MBA Thesis 2007 Bela Varkonyi

University of Pécs Faculty of Business and Economics MBA Program

Financial Models for IMS Based Services

MBA Thesis

Author: Bela Varkonyi

Thesis Supervisor: Zsolt Bedo Assistant lecturer

Pécs, 2007.


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Contents

1 Introduction...............................................................................................................1 2 Business Impact of IMS Services .............................................................................2

2.1 IMS Overview................................................................................................... 2 2.1.1 Mobile 3G Technologies........................................................................... 2 2.1.2 IP Multimedia Subsystem History............................................................ 4 2.1.3 Next-Generation Networks ....................................................................... 6 2.1.4 Convergent Networks ............................................................................... 7 2.1.5 Next-Generation Operation Support Systems........................................... 9 2.1.6 Next-Generation Business Support Systems .......................................... 10

2.2 New Business Models in Telecommunications .............................................. 12 2.2.1 IMS Value Chain .................................................................................... 12 2.2.2 Technology Innovation Impact ............................................................... 13 2.2.3 Structural Changes .................................................................................. 14 2.2.4 Customer Models .................................................................................... 16 2.2.5 Supplier Models ...................................................................................... 18

3 Existing Financial Models in Service Management ...............................................21 3.1 Financial Control of Service Development ..................................................... 21

3.1.1 Business Development Planning............................................................. 21 3.1.2 Service Development Planning............................................................... 23 3.1.3 Investment Business Case ....................................................................... 25 3.1.4 Investment Decisions .............................................................................. 28 3.1.5 Project Controlling .................................................................................. 30

3.2 Financial Control of Service Operations ......................................................... 31 3.2.1 Revenue Monitoring ............................................................................... 31 3.2.2 Cost Monitoring ...................................................................................... 32 3.2.3 Benchmarking ......................................................................................... 34 3.2.4 Profitability Analysis .............................................................................. 35 3.2.5 Service Termination Decision................................................................. 35

3.3 Existing Modeling Tools................................................................................. 36 3.3.1 Excel Worksheets.................................................................................... 36 3.3.2 Modeling Software.................................................................................. 36 3.3.3 Business Intelligence Applications ......................................................... 37

4 Financial Models for IMS Services ........................................................................38 4.1 Business Model............................................................................................... 38

4.1.1 Revenue Structures ................................................................................. 39 4.1.2 Cost Structures ........................................................................................ 39 4.1.3 Cost Dependencies .................................................................................. 40 4.1.4 Key Performance Indicators.................................................................... 41 4.1.5 Time scales.............................................................................................. 41

4.2 Investment Decision Models........................................................................... 42 4.2.1 Overview of Evaluation Methods ........................................................... 42 4.2.2 Discounted Free Cash-Flow.................................................................... 44 4.2.3 Economic Value Added .......................................................................... 47 4.2.4 Cost-Benefit Analysis ............................................................................. 48


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4.2.5 Real Options Analysis .............................................................................49 4.2.6 Scenarios .................................................................................................51

4.3 CAPEX Planning.............................................................................................51 4.3.1 Project Portfolio Management ................................................................51 4.3.2 Periodic Reviews .....................................................................................52 4.3.3 Procurement Controls..............................................................................53 4.3.4 Savings Campaigns .................................................................................54

4.4 OPEX Planning ...............................................................................................54 4.4.1 Service Portfolio Management ................................................................54 4.4.2 Enforcing Savings ...................................................................................54

4.5 Investment Performance Evaluation ...............................................................55 4.5.1 Financial Profit-and-Loss Analysis .........................................................55 4.5.2 Economic Value Added Calculations .....................................................55 4.5.3 Application of Benchmarking .................................................................56

4.6 Proposed Modeling Tools ...............................................................................57 4.6.1 Available Modeling Tools.......................................................................57 4.6.2 Excel Workbook Requirements ..............................................................57 4.6.3 Software Technology Requirements .......................................................59 4.6.4 Reference Implementation ......................................................................60 4.6.5 Modeling workflow.................................................................................60

5 Application of Financial Models for IMS Services ............................................... 63 5.1 General Templates for IMS Services ..............................................................63 5.2 Video sharing ..................................................................................................63 5.3 Presence and network address book ................................................................64 5.4 Instant messaging ............................................................................................65 5.5 Push-to-talk .....................................................................................................68 5.6 Presence based IP telephony (voice and video) ..............................................71 5.7 Mashup services ..............................................................................................72

6 Summary ................................................................................................................ 73 6.1 Current Practice in IMS Financial Modeling ..................................................73 6.2 Proposed Financial Modeling Solution...........................................................74 6.3 Further Study...................................................................................................75

7 References ................................................................................................................. I 8 Appendices............................................................................................................... 1

8.1 Implemented Financial Models .........................................................................1 8.2 Users Guide.......................................................................................................3

8.2.1 Workbook structure ...................................................................................3 8.2.2 Naming conventions ..................................................................................4 8.2.3 Color coding and other visuals..................................................................5 8.2.4 File linking ................................................................................................6 8.2.5 Self-audit tools ..........................................................................................6 8.2.6 Exception handling....................................................................................7

8.3 Content of the Attached CD..............................................................................8


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List of Figures

Figure 2-1. Power efficiency of VoIP ............................................................................... 4 Figure 2-2. Uptake of IMS Services ................................................................................. 5 Figure 2-3. Simplified view of Common IMS.................................................................. 7 Figure 2-4. New IMS value chain................................................................................... 12 Figure 2-5. Service architecture evolution...................................................................... 14 Figure 2-6. New revenue and cost charateristics in IMS ................................................ 15 Figure 2-7. Value-based pricing opportunities ............................................................... 16 Figure 4-1. Arvetica business model framework ............................................................ 38 Figure 4-2. Arvetica BMF example: Skype .................................................................... 39 Figure 4-3. Modeling workflow overview...................................................................... 62 Figure 5-1. Video sharing architecture ........................................................................... 64 Figure 5-2. Presence architecture.................................................................................... 65 Figure 5-3. IMS PIM architecture (SIMPLE) ................................................................. 66 Figure 5-4. IM client enabled handsets forecast ............................................................. 68 Figure 5-5. IMS OMA PoC architecture......................................................................... 69 Figure 5-6. Push-to-anything roadmap forecast.............................................................. 70 Figure 5-7. IMS presence based telephony architecture ................................................. 72


Bela Varkonyi Financial Models for IMS Based Services 1

1 Introduction In the last few years a new major trend has been emerged in the mobile tele-

communications sector: the preparation for the introduction of IP Multimedia Sub-

system (IMS) based services. One of the biggest issues is to find the proper schedul-

ing of such service deployments and commercial rollouts. After the service introduc-

tion a strict financial control is needed to achieve the established business goals. All

these activities shall be based on a reliable financial modeling framework.

There are also regulatory requirements that necessitate the use of detailed fi-

nancial models for IMS services. The Sarbanes-Oxley (SOX) law or similar corpo-

rate governance legislation are applicable to most big telecommunications companies

and mandate the top management to take personal responsibility for the transparent

operations of the company. It is also important to document the costs behind product

prices, since most of these enterprises were monopolies in the recent past, so they are

heavily regulated by the national and international telecommunications authorities.

As a consequence, investment decisions and service performance shall be docu-

mented not just to satisfy the controlling needs of the company owner, but also to

support the compliance to the various regulations.

In this study we will make an overview of business process and financial con-

trol frameworks used at mobile operators. Based on this overview we will determine

the detailed requirements for the financial modeling of IMS services. Then we will

analyze the possible methods for this modeling, and finally we will propose a rec-

ommended solution. The selected models will be implemented using spreadsheets

and we will show some examples how these models could be used in the lifecycle

management of IMS services.

The following main financial model categories will be investigated:

• Future return on investment for service introduction decisions

• Service revenue forecasting

• Annual CAPEX planning

• Annual OPEX planning

• Activity based costing for common infrastructure and support environment

• Opportunity costs


Financial Models for IMS Based Services Bela Varkonyi 2

• Cost savings

• Total cost of ownership forecasting

• Total cost of ownership historical analysis

• Service revenue synergies, dependencies, corrections

• Total service revenue measurement

• Analysis of historical return on investment for performance evaluation

• Financial value of existing IMS infrastructure, support environment, and ser-

vice capabilities

• Financial risk management

In this study we will analyze the following IMS based services:

• Video sharing

• Presence

• Instant messaging

• Push-to-talk

• Presence based IP telephony (voice and video)

The scope of the study is limited to propose solutions for those issues that are

really relevant to IMS services. As this is a new technology and quite complex in its

details, most controlling departments are not ready to handle the special aspects of

IMS services. In this study we will focus on those tasks only that could be assigned

to technology departments, and in some way to marketing and business development

departments. We will intentionally not deal with such items as financing decisions,

deriving calculative rates, managing financial risks, etc. This is left to the financial

departments and follows well established practices that would not change by the in-

troduction of IMS services.

2 Business Impact of IMS Services

2.1 IMS Overview

2.1.1 Mobile 3G Technologies

[3G Americas 2006] summarizes the trends in mobile 3G technologies put-

ting the emphasis on quick uptake in HSPA technologies (HSDPA and HSUPA) cre-



ating a true wireless broadband experience comparable to ADSL. Recently the reve-

nue contribution of data services jumped over 20% and may reach up to 50% in some

cases because these higher speeds attract a lot more customers then the previous

GRPS and EDGE solutions capable only to provide ISDN speeds.

The higher speeds of HSPA enable real multimedia applications while the

lower speeds of GPRS and first generation UMTS were not really adequate for video

content. One way video download streaming became quite popular in various types

of mobile TV offerings, but only HSDPA provides enough bandwidth that matches

the user expectations. UMTS video services proved to be a big failure, especially the

circuit-switched video telephony. Packet-switched solutions would not help on the

problem, since in 1st generation UMTS the maximum uplink speed is 64 Kbit/s, the

same as with circuit-switched video. Even with HSDPA the uplink is maximum 384

Kbit/s that is just the same as legacy ISDN video conferencing. Only with HSUPA it

becomes possible to make good quality peer-to-peer video streams. HSUPA will

become a general commercial service in Hungary only by the end of 2007.

In classical mobile telephony voice services are provided by circuit-switched

(CS) technology, while data services are provided by packet-switched (PS) techno l-

ogy. The major difference is that statistical multiplexing might result in better re-

source utilization in the packet-switched domain. Without getting lost in technical

details we have to note that CS and PS approaches might be combined in the multiple

overlays in a complete networking solution. However, based on the economics of

larger scales and tighter competition the clear winner is the IP protocol and classical

TDM and recent ATM technologies are being phased out. Replacing old CS tele-

phone exchanges requires new IP based softswitches. Here the dominant protocol is

SIP, and IMS is also based on the extension of the more than decade old SIP stan-

dards.

Rysavy and 3G Americas 2007) emphasizes that HSPA is the enabler tech-

nology for the migration to IP based mobile solutions. It has enough capacity to sup-

port multiple customers in a cell to use VoIP services. As [3G Americas 2007] ex-

plains without the higher uplink capacity of HSUPA large scale VoIP over cellular

services would not work. The statistical multiplexing nature of IP traffic leads to

interesting consequences. In [Figure 2-1] we can illustrate that the power utilization

improves by migrating to VoIP and thus improving cost effectiveness. Another typ i-



cal example for potential cost savings is mentioned in [3G Americas 2007] when

introducing HPSA+ proposals for the one-tunnel architecture. The current RNC and

Node B might be merged together, and the SGSN can be reduced to control plane

functions. User plane resource will be handled only by the GGSN and the NodeB.

Figure 2-1. Power efficiency of VoIP

Source: [Rysavy and 3G Americas 2007]

In the next few years UMTS Release 8 development and standardization will

show a significant progress as described in [3G Americas 2007]. The core network

will become all IP and the Evolved Packet System (EPS) will be even simpler than

the HSPA+ One-Tunnel Architecture. The Long-Term Evolution (LTE) radio tech-

nology will increase the access speeds into FastEthernet regions, so we could see a

user experience similar to today’s local area networks.

2.1.2 IP Multimedia Subsystem History

UMTS appeared first in the form of 3GPP Release 99 radio network where

the circuit-switched and packet-switched domains are totally separated. 3GPP Re-

lease 5 introduced the so called “IP Multimedia Subsystem” or IMS. IMS is layered

on top of the packet-switched domain. There was a quick progress of newer IMS

definitions in Release 6 and Release 7 of UMTS. However, mobile radio networks

are still mostly at Release 99 only, and just recently migrating to Release 4. [3G

Americas 2006] and [Rysavy and 3G Americas 2007] describe a lot of future en-

hancements to the mobile radio network, but we have to emphasize again, that these

are just on paper and cannot be implemented yet in real life.



