TERA is a tool for techno-economic assessment of communication networks and services. It is a spreadsheet based application which has been designed as a very open tool, giving maximum flexibility towards the user.
Compared to its predecessor, the TERA tool aims at the study of architectures spanning the whole telecom network, not only the access network. It is also capable of handling advanced telecommunication services like networked multimedia. The techno-economic assessment methodology implemented in this tool is based on the work carried out within AC226 OPTIMUM and AC364 TERA projects.
The main scope of the work for which this tool aimed at within TERA project is the evaluation of the introduction of advanced telecommunications services in both wireline and mobile networks.
The framework of the TERA techno-economic evaluations is shown in the Figure 6.
Figure 6. The TERA information flow.
The procedure for carrying out a business case study is following:
1. Make a survey of necessary applications and the future needs
2. Translate future needs into relevant architectures and bearer services.
3. Evaluate the services and architectures by using the tool
4. Select the optimal architecture and set of bearer services based on the economic output from the tool.
The following discussion will concentrate on the point 3., i.e. how to do the actual evaluation with the tool.
The user defines the study period, which is best adapted to the case at hand. For fixed network deployment, for example, a ten-year period is reasonable, considering the time it takes to reach market maturity. The services to be provided must be specified. This includes the definition of the market penetration of these services over the study period. Also the tariffs for services have to be defined, i.e. the part of the tariff that is attributed to the network under study. From the combination of yearly market penetration and yearly tariff information TERA calculates the revenues for each year for the selected service set.
Next, the architecture scenarios to provide the selected service set must be defined. This needs network planning expertise and is mostly outside of the framework of TERA methodology. TERA includes a geometric models, that will assist in the network planning by automatically calculating lengths for cables and ducting. These geometric models are optional parts of the methodology and TERA can be used without them, e.g. for radio access technology evaluation, where no geometric models are necessary. The result of architecture scenario definition is the so-called shopping list. This list is made for each year of the study period and it shows the volumes of all network cost elements (equipment, cables, cabinets, ducting, installation etc.) and the distribution of these network components over different flexibility points and link levels.
The costs of the network components are calculated using an integrated cost database. Architecture scenarios together with the cost database give investments for each year. A cost database, containing data gathered from many European sources, was developed within the AC226 OPTIMUM project and it has been extended within the TERA project.
In general, various approaches towards Operation, Administration and Maintenance (OA&M) costs are possible. The predecessor of the TERA tool used a simple proportional approach, relating the OA&M cost to the cumulative capital investment in the network. In this approach, each network component in the cost database was classified by an OA&M class. This OA&M class defined a percentage of the cumulative investments. This percentage is used to calculate OA&M costs for this network component on annual basis. This approach has been re-thought in the TERA project because modern networks have different types of equipment and also different types of OA&M cost components. This means that OA&M costs are not as directly related to the investments as they have been in traditional telecommunications networks.
Investment costs together with OA&M costs give life-cycle cost for the selected architecture and service scenario.
Finally by combining service revenues, investments, operating costs and general economic inputs (e.g. discount rate, tax rate) TERA gives cash flows and other indicators of economic performance like NPV, IRR, Payback period etc.
In the context of the TERA project studies, this version of the tool is extended to model, dimension, and calculate cost of both the transport and switching part of the network in addition to the access network models used with previous versions of the tool. This is done by extending the number of network levels available in the geometric model and by studying the required resource sharing and traffic dimensioning problems.
The situations where the end service is supplied by several service/network operators is the standard nowadays. The earlier methodology, used for the evaluation of access networks, assumed that there exists only one interface to another operator. The TERA tool is capable of handling more complex operator scenarios.
The Operation, Administration and Maintenance (OA&M) costs are divided into three separate components. Conceptually the three components are defined as follows:
M1 - Represents the cost of repair parts. This component is included automatically in the models and is driven by the investments.
M2 - Represents the cost of repair work. This is also automatically included in the models. Detailed description of M2 component is given below.
