vs Standard
Appraiser # Inspected # Matched Percent 95% CI
1 100 96 96.00 (90.07, 98.90)
2 100 97 97.00 (91.48, 99.38)
3 100 96 96.00 (90.07, 98.90)
# Matched: Appraiser’s assessment across trials agrees with
the known standard.
Between Appraisers
# Inspected # Matched Percent 95% CI
100 97 97.00 (91.48, 99.38)
Result: Data seems to be good and measurement errors are under limits.

GAGE R&R

GRAPHICAL SUMMARY
 Data is found
Non Normal
In Normality test.
 Thus, we are considering
Median as reference.
 Target median should be less
than 95% CI range of median.
 We have decided to take 2.5
min/bill as our target.

HISTOGRAM
 Histogram between
Frequency and AHT of all data
points.
 Target of 2.5 min/bill is as
highlighted in graph.
 Current median is 2.66
min/bill as shown in graph.
 We need to shift the peak of
graph to
2.5 min/bill.

PROCESS CAPABILITY ANALYSIS
PROCESS CAPABILITY
Mean 2.69
Standard Deviation 0.5449
Variance 0.2969
Median 2.66
Total Opportunities 3371
Defects 2120
Defect % 62.87%
Yield % 37.13%
DPMO 628686
Sigma Level 1.17
Sigma Level of the process is very poor.
Improvement in Process capability is
necessary.
Low
High
Moderate
σ level

To check if the data is normal
or non normal.
Results: Data is Not normal (Ha)
Aim:
Observation:
Null and alternate
hypothesis:
Ho – Data is normal
Ha – Data is non normal
NORMALITY TEST
Numerous data points seems
to be off the normality line.
P-Value <0.005

Aim:
To check the Stability of the
process.
Observations:
Area P-Value
Cluster 0.001
Mixtures 0.999
Trends 0.082
Oscillation 0.918
 P-value of clustering is less
than 0.005 thus, it shows the
presence of clusters.
Result: Data is Random.
RUN CHART OF AHT in minutes
Null and alternate
hypothesis:
Ho – Data is not random
Ha – Data is random

CAUSE & EFFECT DIAGRAM
Fishbone diagram
(also known as
Ishikawa-diagram)
identifies possible
causes for an effect or
problem. In our case,
the problem is AHT of
bills.

BRAINSTORMING-ROUND ROBIN
Brainstorming is a
group creativity by
which efforts are
made to find a
conclusion for specific
problems by gathering
a list of ideas.
Sr. Managers 1
Managers 3
Ass. Managers 2
Sr. Executives 3
Executives 8
Team Leaders 8
Total 25
A brainstorming session was being organized on
15-April-15.
In which people of different designations &
departments participated.
In this, all participants voted YES/NO on their
checklist for the problems according to their
opinion (as shown in graph)
Their ideas has also been added.
Participants:
0
2
4
6
8
10
12
14
16
18
20
Votes

DELPHI TECHNIQUE
What is Delphi technique?
The Delphi technique is a structured communication technique that is a
systematic & interactive method which relies on a panel of only subject
matter experts.
 Feedback from ground level staff
 Reveals hidden X’s via secret conversation with SMEs.
 Unbiased results
Without any information to management, We went for a GEMBA WALK on floor to see the
problems and talked to the Subject Matter Experts.
We have found several more X’s:
 Keyboards are aged & do not work well
 Operators have older version of SAP Netweaver
 Computer configuration is out dated
 Seats are not comfortable
 Table height more/less

