Continuous Improvement Toolkit Graphical Analysis

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Continuous Improvement Toolkit

Graphical Analysis

Continuous Improvement Toolkit . www.citoolkit.com The Continuous Improvement Map Managing Deciding & Selecting Planning & Project Management* Risk PDPC Decision Balance Sheet Importance-Urgency Mapping Daily Planning PERT/CPM

FMEA RAID Log* Force Field Analysis Cost Benefit Analysis MOST RACI Matrix Activity Networks

Risk Assessment* Break-even Analysis Voting TPN Analysis SWOT Analysis Stakeholder Analysis Decision Tree Pick Chart Four Field Matrix Fault Tree Analysis Project Charter Improvement Roadmaps Critical-to Tree QFD Portfolio Matrix Traffic Light Assessment PDCA Policy Deployment Gantt Charts DMAIC Kano Analysis Matrix Diagram Paired Comparison Lean Measures Kaizen Events Control Planning Cost of Quality* Pugh Matrix Prioritization Matrix Bottleneck Analysis** A3 Thinking Standard work Document control OEE KPIs Pareto Analysis C&E Matrix Process Yield Understanding Cross Training Implementing ANOVA Chi-Square Descriptive Statistics Value Analysis Solutions** Capability Indices Cause & Effect Probability Distributions Hypothesis Testing Design of Experiment Mistake Proofing Ergonomics Gap Analysis* Histograms & Boxplots Multi vari Studies Confidence Intervals Simulation TPM Automation Reliability Analysis Graphical Analysis Scatter Plots Correlation Pull Flow Just in Time Understanding Regression MSA 5 Whys Performance Run Charts Root Cause Analysis Data Snooping Visual Management 5S Benchmarking** Control Charts Fishbone Diagram Tree Diagram* SIPOC* Waste Analysis Quick Changeover Data collection planner* Sampling Morphological Analysis How-How Diagram** Process Redesign Time Value Map Value Stream Mapping Check Sheets Interviews Brainstorming SCAMPER** Attribute Analysis Spaghetti Diagram Affinity Diagram Relationship Mapping* Flow Process Charts Service Blueprints Questionnaires Focus Groups Data Mind Mapping* Lateral Thinking Flowcharting IDEF0 Process Mapping Observations Collection Suggestion systems Creating Ideas Designing & Analyzing Processes Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis

 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).

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis

 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 analyze any process is to plot the data.  Many graphical tools are available which can generate graphs quickly and easily.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis

 Different graphs can reveal different characteristics of your data: • Central tendency. • Dispersion. • The general shape for the distribution.

 Conclusions drawn from graphs may require verification through advanced statistical techniques such as significance testing and experimentation.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis

 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 anything useful, try another one.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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, SPC charts and radar charts are all line charts.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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 the use of a model to predict future values based on observed values.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – The average time it needed to change a label:

50 47.2

45 42.9

39.8 38.6 40 37.5 36.6 35.0 35.2 34.3 35 32.7 30.8 29.0 30

20 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 - Graphical Analysis Example – The number of unanswered calls in a call center:

31 30 30 30 28 27 27 27 27 27

25 25 24 24 22 22 22 21 21 21 20 20

20 Unanswered Unanswered Calls 15 15

10 Wk 1 Wk 3 Wk 5 Wk 7 Wk 9 Wk 11 Wk 13 Wk 15 Wk 17 Wk 19 Wk 21

A time series plot for evaluating count data

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – The number of scrapped products generated from three machines:

Machine 1 Machine 2 Machine 3 12,000

10,000

8,000

6,000

Scrapped Scrapped Products 4,000

2,000

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A grouped bar chart displaying the number of occupied beds in a hospital in two consecutive years.

Year 1 Year 2 600

500 480 450 440 432 440 420 426 420 389 399 400 380 363 359 352 360 342 340 350 350 340 320 320 325 309 300

200

100 Number of Occupied Beds Occupied of Number

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A stacked bar chart displaying the number of occupied beds in a hospital in two consecutive years.

Year 1 Year 2 1000

900

800

700

600

500

400

300

200 Number of Occupied Beds Occupied of Number 100

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Dotplots:  A Dotplot is a graphical representation of data using dots plotted on a simple scale.  A form of frequency distribution.  It is suitable for displaying small to moderate 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A dotplot that displays the number of complaints made by customers in a given period of time.

1 6 1 8 20 22 24 26

Number of Complaints

A dotplot for evaluating count data

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A dotplot showing the GPA scores of all students in a business college.

0.6 1 .2 1 .8 2.4 3.0 3.6 GPA

Each symbol represents up to 4 observations. A dotplot for evaluating continuous data

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A dotplot is created to compare the teachers who had been on sick leave between two types of schools.

School Type Public Private

0.0% 20.0% 40.0% 60.0% 80.0% 1 00.0%

Sick %

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – An analysis that was conducted for diagnosing the presence of diabetes at a workplace.

Describes the shape of the data

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – An analysis that was conducted for diagnosing the presence of diabetes at a workplace.

Low level

Diabetes under control New diagnosis High levels

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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 data set even if there are similar data points.  They give an idea of the distribution shapes and whether outliers are present.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – An individual value plot showing the responses of a particular marketing campaign that uses multiple advertising methods.

1 5

n o

p 1 0

e R

0 Magazine Mail Newspaper Type of Advertising

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Individual Value Plots:  What can you conclude from this Individual Value Plot?

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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 indicates a high value.  A line is normally drawn connecting the data values for each data set.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A radar chart that displays the daily mean temperatures in four different cities over the year.

Jan 40 Dec Feb Abu Dhabi 30 Istanbul

20 Helsinki Nov Mar 10 Cape Town

Oct -10 Apr

Sep May

Aug Jun

Jul

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Example – A multi-vari chart showing how the type and composition affect the durability of a carpet.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Scatter Plots:  Many problems require the estimation of the relationship between two or more variables.  Scatter plots are used to study the relationship between two variables.  They are used to determine what happens to one variable when another variable changes value.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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 points will fall in a straight line if they fit the distribution in question.  They are an improvement from just assessing visually.

Normal Probability Plots

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis 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 and graphs for count and attribute data.  Remember that you need to perform additional statistical analysis before drawing any conclusion.

Continuous Improvement Toolkit . www.citoolkit.com - Graphical Analysis Graph Selection:

Count/Attribute Data Continuous Data

Bar Charts Dotplots Determine the Comparing shape of the data Pareto Charts between Histograms* groups Pie Charts Individual Value Plots Understanding the differences Determine the Boxplots* between groups Dotplots shape of the data Understanding Understanding Time Series Plots Time Series Plots process stability process stability Study relationships Study relationships Scatter Plot between variables Scatter Plot between variables Understanding the Multi-Vari Charts source of variation * Larger amount of data

Continuous Improvement Toolkit . www.citoolkit.com