1.Introduction
The advent of a European Space industry in the early 70’s was driven by the development of the ARIANE launcher and the needs for both Defence and civilian satellites:
• Communications links were the prime movers, since Defence end-users needed to cover the whole earth, whereas communication links must be available on a 24/365 basis, in endangered areas
• Observation systems came next, mixing both meteorological applications and observation needs (in the visible, infra-red and radar domain), involving defence, civilian and scientific applications.
Yet, over the past twenty years, the European Space industry, like the European aeronautic industry, has migrated from prominently defense-based investments and applications to an increasingly wider spectrum of commercial activities.
Innovative commercial services have been created using large scale space infrastructures: this is the case for earth observation-based services, resulting in major advances, for instance in meteorological forecasts, environmental monitoring or risk mitigation strategies after significant industrial or natural disasters have occurred.
The major challenge for the whole value chain of the resulting downstream service players remains to capture all or part of such application markets, leaning on robust business models that will remain attractive, whatever other competitive solutions may do.
However, both public decision makers involved in space infrastructure investments AND industrial players using such infrastructures are facing a dilema 1
On the one hand, the European Earth observation industry was born to meet strategic needs “of public interest”, including defense, security, environment monitoring, meteorology and even basic science. Investments in the critical space infrastructures are then based on very long decision making processes, requiring lengthy inter-governmental consultations: the life cycle of any new Earth Observation program development is a minimum of 15 years between idea inception and the end of the satellite infrastructure. Moreover, decisions are driven by technological excellence to make these infrastructures reliable, with performance requirements very often near the limits of the best available technologies.
On the other hand, the learning curves of the service industry involved in environmental activities, together with the growing demand for more service applications, drive these technologies towards standardized and open applications. These new application segments are regulated by much shorter life cycles (say 5 years) facing competition coming from other technologies, event though satellite infrastructures become affordable enough to capture part of some emerging service markets, often related to regional development. The business landscape may then change very rapidly, narrowing the satellite infrastructure capabilities to a small part of the whole value chain, since exhibiting lower performances than new ground based or air borne systems.
A major challenge for Europe will therefore be to link public interest, large scale infrastructure investments with the needs of regional, highly innovative, local services using such infrastructures.
In the USA, linking both markets relies significantly on the Defense application “driving belt”, where innovative companies:
• can “spin slow” on the public market side, which is well structured and receives more than five times the money that Europe is investing in R&D for Defense applications
• are able to “spin fast” on private markets since most of the critical R&D has been paid for by the public sector.
Europe must therefore invent another way of linking both wheels, through other support schemes to start-ups and SMEs that take into account specific European features:
• Within the “public interest” segment, the few remaining space players will continue operating with a technology push approach, since technology excellence remains a prerequisite. They will capitalize more and more on their satellite based knowledge to develop downstream applications on their own or with public support: the risk is that they can block the access to data since owning part of the IPR.
• Within the mass market segment, a significant number of SMEs will continue striving to develop innovative service activities based on a market pull approach. Many of them will not belong to the space community: their offer will target niche markets, with the possibility of missing clear interfaces with the upstream satellite data providers. They may even develop new services for their regional customers using US Earth Observation data, whereas European Earth Observation data exist for the same application, but are not formatted to be made accessible and affordable.
The GMES environment will need to bring dedicated answers to such SMEs, which will have to prove to be as efficient as the US environment has shown to be. The present paper aims at demonstrating that new business models will emerge in the coming years which will help the Earth Observation ecosystem of enterprises grow
2.Background: to-day’s EO/GMES ecosystem
The EO/GMES ecosystem is still an emerging industry characterised by:
• *a significant number of university or public space agency- spawned start ups and SMEs* (mostly with less than 30 people), focusing on specific pieces of the R&D value chain (data processing, data interpretation, decision-making based on EO data)
• *the combined role of entrepreneur’s personal equity and continuous public support to deliver services* that are not stabilised market-wise for a very long period of time (either due to knowledge improvement, as pure science generates applications, or due to customers’ evolving needs)
• *a market developed know-how or knowledge that leans on earth observation data*, very often this know-how or knowledge has not been patented, and is very much dependent on the access to raw observation data (including timely availability and cost of acquisition over significant periods of time).