Measure or X’s Data Type Operational Definition Data responsibility Hypothesis Tests
Week Ending (Friday) Discrete Fridays VS Other days IT Team Mood’s Median Test
Team Leader Discrete Person responsible for Team Management HR & MIS Data Mood’s Median Test
Trainer Discrete Person responsible for Imparting Training HR & MIS Data Mood’s Median Test
AM Discrete Person responsible for Management HR & MIS Data Mood’s Median Test
Manager Discrete Person responsible for Upper Management HR & MIS Data Mood’s Median Test
Complexity Discrete 1 – 2 – 3 as per strategy metrics Strategy Team Mood’s Median Test
Transaction Type Discrete Defined per source type originated SAP Team Mood’s Median Test
Shift Discrete Time Slot defined to work HR Data Mood’s Median Test
Gender Discrete Sex of the individual HR Data Mood’s Median Test
Location Discrete Work location i.e. Gurgaon & Bangalore HR Data Mood’s Median Test
Qualification Discrete Highest degree of education of an Individual HR Data Mood’s Median Test
Marital Status Discrete Current marital status i.e. Single or Married HR Data Mood’s Median Test
Typing Speed Continuous Words typed per minute Training & IT Team Regression Analysis
Age Continuous Age of an individual in years HR Data Regression Analysis
Experience Continuous Total experience in the process in months HR Data Regression Analysis
Quality Discrete Monthly Quality score obtained by agent Quality department Mood’s Median Test
Operating System Discrete Windows XP, Vista and Windows 7. IT Team Mood’s Median Test
System Configuration Discrete RAM- 512mb, 1GB and 2GB IT Team Mood’s Median Test
ASP Version Discrete Version- 720 and 740 IT & ASP Team Mood’s Median Test
Keyboard Discrete Different manufacturers i.e. Deill or Unitech IT Team Mood’s Median Test
DATA VALIDATION OF X’s

HYPOTHESIS TEST- AHT vs Trainers
Null hypothesis (Ho) - All medians are equal
Alternative hypothesis (Ha) - At least one median is
different
Mood Median Test: AHT versus Trainer
Chi-Square = 50.88 DF = 7 P = 0.000
Individual 95.0% CIs
Trainer N≤ N> Median Q3-Q1 --------+---------+---------+--------
Gagan 196 260 2.742 0.754 (----*----)
Kishore 227 217 2.648 0.572 (---*----)
Lalit 190 207 2.694 0.642 (------*------)
Praveen 202 187 2.660 0.617 (--*-)
Ruhani 274 165 2.482 0.661 (----*-----)
Sudesh 240 204 2.616 0.625 (----*---)
Varun 156 208 2.735 0.594 (--*----)
Vinay 201 237 2.722 0.651 (----*---)
--------+---------+---------+--------
2.52 2.64 2.76
To check if different trainers are affecting the
AHT.
Aim:
Observations:
Result: Different trainers are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Qualification
Mood Median Test: AHT versus Qualification
Chi-Square = 129.53 DF = 10 P = 0.000
Quali. N≤ N> Median Q3-Q1 - -+---------+---------+---------+
B.A 322 219 2.566 0.573 (---*---)
B.B.A 91 127 2.806 0.679 (------*---)
B.C.A 117 97 2.614 0.596 (---*---)
B.Com 323 245 2.580 0.661 (--*--)
B.Sc 264 205 2.579 0.653 (---*---)
B.Tech 96 64 2.575 0.491 (-----*---)
M.A 81 85 2.679 0.609 (----*--)
M.C.A 161 183 2.703 0.632 (--*----)
M.Com 99 189 2.833 0.664 (--*---)
M.Sc 40 83 2.851 0.712 (------*--------)
MBA 92 188 2.910 0.841 (-----*--)
----+---------+---------+---------+--
2.55 2.70 2.85 3.00
different
To check if different qualifications are affecting
the AHT.
Aim:
Result: Different qualifications are highly affecting the AHT.
Observations:

HYPOTHESIS TEST- AHT vs Typing Speed
different
Regression Analysis: AHT vs Typing Speed
The regression equation is
AHT = 4.942 - 0.04724 Typing Speed
S = 0.284281 R-Sq = 72.8% R-Sq(adj) = 72.8%
Analysis of Variance:
Source DF SS MS F P
Regression 1 728.22 728.220 9010.86 0.000
Error 3369 272.27 0.081
Total 3370 1000.49
Typing Speed is directly proportional to AHT.
Result: Different typing speeds are highly affecting the AHT.
To check if different typing speeds are affecting
the AHT.
Aim:
Add Gridlines Observations:
80706050403020
8
7
6
5
4
3
2
1
S 0.284281
R-Sq 72.8%
R-Sq(adj) 72.8%
Typing Speed
AHT
AHT = 4.942 - 0.04724 Typing Speed

