Development of the Danish LRAIC model for fixed networks - - PowerPoint PPT Presentation
Development of the Danish LRAIC model for fixed networks Presentation of the 1st draft model February 2020 This document was prepared by Axon Consulting for the use of the client to whom it is addressed. No part of it may be copied or made
This document was prepared by Axon Consulting for the use of the client to whom it is addressed. No part of it may be copied or made available in any way to third parties without our prior written consent.
Presentation of the 1st draft model
Development of the Danish LRAIC model for fixed networks
February 2020
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This presentation is aimed at achieving a common understanding
and relevance of this regulatory process
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Procedures to respond to the 1st public consultation Description of the consultation materials Introduction to the model, its inputs and outputs Presentation of the model’s associated documentation Key differences with the current price decision Q&A session to address stakeholders’ concerns Improved alignment between all parties involved Easier reviewing process for service providers More accurate and relevant feedback Avoid misunderstandings
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Contents
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In accordance with the original timetable of the Project, the DBA has launched the 1st consultation with the industry on 3 February
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Phase
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Activity led by Axon/DBA
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Activity with support from stakeholders
Project Activities and Tasks Phase 1. Inception and development of the model's methodology 1.1 Development of the model's methodology 1.2. Public consultation on the model's methodology with the industry Phase 2. Data collection 2.1 Development of the data collection templates 2.2. First data collection process with Service Providers 2.3. (Potential) Second data collection process (equivalent process as for the first one) Phase 3. Development of the 1st draft model to be submitted for consultation Phase 4. Yearly update of the cost model and public consultations 4.1. 1st Consultation with the industry 4.2. 2nd Consultation with the industry 2019 2020 A M J J A S O N J J A D J F M A M
Project timetable as presented in the kick-off meeting held in May 2019
The 1st consultation on the model and its associated documentation has been launched on 3 February, in
line with the timings set in the Project’s timetable presented to the stakeholders in May 2019.
The 1st consultation process has been scheduled for 5 weeks. This means that stakeholders’ feedback is
expected by no later than 6 March 2020.
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The fixed LRAIC model submitted to consultation needs to be understood in the light of the MRP published in 23 October
6 The 1st draft fixed LRAIC model has been developed following the guidelines stablished in the Model
Reference Paper (MRP) published by the DBA in 23 October.
The MRP was already consulted from 1 July to 30 August. This consultation starting on 3 February is
therefore solely focused on the draft model and not the MRP. Illustrative excerpt of the MRP Illustrative excerpt of the position statement
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To answer to this 1st consultation process, stakeholders are invited to use the template included in the consultation document
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Illustrative excerpt of the template to comment
Service Providers are requested to disclose their position to each of the questions raised, together with their
comments and justifications.
DBA kindly requests that stakeholders state their position through the template provided.
# Category Question Position (Agree / Partially Agree / Disagree) Comments and justifications 1 Inputs Do you agree with the demand considered for the modelled operator? If you don’t agree, please justify your position and provide supporting information and references. 2 Inputs Do you agree with the coverage levels considered for copper, fibre and coax access networks? If you don’t agree, please justify your position and provide supporting information and references. … … ...
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Some additional indications to the provision of feedback to the 1st consultation process
8 All comments will have to be submitted by 6 March 2020.
consultation round will prioritize comments that are i) significant for the results of the model and ii) have been thoroughly justified.
Meeting 26 February 2020, deadline for prioritized questions 19 February 2020
DBA will circulate its answers to all questions received.
To provide you with the best answers (including relevant illustrations, examples etc), we urge you to send in questions before this date.
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The implementation of the model has been performed over two different software platforms to fully exploit their advantages
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R model Excel Model
Powerful tool that allows us to work with high
volumes of data:
The R model is used for the geographical
analysis:
The results from the R model are seamlessly
loaded into the main excel model.
Network dimensioning and costing algorithms
are implemented in the Excel model.
The model is fed with inputs from the R
model as well as with other inputs that are
demand).
The Excel model is mainly responsible for
costing the network and allocating the costs to the modelled services.
We expect most of the stakeholders’ review
efforts to be focused on the Excel model.
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The geographical model implemented in R calculates a set of key dimensioning indicators that are later used in the Excel model
The R model architecture is based on three main
blocks:
geographical conditions of Denmark (e.g. addresses, routes) as well as TDC’s network (e.g. nodes locations).
geographical analysis of the networks.
indicators such as the average distance of the local loop.
