RLM & Associates LLC Your Lean Six Sigma & Project Management Trainers

RLM & Associates LLCYour Lean Six Sigma & Project Management Trainers

Lean Six Sigma DMAIC WorkshopGreen Belt Part 3

6 σ Green Belt

04/21/23 1Kraft Foods Green Belt

04/21/23 Kraft Foods Green Belt 2

Building Effective Teams

Building Effective Teams


Why Teams?

Improves productivity

Better results (products, processes, services)

Better able to handle complex problems

Can handle many aspects of the business

Differentiation through diversity of thoughts

Improves morale, enthusiasm and creativity

Teams succeed over the work of the lone genius!

Teams succeed over the work of the lone genius!


High Performing Teams

Teams have a sense of PPurpose, they are EEmpowered, they practice good RRelationships & Communication, they exhibit FFlexibility, then try for OOptimal Performance, they RRecognize & Appreciate others and have high MMorale.

Blanchard’s Model

When all components are strong,location or product becomes irrelevant

When all components are strong,location or product becomes irrelevant


Characteristics of Effective Teams

Effective teamwork encompasses:– Developing a charter – Defining team members’/leader’s roles– Establishing procedures and ground rules– Establishing relationships

Effective TeamsWhich individuals do which activities or tasks?

How do we feel about each other, talk with each other, and affect each other?

What do we do, intend to do, and why?(Purpose, Scope, Goals, Selection)

How do we do what we do? What processes and systematic approaches do we use?


Team Growth Stages

All effective teams move though stages of growth. A team must work through four developmental stages to be successful. Team leader and members must understand the different stages and adapt their behavior to maximize team effectiveness.

Team Growth Stages

Forming

Performing Storming

Norming


Conflict Resolution

In order for teams to move forward from Storm to Norm, teams must understand:

– How to identify conflict and how to resolve it

– How to identify blockages and how to unblock

– How team blockages affect progress and how to unblock them

When managed correctly, conflict produces new ideas, solves problems, expands capabilities, and improves creativity

When managed correctly, conflict produces new ideas, solves problems, expands capabilities, and improves creativity


Helping Teams with Conflict

Listed below are some key steps for helping a team work through conflict. This is a suggested approach, but team leaders may use different steps. Team leaders may have to alternate between these steps as they work through conflict with the team.

Clarify and summarize different points of view Ask for points of agreement and disagreement Look at situation from customers points of view Get data Place yourself in the other person‘s position Ask how to resolve differences


Define Phase Checklist

Is the project charter complete, accurate, and SMART?

Is the as-is process mapped appropriately?

Are Critical Customer Requirements documented?

Have any quick wins been identified?

–If so, implemented?


Measure

Measure


Measure Phase Process Flow

Identify Measurement and Variation

Determine Data Type

Develop Data Collection

Plan

Perform Measurement System

Analysis

Perform Data Collection

Perform CapabilityAnalysis


Measure Phase Objectives

Define the process measures

Identify the types, sources, and causes of variation in the process

Determine data requirements

Develop a data collection plan

Perform Measurement System Analysis

Conduct data collection

Determine baseline capability of the project as SQL–(Sigma Quality Level)


Why Measure?

Measurement allows teams to…

– Establish baseline performance

– Isolate sources of variation

– Identify areas in which improvements can be made


Value Performance Measures –Customer Value Achieved?

SuppliersProcess Inputs

Business Processes

Process Outputs

Critical Customer

Requirements

Important Decisions Based on Linking

Customer Expectations to Process Performance

Input Measures

Process Measures Output

Performance Measures

Customer Value


Input, Process and Output Indicators

Input Indicators

Process Indicators

OutputPerformance

Indicators

# of customer inquiries

Type of customer inquiries

# of orders # of positions open Type of position open Accuracy of the

credit analysis Timeliness of the

contract submitted for review

Cost per transaction Time per activity Amount of rework Turnaround time Variability of an activity

Percent defective Number of errors Total response

time Invoice/billing

accuracy Revenue

These should all appear on your process map

Critical Customer RequirementsCritical to the Process

Critical Customer RequirementsCritical to the Process


Process Elements/Indicator Relationships

Start Boundary __________ End Boundary ____________

Suppliers Inputs Outputs Customers

Process

Input Indicators Process Indicators Output IndicatorsMeasures that evaluate the degree to which process inputs, provided by suppliers, are consistent with what the process needs to convert into customer-satisfying outputs.

