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SIX SIGMA (BLACK BELT)–PROJECT Page 1
SIX SIGMA BLACK BELT
PROJECT REPORT
MANAGING & ENHANCING QUALITY OF IT OPERATIONS BY REDUCING THE UNPLANNED DOWNTIME
HAKEEM–UR–REHMAN 27–02–2012
Lahore, Pakistan
SUPERVISOR: DR. NADEEM SHAFIQ BUTT
THIS PROJECT REPORT IS PART OF THE REQURMENT FOR THE
SIX SIGMA BLACK BELT COURSE
ORGANISED BY
PIQC INSTITUTE OF UALITY
AND
SINGAPORE QUALITY INSTITUTE
SIX SIGMA (BLACK BELT)–PROJECT Page 2
TABLE OF CONTENTS
Sr. No. Topic Page No.
1 DEFINE PHASE 3 Project Charter 4
Deployment Process Flow Diagram 5 SIPOC Diagram 5 KPI’s and KPO’s 8
2 MEASURE PHASE 9
Measurement System Analysis (MSA) 10 Line Chart (Month Wise Downtime) 12 Pie Chart (Category Wise Downtime) 13 Pareto Analysis (Category Wise Downtime) 13 Cause & Effect Diagram (Downtime) 14 Pie Chart Country Wise Downtime 14 City Wise Downtime 14 Bar Chart Shift Wise Average Downtime 15 Gender Wise Average Downtime 16 Qualification Wise Downtime 16 Experience Wise Downtime 17 Age Wise Downtime 17 Multiple Bar Chart Country & City Wise Downtime 17 Qualification & Experience Wise Downtime 18 Age & Experience Wise Downtime 18 Probability Plot 18 Current Sigma Level Calculation 19
3 ANALYSIS PHASE 20
Testing of Hypothesis 21
4 IMPROVE PHASE 33 Design of Experiment 34
5 CONTROL PHASE 42 Process Failure Mode & Effect Analysis 43
Control Charts 59
SIX SIGMA (BLACK BELT)–PROJECT Page 3
DEFINE PHASE:
Project Charter Process Flow Diagram SIPOC Diagram
KPI’s & KPO’s
DEFINE
PHASE
SIX SIGMA (BLACK BELT)–PROJECT Page 4
PROJECT CHARTER: PROJECT TITLE:
Managing & Enhancing Quality of It Operations By Reducing The Unplanned Downtime
BUSINESS CASE:
Last year (from February to August, 2011) due to the different issues in the IT operations and
development company faces unplanned downtime which causes the loss of revenue,
reputation and customers. By considering these issues the overall losses are approximately
Average Rs. 23981100 per month (Average Downtime per month X Average Cost (Human
Resource) per Minute X 7 Months).
By reducing above said losses by 30%, we will be able to save approximately average Rs.7194330 per month.
PROBLEM STATEMENT:
Managing quality by controlling and improving processes of identified major downtime categories which are causing 45% of total down time.
OBJECTIVE: Reduction in %age downtime up to 30% of the total downtime.
METRICS: Primary Metric = Downtime (%) = (Total Downtime / Total Production Time) * 100
Secondary Metric = % Yield
PROJECT SCOPE:
IT Operations & Development
BEFORE IMPROVEMENT MONTHLY DOWNTIME:
AFTER IMPROVEMENT MONTHLY DOWNTIME:
Schedule:
Feb Mar Apr May Jun Jul Aug
Total 8079 6961 7047 6263 6559 5405 6645
0
2000
4000
6000
8000
10000
To
tal D
ow
nti
me
Month wise Total Downtime
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Total Downtime 8079 6961 7047 6263 6559 5405 6645 5430 4355 2122 2276
0
2000
4000
6000
8000
10000
To
tal D
ow
nti
me
Month Wise Total Downtime
ID Task Name Start Finish Duration
Oct 2011 Nov 2011 Dec 2011 Jan 2012 Feb 2012
23/10 30/10 6/11 13/11 20/11 27/11 4/12 11/12 18/12 25/12 1/1 8/1 15/1 22/1 29/1 5/2 12/2
1 10d10/28/201110/17/2011Define
2 15d11/18/201110/31/2011Measure
3 15d12/9/201111/21/2011Analyze
4 35d1/27/201212/12/2011Improve
5 15d2/17/20121/30/2012Control
SIX SIGMA (BLACK BELT)–PROJECT Page 5
DEPLOYMENT PROCESS FLOW DIAGRAM:
Process Flow Diagram; IT Operations and Development
GN
OC
NT
Ad
min
Te
am
He
lp D
esk
De
ve
lop
me
nt
Te
am
DB
A T
ea
mD
iale
r T
ea
mO
pe
ratio
ns
Te
am
Clie
nt
Se
rvic
es
Develop Query
to Load the
Leads
Correct
formatLoad the Leads
Update Filter
Getting
LeadsStart DialingYes
Yes
Open the Bridge
No
Request to
update the filter
No
Get Required
Teams on the
Bridge
Login Agents
Give Rights to the
Agents
Request to Load
the Leads
Develop
Campaign Script
Document that contains
requirements for new
campaignRequest to Create
New Campaign
Data which
Need to be
Loaded
Deploy Script
Approval for Script
Deployment
Yes
Update ScriptNo
Record
Downtime
Analyze Current
System and
Request
Maintainance
Perform System
Maintainance
Have Login
Rights
Report any
Production
Impacting Issue
Provide Downtime
Details to
Concerned Person
Perform Database
Maintanance
Apply Filter Reboot Dialers
Analyze
Performance
Satisfied with
Performance
Inform
Client
Change Dialing
Parameters
Yes
No
Assign/Unassign
Machine
Develop Filter for
Leads Selection
Perform Leads
Scrubbing
Set Rules to
Access the
Network
Monitor Network
Traffic
Perform
Maintenance
Activity of Telco
Lines with Career
Analyse Network
Health in Case of
Issues
SIPOC DIAGRAM:
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Development Team
Operations Team
Strategy Analyst
Dialing
Filter Dialing
Criteria Email
APPLY FILTER
Operations team
requests filter update
Development team
develops the filter
Dialer team implements
the filter and checks the
leads count
Dialer team provide the
updated leads count and
filter to development team
Correct Leads Enough Leads
Available
Operations
Team Agents
SIX SIGMA (BLACK BELT)–PROJECT Page 6
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
NT Admin
Credentials with the rights to reboot
Reboot Dialer
Dialer team analyst
stops the controller
Analyst stops the
CTIEngine and Dialogic
Restart the machine
Once machine is backup
restart the dialogic
Restart the CTIEngine
and Controller
applications
Dialer is ready for
production
Controller up
and running CTI Engine up
and running Dialogic up and
running
Dialer Team Agents
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Client Client
Services Team
Client
Requirements Client's
Approval Client
Services Approval
UPDATE SCRIPT
Client services requests a
change in script
Developer makes changes
in the script
Script is tested on test
server
Developer sends the script
to Dialer Team for
deployment in production
Dialer Team deploys the
script after getting
appropriate approvals
Correct Script
With Updated Information
Agents Client
Services Operations
Manager Developer
SIX SIGMA (BLACK BELT)–PROJECT Page 7
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Client Services
Strategy Analyst
Previous
Dialing Data New Strategy
CHANGE DAILING
PARAMETERS
Client Services/Strategy Analyst
request change in parameters
Dialer Team analyst implements
the strategy
Dialer Team supervisor verifies
that the change has been
implemented correctly
Dialer Team inform the requestor
that change has been implemented
Target
Strategy Met Dialing with
New Parameters
Strategy
Analyst Client
Services Team
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Client Services
Client
Lead files
LEADS LOADING
Operations team
requests filter update
Development team
develops the filter
Dialer team implements
the filter and checks the
leads count
Dialer team provide the
updated leads count and
filter to development team
New Leads
Operations
Team Client
Services Dialer Team
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
NT Admins Dialer
Team
X-ten NT login
credentials Agent
application login credentials
LOGIN AGENTS
Agent starts soft phone
Agent logs into terminal
server using his
credentials
Agents starts agent
application and login
Once agent is logged
into agent application
he logs into the
campaign
Required campaign is
loaded and agent starts
dialing
Agent
Application Campaign
Loaded
Agents
SIX SIGMA (BLACK BELT)–PROJECT Page 8
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Machine Owner
Required
approvals Required
machine information
MAINTENANCE
Dialer Team request
field support to
perform maintenance
Field support team
performs the
maintenance and
restarts the machine
Dialer Team restarts
the appropriate
applications
Machine up and
running
Dialer Team NT Admin
KPI’s and KPO’s:
KPI’s X KPO’s Y
Month X1 Downtime Y1
Gender X2
Qualification X3
Experience X4
Country X5
City X6
Shift X7
SIX SIGMA (BLACK BELT)–PROJECT Page 9
MEASURE PHASE:
Measurement System Analysis Line Chart Pie Chart Pareto Chart Cause & Effect Diagram Bar Chart Multiple Bar Chart Probability Plot Current Sigma Level
MEASURE
PHASE
SIX SIGMA (BLACK BELT)–PROJECT Page 10
Process performance is measured in terms of downtime per month. This time is measured from the clock and noted on an Excel sheet. Different cases of intervals were provided to operators to evaluate those intervals as “Good” or “Bad”. While conducting study, Downtime 60 minutes as good and others as bad. After that operators’ performance was put in Minitab-16 and Measurement System Analysis for Attribute data was analyzed. Results as shown below:
MEASUREMENT SYSTEM ANALYSIS: According to AIAG 10% overall error rate is acceptable in measurement system. Below report indicating that our Measurement system has acceptance up to 93.3%. Hence our Measurement system is acceptable.