HYPOTHESIS TEST- AHT vs Locations
Mood Median Test: AHT versus Location
Mood median test for AHT
Chi-Square = 29.71 DF = 1 P = 0.000
Location N≤ N> Median Q3-Q1 --------+---------+---------+------
Bangalore 741 586 2.596 0.622 (------*-----)
Gurgaon 945 1099 2.706 0.643 (---*-----)
--------+---------+---------+-----
2.600 2.650 2.700
different
To check if different locations are affecting the
AHT.
Aim:
Observations:
Result: Different locations are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Shifts
Mood Median Test: AHT versus Shift
Chi-Square = 50.02 DF = 3 P = 0.000
Shift N≤ N> Median Q3-Q1 --------+---------+---------
Afternoon 355 263 2.592 0.624 (------*-----)
Evening 338 280 2.592 0.608 (-------*-------)
Morning 329 277 2.621 0.636 (------*-----)
Night 664 865 2.736 0.630 (---*---)
--------+---------+---------
2.590 2.660
different
Observations:
Aim:
To check if different shifts are affecting the AHT.
Result: Different shifts are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Age
Regression Analysis: AHT versus Age
AHT = 2.785 - 0.003048 Age
S = 0.544533 R-Sq = 0.2% R-Sq(adj) = 0.1%
Analysis of Variance
Source DF SS MS F P
Regression 1 1.53 1.52688 5.15 0.023
Error 3369 998.96 0.29652
Total 3370 1000.49
Observations:
Aim:
To check if different age is affecting the AHT.
different
Result: Different ages are moderately affecting the AHT.

HYPOTHESIS TEST- AHT vs System Configuration
Observations:
Aim:
To check if different system configurations are
affecting the AHT.
different
Result: Different system configurations are not affecting the AHT.
Mood Median Test: AHT versus Sys Config
Chi-Square = 0.13 DF = 1 P = 0.718
Sys Config N≤ N> Median Q3-Q1 -----+------+------+------+-
1024mb 835 845 2.6684 0.6511 (-------------*-----------
--)
512mb 851 840 2.6627 0.6422 (---------------*--------------)
-----+------+------+------+-
2.640 2.660 2.680 2.700
Overall median = 2.6654

HYPOTHESIS TEST- AHT vs Manager
Mood Median Test: AHT versus Manager
Chi-Square = 29.71 DF = 1 P = 0.000
Manager N≤ N> Median Q3-Q1 --------+---------+---------+--
------
Uttam 741 586 2.596 0.622 (------*-----)
Vikas 945 1099 2.706 0.643 (---*-----)
--------+---------+---------+--
2.600 2.650 2.700
Overall median = 2.665
Observations:
Aim:
To check if different managers are affecting the
AHT.
different
Result: Different managers are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Experience
Regression Analysis: AHT versus Experience
AHT = 2.690 + 0.000993 Experience
S = 0.544947 R-Sq = 0.0% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 0.01 0.006532 0.02 0.882
Error 3369 1000.48 0.296967
Total 3370 1000.49
Observations:
Aim:
To check if different experiences are affecting the
AHT.
different
Result: Different experiences are not affecting the AHT.

HYPOTHESIS TEST- AHT vs Complexities
Mood Median Test: AHT versus Complexity
Chi-Square = 7.09 DF = 2 P = 0.029
Comp. N≤ N> Med. Q3-Q1 -------+---------+---------+---------
1 608 535 2.628 0.601 (-------*---------)
2 540 584 2.692 0.692 (---------*---------)
3 538 566 2.682 0.647 (----------*-------)
-------+---------+---------+---------
2.625 2.660 2.695
Observations:
Aim:
To check if different complexities are affecting the
AHT.
different
Result: Different complexities are not affecting the AHT.

