1. Special considerations regarding the development of cost models in small countries IIR‘s Telecoms Cost Accounting Conference 2009, Dubai 25th – 29th October 2009

2. SBR 25.06.20152 SBR Juconomy Consulting AG offers sound business, technical, regulatory and legal advice on regulated markets in the telecoms sector and other network industries (post, electricity, gas, railways), as well as the media and information technology (ICT) segments Established 1st March 2004 Practices in Düsseldorf and Vienna

3. SBR 25.06.20153 Afghanistan, Austria, Bahrain, China, Czech Republic, France, Germany, Ghana, Greece, Italy, Kosovo, Madagascar, Namibia, Netherlands, Norway, Oman, Poland, Romania, Samoa, Saudi Arabia, Slovenia, Spain, Switzerland, Tunisia, UAE, UK Broad international project experience in Europe, the Middle East, Asia, Africa and the Pacific

4. SBR‘s experiences from cost modelling 25.06.20154 Top-down and bottom-up cost models Models for regulators, operators and industry organisations Cost models provided in e.g. Germany, Austria, Afghanistan, Samoa etc. Projects on regulatory cost issues in Germany, Austria, Bahrain, UAE, Madagascar etc.

5. Content 25.06.20155 Introduction Establishing Cost Models in Small Countries Doing Cost Assessments in Small Countries Summary

6. Introduction 25.06.2015 Listenpunkt Aspects Cost models (CM) Small countries CM are required for both operators and regulators. Aims of CM are e.g. to set prices (through regulator or operator), decide on investments and acquisitions. Operators and regulators in small countries faces some different considerations  e.g. smaller networks, smaller and/or less operators, less economies of scale. Definition of a small country: one with less than 1-2 Mio. inhabitants.

7. Introduction Modelling decisions to be made are including a large set of aspects: Cost of capital (WACC CAPM or current costs) Identification of cost drivers Identification of CVRs (cost volume relationships) Definition of services Definition of business units 25.06.20157 Cost Base (LRIC/LRIC+/ FAC/Marginal Costs) HCA vs. CCA (w/o FL) Bottom-up or top-down

8. Special issues regarding CM in small countries 25.06.20158 Low economies of scale Limited ressources for economic modelling Low transmission costs but high OH costs Centralized organisations Network design Economical issues Issues for regulators Simple backbone network structures and traffic modelling Small territory  No geographical deaveraging possible More detailled modelling required Large proportion of international traffic Few and/or small operators  Challenging competition situation Less anonymous and more direct communication (?) Limited resources

9. Cost modelling in small countries 25.06.20159 Situation in small countries Smaller networks but more detailled modelling Small or no backbone / simple backhaul Low transmission costs but high proportion of OPEX Cost constraints on modelling Challenging market situation for regulators Direct communication Development of the models Top-down vs. Bottom-up FAC/FDC vs. LRIC HCA vs. CCA Definition of services and cost centers Designing the network Cost assessments Operator to be modelled Data gathering Decisions to be made

10. Content 25.06.201510 Introduction Establishing Cost Models in Small Countries Doing Cost Assessments in Small Countries Summary

11. Cost base: FAC/FDC vs. LRIC 25.06.2015 Pros Implies low costs for the regulator Lower requirements on the know-how of the regulator Low risk of underestimating the costs The pros and cons of FAC/FDC Cons Information asymmetries in combination with principal-agency problems makes it hardly possible for the regulator to approve the data delivery from the operators Difficulties to define and quantify the allocation keys Difficulties to exclude inefficiencies Implies high costs for the operators Updates of the cost models implies extensive work Intransparent regulation as most data is not public 11

12. Cost base: FAC/FDC vs. LRIC 25.06.2015 Pros Incentives for operators to minimize costs Excludes historic developments and sunk costs Excludes inefficiencies The pros and cons of LRIC Cons Enables bottom-up modelling  Less principle-agency problems Implies low costs for the operators (due to limited data gathering) Updating the cost models is relatively easy at a low cost Requires extensive knowledge for the establishment of the cost models in order to assess all relevant costs Implies high costs for the regulator Difficult to assess the incremental cost and to exclude inefficiencies in a top- down model Risk of underestimating the costs 12

13. Cost base: FAC/FDC vs. LRIC 25.06.201513 * High setup costs but low costs of operation of the cost model Characteristics of modelling in small countriesFAC/FDCLRIC Smaller networks but more detailled modelling-++ Small or no backbone / simple backhaul+++ Low transmission costs+++ High proportion of OPEX++-- Cost constraints on modelling---* Challenging market situation for regulators+/- Direct communication++ Small capacities at regulated operators---