standard 93.3% of the time.
The appraisals of the test items correctly matched the
100%< 50%
YesNo
93.3%
Najeeb RehmaFahad JavaidHassan Rauf
120
100
80
60
40
20
0
93.3%
thus very difficult to assess.
the study were borderline cases between Good and Bad,
-- High percentage of mixed ratings: May indicate items in
items are being passed on to the consumer (or both).
many Good items are being rejected, or too many Bad
-- High misclassification rates: May indicate that either too
or incorrect standards.
problems, such as poor operating definitions, poor training,
Low rates for all appraisers may indicate more systematic
indicate a need for additional training for those appraisers.
-- Low accuracy rates: Low rates for some appraisers may
measurement system can be improved:
Consider the following when assessing how the
Overall error rate 6.7%
Good rated Bad 10.0%
Bad rated Good 3.3%
ways)
Mixed ratings (same item rated both 13.3%
Misclassification Rates
85.0
100.095.0
Attribute Agreement Analysis for Results
Summary Report
% Accuracy by Appraiser Comments
Is the overall % accuracy acceptable?
SIX SIGMA (BLACK BELT)–PROJECT Page 11
Item 9
Item 7
Item 2
Item 5
Item 1
3020100
Item 10
Item 8
Item 6
Item 4
Item 3
3020100
Najeeb Rehma
Fahad Javaid
Hassan Rauf
30150
Najeeb Rehma
Fahad Javaid
Hassan Rauf
30150
Najeeb Rehma
Fahad Javaid
Hassan Rauf
30150
Most Frequently Misclassified Items
Appraiser Misclassification Rates
Overall Error Rate = 6.7%
Attribute Agreement Analysis for Results
Misclassification Report
% Good rated Bad % Bad rated Good
% Good rated Bad % Bad rated Good % Rated both ways
Najeeb Rehma
Fahad Javaid
Hassan Rauf
100806040
Bad
Good
100806040
2
1
100806040
Najeeb Rehma
Fahad Javaid
Hassan Rauf
Najeeb Rehma
Fahad Javaid
Hassan Rauf
100806040
Good
Bad
% by Appraiser
% by Standard
% by Trial
% by Appraiser and Standard
Attribute Agreement Analysis for Results
Accuracy ReportAll graphs show 95% confidence intervals for accuracy rates.
Intervals that do not overlap are likely to be different.
SIX SIGMA (BLACK BELT)–PROJECT Page 12
i
iItems
Mix of
reduce your ability to assess how well the appraisers rate that type of item.
have 50% Good items and 50% Bad items. If you have a small percentage of items of one type, you
It is good practice to have a fairly balanced mix of Good and Bad items. Your data shows that you
Rates
and Error
Accuracy
Rated both ways= 13.3%
Bad rated Good= 3.3%
Good rated Bad= 10.0%
Error= 6.7%
Accuracy= 93.3%
(10 items x 3 appraisers = 30). The accuracy and error rates are:
would have 30 (5 x 3 x 2). To calculate the error for items rated both ways, you would have 30 values
calculate the error rates for Good items, you would have 30 appraisals (5 x 3 x 2); for Bad items you
and 5 Bad, and three appraisers test each item twice for a total of 60 appraisals (10 x 3 x 2 = 60). To
The accuracy and error rates are calculated across all appraisals. Suppose you test 10 items, 5 Good
Check Status Description
Attribute Agreement Analysis for Results
Report Card
LINE CHART:
Above line chart and descriptive statistics shows last seven months trend of the total production downtime on monthly basis.
Feb Mar Apr May Jun Jul Aug
Total 8079 6961 7047 6263 6559 5405 6645
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
To
tal D
ow
nti
me
Month wise Total Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 13
PIE CHART:
From pie chart of category wise production downtime we can clearly observe that “unknown” was the largest downtime category with the share of 25% of total downtime. “Dialer Software” and “Procedure Error” were the second largest downtime category with 12% share of each catagory. Overall, we have a clear picture of percentage of downtime associated with each root cause category through pie chart.
PARETO ANALYSIS:
Downtime 1933 568111661 5465 5379 5237 4652 2842 2066 2043
Percent 4.1 12.124.8 11.6 11.5 11.2 9.9 6.1 4.4 4.4
Cum % 87.9 100.024.8 36.5 47.9 59.1 69.0 75.0 79.4 83.8
Root Cause Category
Other
Networ
k Har
dwar
e
Networ
k
Client
Related
Telco
Facilities
Chan
ge E
rror
Dialer S
oftw
are
Proc
edur
e Er
ror
Unkn
own
50000
40000
30000
20000
10000
0
100
80
60
40
20
0
Do
wn
tim
e
Perc
en
t
Category Vs Downtime
Change Error 11%
Client Related 4%
Database 1%
Dialer Hardware 3%
Dialer Software 12%
Facilities 10%
Maintenance 1%
Network 4% Network Hardware
4% Procedure Error
12%
Service Provider 0%
Software 3%
Telco 6%
Unknown 25%
Windows server 4%
Category Wise Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 14
After constructing the Pareto chart of downtime of causes it was observed that out of remaining 14 categories (except “Unknown”) only 4 were responsible for a downtime of 44.2%. Procedure error and Dialer software proved to be the first and second largest category of downtime which was responsible for an 11.6% and 11.5% of the total downtime respectively. Change error caused 11.2% while facilities caused around 9.9% of total downtime. From above information, main four major categories identified which are Change Error, Procedure Error, Facilities Failure and Dialer Software. These four categories alone were responsible for 44.2% of total downtime. By managing these four categories we can considerably increase the quality by reducing unplanned downtime.