The R model can be controlled through a user-
friendly interface. The end-user does not need to get involved into R programming.
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Architecture of the R model
Calculations Inputs Results*
Address database Route database Coverage database Nodes locations Distribution of lines Coverage Equipment inventory and disaggregation Transmission characteristics
Note(*): The outputs of the R model are generated for each combination of geotype, region, regulation and dwelling type
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A complete version of the R Model with a sample dataset has been circulated with stakeholders as part of the 1st Public Consultation
While the sample R model shared with the
industry includes all algorithms employed, it has been loaded with inputs from only two random areas* in Denmark in order to:
modelled operator.
computationally intensive.
Stakeholders can analyse the algorithms in this
sample R model and assess the reasonability of the results produced for these two sample areas. The complete outcomes of the R model (although with some degree of anonymization) are available in the Excel model.
12 Note(*): Locations of the access nodes included in this area have been randomised as well.
Areas included in the sample version of the R model
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The outputs from the R model can be easily exported into the Excel model
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The Excel model follows a classical Bottom-Up approach, with three distinct blocks, to calculate the service-level results
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Architecture of the Excel model
Geographical inputs Location of network nodes Routes between network nodes Network footprint assessment Aggregation of the results into levels Results: Network costs of the services Market and network inputs Bottom-Up LRAIC Model architecture Resources Costing (CAPEX & OPEX) DIMENSIONING MODULE Access network Dimensioning drivers Copper Fibre Coax Transmission network L3 Access Aggregation Distribution Core
Inputs Calculations Outputs
The Excel model architecture is based
calculate the results. This includes the demand of the services, network information, among
characterize the network and calculate the costs of the network elements involved.
costs to services and presentation
levels of disaggregation.
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Inputs included in the Excel model have been anonymised to preserve confidentiality
The Excel model’s inputs which have been extracted
from the data provided by the modelled operator have been anonymised to preserve their confidentiality.
To anonymise these inputs, they have been generally
multiplied by a random factor between ±30% (and up to ±50% in some cases – e.g. demand forecasts –).
The inputs that have been anonymised are presented
in a red background so they are easily distinguishable.
The anonymisation of the inputs implies that the
results included in the model for consultation do not represent the actual figures handled by DBA.
Some of the real outcomes produced by the model
have been included in this presentation and in the consultation document.
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Illustrative example of anonymised inputs
Information about the chains in the aggregation network Chain code # of nodes Route length (km) % of traffic AGG-1 6 153 3,90% AGG-2 3 110 2,73% AGG-3 6 176 5,43% AGG-4 9 360 5,55% AGG-5 4 162 5,37% AGG-6 3 153 4,74% AGG-7 7 224 4,25% AGG-8 6 173 4,08% AGG-9 4 131 2,55% AGG-10 4 172 5,00% AGG-11 3 156 2,57% AGG-12 1 309 1,02% AGG-13 8 230 3,71% AGG-14 4 135 2,35% AGG-15 4 89 2,52% AGG-16 3 71 3,73% AGG-17 2 28 2,44% AGG-18 4 84 3,49% AGG-19 3 20 3,79% AGG-20 3 10 9,07% AGG-21 6 121 3,04% blank
93 3.067 81,35%
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The inputs considered play a key role in the determination of the model’s outcomes (unit costs per service)
The 1st draft model includes the inputs
that are representative of the modelled
However, if different inputs were used
(e.g. coverage, demand of another
the model would differ.
The control panel of the model
(“COVER” worksheet) allows the users to quickly select different sets of inputs
results (note: the “RUN” button needs to be pushed to assess how the new inputs will impact the model’s outputs).
Overview of the COVER sheet of the model
LRAIC Model for Fixed Networks
Control panel Execution mode Full execution Execution time 03:22 1 Input scenarios Demand scenario Base case selected.demand.scenario Copper shutdown year 2.030 selected.copper.shutdown GENERAL CHECK Annualisation of copper shut-down costs GRC annualised within active yearsOK
selection.annualisation.copper.shutdown Remove fully depreciated assets? Yes selection.fully.depreciated Percentage of fully depreciated assets 50% selection.fully.depreciated.percentage Annualisation methodology Economic Depreciation selection.annualisation.method WACC 4,54% input.wacc Risk premium 2,00% input.risk.premium Consider productivity factor? Yes selection.productivity.factorRUN
UPDATE KPIs
CONTENTS MAP
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Inputs (and thus, the results) of the model have been prepared to be representative of the current modelled operator (TDC)
Therefore, the 1st draft model, including its inputs (see section 3 of this presentation) and outputs (see
section 4 of this presentation), are so far only representative of TDC.