The industry is growing and accelerating 2 , as shown by the indicators provided below.
| Estimated overall employment (2004) | 2,900 employees |
| Average EO-specific revenue per employee | €107k |
| Estimated total annual revenue for EO value adding activities (2002) 3 | €285 million |
| Average Revenue growth (2000-2002) | 19.4% CAGR |
| Profitability (2002 average gross margin) | 10.3% |
Basic indicators of EO service VA Industry
The estimated total annual revenue is split into 78% of income from sales (to public and private sectors) and 22% of income from development financing (from national and international agencies). The average industry revenue growth rate is ahead of several comparable industries. But concentrated in a few large companies: 77% of the industry’s growth came from just 6 companies, and almost half of that from just one company.
Overall, the industry profitability has improved, with an average gross margin of 10.3% in 2002 compared with just 1.8% in 2000: large VACs do not have higher gross margins (10.0% in 2002) than small VACs (10.7% in 2002), thus showing no direct link between profitability and scale.
A large part of the demand for EO services comes from the public sector. Public authorities and decision makers at all levels (regional, national, and international) are the primary users of EO services and products. Yet, the demand for EO services is still fragmented:
• decision makers at all levels are not yet convinced that services are reliable in terms of their quality and continuity;
• decision makers need to see from experience that those services will contribute to their organization’s objectives to justify meeting the cost of their long-term operation, maintenance and renewal 5.
The EO industry is characterised by sophisticated products, constant technological innovations and ever-changing demand as the market evolves. Although EO products exist at all maturity stages, the majority of products are experiencing a growth phase, i.e. sales are growing and expected to continue to do so. This indicates that the industry overall is in a healthy position. However, the percentage of products in a start up phase (approx. 10%) seems to be low for an innovative industry (see below).
The EO industry is highly competitive: only less than 10% of products and services have no competition or a single competitor. Competition exists between EO service providers as well as between traditional or non-EO alternatives. Moreover, it extends across world markets. In general, the European industry EO faces increasing competition from US companies 7 who are supported by large government contracts for national security needs (ClearView, NextView), and global institutional operators such as NOAA & USGS.
3.The future ecosystem: trends for winning business models
This section argues that the anatomy of the earth observation ecosystem as depicted above must evolve in order to attract more investments, in a way similar to what is proposed in a recent paper for the biotech industry 8 . Why?
Although the above ecosystem anatomy may look quite similar to the anatomy of the software or semi conductor industry, its specific R&D features make it quite different from what is known in the software or semiconductor industry. As a matter of fact, it is more similar to the anatomy of the biotechnology industry:
• *uncertainty is rooted in the limited knowledge of large scale interacting systems* (for instance thermal currents in oceans, water vapour cycle in the atmosphere…): this is not the case in the IT or semiconductor sectors, where at the end of an innovation cycle, the product will function anyway (meeting more or less the expected performances). GMES-based development cycles are therefore more uncertain, ending up with prototype failures: the expected performances can then never be reached.
• *the process of environmental R&D cannot be split into pieces*: it requires a wide range of disciplines working together in an integrated fashion.
• *the knowledge in the various disciplines is very often tacit or intuitive* (since difficult to model): this makes collective learning very difficult.
This has indeed consequences on the evolution of EO/GMES markets:
• *advances in modelling, space instrumentation have not significantly reduced the above uncertainty*. Under certain circumstances, it may have increased it because modelling results and measured data raise more questions than they give answers to the issues that EO is supposed to address (see for instance the Carbon cycle modelling),
• *uncertainty translates into high, long-term risks*: in the biotech sector people have used patents to monetize intellectual property. This helps bridge the funding gap between basic R&D and the costs of developing a solution that reaches the market. However, public equity markets are not able to value firms on the basis of their ongoing R&D projects. Adequate information must be made (compulsorily) available to sophisticated valuation techniques (like real options) in order to be able to value the company. However, most biotech companies are reluctant to give away know-how to outsiders based on the disclosure of whether their R&D project works. This is exactly what happens in the EO industry. Most of the companies have built up internal know-how that cannot be patented. And overall, return on investments of these companies is still not in phase with what venture capitalist expect from other sectors. The system for monetizing intellectual property simply will not work in the GMES area.
• *Integration is a prerequisite for application, in many industrial areas*: many issues must be addressed at once, and the solutions must work as a whole in fine.
There are two ways of achieving integration:
Use market-reliant networks: experts integrate knowledge through alliances, licensing and collaborative R&D. This is the biotech sector approach;
Use all the needed pieces of a puzzle (vertical integration): this is what large pharmaceutical companies do in the biotech sector.
