Monte-Carlo value analysis of High-Throughput Satellites: Value levers, tradeoffs, and implications for operators and investors

High-Throughput Satellites (HTS) are a distinctive class of communication satellites that provide significantly more throughput per allocated bandwidth than traditional wide-beam communication satellites. They are the proverbial wave of creative disruption in the space industry and are poised to disrupt the communication market in significant ways. The objective of this work is to develop a decision-analytic framework for assessing the value of High-Throughput Satellites and to provide meaningful results of the value of such systems under realistic design, operational, and market conditions. We develop the cost and revenue models of HTS. To build the revenue model, we develop a hybrid data-driven and scenario-based load factor model that combines historical data based on financial records from current HTS operators with extrapolations based on best-, nominal-, and worst-case scenarios. We then integrate the cost and revenue models within a stochastic simulation environment and perform Monte-Carlo analysis of the net present value (NPV) of HTS. One important result is that a medium-sized HTS significantly outperforms a roughly equivalent traditional wide-beam satellite, even under the worst-case loading scenario. Another important result, here identified and quantified, is the tradeoff between the average revenue per user (ARPU) and average loading of the satellite and how it is mediated by the downlink speed provided to consumers. This result can be used in different ways, for example, by helping define the boundaries of what is competitively achievable in terms of ARPU and downlink speed offerings. The implications of these results are that they delineate the pathways to financial failure and the boundaries beyond which an HTS will be value-negative, or alternatively, the asymptotic minimum values for an HTS to be value-positive.