advanced innovation group | improvement in quality score

The Voice of the Customer - VOC

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Customer Comments Critical to Quality-CTQ’s

ABC Bank was formed in 1969 through the merger of two separate banks, the AB of British South Africa and the TT of India, Australia and China.

Listed on the London, Hong Kong and Mumbai stock exchanges, and rank among the top 20 companies in the

FTSE-100 by market capitalization.

Voice Of Head Of Operations North US Banking :

There has been a significant dip in QC scores for voice associates.This would have possible impact on overall customer satisfaction and related SLAs.

The voice QC score of an associate should be > 85%

Project Charter

Business case:ABC Bank is Listed on the London, Hong Kong and Mumbai stock exchanges and ranked among the top 20 companies in the FTSE-100 by market capitalization.Currently the Contact Center caters to the Customers Of the bank for Debit Card and related services.

Team

VP – Shishir (Cust Service Operations) Manager Ops – Pradeep BB – Naveen G.B & SME – CS-Ops Team (Ram) Quality Coach – Jerry Team Lead – Tom

Problem StatementThe overall Voice QC scores for Cust_ service operations from (Jan-Mar’12) has been 64% vs. required of 85% .More than 75% of the population of associates, scores have been below the required QC score benchmark of 85%.

Goal Statement

To achieve Voice QC scores for Cust_ service operations to 87% per month by end of Aug,12 and sustain .

In Scope :

•Voice QC scores for Cust_ service operations •QC team (Voice)

Out Scope :• Non Voice Team•Admin Team•Client Support Team (Data ,Admin, Tech support)

Milestones Target Date Actual date

D 17-Sep-12 M 26-Sep-12 A 17-Oct-12 I 26-Nov-12 C 17-Dec-12

Critical To Quality Tree

Improvement in Call QC scores / month for ABCBank Contact Center Operations

Improvement in Call QC scores / month for ABCBank Contact Center Operations

CTQs

Product KnowledgeProduct Knowledge

EffectiveTraining and CoachingEffectiveTraining and Coaching

Number of calls handled(Call Volume) /associateNumber of calls handled(Call Volume) /associate

Technology & IT( Headsets ,networks , PCs & Other applications/ softwares

Technology & IT( Headsets ,networks , PCs & Other applications/ softwares

Tenure of associatesTenure of associates

SIPOC

•ABC (Bank Cards)

•Card Holders (Customers) of XYZ Bank

• Resolve Callers

(Customers) query.

•Update Customer’s account

with current status .

•Update notes on Customer’s

accounts.

•Customer accounts getting

routed to appropriate

unit/department for further

resolution.

•Update required info on

Account # on which contact

established

•Update notes on Account

•Route Account as per

procedure (SOP)

•Ask for purpose of call

•Ask details of query

•Attempt to provide on call

solution to caller as per

guidelines (SOP)

Contact withCustomer3rdparty,vendorCustomer’s representative

•Call received-Inbound /

•Call made – Outbound

•Verify details of Party on

phone

•ASSOCIATE PHONE & SYSTEM

LOGIN

•ASSOCIATE READY FOR

INBOUND & OUTBOUND CALLS

•Customer Accounts :

Call / Query

• IT & Technology Support

• ABCBank (Bank Cards) – Contact Center operations team members

•Customer Accounts volume from ABCBank (Bank Cards) strategies team.

ABC Bank (Bank Cards) – Customer Service Delivery Team

•Call recording Tool –

Captures (Voice & Screen) of

sample calls daily.

Data Collection Plan What To Measure ?

mMEASURE

Project Y / KPI Operational Definition Defect Def Performance StdSpecification Limit

OpportunityLSL USL

Improvement of Call QC score for ABC Bank-Contact Center

ABC Bank-Contact Center , caters to all incoming customer queries on Toll Free # and provides resolution to Customer queries. Accounts are updated with appropriate notes and information.

Call Score %age is less than 85%

Voice QC scores Greater than OR

equal to 85%85% 100%

•Calls handled by Contact

Center

Data Collection Plan How To Measure ?

mMEASURE

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?

