---
_id: '66709'
abstract:
- lang: eng
  text: In increasingly volatile and uncertain markets, corporate resilience has become
    a critical capability in strategic product planning. Companies face significant
    challenges in systematically monitoring and interpreting heterogeneous environmental
    data originating from diverse sources, formats, and temporal contexts. While predefined
    workflows and decision trees can support strategic analysis, they often lack the
    flexibility required to cope with dynamic market conditions and foresightrelated
    data from extreme dispersed and heterogeneous sources. This paper proposes a method
    to enhance corporate resilience through the application of generic, reusable AI-based
    workflows in strategic product planning. The approach integrates Data Science
    and Artificial Intelligence methods into modular, visually modelled workflows
    that enable hybrid human-AI decision-making. Based on a systematic literature
    review and an analysis of industrial challenges, key success factors and resilience
    criteria are identified. These insights are used to develop a method that supports
    internal and external analyses, scenario-based strategy development, and adaptive
    implementation monitoring within a generic workflow structure. The method leverages
    techniques such as machine learning and generative AI to process structured and
    unstructured data, identify patterns, and support real-time strategic assessments.
    Validation with decision-makers from medium-sized companies demonstrates improved
    transparency, repeatability, and cross-functional collaboration compared to predefined
    workflows.
author:
- first_name: Deniz
  full_name: Özcan, Deniz
  id: '58595'
  last_name: Özcan
- first_name: Iris
  full_name: Gräßler, Iris
  id: '47565'
  last_name: Gräßler
  orcid: 0000-0001-5765-971X
citation:
  ama: 'Özcan D, Gräßler I. Corporate resilience through generic AI-based workflows
    in strategic product planning. In: Graessler I, ed. <i>1st International Symposium:
    March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>. Universitätsbibliothek;
    2026. doi:<a href="https://doi.org/10.17619/UNIPB/1-2636">10.17619/UNIPB/1-2636</a>'
  apa: 'Özcan, D., &#38; Gräßler, I. (2026). Corporate resilience through generic
    AI-based workflows in strategic product planning. In I. Graessler (Ed.), <i>1st
    International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn
    University</i>. Universitätsbibliothek. <a href="https://doi.org/10.17619/UNIPB/1-2636">https://doi.org/10.17619/UNIPB/1-2636</a>'
  bibtex: '@inproceedings{Özcan_Gräßler_2026, title={Corporate resilience through
    generic AI-based workflows in strategic product planning}, DOI={<a href="https://doi.org/10.17619/UNIPB/1-2636">10.17619/UNIPB/1-2636</a>},
    booktitle={1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute,
    Paderborn University}, publisher={Universitätsbibliothek}, author={Özcan, Deniz
    and Gräßler, Iris}, editor={Graessler, Iris}, year={2026} }'
  chicago: 'Özcan, Deniz, and Iris Gräßler. “Corporate Resilience through Generic
    AI-Based Workflows in Strategic Product Planning.” In <i>1st International Symposium:
    March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited
    by Iris Graessler. Universitätsbibliothek, 2026. <a href="https://doi.org/10.17619/UNIPB/1-2636">https://doi.org/10.17619/UNIPB/1-2636</a>.'
  ieee: 'D. Özcan and I. Gräßler, “Corporate resilience through generic AI-based workflows
    in strategic product planning,” in <i>1st International Symposium: March 24 –
    26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, Paderborn, 2026,
    doi: <a href="https://doi.org/10.17619/UNIPB/1-2636">10.17619/UNIPB/1-2636</a>.'
  mla: 'Özcan, Deniz, and Iris Gräßler. “Corporate Resilience through Generic AI-Based
    Workflows in Strategic Product Planning.” <i>1st International Symposium: March
    24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited by Iris
    Graessler, Universitätsbibliothek, 2026, doi:<a href="https://doi.org/10.17619/UNIPB/1-2636">10.17619/UNIPB/1-2636</a>.'
  short: 'D. Özcan, I. Gräßler, in: I. Graessler (Ed.), 1st International Symposium:
    March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University, Universitätsbibliothek,
    2026.'
conference:
  end_date: 2026-03-26
  location: Paderborn
  name: International Symposium on Hybrid Intelligence in Product and Production Engineering
    1. 2026 Paderborn
  start_date: 2026-03-24
date_created: 2026-08-13T13:08:25Z
date_updated: 2026-08-13T13:12:01Z
department:
- _id: '43'
- _id: '9'
- _id: '26'
- _id: '152'
doi: 10.17619/UNIPB/1-2636
editor:
- first_name: Iris
  full_name: Graessler, Iris
  last_name: Graessler
language:
- iso: eng
publication: '1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute,
  Paderborn University'
publisher: Universitätsbibliothek
quality_controlled: '1'
status: public
title: Corporate resilience through generic AI-based workflows in strategic product
  planning
type: conference
user_id: '58595'
year: '2026'
...