However, this situation could change in the future, as captured in the MRP:
“Nevertheless, if any other operator is also designated to have SMP in markets 3a and 3b, the model should be ready to assess its costs following the methodology described in this document.”
In such situation, while the structure and architecture of the Excel and R models would be preserved as
shown before in section 2 of this presentation, their inputs would be adjusted to reflect the operations of the new SMP operator. A different set of inputs would be developed for each modelled operator based on their actual data thus leading to different results for each SMP operator.
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MRP: “The modelled operator(s) should be, at all times, the SMP operator(s) in markets 3a and
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The model relies on four main categories of inputs to calculate the final results at service level of the modelled operator (TDC)
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Input Description Main sources
► Operators (TDC) ► Existing LRAIC model
Demand Demand of the services included in the cost model for the 2005-2038 period. Geographical inputs Network volumes in the different access networks (copper, fibre and coax).
► Roads and buildings data ► Network nodes (TDC)
Network inputs Inputs related to network parameters
► Industry constants ► Configuration of TDC’s
network Unit costs Unit CapEx, OpEx trends and useful lives of the network elements.
► Operators (mostly TDC) ► Existing LRAIC model ► International benchmarks
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Demand Unit costs Geographical inputs Network inputs
Disclaimer The figures included in this section have been anonymised with a random factor to protect data confidentiality. They are shown as in the Excel model
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±50%
Input Anonymisation Factor
±30% ±30% ±30%
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1,0 1,5 2,0 2,5 3,0 Access lines (MM) Copper Fibre Coax
We have defined the demand based on the data provided by TDC, distinguishing the lines to be supported by each access network
Service demand is one of the main
inputs of the cost model:
dimensioning of the transmission network as well as the final drop cabling.
the unit costs of the services.
As per the MRP
, each access network supports its own demand.
The demand of each service has
been anonymised independently of the others.
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Access lines in each access network*
Expected shut down in 2030 See next slide
Note(*): The number of lines included in this figure has been anonymised with a random factor to preserve the confidentiality of the data
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The model considers that, as a base case, the copper network could be switched-off in 2030
The exact year in which the copper
access network is going to be shut down by the modelled operator is unknown so far. As such, the copper switch off year is an input of the Excel model that can easily be adjusted by the user.
As a base case, the model considers
the copper network to be switched off in 2030. In all scenarios, we consider a copper shut down timeframe of 5
progressively disconnected from the copper network and switched to the fibre access network.
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Access copper lines under different switch-off scenarios*
1,0 1,5 2,0 2,5 3,0 Access lines (MM) Switch-off in 2030 No switch-off
Note(*): The number of lines included in this figure has been anonymised with a random factor to preserve the confidentiality of the data
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Data provided by the operators has been the main source to populate unit cost inputs
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OpEx CapEx
Type of cost Description Source
Unit CapEx
► Acquisition and
installation costs (DKK per element)
► Based mostly on information from TDC ► Crosschecked with data from other operators and
Axon’s international benchmark. CapEx Trend
► % of yearly change in
unit CapEx
► Operators did not provide this data. ► Input based on data from the existing cost model
and Axon’s international benchmark. Useful life
► Time for asset
depreciation (years)
► Operators provided only financial (book) data. ► Input based on data from the existing cost model
and Axon’s international benchmark. Unit OpEx
► Operational and
maintenance costs (%
► Operators provided limited data. ► Input from the existing cost model, Axon’s
international benchmark and KPIs from TDC’s AS. OpEx Trend
► % of yearly change in
unit OpEx
► Based on inflation data extracted from public
sources Percentage of labour costs
► Costs related to man-
work (% of OpEx)
► Input based on data reported by TDC (AS). ► These percentages are used to calculate the
weight of the productivity factor.
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The unit prices of copper and coax civil infrastructure assets have been adjusted to remove fully depreciated assets (1/2)
24 Based on the figures provided by TDC in its FAR, the percentage of fully depreciated civil infrastructure assets
in TDC’s copper access network has been estimated at around 36,8%*.
However, there are three main factors that could distort the representativeness of this figure:
FAR, but may have been in use by TDC in 2005. This could lead to this percentage being underestimated.
to the lack of any other information. This could probably lead to an overestimation of this percentage.
be preferred, but they were only used for regulatory purposes since the late 2000s. This means that TDC probably recovered most of the access assets’ costs beforehand based on its financial useful lives. The consideration of the regulatory useful lives, as proposed, may underestimate this percentage.