Examples: # of customer inquiriesType of customer inquiries# of orders # of positions open Type of position openAccuracy of the credit analysisTimeliness of the contract

Measures that evaluate the quality of the transformation processes – the steps used to convert inputs into customer-satisfying outputs

Examples: Availability of service personnel Time required to perform credit review % of non-standard approvals required # of qualified applicants Total cost of service delivery Total overtime hours

Measures that evaluate dimensions of the output – may focus on the performance of the business as well as that associated with the delivery of services and products to customers.

Examples: # of calls/hour taken by each service rep 2nd year customer retention figures Total # of meals delivered % customer complaints


More on Measurement Considerations

One rule holds regardless of the measures you select; try to use as few indicators as possible

There is a cost/benefit and relevance relationship to measuring. Too many measures are costly, unproductive, and may divert attention from critical areas.

Not enough or incorrect process indicators will not allow you to identify defects before they occur


CCRs and Multiple Output Indicators

Some CCRs may be measured in terms of one specific expectation a customer has. Others may require several output indicators. The table shows how one CCR can have one or several associated output indicators.

This table lists the second CCR from the above table, but shows it as three different critical customer requirements associated with the delivery of a vehicle.

Regardless of how the CCR is stated, teams must be sure to identify all of the CCRs associated with a process production service and make sure that the CCRs are measured by the output indicator.

Output IndicatorProduct delivery cycle time from the completion of the customer order to the delivery of the product

number and type of vehicle specifications delivered correctlyactual delivery time vs. promiseddelivery time for each vehiclenumber of times vehicles were delivered to location other than what is specified on agreement.

Critical Customer Requirement

Product is delivered within three hours of order taken

Right vehicle is delivered at the right time tot he right location Output

Output IndicatorNumber and type of vehicle specificationsdelivered correctly

actual delivery time vs. promised deliverytime for each vehicle

number of times vehicles were delivered to location other than what is specified on agreement

Critical Customer Requirement

The vehicle delivered meets the vehicle specifications as described in the contract

The vehicle is delivered within the time specified in the contract

The vehicle is delivered at the location specified in the contract


Indicators

Input Indicators

Process Indicators

Output Indicators


Measurement Planning



Variation

Variation means that a process does not produce exactly the same result every time the product or service is delivered

Variation exists in all processes

Measuring and understanding variation in our business processes helps identify specifically what the current level of performance is and what needs to change in order to reduce the variability and therefore reduce the defects delivered to customers


Two Basic Types of Data

Attribute Data

–Go/No Go–Good/Bad–Pass/Fail

Whether something is

happening or not

Variable Data

–Time–Temperature–Size

Information about what is happening


Two Basic Types of Data

Before data collections starts, classify the data into different types: continuous or discrete. This is important because it will:

– Provide a choice of data display and analysis tools– Dictate sample size calculation– Provide performance or cause information– Determine the appropriate control chart to use– Determine the appropriate method for calculation of Sigma

Continuous or variable

Measured on a continuum

Objective Time Money Weight Length

Subjective Satisfaction Agreement Extent Type of error

Discrete, categorical or attribute

Count or categories

Objective Count defects # approved # of errors Type of document

Subjective Yes/No Categories Service performance rating (good, poor) Satisfaction Agreement


Obtaining the Measurements

Data collected will only be as good as the collection system itself. In order to assure timely and accurate data, the collection method should be simple to use and understand. There are several methods. The most common are:

