Continuous Improvement Toolkit...Continuous Improvement Toolkit . truly show that a picture is worth...
Transcript of Continuous Improvement Toolkit...Continuous Improvement Toolkit . truly show that a picture is worth...
Continuous Improvement Toolkit . www.citoolkit.com
Continuous Improvement Toolkit
Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Check Sheets
DataCollection
Process MappingFlowcharting
Flow Process Charts
5S
Value Stream Mapping
Control Charts
Mistake Proofing
Tree Diagram*
UnderstandingPerformance
Fishbone Diagram
Design of Experiment
ImplementingSolutions**
Creating Ideas
Brainstorming Attribute Analysis
Deciding & Selecting
Decision Tree
Force Field Analysis Cost Benefit Analysis
Voting
Planning & Project Management*
Value Analysis
Kaizen Events
Quick Changeover
ManagingRisk
FMEA
PDPC
RAID Log*
Observations
Focus Groups
UnderstandingCause & Effect
Pareto Analysis
IDEF0
5 Whys
Matrix DiagramKano Analysis
KPIs
Lean Measures
Importance-Urgency Mapping
Waste Analysis
Fault Tree Analysis
Relationship Mapping*
Benchmarking**
SCAMPER**
C&E Matrix
Confidence Intervals
Pugh Matrix
SIPOC*
Prioritization Matrix
Stakeholder Analysis
Critical-to Tree
Paired Comparison
Improvement Roadmaps
Interviews
QFD
Graphical Analysis
Lateral Thinking
Hypothesis Testing
Visual Management
Ergonomics
Reliability Analysis
Cross Training
How-How Diagram**
Flow
Time Value Map
ANOVA
Gap Analysis*
Traffic Light Assessment
TPN Analysis
Decision Balance Sheet
Suggestion systems
Risk Assessment*
AutomationSimulation
Break-even Analysis
Service Blueprints
DMAIC
Process Redesign
Run Charts
TPM
Control Planning
Chi-Square
SWOT Analysis
Capability Indices
Policy Deployment
Data collection planner*
Affinity DiagramQuestionnaires
Probability Distributions
Bottleneck Analysis**
MSA
Descriptive Statistics
Cost of Quality*
Process Yield
Histograms & Boxplots
Just in Time
Pick Chart
Portfolio Matrix
Four Field Matrix
Root Cause Analysis Data Snooping
Morphological Analysis Sampling
Spaghetti Diagram
Pull
OEE
Mind Mapping*
Project Charter
PDCA
Designing & Analyzing Processes
CorrelationScatter PlotsRegression
Gantt Charts
Activity NetworksRACI Matrix
PERT/CPMDaily Planning
MOST
Standard work Document controlA3 Thinking
The Continuous Improvement Map
Multi vari Studies
Continuous Improvement Toolkit . www.citoolkit.com
Statistic is the science of describing,interpreting and analyzing data.
Statistics may be: • Graphical:
Makes the numbers visible.
• Inferential:Makes inferences about populations from sample data.
• Analytical:Uses math to model and predict variation.
• Descriptive:Describes characteristics of the data (location and spread).
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Graphs truly show that a picture is worth a thousand of words.
A long list of data is usually not practical for conveying information about a process.
One of the best ways to analyzeany process is to plot the data.
Many graphical tools are available which can generate graphs quicklyand easily.
- Graphical Analysis
*
Continuous Improvement Toolkit . www.citoolkit.com
Benefits:
Allows to learn about the nature of the process.
Enables clarity of communication.
Helps understanding sources of variation in the data.
Provides focus for further analysis.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Different graphs can reveal different characteristics of your data:• Central tendency.
• Dispersion.
• The general shape for thedistribution.
Conclusions drawn from graphs may require verification through advanced statistical techniques such as significance testing and experimentation.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Graphing the data can be utilized for both historical data and live data collection activities.
You need to pick the right graphical tool as there are a lot of different ways to plot your data.
If one graph fails to reveal anythinguseful, try another one.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Line Charts:
One of the simplest form of charts.
Useful for showing trends in quality, cost or other process performance measures.
They represent the data by connecting the data points by straight lines to highlight trends in the data.