In 2004-2005 there were a lot of claims that IMS would quickly replace the

aging circuit-switched services. However, classical telecommunications vendors

(Ericsson, Nokia Siemens, Alcatel-Lucent, Nortel, Huawei, etc.) were not quick to

throw out their investments and most operators were convinced to do an interim step

using 3GPP Release 4 network technologies. IMS theoretically opened up the com-

petition by enabling IT and IP networking vendors to break into the telecommunica-

tions equipment market. HP, IBM, Cisco Systems, and many smaller companies

hoped to benefit from IMS, but up to now most of them failed miserably. The classi-

cal telecommunications vendors attacked back by grabbing most of the IMS con-

tracts, so they could control timing and recapture investments in older technologies.

To get the contracts they showed how big the potential cost savings are when moving

voice services from the CS to the PS domain. Once they realized the big potential

competition they cut back in IMS terminal development efforts and lowered the

prices of Release 4 equipment significantly to catch most of the advantages in an

area where the new competitors could not play. They also slowed down standardiza-

tion progress (the most notable example is the JSR-281 API).

Figure 2-2. Uptake of IMS Services

However, the IMS projects started in 2005-2006 at the dominant operators

starts showing some results in the near future [Figure 2-2]. There are some initial

commercial IMS services already on the market (Softbank in Japan and AT&T Wire-

less in the USA). The first IMS technology based services earlier rolled out by TIM,

Italy or TMN Portugal, or Telefonica, Spain are not considered as true IMS solu-



tions, since they are still vertical silos and do not implement the shared infrastructure

concept of IMS. According to expert estimates, as soon as good commercial grade

IMS terminals will become more available in 2008 a lot of operators will launch IMS

services.

In mobile networks IMS will be used first for value-added services (VAS)

and not for replacing the current voice offerings. Such services might include video

sharing, presence and instant messaging, push-to-talk, etc. Classical CS telephony

currently provides some quality-of-service guarantees, while the new IMS based PS

telephony solutions cannot, since the classical telecommunications vendors inten-

tionally do not implement the necessary modifications in the mobile radio and core

networks. This practically blocks the distribution of both IMS and other VoIP com-

petitors such as Skype, GoogleTalk, MSN, Fring, Gizmo, etc.

IMS is also not a mature, finished technology. A lot of further development is

still needed before it can fully replace older CS solutions. As [3G Americas 2006]

reviews it, the major development areas are: fixed broadband access to IMS (FBI),

IMS multimedia telephony enabler (MITE), combining CS and IMS (CSI), policy

and charging convergence (PCC), and voice call continuity (VCC). That means that a

lot of investments will be done into IMS even at operators who already started with

IMS. These investments might peak out in 2010-2012 and then slowly degrade once

the new build outs are finished. We agree with [3G Americas 2006] that the trans i-

tion to PS only mobile networks, and thus IMS, may end up only in 2017 or even

later.

2.1.3 Next-Generation Networks

[Jaffe 2004] identifies the fundamental changes in telecommunications for the

beginning of the 21st century stating that carrier-grade VoIP and new service enablers

are the same level as the truly revolutionary nanotechnology. These new telecommu-

nications technologies are also called “Next-Generation Network” or NGN. It was

first standardized in the ETSI TISPAN project. The core element of TISPAN NGN is

the 3GPP IMS. Some extensions were added to handle the special needs of fixed- line

networks. However, in 2007 the NGN standardization efforts were merged between

ETSI and 3GPP resulting in the “Common IMS” concept [Figure 2-3], so from Re-

lease 8 of UMTS the two standards will be unified as noted by [3G Americas 2007].



Figure 2-3. Simplified view of Common IMS

Source: [3G Americas 2007]

One of the biggest issues in classical fixed- line networks is that the customer

cannot be identified clearly in classical telephony. The authentication is done by a

physical location basis and the same terminal is used by multiple persons (for exam-

ple a family). In mobile telephony the devices are related to individua ls and the basic

assumption is that the device belongs to a well identified person. This is supported by

the usage of UICC cards with SIM, USIM, or ISIM modules. The fixed- line NGN

might need to keep compatibility with the legacy telephony services, so introducing

SIM authentication would be a big problem. These types of cultural differences make

it very difficult to fully merge fixed- line and mobile networks. With the new “Com-

mon IMS” approach such differences will be accommodated as dynamically man-

ages options configurable per subscriber or user identity.

Another important new proposal is the Next Generation Mobile Network

(NGMN). This new mobile technology will provide all the necessary elements that

are still not enough good for reaping the full benefits of IMS. Promises include a

much better QoS (optimized for IP networks), an efficient always-on support, and

seamless mobility [Akhavan et al. 2006]..

2.1.4 Convergent Networks

One of the current telecommunications industry trend is convergence. It is

happening in multiple dimensions. On the business level, a lot of fixed operators

merged backed its mobile arms. One of the early runners was Telecom Italia, and

such major companies followed as France Telecom. Currently Magyar Telekom is



also going through such reorganization. This means that separate mobile and fixed-

line business unit will cease to exist and new units will be organized around retail

and business customer market segments.

This business trend is enabled by the convergence of network technologies.

All telecommunications services will migrate in the future to IP protocol based solu-

tion. The most notable example is the British Telecom 21CN project. The new ne t-

work changes the vertically separated silos into a horizontally layered unified archi-

tecture. At the lowest layers different access technologies will still proliferate, but as

move up a common IP network will be used for general network transport. Some

argue that operators should stop here and let the services to be offered by third-

parties like Google, Yahoo, Microsoft, etc. The IMS/NGN concept goes against this

Internet trend. It supports the survival of the intelligent network model that worked

so well for the telecommunications companies for decades. IMS provides a common

control plane for a big range of applications in the PS domain. From UMTS Release

8 even CS domain services could be controlled by IMS as foreseen by [3G Americas

2007]. IMS Centralized Services (ICS) will be a big turning point in replacing cur-

rent network architectures, but it may take another decade to get there. The conver-

gence of the control plane promises a significant reuse of resources and thus potential

cost savings. Increased reuse may also help to get faster adaptation to ever changing

market conditions.

We may also expect a convergence in security solutions. The UICC card is

the clear winner among all kind of security devices if look at the numbers of mobile

customers. [3G Americas 2007] summarizes those new features coming in UMTS

Release 8 that would make a convergence based on UICC even more likely. The fu-

ture UICC cards will have gigabytes of memory and near- field contact (NFC) possi-

bilities. The later feature has started to replace credit cards in Japan already and will

come even to in Hungary very quickly.

On of the biggest problems with authentication and authorization algorithms

that we cannot rely on the CPU environment where the software is executed in a

general PC environment. The only reliable solution is when the authentication be-

tween the network and terminal is done by a hardware protected special device like

the UICC where only strictly controlled software could be run. Practically each PC

or mobile handset will have minimum two independent CPU environments: one to



run the application and another on the UICC to run the security algorithms. Currently

the only technology that can open up the UICC authentication and authorization pos-

sibilities in standard way is the IMS. The Advanced IMS proposal brought up in Au-

gust 2006 is based on this recognition and plans to extend the IMS architecture onto

other protocols than the current SIP.

IMS is also a way to converge in the standardization sector. Originally 3GPP

proposed this solution, but not alone, from the very beginning they relied on cooper-

ated with the Internet Engineering Taskforce (IETF), which specifies key protocols

such as SIP. On the other end the Open Mobile Alliance (OMA) specifies end-to-end

service- layer applications. The overall IMS architecture and standards are supported

by almost all relevant standardization organizations: the GSM Association (GSMA),

the ETSI, the CableLabs, the Parlay Group, the ITU, the American National Stan-

dards Institute (ANSI), the ETSI Telecoms and Internet converged Services and Pro-

tocols for Advanced Networks (TISPAN) program, the Java Community Process

(JCP), and many national and regional standardization bodies, too. All really com-

petitive market alternatives (such as Skype) are proprietary and would never be stan-

dardized. This is still unclear if these alternatives could kill IMS or not, but more

recent traffic data in operator networks show that telecommunications companies

have a real chance to kick back and remain competitive with pure Internet based ser-

vices. But only by reducing costs significantly, changing pricing models and accept-

ing lower EBIDTA margins.

In about one decade from now on we can expect that all telecommunications

services will be managed on top of a common IMS platform utilizing UICC cards in

the terminals and relying on IP as a network transport technology. That means that

financial planning of IMS services will be the basic everyday practice for all surviv-

ing telecommunications operators.

2.1.5 Next-Generation Operation Support Systems

Convergence is also happening in other important areas of telecommunica-

tions activities. The two camps of classical TMN and Internet style SNMP manage-

ment are coming together under the NGOSS umbrella. The NGOSS project started

by the TeleManagement Forum aims to standardize the operation support systems

(OSS) to fit into the trend of the NGN (IMS) developments. They propose a common



business process framework, called the eTOM model. It was accepted by ITU-T as a

general international standard and various vendors take into account when develop-

ing new software versions. Even ERP systems such as SAP follow the eTOM model

in their latest releases.

On of the big advantages of the eTOM model that it creates a common lan-

guage with which business and technology people could understand each other and

get an agreement on business models and processes. eTOM follows a multi-

dimensional layered architecture based on the value creation chain concept. It clearly

defines the differences between resource, services, and products. It gives good guid-

ance for reusing business process experience of the whole industry. Since OSS ven-

dors migrate to NGOSS in their new products, those telecommunications companies

might get competitive advantage who are able to accommodate the eTOM model in

their organization, processes, and information systems.

NGOSS also influences business model and financial engineering efforts. It is

a good idea to use the international standard terms provided by eTOM in these activi-

ties to enable better benchmarking and optimization. However, we should keep in

mind, that eTOM is just a reference framework, each company have a lot of possi-

bilities to things differently than the others. If all companies had to be the same, then

the competition would not be based on innovation anymore. The eTOM model shall

be seen similar to other reference frameworks such as the 7- layer OSI model in net-

working, the ITIL in information systems management, the CobiT in information

systems audit, or the COSO in corporate governance.

IMS integration with the OSS is done typically using SNMP or CORBA pro-

tocols. Some functions may also use the SOA architecture and its SOAP/HTML im-

plementation. An element management system (EMS) and a network management

system (NMS) are also essential functions to have, since the IMS architecture in-

cludes a lot of components and quite complex to troubleshoot.

2.1.6 Next-Generation Business Support Systems

Sometimes it is very difficult to make a differentiation between OSS and BSS

(Business Support System). In most of literature, in products, and in internal com-

pany names the borders are very fuzzy. However, we have to make some distinction

to be able to manage the complexity of OSS/BSS solutions and processes. In our



opinion the separation shall be based on the involvement of the customer. If we have

something to do with customer related activities such as charging, mediation, rating,

billing, provisioning, CRM, then we are in the BSS domain. If the tasks are focusing

on the network and services without looking at the individual customers, then we are

in the OSS domain. The OSS domain includes element management, network man-

agement, performance management, event and fault management, configuration

management, etc. ITU-T TMN also adds authentication, authorization, accounting

(AAA), and other security management functions to the OSS domain. This could be

challenged based on our previous definition, but unfortunately we are not in a posi-

tion to clean up this mess in the industry.

The BSS area is classically very much based on mainly proprietary solutions.

Some underlying technologies are standardized, but the high layers not. There are

two major business models in billing: post-paid and pre-paid. The pre-paid solution

was made popular by the mobile operators, but nowadays it is also available for

fixed- line and Internet services. The pre-paid scheme requires on- line charging that

puts a much bigger burden on IT systems. This was enabled only by recent advances

in IT technologies. Off- line charging is less performance demanding, since here the

mediation, rating, and billing processes are detached from the customer servicing by

the network.

Maintaining these two separate billing and charging architectures could in-

crease the costs significantly. With the progress in IT systems performance in recent

years new convergent billing solutions have emerged. In these systems a single on-

line charging technology is used, where off- line charging is used for reconciliation.

Convergent billing makes it possible to put usage limits unto specific service by post-

paid subscribers.

There is also a convergence on the pricing scheme level by introducing ser-

vice packages or bundles. A characteristic example is the T-Mobile Relax tariff

where practically the post-paid subscriber buys a pre-paid service package. It is also

common to have usable minutes included in the monthly subscription fees. Although

these business models do not necessarily require a convergent billing technology, it

is of course more efficient to implement the IT support systems with it.

The IMS infrastructure components have standardized charging interfaces

(Ro/Rf). These are based on the DIAMETER protocol and shall support both on- line



and off- line charging. Even the mediation function could be part of IMS in the form

of a Charging Collection Function (CCF).

2.2 New Business Models in Telecommunications

2.2.1 IMS Value Chain

IMS introduces radical changes in the value chain, too. The traditional mobile

networks are based on vertical integration of network and services. IMS focus on a

loose integration of more players than before [Mavrakis and Kamal-Saadi 2006]. The

number of infrastructure and service providers could be increased because of the

open standard interfaces [Figure 2-4]. The easier integration of new partners reduces

the time-to-market significantly.

