Data & Process Excellence Experience
– ESSC Module Training –
Objectives and Structure of the ESSC Module Training Courses
The ESSC training modules offer a comprehensive professional development opportunity for specialists and managers in the fields of data analysis, statistics, and operational excellence. The modules are designed to teach practical methods that can be immediately applied in the workplace. Participants not only learn theoretical concepts but also how to apply them in practice, enabling them to serve as internal points of contact and experts within their organizations.
The program is designed for Black Belts, Master Black Belts, data analysts, quality managers, and executives who want to optimize data-driven decision-making processes and deepen their methodological expertise.
Each module was developed with the goal of providing participants with in-depth knowledge and the ability to confidently apply the methods taught. In addition to simply imparting knowledge, the program focuses on interpreting results and independently using statistical and analytical tools.
Module Structure
The training program consists of eight standalone modules that can be booked individually. The modules include both theoretical content and practical exercises, case studies, and interactive group work to ensure a lasting understanding.
The modules will initially be offered as online training sessions via Zoom to allow for flexible participation. Depending on demand, in-person training sessions or hybrid formats can also be organized.
Modules
1️⃣ Fundamentals of Statistics & Data Analysis (Refresher & In-Depth)
2️⃣ Experimental Planning & Design of Experiments (DoE)
3️⃣ Statistical Modeling & Machine Learning
4️⃣ Advanced Statistics for Master Black Belts
5️⃣ Lifespan & Reliability Analysis
6️⃣ Soft Skills for Six Sigma Projects
7️⃣ Rollouts & Implementation
8️⃣ Methods of Operational Excellence
Who is this training intended for?
- Data analysts and quality managers who want to advance their careers.
- Black Belts and Master Black Belts who want to deepen their methodological expertise.
- Executives and those interested in OPEX who want to implement innovative approaches.
- Trainers and coaches who want to expand their training skills.
- Rising Star
ESSC Master Black Belt Certification
With the Data & Process Excellence Experience, the ESSC offers a structured opportunity for professional development to anyone who wishes to advance their methodological skills and pursue ESSC MBB certification.
- Each module is worth 2 points.
- A total of 8 points are required for ESSC-MBB certification, which can be earned through modules of the student’s choice or eligible qualifications.
- The modules are based on the ESSC’s official training guidelines.
- You can find the requirements for successful certification in the “Guidelines for Six Sigma Master Belt Certification.”
- A table is available for self-assessment of your qualifications, which can be downloaded. It helps you identify your strengths and areas for development (LINK to our training guidelines).
Credit for Existing Qualifications
Existing qualifications may be credited in consultation with the ESSC Senior Master Black Belt (SMBB). The 8 points required for MBB certification can, of course, also be earned through a combination of modules and documented experience.
If you are interested in certification, please contact us to discuss your individual needs with a Senior Master Black Belt (SMBB) and to receive information about possible fees.
A brief overview of all modules and their contents
Discover the modules of the Data Excellence Experience
Here, we present a selection of professional development modules developed as part of the Data Excellence Experience.
This program is backed by an experienced team of trainers and the European Six Sigma Club Deutschland e.V.—ensuring in-depth knowledge, practical content, and the ability to implement solutions effectively over the long term.
Look forward to concise insights, tangible benefits, and new perspectives for your data-driven processes!
Module 1: Statistics & Data Analysis in Practice
(Refresher & In-Depth Training for Quality and Process Experts)
In this module, you’ll refresh your knowledge of statistics in a targeted manner and apply it directly to your day-to-day work—from process capability and measurement system analysis to hypothesis testing and regression. The focus is on practical examples from manufacturing and the service industry, best practices, standards and guidelines, as well as very specific tips for your role as an internal point of contact for data-driven decisions.
Key topics of this module:
➡ Fundamentals of Statistics for Process Analysis & Quality Control – Practical Approach.
➡ Exploratory data analysis and visualization.
