My new book – “Emperor Ofcom’s New Clothes” – set out how a focus on market forces for managing spectrum and mobile networks has resulted in networks that have less coverage and capacity than would be optimal for most countries. The book works through a detailed assessment of how this came to happen in the UK and the way to deliver networks that maximise the economic and social benefits for the country.
In this series, we look at how to extend this analysis and methodology beyond the UK. Most countries face similar challenges, and hence many of the same ideas apply. This first instalment looks at how to assess the current situation; subsequent articles will cover optimising governance and lowering network deployment costs.
While subscribers in most countries are clear that they want fewer not-spots and better broadband, it is rare that a country has collected good data on the current status of its fixed and mobile networks. This is because: 1) such data is often hard to collect; 2) commercial operators rarely want to reveal the status of their networks; and 3) there are generally no calls for the data.
There are many ways to gather good data. Over the last few years, one option has come to the fore – crowdsourcing. Apps on mobile phones can report hundreds of measurements a day per phone to a database. With millions of phones, this can rapidly lead to an extensive dataset. The data can cover mobile signal levels, mobile data rates, and Wi-Fi data rates, which give a good indication of the speed of fixed broadband connections. The measurements also have the benefit of aligning with a user’s experience, whereas operator-led measurements may not account for practical degradations such as phones being in pockets or having poor quality antenna. Measurements are kept up-to-date, so changes in connectivity can be tracked as they happen. A regulator can set up its own app, but it is typically easier to work with existing crowdsourcing companies who can process and interpret the data gathered. Putting a process in place, capturing sufficient data, and analysing it might take a few months for the first report. Then, the activity can continue to run in the background.
Once there is a good understanding of the current situation, it should be compared to what is desired. This is a somewhat iterative process that we will return to in the next instalment. Broadly, good quality coverage should be expanded to all areas where the national benefit exceeds the cost. Both benefits and costs are hard to determine, and both will change over time, but at this stage, what is needed is an approximate assessment of how far off the ideal situation current levels of coverage might be. To undertake this approximate assessment, operators could be asked for typical coverage costs for the areas of interest (often rural) equating to the cost of building a mast and deploying a base station. These costs can then be stated on a per km2 basis. Studies on the benefits to national gross domestic product (GDP) from mobile connectivity, undertaken in the country in question or similar countries, can then be used to determine the value per person. Dividing the cost by the value per person gives the minimum population density needed to make the investment viable. Country demographic data can then be used to work out the size of the area where there is sufficient population density but a lack of quality coverage. The calculation could also be made for lower cost coverage, especially if achieved through techniques such as high-altitude platforms (HAPS), which will be discussed in subsequent articles.
This area of unmet coverage needs to be coupled to a prediction as to the investments that might be made by the current operators in the absence of intervention. For example, if coverage is currently expanding rapidly, then there is little need to change existing policy, at least until the rate of coverage expansion slows. Understanding operator finances is also helpful – operators that have a low return on capital are unlikely to expand coverage and capacity significantly.
My book set out the need for both coverage and capacity – for good quality coverage that can deliver sufficiently high data rates to all. Understanding the scope for growth in data demand is another important element, as high levels of growth may require improved capacity to be installed in existing coverage areas. Most countries have data on average consumer data usage over time; this data can be extrapolated to predict future growth. Note that in many countries, growth is slowing, from around 50% per year a few years ago to closer to 20% now. Hence, any extrapolation might expect this slowdown to continue unless there were national reasons to expect otherwise. If there is a need for increased capacity, either because the measurements indicated slow current data rates, or because of an expectation of strong growth, then the costs of this need to be factored into the total cost of delivering ideal network capabilities.
Another important element of taking stock is understanding what has and has not worked in the past. For example, have shared coverage initiatives been implemented and if so, did they deliver on the benefits expected?
This first stage of “taking stock” is likely to take three to six months, unless there is good measurement data already in place. The output is an understanding of the gap between the current situation and an approximate assessment of where the ideal levels of coverage and capacity are likely to lie, coupled with an understanding of the extent to which any gap might be closed without intervention. For almost all countries, the answer will be that there is a significant gap – the next two instalments of this series will set out how to go about ensuring that the gap is filled.
Emperor Ofcom’s New Clothes by Stephen Temple and William Webb: https://www.amazon.co.uk/dp/B0CRGSSZSS?ref_=pe_93986420_774957520.
To find out how you can implement the legislation and regulation to make your country a fully connected nation, please contact us below.