Figure 2-4. New IMS value chain

On the other hand, there are new dangers with this openness. If the operator is

not able to come out quickly enough with new services, anyone else could do that

using the operator’s IP network as a dumb bitpipe. Although this way it is difficult to

provide guaranteed quality of services (QoS), as the Internet has proved it the best

effort services could be just good enough and no one would pay extra for the pre-

mium quality. The operator may have some advantages though. It “owns” the cus-

tomer for a long time, it has established a brand and loyalty, it has a sophisticated

shop network and other well established marketing channels, and it also has a very

fine tuned customer relationship management and service operations. If packaged

together properly, these features might be attractive to a potential competitor to be-

come rather a part of the ecosystem as a specialized provider of only once compo-



nent of the end-to-end service. So the operator can still keep the control and stay the

most profitable element of the value chain.

2.2.2 Technology Innovation Impact

IMS/NGN technologies are mainly evolving as a software solution enabling

more and more applications to be developed very quickly. As [Mauboussin and Hiler

1998] point out this capital is very much different form physical capital in 3 main

aspects: non-rival good, low incremental costs for new applications, increasing re-

turns. Although the classical telecommunications vendors do their best to maintain

their old closed frameworks and linear value chains, sooner or later IMS/NGN and

Web2.0 will push the operators to open networks and economic webs. Closed garden

data services will be opened to the internet, 3rd party developers will get more access

to the telecommunications infrastructure.

When applying IMS/NGN technologies we can expect the 7 major mecha-

nisms identified by [Mauboussin and Hiler 1998] to be valid. High upfront costs can

be clearly seen from the original bids done by vendors and the attempts to create risk

sharing contracts between operators and vendors. It is also supported by the steep

organizational learning curve and the high efforts in OSS/BSS integration. First-

mover advantage is expected by operators and clearly proven by Ericsson and Nokia

Siemens Network in the vendor space by grabbing the majority of IMS contracts.

Path dependence could be studied on how HSPA is killing Wifi and WiMax hopes

and similar schemes could happen with IMS/NGN if not delayed for a too long time.

Tipping points are a way of everyday life for mobile operators and IMS/NGN would

not be an exception. Network effect is also proven by the failure of alternative VoIP

services in competing with classical mobile solutions. Positive feedback is very

common in internet based services. Lock- in is also common with telecommunica-

tions operators, although regulators tried to break it with number portability schemes.

However, it had only limited effects and loyalty is still very strong and churn is kept

under control.

A proper IMS/NGN investment decision and project execution might benefit

from the expected results described by [Mauboussin and Hiler 1998]: increasing re-

turns, monopoly rents, dominance of an “inferior” product (IMS/NGN might be con-

sidered as such by alternative solutions). Once we move to IMS/NGN we will see



some characteristics such as a bigger economic web by utilizing open standards in-

terfaces everywhere, arising complementors such Microsoft and Cisco Systems, and

the punctuated equilibrium behavior making our revenue estimates very much uncer-

tain. Other advices from [Mauboussin and Hiler 1998] could be also applied to

IMS/NGN: heavily discount new products to catch market share, link and leverage

especially in presence and instant messaging, use the power of economic web with

suppliers, partners, and customer communities such as iWIW, do not waste to much

efforts on optimization, rather focus on quick adaptation, and apply psychological

warfare against your competitors in clearly demonstrating your competitive advan-

tage continuously. It is very important in the new economy to extend the competitive

advantage period, since this is the most important driver of shareholder value.

2.2.3 Structural Changes

IMS brings a change in the paradigm how services are organized a mobile

network. Traditionally, each new service was deployed as a vertical silo with its own

solutions for similar functionalities such authentication, authorization, accounting,

session management, load balancing, remote management, charging, etc. One of the

big promises of IMS is to increase the reuse of existing resource by introducing a

horizontal structure into the service architecture [Mavrakis and Kamal-Saadi 2006].

A common call control layer is put between the converged IP access network and the

application logic [Figure 2-5].

Figure 2-5. Service architecture evolution

Utilizing this new IMS service architecture the telecommunications company

may speed up the rollout of new services significantly, since a lot of development



and system integration work is not repeated, just reused. The additional costs induced

by a new service are reduced, since we need much less hardware and software, too.

However, the IMS infrastructure is very complex and might be also relatively expen-

sive. According to [Mavrakis and Kamal-Saadi 2006] the overall cost saving could

be achieved only if at least 4-5 service are launched on top of the common IMS core

[Figure 2-6].

Figure 2-6. New revenue and cost charateristics in IMS

It is a very important issue how to establish a business case for the IMS infra-

structure, since it does not generate any revenue, only the services could. When we

implement these services, the IMS core costs would be already sunken costs, except

some capacity extension generated by the new service. But when we look at the

overall performance of the company, the large initial investment into the IMS infra-

structure cannot be ignored, decision makers tend to have a reverse sunken costs ef-

fect [Johnston 2000]. Later we will suggest solutions for this problem.

Besides the long term cost advantages, we should not forget the IMS enables

a new type of service development. Because of the small marginal costs and the sim-

plicity of introducing a new service, the operator is able to setup a new service very

quickly and it is possible to terminate the service and replace it with another one a

shorter time scale. So IMS brings an agile production facility to the telecommunica-

tions world that supports mass customization. Much smaller market segments could

be targeted with specific products than ever before.



2.2.4 Customer Models

Telecommunications customers are usually divided into two major market

segments: individuals and companies. In September 2007 both Magyar Telekom and

Vodafone Hungary has been reorganized around this idea. Further segmentation is

done on potential revenue generation capabilities. Sophisticated CRM systems are

able to do even micro-segmentation. Marketing campaign for new products can be

extremely targeted based on long-time statistical analysis. This fine tuned value-

based pricing [Torrance et al. 2007] is the major asset of classical telecommunica-

tions companies on which they can build their survival strategies.

Figure 2-7. Value-based pricing opportunities

Source: [Torrance at al. 2007]

IMS is very well tuned to this type of customization unto smaller market

segments. It support a quick time-to-market, since only control logic has to be deve l-

oped as new in the form of an applications server, all other components are ready to

be reused. The only delaying factor could be when we overstep a capacity limit in the

IMS infrastructure and extension is not avoidable. IMS also helps to introduce agile

production and mass customization schemes that are successfully utilized in classical

industries such as car making.

Fine tuning services for micro-segments provides one of the secret tools of

the big telecommunications companies. Other Web based competitors such as

Google or Skype could not “own” the customer so well as the legacy telecommunica-



tions firms. Differentiation by offering many smaller services would help to achieve

the goal of better price discrimination and thus maximizing revenues.

There are two major indicators for customers. On is the Average Revenue per

User (ARPU), the other is the Customer Lifetime Value (CLV). The ARPU is usu-

ally calculated on a monthly basis and extensively used in international benchmarks.

Marketing efforts are often centered on certain ARPU goals, so simpler financial

models in many cases just apply a simple ARPU estimate or forecast. Revenues are

calculated by multiplying the number of customers with the average ARPU. While

this works well for basic GSM voice services, we would suggest to use somewhat

more details models for IMS services, since here each service will have much less

users for a much shorter time and regression based forecasting could not be done

properly.

The CLV is the present value of all future expected cash flows from a specific

customer. Even real options could be taken into account in the CLV calculations. The

CLV driven management is only possible with sophisticated CRM systems, so it is

quite a recent trend. Based on the CLV the operator various actions: high CLV cus-

tomers would get preferential treatment in the shops, in call centers, in on- line ser-

vices; they would also get special loyalty programs and offers; some campaigns shall

be targeted directly to them. On the other hand, very low CLV customer might be

handled with degraded services, they would get no discount or other benefits, some-

times they would be even encouraged to move to another operator. One smaller

fixed- line telecommunications operator in the UK went so far, that they kept only the

top 1000 business customers to become really profitable.

In IMS financial models it is important to relate all revenue estimates to

ARPU and CLV, since for these indices it is easy to make historical comparisons to

cross-check the reality of the forecasts done in natural measures.

A critical point in determining service uptake by customers to know what

handsets or terminals are available in the market and what the customers already own

and use. The capabilities of the terminals shall be analyzed against the service re-

quirements and for each new service the overall available terminal numbers shall be

estimated. This would make an upper limit on the number of subscriptions.

The willingness to pay for services could be very much different from market

to market. One good example is push-to-talk that was a big success in the USA and a



big failure in Europe as well as in Hungary. Probably such problems are also rooted

in finding the right marketing strategy and especially not selecting the proper pricing.

There are also significant variations on what type of rating schemes could be ac-

cepted, but the general trend is to go into the direction of flat rates. However, flat

rates are difficult to handle in terms of resource consumption. A good example is

Internet services. Some customers download so much, that they generate big losses

for the operator. Some companies silently terminate such user because of a violation

of fair use policy, some companies establish upper limit quotas on critical resources.

In IMS services we have serious resource management concerns since it is an

inherently multimedia platform and it requires an always-on network connection, so

some kind of bundling and packaging is necessary to balance out the wish for flat

rates or controllable costs at the customer and the overloading and service degrada-

tion as a result of uncontrolled usage.

2.2.5 Supplier Models

In classical telecommunications the pricing for supplied technology platforms

and solutions was based on a revenue sharing model. In this scenario both the opera-

tors and the vendors are monopolistic or oligopolistic, there are hidden cartels, and

the game between these two players may lead to rather unexpected costs. Recently

there has been a strong consolidation in the mobile network sector, so currently there

are only less than 10 global suppliers who would have any chance to win a bigger

RFQ. Sometimes the operator and the vendor live in symbiosis, operators might even

outsource the whole technology organization to the supplier (Ericsson and Nokia

Siemens is very successful in this area recently). If revenue sharing means a pay-as-

you-go model, then it also contains a risk sharing agreement and thus in could be

even very beneficial for the operator to introduce new revenue streams. However,

later the costs might become too high. Revenue sharing appears in many cases in the

form of the customer usage based licensing fees. This is in sharp contrast with typical

IT and IP network components where only technology limits would enforce buying

more equipment and thus increasing the costs. Sometimes the scene is not so clear,

and if an IT company is too dominant in a certain field, they start behaving like a

telco vendor quite soon.



In classical IT or IP networking the pricing is usually cost based and they are

relatively fixed margins maintained for a longer time by the vendor. The reason be-

hind this is the much bigger competition, so the prices are more determined by the

market and less by the individual negotiations. Large telecommunications companies

could get significant discounts on list prices. Sometimes this could be between 30-

50%, so practically the vendor has no profit on these sales. They just do it for the

value of refe rence and volume, and in hope for future technical support revenues that

may be up to 7-15% per year of the original purchase price.

The telco and IT pricing models are also contradictory because the scales are

very different. Typical IT and IP products are produced in a high volume, so the ven-

dors could benefit from the relatively smaller fixed costs of development. Usual telco

products have only a few licensees, they require a lot of customization, so the high

development cost shall be distributed unto a few projects only. Historically telco

vendors preferred a lot of proprietary solutions, even the vendors encouraged it in

many cases to kept their monopolies and lock in the customers.

Only recently we have seen the role of open standards becoming dominant in

the telecommunications space, too. One such example was the GSM network. How-

ever, here the investment costs were so high to enter the market, that the oligopoly of

the vendors was not broken. IMS promises to get the best out of the IT and IP net-

works business model. IMS components and solutions could be delivered globally

and locally by many dozens of serious players. So competition is significantly in-

creased. IT culture companies could reduce prices significantly. Of course, the clas-

sical telco vendors did not give up their practices, they try to be very quick to get into

IMS and then use all kind of trick to keep out the newcomer IT companies.

Another trend is to offer hosted services by third parties for operators. Actu-

ally, in the case the operator might be even degraded to an access pipe, and most of

the revenue is taken by the hosted service provider. Unfortunately, IMS could be

such a service, since it relies only on a general IP access, so anyone would be able to

start IMS services without even consulting with the operator. This is similar to

Skype, Google, MSN, etc. Hosted services are very much liked by marketing or bus i-

ness development when the forecasted volumes are small and risky. There are no big

upfront investments and still the customer needs could be satisfied. But it has an im-



portant consequence, we sell out our business and the operators might become a

dumb pipe only, and its size shall be reduced significantly.

IMS is considered as strategic investment by most telecommunications com-

panies. They do not want to follow the path of the typical internet providers, they

believe in the concept of an intelligent network. But because of the intense competi-

tion from other business models such as Google, it is critical to keep IMS investment

costs as low as possible. This means the open standards and interoperability shall be

emphasized.

One example is the usage of carrier-grade, high-availability hardware. The

dominant standard that fits well with IMS is the AdvancedTCA (ATCA). The cost of

a classical telco server and an ATCA server might differ by one magnitude (!). Clas-

sical telecommunications vendors do not like ATCA, since it gives too much free-

dom to the operator. However, it is in the basic interest of the operator to push for

open standards like ATCA, since only such a policy would give a best-of-breed mix-

ing and matching possibility. Operators may go so far, that they could buy the ATCA

system for a hardware specialist in high volume for multiple systems, and for each

applications they would buy only the software and the system integration from the

telco specia list. For the new contenders ATCA may significantly reduce the cost of

entry into the IMS market [Partridge 2006].