O&A - This component represents Operation & Administration costs and it has to be included manually when building models. Typically it would be driven by services, say by number of customers, or by number of critical network elements.
Figure 7. The TERA OA&M methodology.
The calculation of M2 component is based on failure rate and on time it takes to repair the faulty unit. Input parameters are:
1. Cost of work hour, Pl [€/hour]. (defined in time series sheet)
2. Mean Time Between Repairs, MTBR. [ years] (defined in database for each cost component)
3. Mean Time To Repair, MTTR. [hours] (defined in database for each cost component )
The formula for calculating M2 is
In order to implement this, two classes for MTTR and MTBR must be defined in the database.
The total maintenance costs caused by any single cost component in year i are
where
Vi is the equipment volume in year i
Pi is the price of cost item in year i
class is the maintenance cost percentage (defined by choosing MaintenanceMaterialClass for every cost component)
Pl is the cost of one working hour
MTTR is the mean time to repair for the cost item in question
MTBR is the mean time between failures for the cost item in question
A lot of theoretical work on the Risk Assessment was done within the TITAN project. There were also some calculations made applying a commercial Risk Assessment tool called Crystal Ball. The practice showed however that the running of this tool was a relatively slow process. This problem has been at least partially solved by improving the speed of the actual calculation process.
The TERA project has developed an additional software package that can be used together with the TERA tool to take into account the impacts of network externalities. This add-in package takes the market parameters as input and estimates from that how and when the service is likely to break through or vice versa it can give recommendations e.g. for tariffing in order to achieve the desired service penetration.
The main inputs for the model evaluations are the definitions of network architecture and service scenarios. The subscriber density is the most important parameter to the geometric model.
The architecture scenario is defined in a shopping list which indicates how the network is built out during the study period. The shopping list defines the amount of equipment needed in the network and, the time when the various components actually are implemented.
The service scenario defines how many subscribers are connected to a certain service at a certain year and how much revenue one service user means for the network operator per year. The penetration of the service, expressed in terms of number of users versus time is a key input to the calculation tool of TERA.
The TERA methodology contains the possibility to use a geometric model to calculate the cable and duct lengths in the network. The main input to the geometric modelling is the subscriber density. This parameter is often used to study the sensitivity of the cost of the system to various geographic conditions.
In the evaluation of investment scenarios there can be several points of view. Depending on the complexity of the scenario various commonly used indicators, like Payback Period, NPV or IRR, can give differing results in comparisons. Because of this, it is often necessary to use several figures of merit for the studies to get an thorough understanding of the economic issues related to each scenario.
In most of the cases these evaluations have some less known inputs. In these cases it is advisable to apply sensitivity analysis and/or risk assessment methodologies to these inputs using multiple figures of merit as indicators.
In most of the evaluations the calculation includes the revenues from the services. TERA methodology handles the revenues simply by estimating a certain annual tariff for each service per connected customer. However, it must be noted that revenues in TERA refers to the part going to the access operator, not the total amount customers will pay for their telecommunications services.
The above revenues input is critical for the subsequent calculation of further economic outputs like Profits, Retained Profits and Cash Flows.
The first output of the TERA methodology is the investment cost of the network project. Because the TERA methodology studies scenarios, the investments are usually spread over the study period. To get a single figure of merit for the total investment, the future investments are discounted to the start of the study period using the conventional discounting formula. The total discounted investment cost is usually called First Installed Cost.
In the TERA methodology the network is subdivided into a hierarchy of flexibility points and link levels. Links interconnect flexibility points. All links or flexibility points in the same hierarchical level form a so-called network level.
The current implementation of the methodology allows the investments to be analysed based on physical location of the cost components in the network (by hierarchical network level).
Life Cycle Cost is defined as the sum of global discounted investments and global discounted running costs. This gives the total costs for constructing and running the network over the study period.