Taking all this into consideration, observations #1 and #3 would imply a higher percentage of fully
depreciated assets, while observation #2 would lower this percentage.
Note(*): Please see the main consultation document for further details on the calculation of this figure.
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The unit prices of copper and coax civil infrastructure assets have been adjusted to remove fully depreciated assets (2/2)
25 As a result of the uncertainty described in the previous slide, the model includes an option in the control
panel to define the percentage of fully depreciated assets. Alternatives included for this percentage are 30%, 40%, 50% and 60%. These alternatives have been defined in consistency with the BEREC’s benchmark on this matter.
As per the observations presented in the previous slide, DBA has considered the percentage of fully
depreciated copper and coax civil infrastructure assets to be 50% as a base case in the 1st draft model. This percentage has been considered when producing the results shown throughout this presentation.
However, we invite stakeholders to comment on (and justify) the percentage they consider to be more
representative for the modelled operator.
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Geographical inputs are used to calculate the passive infrastructure needs of the copper, coaxial, fibre and transmission networks
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►Addresses database. ►Routes database. ►Network nodes. ►Coverage (including forecasts) for each access network. Step 1: Input assessment
Excel Model
►Determination of routes between the network nodes and buildings. ►Calculation of the location of distribution points. ►Analysis of the quantity of network elements required. Step 2: Geographical analysis ►Definition of the existing geotypes. ►Assigning the corresponding geotype to each building. ►Aggregation of the network elements into each geotype. Step 3: Geotype aggregation
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Step 1: Input assessment. While addresses and routes’ databases are public, network nodes have been extracted from TDC’s data
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Network nodes Routes Identification of Buildings
Extracted from the DBA’s addresses database Extracted from the DBA’s routes database Extracted from the nodes database provided by TDC
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Step 1: Input assessment. The coverage footprint is defined separately for each of the three access technologies and is one of the key inputs
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Copper and coax
Input based on data from TDC. Coverage levels are constant in the modelling
period.
However, in order to avoid inefficiencies in
copper, we consider no CapEx reinvestment or OpEx continuity after the switch-off of a Central Office (CO). Fibre
Input based on data from TDC. Coverage expected to increase over time.
Coverage of the three access networks*
1,0 1,5 2,0 2,5 3,0 3,5 Homes connected (MM) Copper Fibre Coax
Note(*): The number of connected homes included in this figure have been anonymised with a random factor to preserve the confidentiality of the data
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Step 2: Geographical analysis. Based on these inputs, the R model calculates the volume of network elements needed in each access network
29 The final aim of the geographical analysis is to
calculate the number of passive network elements.
The network elements constitute the resources
needed in order to reach the coverage footprint of each access network in Denmark.
Examples of access network elements assessed in
the geographical analysis include cables, trenches and manholes, joints, splitters… All this information is calculated at building level.
The algorithms implemented in the R model are
thoroughly described in the descriptive manual (section 4).
Outputs Calculations Inputs
If # of homes passed Street Cabinet of 192 homes passed Street Cabinet of 384 homes passed Number of Street Cabinets of 384 homes passed Nº of SCs = Homes passed / Max.capacity of SC Number of homes passed per MDF SC sizes
< 192 homes passed > 384 homes passed Between [192,384] homes passedIllustrative algorithm used in the R model
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Step 2: Geographical analysis. In addition, the R model calculates the required transmission network based on TDC’s data
The transmission network is divided into
four different layers:
between the access and transmission networks (approx. 1000 nodes).
from the different L3 Access chains (approx. 90 nodes).
towards the core network (approx. 12 nodes).
enables full interconnection between all core nodes (4 nodes).
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Architecture of the transmission network
L3 Access Network L3 Access Node Agg. Network Distribution network Core network L3 Access Node
Core Router Core Router Access Network Access Network
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Step 3: Geotype aggregation. Data at building level is aggregated based on the region, building type, regulatory status and geotype
While the classification of the homes based on region, type of building and regulatory status is direct, we
performed a clustering analysis to categorise each central office into URBAN, SUBURBAN and RURAL.
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Disaggregation of the central offices into geotypes
10 15 20 25 50 100 150 200 Buildings covered by CO (‘000) Area covered by CO (km2) Rural Suburban Urban Region Urban Suburban Rural Hovedstaden 12,0% 26,0% 62,0% Midtjylland 0,9% 6,0% 93,1% Nordjylland 0,5% 4,1% 95,5% Sjælland 0,4% 4,8% 94,8% Syddanmark 1,1% 3,6% 95,3%
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Finally, a set of inputs characterizing the network is introduced in the Excel model and mainly used for dimensioning purposes
A number of different inputs are relevant in
network.