A standard or a goal line may also be drawn to verify actual performance against identified targets.
Time series plots, run charts, SPCcharts and radar charts are all linecharts.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Time Series Plots:
Line charts used to evaluate behavior in data over a time interval.
They can be used to determine if a process is stable by visually spotting trends, patterns or shift in the data.
If any of these are observed, then we can say that the process is probably unstable.
It requires the data to be in the order which actually happened.
More advanced charts for assessing the stability of a process over time are run charts and SPC charts.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Time Series Plots:
Time Series Analysis is the analysis of the plotted data in order to get meaningful information.
Different behaviors of the data can be observed such as:• Upward and downward trends.
• Shifts in the mean.
• Changes in the amount of variation.
• Patterns and cycles
• Anything not random.
Time Series Forecasting is theuse of a model to predict futurevalues based on observed values.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – The average time it needed to change a label:
- Graphical Analysis
37.5
35.0
42.9
39.838.6
47.2
36.6
34.3
30.8
35.2
32.7
29.0
20
25
30
35
40
45
50
55
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
A time series plot for evaluating continuous data
Continuous Improvement Toolkit . www.citoolkit.com
Example – The number of unanswered calls in a call center:
- Graphical Analysis
A time series plot for evaluating count data
25
27 27 2728
2221
30
24
27
15
20
24
31
2221
2221
20
30
27
10
15
20
25
30
35
Wk 1 Wk 3 Wk 5 Wk 7 Wk 9 Wk 11 Wk 13 Wk 15 Wk 17 Wk 19 Wk 21
Unansw
ere
d
Calls
Continuous Improvement Toolkit . www.citoolkit.com
Example – The number of scrapped products generated from three machines:
- Graphical Analysis
0
2,000
4,000
6,000
8,000
10,000
12,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Scra
pped
Pro
ducts
Machine 1 Machine 2 Machine 3
Continuous Improvement Toolkit . www.citoolkit.com
Pie Charts:
Circular charts that make it easy to compare proportions.
Widely used in the business and media worlds for their simplicity and ease of interpretation.
They represent each category as a slice of the pie.
They display the proportion of each category relative to the whole data set.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Pie Charts:
A Doughnut Chart is a variation of the pie chart with a blank center.
It allows for additional information to be included about the data.
Pie and doughnut charts work well with few categories.
They are suitable for presenting data for around seven groups or fewer.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Bar Charts:
Used to display frequencies of attribute data.
They focus on the absolute value of the data.
The bars on the chart are presented horizontally or vertically.
When a bar chart presents the categories in descending order of frequency, this is called a Pareto Chart.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Bar Charts:
Grouped Bar Charts display bars clustered in groups.
Staked Bar Charts stack bars of each group on top of each other to show the cumulative effect.
A 100% Staked Bar Chart is used for demonstrating the difference in proportion between categories.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – A grouped bar chart displaying the number of occupied beds in a hospital in two consecutive years.
- Graphical Analysis
450
420432
363
320340
309
350
320340
389
440440426 420
380
342359 352 360
350
325
399
480
0
100
200
300
400
500
600
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Nu
mb
er o
f O
cc
up
ied
B
ed
s
Year 1 Year 2
Continuous Improvement Toolkit . www.citoolkit.com
Example – A stacked bar chart displaying the number of occupied beds in a hospital in two consecutive years.
- Graphical Analysis
0
100
200
300
400
500
600
700
800
900
1000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Nu
mb
er o
f O
cc
up
ied
B
ed
s
Year 1 Year 2
Continuous Improvement Toolkit . www.citoolkit.com
Dotplots:
A Dotplot is a graphical representation ofdata using dots plotted on a simple scale.
A form of frequency distribution.
It is suitable for displaying small tomoderate data sets.
The X-axis is divided into many small intervals called bins.
The data values falling within each bin are represented by dots (one or more dots per data point).
The end result is a set of vertical lines of dots.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Dotplots:
It is generally used when the data is discrete.
It can also be used to present continuous data.
It shows where the data are clustered, where the gaps are located and can help identify outliers.
Dotplots are also useful for comparing distributions in terms of their shape, location and spread.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – A dotplot that displays the number of complaints made by customers in a given period of time.