Improvement of Call QC score for ABCBank-Contact Center

Discrete Data

QC scores

•Team Wise•Associate Wise•Week Wise

% Call QC score =Sum of Weight age of call

parameters / 100

%age QC score

•Call QC database

maintained by QC team

Existing N/A 4-July-12 All Call QC performed :

Validation Measurement System throughEffectiveness & Efficiency

mMEASURE

Effectiveness

Efficiency

Volume

Opportunities (Samples Taken) 30

Errors 4

Result 86.67%86.67%

Volume

Opportunities (Samples Taken) 30

Errors 5

Result 83.33%83.33%

Efficiency & Effectiveness is successful, hence the data (measurement system) is all right for further analysisConsent has been received on above Measurement System - benchmarks to be treated as effective from Business Leaders.

KPI Data Type

QC Score %age Discrete

Microsoft Office Excel 97-2003 Worksheet

Data Sheet

Current Capability - Process Sigma Level mMEASURE

Since (Y) Quality Score is Discrete Data Type hence DPMO method DPMO method is used to calculate current sigma Value of Process.

(Y) Data Type : Discrete

# Of Opportunities 181

Pass 39

Fail 142

DPO 0.784530387

DPMO 784530.387

Current Sigma Level Of Process is : Current Sigma Level Of Process is : 0.71 0.71 δδ

Stability Check Of Process – Run Chart

180160140120100806040201

100

90

80

70

60

50

40

30

20

Observation

Call Qualit

y (In

%)

Number of runs about median: 81Expected number of runs: 91.5Longest run about median: 8Approx P-Value for Clustering: 0.059Approx P-Value for Mixtures: 0.941

Number of runs up or down: 120Expected number of runs: 120.3Longest run up or down: 3Approx P-Value for Trends: 0.476Approx P-Value for Oscillation: 0.524

Run Chart of Call Quality (In % )

Since P-value is more than 0.05 for all four behaviors hence the is data is considered to be stable.

Normality Test

Normality: P value >

Shape: Non-Normal or Normal

Measure of central tendency :data is normal measure of central tendency will be Mean / Median

Aim: The project shall focus on shifting the central tendency and reduction in variation.

mMEASURE

Null and alternate hypothesisHO – Data is normalHA – Data is non normal

Normality: P value is 0.005 , hence data is non-normal

Measure of central tendency :SInce Data is non-normal measure of central tendency will be Median.

OBSERVATION

Graphical SummaryGraphical Summary to check Centering and Variation. Path : Stats > Basic Stats > Graphical SummaryIf target is met then problem with VariationIf target is not met then problem with CenteringSince P-value < 0.05 data is not normal hence we consider MEDIAN Target: 85% , Median: 64% (Target is not met), i.e.: Problem is for centering

9075604530

Median

Mean

72706866646260

1st Quartile 46.500Median 64.0003rd Quartile 83.000Maximum 100.000

61.170 67.317

59.838 71.000

18.996 23.368

A-Squared 2.08P-Value < 0.005

Mean 64.243StDev 20.955Variance 439.107Skewness -0.04708Kurtosis -1.17315N 181

Minimum 25.000

Anderson-Darling Normality Test

95% Confidence I nterval for Mean

95% Confidence I nterval for Median

95% Confidence I nterval for StDev95% Confidence I ntervals

Summary for Call Quality (In % )