These inputs include, among others:
yearly consumption of a typical user in each access network
utilisation from each service (broadband, VoD, TV).
to properly account for multicast traffic.
These, along with other inputs, play a relevant
role in the calculations of the Excel model.
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Broadband traffic per line in each access network*
2.000 3.000 4.000 5.000 6.000 7.000 GB/active line/year Copper Fibre Coax
Note(*): Figures included in this exhibit have been anonymised with a random factor to preserve the confidentiality of the data
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4.1 Reconciliation of the number of assets and cost base 4.2 Service-level results 4.3 Comparability with the previous fixed LRAIC model
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We have successfully validated the reconciliation of the model’s results with TDC’s operational and financial data
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Type of reconciliation Description Sources Conclusion Resources
► The number of elements calculated by
the model is compared to the actual number of elements reported by the
► Reconciliation target: ±10% ► Volumes
reported in the Data Request
► Existing
LRAIC model
Cost base
► The reconciliation of the cost base
compares the costs of the model with those of the operator.
► Reconciliation target: ±10% ► Regulatory
accounts of TDC
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The reconciliation in terms of network elements is highly accurate compared to the figures reported by TDC
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10% 30% 50% Fibre Cable Trenches (km) OLT MSAN - PTP % variation
Copper networks* Fibre networks* Coax networks* Transmission networks*
10% 30% 50% Copper cable Trenches (km) MSAN MDF DP % variation
10% 30% 50% Coax cable Coax trenches CMC TAP Coax cabinet % variation
10% 30% 50% TX fibre Core router L3 router Subm. cable Landing stations % variation Consistent with coverage data Migration towards the chain config. Migration to DOCSIS 3.1
Note(*) References from TDC for the elements coloured in grey were not available. However, we compared the reasonability of these figures, when possible, with the results of DBA’s previous fixed LRAIC model.
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AS AS (exc. voice, mobile, etc.)* Cost base for reconciliation CapEx
To assess the reconciliation of the cost base with TDC’s data, we extracted its costs from an analysis of its AS information
TDC reported its Accounting Separation (AS)
results with a deep disaggregation for the year 2018.
This information included details on the OpEx
and CapEx from network elements associated to the copper, fibre, coax and core and transmission networks.
TDC already identified the voice costs that
should not be included in the reconciliation analysis of the model.
In addition, TDC provided descriptions that
allowed us to discard elements that were not relevant for the current modelling exercise (e.g. customer equipment or installation).
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Cost base from TDC’s AS
AS AS (exc. voice, mobile, etc.)* Cost base for reconciliation OpEx
Copper access Fibre access Coax access Transmission Mobile Other
Note(*): Categorisation of voice, mobile and other costs not relevant for the LRAIC model was provided by TDC.
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TDC Model TDC Model CapEx (Depreciation) OpEx Cost (MM DKK) Copper Fibre Coax Transmission
The reconciliation of the cost base shows reasonable outcomes for each network section, both in terms of OpEx and CapEx
CapEx reconciliation
To calculate a depreciation from the model that is
comparable to the one from TDC, the following adjustments have to be made in the model:
(without indexing) to all years of the model. OpEx reconciliation
No adjustments are performed to the base OpEx
produced by the model for the reconciliation.
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Reconciliation in terms of cost base
+3,9%
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4.1 Reconciliation of the number of assets and cost base 4.3 Service-level results 4.2 Comparability with the previous fixed LRAIC model
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Five key methodological factors hamper the comparability of the results between the current and the previous model
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Demand considered Fully depreciated assets Fibre access topology Network footprint Depreciation profile
The new model considers the actual network
footprint of each access technology, including rollout forecasts, instead of a full network coverage of DK.
Each access technology handles only the lines they
actually support. In the old model, the same total demand (sum of customers in TDC’s copper, coax and fibre networks) was considered in each network.
The actual mix between PTP/GPON from TDC is
considered in the new model. The previous model considered either all PTP or all GPON.
A new functionality to exclude fully depreciated
assets has been added for copper and coax access networks.
The current model adopts economic depreciation as
a base case, while the previous one mainly relied on tilted annuities. However, the new model can calculate cost based on tilted annuities.
