The key metric for satellite operators has traditionally been fill rates. Fill rates are an accurate measure of success for widebeam FSS satellites in which video is the major application as video is constantly beamed and hence fill rates equate to utilization.  An added benefit is that contracts are long term leading to relatively stable transponder prices.

However, HTS systems focus on serving data traffic, and broadband demand is concentrated in peak hours, making fill rates a poor metric for capacity utilization. Furthermore, the large amount of new capacity being launched creates pricing instabilities. All in all, fill rates are a poor predictor of success for an HTS system. If fill rates are no longer applicable, then the question is: how do satellite operators measure the success of an HTS system?

One could say that 2016 will be the year in which HTS goes mainstream. Intelsat will launch EpicNG, and all big 4 will have HTS capacity (each with completely different approaches), Inmarsat started the year launching commercial services on its GX constellation, and regional players are accepting this new technology either with entire HTS satellites or hybrid payloads. Most of the data traffic boom forecasted for the coming years will be captured by HTS systems. According to NSR’s VSAT and Broadband Satellite Markets, 14^th Edition Report, in 2014 HTS systems already accounted for 54% of data traffic for fixed broadband services, but this contribution will grow to reach an astonishing 96% in 2024 illustrating why an HTS play is essential for satellite operators to stay relevant in data verticals.

HTS needs to be part of the strategy for any satellite operator targeting data applications. But these investments should not be guided by legacy performance indicators like fill rates. Focusing too much on maximizing fill rates would lead to wrong strategic directions (for example) by exclusively targeting low-value high-volume applications like consumer broadband causing congested beams at peak hours with poor quality of service while missing the high-value opportunities in verticals like mobility or wireless backhaul. It is time for a new set of metrics adapted to the new business models growing around HTS ecosystems that puts satellite operators on the right track for growth and profitability. 

KPIs for Capacity Utilization

Data applications present great variance between peak and valley capacity consumption. This makes fill rates difficult to define and of low relevance for measuring capacity utilization. Similar to congestion in transportation during rush hour, when demand outweighs capacity, consumer broadband demand becomes concentrated during evening hours. This was a common issue for several operators in 2015. For instance, Eutelsat’s KA-SAT reached saturation at peak hours in its most popular beams but continued to add enterprise customers and academic institutions. Similarly, ViaSat also suffered from beam congestion but continued to attract more air mobility services.

Luckily, different verticals have different usage patterns. To add even a further layer of complexity, geographical distribution of users must also be considered with different beams presenting wide differences in the number of subs or with mobility customers following changing routes like the reversing westbound and eastbound flows in the North Atlantic Air Corridor.

To maintain service quality and accommodate room for growth, satellite operators need to plan capacity to meet peak rates, rather than average rates. However, this presents some key challenges. As outlined in NSR’s VSAT and Broadband Satellite Markets, 14^th Edition Report, close to 90% of the data traffic for satellite broadband markets will be originated by consumer broadband. Because of the dominance of one vertical over others, the gap between peak and average traffic is growing. Additionally, consumer broadband consumption composition is also changing, accelerating the consumption of video further increasing this peak-to-average ratio. To put this in context, global IP busy-hour traffic will grow at a CAGR of 31% compared with 26% for average traffic, according to Cisco’s Visual Networking Index 2015.

Source: Cisco Visual Networking Index

Satellite operators need to create new measures for operational efficiencies. An operator that is able to combine different applications to reach a balanced “peak usage” vs. “average usage” would mean that it is best using the capacities of its system. However, it also must be noted that “peak usage” must maintain some margin over “peak capacity” to ensure service quality and room for growth. With satellite operators’ increased visibility over client’s usage patterns through Managed Services, attracting a balanced customer base should become an objective for these new systems. Given the growing peak-to-average ratio in capacity consumption, one can understand the high interest of satellite operators in flexible satellites than can shape the beams to follow the capacity demand usage patterns.

From Measuring Volume to Revenue Generation

Every data vertical has very different pricing and revenue generation dynamics. It would be difficult to have an accurate picture of performance by only looking at operational efficiencies when comparing verticals with such different revenue trends as consumer broadband (high-volume, low-margin) with backhaul, trunking or mobility (low-volume, high-margin). Measuring only volume (fill rates) can’t predict if an HTS system would be profitable.

In order to capture this variance in the capacity to monetize the Mb depending on the vertical, it is necessary to visualize the “Average Revenue per Used Mb”. This figure would show the capacity of a satellite operator to attract high valuable customers.

What’s the Role of Technology, Capacity Supply & the Changing Cost Equation?

There are HTS systems specifically built for some verticals like EchoStar 17 for consumer broadband or Inmarsat’s GX for mobility. The design criteria for these systems are very different, from purely maximizing throughput to maximizing coverage area. Accordingly, it is necessary to have a wider perspective when comparing HTS systems and not only look at revenue generation but also compare the systems’ costs. Comparing “Average Revenue per Used Mb” with “Average Cost per Supplied Mb” would give a vision of the Return on Investment the system can achieve.

Satellite operators have recently put a lot of emphasis in reducing the CAPEX/MHz ratio of their new satellites. Electric propulsion, payload scalability or launch costs have been some of the fronts used to cut costs.

Last but not least, the shift from a B2B to a B2C industry occurring with the rise of consumer broadband comes with new cost structures, especially the high operating costs of customer acquisition and service of a B2C business compared with old CAPEX-intense B2B cost structures.

Bottom Line

The wide variance in usage patterns of HTS systems together with the pressure on pricing makes fill rates a meaningless measure of success for HTS architectures. Measuring volume alone is no longer relevant if it’s not accompanied with a measure of how effective the utilization of the assets is and what net margin this volume can produce.

HTS is opening new markets for satellite operators, and the industry needs to completely re-think the business models to serve these green fields. This includes how to measure success.

There is currently no single metric or a combination of metrics that best measure HTS success. However, this will surely be a topic that will be vetted by the industry in the coming months, both for internal performance checks as well as for external financial benchmarks in formulating investment decisions.