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Six Sigma Master Black Belt Body of Knowledge – 2013

In Six Sigma Black Belt Curriculum and Body of Knowledge – 2012, a universal, highly technical body of knowledge was proposed to equip Black Belts with the expertise and abilities needed to lead nontrivial process improvement efforts over a full spectrum of diverse scenarios. But what additional technical knowledge should be expected for a Master Black Belt?

This article addresses the minimum additional technical knowledge that a Master Black Belt should possess beyond the topics already defined for Black Belts. There are many statistical tools not mentioned here that could be useful as part of a Master Black Belt’s toolbox – this list is not intended to limit the body of knowledge for a Master Black Belt.

Click here to read the previously published “Master Black Belt Curriculum and Body of Knowledge” on iSixSigma.com.

An effective Master Black Belt must possess skills and knowledge outside of these Six Sigma technical topics. A Master Black Belt should have a mastery of Lean, total productive maintenance and Design for Six Sigma along with leadership skills, project management skills, change management skills, and instructional and presentation skills. Years of experience in project work, coaching, classroom instruction and higher-level strategic planning are also critical for an effective Master Black Belt.

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A Master Black Belt who is advising or guiding an organization must be able to identify the roadmap made up of individual projects based on assessments of the operation against the business needs in order to close the gap on perfect operation. Without this broad, strategic view of the improvement efforts, all the work is pointless. Thus, technical knowledge represents only a portion of the makeup of a successful Six Sigma practitioner. Nonetheless, a Master Black Belt must be able to provide a high degree of technical expertise when called upon, and consequently there should be a corresponding minimum body of knowledge associated with that title.

As a baseline, a Master Black Belt should have a mastery of these following advanced Six Sigma topics:

1General linear model (GLM): This is the basis for the ANOVA (analysis of variance) and regression topics that Black Belts are expected to understand. Factors, covariates, crossed, nested and mixed structures all have important applications and are important to master, particularly when teaching ANOVA to Black Belts.

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2Advanced regression: A Master Black Belt should be able to apply general and nonlinear regression to data sets when appropriate. General regression allows for interactions between predictors while nonlinear regression allows an arbitrary prediction equation to be defined and fitted to the data.

3Advanced DOE (design of experiments): Black Belts should be able to perform 2k full and fractional factorials, general full factorials, multiple response optimization, central composite design, response surface methods and evolutionary operation DOEs. In addition to these types of DOEs, Master Black Belts should be able to perform the following advanced designs:

  • Robust design: This type of DOE analyzes the variation of an output so that a design can be determined that will minimize this variation over the conditions and operational settings of the product or service.
  • Mixture design: This DOE is useful when there are constraints on the factor settings as is the case for recipe or mixture settings where the inputs must add up to 100 percent.
  • Split plot design: This is a useful technique when dealing with hard-to-change factors in the experimental design.
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4Ordinal and nominal logistic regression: Black Belts should understand binary logistic regression, but Master Black Belts should also be well versed in applying the logistic regression approach to ordinal and nominal data.

5Measures of association: This is essentially correlation analysis with discrete data. It is particularly useful for analyzing and interpreting survey results or performing an attribute gage R&R study using an attribute agreement analysis. Survey design and analysis should be part of this topic to ensure that surveys are created to give meaningful results when analyzed using measures of association or other analytical techniques.

6Principle components/factor analysis: This type of analysis is useful when there are highly correlated factors in the data. A principle components/factor analysis can help to reveal underlying root causes that may be manifested as different combinations of factors in the data set.

7Advanced probability distributions: Black Belts should understand and be able to analyze normal, t, F, chi-squared, binomial, Poisson, exponential, Weibull and lognormal distributions. In addition to these, a Master Black Belt should be able to derive the hypergeometric distribution and should have a solid understanding of the basic event probability concepts, and also permutations and combinations that are the key concepts behind this fundamental distribution. Other probability distributions such as gamma, geometric and negative binomial should also be understood.

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8Data transformations: Performing data transformations without understanding when they are necessary and how to properly apply them has led to many errors and much confusion throughout the history of Six Sigma. A Master Black Belt should know when a transformation is appropriate (e.g., non-normality or heteroskedasticity), what is the simplest effective technique (Box-Cox, Johnson, etc.) and how to communicate the results of a transformed set of data.

9Extended gage R&R: This is essentially an application of the GLM to a variable gage R&R study. Whenever there are factors beyond parts and operators (such as test stands or facilities), the standard gage R&R design is not sufficient. An extended gage R&R study is also necessary when there are combinations of crossed and nested factors in the measurement system.

10Advanced time series analysis: Forecasting is one of the most commonly flawed undertakings of businesses. Understanding such advanced time series analysis concepts as autocorrelation, cross correlations and auto regressive integrated moving average (referred to as ARIMA) can be extremely useful in improving a company’s forecasting accuracy and comprehension of forecasting limitations.