Often the sole reason for a techno-economic study is the evaluation of the cost of the proposed network build. The reason might be a new network or an upgrade to the existing network. In these cases it is not always necessary to add any service revenues to the study and the final result of the study can be either First Installed Cost or Life Cycle Cost of the project. In this case this methodology and the tool are especially suitable for comparative studies between competing network technologies.
The Cash Balance (Cumulative Cash Flow) time-series is a very informative figure for a network and service scenario. Especially for a green field case it gives much information in a single picture.
Figure 8. Example Cash Balance Curve
A typical Cash balance curve for a network scenario goes first deeply down to the negative side because of the high initial investments. If the scenario is profitable, the cash flow turns positive fairly soon and the Cash Balance curve starts to rise. The lowest point in the Cash Balance curve gives the amount of funding required for the project. The point in time when the Cash Balance turns positive gives the Payback Period for the project. This is the usual case when studying a single technology scenario in green field situation.
In an investment scenario where most of the expenditure happens in the beginning of the study period, the Payback Period gives a good indication of the efficiency of the investment. If the scenario is more complex, that is, if there are for example several technology steps in an upgrade situation, it is not possible to define a single Payback Period. It is still possible to use the Cash Balance curve as an indicator for the profitability of the scenario. In these cases it is important to study the trend of cash flow at the end of the study period.
The Net Present Value gives a single figure of merit for a project. Its definition is the Sum of Discounted Cash Flows plus Discounted Rest Value of the project. It gives the monetary value of the whole project in today's money. It is a good indicator for the profitability of the scenario especially in these cases where the Payback Period cannot be used because major investments are spread out in time.
The weakest point in this figure of merit is the definition or calculation of the rest value of the network. There are several ways to try to define this value. The usual approach uses the bookkeeping value of the network as the Rest Value because it is the only figure that can be calculated from the inputs already available.
IRR is the discount rate at which the NPV is zero. If the IRR is higher than the opportunity cost of money (that is, interest of an average long term investment), the project is viable.
If the scenarios to be compared are not similar enough, for example if the size of these networks is different, these can not be easily compared using Net Present Values. In these cases Internal Rate of Return gives a good indication for how "good value for the money" these networks give.
The geometric model is an optional part of the TERA tool and techno-economic model can be, and they often are, constructed without the geometric model. If needed, the geometric model is used to estimate the amount of cable/fibre and ducting required in the network. On a conceptual level the geometric model is a function that takes several inputs such as subscriber density, network topology (star, ring, bus), average cable over length, duct availability, etc. and gives two outputs, which are the total amount of cable/fibre required in the network and the total amount of new duct required. Various geometric models were developed and used in the TITAN project. The most advanced model (the TITAN model) is implemented in TERA tool and described below.
The earlier models used in techno-economic analysis were based on a star topology and a polygon geometry, which resulted in rather inflexible system. The now used TITAN model is more flexible in many ways. It allows modelling of clustered areas where subscribers are not homogeneously distributed. The topology can be either a star, ring or bus or a combination of these. Also the shape of the model area and location of flexibility points within the model area are taken into a consideration.
Following is a short derivation of the TITAN model.
Figure 9. The first three levels of the TERA geometric model.
In the figure above the basic structure of the TITAN model is shown. The model is based on a layer structure where each layer uses the same basic TITAN geometric model, but with different parameters. Between the layers there can be a certain amount of empty space. One layer can, for example, represent a village and next higher layer is a larger region where there are villages here and there and uninhabited areas in between.
The basic model area in each layer is rectangular as depicted in the following figure.
Figure 10. The basic model area for one model layer.
The next figure shows how the ducts are located within the basic model area.
Figure 11. Ducts within the basic TERA model area.
Duct length is given by
(1)
Where n is the distribution ratio at given network level. Each square in the model area represents a lower model layer or at the lowest level a subscriber. The sublayer/subscriber located at point (i,j) will be connected to distribution point (x,y) with a cable that makes one rectangular turn on its way. The total cable length will be:
(2)