CAUSE & EFFECT DIAGRAM: Below cause & effect diagram indicating that there are number of root causes which are responsible for downtime in the system. Four major causes (i.e.: Procedure Error, Facilities Error, Change Error and Dialer Software Failure) are considered to identify the root causes.
Downtime
Procedure Error
Dialer Software Failure
Facilities Failure
Change Error
Natural disaster
Procedure misunderstanding
Lack of Education
Not clearly defined
Procedure wrongly followed
Inexperienced technician
Documentation not available
Not considered important
Not upgraded
Lack of job knowledge
Not enough trained resource
Trainings not arranged
Lack of automation
Resistance to change
Resources not available to
develop customized tools
Resources are busy in other tasks
Tools are considered
unimportant
Lack of ownership
Change manager/implementer
not properly defined
Change was not properly tested
Lack of time
Campaign needs to go live
on short noticeNot good enough
testing environment
Change implemented wrongly
Change was misunderstood
Lack of communication
between stakeholders
Earthquake
Virus attack
Virus database
was not updated
Some malicious
software installed
Poor Maintenance
System upgrade is costly
Maintenance performed
on wrong time
Misunderstanding of timings
Software crash
Incompatibility with
other components
Not thoroughly tested
Unhandled exception
Too much load
Load unbalancing
QA not performed before release
New version needs to be
released immediately
Wrong parameters applied
Lack of
experience/knowledge
Lack of education/training
Parameters were not
double checked
Agents logging into
wrong machine
Proper login information
was not provided
System crash
Too much load
Incompatibility after
system upgrade
Storm
FireFlood
Hardware failure
Antivirus was
not installed
Technology failed during change
Current system does not
support upgrade
PIE CHARTS:
95%
0% 1%
4% Country Wise Downtime
Pakistan
Philippines
Senegal
United States of America
SIX SIGMA (BLACK BELT)–PROJECT Page 15
From pie chart of Country wise downtime we can clearly observe that “Pakistan” was the largest downtime country with the share of 95% of total downtime.
From pie chart of City wise downtime we can clearly observe that “Lahore” was the largest downtime city with the share of 85% of the total downtime. BAR CHARTS:
Above bar chart indicates that average downtime occurs in the evening and morning shifts are much higher than the night shift.
Beckley 0%
Bend 1%
Charlston 0%
Dakar 1%
Karachi 10%
King of Prussia 1%
Lahore 85%
Manila 0%
Pittsburg 2%
City Wise Downtime
Evening Morning Night
Total 58.94 56.94 39.95
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
Av
era
ge D
ow
nti
me
Shift wise Average Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 16
Above bar chart indicates that average downtime occurs due to male is more than female.
Legend:
A Levels A-Levels
BBIT Bachelors in Business and Information Technology
BCE Bachelors in Computer Engineering
BCS Bachelors in Computer Science
BEE Bachelors in Electrical Engineering
BIS Bachelors in Information Systems
BIT Bachelors in Information Technology
BT Bachelors in Telecommunication
MCS Masters in Computer Science
MIS Masters in Information Systems
MISS Masters in Information Systems Security
MT Masters in Telecommunication
Due to lesser counts in few categories’ regarding the downtime bar chart used to high light major responsible qualification levels. So, most of the downtime are due to Graduate (i.e.: BIT, BT and BCS).
Female Male
Total 39.79 50.28
0.00
10.00
20.00
30.00
40.00
50.00
60.00
Av
era
ge
Do
wn
tim
e
Gender Wise Average Downtime
ALevels
BBIT BCE BCS BEE BIS BIT BT MCS MIS MT
Sum of Downtime 4985 5145 156 6827 1704 3289 11470 7488 86 420 5389
Count of Downtime 142 132 2 144 59 52 190 117 2 1 104
0
2000
4000
6000
8000
10000
12000
14000
To
tal D
ow
nti
me
Qualification Wise Total Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 17
Above bar chart indicates that the lesser experience persons are more responsible for downtime.
Above bar chart indicates that the people having less than 34 years age are more responsible for downtime. MULTIPLE BAR CHARTS:
2-3 4-5 6-7 8-9 10-11 12-14
Sum of Downtime 15236 16884 10967 3033 809 30
Count of Downtime 334 291 230 74 15 1
02000400060008000
1000012000140001600018000
Tota
l Do
wn
tim
e
Experience Wise Total Downtime
28-29 30-31 32-33 34-35 36-37 38-39 40-41 50-51 54-55
Sum of Downtime 8664 20699 7833 2647 3954 1702 651 457 352
Count of Downtime 198 459 120 50 50 43 10 8 7
0
5000
10000
15000
20000
25000
Tota
l Do
wn
tim
e
Age Wise Total Downtime
Karachi Lahore Manila Dakar Beckley BendCharlst
onKing ofPrussia
Pittsburg
Pakistan PhilippinesSenegal United States of America
Sum of Downtime 4668 40016 195 451 92 250 58 352 877
Count of Downtime 93 808 2 16 5 4 1 7 9
05000
1000015000200002500030000350004000045000
To
tal D
ow
nti
me
Country & City Wise Total Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 18
Above multiple–bar chart indicates that the most of downtime occurs in Lahore, Pakistan.
Above multiple–bar chart indicates that the most of downtime occurs due to lesser experience and having Graduate (i.e.: BIT, BT, BCS) qualification.
7006005004003002001000-100-200
99.99
99
95
80
50
20
5
1
0.01
Downtime
Pe
rce
nt
Mean 49.69
StDev 62.08
N 945
AD 82.236
P-Value <0.005
Probability Plot of DowntimeNormal
Above probability plot of the overall downtime for all root cause categories indicating a non–
normal distribution because the p-values for the Anderson-Darling test are less than 0.05
0100020003000400050006000
6-7
2-3
4-5
6-7
8-9
4-5
2-3
4-5
6-7
8-9
2-3
2-3
4-5
8-9
2-3
4-5
8-9
2-3
4-5
6-7
10
-11
4-5
12
-14
4-5
4-5
A Levels BBIT BCE BCS BEE BIS BIT BT MCS MIS MT
Tota
l Do
wn
tim
e
Qualification & Experience
Qualification & Expereince Wise Total Downtime
02000400060008000
100001200014000
2-3
4-5
2-3
4-5
6-7
2-3
4-5
6-7
8-9
2-3
4-5
8-9
6-7
2-3
4-5
8-9
2-3
4-5
8-9
12
-14
10
-11
10
-11
28-29 30-31 32-33 34-35 36-37
38-39 40-41 50-51
54-55
Tota
l Do
wn
tim
e
Age & Experience
Age & Expereince Wise Total Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 19
MEASURING THE CURRENT PROCESS SIGMA LEVEL:
Root Cause Categories
Downtime (Minutes per Year)
Root Cause Categories Downtime
(Minutes per Year)
Dialer Software 5379 Procedure Error 5465
Dialer Hardware 1431 Network Hardware 1933
Network 2043 Database 677
Windows Server 1685 Telecommunication (Telco) 2842
Facilities 4652 Software 1257
Client Related 2066 Service Provider 140
Maintenance 491 Unknown/Other 11661
Change Error 5237 TOTAL 46959
COST OF DOWNTIME:
Total Production time (Minutes) per Month = 15 hours X 60 Minutes X 26 Days = 23400
Average Down Time (Minutes) per Month = 6708
Average Cost per minute (Human Resources) = Rs. 3575
Average down time Cost / month = Rs. 23981100
SIGMA LEVEL CALCULATIONS:
LAST SEVEN MONTH STUDY:
Total Downtime (Minutes) = 46959
Total Production Time (Minutes) = 163800
Opportunity per Unit = 1
DPU (Defects / Unit) = 46959 / 163800 = 0.2867
DPO (Defects/opportunity) = 46959 / (163800 X 1) =0.2867
Yield = 1 – DPO = 1 – 0.2867 = 0.7133
DPMO = 286685 (defects/million opportunity)
Sigma Level = 2.06 (Using M.S. Excel)
CONCLUSION: From above said investigations it is concluded that most of the downtime occurs in Lahore, Pakistan. On average in evening and morning shift downtime occurs more than night shift and male are more responsible than female for this downtime. Persons’ having lesser experience and having graduate level qualification (i.e: BIT, BT, BCS) are more responsible than others.
