The dynamic nature of governance structures for large investments: measurement and modeling, organizational fit, and lifecycle value

This article introduces a framework for governance of large industrial investments that dynamically connects organizational management to the investment’s physical state of operation (current or predicted). An important component of the framework captures the relation of individual industrial investments to the larger systems in which they operate. Our case studies are bridge infrastructure investments, which are part of roadway networks, and container ships, which are part of the container shipping industry. Through ongoing sensing, measurement, analysis, and managerial intervention, the framework recognizes the dynamic nature of the physical investment (i.e., the bridge or the container ship) over time, and enables system governance to adapt and fit to changing real-world conditions. Evolution of system governance in response to changes in investment conditions allows for continuous improvement of financial performance and for a larger overall value proposition. We also show that sensing and modeling technologies can increase the adaptability and flexibility of network governance and leadership throughout the various phases of an investment's lifecycle.Our framework uses a value-based approach to assess the measurement needs of an investment to determine four different value propositions: social, environmental, economic and functional. Social value describes communal benefits (i.e., a bridge’s benefit to a community). Environmental value reflects the environmental impact at both the industry- and investmentlevel. Our case studies use the Net Present Value (NPV) curve to illustrate economic impacts over the investment’s lifecycle. The functional value of an investment reflects total output from the social, environmental, and economic value. Our case studies present the multitude of actors and processes that impact the value of industrial investments over their lifecycle. These actors are essential to consider when predicting physical performance and system requirements, and adapting governance to fit changing conditions.