Because of these trends, in IMS financial models the cost of hardware and

software shall be clearly separated and cannot be fused together. Classical telco ven-

dors will still try to play by moving costs from one category to the other, but this

should be discouraged by the operator as much as possible with special requirements

in RFIs and RFQs. The operator shall also insist on having more cost based pricing

and less customer traffic based royalties. Since a lot of standard IT components are

used, the quickly decreasing prices shall be expressed in models by some mandatory

price erosion schemes. Other prices should be also maximized in nominal values and

even inflation based correction shall be avoided in contracts motivating the vendor to

sell its software to more companies. Only in human resource intensive components

such as system integration, technical support, and training it is advisable to accept

inflation based corrections. To control all these goals, the supplier costs shall be di-

vided into multiple categories and future costs estimates shall be cross-checked



against these recommended policies (if they were put already or could be put into the

supply contracts).

Another important characteristic of IMS supplier cost estimation is the sig-

nificant stepwise nature of capacity extensions. Adding a single ATCA blade to a

softswitch may increase the customer serving capacity by even 100,000 users, and

the hardware cost for this could be below 5,000 EUR. Of course, license costs would

be much higher, but even this would come in big packages. So when we introduce a

smaller IMS service, the necessary capacity might be already there, but if we are the

edge we may incur extra costs. Thus customer traffic to investment cost transforma-

tions could be very much non- linear and even stochastic based on how the race con-

dition with other services for common resources is happening.

In a few years, when IMS solutions will mature enough for supporting true

agile production and mass customization, then financial models for new IMS ser-

vices shall be revised significantly. In this future situation most new services will be

very much short lived, only a few months, or maximum 1-2 years. Present value

based complex calculations would become a little bit overkills. A lot of services

could be created even directly by the customer utilizing so called “mashup” plat-

forms. In this case, the major investment decision will be about the mashup platform

and not the individual services.

3 Existing Financial Models in Service Management

3.1 Financial Control of Service Development

3.1.1 Business Development Planning

In efficient companies service management is driven by business planning

and not left alone for technology people to execute their dreams. Business develop-

ment planning is strongly related to the company wide annual financial planning cy-

cle as described in [Bíró, Nagyné Sáfár, and Urbán 2000]. It starts with a collection

of ideas for generating new revenue streams, improving on existing services, or ter-

minating unprofitable business activities. The bottom-up driven catalog of project

ideas is carefully studied for feasibility. Both the technology and financial aspects are

analyzed in parallel. Based on the results of the feasibility studies a list of candidate

projects is generated by the business development department. A detailed CAPEX



and OPEX plan (together with revenue forecasts) is created to estimate the overall

effect on the company’s financial results.

If the aggregates do no fit with the strategic plans, then an interactive adjus t-

ment process is started. [Bíró, Nagyné Sáfár, and Urbán 2000] identify 3 major direc-

tions to provide the necessary balance between the strategic expectations and the

business development capabilities. The reduction of result expectations is very rare

and almost never happens yet in the telecommunications sector. This may change in

the future, since there are serious problems with current business models. The usual

30-40% of EBIDTA ratio might not be possible in the future, and probably a 10-20%

ratio should be accepted by the owners (closer to what can be achieved in classical

industries). Increasing revenues is the first priority in telecommunications compa-

nies. However, most of the markets are declining or saturating in developed countries

(such as Hungary). That means that it is very difficult to make significant increases

on the short term, a killer application is still not found. There are some claims that

IMS will help to rescue, other candidates are IPTV and community-based services.

All these problems lead to the most common solution nowadays: cutting the costs.

The business environment in telecommunications change very rapidly, so it is quite

typical to review all the business deve lopment and the underlying CAPEX and

OPEX plans each quarter. Practically the business plans are not static even inside one

business year. Rather they are dynamically adjusted with quarterly rolling updates.

Monthly modifications are not used, since the planning process would not fit into

such a short period.

The yearly business plan is approved by top management, while smaller ad-

justments are delegated to middle level managers. If the quarterly update becomes

significant, then the approval goes back to top management.

The approved business development plan lists all those projects that are al-

lowed to be executed. However, “business as usual” technology activities, such as

general capacity increases, are currently typically not included in the business devel-

opment plan. That means that the technology departments have such CAPEX and

OPEX items that are not directly related to bus iness development plan items, but

handled directly by the overall strategy planning of the company. This is a shortcut to

ease the burden on some of the overloaded organizational units, but it may lead to

suboptimal performance.



The future goal shall be treating all investments in the same framework and

do not let technology departments to make investment decisions without the direct

involvement of the business development department. However, this assumes a high-

level technology knowledge inside the bus iness development organizations that is

not always available. In this case, an optimal planning is not guaranteed and techno l-

ogy departments have to play partially the role of business development. This is a

serious conflict of interests, and could easily undermine the efficient operations of

the company. In a fast growing market situation such problems can be hidden from

the owners, but in a declining market the conflict will come to the surface. So a

proper financial modeling will become even more important.

3.1.2 Service Development Planning

Service development planning is normally driven by an approved annual

business development plant. However, in such fast moving markets as mobile ne t-

works, sometimes this sequence is very difficult to keep. OPEX and CAPEX fore-

casts might be needed in summertime already, while the business plan is finished

only at the end of the year. Because of that, the CAPEX and OPEX budget owning

technology departments have to do a lot of estimates on what the business develop-

ment department would propose later. This requires a lot of practical experience in

financial modeling.

In an ideal situation, after a business development idea is accepted for further

investigation, a feasibility study is done mainly from the marketing perspective. If it

looks promising, then high- level investment cost estimation follows. If it still looks

good, then the technology departments have to do a more detailed CAPEX and

OPEX forecast. Usually this would be based on price quotations from vendors. In

most cases this is impossible, since prices are almost arbitrary in many projects, and

only a minority of service developments could work with standard prices are already

done contracts. In IMS we can move to a more standard pricing, especially with the

infrastructure components, so the cost forecasts might become more reliable than

usual.

[Varga 2007] also emphasizes that in real practices most of the CAPEX and

OPEX forecasts are based on previous experience. It is a common problem at various

types of companies that at the time of the planning typically full price quotations are



not available. To be able to make such a historical analysis, the various projects shall

be allocated to long-term hierarchical, aggregating financial project codes. Without

this, a comparison to the past would not be possible.

If time and resources allow it, then a Request for Information (RFI) tendering

process is started to get better input date for the cost forecasting. However, in an RFI

vendors may not want to reveal their true prices, and also they are a lot of uncertain-

ties in the technology solutions that would influence the overall costs significantly.

Since RFIs could eat up a lot of resources, it might be also used to establish a short-

list from the most promising vendors. Later on, when the project gets into the execu-

tion phase, only these suppliers would be invited for a Request for Quotation (RFQ)

tender. This is necessary to keep motivating the vendors to send resources on an-

swering the RFI.

Once a project proposal gets through all the filters, they are ranked by the es-

timated investment costs. Projects above a certain threshold require the creation of a

business case (BC) and a higher decision body shall make an approval based on the

result of the business case analysis.

A project can be continued only after the BC has been approved. The RFQ is

usually very resource consuming, so normally it is not allowed to happen before a

preliminary BC decision. However, once we know the real prices as a result of the

RFQ process, the BC shall be updated, and the decision bodies must be consulted

again to get a final approval.

All project requests, active and closed projects shall be maintained in a multi-

project management (MPM) system in a big telecommunications company. There

could be more than a thousand projects, so portfolio management would not be pos-

sible without proper information systems support. Standard MPM products can man-

age a lot of information efficiently, but in most cases they are not able to handle the

financial models required for a BC. Only the end results might be entered into the

standard MPM systems.

Because most of the CAPEX planning is based on historical data with a lot of

uncertainties, it is very typical to plan a lot of buffer budget by the technology de-

partments that the financial controllers are not able to recognize. Once the budget

execution is started, usually a significant part of the budget will not be consumed, but

a lot of new requests also arise. The middle level managers are highly motivated not



to give back any unused resources, so they would allocate these remains to their pet

projects, and financial controllers would have a hard time to avoid getting unprofit-

able projects into the portfolio. These under-the-radar stealth projects are generating

sunken costs that would make future business cases look better. This may mislead

the decision makers on the true profit contribution of a project. However, until the

financial controllers do not learn technology in more details, they have no chance to

discover if different cover names really hide various parts of a bigger project just to

stay below the detection thresholds.

On the other hand, if the technology departments have a better strategic think-

ing than the marketing or business development departments who might have very

short-term motivations, then these stealth projects may generate a lot of valuable real

options and create a true competitive advantage. Too much tightness and bureauc-

racy might do more value damage on the long-term than saving some immediate ex-

tra costs. The black art is to find the right balance between financial control of ser-

vice development planning and the flexible real options created by technology pet

projects.

3.1.3 Investment Business Case

It is very common in the whole ICT sector, not just in telecommunications, to

create a Business Case (BC) for each new project proposal that oversteps a prede-

fined investment threshold. [Lancz 2006] emphasizes the role of the BC in support-

ing the comparison of decision alternatives. [Varga 2007] compares four major fi-

nancial analysis alternatives in current corporate practice and concludes that we

should select the best fit for the project on a case by case basis. [Lancz 2006] focuses

more on the cost analysis, since its scope is only IT that is in many cases only a cost

center. It adds up the VCO and TEI methods to the usual ROI, NPV, TCO, weighted

scores approaches. The TEI model is not very much liked by financial departments

since it gives too much freedom to the technology departments for creative virtual

savings that could not be realized later. The VCO model is practically a subset of the

TCO. The current practice of big telecommunication companies prefer the TCO for

evaluating even supplier quotations in RFQ processes.

[Varga 2007] suggests certain breakdown structures for the costs and benefits

calculations : CAPEX vs. OPEX, software vs. hardware, real and virtual savings, di-



rect and indirect costs, etc. Since most companies do something similar we will also

follow these ideas in our later modeling proposals.

In our opinion, the static ROI method is not a good fit for telecommunications

services, since their typical lifecycle spans many years, so the time value of money

should not be ignored. The NPV and TCO methods are not really alternatives. Rather

the cost element of an NPV analysis should be estimated by a TCO methodology.

However, there are some projects, where direct revenues cannot be identified, and

cost saving benefits could alone justify the investment. If the project is very short-

term, then an NPV analysis is not necessary. In the IMS services area, we would not

expect such short projects in the near future, so we would stick to a combination of

NPV and TCO.

[Lancz 2006] correctly points out that process of creating a Business Case is

sometimes more important then the specific resulting numbers. The mandatory BC

creation rule over a threshold is a very efficient tool to enforce some discipline into

the capital budgeting activities. Without this, a lot of too risky projects would get

through and the company could suffer on the long run. However, the BC creation

may take up a lot of resources and time, so if done in a too formal way, it might have

a bad impact on time-to-market goals.

In big enterprises the interests of the owners and the top ma nagement are dif-

ficult to enforce. Top management can determine the overall budgets for certain ac-

tivity categories, but they have no chance to control one-by-one a project portfolio

with thousands elements. So the middle management has a lot of freedom in actual

capital budgeting decisions. Sometimes they are motivated to cheat the BC rule by

artificially dividing bigger projects into smaller ones. Financial controlling has a dif-

ficult task to discover such schemes and enforce a consistency in project structures.

One of the best mitigation against BC fraud is to make the BC process sim-

pler and less bureaucratic. This could be supported by good templates and software

based automation tools. Our aim is to provide such means to satisfy both the control-

ling objectives and reduce the workload on the already very busy project managers.

Another big problem of BC creation is the inherent uncertainty of cost and

revenue estimates based on the usual planning process sequencing. Here again the

middle management motivation could be significantly different from the overall

company interests. They want to build their own little empires by grabbing as much



resources as possible. However local optima would not add automatically into a

global optimum. Middle level managers could easily offset revenue and cost esti-

mates, so they would get approval, although the project does not have a positive con-

tribution when evaluated properly.

The current mitigation strategy against BC fraud is usually based on the

transparency of estimations and peer-to-peer review. A critical point is to insist on

getting the estimates in natural terms (such as number of compatible handsets, poten-

tial customers, usage and traffic patterns, pricing schemes, etc.) and calculate the

financial numbers by well established models only. Direct modifications of financial

numbers shall be avoided as much as possible. However, it should not be forbidden

totally, since models are never perfect, so fine tuning might be necessary. This shall

be an exceptional process, and special compensating controls should protect the

global company interests.

It is also important to have many value generating projects, so if we reject too

much, then the company will also go out of business. It shall be clearly communi-

cated, that only marginal revenues and costs shall be taken into account that are the

direct consequences if we do this project or not. Sunken costs and other fixed costs

that are not related to the project decision shall not influence the approval of rejec-

tion or the project.

