Lean Six Sigma meets data science: Integrating two approaches based on three case studies
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| Publication date | 07-2018 |
| Journal | Quality Engineering |
| Volume | Issue number | 30 | 3 |
| Pages (from-to) | 419-431 |
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| Abstract |
The amount of available data is rapidly increasing, which is an opportunity to the Lean Six Sigma (LSS) methodology. Starting off with a well-established definition of LSS as theoretical foundations we employ theory-generating case-study research. Three successful improvement projects from a large financial services firm in the Netherlands are analyzed. Clear differences to the definition of LSS are observed. The research leads to three recommendations for integrating data science in LSS. Concerning the structure of an improvement organization, skills of employees and, practical modifications to LSS's celebrated DMAIC roadmap to solidify its applicability in the modern age of data.
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| Document type | Article |
| Language | English |
| Published at | https://doi.org/10.1080/08982112.2018.1434892 |
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