14. Top-down vs. Bottom-up and HCA vs. CCA 25.06.201514 FAC/FDC Top-down as bottom-up is hardly possible Both HCA and CCA are available (Decision should depend on the age of the networks, historic development and development of equipment prices etc.) LRIC Top-Down or bottom-up decision depends on aspects like the support from the operators and their accounting departments, certainties about inefficiencies and the definition of cost centers and services etc. Based on the simplier network design in small countries, a bottom-up approach is often more appropriate for small countries LRIC as cost standard is generally to be used with CCA Decision on top-down vs. Bottom-up as well as HCA vs. CCA depends inter alia on the decision on FAC vs. LRIC

15. „Building the network“ within the model 25.06.201515 1-3 core sites (switches and MSCs) – limited backbone Simple star-formed backhaul network Low traffic volumes Short distances Characteristics of networks in small countries More detailed models required as the „law of large numbers“ does not apply. Importance to downsize the networks (including number of nodes) in order to increase utilization. Redundancy problems have high impact on costs Compression is no large issue Implications for the network modelling

16. Modelling must be aligned with available data 25.06.201516 Garbage in – garbage out A cost assessment based on modelling can never be better than the quality of the inputs. If the model is more detailed than the availbale input variables, the outcome has no quality! 1. The cost modelling must be aligned with the data gathering process 2. Cost models must be adapted to each country 3. Tailormade cost models have a higher quality

17. Content 25.06.201517 Introduction Establishing Cost Models in Small Countries Doing Cost Assessments in Small Countries Summary

18. Definition of the „operator“ to be modelled 25.06.201518 Multiple real operators The costs are modelled for all regulated operators Assessment is time consuming as all operators must deliver input data Benchmarks are less required as multiple input are delivered nationally One real operator The costs are modelled for one operator and results are used for all market participants Assessment quality and time needed rely on the one operator Benchmark data can be used to a limited extent Hypothetical operator The cost models are fed with input data for a virtual hypothetical operator Enables easy use of benchmark data Assessment effort is relativ low as only one operator is modelled Decision depends on national conditions, e.g. the number of operators, legal situation, market situation, aims of the regulator, age of the networks etc.

19. General quality aspects of data gathering 25.06.201519 Garbage in – garbage out Understanding the deliverables Cross checking of the data Quality aspects Interaction with the operators has a large impact on quality. National adaptation of cost models required. Standardized cost models have the risk of lower quality. International benchmarking and triangulation in the data gathering required. Implications for the network modelling

20. International benchmarks Challenge to adjust data from large countries to small countries  i.e.for network equipment, OPEX ratios and other mark-ups International benchmarks Challenge to adjust data from large countries to small countries  i.e.for network equipment, OPEX ratios and other mark-ups Challanges regarding the data gathering in small countries 25.06.201520 Miscellanious 3rd party resources (consultancy studies, white papers, ITU sources) mostly done for large countries Miscellanious 3rd party resources (consultancy studies, white papers, ITU sources) mostly done for large countries Data Gathering from operators a) Small countries have few operators  Heavy dependency on existing operators and difficulties to assess the quality of data. b) Distance to operators is limited enabling intense contact with operators as long as these are managed nationally c) As operators and regulator are relatively small, the resources are limited Data Gathering from operators a) Small countries have few operators  Heavy dependency on existing operators and difficulties to assess the quality of data. b) Distance to operators is limited enabling intense contact with operators as long as these are managed nationally c) As operators and regulator are relatively small, the resources are limited

21. Content 25.06.201521 Introduction Establishing Cost Models in Small Countries Doing Cost Assessments in Small Countries Summary

22. 25.06.201522 Small networks and regulators accompanied by limited resources Required detailled modelling of networks (but therefore less modelling of backbone networks) Dependancy on a small number of operators to deliver input data Larger importance of OPEX relative to CAPEX than in bigger countries Cost modells in small countries

23. Summary 25.06.201523 High proportion of fixed costs due to low volumes and less economies of scale  Traffic sensitive models and costs Relatively high transmission costs due to low economies of scale Network quality drives costs to a large extent  The degree of redundancy rapidly leads to low utilization Relatively high OPEX due to low volumes No or low backbone costs Expected results from the cost assessment in small countries

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