Consulting typically begins with a thorough analysis of current business processes to identify weaknesses and areas with improvement potential. Clear goals for the Six Sigma project are established based on these insights.

A crucial component of Six Sigma is training employees in various methods and tools. Consulting firms offer training ranging from yellow and green belts to black belts, depending on the company's needs.

Consultants can assist in planning and executing Six Sigma projects, including defining project objectives, allocating resources, creating schedules, and monitoring progress.

Central to Six Sigma is the use of data to understand problems and develop solutions. Consultants help identify relevant data sources, collect data, and apply statistical analysis techniques.

Based on the results of data analysis, consultants develop recommendations for process optimization and improvement. This may involve restructuring workflows, introducing new technologies, or implementing best practices.

Introducing Six Sigma may require changes in corporate culture. Consultants assist in developing change management strategies to ensure that employees accept and support the new approach..

Six Sigma is not a one-time initiative but a continuous improvement process. Consultants help companies implement mechanisms to sustain improvements achieved and continue the process of continuous improvement.

Consultants assist in creating reports and dashboards to track the progress of Six Sigma projects and quantify their business benefits. This allows companies to assess the ROI of their investments in Six Sigma.

The design of studies or experiments requires careful planning and consideration of various factors to obtain meaningful and reliable results. Here are some important steps and considerations to help design studies or experiments:

Data cleaning, transformation, and preparation are critical steps to ensure data is suitable for analysis and produces accurate and reliable results. The quality of your data has a significant impact on the results of your analysis. Therefore, it is important to invest time and care in data cleaning, transformation and preparation to ensure that your data is suitable for the desired analysis.

Selecting the appropriate statistical analyzes depends on your specific objective, data structure, and hypotheses. Here are some common statistical analyzes and in which situations they are typically applied. Choosing the right statistical analysis depends on the specific characteristics of your data and your project goals. We use statistical software or programming languages such as Minitab, R, Matlab, Mode Frontier, Phython and also Excel to perform these analyzes as they provide tools and functions to perform a variety of statistical tests and interpret the results.

Interpreting the results of statistical analyzes is crucial to finding out whether your Y (effect or effect KPOV's) or hypotheses have been confirmed or refuted. Interpreting statistical results often requires clear communication and the ability to convert complex statistical concepts into understandable statements. It may be helpful to discuss the results with colleagues or experts to ensure that your interpretations are appropriate and factual.

Choosing the right statistical software or tools depends on the specific requirements. We use the most popular and well-known statistical software packages and tools commonly used for statistical analysis,

Creating charts, graphs, and visualizations is crucial to presenting data and results in an understandable and compelling way. Here are some recommendations and steps to help create such visual representations.

Conducting additional analyzes to identify specific differences between groups after a significant overall effect has been identified is an important step in gaining deeper insights into your data. This is often called post hoc analysis and is typically done after a significant ANOVA (analysis of variance) to determine which groups are significantly different from each other. Here are some commonly used techniques for post hoc analysis:

Producing reports or scholarly articles that include your research questions, methods, results, and conclusions requires care and structure. Creating a scientific report or article takes time and commitment, but it is an essential step. We ensure your report is well researched, clearly written and designed according to scientific standards to have the greatest impact. Here are some steps and recommendations to help you with this process:

Assessing the validity and robustness of the chosen statistical methods and adapting them to the specific data are crucial steps to ensure that your analysis produces reliable results.

Organizing training or workshops to improve student or staff statistical understanding is a valuable initiative to promote data literacy and skills within your organization. Organizing training or workshops to improve statistical understanding develops your employees' data literacy and helps promote more informed decisions and scientific research. It is important to regularly review and adapt training to ensure it meets current needs and developments in your area of expertise.

Long-term advice and support for recurring statistical requirements in projects or research work can help improve the quality and effectiveness of your data analyses. Providing long-term advice and support on statistical matters can help improve the quality and reliability of your projects. It also enables effective use of statistical insights to make informed decisions and generate scientific knowledge.