SIX SIGMA (BLACK BELT)–PROJECT Page 20
ANALYSIS PHASE:
Testing of Hypothesis
ANALYZE
PHASE
SIX SIGMA (BLACK BELT)–PROJECT Page 21
500
250
0
500
250
0
500
250
0
500
250
0
Pakistan
Philippines
Senegal
United State
United State
Senegal
Philippines
Pakistan
5002500
Data in Worksheet Order
Investigate outliers (marked in red).
Distribution of Data
Compare the location and spread.
One-Way ANOVA for Downtime by Country
Diagnostic Report
SIX SIGMA (BLACK BELT)–PROJECT Page 22
Differences among the means are not significant (p > 0.05).
> 0.50.10.050
NoYes
P = 0.076
Philippines
United State
Pakistan
Senegal
4002000-200-400
means at the 0.05 level of significance.
You cannot conclude that there are differences among the
1 Senegal
2 Pakistan
3 United State None Identified
4 Philippines
# Sample Differs from
Which means differ?
One-Way ANOVA for Downtime by Country
Summary Report
Do the means differ?
Means Comparison Chart
Comments
The result of the above test shows that County is an insignificant factor as the P–value is more than 0.05.
SIX SIGMA (BLACK BELT)–PROJECT Page 23
The result of the above test shows that City is an insignificant factor as the P–value is more than 0.05.
SIX SIGMA (BLACK BELT)–PROJECT Page 24
500
250
0
500
250
0
500
250
0
Evening
Morning
Night
6005004003002001000
Evening
Morning
Night
Data in Worksheet Order
Investigate outliers (marked in red).
Distribution of Data
Compare the location and spread.
One-Way ANOVA for Downtime by Shift
Diagnostic Report
Differences among the means are significant (p < 0.05).
> 0.50.10.050
NoYes
P = 0.000
Morning
Evening
Night
806040
implications.
the size of the differences to determine if they have practical
overlap indicate means that differ from each other. Consider
Chart to identify means that differ. Red intervals that do not
means at the 0.05 level of significance. Use the Comparison
You can conclude that there are differences among the
1 Night 2
2 Evening 1
3 Morning
# Sample Differs from
Which means differ?
One-Way ANOVA for Downtime by Shift
Summary Report
Do the means differ?
Means Comparison Chart
Red intervals that do not overlap differ.
Comments
SIX SIGMA (BLACK BELT)–PROJECT Page 25
The result of the above test shows that shift is a significant factor as the P–value is less than 0.05.
891802713624535446357268179901
500
250
0
51464136312621161161
Downtime (Fe, you would have a 90% chance.
the difference. If Downtime (Ma was 22.253 greater than
Downtime (Fe, you would have a 60% chance of detecting
If the true mean of Downtime (Ma was 14.433 greater than
For alpha = 0.05 and sample sizes = 892, 53:
100%
22.253
90%
14.433
60%< 40%
Data in Worksheet OrderInvestigate outliers (marked in red).
14.433 60.0
16.495 70.0
18.907 80.0
22.253 90.0
Difference Power
sample sizes of 892 and 53?
What difference can you detect with your
sample sizes.
Power is a function of the sample sizes and the standard deviations. To detect a difference smaller than 18.907, consider increasing the
2-Sample t Test for the Mean of Downtime (Male and Female)
Diagnostic Report
Downtime (Ma Downtime (Fe
Power
What is the chance of detecting a difference?
SIX SIGMA (BLACK BELT)–PROJECT Page 26
6005004003002001000-100
Downtime (Ma
Downtime (Fe
the mean of Downtime (Fe (p > 0.05).
The mean of Downtime (Ma is not significantly greater than
> 0.50.10.050
NoYes
P = 0.084
20151050
results of the test.
samples. Look for unusual data before interpreting the
-- Distribution of Data: Compare the location and means of
that the true difference is between -2.0710 and 23.047.
the difference from sample data. You can be 90% confident
-- CI: Quantifies the uncertainty associated with estimating
0.05 level of significance.
mean of Downtime (Ma is greater than Downtime (Fe at the
-- Test: There is not enough evidence to conclude that the
Sample size 892 53
Mean 50.280 39.792
90% CI (46.83, 53.73) (27.699, 51.886)
Standard deviation 62.571 52.573
Statistics Downtime (Ma Downtime (Fe
10.488
(-2.0710, 23.047)
Difference between means*
90% CI
* The difference is defined as Downtime (Ma - Downtime (Fe.
2-Sample t Test for the Mean of Downtime (Male and Female)
Summary Report
Distribution of Data
Compare the data and means of the samples.
Mean Test
Is Downtime (Ma greater than Downtime (Fe?
90% CI for the Difference
Does the interval include zero?
Comments
SIX SIGMA (BLACK BELT)–PROJECT Page 27
at most a 60% chance of detecting a difference of 23.539.
least a 90% chance of detecting a difference of 159.82, and
Based on your samples and alpha level (0.05), you have at
100%
159.82
90%
23.539
60%< 40%
23.539 3.5 - 60.0
126.15 60.0 - 100.0
139.35 70.0 - 100.0
150.83 80.0 - 100.0
159.82 90.0 - 100.0
Difference Power
with your sample sizes?
What difference can you detect
Masters in_1 104 51.817 57.211 (40.691, 62.943)
A Levels 142 35.106 43.816 (27.836, 42.375)
Bachelors _2 132 38.977 41.490 (31.833, 46.121)
Bachelors _3 2 78 56.569 (-430.25, 586.25)
Bachelors _4 144 47.410 51.121 (38.989, 55.831)
Bachelors _5 58 29.034 38.518 (18.907, 39.162)
Bachelors _6 52 63.25 66.703 (44.680, 81.820)
Bachelors _7 190 60.368 75.072 (49.625, 71.112)
Bachelors _8 117 64 82.220 (48.945, 79.055)
Masters in_9 2 43 18.385 (-122.18, 208.18)
Qualification Size
Sample
Mean Deviation
Standard
95% CI for Mean
Individual
Statistics
150.83, consider increasing the sample sizes.
Power is a function of the sample sizes and the standard deviations. To detect differences smaller than
One-Way ANOVA for Downtime by Qualification
Power Report
Power
What is the chance of detecting a difference?
Differences among the means are significant (p < 0.05).
> 0.50.10.050
NoYes
P = 0.016
Bachelors _3
Masters in_9
Bachelors _6
Bachelors _8
Bachelors _7
Masters in_1
Bachelors _4
Bachelors _2
A Levels
Bachelors _5
3002001000-100
implications.
the size of the differences to determine if they have practical
overlap indicate means that differ from each other. Consider
Chart to identify means that differ. Red intervals that do not
means at the 0.05 level of significance. Use the Comparison
You can conclude that there are differences among the
10 Bachelors _3
1 Bachelors _5 6 7
2 A Levels 6 7
3 Bachelors _2
4 Bachelors _4
5 Masters in_1
6 Bachelors _7 1 2
7 Bachelors _8 1 2
8 Bachelors _6
9 Masters in_9
# Sample Differs from
Which means differ?