HYPOTHESIS TEST- AHT vs Transaction Types
Mood Median Test: AHT versus Transaction Type
Chi-Square = 4.31 DF = 4 P = 0.366
Transaction Individual 95.0% CIs
Type N≤ N> Median Q3-Q1 +---------+---------+---------+----
--
1 327 343 2.684 0.650 (-----------*------)
2 338 318 2.648 0.611 (----------*----------)
3 328 348 2.679 0.687 (----------*-------------)
4 368 330 2.630 0.631 (------*--------------)
5 325 346 2.677 0.652 (--------*-----------)
+---------+---------+---------+------
2.600 2.640 2.680 2.720
Observations:
Aim:
To check if different transaction types are
affecting the AHT.
different
Result: Different transaction types are not affecting the AHT.

HYPOTHESIS TEST- AHT vs Operating Systems
Mood Median Test: AHT versus Operating System
Chi-Square = 552.37 DF = 1 P = 0.000
Operating Individual 95.0% CIs
System N≤ N> Median Q3-Q1 ----+---------+---------+---------+-
-
Win7 1556 962 2.550 0.534 (-*)
WinXP 130 723 3.161 0.401 (*)
----+---------+---------+---------+--
2.60 2.80 3.00 3.20
Observations:
Aim:
To check if different operating systems are
affecting the AHT.
different
Result: Different operating systems are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs ASP Version
Mood Median Test: AHT versus ASP Version
Chi-Square = 22.45 DF = 1 P = 0.000
SAP Individual 95.0% CIs
Version N≤ N> Median Q3-Q1 ----+---------+---------+---------+--
720 892 754 2.606 0.711 (-----*-------)
740 794 931 2.704 0.591 (----*-----)
----+---------+---------+---------+--
2.600 2.640 2.680 2.720
Observations:
Aim:
To check if different ASP versions are affecting
the AHT.
different
Result: Different ASP versions are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Quality Scores
Mood Median Test: AHT versus Quality
Chi-Square = 0.10 DF = 2 P = 0.950
Quality N≤ N> Median Q3-Q1 -+---------+---------+---------+-----
8 571 575 2.6669 0.6304 (-----------*--------------)
9 545 536 2.6559 0.6566 (------------*----------------)
10 570 574 2.6689 0.6651 (-------------*-----------)
-+---------+---------+---------+-----
2.625 2.650 2.675 2.700
Aim:
To check if different quality scores are affecting
the AHT.
different
Observations:
Result: Different quality scores are not affecting the AHT.

HYPOTHESIS TEST- AHT vs Keyboards
Mood Median Test: AHT versus Keyboard
Chi-Square = 72.23 DF = 1 P = 0.000
Keyboard N≤ N> Median Q3-Q1 --------+---------+---------+-----
---
Deill 1153 912 2.602 0.598 (--*--)
UniTech 533 773 2.815 0.695 (----*---)
--------+---------+---------+--------
2.640 2.720 2.800
Aim:
To check if different keyboards are affecting the
AHT.
different
Observations:
Result: Different keyboards are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Marital Status
Mood Median Test: AHT versus Marital Status
Chi-Square = 10.83 DF = 1 P = 0.001
Marital Individual 95.0% CIs
Status N≤ N> Median Q3-Q1 -------+---------+---------+-------
--
Married 913 817 2.629 0.654 (-------*-------)
Unmarried 773 868 2.701 0.635 (--------*------)
-------+---------+---------+---------
2.625 2.660 2.695
Aim:
To check if different marital statuses are affecting
the AHT.
different
Observations:
Result: Different marital statuses are not affecting the AHT.

