Six Sigma Green Belt Training Lecture 5 Measure: Data Collection

Six Sigma Introduction Green Belt Training Six Sigma Introduction Define Measure Improve Control

Measure the current process to understand the performance

Measure Data Collection MSA Process Stability Process Capability

Measure Phase Deliverables Mapped Process Quick wins Implemented A confirmed Operational Definition Analyzed Measurement System Determine process stability & process capability

Measure Data Collection MSA Process Stability Process Capability

Data Collection Objectives Why Collect Data? Populations & Samples When to Collect Data? How to Collect Data?

Why collect data? Data is the Voice of the Process (VoP) VoP and VoC need to speak the same language An operational definition is essential Data Can validate root causes Can be used for trending Helps prove anecdotal statements Can be graphed to identify sources of variation

When to collect Data Define Phase Measure Phase Analyze Phase Quantify the business case Establish a SMART metric Measure Phase Voice of the Process Measurement System Analysis Process Capability Analyze Phase Understand the root cause of the problem Improve Phase Pilot Design of Experiments Control Phase Repeat the same measurements as done in Measure phase Control Charts

Collecting data is a key step in the process of making good decisions Data Decision Cycle ???? Need for decision Good decision What are right questions? Measure phase questions: Project Y stable? Project Y capable? Type of problem? The DMAIC way Answer questions based on data analysis Analyze the data using graphs and statistical methods What data do we need? Collect the data Collecting data is a key step in the process of making good decisions

How much data to collect?

Samples & Populations

How much data to collect Since it is not always practical, possible or economic to measure everything in the population, we usually take a random sample

Taking a “Peek” at a Few to Make Estimates about the Total Sampling Taking a “Peek” at a Few to Make Estimates about the Total

Key Terms Population: EVERY data point that has ever been or ever will be generated from a given characteristic. Sample: A portion (or subset) of the population, either at one time or over time Observation: An individual measurement.

Ways of Sampling Process Sampling Population Sampling Sample Process in Motion Helps understand nature and conditions of the process Population Sampling Sample Determines characteristics of the population

Methods of Sampling Stratified Random Sampling Random Sampling each item has equal probability of being selected population “stratified” into groups random selection within each group Systematic Random Sampling Subgroup Sampling Process in Motion every nth item 3 samples at this point each hour

Sampling Exercise

Types of Sampling Errors Error in sampling Error due to differences among samples drawn at random from the population (luck of the draw). This is the only source of error that statistics can accommodate. Bias in sampling Error due to lack of independence among random samples or due to systematic sampling procedures (height of horse jockeys only). Lack of measurement validity Error in the measurement does not actually measure what it intends to measure (placing a probe in the wrong slot measuring temperature with a thermometer that is just next to a furnace). Error in measurement Error in the measurement of the samples.

How to Collect Data Automated Data Collection Manual Collection IBEX ClinStar HED HSM Manual Collection Manual Forms Patient Charts/Sheets Time Studies Observation Studies

Manual data collection forms Unfortunately, most projects do not have data and data collection forms need to be created by the project team Create the form such that it can capture all the relevant information that may be required to solve the problem Train all those involved in the data collection as to how the form is to be completed and test the form for a day Work out all of the issues prior to full implementation to ensure the correct data is being collected Ensure the data from the forms is entered into a database as quickly as possible

Manual Data Collection Identify elements of data that will be collected What are we measuring? When are we collecting data? All shifts? All days? How long will we track this metric(s)? Who is responsible for collecting the data? Who is asking us to do this? WIFM? Confirm Operational Definitions with your team and train your data collectors This step is essential to make sure that everyone is measuring the same thing This will be pertinent later on in this phase when we talk about Measurement System Analysis (MSA) Create a Data Collection Plan

Obtaining the measurements There are several simple methods to collect initial data The most common are Check sheet: 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 Check sheet example: applications returned for missing data © 2002 IBM Corporation (unpublished). All rights reserved. Version 1.0.

Example data collection form Identification of the largest contributors Identifying of data is normally distributed Identifying sigma level and variation Root cause analysis Correlation analysis Pareto chart Histogram Control chart Scatter diagrams How will data be used? How will data be displayed?

Summary Describe when & why we collect data At this point, you should be able to: Describe when & why we collect data Understand the different ways and methods to sampling Explain the different types of sampling errors Create and implement a data collection plan