For the first approach, strong IP protection is needed. In the EO sector, the IP regime is very complex and risky. And the knowledge is tacit, i.e. cannot be precisely described in writing. Hence, the pace of learning together is slow; this makes collaborative projects run out of money very easily.
• *In the EO sector, what is known from R&D pales in comparison to what remains to be understood*. The ability to learn from past experience is still low because of the tacit nature of this knowledge. The learning of any SME active in EO is the aggregation of what individuals know and the insights shared by the teams. Very often this knowledge is not formalised and cannot be codified easily: sharing experiences in market-reliant networks takes time.
• *Overall, the EO R&D process faces productivity issues*. This analysis suggests that, as shown by profitability growth, new anatomies must be searched to make EO services more productive:
new sales models (like two-sided network approach)
new organisations and alliances (to either package products faster or find clients with more recurrent needs)
Such anatomies will have to cope with the typical R&D uncertainty and related high risks of the EO sector, to allow interdependent problem solving and to harness the collective experience of several scientific and engineering disciplines.
4.Building future business plans in practice in the EO/GMES area
Building robust business plan always relies on convincing arguments that structure the five key pillars onto which any business model must be built:
• VALUE (the WHAT?), which provides an overall view of a firm’s offering that represents a new, distinctive benefit or value for its customers;
• CUSTOMERS (the WHO?), which refer to the market potential for that value and to how the company reaches its customers and keeps them with the proposed value;
• MANAGEMENT (the HOW?), which refers to the management of the company’s resources necessary to deliver the firm’s value;
• NETWORKING capability (the WITH WHOM?), which measures the management’s willingness to favour open rather than closed innovation;
• FINANCIALS (the HOW MUCH?), which is the culminating point of a business model, which permits a focus on the specific components of a business model contributing to the company profitability (revenue/cost structure).
In the next section, several key invariant issues are addressed. The INVESAT project has shown that these issues will have to be faced in the next decade to strengthen each of the above five pillars. They all deal with a reinforcement of networking capabilities, very often indeed at worldwide level.
Focused long term co-operations
Existing and future EO players must emphasize focused long-term collaborations allowing the sharing of proprietary information, joint learning and more productive research. This leads to several approaches to catalyze cooperative growth:
o Engage in exclusive license agreements between public laboratories and start-ups especially when the newly-born company must build the full capability to sell the highly novel service (and this capability does not exist elsewhere);
o Support non-exclusive license agreements with public laboratories when the technologies involved have several development paths (yet uncertain);
o Focus R&D agreements between start-ups/SMEs and public research organisations that have two distinctive features to minimize R&D costs:
• Cross-disciplinary research teams to avoid fragmentation of the knowledge and faster integration to reach the market earlier,
• Translational research, where basic science can be easily translated into a specific service opportunity by the public R&D players.
Overall, EO R&D will require more and more integration of different highly interdependent disciplines. This integration is a prerequisite for industrial application. Hence, business models with more vertical integration in the R&D and in the business alliances will be favoured. Vertical integration 9 requires a degree of scale which implies that established large EO companies are well positioned to be integrators of R&D developed by small VACs .
There are signs of vertical integration coming from the success of virtual globes. Vertical integration can be anticipated to continue in the future as part of the satellite operators’ strategy.
Teaming with complementary service/data providers to create more value for the customer
In today’s EO VA industry, teaming with complementary service providers is used to a limited extent to mitigate the impact of the lack of highly skilled resources, which constrains operations and sales activities, especially in SMEs. Consolidation among these smaller VACs may be vital to the industry’s future health. They can develop new niche markets using collaborative approaches to reach novel horizons together at European, if not world, level. EO VACs could work together in order to strengthen individual EO offerings, and in particular, to collaborate with other service providers outside the EO industry to deliver more complete solutions. The development of the MASS (Multi-Application Support Service System) platform by SPACEBEL, under ESRIN funding, goes along that direction 10 .
Another key element of the GMES value network is data suppliers. Data supply is a key part of the VACs ability to deliver; companies must work in close co-ordination with their data suppliers to ensure this critical resource is optimised for them, securing access within appropriate agreements.
Network management
In value networks, interdependency between the network players is crucial: the performance of each GMES company increasingly depends on the influence it has over assets outside of its own boundaries. There are two main dimensions that structure the behaviours and attitudes of the network manager:
• the level of benefits that it gets from value integration
• the level of control it has on the network for pricing and making transactions happen.
