We help industrial companies and business teams improve processes measurably. Reliable data is combined with statistics, Lean Six Sigma, Design for Six Sigma, Data Literacy, Data Mining and Process Mining – and translated into practical, sustainable improvement
Our approach connects data competence, rigorous analysis and consistent implementation. This creates one continuous value chain from the data foundation to sustainable process improvement.
Effective process improvement starts with a reliable data foundation. We create transparency around data quality, KPIs and process conditions so teams can work with facts rather than assumptions.
Statistics, Six Sigma and Design of Experiments help separate symptoms from real causes. Raw data becomes dependable process knowledge that supports better technical and business decisions.
Insight only creates value when it reaches the process. We translate analysis into robust actions, clear management systems and sustainable gains in quality, efficiency and business performance.
Our capabilities are designed to work together. Depending on the challenge, we combine the methods needed for the data foundation, analysis and practical implementation
Teams learn to assess data quality, KPIs and visualizations confidently and use data as a sound basis for business decisions
We combine Lean principles with DMAIC and data-based root cause analysis to reduce waste and improve process performance sustainably
Structured DMAIC improvement projects with reliable KPIs and statistical methods for quality, performance and process capability
Develop robust products and processes from the start using clear customer requirements, systematic design and statistical validation
Management Control & Reporting Systems make relevant KPIs visible and create a dependable basis for steering and management reviews
From hypothesis testing and regression to multivariate analysis, we turn complex data into practical answers to process questions
We connect processes, data and organization, assess digital maturity and develop practical roadmaps instead of isolated technology projects
Data mining and machine learning reveal patterns, segments and predictive opportunities in complex process and business data
Stemann Consulting combines deep methodological expertise with practical experience in manufacturing, quality, development and data-driven improvement projects. We do not apply as many tools as possible; we use the right ones for the actual challenge
Explore our consulting approach
The Data Mining training follows the CRISP-DM process from data preparation to clustering, classification and prediction. Participants learn how to assess models and translate analytical results into practical decisions
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The Process Mining training covers event logs, process discovery, conformance checking and performance analysis. It makes real process variants, waiting times and bottlenecks visible and actionable
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The Six Sigma Green Belt training combines DMAIC, statistics and project coaching. Participants work on a real improvement project and learn how to validate root causes, implement solutions and sustain measurable results
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