HYPOTHESIS TEST- AHT vs Gender
Mood Median Test: AHT versus Gender
Chi-Square = 86.87 DF = 1 P = 0.000
Gender N≤ N> Median Q3-Q1 ---+---------+---------+---------+--
-
Female 506 768 2.829 0.702 (---*---)
Male 1180 917 2.597 0.587 (--*-)
---+---------+---------+---------+---
2.60 2.70 2.80 2.90
Aim:
To check if different genders are affecting the
AHT.
different
Observations:
Result: Different genders are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Gender & Location
Aim:
To check if different genders in different locations
are affecting the AHT.
different
Observations:
Result: Different different genders in different locations are highly affecting the AHT.
As the Boxplot shows,
Bangalore-females(Avg. 3.2min) takes
more AHT as compared to Gurgaon-
Females(Avg. 2.75min).
Whereas, Males on both locations are
close to median with a little difference
between each other(< 0.25min)

HYPOTHESIS TEST- AHT vs Week Days
Mood Median Test: AHT versus Day
Chi-Square = 21.38 DF = 1 P = 0.000
Day N≤ N> Median Q3-Q1 ---------+---------+---------+----
---
Friday 639 771 2.716 0.645 (-----*------)
Other Days 1047 914 2.627 0.633 (-----*----)
---------+---------+---------+-------
2.640 2.680 2.720
Aim:
To check if different week days are affecting the
AHT.
different
Observations:
Result: Different week days are highly affecting the AHT.

HYPOTHESIS TEST- AHT vs Team Leader
Mood Median Test: AHT versus Team Leader
Chi-Square = 13.20 DF = 9 P = 0.154
Leader N≤ N> Median Q3-Q1 ----+---------+---------+---------+--
Akash 164 184 2.706 0.717 (--------*----)
Amit 169 150 2.617 0.551 (---*-------)
Ashutosh 155 167 2.686 0.635 (------*----------)
Gaurav 160 186 2.732 0.677 (---------*----)
Jigar 162 159 2.660 0.697 (------*------)
Kartik 155 169 2.704 0.596 (-------*------)
Manoj 154 179 2.715 0.567 (--------*---------)
Paras 169 155 2.644 0.700 (-----*--------)
Rajat 206 179 2.605 0.632 (----*----------)
Yogender 192 157 2.594 0.674 (-------*---------)
----+---------+---------+---------+--
2.560 2.640 2.720 2.800
Aim:
To check if different team leaders are affecting
the AHT.
different
Observations:
Result: Different team leaders are not affecting the AHT.

QUALITY FUNCTION DEPLOYMENT
Vital X's
Rating
Action Plans
CompletenessMatrix
InstalltypingtutorinallPCs
Daily15min.typingpractice
compulsoryforallemployees
Monthlytypingtestsand
prizes&Certification
Infuture,recruitmentofpeoplehaving
typingspeed≤45wpmmandatory
Masterdegreeholdersshouldbegiven
sensitivitycounselingthat
theyhaveanimportantrole
Infuture,recruitmentofBachelor
degreeholdersarerecommended
InstallWin7inallPC’s
1-hourtrainingofWin7features
ChangeUnitechkeyboards
withDeill*
Trainingtoalltrainersand
feedbackfromassociates
regardingimprovements
Alltrainersmustadoptthesame
improvedmethodoftraining
MonthlyTargetstotrainers
Swappingtransfersofparticular
designationstoeachplant
SpecialtrainingprogramforBangalore-
Females
Manage30-70%of
Female-maleRatio
Flexibletoleaveofficeonlyafter
completingtheday'starget
Camerainstallationsandstrictactions
toblameworthy
Exchangeboththemanagers
witheachother
InstallASP*740inallsystems
Typing Speed 10 6 8 7 9 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 350
Qualifications 9 0 0 0 0 7 8 0 0 0 0 0 0 0 0 0 0 0 0 0 135
Operating System 9 0 0 0 0 0 0 9 7 0 0 0 0 0 0 0 0 0 0 3 171
Keyboard 8 0 0 0 0 0 0 2 2 8 0 0 0 0 0 0 0 0 0 0 96
Trainer 7 0 0 0 0 0 0 0 0 0 7 7 7 4 0 0 0 0 0 0 175
Location 6 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 5 0 54
Gender 5 0 0 0 0 0 0 0 0 0 0 0 0 0 7 5 0 0 0 0 60
Fridays 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 32
Shift 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 9 0 0 54
Manager 3 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 9 0 42
ASP Version 2 0 5 0 0 0 0 5 3 0 0 0 0 0 0 0 0 0 0 9 44
Deployment Matrix → 60 90 70 90 63 72 107 85 114 49 49 49 67 35 25 27 59 57 45 Total
Investment ≅ $0 $0 $500 $0 $0 $0 $2,000 $0 $1000 $0 $0 $0 $0 $300 $0 $0 $2,000 $0 $1,500 $7,300
High ≥90
Medium ≥60
Low <60
 Quality Function Deployment shows what action plans we need to do first and further according to their preference.
 Also it is showing how much investment we need to do for a particular plan.