Organize Potential Cause – CE or Fish Bone Diagram

Factors identified through brainstorming

aAnalyze

scoresQuality

Environment Methods

Personnel

Qualification

Trainer

Team Leader

Experience Type

Tenure

Age

Gender

Process Complexity

Process Knowledge

Location

Shift

Cause-and-Effect Diagram

Potential Xs and hypothesis Tests

# Potential Xs Description Data Type Test Reason

1 Age Age of FTEsContinuou

s BLR

2 GenderGender sub-grouped into male &

female DiscreteChi Square - Cross

TabulationSince Y is Categorical, X is

Categorical

3 ShiftShifts sub-grouped into morning ,

evening & night DiscreteChi Square - Cross

TabulationSince Y is Catergorical, X is

Categorical

4 Process Knowledge process knowledge scores of FTE's DiscreteChi Square - Cross


Categorical

5 Tenure Tenure of FTE's in years Continuous BLR

6 Experience Type Domain experience DiscreteChi Square - Cross


Categorical

7 Team Leader All TL's in the project DiscreteChi Square - Cross


Categorical

8 Trainer All Trainers in the project DiscreteChi Square - Cross


Categorical

9 Location Location of Service Delivery DiscreteChi Square - Cross


Categorical

10 Process Complexity Process complexity for DiscreteChi Square - Cross


Categorical

11 QualificationEducational and Professional

Qualification of FTEs DiscreteChi Square - Cross


Categorical

Sl. No Potential Xs Description Data Type Test Reason

1 Age Age of FTEs Continuous BLR

Result / Observation

P Value 0.598; p_value >0.05 hence Ho(Null Hyp) which means there is No significant impact of Age of FTEs on Y (Qc Scores)

Sl. No Potential Xs Description

Data Type Test Reason Result / Observation

2 GenderGender sub-grouped into male &

female DiscreteChi Square - Cross

TabulationSince Y is Catergorical, X

is Categorical

Tabulated statistics: SLA Met Status, Gender

Rows: SLA Met Status Columns: Gender

F M All

Fail 63 79 142Pass 16 23 39All 79 102 181

Cell Contents: Count

Pearson Chi-Square = 0.139, DF = 1, P-Value = 0.709Likelihood Ratio Chi-Square = 0.139, DF = 1, P-Value = 0.709

Would it be correct to refer Pearson Value and infer Correlation between X and Y in terms of impact ,Magnitude of impact, Regression Equation ?

Tabulated statistics: SLA Met Status, Gender

Rows: SLA Met Status Columns: Gender

F M All

Fail 63 79 142Pass 16 23 39All 79 102 181

Cell Contents: Count


Would it be correct to refer Pearson Value and infer Correlation between X and Y in terms of impact ,Magnitude of impact, Regression Equation ?

Result / ObservationChi Square Cross Tabulation Checks Expected Vs Observed Values.

P_value is 0.7.09,which is > 0.05. Hence Ho(Null hypo) which means No significant difference between expected and observed values.

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Contribution to Chi-square


P>0.05 (0.746) i.e. Ho(null hypothesis)

No significant difference between expected vs observed

Sl. NoPotential

Xs DescriptionData Type Test Reason Result / Observation

3 ShiftShifts sub-grouped into morning ,

evening & night DiscreteChi Square -

Cross TabulationSince Y is Catergorical,

X is Categorical

p_value is 0.746 which states p_value > 0.05. Hence Ho(Null Hypo) which means No significant difference between expected and observed values.

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P value,0.05, ha(alternate hyp)Significant difference between expected vs observed value

Sl. No Potential Xs Description Data Type Test Reason Result / Observation

4Process

Knowledge process knowledge scores of FTE's Discrete

Chi Square - Cross


Categorical

P value,o.o5, ha(alternate hyp)Hence significant difference between expected vs observed value

Result / Observation

BLR P_value is 0.001 which is < 0.05. Hence Ha(alternate hypo) which means Significant impact of X(Tenure) on Y (Quality)

5 Tenure Tenure of FTE's in years Continuous BLR

Binary Logistic Regression: SLA Met Status versus Tenure

Link Function: Logit

Response Information

Variable Value CountSLA Met Status Pass 39 (Event) Fail 142 Total 181

Logistic Regression Table

Odds 95% CIPredictor Coef SE Coef Z P Ratio Lower UpperConstant -1.03871 0.315958 -3.29 0.001Tenure -0.0782532 0.0826167 -0.95 0.344 0.92 0.79 1.09

Result / ObservationChi Square Cross Tabulation Checks Expected Vs Observed Values.

