Measure Phase

How to do Six Sigma Projects - MeasurePhase - Class 2 including MSA & As-is ProcessCapability

Step 1 : Problem Identification / Improvement Opportunity Identification

Step2 : Gather voice from Stakeholders

Step 3 : Convert CTQ

Step 4 – Create Project Charter

  • Business Case
  • Problem Statement
  • Goal Statement
  • Scope
  • Roles & Responsibilities Identification & Assignment
  • Process Flow Chart
    • High Level – COPIS
    • Detailed – Flowchart

 

Sponsor Approval

  • Budget need
  • Resources
  • Data
  • Risk

 

 

Measure Phase

  1. Identify the CTQ Characteristic / CTQ Metric for the project
  2. Create Data Collection Plan
  3. Collect Data
  4. Validate Data (Using MSA experiments)
  5. Assess as-is Process Capability

 

Identify the CTQ Characteristic / CTQ Metric for the project

  • Critical to Quality
    • Tea – Hot, Taste, Sugar Quantity, Milk, Presentation, Quantity, Ingredients

Project CTQ – Handling time, Count – Attrition/Defect, Productivity % or count

Handling Time per agent per day/ HT Per month for the process

  • Quality Score per agent per call/
  • Attrition Count

Quality % - Quality % as a monthly average, Weekly Quality % for the team,

Create Data Collection Plan

NU – Motor Insurance – FSA – Claim TAT =13 Days, Our as-is TAT = 23

  • Customer called to inform about accident
  • New claims team would notify engg
  • If car was beyond repair – my team was notified (TLR)
  • Notification or claim was recd in Manager Queue
  • Allocate to AM Queue
  • Allocate to case handler
  • Call the customer and seek car papers etc
  • Docs received, price quote – Pay the customer

TAT of Customer Contact

  • Agents = Call the customer and seek car papers etc - Allocate to case handler
  • Manager = Call the customer and seek car papers etc - Notification or claim was recd in Manager Queue
  • NU = Call the customer and seek car papers etc - Customer called to inform about accident
    • PH not available – someone else was spoken to
    • Send letter – First point of contact’
    • Authorized person other than PH

AMHI

NPS

1 Customer – 20-30 feedback (negative)

1 Policy -

 

 

 

 

Operational Definition –

Pizza Delivery Time –

  • Start – time when order added on the system
  • End – When the delivery person reaches the first point of contact.

 

Chq Clearance TAT

  • Start: When chq presented in the bank for clearance
  • End : Money available as available balance in the account

RU

% people who are billable

# of billing people/Total HC – Non Billable

 

Good Employee

Present –

Quality Score Monthly

CT (weekly)

 

Formula =

Sum of total Quality Score/total no of calls

 

18/20

P1 = 86% 86/100

P2 =76% 76/100

p3 =74%

= No of pass parameter/Total no of applicable parameter

 

Y

Operation Definition

Performance Std

Defect Def

USL & LSL

Pizza Delivery TAT

Difference between Start – time and end time when start time is when order added on the system

End – When the delivery person reaches the first point of contact.

 

30 Min

Each time that the pizza delivery exceeds 30 min – it shall be termed as defect

Upper Spec Limit = 30 Min

Lower Spec Limit = NA

Weekly Quality Score

% Passed parameters from the total applicable parameter

75%

Each week when QS is not equal to or greater than 75% it shall be termed as a defect

USL = NA

LSL = 75%

 

 

60%

Any student receiving less than 60 shall be termed as defect

USL = NA

LSL = 60%

Compliance %

 

 

 

USL = NA

LSL = 85%

 

 

 

 

 

 

Formula to be used

Data Items needed

Unit

Decimals used

Data Container to be used

New or existing

When ready

# of pass parameters/#of applicable parameters*100

  1. Pass parameters count weekly
  2. Applicable parameter count

 

%

 

Excel/Software

 

 

 

 

Y

Ops Def

Performance Std

Defect Def

USL LSL

 

Monthly Quality Score

% Passed parameters from the total applicable parameter in a month

95%

Monthly Quality Score less than 95% shall be termed as defect

USL = NA

LSL = 95%

 

Weekly Handling Time Scores

Average of Sum of handling time of all calls in a week against the number of calls handled

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Formula to be used

Data Items needed

Unit

Decimals used

Data Container to be used

New or existing

When ready

 

 

 

 

 

 

 

 

 

 

 

 

 

Validate Data

 

Sources of Variation

True Process Variation

 

Measurement Error

People

  • Skill Issue
  • Will issue

Machine

    • Breakdown
    • Maintenance issues
    • Process of usage not known
    • Calibration

 

Repeatability

  • Same Operator
  • Same thing
  • Same equipment
  • The amount of variation observed is called Repeatability
  • Different Tests use different measures of variation
    • Std Dev. Variance (GRR)
    • Range ( X Bar R)

3 Kg, 3.2 Kg, 3 KG

Reproducibility

  • Change Operator
  • Change Equipment
  • Change Both
  • The amount of variation observed is called Reproducibility
  • Different Tests use different measures of variation
    • Std Dev. Variance (GRR)
    • Std Dev
    • Range ( X Bar R)

 

 

 

 

 

MSA – Discrete Data

Effectiveness

% Agreement between multiple readings (different Operators or same operators)

We see that there are 9 agreements out of 10 instances.

Hence my effectiveness score is 9/10 or 90%

 

 

Efficiency

Check for % agreement by introducing a master calibrator.

 

% agreement

 

Swati

Jyoti M