FAILURE MODE EFFECT ANALYSIS
X's ACTION PLANS FAILURE MODES EFFECT ON EDR S O D RPN RMS RTP RESPONSIBILITY
Typing
Speed
Install typing tutor in all PCs Typing tutor not working No improvement in typing speed 6 4 1 24 Accept
Install latest TT & provide assistance
with helpline number
IT Team
Daily 15 min. typing practice compulsory for
all employees
Employees not participating in practice No improvement in typing speed 6 6 1 36 Accept
Daily attendance and monthly Quality
score depends on it
Trainers
Monthly typing tests and prizes & Certification Biased Results or less participation Prizes to non-deserving 5 6 6 180 Accept Feedback from participants AGM-Operations
In future, recruitment with typing speed
≤45wpm mandatory
Lesser Recruitment Less faculty 5 7 1 35 Accept Widen the hiring area HR Team
Employees demanding high salary Financial loss to company 5 5 1 25 Avoid - -
Qualificati
ons
Master degree holders should be given
sensitivity counseling that they have an
important role
Members do not attend counseling No improvement in AHT 4 5 1 20 Accept Provide them refreshment to woo HR Team
MD holders (seniors in union)
shows ego and do not improve
Negative impact on AHT or
Union Strike 7 7 3 147 Accept Management to convince Union Admin deptt.
In future, recruitment of Bachelor degree
holders are recommended
Less Recruitment
Less faculty and B. degree holders
demanding high salary 5 7 1 35 Accept
Give them early bonus by deducting it
from Diwali bonus
Finance Deppt.
Operating
System
Install Win7 in all PC’s Win7 difficult to use for some No or –ve impact on AHT 5 4 3 60 Avoid - -
1-hour training of Win7 features Operators not able to understand No or –ve impact on AHT 4 6 2 48 Transfer Hire 3rd
party quality trainer HR Team
Keyboard Change Unitech keyboards with Deill* New keyboards difficult to use No improvement in AHT 8 3 2 48 Avoid - -
Trainer
Training to all trainers and feedback from
associates regarding improvements
Biased feedback Skilled trainers not getting credits 6 5 6 180 Transfer Feedback from participants too AGM-Operations
Training not effective No improvement in AHT 6 3 3 54 Avoid Deploy an end-training test HR Team
All trainers must adopt the same method of
training
Trainers failed to adopt
same method
No improvement in AHT 5 5 4 100 Transfer Hire 3rd
party quality trainer Admin deptt.
Monthly Targets to trainers
Trainers failed to achieve targets AHT fines 8 7 2 112 Accept
Notice them that incentives are based
on target completion
AGM-Operations
Targets are not achievable Trainers not giving efforts 6 6 1 36 Accept Praise on satisfactory target completion Upper Mangmnt.
Location
Swapping transfers of particular designations
to each plant
Employees refuse to accept
transfer order
Internal disturbance in company 6 3 1 18 Accept
Transfer them for a short period and
analyze results
HR Team
Gender
Special training program for Bangalore-
Females
No impact on B-F after program No improvement in AHT in B 7 3 3 63 Transfer
Hire 3rd
party quality trainer fire
undisciplined operators
Admin deptt.
Maintain 30-70% of Female-male Ratio Less recruitment Less faculty 5 7 1 35 Accept Widen the hiring area HR Team
Fridays
Flexible to leave office only after completing
the day's target
Workers leaving without
completing targets
Negative impact on AHT 7 8 2 112 Accept
Strict actions for blameworthy + Impact
on incentives and bonuses
Managers
Shift
Camera installations and strict actions for
blameworthy
Surveillance ignorance or
biased actions
Workers sleeping in night shifts,
thus no improvement 6 6 5 180 Transfer Surveillance by 3rd
party HR Team
Manager Exchange both the managers with each other No impact or improvement No improvement in AHT 6 3 2 36 Accept Transfer for a short period HR Team
ASP
version
Install ASP 740 in all systems
New ASP Version may be difficult
to operate by some users
No improvement in AHT 6 4 3 72 Avoid Initial difficulties only -

