S.P.O.T. Scenario Planning Optimisation Tool
A Tool for Comparing Individually Optimised Construction Scenarios Based on Cost Minimisation
J. Copinga (TU Delft - Civil Engineering & Geosciences)
Martijn Leijten – Mentor (TU Delft - Organisation & Governance)
T.R. van Woudenberg – Graduation committee member (TU Delft - Applied Mechanics)
Hans Ramler – Graduation committee member (TU Delft - Integral Design & Management)
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Abstract
Construction planning often involves comparing multiple execution scenarios to identify the most effective approach. In practice, this process relies heavily on the planner’s experience and intuition, making decisions difficult to substantiate. This study addresses the question: “How can construction planning scenarios of high-rise apartment buildings (<70m) be effectively compared to support data-driven decision-making in the Netherlands?” Using the Design Science Research method, the study investigates the challenges planners face and explores how construction scenarios can be evaluated more systematically. The aim is to develop a framework and design a tool that supports holistic, effective, and data-driven comparisons of construction scenarios.
Through a literature review and 13 practitioner interviews, six key factors were identified as essential for scenario comparison. These include cost, time, resources, risk, sustainability, and cash flow. These factors and their methods of incorporation were included in the framework. A decision-support tool was designed to operationalise the framework. It largely automates the comparison process, incorporates familiar visualisations, and allows planners to input project-specific scenarios. To improve comparability, the tool applies two optimisations: crane allocation (resource-based) and float-based task shifting (technique-based). Each scenario is evaluated under near-optimal conditions using a full, or rule-based, exhaustive search, reducing inefficiencies and focusing comparisons on strategic differences. Validation showed the tool aligned with planners’ working methods and mostly improved the speed and quality of scenario analysis.
The research demonstrates that the developed framework and tool improve scenario comparison by supporting quick, transparent, well-substantiated decisions. Optimisation ensures fair comparisons, and the use of familiar visuals improves usability and communication. Further development and real-world application are recommended to refine the tool and increase adoption. Future research is based on the limitations and could extend the approach to other project types, phases, or stakeholders.