One-Way ANOVA for Downtime by Qualification
Summary Report
Do the means differ?
Means Comparison Chart
Red intervals that do not overlap differ.
Comments
SIX SIGMA (BLACK BELT)–PROJECT Page 28
The result of the above test shows that qualification is a significant factor as the P–value is less than 0.05.
SIX SIGMA (BLACK BELT)–PROJECT Page 29
500
250
0
500
250
0
500
250
0
500
250
0
28 29 30
31 32 33
35 36 38
40 50 55
55
50
40
38
36
35
33
32
31
30
29
28
5002500
Data in Worksheet Order
Investigate outliers (marked in red).
Distribution of Data
Compare the location and spread.
One-Way ANOVA for Downtime by Age
Diagnostic Report
Differences among the means are significant (p < 0.05).
> 0.50.10.050
NoYes
P = 0.000
33
50
36
55
31
32
29
35
38
28
30
40
3002001000-100
implications.
the size of the differences to determine if they have practical
overlap indicate means that differ from each other. Consider
Chart to identify means that differ. Red intervals that do not
means at the 0.05 level of significance. Use the Comparison
You can conclude that there are differences among the
10 36 1 2 3 4
11 50
12 33
1 40 7 8 10
2 30 10
3 28 10
4 38 10
5 35
6 29
7 32 1
8 31 1
9 55
# Sample Differs from
Which means differ?
One-Way ANOVA for Downtime by Age
Summary Report
Do the means differ?
Means Comparison Chart
Red intervals that do not overlap differ.
Comments
SIX SIGMA (BLACK BELT)–PROJECT Page 30
The result of the above test shows that age is a significant factor as the P–value is less than 0.05.
SIX SIGMA (BLACK BELT)–PROJECT Page 31
500
250
0
500
250
0
500
250
0
2 3 4
5 6 7
8 9 10
10
9
8
7
6
5
4
3
2
5002500
Data in Worksheet Order
Investigate outliers (marked in red).
Distribution of Data
Compare the location and spread.
One-Way ANOVA for Downtime by Experience
Diagnostic Report
Differences among the means are significant (p < 0.05).
> 0.50.10.050
NoYes
P = 0.000
9
5
10
4
6
3
2
7
8
16012080400
implications.
the size of the differences to determine if they have practical
overlap indicate means that differ from each other. Consider
Chart to identify means that differ. Red intervals that do not
means at the 0.05 level of significance. Use the Comparison
You can conclude that there are differences among the
1 8 9
2 7 9
3 2 9
4 3 9
5 6 9
6 4 9
7 10 9
8 5
9 9 1 2 3 4 5 6 7
# Sample Differs from
Which means differ?
One-Way ANOVA for Downtime by Experience
Summary Report
Do the means differ?
Means Comparison Chart
Red intervals that do not overlap differ.
Comments
SIX SIGMA (BLACK BELT)–PROJECT Page 32
The result of the above test shows that experience is a significant factor as the P–value is less than 0.05.
CONCLUSIONS:
Testing of Hypothesis indicating that the few Key Input Variables (KPI’s) are became significant
like Shift, Qualification, Experience and Age. In Improve phase, further experimentation will be
done by considering following significant factors that is Shift, Qualification, and Experience.
While age is a significant factor but it’s a noise factor that’s why not considered it further.
SIX SIGMA (BLACK BELT)–PROJECT Page 33
IMPROVE PHASE:
Design of Experiment
IMPROVE
PHASE
SIX SIGMA (BLACK BELT)–PROJECT Page 34
300250200150100500
Median
Mean
18016014012010080
1st Q uartile 55.00
Median 135.00
3rd Q uartile 180.00
Maximum 280.00
90.34 175.29
85.76 180.00
58.88 123.36
A -Squared 0.33
P-V alue 0.483
Mean 132.81
StDev 79.71
V ariance 6353.23
Skewness 0.040952
Kurtosis -0.641979
N 16
Minimum 10.00
A nderson-Darling Normality Test
95% C onfidence Interv al for Mean
95% C onfidence Interv al for Median
95% C onfidence Interv al for StDev
95% Confidence Intervals
Summary for Downtime
Graphical summary of the response clears that the data generated (i.e.: response) against the Design of Experiments is normally distributed and hence the assumption of the normality is fulfilled.
SIX SIGMA (BLACK BELT)–PROJECT Page 35
20-2-4-6-8
99
95
90
80
70
60
50
40
30
20
10
5
1
Standardized Effect
Pe
rce
nt
A Shift
B Q ualification
C Experience
Factor Name
Not Significant
Significant
Effect Type
BC
B
Normal Plot of the Standardized Effects(response is Downtime, Alpha = 0.05)
SIX SIGMA (BLACK BELT)–PROJECT Page 36
A
AB
AC
ABC
C
BC
B
876543210
Te
rm
Standardized Effect
2.306
A Shift
B Q ualification
C Experience
Factor Name
Pareto Chart of the Standardized Effects(response is Downtime, Alpha = 0.05)
50250-25-50
99
90
50
10
1
Residual
Pe
rce
nt
200150100500
50
25
0
-25
-50
Fitted Value
Re
sid
ua
l
40200-20-40
6.0
4.5
3.0
1.5
0.0
Residual
Fre
qu
en
cy
Mean -4.44089E-15
StDev 24.31
N 16
16151413121110987654321
50
25
0
-25
-50
Observation Order
Re
sid
ua
l
Normal Probability Plot Versus Fits
Histogram Versus Order
Residual Plots for Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 37
EveningNight
200
150
100
50
MatersA-Levels
142
200
150
100
50
Shift
Me
an
Qualification
Experience
Main Effects Plot for DowntimeData Means
Main effect plots of shift, qualification & experience shows that the most dominating factor is the
qualification. As it gives visible variation in the downtime required for the reducing the
unplanned downtime.
14
2
Maters
A-Levels
EveningNight
Experience
Qualification
Shift
37.5
185.0230.0
15.0
115.0
210.0165.0
105.0
Cube Plot (data means) for Downtime
Cube plot for downtime shows the optimum conditions for the desired results. If minimum
unplanned downtime is required than organization must work with the combination of Night shift,
Master Qualification, and 14 year of experience (mean’s maximum experience).
SIX SIGMA (BLACK BELT)–PROJECT Page 38
RESPONSE OPTIMIZATION:
When optimizer is run for the goal of minimum downtime evaluation, it gives minimum downtime
which is 15 minutes.