CONTROL PLAN
Sr. Control Plans Suggested Action Plan Responsibility Frequency Scope
1 Unitech keyboards to be changed IT Head to arrange & change all Unitech keyboards IT Head Once
2 Windows7 to be installed IT Head to arrange and update all PCs with Win7 IT Head Once
3 Update hiring process with mandatory ≤45wpm speed HR Head to deploy new recruiting policy HR Head Once
4 Daily Typing practice (15 min.) Inform Shift Incharge to plan & deploy activity Shift Incharge Alternate Days
5 Windows7 features training IT Head to plan and execute a training session IT Head Once
6 Update hiring process preferring Bachelors Degree holders HR Head to update company hiring policy HR Head Once
7 Typing tests to be conducted Notice and schedule all training managers Training manager Monthly
8 Swapping transfers of Bangalore-F and Gurgaon-F HR Head to confirm transfers if possible HR Head Once
9 Sensitivity counseling to Master Degree Holders Training manager to deploy counseling sessions Training manager Once
10 Typing Tutor to be installed IT Head arrange app and confirm deployment IT Head Once
11 Cameras to be installed IT Head to install cameras at specific areas IT Head Once
12 Managers to be swapped of both locations HR Head to notice managers for transfer HR Head Once
13 Common training to be given to all trainers AGM to plan & deploy common training sessions AGM- Operations Once
14 Monthly targets to be given to all trainers AGM to decide and give monthly targets AGM- Operations Monthly
15 ASP* 740 to be installed on all PCs IT Head to install ASP* latest version (740) IT Head Once
16 Special Training sessions for Bangalore-Females Training man. to deploy special training sessions Training manager
17
All operators to be notified that they can leave office after
completing the day's target
Adm-Manager to display notice for this facility Admin-Manager Once
18 Update hiring process to prefer males HR Head to change hiring ratio to 70-30% (M-F) HR Head Once
19 Strict action policy to be introduced against guilty HR head to publish notice for strict action HR Head Once
All Employees All Trainers All Operators All Managers All Master degree holders

IMPROVEMENT VALIDATION- Before & After Analysis
Observations:
Histogram representation of data shows improvement in monthly AHT of the process.

CONTROL CHART- Post Improvement
Observations:
Negligible amount of points are out of the limits.
(Data of 1 month-1500 data points post project is analyzed)

SUMMARY
Pre-Improve Calculation Post-Improve Calculation
Mean 2.69 2.16
Median 2.66 2.09
Standard Deviation 0.5449 0.4073
Variance 0.2969 0.1659
Total Opportunities 3371 1400
Defects 2120 301
Pass %age 37.13 78.5
Defects %age 62.87 21.5
DPMO 628,686 215,000
SIGMA level 1.17 2.10

THANK YOU
Regards:
Livanshu Kashyap
livanshu@gmail.com

Six Sigma Project- GB

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