- Graphical Analysis
262422201 81 6
Number of Complaints
A dotplot for evaluating count data
Continuous Improvement Toolkit . www.citoolkit.com
Example – A dotplot showing the GPA scores of all students in a business college.
- Graphical Analysis
3.63.02.41 .81 .20.6
GPA
Each symbol represents up to 4 observations.
A dotplot for evaluating continuous data
Continuous Improvement Toolkit . www.citoolkit.com
Example – A dotplot is created to compare the teachers who had been on sick leave between two types of schools.
- Graphical Analysis
100.0%80.0%60.0%40.0%20.0%0.0%
Sick %
Public
Private
School Type
Continuous Improvement Toolkit . www.citoolkit.com
Example – An analysis that was conducted for diagnosing the presence of diabetes at a workplace.
- Graphical Analysis
Describes the shape of the data
Continuous Improvement Toolkit . www.citoolkit.com
Example – An analysis that was conducted for diagnosing the presence of diabetes at a workplace.
- Graphical Analysis
New diagnosis
High levels
Diabetes under control
Low level
Continuous Improvement Toolkit . www.citoolkit.com
Individual Value Plots:
Graphs that are useful to give an overall picture of the individual values that make up a data set.
Often used for comparing distributions that have small number of data.
They enable to see all the values of a dataset even if there are similar data points.
They give an idea of the distribution shapesand whether outliers are present.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – An individual value plot showing the responses of a particular marketing campaign that uses multiple advertising methods.
- Graphical Analysis
NewspaperMailMagazine
20
1 5
1 0
5
0
Type of Advertising
Resp
on
se
Continuous Improvement Toolkit . www.citoolkit.com
Individual Value Plots:
What can you conclude from this Individual Value Plot?
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Radar Charts:
Used to display and compare multiple data sets over a range of characteristics or over a specific period of time.
It comes in the form of a two-dimensional chart.
It has a radial axis and an angular axis.
After plotting the data, a point close to the center indicates a low value and a point near the edge indicatesa high value.
A line is normally drawn connectingthe data values for each data set.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – A radar chart that displays the daily mean temperatures in four different cities over the year.
- Graphical Analysis
-10
0
10
20
30
40
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec Abu Dhabi
Istanbul
Helsinki
Cape Town
Continuous Improvement Toolkit . www.citoolkit.com
Multi-Vari Charts:
Variation in the data may come from multiple sources.
A Multi-Vari Chart is a graphical tool that allows to visually show where the major variation is coming from.
Multiple variables are plotted together on a single chart.
Often used when studying the variation within:• A subgroup.
• Between subgroups.
• Over time.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Example – A multi-vari chart showing how the type and composition affect the durability of a carpet.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Scatter Plots:
Many problems require theestimation of the relationshipbetween two or more variables.
Scatter plots are used to study therelationship between two variables.
They are used to determine whathappens to one variable whenanother variable changes value.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Probability Plots:
Graphical techniques that provide a more decisive approach for determining if your data follows a particular distribution.
Constructed in a way that the pointswill fall in a straight line if they fit thedistribution in question.
They are an improvement from justassessing visually.
- Graphical Analysis
Normal Probability Plots
Continuous Improvement Toolkit . www.citoolkit.com
Graph Selection:
The graphs you choose depends on:• The type of data you have.
• The objective you are trying to achieve.
There are graphs for continuous data andgraphs for count and attribute data.
Remember that you need to perform additionalstatistical analysis before drawing any conclusion.
- Graphical Analysis
Continuous Improvement Toolkit . www.citoolkit.com
Graph Selection:
- Graphical Analysis
Continuous Data
Dotplots
Histograms*
Individual Value Plots
Boxplots*
Time Series Plots
Determine the shape of the data
Scatter Plot
Multi-Vari ChartsUnderstanding thesource of variation
Study relationshipsbetween variables
Understanding process stability
Understandingthe differencesbetween groups
* Larger amount of data
Count/Attribute Data
Bar Charts
Pareto Charts
Pie Charts
Dotplots
Comparing betweengroups
Determine the shape of the data
Time Series PlotsUnderstanding process stability
Scatter PlotStudy relationshipsbetween variables