SOCIETY | Sep 12, 2017

Earth Observation: use of data and business models

What kind of business is generated by the data collected via satellites?

Recently, interest in Earth Observation data and its exploitation has greatly increased, both from the point of view of social benefits and as a driving mechanism for the industrial sector.

The European Space Agency with the Copernicus programme, is moving towards global satellite coverage of Earth, with satellites capable of capturing more and more parameters, thus generating an incredible amount of data. Aiming to involve as many users as possible, the ESA has tried to exploit various approaches: from TEP (Thematic Exploitation Platform), an online gateway subdivided by themes that allow researchers to quickly process EO data, to the EO Marketplace, enabling businesses to offer new products and services based on Copernicus data and other sources.

If we look closer, these approaches are based on the pipeline business model, whose success depends on optimising activities, which are for most part the company’s own assets, within the value chain. At the end of the value chain, the asset is delivered to the final consumer. To clarify, this is the business model that has dominated this last century, adopted by Coca Cola, to P&G or GE. An approach that enables actions that are targeted to stimulate demand, build brand identity and leverage sales volumes in search of a cost-competitive advantage.

How does the business model change in the digital arena?

Something has however changed with the digital revolution. The latter’s cornerstones are the very forces that compose it: digitization, ICT and connectivity. Digitizing means transforming a document, image, sound, or any other analogue material into a binary sequence of 0 and 1, which can be processed by a computer. The computer can store the information directly within a database and then share it (Information Technology), or it can also be used for (Information and Communication Technology) processes that become increasingly efficient and that, driven by the spread of the Internet paradigm, go on to also define the ultimate strength of the digital revolution: connectivity. This latter refers to the information transmitted online.

Our world is increasingly connected and interconnected, and the two forces, linked to automatic information (literal meaning being “Information Technology”) enable us to imagine a world where the Internet can be extended to objects, industries, and actual places, thus becoming the IoT (Internet of Things) and throwing the doors wide open to a universe full of challenges and possibilities. This is called a “revolution” because the transformation cannot just be achieved by “adding the digital element”; a change is needed in which the perspective, the processes and the companies themselves become digital by integrating a digital culture at every level.

On the entrepreneurial level, the scenario we face is that in which demand assumes much greater importance and the warehouse is replaced by the interaction between users, who represent its fundamental resource. It is not therefore the control of resources that is critical, but rather the way they are governed.

The forces that have been created in the last decade all work very differently from the pipeline model. This becomes evident if we think of the five High-Tech leaders: Alphabet (Google), Apple, Facebook, Microsoft and Amazon. In every digital economy business, the online platform and its networking effects are convergence elements of this paradigm shift from the pipeline model platform. On the one hand, the platform plays the role of a content aggregator, capable of contemporaneously satisfying various questions of a different nature, bringing together both the producer’s side and that of the consumer; on the other hand, that of network externalities (or effects), i.e. the typical phenomenon that occurs when one user creates value for another. Thus, a service increases in value in line with the increasing number of interacting individuals.

A particular case of network externalities is represented by the cross side network effect) phenomenon. These latter are not related to the diffusion of the product between members on the same side of the market, but to the diffusion of the product on the other side. A typical example, to convey the idea, is that of consolle: side 1 – video-gamers, side 2 – video game developers; a user on one side attracts more users on the other side and vice versa. Add to these features other strengths such as the central role that the algorithm assumes in performing matching between users and content (always better to increase use), the evolution of technological information, reduction in transaction costs – which have rendered it no longer necessary to physically maintain an infrastructure or asset – this is how companies like AirBnB or Uber have been able to grow and beat the competition, hence revolutionising the rules of competitiveness.

The reason for their success? AirBnB has dematerialised rooms and Uber has done the same with owned cars. These features help the business model to progress faster, or rather expand without meeting the limits that are intrinsic to certain resources, which are by definition scarce, as S.P. Choudary also explains in his 2015 book, Platform Scale. Just as the Internet Economy has allowed these companies to have very high volumes compared to their competitors Digital Transformation could in the same way assume the role of maximising the exploitation of Earth Observation data. The social utility of this data, appropriately exploited, is potentially enormous.

Earth Observation Data Utility: the case of Villa Adriana

The data in question was utilised at Villa Adriana in Rome where the Artek-Satellite enabled services for preservation and valorisation of cultural heritage, evolution of the Videor – project – involving ESA, ASI and Nais, in collaboration with the ISCR – Higher Institute for Conservation and Restoration – created a continuous, updatable, web-accessible monitoring system with the aim of safeguarding cultural heritage by means of powerful satellite eyes capable of identifying assets potentially at risk. The project helps in understanding how the flow of visitors moves within the archaeological site and thus enables identification of the most interesting items and the most suitable paths. Artek is not only accessible to staff but also to the public who can consult the information and observe Adriano’s home from above. This makes it possible to exploit sponsorship in the future via advertising applications for mobile devices that can offer a major economic support.

A further application emerged after analysing the data collected by the Smos mission satellites aimed at preventing the risk of locust invasions to protect crops and optimise use of pesticides, with the help of an advance 2-3 month forecast.

