Six Sigma Tool Navigator: The Master Guide for Teams

2017-07-07 02:10:07

AKA

Polygon Trend Comparison

Classification

Analyzing/Trending (AT)

Tool description

A polygon overlay is a graphical representation of many data variables, encoded for quick comparisons. It is a statistical tool that shows trendlines and correlations found in historical data.

Typical application

To plot data for forecasting purposes.

To allow results comparisons.

To verify status of progress.

To provide supporting data in a problem-solving effort.

Problem-solving phase

→	Select and define problem or opportunity
→	Identify and analyze causes or potential change
	Develop and plan possible solutions or change
→	Implement and evaluate solution or change
	Measure and report solution or change results
	Recognize and reward team efforts

Typically used by

1	Research/statistics
	Creativity/innovation
4	Engineering
3	Project management
	Manufacturing
6	Marketing/sales
	Administration/documentation
	Servicing/support
5	Customer/quality metrics
2	Change management

links to other tools

before

Data Collection Strategy

Observation

Event log

Surveying

Frequency Distribution (FD)

after

Trend Analysis

Process Analysis

Pie Chart

Stratification

Presentation

Notes and key points

Do not exced five data variables on one cart; it may become difficult to scale every variable if vertical scales cannot be used for more than one variable. if there is a great numerical difference that requires separate vertical scale designations (upper/lower limits), a common denominator must be used to align scales from the zero point on the overlay graph.

Step-by-step procedure

STEP 1 Draw the vertical axis to be 75 percent of the horizontal axis. This 3:4 ratio rule is used to ensure unbiased graph construction. See example Company Reengineering and Retraining Results.

STEP 2 Identify the number of scales and their upper and lower limits required to include all data points.

STEP 3 Encode and name different data sets.

STEP 4 Graph data, anchoring it to its specific scale.

STEP 5 Verify that all raw data have been accounted for and properly converted to corresponding frequencies and positions on the graph.

STEP 6 Ensure that the title of the graph and all designations provide accurate descriptions of the data. Use notes if necessary to guarantee clarity.

STEP 7 If desired, continue to plot data for ongoing treendline analyses.