@inproceedings{67284,
  abstract     = {{<jats:p>For foresightful strategic decisions in engineering and production, it is important to identify and classify operational engineering data inmanufacturing companies in terms of relevance and impact. Established methods like Scenario-Technique or roadmapping consider expertise of strategic decision-makers and central decision-making bodies by, for instance, workshops and interviews. There is no overarching approach for evaluating the variety of operational data sources and feed them into specific data processing pipelines targeting strategic decision support. Based on a systematic literature analysis and comprehensive industrial experience, requirements are derived. These requirements are used to develop a method to identify, classify and evaluate data for strategic decision-making. The method is validated in an industrial project. The aim is to exploit informal and fragmented data from operational levels into structured, transparent decision support for strategic players.</jats:p>}},
  author       = {{Gräßler, Iris and Özcan, Deniz}},
  booktitle    = {{AHFE International}},
  issn         = {{2771-0718}},
  location     = {{Paris}},
  publisher    = {{AHFE International}},
  title        = {{{Extended Exploitation of Data in Manufacturing Companies for Strategic Decision-Making}}},
  doi          = {{10.54941/ahfe1008175}},
  volume       = {{237}},
  year         = {{2026}},
}