– Checksheet - a simple log of ―tick marks‖ representing the volume and type of work – Time stamps - a recording of the time that each activity begins and ends

Example: Checksheet Applications Returned for Missing Data

All data can be collected manually (writing in the log, recording the time, etc.) or automatically. Automatic data collection assures accurate and timely data, and removes the burden of collection from the operator of the process. But, it can be very expensive to set up. It usually involves computer programming and/or hardware. For most initial efforts, a paper log is the most cost effective form of data collection

Reason Missing Incorrect

Address X x x x x X x x x x

Phone X x x x X x

Employment Info X x X x x


Data Collection

Measurement management starts with a data collection methodology.

Identity Measures

Step 1Develop Operational

Definitions for Measure

Step 2Develop Measurement

Plan

Step 3Collect Data

Step 4Display and Evaluate

Data


Step 1: Develop Operational Definitions

Step 1: Operational DefinitionAn operational definition is a concept that helps guide the team‘s thinking on what they need to measure as well as the key attributes of the measure: what, how, and who. It provides the foundation for the team to reach agreement and build consistency and reliability into data collection. This helps ensure any person using the definition will be measuring the same thing.

Provides everybody with the same meaning

Ensures that consistency and reliability are built in up front

Describes the scope of the measure (what is included and what is not included)


Step 2: Develop a Measurement Plan

Step 2: Measurement PlanDetermining current process performance usually requires the collection of data. When developing a measurement plan ensure that:

The data collected is meaningful The data collected is valid All relevant data is collected concurrently

Questions to AnswerWhat precise data will be collected?

Performance measurement? Causes of process deficiencies?

Do we analyze all relevant data or a sample?What is the right sample size? What is the right frequency?What will be the sample selection method?

What tools are necessary? What formats will be used?What logs will be kept? Do we need a computer?


Questions to Answer

What logistical issues are relevant?Who will collect data?Where is the data located?When will it be collected?What additional assistance is required?

What you want to do with the data?Used daily, weekly, etc.Identify trends in the process dataIdentify deficiencies in the processDemonstrate current process performanceIdentify variation in a processIdentify a cause and effect relationship



Considerations for other data that should be collected at the same time:How will you display the data? What do you want to do with the data after it is collected?How do you want to stratify the data?What data might you need to identify and verify root cause?

Data collection is a balance between time, money and accuracy (getting the data you need).

Example: Cycle time - loan application processing


Performance Measure

Operational Definition

Data Source and Location

Sample Size Who Will Collect the

Data

When Will Data be

Collected

How Will Data be

Collected

Other Data that should be Collected at the same

time

Time to Process a

Loan Application

Fax date, time

Decision fax

Date, time

Loan application

Represent-ative fax

center

289 Tim SmithDave Man

During the first week

of the month

10/1-10/7

Randomly selected

from September

Type of loan

Amount of loan

DealerTime of

dayDay of week



Performance Measure




Data

When Will Data be

Collected

How Will Data be

Collected


time


Team Exercise

Complete Process Indicators Template

Complete Measurement Plan



Performance Measure




Data

When Will Data be

Collected

How Will Data be

Collected


time


Step 3: Collect Data

Follow the plan —note any deviations from the plan

Consistency —avoid bias

Observe data collection


Data Collection


Measurement System Analysis/Gage R&R

Measurement System Analysis/Gage R&R


The Importance of Measurement System Analysis (MSA)

Is the importance of conducting an MSA being overlooked?– Many resources can be wasted trying to improve a

process when a major source of variability is the measurement system

– More consideration needs to be given to the measurement system before beginning process improvement work

The measurement system is only one source of variability when measuring a product or process

The purpose of a measurement system is to better understand the sources of variation that can influence the results produced by the process under investigation


Repeatability (Precision)

The variation between successive measurements of the same part, same characteristic, by the same person using the same instrument. Also known as test/re-test error, used as an estimate of short-term variation.