What services could be developed to benefit companies and businesses?

What could happen to ESA data and to the EO world if the platform model was adopted in this market? How many developers, data scientists and businesses could be attracted by the presence of users on the other side, to avail of? What if users themselves could participate in the content creation process as occurs with Idea Management? These are the questions we need to answer. There are numerous scenarios for debate and perhaps even the idea of a platform model in the EO sector is not so far-fetched.

Meanwhile, giants like Google and Amazon are ready to break into the market. Google, among other things, with services such as Google Maps, Google SOS Alerts, has been and will be able to generate real benefits for the company as opposed to what has been achieved so far by other bodies, probably for its clear-thinking, expertise and the power to imagine and implement certain projects. If you use Google Maps you will understand the power of calculation, interface cleaning, simplicity, intuition and the concept of anticipating users’ needs; features that have always distinguished Google products. Furthermore, Google Earth Engine which utilises Earth Observation data from ESA, NASA and other bodies, provides a Cloud Storage that handles petabytes of public satellite data (1 quadrillion bytes) and embeds increasingly more datasets. It is almost certain that such data, algorithms (also thanks to user collaboration) and generated services will be exploited in more advanced Google applications, such as in the realms of the self-drive car.

The Google self-driving car project (now known as Waymo), can be both a complementary asset, by sampling information such as pollution, road conditions, driving style, or whatever will populate the database as well as users of Earth-observation data, reporting on traffic congestion, weather situation, etc. It is clear that leaving this area to Google or other American giants also means continuing to massively concentrate knowledge concerning our planet (and of us) and granting them even more data to analyse.

Perhaps, at European level, it would be necessary to speed up in the EO sector, solidifying initiatives that the ESA is trying to develop, seriously considering the possibility of exploiting a platform model that is able to grow rapidly and above all to attract developers, data scientists and users through a system of incentives that stimulate use, interaction, and value exchange within the platform. This would facilitate the achievement of critical mass, that is, the number of users that makes it attractive to use a particular asset. One thing that definitely cannot be neglected is the knowledge of the end-market, the needs of the players involved and the willingness to pay. If, however, the evidence shows that there is a conspicuous mass of interested users, but with scarce willingness to pay for the service, then a major distributor will be necessary. This role may be taken on by Google or a media company that, in exchange for other time spent by users among their services and in exchange for user-generated data, would be willing to offer free services, in fact, on subscription of the user

What is the future of EO?

Among the in-house ESA innovations there is the enormous reduction in the temporal gap between the time when the data is acquired and when it is stored and made available. Perhaps this could be the competitive advantage that the European Space Agency could exploit, allowing the use of data in services that until now, because of time-lags, were precluded. It is not just the anonymity of the major players and the business model that are involved in making the future of EO uncertain, but also the phenomenon of substitute products that should not be underestimated.

A large quantity of data captured by satellites could suffer from competition from widespread sensors that could capture the same data, (or similar, still however capable of meeting usage needs), at a lower cost and more rapidly. For example if, in the future, our smartphones had a sensor capable of assessing the presence of pollutants in the air and were quite capillary – this is an example to also extend the concept to other information that could be potentially intercepted by non-spatial sensors mounted on smart objects – it could render some types of satellite unnecessary. These sensors seem to be already available and could be embedded on new smartphones, so it’s logical to ask: does it still makes sense to launch Sentinel-5p (which will be able to monitor air quality and pollution levels), which has been postponed to this September?

Services that require high-definition viewing from above are easier to defend. The game being played here is a major challenge that will fix the foundations for a great number of future services for both society and business. It is crucial to make a timely assessment of the existing and future replacement products and understand how technology is evolving in this field. It is also pivotal to understand which needs may be met from the collected data, what manipulations are needed and who will be the players to benefit from the services, having their needs amply satisfied. To understand which business model may be best to use, the following approach can be adopted: putting matrix products from Earth observation with the market segments that are of potential interest. Each matrix box can be suitably weighted according to the size of the market and the difficulty in creating the dataset offering that particular service.

If there are many major users who are willing to pay, the approach that ESA is using, i.e. the pipeline, is the right one. The value chain will reach the end customer who will pay it back. On the other hand, if the largest markets are formed by users who do not want to pay, then the winning model is the platform one, so obviously a player will be needed to act as a distributor and who, in exchange for a certain type of value from users, is willing to offer the service. We are talking about a Google, Facebook or media company of the moment. This would represent a win-win for the market, but would also reignite the problem of the concentration of user data value if the company in question was not European.

We will soon find out whether Europe can leverage its assets and propose a winning model, even to decentralise the digital market, or whether it will be America that will drive the diffusion of the Earth Observation, Big Data; providing of course that the EO market continues to grow and does not encounter other obstacles. It turned out in fact from a projection up to 2030, that about 80% of EO data demand will still be from Public Administration and this would not be sustainable. It will therefore be necessary to promote so-called user uptake, simplifying access to data and promoting industrial access to increase awareness. This will all have to be done by taking advantage of the most appropriate business model to create a sustainable market for EO, which seems to have come to a turning point.