Creating and capturing value requires very often a central firm exploring the potential to create value for customers in a radically new way and shaping the external environment. This central firm brings together players with different assets and competences.
As a general rule, attention must be paid with the governance rules of inter-organisational ties in the value network: they have to maximise the joint created value and assure that the created value is shared among the network participants, so that each of them is better off than when they would leave to be out of the network.
Value distribution
The viability of open business models is greatly dependent upon the generation of value not only for the customer, but also for the network of firms that collaborate to provide the product/service. Joint value creation is determined not only by the firm-level resources and aggregated competencies but also, and more important, on how effectively and efficiently resources are combined and governed at the network level. Therefore, favouring value appropriation by the different networks players is a critical part of the business plan execution.
Whereas major recent research studies have been focused on defining the determinants and measures of customer’s value, there is little known about the value that is expected and delivered to firms through their participation in inter-firm networks. The value created has to be distributed among different participants (including the targeted customers). Value appropriation has to be also considered jointly with value creating at network level: the quality of the collaboration of the participants and the value-sharing among them determine how much value the network as a whole can create.
Value networks rely on long-term incentive structures to motivate participants: by joining the network, participants find that they are able to improve rather than working on their own. A general rule is to check that all players necessary for the smooth working of the value network are better off than in competing business systems.
5.A new promising approach: business plans relying on two-sided markets
Many EO/GMES business models fall into the category of two-sided markets and networks, which link markets from different sides of their customer networks through platforms.
| There are three key factors to be considered in designing business models in a two-sided market: |
1. Pricing the platform, i.e. determining which side should be subsidised, the degree of subsidisation and how much of a premium and for how long the other side would be willing to pay in order to have access to it. A price for each side of the market has to be chosen considering the impact on the other side’s growth and its willingness to pay. As the number of “subsidy side” users is crucial to developing strong network effects, usually prices for this side are set below the level one would charge if the subsidy side were seen as an independent market. On the contrary, the money side pays more than it would if it were viewed as an independent market.
2. Managing the winner-take all dynamics: in some two-sided industries, only one company controls the platform (ex. eBay’s auctions); in others, multiple companies share the dominant platform (ex. the DVD standard). When a network industry is likely to be served by a single platform, one must decide whether to share the platform with competitors or fight for its control.
3. Facing the threat of envelopment by competitors: a response to this threat is to change the business model, for example by switching or changing its money side (see the Google Map case against Microsoft) or finding new allies.
6.An illustration: the SoDa Internet platform
Climate change studies, solar electricity production, and human health are just three vital research areas to benefit from SoDa, a new web service linking the world’s leading solar radiation databases. Better yet, this EU-funded project helped create new businesses, advanced web technology and is now turning in a profitable commercial exploitation.
It started in 1999 with a seemingly modest goal. The SoDa project sought simply to link, online, various databases about solar radiation, what is usually called sunshine, via one website. It was partly funded by the European Commission from 2000 to 2003. The consortium gathered universities and small enterprises from the European Union and Switzerland.
Yet, the project was far more fruitful than anyone expected. It helped develop new, technically challenging, web service tools. It spawned completely new businesses, and is leading to the optimal development of solar power stations. It helps researchers understand extreme climate events like the August 2003 heat wave in France. It provides a model, inspiration and the technical means for other projects to link publicly funded climate data.
The SoDa project cost €2.11m, with €1.19m from the EC, but its impact punches above, way above, its weight. At the end of the EC-funded project, the SoDa Service was set as an operational service by Ecole des Mines de Paris, in collaboration with former partners. SoDa links the world’s most important sunshine databases like NASA’s database, the National Oceanic and Atmosphere Administration (NOAA) and the Ecole des Mines in France. There are over 20 other databases linked into the system, too. These databases use all sorts of high-tech technologies like satellite observation, ground monitoring and sophisticated modelling to calculate the amount of solar radiation reaching the world’s surface. Prior to the launching of SoDa all these data were dispersed across the world, in information banks, all sealed off from each other. SoDa’s innovation was to link those databases together, across the internet, and present the data in a unified, usable form.
