About the Forecast Database

The Machina Research Forecast Database is a comprehensive guide to the global M2M market opportunity. Our segmentation of the market is based on 12 M2M sectors, plus a thirteenth non-M2M sector 'PCs, tablets and handset data'. Within each of these 13 sectors there is a diverse set of devices, applications and services. As a result we base our analysis on individual applications, of which there are over 180 covering all of M2M. We then roll these applications up into application groups, of which there are 61.

This is illustrated in the chart below giving the example of healthcare. In this example the healthcare sector has 8 application groups. One of the application groups, Assisted Living, comprises five distinct applications. All of the data in the Forecast Database is presented at the application group level. Another example is the utilities sector which has a breakdown between three application groups: smart meters, electric vehicle charging and transport & distribution management. 

For each of the 61 application groups included in the Forecast Database we present the same sets of data. Broadly speaking this splits into three categories: connections, traffic and revenue. Further detail on these three elements is provided below.

Connections and RGUs

The Forecast Database counts M2M connections regardless of technology. Connections is split between seven categories. Three are wireless wide area network (i.e. 2G, 3G, 4G). The remaining four are short range (including WiFi, Zigbee, Z-Wave etc), MAN (including diverse technologies such as wide-area powerline and mesh), wide-area fixed (including DSL, cable and fibre) and satellite.

It is important to note that we distinguish between connections and revenue generating units (RGUs). In many cases there are multiple connected devices per RGU (e.g. in the case of a connected alarm system). In some there are multiple RGUs per connection (e.g. in the case of a vehicle platform supporting navigation, tracking and in-vehicle entertainment applications through a single connection). 


Traffic tends to closely follow connections. We apply assumptions of average traffic usage to each of the connection or RGU types as appropriate. Traffic is solely a measure of wide area network traffic.


The revenue forecasts within the Forecast Database are very detailed. Total revenue comprises income from the sale of M2M devices and/or services. It includes device costs (the total cost where connectivity is integral and module costs where devices can optionally have connectivity enabled), monthly subscription, connectivity and traffic fees.

We further break down the revenue into constituent parts. For example, the devices piece is split between the device itself and the connectivity module. The services element is the most complex, comprising the service wrap (i.e. the actual service that is facilitated by the connectivity), the service enablement function, and the provision of connectivity.

Each of the elements presented in the chart below is available in the Forecast Database for each application group and each country.

We also identify what revenue is addressable by a mobile network operator (MNO) and also, as a continuation, what revenue we expect MNOs to take. To achieve this, each of the revenue elements is considered separately for each application. So, for instance, mobile traffic revenue is expected to go 100% to an operator in all application groups, whereas device revenue will tend to be much more heavily contested with other companies, e.g. specialists in the particular sector. So, for any application, a portion of each revenue is considered to be addressable by an MNO, and a portion is expected to accrue to them. These "MNO Addressable Revenue" and "MNO Expected Revenue" indicators are also included in the Forecast Database. 


It is almost impossible to give a definitive methodology for the Forecast Database. Each of the application groups has different dynamics requiring particular attention. As a result, the methodology for each application group will be competely different. However, there are some general things that we tend to take account of when compiling each of the application group forecasts: 

  • Current adoption: Our first task when forecasting an application is to find all salient data about current deployments. This involves a lengthy trawl of all available primary and secondary data.
  • Regulation: One of the major drivers of M2M is government mandate. This can take the form of explicitly requiring that a device be connected (e.g. eCall in Europe). Or it might be implicit in a regulation (e.g. frequent meter reading would be impractical otherwise). Or it may be necessary to indirectly achieve government targets (e.g. reducing carbon emissions). All of these have an impact and help to drive M2M. 
  • Demographics: Naturally we also take account of standard demographic and socio-economic statistics. Population size and disposable income will be a key determinant of the adoption of connected consumer electronics devices. Meanwhile aging populations are strong determinants of the use of healthcare applications.  There are a number of statistical indicators that might or might not be relevant in any particular application including population, number of households, penetration of cars, and many more.
  • Sector-specific statistics: The addressable market for certain applications will vary tremendously depending on particularly characteristics of the market. For instance, the opportunity for the Extractive sector in a market such as the Netherlands is limited, whereas in Saudi Arabia or Canada it is substantial. Similiarly, the opportunity for smart gas meters in Sweden is negligible because piped natural gas is rarely seen, although it is common in neighbouring countries. All of these market-specific idiosyncrasies need to be considered.
  • Service deployment plans: We speak to a lot of companies in the M2M industry and as a result are party to lots of information about who is launching what service and where.
  • Value chain positioning: The value chain for each M2M application is very different and we need to understand who does what in order to identify the revenue opportunity for all of the different participants (see Revenue, above). We spend a huge amount of time with all participants in the M2M value chain identifying who will be the winners and losers. 
  • Technology availability: Clearly the technology splits in our forecasts depend on the availability of those technologies. Therefore we factor in technology deployment plans into our forecasts.
  • Evolving bill of material costs: One of the constituent parts of our revenue forecast relates to device. Therefore we need to be aware of the cost implicit in connecting devices. Furthermore the cost of connected modules will have a substantial impact on connections. As a result we need to closely monitor prices.

Once we have built this bottom-up forecast we then undertake a process of tallying this with the figures from operators and regulators around the world to which we're party. This is specifically relevant to wireless wide-area network connections. This way we can ensure that our bottom-up picture of the current market tallies with our understanding of the total size of the market globally and on a country-by-country basis. And finally, we're constantly testing our assumptions with the toughest critics there are: our clients.

If you would like to discuss our methodology, please do get in touch.

Accessing the Forecast Database

The full Forecast Database is available to clients of the Machina Research Advisory Service. It is accessible online and interrogateable via our Forecast Database console. This can be found via the Forecasts tab on the website. 

The console (below) allows subscribers to select data by region, country and year. They can then select from 61 application groups across our 13 segments. Finally they choose which of our comprehensive set of metrics they want. Then hit "Generate Now!" and the data will be delivered in excel format.

Further information about definitions can be found in this document.

If you have any further questions about the Forecast Database, or if you would like to arrange a demo, please don't hesitate to contact us.

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