Six Sigma Tools for continuous quality improvement


Statistics Software

Your Systems2win Six Sigma software does those things well

that your favorite statistical software probably does poorly:

Pareto Diagram FMEA OEE
  1. Basic Quality Tools
  2. Root Cause Analysis tools
  3. Problem Solving tools
  4. Design for Six Sigma tools
  5. TPM Total Productive Maintenance

Statistics Tools NOT offered by Systems2win

The majority of time in Six Sigma Black Belt training is devoted to learning complex statistical methods.

There are already many excellent statistical packages to choose from, and you will find your Systems2win templates to be an excellent complement to any statistics software that you choose to use to do advanced statistical analyses, such as:

Design of Experiments

Design of Experiments is a Six Sigma method for designing and analyzing a minimum number of carefully planned experiments on a process.

Usually a series of experiments that start broadly, and then focus on the few factors identified as most critical.

Hypothesis Testing

Scientific methods to analyze data to answer the question:
"What is the probability that these results could have happened by random chance?"

Popular types of hypothesis tests include chi-square test, t-test, z-test, F-test, ANOVA analysis of variation

Regression Analysis

scatter plot

Your Scatter Plot template
supports simpler
Correlation Analysis,
rather than Regression Analysis

You can use your Scatter Plot template  (ScatterPlot.xlsx)
to analyze pairs of numerical data
l ooking for patterns of possible relationship.

The simplest pattern is linear (a straight line through a scatter diagram),
where you can use simple Correlation Analysis.

which is supported by your template.

Another (more complex) way to analyze a linear relationship is to use Regression Analysis
to draw the best-fit straight line through your data,
and generate a table of statistical data for you to analyze — including:

  • Slope of the line (indicating positive or negative correlation)
  • Intercept (where the line crosses the y axis)
  • Coefficient of determination, r2 (a number between 0 and 1, indicating how closely the data fits the line)
  • Confidence interval (the range where the true line will fall — if you measure a larger sample)

Other (even more complex) types of regression analysis include non-linear regression and multiple regression (for multiple variables).

Regression Analysis complex enough to bring in your Black Belts to help you.
Your Systems2win templates do not support regression analysis.

Normal Probability Plot

Quantile-Quantile Plot, Q-Q Plot


Usually, your Excel Histogram template  (Histogram.xlsx)
will allow you to easily assess whether or not your data fits a normal distribution.

Some advanced Six Sigma practitioners, however, sometimes also like to supplement a histogram with a Q-Q graph to further evaluate whether a set of data fits the form of a normal distribution.

Process Capability Study

Your Excel Histogram template has features to help you quickly assess the anticipated defects per million opportunities and the Sigma Quality Level of your process.

Some advanced Six Sigma practitioners also like to further analyze the ability of a stable process that fits a normal distribution to generate output within specification limits for a particular quality characteristic.

You will analyze the following variations of PCI Process Capability Index —
comparing process variation to specifications.

  1. Cpk and Cp, or Ppk and Pp — to minimize the amount of out-of-tolerance occurrences
  2. Cpm and Cpmk — to minimize the average variation from target

Repeatability and Reproducibility Study

aka R&R, Gage R&R, MSA Measurement System Analysis

To analyze variation of a measurement system that uses an instrument or gage —
comparing variation in the gage reading to variation in the total process
(as observed in some way other than the gage).

Box Plot

aka Box and Whisker Plot

A way to summarize the most important statistical data to show where data falls, and how much variability exists.

More types of Control Charts

Control Chart template

Your Systems2win Control Chart template is best of class
for creating a u-chart, p-chart, or u-chart of Attribute data

and is especially good for charting data using a moving range
(for example, the last 30 days),
even if there is a process change in the middle of your moving range
(for example, you changed the process, and now want to start measuring a new average, rather than averaging the old and new processes together).

Advanced statistical software will also offer other types of Control Charts for Variable data, and less popular types of data — including Chart of Individuals, X bar and R, X bar and S.

What's your ratio of Black Belts to Green Belts?

If you have already completed the extensive statistical training to earn your Six Sigma Black Belt

then all of the statistical tools and methods are already familiar to you,
and you undoubtedly already own and use your own favorite statistical software to do these types of analyses.

If your eyes are glazing over,

then you will appreciate why Systems2win does not offer tools for these types of sophisticated statistical analysis.

Questions to ponder

when considering whether to supplement your favorite statistical software with Systems2win templates

  1. How many Six Sigma Black Belts do you have?

    (that understand the above types of statistical analyses)

  2. If you owned a license for unlimited users,
    how many people could participate to improve their own processes
    using the Systems2win templates?

    (that use simpler methods to begin with, and have better online training)

















Your purchase price is usually justified with the 1 or 2 templates that you use most

The others are a really nice
"gift with purchase"

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