The SoDa system is fast, thus permitting online applications to analyse the data. All this is done transparently, invisible to the user. Ease-of-use and quality of data has led to major growth of the service, up from 2,500 unique visitors in 2002, when the project ended, to a projected 27,500 professional users in 2007. Several services delivered by the SoDa Service are charged to the clients, others are for free.
The SoDa Service provides the very best quantity and quality of solar radiation data, with applications in areas as diverse as renewable energies, agriculture, building design, meteorology, materials science and even human health. It has also led to some new, innovative services, such as the monitoring of home panels for electricity production. But all these services are just the beginning. SoDa is extended with the help of the International Energy Agency and European Commission. Open source tools should be developed around common standards if the model is to be used in other services. This is a technical challenge, since open source standards can be amazingly complex.
7.Conclusion
EO based businesses will still involve a lot of new knowledge acquisition. Hence, uncertainty will be rooted in the business plans since the process of “environmental” R&D cannot be split into neat pieces, and the knowledge in the various disciplines needed to solve business issues is very often tacit or intuitive, which makes collective learning very difficult. This has two direct consequences for EO/GMES companies:
•uncertainty translates into high, long-term risks
•integration is a prerequisite for high quality applications in many industrial areas.
Achieving integration requires the use of market-reliant networks and a trend toward more vertical integration for the companies active in this market: this is what can be observed at EU level where public bodies have been encouraging the so-called integrated R&D projects to prepare the supply of high quality, processed satellite data for several field of applications (the so-called Core Services: Ocean, Atmosphere, Land).
End user wise, two sided markets/networks, like the Google Earth model, should be able to bring very rewarding ways of selling services based on Earth observation. It is expected that prototype applications will be created in the years ahead, especially in sectors that can use simultaneously several of the above core services to bring the appropriate added value: notably the renewable energy sector, water management, waste management, public health monitoring.
8.Acknowledgements
This work was financially supported in part by DG Enterprise under the INNOVA initiative (Contract N° 022513). The INVESAT consortium partners are thanked for participating in the stimulating discussions on shaping the future of several EO-based innovative business models all over Europe.
1 Ghiron F., European Parliament , ITRE Mini-Hearing on Space, 16 JULY 2007
2 “The State and Health of the European and Canadian EO Service Industry” Technical report, September 2004, ESA, Booz Allen Hamilton, VEGA
3 These revenues exclude primary sales of basic EO imagery (estimated at 25-30 million Euros per year).
4 Data normalized to the year 2000 = 100 points
5 EC Commission, GMES: From Concept to Reality , SEC1432
6 Five key stages of a product lifecycle are identified: start-up (the product is in its infancy); rising (sales are growing and expected to continue to do so); *mature* (sales have reached a steady state); *declining* (sales are reducing but still possible); *end of life* (sales have declined to a terminal point and effort is better directed elsewhere). The chart is based on a characterization of the EO products interpreted by the VEGA study team.
7 Three of the most important US companies involved in remote sensing are: Digitalglobe, OrbImage, and Space Imaging, Inc. These companies operate satellites, provide a range of products and tend to operate through worldwide partnerships.
8 GaryPisano “ Can Science be a business ? Lessons learnt from Biotech” Harvard Business Review, October 2006, page 114
9 Vertical integration describes a style of ownership and control. The degree to which a firm owns its upstream suppliers and its downstream buyers determines how vertically integrated it is. Vertically integrated companies are united through a hierarchy and share a common owner. Usually each member of the hierarchy produces a different product or service, and the products combine to satisfy a common need.
10 See http://services.eoportal.org/
Serge Galant is CEO and takes care of Technofi’s Business development in order to provide innovation management technique to the manufacturing and service companies. His main activities and responsibilities are to stay in charge of finding new sectors involving technology innovation as a vector of growth (both turnover and profits), reshaping new activities in the field of Consulting and Technical assistance and marketing and sales for the new growth sectors for the company: transportation.
He was involved in the development of many innovative technologies (energy, defence, telecommunication, transportation, aerospace, agro food, bio technology). From 1992 to 1998, he was Director for New Business Development of BERTIN and CEO of ORKIS, a subsidiary of BERTIN in image processing. In 1998, he joined Technofi as a Vice President for Business Development in the private sector. In 2001 he has been appointed as CEO and main shareholder of Technofi.
Serge Galant holds an Aeronautical Engineer degree from ENSMA, Poitiers, France (1971) and PhD in Mechanical Engineering from The Massachusetts Institute of Technology, Cambridge, USA (1975).