The first reason motivating the need for advanced evaluation techniques is the constant and rapid evolution in the telecom sector, clustered with the doubt surrounding future economic growth. This increases the uncertainty of the environment in which companies make investment decisions. Several real-life examples reflect this uncertainty. The financial crisis has reduced the consumer confidence, resulting in a decrease in consumption by these consumers. As a result, turnover growth rates have decreased. Another example is linked to the ongoing technological evolution in the mobile phone sector. Cell phones have evolved from portable phones to handheld computer devices, allowing users to be connected everywhere, every time. This evolution is reflected in the market evolution during the past decade. While Nokia has been the largest mobile phone producer from 1998 to 2011, Samsung has overtaken them in 2012. The main cause is the small market share of Nokia on the smart phone market, where Google (Android) and Apple (iOS) dominate. In this smart phone market, Nokia’s market share is not even in the top five. In the overall mobile phone market, Nokia’s share has been steadily dropping to 15%. Linked to the evolution of devices, customers require an ever increasing bandwidth. The first mobile phones were only used for voice communication. The Global System for Mobile Communication (GSM) standard describes the protocols for second generation digital cellular networks. As data communication became more important, new standards were developed, leading to third (3G) and even fourth generation (4G) protocols. Long Term Evolution (LTE) already offers a peak download data rate of 100Mbit/s, while LTE Advanced can handle data rates up to 1 Gbit/s. Another source of technological uncertainty is linked with the performance of new technologies and equipment. Achieved speeds of wireless technologies are impacted by several environmental factors. Attenuation of signal strength is impacted by line of sight, physical obstacles like walls and interference with other technologies. And how is such uncertainty handled when planning and dimensioning the network?
Next to general economic environment and technological evolution, a third uncertainty driver is regulation. Regulatory regimes can have a large impact on the initial viability assessment of business cases, but this regime can also change significantly during the project lifetime. For example, in Brussels, the government has decided to only allow antennas with a electromagnetic field up to 3 volt per meter. In addition, in a radius of 200 meter around the antenna, only 1.5 volt per meter is permitted. As regulation impacts the technology modelling, resulting in the requirement to install a denser mobile network, this increases the costs and thus reduces the viability of a 4G network deployment by a mobile network operator in the capital of Belgium. As spectrum licences have already been acquired for a larger geographic area, this regulation in turn reduces the
economic viability of the 4G spectrum investment. In the fixed broadband market, European National Regulatory Authorities (NRA) have implemented two aspects concerning local loop access. First, incumbents must provide access to their local loop to other licensed operators. Providing such access requires the installation of extra equipment in the central offices and results in extra operational processes when customers are connected or migrated. Secondly, price caps for this access to the local loop were introduced. New entrants pay a fixed monthly rental fee per customer to get access to the network of the incumbent. By enforcing such prices, regulation clearly impacts the profitability of both the incumbent’s and new entrant’s business case.
The second motivation is the continuing trend in market structure. As a result from the liberalisation in Western economies, only few industries remain protected. All other sectors are characterised by competition between different companies. Two examples of such sectors are the energy and telecom market, which have undergone significant liberalisation in the last two decades [2.1]. In the European energy market, former monopolies have been opened up to new, possibly foreign entrants. Today, consumers can purchase energy from different suppliers, those suppliers can buy their energy on a market where different producers offer energy. Only the transport and distribution networks remain a natural monopoly. However, by splitting the previously vertical integrated providers, extra operational processes are now required, e.g. in the case of billing, customer migration, etc. In the telecom market, a similar trend has occurred. In the 1990s, the former incumbents have lost their monopoly on voice and data transmission, increasing the dynamism, uncertainty and competition. At the same time, other sectors previously populated with multiple firms have noticed a trend of continuous consolidation, resulting in oligopolistic markets. These two aspects can be categorised as increased uncertainty and competition. Within this environment, companies need to make investment decisions, taking into account that whatever they decide; the outcome of the investment project is subject to a lot of uncertainty and might trigger competitive reaction. Cost evolution and customer preference are only two aspects impacting the outcome. In addition, within the concentrated market, the company needs to take into account the effect of their decision on its competitors, and possible reciprocal actions. Price wars are just one example of such competitive interaction. One firm decides to lower its price in order to attract a higher market share, churning customers from competition. However, when competitors observe this effect, they lower their prices as well. With such dynamics, a vicious circle can occur, where companies continue to lower their prices, up to the level of their marginal production cost. As a result, some firms will be forced out of the market, as they can no longer generate profit, while the remaining firms operate at very low or even zero profit margins.
However, competition is not the only possible market interaction. In a concentrated industry, cooperation models emerge as well. While overt and tacit collusion are forbidden, firms can cooperate in order to gain competitive advantage. This can be by striving for cost reductions, but also in search of new standards. In case of the development of the successor of the DVD format, different industry players cooperated in the Blue-Ray disc Association. Other examples are 3GPP and the Wi-Fi Alliance. In case of Wi-Fi, early Wi-Fi (802.11) suffered from interoperability problems. As a result of a compromise in the standardisation process, two incompatible modulation options were provided. A group of vendors founded the Wireless Ethernet Compatibility Alliance (later the Wi-Fi Alliance) to resolve this issue and promote their preferred option. They set up the testing and certification under the Wi-Fi certification logo [2.2]. When operating in this environment, companies face two challenges in managing these aspects. The first one links to uncertainty surrounding future evolutions. Following your gut feeling tells you it is better to remain flexible to react to unforeseen changes, than to commit all your resources into a do-or-die decision. In a static environment, the latter would be without risk, but with fast and unpredictable changes, the former is the most interesting. Committing without flexibility to change comes with high risk. As a result, in every investment decision, it should always be checked if you can react flexibly to a changing environment. In absence of competition, it is better to wait with the investment until no more uncertainty remains.
The second challenge is managing competition, and more specifically, gaining and maintaining a competitive advantage. In this case, gaining a first mover advantage is typically the key to gain the advantage. When moving first, the company cam pre-empt competition. Research and Development (R&D) efforts in order to obtain patents or the purchase of a wireless spectrum licence fit under gaining such a competitive advantage. However, the decision to make the investment in R&D or in licences must thus be made under a large amount of uncertainty. The chances of R&D in resulting in the discovery of new medicine are small, and a wireless license is acquired before introduction of the new service, thus resulting in a large uncertainty on the potential customer uptake and the related revenues, or even on the performance of the new technology in the field.
As a result, companies operating in the current environment are constantly balancing these two opposite ideas. They want to remain as flexible as possible, postponing investment until the uncertainty clears, and trying to move as fast as possible to keep ahead of their competitors. Translating these two concepts so they are reflected in the project valuation is a main question arising today. Traditionally, such valuations are conducted through a techno-economic analysis.
A typical techno-economic analysis consists of modelling cost and revenue predictions. The modelling is based on a clear understanding of the underlying technologies, hence techno-economics. Performing a techno-economic analysis of the deployment of a mobile broadband access network (e.g. 4G) requires insight in the provided data rates, cell capacities, impact of line of sight, etc. From this modelling, an interpretation of the economic viability of the project can be made. However, this approach can only be followed when the actor conducting the project has financial objectives. In reality, actors have additional non-financial objectives. Or even no financial objectives at all, e.g. regulators. More background on players and their objectives can be found in Chapter 3.