In classical investment decision studies we see a single upfront investment

only. In real life at telecommunication companies this would not be a proper model,

since the border between OPEX and CAPEX is very fuzzy and bigger investment

costs are almost always distributed in time somewhat. For example, it is a usual prac-

tice to pay only 80% at acceptance and commissioning, and pay the remaining dues

only after a longer stability testing period successfully passed. It is also typical to

include the first few years of support costs into the guarantee services, thus practi-

cally converting OPEX into CAPEX.

We have studied some existing investment business cases from a big tele-

communications company. Unfortunately, we cannot publish the details since such

business cases are top secret. However, we can summarize some characteristic points

about the structure and key performance indicators applied.

The cash-flow balances are estimated indirectly from natural measures, but

all calculations are done in a rather monolithic single workbook with very few auxil-



iary worksheet added. The basic idea is to compute the NPV of the free cash-flows

(FCF). These models also calculate the IRR. The calculative interest rate is WACC,

although sometimes a risk premium is added. The cash flow definitions could be

very much different from BC to BC. The basis is the EBIDTA contribution, but

many types of opportunity costs could be added, tax shields or other tax effects might

be taken into account or not, terminal value handling varies. This is not different

from what we could see globally in the financial literature [Ehrhardt and Wachowicz

2007]. However, the FCF definition inconsistencies make practically impossible an

appropriate comparison of multiple projects. Currently, this is not a big issue, since

the BC is used only for filtering, but not for project ranking or portfolio planning by

mathematical programming.

Basic sensitivity analysis might be added to the worksheets. Risk is managed

either by a risk premium in the discounting rate or by a scenario analysis.

The BC is not always related to specific project, it might be about the history

of a service and the expansion of it with some new features or more capacity. In this

case, there are a lot of technical and marketing KPI values added to the analysis. It is

also difficult to reconcile the BC with the actual CAPEX and OPEX plans. They

seem to be quite disconnected.

There are many project specific structures, although the basic guidelines are

consistent. It is left very much to the discretion of the financial modeler which com-

ponents to include or exclude, and it usually difficult for another person to fully catch

the logic of the modeling decisions. The presentation of the computations and results

is not standardized and very difficult to audit and trace. End results could be entered

into other financial systems such a SAP or Cognos, but the most important parts of

calculations are always done in Excel. The spreadsheets are managed exclusively by

the financial department, the technology or marketing departments have limited or no

access.

3.1.4 Investment Decisions

[Fónagy-Árva and Zéman 2005] summarizes an investigation of controlling

methods in Hungary. The dominant tool for project decisions is the Net Present

Value (NPV) of future cash-flows. It is also common to compute the Internal Rate of

Return (IRR), the Return on Investment (ROI), and the Payback Period. Other meas-



ures, such as the Profitability Index (PI) are very rare in real life practice. We have to

emphasize here that in most cases the investment decision is driven by 3-5 measures

and not by a single variable.

For past performance evaluation the most popular measures are PBT, reve-

nue, EBIT, EBITDA, ROA, ROE. Quite often they also use EVA, ROCE, or

NOPAT. Of course, these are mainly for the whole company evaluation, but they

could be used for projects as well (with some modifications).

In management incentive programs the top measures are EBIDTA, ROCE,

EBT, NOPAT, PBT, revenue, and EVA. Here again in most cases the eva luation is

done by 3-7 performance indicators.

[Ulbert 2002] argues that investment decisions shall be made in two phases.

First a simple static analysis should be done that filters out wrong proposals. Then a

dynamic analysis should be applied taking into account the time value of money.

Current telecommunications practice in Hungary does not follow this two phase

model. Only dynamic analysis is done, classical static analysis methods are adapted

to take into account the time value of money. One example fo r such adaptation is the

dynamic payback period described in [Ulbert 2002]. There are multiple reasons for

this approach: the high volatility of interest rates and currency rates, the high risks in

revenue realization in packet switched services, the general availability of spread-

sheet tools to do discounting easily, and the financial culture where mostly young

people do all the calculations who were already taught to do present value or future

value calculations by default.

The decision workflow in a typical big telecommunications company might

be different based on the size of the investment project. Before a project is started

various management boards discuss and approve the proposals and the attached BC.

Once the project started a project governance committee controls the refinement of

the financial parameters of the project. Capital budgeting is done in a rather heuristic

way. Project proposals are filtered in multiple rounds partly based on the BC, but

also taking into account a lot of other aspects. BC KPIs are generally not used for

ranking only for filtering. The iterations are continued in multiple rounds until they

fit into the previously approved budget. First the CAPEX plan is created, and a little

bit later the OPEX plan, since it has some dependencies on the approval of the

CAPEX plan. Each organizational unit has some freedom to shuffle budget among



their own projects, but regularly they have to explain it to various levels of techno l-

ogy decision makers and financial controllers. Bigger modifications have to be sent

back to the management boards to get an approval. Minimum each quarter a full re-

view is done. Unused budgets are collected and reallocated to new proposals. There

are always a lot of proposals sitting in a waiting in queue. If resources become avail-

able, then first they evaluate the projects from this queue and if there still resources

left, then they initiate new proposals.

3.1.5 Project Controlling

Project controlling is becoming recently an important part of the overall pro-

ject management process to avoid the high failure rate of ICT projects that character-

ized the history up to now. [Véry 2003] defines the role of the project controller as a

bridge between the project management and the financial system. The project con-

troller would help the project management in high- level planning of performance and

costs. She could also help interfacing to the financial system for detailed revenue and

costs planning and monitoring, or even involved in liquidity management. If we have

a project controller than the project management might offload such duties as return

on investment analysis, traffic and profit forecasting, human resources time control-

ling.

In current telecommunications practice this role is taken by a dedicated con-

trolling expert only in very big projects. However, the lack of a professional project

controller in middle sized projects causes a lot of problems. As a minimum, a busi-

ness case is usually prepared for the investment decision, but then there are no re-

sources to implement a continuous project controlling process properly. The model-

ing tools we propose in the later sections will make it possible that project managers

and project coordinators with background in technology would be able to fulfill the

role of a project controller more efficiently.

Once the project has been approved and project execution is in progress, it is

very important to control the project and make corrective actions as soon as possible.

[Nemeslaki, 2006] suggests using the project Earned Value Analysis (EVA) for this

purpose. It is well supported by usual IT systems for multi-project management (e.g.

Microsoft Project Server). However, in the big telecommunication companies they

might use simpler methods, since in the huge project portfolio not the individua l pro-



ject performance, rather the whole portfolio performance what really counts. In new

technologies the uncertainties are so high, that deviations from plans are the norm,

not the exceptions. IMS based services fall into this category, while capacity exten-

sion projects of established networking technologies might be handled with the clas-

sical EVA method.

It is common in the telecommunications sector to use a multi-project man-

agement (MPM) system, as defined by [Tóth 2001], to have a better control over the

hundreds of projects running in parallel. If the project justifies the extra efforts of

maintaining detailed financial information inside the multi-project management sys-

tem (MPM), then all the project-EVA related calculations and reports are practically

given. (A good example for such a software tool is the Microsoft Project Server

combined with the Microsoft Sharepoint Portal Server with some company specific

adaptations added.) So we do not focus on this aspect, since the functions of a project

controlling subsystem as described by [Tóth 2001] are already covered by the MPM

software, we just interface to the MPM system if necessary.

Usually MPM systems can handle special information on the critical prob-

lems in a project. Once a project is started, the project manager has to specify what

the main risks are in the project execution. The project might be time critical, cost

crit ical, human resources critical, etc. And here comes the role of the business case.

Based on the return on investment analysis we can identify if the proposed project is

cost critical. If yes, then the project manager will have an important guide where to

focus the project management efforts.

3.2 Financial Control of Service Operations

3.2.1 Revenue Monitoring

Once a service becomes active, or launched commercially financial control-

ling shall monitor the revenues related to this product or service. Project performance

evaluation could be very difficult if multiple projects results in a single product or

service. In the ERP system there is a significant level of aggregation, so sometimes it

is impossible to acquire the necessary data from there.

The rescue might come from the data warehouse. Here the financial controller

might find the history of those natural measures that were used to calculate the origi-



nal business case. Based on this extract it is possible to determine certain ex post

evaluation values.

Not all services might be integrated properly with the data warehouse. It is

the responsibility of the project manager to make sure that data warehouse support is

built into the service. However, time-to-market pressures and costs cuttings could

block these efforts. A lot of smaller volume or less critical services might be left

without proper historical data for ex post performance analysis.

3.2.2 Cost Monitoring

Cost management starts with procurement. It is very important to have a lot

of guarantees already in the supply and support contracts to limit the risk of in-

creased costs. When extensions or upgrades are ordered based on a framework con-

tract, then procurement always crosschecks if the proper prices were used.

Cost monitoring is also support by the MPM system in the development

phase. A project might need multiple control codes to serve the various reporting

needs. As a minimum we have an MPM project code that links the project to demand

management, risk management, and project documentation systems. We also need

some financial accounting project codes for the ERP system. Yet another code is

used for budgeting: each project shall have some related CAPEX/OPEX plan codes.

But it might other than a simple one-to-one mapping. Procurement could use the

CAPEX/OPEX plan codes to cross-check if a purchase order has an approved budget

behind it. Budget plans are also used to make a variance analysis with monthly re-

views and corrective actions are trigged multiple times in each month by financial

controllers to keep the cash-flow close to the approved plans.

The MPM system could be also used to collect time-sheet data about internal

employee efforts. Since this is a development work that increases the value of the

produced asset, the human resource (HR) costs are loaded into the ERP system to the

specific product category and asset to which the project belongs. When the product

of the project is activated, the HR CAPEX will be included in the starting book value

of the asset. This process could be quite important in a big telecommunications com-

pany, since these costs would reduce the tension on the EBIDTA targets. HR

CAPEX could be in the range of a few percents of EBIDTA, so it cannot be ignored.



However, it creates a lot of issues with the tax authorities so a detailed explanation

and documentation is critical to have these costs accepted a CAPEX at tax audits.

When the service becomes active, a product manager is assigned at the mar-

keting or business development departments. It is the responsibility of this product

manager to continuously monitor the financial performance of the service and make

proposals when to terminate the service.

It is quite common tha t a new service have no support costs for the first few

periods. The support activities for this guarantee time are included in the project

CAPEX. For the company cash-flow management it is very important to maintain the

information when the support costs kick- in, since it increases the cash-flow needs

significantly. It is the responsibility of the technology departments to add all out-

standing support contract obligations into the annual OPEX budget. However, with

so many products, services, and project sometimes mistakes are done, so proper

spares shall be planned to accommodate unforeseen problems.

Based on the recent market growth or decline problems there is a big pressure

to cut OPEX costs. Because of this, most of the cost monitoring (for already active

services) is organized around two major issues: technical support prices and the allo-

cated internal or external operational FTEs. Technical support prices are regularly

renegotiated and organizational synergies might be searched and headcount reduced.

[Varga 2007] describes the hierarchical cost aggregation schemes that most

enterprises use today. Typically they use multiple dimensions as summarized in

[Bíró 1999] to label actual costs according to cost type, cost center, cost owner, re-

lated product, related project, etc.

In the ICT business there are a lot of organization units that cannot be taken

as profit centers, only as costs centers, so they have no revenue. This makes impossi-

ble to do a discounted cash-flow based NPV analysis with a positive value. Many

services utilize common resources that do not appear directly at the service manage-

ment organization. However, for the overall success of the company it is critical to

present these “hidden” costs clearly using a TCO approach and charging these costs

back to the profit centers. [Varga 2007] identifies 4 major methods for cross charg-

ing:

• Direct, when resource allocation is clear;

• Activity based, when resource consumption could be easily metered;



• Output based, when transactions could be easily accounted;

• Proportional, when charging could be tied only to financial data.

Typical ERP systems would support other means of cost allocation, too: such

as internal service prices based on market prices or cost plus margin models, cost

transfer in the accounting system, and fixed cost sharing based on policies [Mészáros

2005].

Modern enterprise practices would prefer Activity Based Costing (ABC) as

described in [Gál 2004], but in real life this would be too complicated and the in-

volved technology organizations would strongly object simplified models, since

those might have a bad impact on the future capabilities and could offset to a very

short term thinking. So we will propose such schemes where the customer charging

data is the basis for cross charging the common infrastructure costs back to the ind i-

vidual services.

3.2.3 Benchmarking

All major telecommunications companies in Hungary have foreign owners. In

these multi-national environments benchmarking plays an important role in manag-

ing the various national subsidiaries. The revenue and cost monitoring systems are

designed such that they could support these international benchmarking needs. Be-

sides these externally enforced performance indicators, each company does regular

benchmarking analysis in all other types as defined in [Tóth 1999]: internal, between

organizations, functional, and general.

One of the most critical aspects is controlling the human resources (HR).

Comparing various organizations is sometimes very difficult, since the processes and

the employment schemes might be quite different. So HR benchmarking is done by

using the so called “Full-Time Equivalent” or FTE. The FTE expresses the workload

of a full-time employed average worker. In many cases a full FTE cannot be allo-

cated to a certain task, so partial FTEs are also used.