CurHigh
Low1.0000D
Optimal
d = 1.0000
Minimum
Downtime
y = 15.0
1.0000
Desirability
Composite
2.0
14.0
A-Levels
Maters
Night
EveningQualific ExperienShift
Night Maters [14.0]
SIX SIGMA (BLACK BELT)–PROJECT Page 39
3002001000-100
99
95
90
80
70
60
50
40
30
20
10
5
1
Downtime
Pe
rce
nt
Mean 132.8
StDev 79.71
N 16
AD 0.328
P-Value 0.483
Probability Plot of DowntimeNormal
Shift Qualification Experience
Evening
Night
Maters
A-Levels
Maters
A-Levels
14
2
14
2
14
2
14
2
20000150001000050000
95% Bonferroni Confidence Intervals for StDevs
Test Statistic 11.06
P-Value 0.136
Bartlett's Test
Test for Equal Variances for Downtime
SIX SIGMA (BLACK BELT)–PROJECT Page 40
Downtime 1933 568111661 5465 5379 5237 4652 2842 2066 2043
Percent 4.1 12.124.8 11.6 11.5 11.2 9.9 6.1 4.4 4.4
Cum % 87.9 100.024.8 36.5 47.9 59.1 69.0 75.0 79.4 83.8
Root Cause Category
Other
Networ
k Har
dwar
e
Networ
k
Clien
t Rela
ted
Telco
Facil
ities
Chan
ge E
rror
Dialer
Softw
are
Proc
edur
e Er
ror
Unkn
own
50000
40000
30000
20000
10000
0
100
80
60
40
20
0
Do
wn
tim
e
Perc
en
t
Pareto Chart of Root Cause Catagories Before Improvement
Total Downtime 1025 1005 967 965 960 17033258 1759 1503 1198 1180 1175 1106 1089
Percent 5 5 5 5 5 917 9 8 6 6 6 6 6
Cum % 70 76 81 86 91 10017 27 35 41 47 53 59 65
Root Cause Catagories
Other
Dialer S
oftw
are
Service
Pro
vider
Proc
edur
e Er
ror
Facil
ities
Networ
k Har
dwar
e
Telco
Chan
ge E
rror
Softw
are
Windo
ws se
rver
Dialer H
ardw
are
Clien
t Related
Networ
k
Unkn
own
20000
15000
10000
5000
0
100
80
60
40
20
0
To
tal
Do
wn
tim
e
Perc
en
t
Pareto Chart of Root Cause Catagories After Improvement
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Total Downtime 8079 6961 7047 6263 6559 5405 6645 5430 4355 2122 2276
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
To
tal D
ow
nti
me
Month Wise Total Downtime (After Improvement "Sep. to Dec.")
SIX SIGMA (BLACK BELT)–PROJECT Page 41
SIGMA LEVEL CALCULATIONS (AFTER IMPROVEMENT):
FOUR MONTH STUDY:
Total Downtime (Minutes) = 14183
Total Production Time (Minutes) = 93600
Opportunity per Unit = 1
DPU (Defects / Unit) = 14183 / 93600 = 0.1515
DPO (Defects/opportunity) = 14183 / (93600 X 1) = 0.1515
Yield = 1 – DPO = 1 – 0.1515 = 0.8485
DPMO = 151528 (defects/million opportunity)
Sigma Level = 2.53 (Using M.S. Excel)
SIGMA LEVEL
BEFORE THE IMPROVEMENT AFTER THE IMPROVEMENT
2.06 2.53
CONCLUSIONS: With new suggested combination provided by the Design of Experiment; the overall system
performance is improved as shown in the above sigma level calculation.
SIX SIGMA (BLACK BELT)–PROJECT Page 42
CONTROL PHASE:
Process Failure Mode & Effect Analysis Control Charts
CONTROL
PHASE
SIX SIGMA (BLACK BELT)–PROJECT Page 43
Process Failure Mode and Effect Analysis: CHANGE ERROR
Process Function /
Requirement
Potential Failure Mode
Potential Effects of
Failure
S
Potential Causes / Mechanisms of
Failure
O
Current Process Controls
D
RP
N
Recommended Actions
Responsibility
Apply Filter Leads never get buffered
High wait time
8
Applied wrong filter
3 Filter is just overviewed to find out any kind of error
5 120 Check the filter in database and get the leads count before actually applying it
Jawad Hassan (Analyst Systems and Production) Wrong filter was
provided 3 6 144
Wrong leads gets buffered
Agents talking to wrong customers
7
Import date of leads not updated 4
No process controls available
7 196
Double check the filter with developer and with Ops manager to discuss the result of implementation and avoid requesting filter change himself
Zeeshan Jamil (Supervisor Systems and Production)
Part of filter missing while
applying
4 6 168
Filter reverted to old one
Agents getting wrong leads
6
Applied for only one day instead of until further notice
4
Usually asked from OPS team if change is only for one day or for until further notice
6 144
Always ask the requester if change is only for one day or its for until further notice
Ali Gohar (Analyst Systems and Production)
Current tasks finished
3
No process controls available
3 54
Tasks audit should be performed every month
Afriaz Cheema (Manager Systems and Production)
Leads Loading Loaded to wrong database
Agent in downtime waiting for leads
8
Wrong information provided by developer 2
Normally developers mentions in which database to
2 32
Always get a confirmation from dialer team and developer
Hammad Haasan (Database Administrator)
SIX SIGMA (BLACK BELT)–PROJECT Page 44
load the leads
about the location of the database
Misunderstanding by the DBA 2
No process controls available
2 32
Loaded with wrong scrubbing information
Customers complaining about DNC
6
Wrong scrubbing information
provided by client services/developer 2
Client services normally mentions the scrubbing criteria
6 72
Double check with the client services before actually scrubbing the leads
Arsalan Ahmed (Database Administrator)
Update Script Incorrect script deployed
Missing some information from script
5
Miscommunication between
developer and client services
5
Developer just relies on the information provided
4 100
Communication regarding script must be documented and understanding must be developed by asking questions
Bilal Sheikh (Software Engineer)
Developer missed the script
6
No process controls available
4 120
Script must be verified after development and before UAT
Bilal Sheikh (Software Engineer)
Missing some call disposition term codes
6
Functionality not working in production
environment
4
Basic testing is performed before going live
7 168
There should be more focus to improve testing environment and employees should be encouraged to do more and more testing in test
Afaq Ali (Deputy Head of Production)
Term codes were not added
6 6 216
SIX SIGMA (BLACK BELT)–PROJECT Page 45
environment before going live
Dialer Application Update
Applications crashing
Agents get kicked out of system
8
Unhandled Exception
4
Some level of exception handling is done by the developer
4 128
More importance needs to be given to the exception handling in programming
Abul Asim (Senior Software Engineer)
Applications not starting
Production affected
7
Parameters not adjusted properly
3
Once issues are reported the parameters are double checked to find out if anything was missed
3 63
Updated parameters should be verified by the supervisor or checked by other team member in order make sure changes are correct
Ahmed Usman (Supervisor Systems and Production)
Application not working properly
Some functionalities stop working like TPV
6
Controller and CTI Engine are not synchronized
4
Information only flows through formal emails
5 120
Both dialer development and CTI Engine development team should have a closer interaction and communication before making any changes in any component. There should be more informal communication
Abul Asim (Senior Software Engineer) Ahmed Raza (Software Engineer)
SIX SIGMA (BLACK BELT)–PROJECT Page 46
Windows Server Update
Dialer Applications crashing
Dialer applications not starting and agents can't login
8
Wrong version upgrade
2
Normally version upgrade is done over the phone as some times clients need not to be aware of the change
6 96
Everything regarding new and old version must be documented including what is current version, what is new version and are the back out steps in case a change is failed
Afaq Ali (Deputy Head of Production)
Unnecessary upgrade to some application and
frameworks 2
Normally upgrades are not allowed
6 96
Automatic upgrade must be turned off as it affect custom build application
Rizwan Ali (System Administrator)
Change dialing parameters
Dialing stopped
agents not getting calls
8
Applied wrong parameter
2
No process controls available
6
Parameters should be double checked
Zeeshan Jamil (Supervisor Systems and Production)
Dialing with wrong parameters
Too fast dialing
3
TAR updated with high value
4 Normally when the issue arises, parameters are checked to make sure if these were updated correctly or not
6 72 Change management system must be properly implemented and every change must be properly documented and approved before actual change is implemented. Change must be verified by supervisor or another person
Asim Zafar (Director IT Operations) Shoib Sakoor (Head of Production)
TAR updated with low value
4 6 72
Dialing in wrong time zones
6 Wrong time zones
opened 5 5 150
Dialing in wrong mode
3
Incorrect dialing mode applied
2 5 30
SIX SIGMA (BLACK BELT)–PROJECT Page 47
Process Failure Mode and Effect Analysis: DIALER SOFTWARE FAILURE
Process Function /
Requirements
Potential Failure Mode
Potential Effect of Failure
S
Potential Cause /
Mechanism of Failure
O
Current Process Controls
D
RP
N
Recommended Action(s)
Responsibility
Software Crash
Application closed itself
Agents logged out and are in downtime
8
Unhandled exception
2
Some known exceptions are handled through programming
6 96
There should be a more focus on exception handling and development team should be more concerned about this
Abul Asim (Senior Software Engineer/Program Architect)
Too many processes
running 3
No process control available
4 96
Application threads should be properly controlled and memory should be managed in a better way
Abul Asim (Senior Software Engineer/Program Architect)
Capacity issues
4
No process control available
2 64
Capacity should be continuously monitored and whenever there are new agents added to the system, the capacity must be rechecked to analyze if current resources are enough to handle this or not
Afriaz Cheema (Manager Systems and Production)