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40 60 80 100 120 140 160 Copper Fibre Coaxial Homes connected (normalised)
The new model considers TDC’s actual footprint in each access network in terms of homes connected
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0% 100%
Impact at service level
► The results for each access network represent more accurately the costs borne by the modelled operator in
its deployment.
► In the case of fibre networks, the model calculates the costs of the areas where the operator has decided to
deploy its services. This leads to lower costs if the areas targeted are more urbanised than the average.
New model Previous model
Same footprint for all access networks
40 60 80 100 120 140 160 Copper Fibre Coaxial Homes connected (normalised) Footprint based on actual homes connected in each network
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40 60 80 100 120 140 160 Copper Fibre Coaxial Demand (normalised)
Similarly, the new model considers only TDC’s demand from each access network separately, instead of the same demand for all
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0% 100%
Impact at service level
► Linked to the consideration of the actual footprint of each access network, the model considers the actual
demand of the SMP operator in each access network, thus maximising the representativeness of the results
New model Previous model
Same demand for all access networks
40 60 80 100 120 140 160 Copper Fibre Coaxial Demand (normalised) Demand based on actual active lines in each network
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The new model considers the actual fibre topology deployed by the modelled operator in each area of Denmark
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0% 100%
Impact at service level
► The model calculates different unit costs for PON and PTP fibre services considering the economics of the
specific areas where they are actually provided.
New model Previous model
The model allowed two deployment alternatives:
As previously described, the model considers the
actual footprint of the SMP operator.
Further, the model considers that some areas
have been covered with a PTP topology and some
Finally, the model considers future deployments in
the basis reported by the modelled operator.
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The new model excludes the costs from the legacy passive assets in line with the requirements from the EC’s 2013 Recommendation
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0% 100%
Impact at service level
► The model calculates the costs for copper and coax access services considering only the assets from the
modelled operator that are not fully depreciated.
► This consideration implies lower unit costs compared to a purely Current Cost Accounting approach.
New model Previous model
The model did not consider any adjustment for
fully depreciated assets or any other adjustment required by EC’s 2013 Recommendation* as the methodology was developed before the publication of these guidelines.
As described in the MRP
, the model does not consider any costs from the fully depreciated assets located in the modelled operator’s copper and coax access networks.
Due to the relative uncertainty in the share of
fully depreciated assets, the model includes different percentages that can be selected by the user to assess their impact on the results.
Note(*): 2013/466/EU Commission Recommendation of 11 September 2013 on consistent non-discrimination
are relevant.
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The consideration of Economic depreciation in the model ensures even costs through the modelling period*
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0% 100%
Impact at service level
► The model considers an even cost throughout the modelling period, only affected by the unit cost trends. ► Compared to a tilted annuities approach, in the future, copper and coax unit costs should be higher (as
demand decreases) and fibre unit costs should be lower (as demand increases).
New model – Example for fibre networks Previous model – Example for fibre networks
2018 2020 2022 2024 2026 Demand and unit cost Unit cost (tilted annuities) Demand 2018 2020 2022 2024 2026 Demand and unit cost Unit cost (econ. depr.) Demand Demand based on actual active lines in each network
Note(*): Only affected by the cost trends introduced for the unit prices of the assets. In this exemplification the cost trend is set to zero and the unit cost is constant (horizontal line).
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4.1 Reconciliation of the number of assets and cost base 4.3 Service-level results 4.2 Comparability with the previous fixed LRAIC model
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The model presents results for two main sets of services
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Recurring Services
Unit costs of the services are presented for the modelled period
(2005-2038). Results may be presented under any desired combination of geotypes.
Consistently with the price scheme in DBA’s Price Decision, the
unit costs of the services are presented as DKK/service/year. Non-Recurring Services
Non-Recurring services (also referred to as ancillary services) are
those that are often needed in the provision of recurring services (e.g. installation for VULA services).
The results of the Non-Recurring services are presented for the
period modelled (2005-2038). DISCLAIMER: The results presented in the next slides (real outcomes obtained by DBA) differ from the outcomes of the Excel model as its inputs have been anonymised.
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The model calculates the results for recurring services from 2005 to 2038. These are presented in worksheet 8A of the model.
48 One of the main objectives of the model is to
calculate the costs of the recurring services.
Some of these services, such as VULA or LLU
are often the most relevant in the development of fixed bottom-up models.
The results are presented in a tabular view
that shows the unit costs of the different services for any desired combination of:
Results of recurring services in the model*
Note(*): Results presented in this table are only illustrative as they have been anonymised.