There are very strict benchmarking goals on the number of FTE per organiza-

tion, per overhead, per product, etc. Typically counting FTE is not easy, since many

functions could be outsourced, and sometimes this outsourcing is done on a project

basis, so it is not an OPEX, rather a CAPEX cost. The resulting performance indica-

tors may have radical variations, an engineering FTE in Czech Republic may pro-



duce 15 times (!) more useful output in half of the time than in Germany. The FTE

based measures are in many cases not directly related to financial performance, they

are mostly used to evaluate how effectively utilize the various organizations the hu-

man resources and make decisions on organizational developments and reducing the

head-count.

Overall FTE benchmarking have a very significant effect on the daily life of

typical multi-national telecommunications companies. When later we propose

schemes for IMS services, then the financial considerations shall be accompanied by

human resources planning and performance evaluation as well.

3.2.4 Profitability Analysis

Profitability analysis of a single project, product, or service is rarely done

automatically. These types of calculations are normally needed only for capability or

capacity extension. Because of the uncertainties and high risks the performance of

the management shall not be judged on individual projects, rather on the overall per-

formance of the business units.

The management and employee incentive system is usually tied to the

EBIDTA and maybe some other key performance indicators that could be easily ex-

tracted from the ERP system. If the organizational unit leaders want to be successful

in getting their bonuses, then they should focus mostly on the EBIDTA contribution

of the various projects in question. This might have a contradiction with the DCF

based decision models usually pushed by financial controlling.

3.2.5 Service Termination Decision

Most of the telecommunication services have a certain life-cycle, and sooner

or later each of them will be terminated and probably replaced with a new, next-

generation similar product. The decision is mainly marketing driven, but operational

costs are an important decision factor.

It is very rare to have any terminal value on telecommunication services. Nor-

mally a service is abandoned only when the underlying systems are outdated and

cannot be sold on the market. Software licenses are not transferable in most cases.

Indeed, it would cause significant costs to help the existing customers to migrate to



something else, to disassemble, remove, and impair the physical systems, since they

are considered usually as dangerous waste.

3.3 Existing Modeling Tools

3.3.1 Excel Worksheets

It is quite common to use Excel worksheets to support investment business

cases. In current practice, for each project a different workbook is created, with spe-

cial, individually developed tables and calculation, where only the fundamental

methods (NPV/DCF) are the same, but everything else is rather different. No tem-

plates are used, difficult to understand all the details, transparency of the calculations

is not achieved, peer-to-peer review is not a reality. If someone makes a mistake or

error in the middle of the worksheet, there is very little chance that it would be de-

tected. Building upon the results requires a lot of trust. The business case analysis is

used for filtering only, not for ranking projects, so there is no pressure for making the

workbooks standardized and the performance indices comparable.

3.3.2 Modeling Software

The dominant tool for financial controlling is SAP or other similar ERP sys-

tems as described in [Fónagy-Árva and Zéman 2005]. This is mostly useful for per-

formance evaluation. However, even at those companies who have sophisticated

ERP systems, it is still quite likely that Microsoft Excel is the tool that further proc-

esses the data received from the ERP system. The advantage of Excel is the transpar-

ency of the calculations and the unparalleled flexibility combined with low software

costs. Adapting company specific controlling methods into an ERP system is both

time consuming and expensive. Excel has some disadvantages, too. If the model be-

comes too complex it is difficult to catch errors, and it is also very complicated to

detect intentional cheating.

Why not to use commercial modeling software available on the market to

achieve our goals? There are many basic problems with these tools. ERP software

such as SAP is typically very much bookkeeping oriented and has some difficulties

to handle an economic logic of cash-flow analysis. It is also not flexible, especially

not for changing algorithms multiple times a day by any financial analysts. This is

violating the basic principles how an SAP system is managed. The Investment Man-



agement module is a good example that it just an administration system and not a

true decision support system. However, SAP could be very well integrated with Ex-

cel worksheets, so our models may have some SAP inputs or outputs.

Another typical approach for budgeting is to use more sophisticated applica-

tions such as Cognos. It has much more sophisticated reporting, performance evalua-

tion, and business intelligence capabilities then SAP, but it still lacks the modeling

capabilities were are looking for, since it is difficult the simulate the technology ca-

pacity allocation process with it. Cognos may nicely complement SAP, too.

We could find only one real telecommunications business modeling tool:

STEM [Bailey 2006]. This has a lot of the features we would need, including input in

natural measures, simulating the technology capacity and rating schemes, calculating

all the investment evaluation parameters with enough flexibility. It is also endorsed

by the ITU-T, so it could be taken as a de facto standard. However, it looks too com-

plicated and expensive for our purpose. It does not have the cultural environment to

be integrated into everyday work, the typical financial analyst, market forecaster, or

technology planner may need too much work to invest into using such a tool. There

is only one university in Hungary where occasionally teach for a small number of

student recently, so it virtually totally unknown even in academic circles, and almost

nobody has ever head about inside the telecommunications companies. Another big

problem is that STEM is designed for investing into networks and services are

somewhat different, so structural problems could also arise while building up service

models. STEM is a good idea for future exploration, but it is a total overkill and not

an efficient solution for our current problems. Our proposed Excel models might ease

the migration to STEM, if a company decides to do so.

3.3.3 Business Intelligence Applications

One of the critical issues in the business modeling is how to estimate the fu-

ture traffic and usage patterns. In some cases we could learn from the past, in some

other cases this is not much help. If we can find a similar service to the analyzed new

IMS service, then the historical data is definitely useful. For example the MMS

might provide a baseline for the worst scenario of video sharing acceptance.

There could be multiple sources for the historical service data. One is the data

warehouse where all the basic traffic parameters and the corresponding marketing



and financial information can be extracted. The technology departments may also use

the OSS/BSS systems for collecting performance management and accounting re-

cords. These methods depend very much on the specific service, so we do not aim to

standardize them. However, it is a reasonable requirement to provide placeholders

for inputting such data into the business models.

4 Financial Models for IMS Services

4.1 Business Model In everyday corporate life the term “business model” is used without really

having a common understanding what it means. [Osterwalder 2004] defined an on-

tology for business models that was consequently developed into the Arvetica bus i-

ness model framework illustrated in [Osterwalder 2007a] and [Osterwalder 2007b].

We will use this framework in our proposed IMS financial modeling tools [Figure

4-1 and Figure 4-2]. The framework will help us to organize the main cost and reve-

nue drivers.

Figure 4-1. Arvetica business model framework

VALUEPROPOSITION

COSTSTRUCTURE

CUSTOMERRELATIONSHIPS

CUSTOMERSEGMENTS

ACTIVITYCONFIGURATION

CORECAPABILITIES

PARTNERNETWORK

REVENUESTREAMS

INFRASTRUCTURE CUSTOMEROFFER

FINANCE

DISTRIBUTIONCHANNELS

Source: [Osterwalder 2007a]

There a large number of different business model proposal for IMS services.

We do not want to vote for one or the other, since in the future there could many

changes in business policies about IMS. Rather, we try to create such a modeling

architecture where we can accommodate all the business models currently in consid-

eration. In the next sections we summarize the basic guidelines how to do this.

It is common in all business models that in financial modeling basically we

have to deal with two main sides: revenue streams and cost structure. The model

shall include a common breakdown structure for all services to help comparisons. On

the other hand, special needs of certain services have to be supported by the general

templates. Similar services could reuse not just the templates, but the already existing

business cases, too.



Figure 4-2. Arvetica BMF example: Skype

free VoIP & value added services

software development

websiteglobal

(non segmented)deliver voice &

video quality

“eBay”

large scalelow margin

internetsoftware development

Source: [Osterwalder 2007c]

4.1.1 Revenue Structures

Revenue structures shall be designed for the mindset of marketing and bus i-

ness development people. It should drive them to find all the important revenue driv-

ers. They should enter estimates of subscriber numbers, usage patterns, uptake pa-

rameters, price flexibility, etc. It is important to provide some simple tuning parame-

ters instead of forcing them to fill out hundreds of cells manually. So some default

product life-cycle profiles should be included in the model. However, we should

keep open the option to enter irregular shapes, too.

Special attention must be given to forecast the terminal value of revenues at

the product cycle tail. Our timescale is will be designed for such a long time that

forces the retirement of the service in this period. Although a similar service could

substitute the terminated old service, but this could be handled as a separate invest-

ment decision with the option to abandon. Since IMS services are focused on soft-

ware in a quickly changing technology environment we can assume that there will be

no salvage value at termination. The hardware will be useful for nothing, and the

software has to be redesigned practically from scratch for a functionally similar ser-

vice. A good example for this effect is the retirement of the first generation IVR pla t-

forms currently due at many telecommunications companies.

4.1.2 Cost Structures

The cost structure shall be designed for technology and financial controlling

or procurement people. It should drive them to find all the significant cost drivers.

They should enter all the major components of the technology platform and all the

related activities in project management, system integration, testing, technical sup-



port, operations, etc. Very small cost components and initial investment costs uncer-

tainties could be handled by a single contingencies item [Ehrhardt and Wachowitz

2006]. The risk-adjusted discount rate is not an appropriate tool for the investment

costs estimation problem, although we could use it for the longer term revenue risk

management.

Contrary to the usual financial textbooks [Brealey and Myers 2003], we can-

not assume that there is a single upfront investment, since in current practice the

payment is divided into minimum two parts, but sometimes many smaller strongly

attached other investments has to be done with a different timing. The single initial

investment restriction would make it impossible to organize our projects in any natu-

ral way. This also means that wherever the literature talks about the single amount of

investment, we have to replace it with the present value of the whole investment

costs stream. However, to avoid the problems with real options discussed later, we

should put only those items into a project that are part of a single run, and typically

the project would either go through as a whole or not.

In IMS services we just manage software, so working capital should not be a

big consideration. Opportunity costs might be handled by the calculative interest

rates. But to implement the total cost of ownership concept in a flexible way, we will

implement items even for such cost drivers, to enable the human modeler to manage

exceptions from the general rules. But we will sign these entries as exceptions, so an

explanation for each such extra input shall be added.

4.1.3 Cost Dependencies

The most difficult part in business modeling telecommunications services is

the correlation between traffic or usage and the costs. Here we need the input for

marketing, that is technically easy to do, but it is almost impossible to capture the

multiple feedback cycles of interactions between usage, capacity, costs, and prices

without making our models extremely complicated.

In IMS services the modeling people will find new challenges. Since IMS is

based very much on the reuse concept, all the capacity allocation needs to take into

account the stepwise nature of capacity upgrades. The dependencies between many

services competing for the same resources will also increase the non-linear behavior



of the models. Non-linear modeling is always a big issue, since we may have only

numerical solutions and the system can become very easily chaotic.

In our proposed models we cannot solve all these problems at once. But we

have to take into account the issue and provide such structures where these depend-

encies are very transparent and we leave enough space for the human modeler to

control the details. There is still no better non-linear decision maker for very com-

plex problems than the human brain.

4.1.4 Key Performance Indicators

Since few focus solely on financial modeling we do not want to include here

a full balanced scorecard for characterizing projects. But based on our experience we

need a number of key performance indicators (KPI) to support the decision makers

properly. A single value, such as the NPV of future cash-flows would not be suffi-

cient.

In later sections we will propose in details the KPIs to be used for evaluating

projects. Here we just emphasize that the main goal of such KPIs is to compare such

investment opportunities that are difficult to evaluate to each other at the first sight.

So these KPIs shall be reasonable for all imaginable IMS services. Otherwise, for

some case we could not compute it and then the comparison becomes impossible.

KPIs will be summarized in a special section of the model, so busy decision

makers, who are not interested in the details, could quickly find them. We have to

limit ourselves with the number of KPIs not make it too difficult to get an overview.

On the other hand, we have to increase the number of KPIs from current practice to

enable better decisions. We will use spatial structure and colors to help the reader to

cope with the bigger complexity of the new KPI set.

4.1.5 Time scales

Business planning could be done on very different time scales. However, in

real life practice the plan granularity has to be balanced between costs and benefits. It

should be also aligned with key financial decision points and it might also express

the uncertainty of the forecasts. For the future estimations we propose a variable time

scale with 3 different densities:

• monthly, for the first two years,



• quarterly for the next two years,

• and yearly for the remaining years.

For the first two years both a detailed CAPEX and OPEX plan shall be avail-

able. In usual company practice financial controlling is done on a monthly basis. In

the current year we would have an approved CAPEX plan with a per month cash-

flow, and since each summertime we might also have a next year CAPEX plan pro-

posal with a monthly granularity.

This corporate planning driven time scale is typically also a good fit for sup-

plier roadmaps. These roadmaps have a very big influence on when a certain invest-

ment activity could be started. As we go into the future, supplier roadmaps would be

based only on quarters or half-years. After 4 years in time, usually there are no more

supplier roadmaps, we could just make vague forecasts, so a yearly time scale would

best express the uncertainty of the data.

