Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
Beyond Coordination: A Multi-Criteria DSM Clustering Approach Tested on AI Center of Excellence Design in Pharmaceutical Medical Affairs
Solberg, Runar (1); Soldal, Kim (2); Yassine, Ali (1,3); Worren, Nicolay (1,2); Christiansen, Tore (2)
Type:
Year:
2026
Editor:
Langner, Christopher; Kreimeyer, Matthias; Panarotto, Massimo; Cascini, Gaetano; Browning, Tyson R.; Eppinger, Steven D.; Yassine, Ali A.
Author:
Solberg, Runar (1); Soldal, Kim (2); Yassine, Ali (1,3); Worren, Nicolay (1,2); Christiansen, Tore (2)
Series:
DSM
Institution:
1: Norwegian University of Life Scienes School of Economics and Business;
2: Reconfig AS;
3: Stevens Institute of Technology
Page(s):
031-040
DOI number:
ISBN:
NA
ISSN:
NA
Abstract:
Design Structure Matrix (DSM)-based organizational design tools typically optimize groupings using a single criterion: coordination cost. In practice, however, organizational design requires balancing multiple criteria, particularly when emerging artificial intelligence (AI) capabilities create opportunities for resource consolidation that are not captured by interaction patterns alone. In this paper, we map a people DSM with a task DSM through activity overlap scoring, using resource consolidation as an additional clustering criterion. We introduce a consolidation overreach penalty in the fitness function. Rather than single run optimization, we propose a structured problem-solving approach combining algorithmic output with stakeholder input. The approach is tested on a 159-person pharmaceutical Medical Affairs organization facing a concrete design question: whether to consolidate AI-augmentable work, fragmented across five functions, into a shared AI Center of Excellence. The results show a new and distinct clustering, reflecting both coordination and resource consolidation criteria.
Keywords:
