Towards value driven construction : Designing Product Service Systems offerings aroundsite level data

Background: The construction industry is under increasing pressure to improve productivity, minimize downtime, and optimize resource utilization. Product-Service Systems (PSS) promise to deliver these benefits by coupling physical equipment with value-adding services. Site-level data—real-time and historical metrics from machinery—lie at the heart of PSS, yet many firms struggle to convert raw telemetry into services that frontline users actually value and adopt. Objectives:This thesis examines which types of site-level data construction professionals perceive as most valuable and how those data can inform the design of PSS offerings. By focusing on the perspectives of operators, planners, mechanics, and dealer representatives, it addresses a gap in understanding how machine-generated insights translate into actionable, user-aligned services. Methods: A qualitative approach combined a structured literature review of PSS, Data-Driven Decision-Making, and Data-Driven Innovation with ten semi-structured interviews. Participants were drawn from small, medium, and large construction firms in Sweden and represented diverse roles in equipment operation and service. Interview transcripts were analyzed using Braun and Clarke’s thematic analysis to surface key data preferences, barriers, and service expectations. Results: Frontline users rated real-time metrics—fuel consumption, idle time, machine utilization, and fault alerts—as essential for immediate adjustment and preventive maintenance. Aggregated weekly and monthly trend reports were prized by planners for strategic scheduling and budgeting. Major obstacles included intermittent connectivity, siloed platforms, information overload, and non-contextual alerts. Desired service features converged on predictive-maintenance notifications, behavior-focused feedback loops, concise prioritized alerts, and customizable dashboards. Dealers emerged as indispensable intermediaries, translating analytics into context-sensitive guidance and fostering trust. Conclusions: Effective PSS in construction demands a socio-technical approach that pairs reliable infrastructure and streamlined analytics with human-centered design and relational support. Services must distill complex data into clear, role-specific recommendations, enable user customization, and be backed by on-site training and mediation by trusted advisors. These insights offer a roadmap for equipment providers to evolve from break-fix vendors into proactive partners, delivering outcome-driven services that enhance efficiency, reliability, and customer loyalty. Keywords: Product-Service Systems, site-level data, construction industry, data-driven service design, user-centered innovation.