In historical performance data the time scale would be based on the natural

reporting unit that is one month. All kind of regression based forecasts would be eas-

ier with a fixed unit, so this raw monthly data should be kept for the whole history

and quarterly and yearly aggregation shall be added for the whole dataset. However,

if we want to compare the historical data with the original plan, a similar hierarchical

aggregation and a resulting variable time scale would be extracted than we suggested

for future estimates.

4.2 Investment Decision Models

4.2.1 Overview of Evaluation Methods

Before an investment decision is proposed and approved in most cases a de-

tailed financial analysis is required to show if this investment will be profitable.

There is a long history of various methods for project evaluation. Most of these

methods are based on general company evaluation and each project is treated like a

separate virtual company. However, there are some important differences between

company and project evaluations. Typically financial accounting is not done in de-

tails on a project granularity in telecommunications firms. It is usually more related

to the organizational structure and profit or cost centers. There are many company

measures that could not be implemented for projects in a reasonable way.



It is not in our scope to make a detailed comparison of the available project

evaluation practices. Rather we will select our choices based on the recommenda-

tions of the contemporary financial controlling literature. [Fónagy-Árva and Zéman

2003] gives an excellent analysis of the evaluation schemes and provides recommen-

dations how to pick up the right method. [Turner 2003a] also adds some practical

advices how to decide between DFCF and EVA. Based on these articles and our own

experience we propose the following approach to IMS services projects:

• Discounted Free Cash Flow (DFCF), as included in the Shareholder Value

Analysis (SVA) method, for forecasting project profitability of a proposed

IMS service;

• Economic Value Added (EVA) for the current period performance measure-

ment of an active IMS service that could be tied the management incentive

schemes;

• Cash Flow Return on Investment (CFROI) for benchmarking active IMS ser-

vices.

For project portfolio planning we will suggest later a pragmatic method partly

based on current practices using multiple key performance indicators (KPI). These

KPI values will be determined from the DFCF calculations.

It is important to note here that the various cash-flows definitions used in

company evaluation could not be used without modifications in project evaluations.

In big telecommunications firms the financing decisions are mostly separated from

the average size individual projects. So for future investment decisions a lot of com-

ponents that are dependent on these unforeseen financing decisions cannot be taken

into account. In past performance evaluation the situation might be different. The

effect of financing schemes could be traced back to the individual projects either

directly or indirectly by some cost allocation methods such as Activity Based Cost-

ing (ABC).

From the 4 major ABC steps summarized in [Gál 2004] the first 3 are already

given by the company environment when we study only IMS services. Our scope is

here only to provide the necessary measures to do the 4th step of allocating the activ-

ity costs back to the products or the underlying projects. The cost drivers are difficult

to identify and it is even more difficult to simplify them into a usable model. Some of

the general overhead costs could be hidden behind the profit contribution expecta-



tion. This is the usual goal of the technology departments: push out everything from

the ABC into this not allocated overhead. The company optimum is somewhere in

between: do ABC where the effect is significant and collect smaller costs into a ge n-

eral overhead.

4.2.2 Discounted Free Cash-Flow

It is always one of the most difficult questions what to include in the cash-

flow of a financial model. Since it is a model only, it should be simpler than the real-

ity, otherwise it is too costly. But if it is too simple, then the decisions might be

wrong. A good compromise is necessary.

It is also a requirement in a big organization to separate duties and workflows

to keep things manageable. Because of this, financing decision shall be separate from

the investment decisions as much as possible. If a project is not too big compared to

the overall size of the company, then this could be done relatively easily. If a single

project has a big impact on the overall results of the company, then we have to take

into account the effects of financing to get a proper decision.

IMS service projects are not expected to be very big in the near future. So the

separation of financing could be assumed based on the Fisher-theorem. The cost of

financing is aggregated into the WACC that is used as the calculative interest rate for

discounting. That means that the free cash-flow could be computed to the firm and

not the equity.

It is also important to note that the major goal of the financial modeling is to

make proper investment decisions. Ranking is more important than the absolute

value of various performance indicators. However, projects are much different in

scale, scope, schedules, etc. So comparing them correctly is a critical requirement.

Although in textbooks [Brealey and Myers 2003] handling the tax effects is

very simple, in real life this could be extremely complicated. Most projects are the

same from the tax perspective so adding tax calculations would not really change the

ranking among these investment proposals. If there are some special tax benefit pro-

grams or other considerations, then we should leave some flexible space for this pro-

ject specific extra costs or benefits in the calculation schemes. So we suggest not

including tax related costs as a standard element into the cost model of the bus iness

case. This would also keep our basic principle that financing decisions are separated



mostly from the investment decisions done as part of CAPEX budgeting in big tele-

communications companies.

It is important to emphasize that the cash-flow in the business case shall in-

clude only marginal contributions that are the direct result of the project. On the cost

side we have to take into account opportunity costs for a proper analysis, too. The

general cost of capital is included in the WACC already, so only such issues shall be

taken here for opportunity costs that are project specific. On the other hand, a project

might create new opportunities that are significant so they should be added into the

calculation. However, these costs and benefits are not cash-flows, so they should be

structured as separate corrections in the final NPV calculations using the linear com-

binational properties of the NPV formulas.

IMS services have some special characteristic that influence the components

of the cash-flow. There is no inventory build-up, so operative working capital costs

cannot be directly connected with an IMS service. The payment schedule and fees

collection problems may cause some working capital requirements at the company

level, but this does not depend on individual projects normally. On the other hand

there could be significant cross-sale and churn control effects of a new or improved

IMS service, so revenue and cost components shall be added for these categories.

NPV calculations will be done for all cash-flow components in a similar, con-

sistent way. Because a single upfront investment cannot be assumed, all costs in the

lifecycle are considered as part of the investment needs based on a present value

scheme. So our formulas will be quite different from those someone can find in clas-

sical financial textbooks and academic articles. All performance indices (NPV, IRR,

PI, etc.) will be adjusted to the time-distributed cost model.

Because of the significant progress in computing resources we have no reason

to simply spreadsheets to the level of usual textbooks and articles where this simpli-

fication is critical for better presentation and understanding. So we determine as

many analysis results as possible, and then organize the output of the model such that

it would be easy to find and pick what is actually needed by the current reader.

So we propose the calculation of three different NPV types: one with WACC,

one with a project risk specific rate, and one with a time variable rate. The later could

be important in developing regions where financial stability is not as good as in the

USA. Most of the literature ignores this problem, since they are based on the US en-



vironment and do not care with the rest of the world. In Hungary, the variable dis-

count rate is mandatory in the public sector for certain projects (61/2005. (VIII. 16.)

Korm. r. 1. §. (2)), and the Financial Ministry publishes each quarter a new updated

35-year discount rate table on its web site.

The various NPV values shall be computed for all possible time periods. The

project can be analyzed by a specific point in time just for standalone evaluation and

basic filtering. Rolling updates shall be supported too in a common calendar struc-

ture. For project comparison and portfolio selection we will normalize the NPV to

the beginning of the current business year.

We will also provide NFV in a similar pattern. This is useful to evaluate the

expected historical performance of the project. The NPV takes out sunken costs, but

sometime we want to now the overall performance, but taking into account the time

value of money. The NFV is also computed for a specific analysis date and for a

normalized calendar point for better comparison. The NFV values will give a better

idea to the management how the projects would influence their longer term perform-

ance evaluation.

The Internal Rate of Return (IRR) is a very popular measure of investment

performance [Graham and Harvey, 2001], although it is only related to the return on

investment in very special cases you could find only in some classical industries.

Using IRR as a dominant guideline for capital budgeting decision might result in

serious mistakes, so recent financial literature and common sense engineering think-

ing suggest not to use it at all as a major factor [Kelleher and MacCormack 2004].

There other misconceptions about IRR [Reinhart 2000], such as the reinvestment

assumption, that could be shown not be valid. A Modified IRR could be created

[Reinhart 2000], but it is still not really helpful when we separate the financing deci-

sions.

We will include IRR calculations into the IMS service model because of its

general popularity, but we will strongly emphasize not to use the IRR for anything

else than characterizing the financial model for the discount rate sensitivity (as a way

to express the stability of the NPV calculation concerning the uncertainties in the

applied discount rates, especially the included risk premium). If the IRR is to close or

below the used discount rates, then the NPV calculation results shall be treated with

special care.



Instead of the IRR, we would push for using the dynamic Profitability Index

(PI) as a relative measure of project performance [Ulbert 2002]. The PI calculations

are also adjusted for a full PV treatment of time-distributed investment costs. IRR is

sometimes also used for computing the CFROI [Tanács and Berze 2001]. In our

opinion this is based on the wrong interpretation of IRR. When CFROI is applied to

a single IMS service project, then a lot of usual components of CFROI would not

apply, so the PI could be the best candidate to satisfy the original definition of

CFROI. That means in practice, that for our IMS services projects CFROI bench-

marking should be done with the dynamic PI values. Our ideas are based partly on

the expert opinion in [Myers 1996] and [Myers 1997].

4.2.3 Economic Value Added

The Economic Value Added (EVA) methodology is applied mostly to whole

firms or business units. [Turner 2003a] describes in details the difficulties of comput-

ing the real EVA from the general accounting data or balance sheet of a company.

The major idea behind these complex corrections is that only those capital elements

shall be counted that are really necessary for operations. When we apply EVA to a

project in an incremental manner it could be easier to focus on the real effects of the

direct investments.

We agree with [Turner 2003a] that EVA is best applied for the evaluation of

past performance and it is a good basis for management compensation packages as

described in [Turner 2003b]. We also emphasize that EVA distributes the cost of

capital unto the whole life-cycle of the investment. Without this creating an efficient

management compensation scheme would be difficult, since in the first few years

typically the DFCF gives a very high negative value.

[Turner 2003a] also explains the relations between the DFCF and EVA meth-

ods. If we discount the future expected EVA, then we will derive the Market Value

Added (MVA). In an ideal market the MVA is in direct correlation with the differ-

ence between market value and invested capital. The total market value of a firm

could be estimated by the DFCF. So the DFCF and MVA evaluation are related to

each other: Market value (DFCF) = Invested capital + MVA.

Theoretically the DFCF and MVA calculations will give the same overall re-

sults [Shrieves and Wachowicz 2001]. However, if we use only estimates and if we



simplify models for practical use, there could be some slight differences in the actual

values. So DFCF and MVA results shall not be compared directly against each other.

But if we use them for separate purposes such as DFCF for investment decisions and

EVA for performance evaluation, then we will get a consistent management ap-

proach despite the small variations in the actual numbers.

There are two major methods to compute EVA. One is the capital charge

method that is operating with accounting performance indicators such EBIT, tax rate,

NOPLAT, etc. The other is the spread method that is based on the difference of

ROIC and WACC. In our opinion, the spread method is the best fit for our financial

modeling. We could use the future value calculations with historical data, while

keeping the same structures as for investment decisions, to determine the NFV of all

investments and all revenues. Then we could get the ROIC and since the WACC is

already given, we could easily compute the EVA.

One of the critical issues is to account only for those assets in the cost section

that are really necessary for the given project or service. It is out of our current scope

to suggest methods how to reconcile the project or service costs with organizational

unit based cost monitoring system. We just notify here that such a scheme would be

necessary to avoid having uncovered costs not allocated intentionally either to ser-

vices or to overhead.

4.2.4 Cost-Benefit Analysis

Cost Benefit Analysis (CBA) is an alternative method to the cash-flow based

NPV analysis. Normally, it is used in public sector projects where revenues cannot

be identified, but still the investment might be beneficial to the society. It is a recent

trend in Hungary to make at least a CBA for any project. This requirement is also

enforced by the European Union when someone applies for financial support.

The key issue in CBA is to find the major benefit drivers and assign monetary

value to these factors. Once this transformation done, the rest of the analysis is al-

most the same than the DCF scheme. Cost drivers could be also different, since such

items might be added that account for environmental damage, or unwanted social

effects.

It is not always possible to transform each benefit or problem into a monetary

value. Or even if it is possible, maybe it is not politically correct (such as the value of



human life). So sometimes the CBA method is replaced by Multi-Criteria Analysis

(MCA). MCA is usually based on a weighted-average scores evaluation, or in a most

sophisticated approach on a multi-dimensional comparison.

In the ICT sector a CBA method could be also used theoretically, since there

are a number of projects having complex dependencies on other projects. We may

also see some environmental or social issues. However, a telecommunications com-

pany management is mainly driven by the balance sheet and shareholder value, so

financial directors would prefer real cash-flow based calculations. There some situa-

tions where revenues cannot be attached directly to an important investments. Such

example is the early implementation of an IMS core infrastructure. How to sell a

project proposal like this? CBA may come to the rescue, but we would need some

good arguments to make the financial people to accept the benefits. A better ap-

proach would be real options that we discuss in the next section.