➡ Hypothesis tests such as the t-test and ANOVA, using real-world examples with interpretations.
➡ Simple and multiple regression in practice.
➡ Handling non-normally distributed data.
➡ Measurement System Analysis (MSA) and Test Process Capability.
➡ In-depth study of SPC tools, process capability analyses, and tolerance intervals.
We’ll be working live with Minitab; we’ll also show selected steps in KNIME, if desired. If you prefer to work with R, Python, JMP, or other statistical software packages, you’re of course welcome to use them—what matters most is understanding the methods and discussing the results together.
Coach: Björn Noreik
Dates (ONLINE)
Date for 2026:
- January 28, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- January 29, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
- January 30, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 2: Experimental Planning & Design of Experiments (DoE)
Participants will develop a solid understanding of how to design, conduct, and evaluate experimental designs. They will be able to identify common pitfalls, optimize experiments, and effectively support teams in their practical implementation.
Key topics of this module:
➡ Fundamentals of full- and fractional-factorial designs—design, analysis, and interpretation (refresher).
➡ Understanding and working with alias structures to correctly interpret interactions.
➡ Experimental design with discrimination analysis to effectively manage effort.
➡ Targeted use of center points to test for nonlinearities and reproducibility.
➡ Factorial designs and advanced DoE methods such as RSM, D-optimal, or definitive screening designs.
➡ Handling and optimizing variation, as well as special designs for factors that are difficult to vary
➡ Strategies for failed experiments and incomplete data—robust planning and flexible adaptation.
Coach: Bert Leyendecker
Dates (ONLINE)
Date for 2026:
- October 8, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- October 9, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 3: Statistical Modeling & Machine Learning
Participants will gain in-depth knowledge of modern data modeling, be able to effectively integrate ML techniques into their work, and confidently support data-driven decisions for process improvements.
Key topics of this module:
Multivariate methods and classical regression models (refresher) to review the fundamentals of statistics. Introduction to Data Orchestration and Machine Learning – Understanding Supervised and Unsupervised Learning. Model development using Python, including data preparation, feature engineering, and validation. Classification and regression methods such as decision trees, Naive Bayes, or neural networks. Differences between traditional and machine learning-based models, including their applications and limitations. Practical application of ML methods for process optimization, including visualization and interpretation. Confident use of model quality, cross-validation, and model comparison to support informed decisions.
Coach: Maik Kschicho
Dates (ONLINE)
Date for 2026:
- May 4, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- May 5, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
- May 6, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 4: Advanced Statistics for Master Black Belts
Participants will significantly expand their statistical expertise and learn to analytically solve even complex problems in real-world contexts. They will gain confidence in selecting, applying, and interpreting advanced statistical methods and will be able to communicate these methods in a way that is appropriate for their target audience.
Key topics of this module:
➡ In-depth study of specific regression methods, such as binary and Poisson regression, for analyzing countable and dichotomous data.
➡ Discriminant analysis and clustering methods to identify differences between groups and reveal underlying structures.
➡ Principal component analysis and dendrograms for dimension reduction and exploratory analysis.
➡ Multivariate quality control charts for monitoring multidimensional process variables.
➡ Nonparametric tests and their use when classical assumptions are violated.
➡ Time series analysis using ARIMA models; reliably identify trend and seasonal effects.
➡ The concept of simulation techniques such as Monte Carlo and discrete models for making robust decisions in the face of uncertainty.
Coach: Daniel Fügner
Dates (ONLINE)
Date for 2026:
- September 21, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
- September 22, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
- September 23, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
- September 24, 2026 – 8:00 a.m. to 12:30 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 5: Service Life and Reliability Analysis
Participants will learn modern methods for evaluating and ensuring product reliability. They will be able to analyze service life data in a targeted manner, plan tests efficiently, and serve as in-house experts on service life and reliability issues.