Region All Degree of urbanisation All Type of building All Regulated areas All Service Units 2005 … 2017 2018 2019 2020 2021 2022 … 2038 Access.Copper.Wholesale.VULA (POI0) DKK / Lines / Year 695 … 890 911 933 954 976 1.000 …
(POI1) DKK / Lines / Year 725 … 927 949 971 993 1.015 1.040 …
…
access (POI0) DKK / Lines / Year
796 806 819 834 857 870 … 1.164 Access.Fibre.Wholesale.Raw access (POI1) DKK / Lines / Year
1.206 1.220 1.236 1.255 1.282 1.300 … 1.683 Access.Fibre.Wholesale.VULA access (POI1) DKK / Lines / Year
985 993 1.003 1.016 1.037 1.048 … 1.317 … …
Access (POI2/POI3) DKK / Lines / Year 524 … 586 593 602 612 622 632 … 935 … …
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rental, fibre the highest, and copper lines fall in between
49 Dynamics in the footprint and
demand of the operator, as well as the characteristics of coax access networks, make the coax access units costs be the lowest.
Both copper and coax unit costs
are affected by the removal of fully depreciated assets, while fibre unit costs are not.
The upward trend of the results is
linked to the expected increase in the unit prices of the assets (price trends). Costs for copper are expected to raise faster due to the higher cost trend for copper cable compared to fibre and coax.
Unit costs of copper, coax and fibre access under real conditions*
400 600 800 1.000 1.200 1.400 1.600 1.800 DKK/line/year Raw copper Raw fibre (POI1) BSA coax (access only)
Expected shut down
Note(*): Figures are representative of the average of all geotypes
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and footprint, lead to lower costs for coax compared to copper
50
Concept
Geographical footprint Customer take-up
Copper
Nation-wide network, reaching most rural areas Medium-level take- up, but rapidly decreasing over time.
Fibre
New network, reaching mostly urban areas Lowest take-up compared to copper and coax, but increasing over time.
Coaxial
Network with roughly half the reach of copper. Gap in rural areas Highest take-up compared to copper and fibre, but decreasing over time. The diverging characteristics of each access network generate differences in their unit costs that go beyond the economics of each technology. In particular, the key divergences are identified in the coverage of these networks (nationwide copper, with fibre located in urban areas and a rural gap in coax) and their take-up. If the same take-up and footprint was considered for all three networks, the highest unit costs would be
CONFIDENTIAL
875 972 1.013 490 915 993 1.255 612 834
400 600 800 1.000 1.200 1.400 1.600 1.800 2.000 Raw Copper VULA Copper (POI1) Raw Fibre Coax BSA (access only) DKK/line/year Price decision Model unit cost Model unit cost (PON fibre)
for copper, albeit visibly below for fibre
51
Model Results vs Price Decision 2020 +5%
+25%
Note(*): Difference compared to a PTP-based service Note(*): Figures for Coax BSA have been extracted from the old access model (considering only passive network elements), as they are not included in DBA’s price decision.
Price inside the DONG Area Price in the rest
+24%* +2% ** Model unit cost (PTP fibre)
CONFIDENTIAL
unit costs obtained compared to the 2020 Decision
52
Fibre access topology Demand considered Network footprint Depreciation profile Fully depreciated assets
Explanation
► As there is an almost nation-wide
coverage of copper, this factor only generates a minor difference.
Impact
► A slightly higher demand considered in
the previous model leads to higher unit costs in the new model.
► This aspect does not apply to copper
networks
N/A
► The removal of fully depreciated assets
lowers the overall cost base for copper networks
► The Economic Depreciation leads to
lower costs than tilted annuities in the year 2020.
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and old MRP explain most of the differences in FTTH unit costs
53
Fibre access topology Demand considered Network footprint Depreciation profile Fully depreciated assets
Explanation
► TDC’s fibre footprint does not include
remote (expensive) areas, lowering the costs compared to the old model.
Impact
► Only demand for fibre is considered in
the new model, which leads to higher unit costs compared to the old model.
► TDC’s deployment with fibre nodes
closer to the end user leads to lower access unit costs in the new model.
► This does not apply as the fibre
network is modelled following a purely CCA approach.
N/A
► Economic depreciation leads to lower
costs than tilted annuities in 2020, but higher unit costs in the following years.
CONFIDENTIAL
per access network is explained by their footprint
The unit costs obtained for copper
networks are higher than for its coax and fibre counterparts.