QA/Testing not performed
extensively
4
No process control available
6 192
Before deployment of application, an extensive QA/testing should be performed and specially stress testing should also be performed
Abdullah (Head of QA)
SIX SIGMA (BLACK BELT)–PROJECT Page 48
Compatibility issues with
other components
3
No process control available 4 96
All relevant stakeholders should be involved during development process
Afriaz Cheema (Manager Systems and Production)
Parameter Configuration
Application not starting or
crashing again and
again
Agents logged out and are in downtime
8
Wrong parameters
applied
3
Implemented himself checks the parameters
6 144
Parameters should be double checked and if possible there should be tools available instead of updating anything from backend
Ahmed Usman (Supervisor Systems and Production)
Agents are not able to
perform their jobs properly
5
Syntax mistake
2
Implemented himself checks the parameters
3 30
Training should be given to the technical teams on the current tools being used
Rabia (Manager Training and Development)
Some values missed
3
Implemented himself checks the parameters
6 90
Parameters should be double check with another team member immediately after any updating
Ali Gohar (Analyst Systems and Production)
Too much load Software crashes or starts malfunctioning
Leads are unnecessarily burned
5
Stuck channels are not released so rest of the
leads are marked as
ND
5
No process control available
5 125
This needs to be taken care at programming level
Abul Asim (Senior Software Engineer/Program Architect)
No further agents are able to login
Resources utilization is too high and no further resources are available to perform further actins
3
No process control available
4 60
OPS team should always inform technical teams if there is any change in current resources allocation
Matthew Debelak (Operations Manager)
SIX SIGMA (BLACK BELT)–PROJECT Page 49
Lead disposition is not properly updated
6
Application is responding slow to database
4
No process control available
5 120
There should a more focus performance optimization
Abul Asim (Senior Software Engineer/Program Architect)
SIX SIGMA (BLACK BELT)–PROJECT Page 50
Process Failure Mode and Effect Analysis: FACILITIES FAILURE
Process Function /
Requirements
Potential Failure Mode
Potential Effect of Failure
S
Potential Causes / Mechanisms of
Failure
O
Current Process Controls
D
RP
N
Recommended Actions
Responsibility
System Crash System shutdown
All relevant resources are in downtime
8
Too much workload
2 Network utilization is normally monitored by GNOC
4 64 Systems should be monitored continuously to check their capacity. Stress testing should also be performed after every couple of months
Afriaz Cheema (Manager Systems and Production)
Incompatibility while updating
with new software/hardware
3 Head of production normally checks with the development team about incompatibility issues
5 120 Compatibility issues must be taken into consideration before updating any software and all stake holders should be informed about the update
Afriaz Cheema (Manager Systems and Production) Afaq Ali (Deputy Head of Production)
Unexpected error 2 No process control available
6 96 Nothing can be done
System never comes backup
All resources are in downtime
8
Hardware failure 3 Nothing can be done
6 144 Hardware’s must be continuously updated
Ehtesham Opel (Manager System Administrator)
Facility Evacuation
All systems are shutdown
All relevant resources are logged out
8
Storm 2 UPS are available in case of electricity failure
3 48 Generators should be ready with extra fuel available
John Skubis (Field Support Officer) Heavy Rains 2 3 48
SIX SIGMA (BLACK BELT)–PROJECT Page 51
Earthquake 2 No process control available
6 96 Nothing can be done
Maintenance System not available for production
Production cannot be started
8
Maintenance started on wrong
time due to misunderstanding
3 Normally emails mention the time
5 120 Time should be properly mentioned either its Pakistan time, US time or UK time
Munam Khalid (Helpdesk Analyst)
Hardware failure during
maintenance
2 No process control available
6 96 Hardware’s must be continuously updated
Afriaz Cheema (Manager Systems and Production)
No one available to restart system
after maintenance as the person is
moved to another site for some
other maintenance
3 On contact person is normally available
5 120 An extra resource should be hired who could be contacted during off contact hours of primary person
Shoib Sakoor (Head of Production)
Virus Attack System shutdown
All user disconnected
8
Antivirus was not updated
2 Antivirus is manually updated
3 48 Antivirus must be regularly updated and security policies must be tightened without exception to anyone. WSUS server must be installed so that all users are automatically updated on regular basis
Ehtesham Opel (Manager System Administrator) Shakeel Husain (Manager Networks)
Some malicious software was
installed
2 All users are not allowed to install the software
4 64
System not recognizing the users
Some users cannot login
6
Windows domain server was
attacked due to lack of security
4 Antivirus and security policies are in place
4 96
Some applications not functioning properly
Users are not able to perform their jobs properly
5
Some malicious software/patch
was installed that affected the
software
3 4 60
SIX SIGMA (BLACK BELT)–PROJECT Page 52
Process Failure Mode and Effect Analysis: PROCEDURE ERROR
Process Function /
Requirements
Potential Failure Mode
Potential Effect of Failure
S
Potential Causes /
Mechanisms of Failure
O
Current Process Controls
D
RP
N
Recommended Actions
Responsibility
Login Agents Agents Stuck on agent application
Can't login
8
Dialer is down and was not restarted
2
No process control available
4 64
Before production starts check all the dialers that these are restarted
Jawad Hassan (Analyst Systems and Production)
Controller is down and was not restarted
4
No process control available
9 288
Before production login a test agent to make sure that dialer applications are up and running
Jawad Hassan (Analyst Systems and Production)
CTI Engine is not properly
working 3 9 216
Dialogic is not working
properly 3 9 216
Agents kicked out of agent application immediately after they login
Can't start production
8
X-ten /dial pad is not configured properly 4
No process control available
6 192
Agents should be properly given training regarding how to configure the phone before they login
Jason Oliver(Operations Manager)
Audio codec is not
configured 3 7 168
Agents should always sit on their designated stations
Joane (Operations Supervisor)
No campaigns loaded
Can't start production
8
Not assigned to the
specific campaign
3
Specific agents are assigned to the campaign when it created
7 168
New agents must always be assigned to the campaign by requesting the required
Joane (Operations Supervisor)
SIX SIGMA (BLACK BELT)–PROJECT Page 53
technical teams before they try to login
Logging in to wrong dialer
3
Supervisors inform the agents about their current dialer
7 168
OPS team should be informed if dialer is changed and it should be documented and OPS should acknowledge the receipt of email as well
Afriaz Cheema (Manager Systems and Production)
No dialing Long wait time
7
Campaign not setup to dial during the specific time agents try to login
4
Production time is normally communicated to Technical teams before production starts
6 168
OPS team must ensure that they always inform technical teams if there is any change in production time
Jason Oliver(Operations Manager)
Reboot Dialer Dialer never comes backup
Loss of production
8
Was shutdown instead of
reboot
3
No process control available
7 168
Shutdown option should be disabled for the user
Nadeem (System Administrator)
Hardware failure 2
No process control available
7 112 Nothing can be done
Applications Failing to start
Dialer is not ready for production
8
Dialogic was not started
with optimum settings
2
No process control available
4 64
Technical support teams should be given proper training and their knowledge should be continuously updated regarding the
Afriaz Cheema (Manager Systems and Production) Shoib Sakoor (Head of Production)
CTI Engine threads were
not stable when next application was started
4 8 256
SIX SIGMA (BLACK BELT)–PROJECT Page 54
Applications were started
in wrong sequence
2 7 112
current processes. Checklists should be maintained and followed if a process always follows the same steps. A test agent should also be logged in before production to ensure applications are properly working
One of the applications
were not started
3 7 168
Script Deployment
Script Missing
Agents can't see the script and can't properly communicate with customers
5
Script was not deployed on one of the
terminal servers
3
Script and files are manually checked on all terminal servers
4 60
An automated application should be developed that deploys the script itself
Afaq Ali (Deputy Head of Production)
Some files were not copied
4 6 120
Wrong Script shown
Performance impacting as agents can't properly communicate with customers
4
Version number was not updated
4
Script version is checked by the person who updates the script
6 96
An automated application should be developed that updates the script version automatically
Afaq Ali (Deputy Head of Production)
SIX SIGMA (BLACK BELT)–PROJECT Page 55
Critical identified processes which should be monitored on regular basis according to corresponding recommended actions.