P_value is 0.457, which is >0.05. Hence Ho(Null hypo) which means No significant difference between expected and observed values.


Pearson Chi-Square = 2.604, DF = 3, P-Value = 0.457

Likelihood Ratio Chi-Square = 2.788, DF = 3, P-Value = 0.425

6 Experience Type Domain experience DiscreteChi Square - Cross


Categorical

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7 Team Leader All TL's in the project DiscreteChi Square -

Cross TabulationSince Y is Catergorical, X

is Categorical


Since p_value is 0.580 which is > 0.05, hence (Ho) Null Hypo .

There is no significant difference between expected Vs. observed

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P_value is > 0.05 i.e. (0.900) stating Ho(Null hypo). Hence there is no significant difference between expected Vs. observed


8 Trainer All Trainers's in the project DiscreteChi Square - Cross


Categorial

P_value is 0.001 which is < 0.05. Hence Ha(alternate hypo) which means Significant impact of X(Tenure) on Y (Quality)

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P-Value = 0.228 which is > 0.05, which means Ho(Null hypo). Hence there is no significant difference between expected vs observed values


9 Location Location of Service Delivery Discrete Chi Square - Cross TabulationSince Y is Catergorical, X is

Categorical

P-Value = 0.228 which is > 0.05, which means Ho(Null hypo). Hence there is no significant difference between expected vs observed values

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P-value > 0.05 , which is (0.606) stating Ho (Null Hypo)Hence there is no significant difference between expected vs. observed values

10 Process Complexity Process complexity for Discrete Chi Square - Cross Tabulation Since Y is Catergorical, X is Categorial

P-value > 0.05 , which is (0.606) stating Ho (Null Hypo)Hence there is no significant difference between expected vs. observed values

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11 QualificationEducational and Professional

Qualification of FTEs DiscreteChi Square - Cross


Categorical



P-value > 0.05, states Null hypo (Ho).Hence there is no significant difference between expected vs actual values

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Sl. No Potential Xs Data Type Test P-Value Impact

1 Age Continuous BLR 0.598 No

2 Gender Discrete Chi Square - Cross Tabulation 0.709 No

3 Shift Discrete Chi Square - Cross Tabulation 0.746 No

4 Process Knowledge Discrete Chi Square - Cross Tabulation 0.01 Yes

5 Tenure Continuous BLR 0.001 Yes

6 Experience Type Discrete Chi Square - Cross Tabulation 0.457 No

7 Team Leader Discrete Chi Square - Cross Tabulation 0.58 No

8 Trainer Discrete Chi Square - Cross Tabulation 0.9 No

9 Location Discrete Chi Square - Cross Tabulation 0.228 No

10 Process Complexity Discrete Chi Square - Cross Tabulation 0.606 No

11 Qualification Discrete Chi Square - Cross Tabulation 0.184 No

Out of the POTENTIAL X’s listed and Hypothesis tests performed ,

VITAL X’s can be determined as Process Knowledge & Tenure

[ VITAL X’s ] OBTAINED FROM HYPOTHESIS TESTS PERFORMED[ VITAL X’s ] OBTAINED FROM HYPOTHESIS TESTS PERFORMED

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PRIORITIZING VITAL X’s PRIORITIZING VITAL X’s

COST

LOWLOW MEDIUMMEDIUM HIGHHIGH

IMPACT

LOW Fitness Levels

MEDIUM

•Tenure•Process Knowledge

Morale

HIGH

Vital X’s are Process Knowledge & Tenure, basis brain storming 2 more Vital X’s have been added which could not have been Quantified : (Fitness Levels, Morale)In order to prioritize Vital X’s factors considered are (IMPACT & COST)

CCOSTOST

IIMPACTMPACT

TTIMEIME

EEFFORTFFORT

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QFD >> Quality Function Deployment / Screening SolutionsScreening Solutions

QFD will help prioritizing the CTQs to perform appropriate actions / activities.

advanced innovation group | improvement in quality score

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