This may be counter-intuitive, as
the traffic in fibre and coax networks is higher than in copper networks.
This situation is driven by the
different footprint of each technology (for instance, there is no fibre in remote areas, where transmission costs are higher) which, in turn, results in an uneven allocation of transmission costs.**
54
Unit costs of copper, coax and fibre bitstream lines*
100 150 200 250 300 350 DKK/line/year Copper Fibre Coax
Note(*): In each year, the cost per line is calculated based on the average uncontended broadband speed for that year. Access costs are not included Note (**): Additionally, the increasing share of copper and coax lines located in rural areas, explains the rising cost trend exhibited by these services (as the unit costs for these services are higher in rural areas than in urban areas).
Start of the copper shutdown
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considered, copper would become the cheapest option
In this case, the differences
between technologies is easily explained by the average consumption per line in each access network.
The cost per uncontended Mbps
decreases rapidly as the network is ready to handle more capacity.
As traffic consumption per line
tapers-out, cost per line becomes relatively flatter over time.
Note that this does not represent
the actual scenario considered in the model (the previous one is).
55
100 150 200 250 DKK/line/year Copper Fibre Coax
Unit costs of copper, coax and fibre bitstream lines*
* In each year, the cost per line is calculated based on the average uncontended broadband speed for that year.
Start of the copper shutdown
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the regulated prices for 2020, especially for fibre
56 Note(*): Difference compared to PTP-based bitstream Note(**): The cost per line is calculated based on the average download consumption per user for that year based on the inputs presented in slide 29. Figures include access costs
1.028 1.109 2.061 2.156 1.149 1.199 1.948 1.987 1.123 1.162
1.000 1.500 2.000 2.500 3.000 3.500 Copper BSA (layer 2) Copper BSA (layer 3) Fibre BSA (layer 2) Fibre BSA (layer 3) DKK/line/year Price decision Model unit cost (Copper) Model unit cost (PON Fibre) Model unit cost (PTP Fibre) Model Results vs Price Decision 2020** +12% +8%
In fibre, differences are explained by the factors described in previous slides
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The model also calculates the unit costs of non-recurring services from 2005 to 2038. These are available in worksheet 8B.
57 The non-recurring and supporting services
currently defined in DBA’s price decision are included in the cost model.
The calculation of these services is relatively
straightforward, considering the staff costs, the time required to perform each activity and any additional CapEx involved.
The model considers trends for CapEx, the
salaries and a productivity gain.
The inputs have been mostly based on data
from the existing model, as TDC decided not to update most of the parameters.
A proposed increase of +20% in technician
costs by TDC was rejected as no justification was provided for this increase.
Results of non-recurring services in the model*
Service Service Identifier 2005 … 2017 2018 2019 2020 2021 2022 2038 Migration Services.From Raw/Shared Copper to BSA/VULA 5.5.2.1 226 … 230 233 232 232 232 232 … 237 Migration Services.From BSA/VULA (without PSTN) to Raw Copper 5.5.2.2 266 … 270 273 272 272 272 273 … 277 Migration Services.From BSA/VULA (without PSTN) to Shared Copper 5.5.2.3 210 … 214 216 215 215 215 216 … 220 Migration Services.From BSA (without PSTN) to BSA (with PSTN) 5.5.2.4 72 … 73 74 73 73 73 73 … 74 … … … … … … … … … … … … Installation.New installation (unassisted) – eBSA 5.6.2.4 463 … 471 476 474 474 474 475 … 484 Installation.New installation (unassisted) – VULA 5.6.2.5 429 … 435 440 439 438 439 440 … 447 Installation.New installation (unassisted) – Raw Fibre 5.6.2.6 389 … 395 400 398 398 398 399 … 406 … … … … … … … … … … … …
Note(*): Results presented in this table are only illustrative as they have been anonymised.
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198 668 534 692 211 712 569 692
200 300 400 500 600 700 800 900 1.000 Migration Services (From Raw/Shared Copper to BSA/VULA) New installation (engineer assisted) – Raw Copper Visit by a technician Interconnection of fibre pairs in optic distributor between points termination (backhaul) DKK/line/year Price decision Model unit cost
Absence of key changes in the inputs/calculations of non-recurring services causes results to be in line with the regulated tariffs
58
Model Results vs Price Decision 2020 +7% +7% +7%
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59
Manager
gonzalo.arranz@axonpartnersgroup.com
Gonzalo Arranz Principal
alfons.oliver@axonpartnersgroup.com
Alfons Oliver
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