Process Function /
Requirements
Potential Failure Mode
Potential Effects of
Failure
S
Potential Causes / Mechanisms of
Failure
O
Current Process Controls
D
RP
N
Recommended Action(s)
Responsibility Root
Cause Category
Login agents Agents Stuck on agent application
Can't login 8 Controller is down and was not restarted
4 No process control available
9 288
Before production login a test agent to make sure that dialer applications are up and running
Jawad Hassan (Analyst Systems and Production)
Procedure Error
Reboot dialer Applications Failing to start
Dialer is not ready for production
8
CTI Engine threads were not stable when next application was started
4 No process control available
8 256
Technical support teams should be given proper training and their knowledge should be continuously updated regarding the current processes. Checklists should be maintained and followed if a process always follows the same steps. A test agent should also be logged in before production to ensure applications are properly
Afriaz Cheema (Manager Systems and Production) Shoib Sakoor (Head of Production)
Procedure Error
SIX SIGMA (BLACK BELT)–PROJECT Page 56
working
Update Script Incorrect script deployed
Missing some call disposition term codes
6 Term codes were not added
6
Basic testing is performed before going live
6 216
There should be more focus to improve testing environment and employees should be encouraged to do more and more testing in test environment before going live
Afaq Ali (Deputy Head of Production)
Change Error
Login agents Agents Stuck on agent application
Can't login 8 CTI Engine is not properly working
3 No process control available
9 216
Before production login a test agent to make sure that dialer applications are up and running
Jawad Hassan (Analyst Systems and Production)
Procedure Error
Apply filter wrong leads get buffered
Agents talking to wrong customers
7 Import date of leads not updated
4 no process controls available
7 196
Double check the filter with developer and with Ops manager to discuss the result of implementation and avoid requesting filter change himself
Zeeshan Jamil (Supervisor Systems and Production)
Change Error
Software Crash
Application closed itself
Agents logged out and are in downtime
8 QA/Testing not performed extensively
4 No process control available
6 192
Before deployment of application, an extensive QA/testing should be performed and
Abdullah (Head of QA)
Dialer Software
SIX SIGMA (BLACK BELT)–PROJECT Page 57
specially stress testing should also be performed
Login agents
Agents kicked out of agent application immediately after they login
Can't start production
8 x-ten / dial pad is not configured properly
4 No process control available
6 192
Agents should be properly given training regarding how to configure the phone before they login
Jason Oliver(Operations Manager)
Procedure Error
Change dialing parameters
Dialing with wrong parameters
Dialing in wrong time zones
6 Wrong time zones opened
5
Normally when the issue arises, parameters are checked to make sure if these were updated correctly or not
5 150
Change management system must be properly implemented and every change must be properly documented and approved before actual change is implemented. Change must be verified by supervisor or another person
Asim Zafar (Director IT Operations) Shoib Sakoor (Head of Production)
Change Error
Parameter configuration
Application not starting or crashing again and again
Agents logged out and are in downtime
8 Wrong parameters applied
3
Implemented himself checks the parameters
6 144
Parameters should be double checked and if possible there should be tools available instead of updating anything from backend
Ahmed Usman (Supervisor Systems and Production)
Dialer Software
SIX SIGMA (BLACK BELT)–PROJECT Page 58
System Crash System never comes backup
All resources are in downtime
8 Hardware failure 3 Nothing can be done
6 144
Hardware’s must be continuously updated
Ehtesham Opel (Manager System Administrator)
Facilities Failure
Too much load
Software crashes or starts malfunctioning
Leads are unnecessarily burned
5
Stuck channels are not released so rest of the leads are marked as ND
5 No process control available
5 125
This needs to be taken care at programming level
Abul Asim (Senior Software Engineer/Program Architect)
Dialer Software
System Crash System shutdown
All relevant resources are in downtime
8
Incompatibility while updating with new software/hardware
3
Head of production normally checks with the development team about incompatibility issues
5 120
Compatibility issues must be taken into consideration before updating any software and all stake holders should be informed about the update
Afriaz Cheema (Manager Systems and Production) Afaq Ali (Deputy Head of Production)
Facilities Failure
Maintenance System not available for production
Production cannot be started
8
Maintenance started on wrong time due to misunderstanding
3
Normally emails mention the time
5 120
Time should be properly mentioned either its Pakistan time, US time or UK time
Munam Khalid (Helpdesk Analyst)
Facilities Failure
SIX SIGMA (BLACK BELT)–PROJECT Page 59
191715131197531
60
40
20
0
Subgroup
Mean __
X=30.16
UCL=57.42
LCL=2.89
191715131197531
150
100
50
0
Subgroup
Ran
ge _
R=88.5
UCL=157.2
LCL=19.7
Xbar-R Chart of Downtime
Stability Report
Is the process mean stable?
Investigate out-of-control subgroups. Look for patterns and trends.
Is the process variation stable?
Investigate out-of-control subgroups. Look for patterns and trends.
SIX SIGMA (BLACK BELT)–PROJECT Page 60
> 5% 0%
NoYes
0.0%
on the Xbar chart.
The process mean is stable. No subgroups are out of control191715131197531
60
40
20
0
Subgroup
Mean __
X=30.16
UCL=57.42
LCL=2.89
191715131197531
150
100
50
0
Subgroup
Ran
ge _
R=88.5
UCL=157.2
LCL=19.7
Comments
Xbar-R Chart of Downtime
Summary Report
Is the process mean stable?
Evaluate the % of out-of-control subgroups.Xbar Chart
Investigate out-of-control subgroups.
R Chart
Investigate out-of-control subgroups.
CONCLUSIONS: Process Failure Mode & Effect Analysis (PFMEA), X-bar & R Charts are suitable for monitoring and controlling the system.
SIX SIGMA (BLACK BELT)–PROJECT Page 61