@inproceedings{Lujan2026_2559,
  author = {Lujan, Guillermo Prado and Engineer-Manriquez, Felipe},
  editor = {Hamzeh, Farook and Poshdar, Mani and Garcia-Lopez,, Nelly P. and Gan, Vincent},
  title = {Integrating SCRUM with the last planner system: an AI-enhanced framework},
  booktitle = {Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)},
  year = {2026},
  pages = {1725--1736},
  address = {Singapore, Singapore},
  issn = {2789-0015},
  doi = {10.24928/2026/0271},
  url = {https://www.iglc.net/papers/details/2559},
  abstract = {While both the Last Planner System (LPS) and SCRUM have demonstrated benefits independently, existing research lacks a practitioner-grounded framework that integrates these approaches across planning horizons. Grounded in a shared epistemological foundation of empiricism (where planning is continuously adjusted through feedback and learning) this study adopts an inductive, case-based approach to develop an initial framework outline. This research consists of a comparative analysis of LPS and SCRUM across six key dimensions, the synthesis of an integrated framework with AI as an augmentation layer, and an illustrative case study of a complex construction project. Results indicate that LPS provides stability through multi-horizon planning and commitment management, while SCRUM enhances short-cycle coordination, learning, and role clarity. AI further supports these processes by improving information synthesis, visibility, and anticipatory decision-making, while maintaining a human-in-the-loop approach. This study contributes a structured, practitioner-informed starting point for integrating Lean, Agile, and AI in construction, highlighting the need for further validation and development through future research.},
  keywords = {Last Planner System, SCRUM, Lean Construction, Integration, Artificial Intelligence},
}