Reproducibility

Reproducibility is the variation in the average of the measurements made by different appraisers using the same measuring instrument when measuring the identical characteristics on the same part.


Bias Effects

Average of measurements are different by a fixed amount. Bias effects include:

– Operator Bias–Different operators get detectable different averages for the same thing– Machine Bias–Different machines get detectable different averages for the same thing, etc.– Others–Day-to-day (environment), fixtures, customer and supplier (sites)

Instrument 1


Stability

The absence of assignable causes of variation; the property of being in statistical control. The consistency of measurements over time.


Discrimination

Discrimination is the capability of detecting even small changes in the characteristic

If unacceptable may not be appropriate to identify process variation or quantify individual part characteristic values

Cannot detect variation of process and special cause variation


Process Capability and Sigma Quality Level (SQL)

Process Capability and Sigma Quality Level


Process Capability – What is it?

Most measures have some target value and acceptable limits of variation around the target

The extent to which the “expected” values fall within these limits determines how capable the process is of meeting its requirements

Quantifiable comparison of Voice of Customer (spec limits)

to Voice of the Process (control limits).

Quantifiable comparison of Voice of Customer (spec limits)

to Voice of the Process (control limits).


Learning Objectives

Learn prerequisites for conducting process capability studies

Learn how Cp and C pk are calculated


Process Capability Ratio – C p

Ratio of total variation allowed by the specification to the total variation actually measured from the process

Typical goals for Cp are greater than 1.33 (or 1.67 for safety items)

If Cp< 1, then the variability of the process is

greater than the specification limits

If Cp< 1, then the variability of the process is

greater than the specification limits


Process Capability Ratio – C p


Process Capability Ratio – C pk

This index accounts for the dynamic mean shift in the process – the amount that the process is off target

Ratio of 1/2 total variation allowed by spec. to the actual variation, with only the portion closest to a spec. limit being counted


Uses of Capability Analysis

Performed on new equipment as part of the qualification and approval process

Performed on existing processes as a means of establishing a baseline of current operations (so it‘s possible to tell when improvement has occurred)

When done periodically, is a means of monitoring wear and tear on equipment, and deterioration of a process for whatever reason (material, personnel, environment, etc.)

Can be done on any process with a spec established, manufacturing or transactional (spec. is needed for the values in numerator), and has a capable measuring system (needed valid denominator value)


Capability Action Plan

Give highest priority to parameters with Cpk‘ s of less than 1.0 (center the dimension, reduce the variation or both)

– If possible, get tolerance relief. (If product/process is mature, and there have been no customer problems, what is the need for this formal spec when another ―de facto‖ spec has been used historically?)

– 100% inspect, measure and sort– Chart using the data from the measurements

Use SPC on parameters with Cpk‘ s between 1.0 and 1.33 (or 1.67 if safety related)

Consider transitioning to First Piece checks for parameters over 1.33 (or 1.67 if applicable), and SPC charting of First Piece and audit data


Sigma Quality Level – Attribute Data

Key Terms Required

– Unit (N)

– Defect (D)

– Opportunity (O)

– DPMO


Calculating SQL – Attribute Data

The first step is to define:

– The Unit (N)

– The Defect (D)

– The number of opportunities for generating a defect (per unit) (O)



DPMO = Total number of defects

Total units x Opportunities per unit

DPMO = (D/(NxO)) x 1,000,000

X 1,000,000


DPMO to SQL

Convert DPMO to Sigma Quality Level (SQL) using the Z table


Z Table to Convert DPMO to Sigma Level


Example

500 Part Orders(N) 3 Opportunities each order (O)

o Lateo Wrong Parto Wrong Address

57 errors are made (D) 12 caught 45 observed by customer

What is the Sigma Quality Level (SQL)?


Costs Are Always Kept in Mind

There is an optimum quality level beyond which the costs of quality improvement exceed the expected cost savings from a reduced number of defects

RLM & Associates LLC Your Lean Six Sigma & Project Management Trainers

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