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11Reliability basics: Reliability is a crucial factor in many businesses for both internal equipment and products being used by customers. A Master Black Belt should have an excellent understanding of reliability concepts such as hazard rates, mean time between failure, censored data, parallel and series designs, as well as the applications of exponential, lognormal and Weibull distributions to reliability scenarios.

There are, of course, many other useful statistical and analytical tools that may be valuable for Master Black Belts depending on the environment in which they are working. These tools can be taught in a two-week Master Black Belt technical training course.

Keep in mind that superior technical knowledge alone does not translate to an effective Master Black Belt. Given that the role’s title implies a “mastery” of Six Sigma tools, these topics should be considered a minimum body of knowledge for someone who goes by the designation of Master Black Belt.

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Comments 12

  1. Jason Merschat

    The Master Black Belt should be in a strategy and leadership position in an organization. The MBB should have vision across the enterprise and not be merely a highly proficient technician. The proficiency in these areas should be what is driven for this level of Mastery beyond technical prowess. I submit that beyond technical aptitude, the MBB be well versed in Organizational Strategy, Organizational Change and Transformation, Leadership, Motivation, Conflict Resolution, Interpersonal Skills, Navigating the Political Landscape of Organizations, Prioritizing and Selecting CI Strategy for the Enterprise.

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  2. Herrick Andrews

    I agree with Jason,

    All 10 items in the list have to do with technical skills such as data analysis, statistics, etc.. I think those are important, but I would have listed as just 2 or 3 of the 10 items. E.g,,

    1. Advanced Statistical Understanding/Appreciation
    2. Data Collection
    3. Data Analysis
    4. Measuring
    5. Teaching (“Those who can teach, teach! Those who can’t, only do.”)
    6. Delegation
    7. Basic Programming (e.g., Microsoft Office VBA)
    8. Project Management (for those who didn’t come from the Proj Mgt ranks)
    9. Long history of success full process improvement experience.
    10. Decision Making (e.g., hierarchial, FDM, non-linear scales)

    I didn’t put a lot of thought into this list, but I hope it gives the general idea.

    It surprises me how many MBB’s I see who don’t know how to review and evaluate a BB’s progress. Not just on their project deliverables, but on their personal growth. Many don’t appreciate statistics, and teach their BB’s the wrong way. I wish I would never see another case where cycle time data is analyzed using Normal distribution methods. Cycle Time data is NEVER Normal, no matter what the normality tests tell you. Yet, I see MBBs telling BBs to use data analysis tools that are designed for analyzing Normal distributions; not cycle time distributions.

    An MBB should see tools like Minitab as a aide to make them work faster, not as a crutch so they don’t have to understand statistics. If, as an MBB, you don’t understand what the tool is doing behind the scenes, you shouldn’t use it; much less teach it.

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  3. Sean Mansfield

    Interesting summary. I have to agree with Jason’s comment. Appreciation and some understanding of these topics are important. The need is also highly industry dependent. Few MBBs have the statistical background and or tenure in job to master all of this. Most of these in practice is a good balance or art and science and easy to misconstrue….

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  4. Mahesh Masurkar

    Good discussion. I agree with Jason’s comment on the role of the MBB in an organization in a nutshell.
    But the exact roles and responsibility of MBB differs from organization to organization.
    I feel it all depends on the # of BBs and MBBs one organization have.

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  5. Billy Jack

    Agree with most of the comments above, especially the first one. When a Master Black Belt is selected in an organization, he/she is a coach and mentor to all belts and owns the competency of all things associated with Improvement of the organiaztion. So I would expand this into knowing things in the basic BB BOK, plus Quality, CMMI, Organizational Leadership, Change Managment, Metrics, and Customer Satisfaction.

    I’ve seen MBB’s who were “math guys” in various organizations, and all they can really do is teach. The real world application for a lot of these “tools” are very few and far between since most improvements are either bottom line driven or forward thinking organizational changes. When these math experts are given real world projects, they often have trouble presenting executive level results because they want to impress people with their analysis.

    Good MBBs need to be good closers and can bring projects to completion, and more importantly, mentor others to do so. The tools listed above only gets people through a DMA project, as opposed to DMAIC.

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  6. Chris Seider

    @Billy Jack. Your last paragraph is perfect.

    No one’s mentioned yet that MBB’s should be good at finding projects with their leadership.

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  7. Peter To

    Among the technical knowledge of a successful MBB, I truly feel that Monte Carlo Simulations should be included as it is so powerful and widely applicable in many functions.

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  8. Simon Bodie

    All valid points
    To me the most important point is that a MBB be a proven master strategist and co-architect of real measurable business transformation.
    Only the actual tangible business results seperate the wheat form the chaff and no amount of technical skill can compensate for this

    I think it was Einstein who said
    Imagination is more important than knowledge (information can be found in books)

    The MBB qualification is almost meaningless without the results.
    Simon

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