Key topics of this module:
Test Strategies for Predicting Service Life—from EOL Tests to HASS, HALT, and Success Run. Analysis of failure distributions and selection of appropriate statistical models (e.g., Weibull, log-normal). Handling censored and uncensored data, including data analysis when only partial information is available. Calculation of typical reliability metrics such as MTTF, MTBF, B10, or lambda. Planning and evaluation of accelerated life-cycle tests, including the Arrhenius and Coffin-Manson models. Use of regression techniques with survival data, such as Cox models.Practical application of warranty analyses and interpretation of operational field data.
Instructor: Barbara Bredner
Dates (ONLINE)
Date for 2026:
- February 4, 2026 – 9:00 a.m. to 1:00 p.m. (CET)
- February 11, 2026 – 9:00 a.m. to 1:00 p.m. (CET)
- February 18, 2026 – 9:00 a.m. to 1:00 p.m. (CET)
- February 25, 2026 – 9:00 a.m. to 1:00 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 6: Soft Skills for Six Sigma Projects
Participants will strengthen their communication and facilitation skills and gain confidence in handling complex group situations. They will not only be able to apply Six Sigma tools methodically and confidently, but also competently lead and support project teams.
Key topics of this module:
Target audience analysis and definition of learning objectives to convey content in a clear and effective manner. Creating compelling presentations that are professional in both content and visual presentation. Communication techniques for conflict management to identify and defuse tensions early on. Confident handling of difficult participants, e.g., in workshops or project meetings. Provide feedback and use coaching methods to promote development and boost motivation. Time and resource management in projects to ensure that goals are achieved realistically and efficiently. Change Management & Dealing with Resistance to Successfully Facilitate Change Processes.
Coach: Ole Fischer
Dates (ONLINE)
Date for 2026:
- April 23, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- April 24, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 7: Rollouts & Implementation
Participants learn how to efficiently plan, roll out, and embed improvement projects under real-world conditions. They strengthen their ability to manage change processes and can act strategically as advocates for excellence methods.
Key topics of this module:
Implementation of Lean principles, including shop floor management, types of waste, and standardization. Effectively design change processes, taking group dynamics and resistance into account. Build and prioritize project portfolios, including the selection of appropriate projects and success criteria. Combine agile methods, such as SCRUM, Kanban, and traditional Six Sigma approaches, in a way that makes sense. Successfully launch the DFSS rollout, fostering enthusiasm within the team and managing critical mass. Integration of Lean Six Sigma into service and production areas, with a focus on real-world examples. Time-to-market strategies and lessons learned to embed methodologies sustainably within the company.
Coach: Michael Ohler
Dates (ONLINE)
Date for 2026:
- September 11, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- October 16, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
Module 8: Methods of Operational Excellence
In this module, participants gain a broad overview of the history of operational excellence and project management methods and philosophies. Insights into organizational and systems theory—including topics such as modern leadership and industrial psychology—shed light on the essential framework for successful collaboration. Cutting-edge topics such as Design Thinking and flat-structured organizations round out the picture and prepare participants for a self-organized, agile future.
Key topics of this module:
Project Management Methodologies: From Traditional (Waterfall) to Agile Methods (Scrum / Kanban) “Theoretical & Consulting” OpEx Concepts – Juran Model, “CIMS” (C. Cormier), “OpEx Consultants” CI System Design Thinking – an alternative, human-centered approach to creative problem-solving and product development Organizations as Socio-Technical Systems: Fundamentals of Organizational and Systems Theory Positive Psychology & New Leadership – Factors for Successful Work in Organizations Progressive Organizational Structures: From Authoritarian Hierarchy to Autonomous Teams and Non-Hierarchical Organizations (Teal)
Coach: Achim Schmidt
Dates (ONLINE)
Date for 2026:
- March 2, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
- March 3, 2026 – 8:00 a.m. to 5:00 p.m. (CET)
Do you have any questions, or would you like to participate?
We look forward to hearing from you.