In this study our scope is IMS services, where there is a direct relation be-

tween the investment needs and the resulting revenues. So in the case the CBA

method is not necessary (\we could apply the DCF method), and we would not rec-

ommend it to use.

4.2.5 Real Options Analysis

As mentioned in the previous section, there are many investments where at

the time of the decision we cannot fully determine the benefits of the project. In re-

cent financial literature a new method emerged that is considered better than the

CBA. This is called “real options”. The name implies that it has something to do with

financial market options. The suggested method uses an analogy between financial

options and real options, and based on this similarity it reuses the formulas for finan-

cial options to calculate the value of real options.

Typical examples are based on the staged project model. At specific mile-

stones we have the option to abandon the investment (cancel a service), or delay the

next stage. This is put into analogy with a call option for a company share. If the real

option can be related to a similarly behaving financial market option, then we can

determine the value of the real option. This works well for mining, where we can be

sure that the deposits could be sold for a reasonable price sooner or later. However,



in the ICT sector, where software is the major component, it would be difficult to see

guarantees for a certain revenue stream.

In theoretical studies someone may ignore such problems [Borison 2003], but

a financial director does not want to play with real options if they are not appropriate

for the case considered.

There are alternatives to real options analysis such as decisions trees with as-

signed probabilities, or Monte-Carlo analysis with market simulation. However,

these are far too complex for our current scope. The main driver behind real options

is the relative simplicity of the necessary calculations such as the Black-Sholes

model.

Real options analysis could be used to answer such questions as when to stop

a service, when to liquidate assets or sell resources, if it is better to continue a service

and utilize a product tail strategy, if we should move resource to another project.

In the everyday life of telecommunications companies in Hungary real op-

tions is not a preferred tool. In the USA we have seen some examples for real options

in telecommunications, but they have long-term market data with large sample sets

and relative stability. If a complete hedging is not available for our real project, then

[Smith and Nau 1995] for example proposed ways to extend the real options for in-

complete or partial markets, but even this requires are lot of reliable and detailed

market data.

Hungary is more a monopoly or oligopoly market in telecommunications,

stock exchange data is not that useful for measuring individual services since major

player are not represented on the financial markets, and data sets are small to make

good statistical analysis. In Hungary, volatility of the real options cannot be com-

puted only guessed. So we loose the main advantage of real options: replacing

guesses with measurements on the financial markets.

There is also an image problem of real options. Many financial managers in

the ICT sector consider it just a trick to push through otherwise bad projects. Some

of them think that the misuse of real options was responsible for the Internet bubble

burst. They might have a different opinion if higher risk increases the value of op-

tions as stated by many real options fans. Sometimes higher risk means that even

smaller revenues cannot be realized, and there is no historical data for value-added



services illustrating revenues going up quickly. So they consider real options a very

dangerous tool that should be avoided if possible.

IMS infrastructure as strategic investment could be definitely an object for

real options analysis. However, for IMS services in Hungary we suggest not to use

real options at the current stage of financial analysis maturity. We will propose sim-

pler means for handling risks. We also recommend organizing projects into smaller

chunks where inside the project we do not have options. Regulations or company

policy may also limit real options (i.e. we may add up further ADSL subscribers al-

though HSDPA would give a better return on investment).

4.2.6 Scenarios

Uncertainty of business estimates could be expressed by not providing a sin-

gle expected value in our calculations, but rather providing a limited number of sce-

narios as part of the standard modeling. Since modeling resources are usually very

limited, in most case we would target only 3 basic cases:

• pessimistic, or slow growth,

• realistic or moderate growth,

• optimistic or fast growth.

This fits well with most of the fuzzy modeling attempts, since these points are

enough to define a fuzzy T-value. However, in real life practice we may not need

fuzzy modeling at all, we just want to emphasize the uncertainty of the future esti-

mates by these 3 standard scenarios.

4.3 CAPEX Planning

4.3.1 Project Portfolio Management

CAPEX planning is based on a project portfolio management methodology.

The major difficulty is that there could be complex project dependencies by using the

same infrastructure and competing for the same resources. We do not aim to solve all

issues at once, we propose just to make a smaller step forward and handle projects as

independent decision in our IMS services financial model.

Our capital budgeting approach keeps the final authority at the human deci-

sion maker. All computed KPIs and rankings are just provided as helping informa-

tion, the software is not allowed to make decisions automatically. This is necessary,



because models are never perfect and exceptions are a way of life. However, by in-

cluding automated suggestion we can better identify exceptions. This would result in

better auditing capabilities and a more efficient corporate governance.

Our proposed financial model will rank the projects according the NPV of the

predicted cash-flows. This maximizes the shareholder value. However, close this

major driver we also display the profitability index and present its contribution to the

portfolio performance. If the PI is too low, then we mark it for rejection. Similarly

we include other KPIs into the CAPEX plan and assist the decision maker by visual

signs if a KPI is good or bad. In a future version we will replace the simple NPV

ranking with an improved integer programming engine. However, even using this

basic capital budgeting tool will be a big cultural shock for decision makers, so we

should not hurry too fast.

Most capital budgeting models are difficult to handle when the CAPEX

schedule is too uncertain. So we propose to divide the original project proposals into

stages, where at each stage we are able to decide on abandoning, holding or redesign-

ing the project. The BC shall be created for each stage separately (as an individual

project) to simplify the decision process. A project with a BC is either approved or

rejected, there are no fuzzy alternatives.

It is also an important measure for a telecommunications company how much

CAPEX is spent in a business year compared to the overall activities. This ratio is

decided strategically and could be easily benchmarked to characterize investment

policies. Magyar Telekom for example targets a 15% CAPEX per revenue rate

[Magyar Telekom 2006]. When responsible managers make decisions on CAPEX

allocation, they have to keep in mind that the project portfolio should support this

goal. Because of this strategy requirement it is very useful to compute similar ratios

both for the individual projects and for each managed investment portfolio.

4.3.2 Periodic Reviews

Financing decisions are somewhat separated from the investment decisions.

However, once a CAPEX plan is approved the financing shall be planned in detail to

provide an optimum cash-flow with the minimum costs. Because of this, a reliable

short term cash need forecast is essential. However, telecommunications investment

projects have a lot of inherent uncertainty. Products and solutions might be delayed,



unforeseen problems could pop up in acceptance testing, problem fixing may be

longer than planned, etc. This kind of quick changes might put in danger the financ-

ing plan execution. Usually there is a big pressure to keep the original cash-flow plan

as much as possible by rearranging the project schedules. If some projects are de-

layed, then probably other projects shall start earlier, purchases would be done

sooner.

As a result, CAPEX plans are not static, they need regular adjustments. Fi-

nancial controlling has to monitor tightly how the responsible technical organizations

reschedule projects to meet the cash-flow plan. If they do not, then the responsible

controller shall step in and enforce action, or escalate to upper management if neces-

sary. On a higher organizational level the remaining changes might cancel them-

selves out, but in the worst case they may even amplify. So a quarterly higher level

(business unit or company wide) aggregate review is also necessary to be able to

make corrective actions in time.

4.3.3 Procurement Controls

CAPEX planning is sometimes difficult since we may not be sure what would

be a price of a future equipment or solution purchase. It is a common practice to limit

future prices for multiple years with framework agreements. So we can include the

price catalogs of such contracts into out financial models.

In some case, it is not a simple catalog of list prices. We need some formulas

to computer the actual price, too. Usually there is a big difference between licenses

for production, test, and development systems. A supply contract may apply some

mandatory price erosion schemes derived from inflation, past experience, and bus i-

ness targets. This is always a big fight between giant telecommunications operators

and vendors, but if RFQ processes are executed properly, then such procurement

controls could work effectively.

Procurement also tends to make final decisions on lifecycle TCO instead of

the price of the current purchase. This means that our proposed financial modeling

tool for IMS services will be used both before the RFQ process with estimates from

an RFI or public market prices, through the price negotiation to set targets, and the

after the contract made for cost monitoring.



4.3.4 Savings Campaigns

Another important role of the proposed IMS services financial model is to

support CAPEX savings campaigns. It is usual in the current market conditions that

investment resources are strategically limited to have nice benchmarking values at

the company level. There are some services where customer uptake could be rather

volatile, or where the responsible managers intentionally do not plan a budget, know-

ing that the option to reject the new subscribers is not real. In this case, the budget

has to be revised when financial controlling detects the excess spending in these ser-

vice areas.

The proposed financial models could be utilized in estimating the effect of

CAPEX cuts. It gives advices in the CAPEX workbook which project should be

abandoned to fulfill the savings requirements.

4.4 OPEX Planning

4.4.1 Service Portfolio Management

OPEX planning starts with assembling existing obligations. The responsible

managers scan all valid contracts and add up the numbers. Human resources costs

shall be separated (including direct outsourcing). Vendor technical support shall be

also grouped together.

There is always an overall OPEX budget limit determined by the strategic

planning process. OPEX is more critical to performance evaluation of decision mak-

ers, since it directly affects the EBIDTA. Because of this, usually there is more em-

phasis on keeping the OPEX low.

It is a basic expectation for supply contracts to include a few years of full

guarantee. That may cover all vendor technical support for the first period. Only

those OPEX costs would appear for new projects that are not covered by the vendor.

This requires making an audit check in the financial model not to input vendor re-

lated OPEX costs for the first few years. However, we have to provide enough flexi-

bility for special cases, so the guarantee parameters should be changeable.

4.4.2 Enforcing Savings

In the middle of the business year a similar effect could happen that we have

already mentioned for the CAPEX budget. Some services generate excess costs, or



the company performance lags, so the EBIDTA target might be saved only by reduc-

ing OPEX. Even if everything goes fine, the owner could stretch the EBIDTA mar-

gins, so costs savings are still necessary.

One of the methods for limiting OPEX is to fix the prices of vendor support.

This is usually based on nominal prices, so actually in real value there is price ero-

sion. For less capable vendors the operator forces frequent renegotiations of support

contract terms. Sometimes the support price depends on the volume or capacity of

installed equipment. In such cases, the operator pushes for price saturation, so the

costs would not grow linearly when investing more into a platform or infrastructure.

The proposed financial models could play in important role in handling

OPEX costs savings requests. It is possible to simulate the impact of changing the

vendor terms, so we can find out which contract would give the best results.

4.5 Investment Performance Evaluation

4.5.1 Financial Profit-and-Loss Analysis

Ex post financial profit-and-loss (P/L) analysis is usually not done in a project

basis. Accounting schemes are in place for organizational units and project portfolios

only. This process is fully automated on ERP systems, so we have not too much to

do with it. If the MPM is integrated into the ERP system, even a project level calcu-

lation is possible.

However, in our environment the MPM is not fully integrated with the ERP

system, so we would also use the IMS services financial models to generate a profit-

and- loss report. By utilizing the shifting windows and the NFV formulas it is easy to

extract the necessary KPIs for different periods. There is one big problem with the

time scales. Investment business cases shall be done with varying intervals, while ex

post evaluation is based on monthly accounting data. To make the two comparable

we have to provide slightly different worksheets for service performance evaluations.

4.5.2 Economic Value Added Calculations

Besides the usual accounting measures, we have already decided to estimate

the economic value added (EVA) for ex post performance evaluation. It is possible to

use the financial P/L tables with some extensions to do it. As we have mentioned

previously, we would use the spread method and we will provide not just current



business year values but also project aggregated with taking into account the time

value of money practically calculating the MVA.

The implementation of MVA is based on the NFV tables. We also aggregate

this for the project (service) portfolio, since this is the more useful measure to be

connected to personal incentive programs. We could also compare the ranking of

various projects based on the NPV values at the time of CAPEX planning and based

on the MVA values at the time of ex post performance evaluation. On the long term

these rankings should have some correlation with each other.

4.5.3 Application of Benchmarking

The application of benchmarking requires that we compute those measures

that are used by other companies and benchmarking organizations. So have to sum-

marize briefly what KPIs are usually utilized in describing the performance of tele-

communications firms.

Most of the big telecommunications companies are public, so their financial

numbers could be easily analyzed down to a certain detail. On this high level there

are some general benchmarks for CAPEX and OPEX budgets:

• CAPEX per revenue should be somewhere around 10-15%,

• OPEX might be about three times the CAPEX,

• Staff costs could be about half of the OPEX.

It also a general agreement by experts, that the introduction of IMS/NGN

shall reduce the workforce in a former PTT company by 25-40%. This saving could

be about 4-9% of the revenue.

Significant deviations from the industry benchmarks shall be analyzed and

explained. To keep the above values at the company level, we should also check the

contribution of each project and take into account when we accept or reject an in-

vestment proposal. This leads to a basic requirement to compute CAPEX and OPEX

separately. It is also tells us to have the staff (human resources) related costs also

summarized. Since a project has typically longer time scales than the annual reports,

we have to take into account the time value of money when calculating these KPIs.

Costs saving expectations are difficult to map onto individual projects. Usu-

ally this is implemented by creating an alternative project plan, where everything

would be done continuing with some old technology. Then they compare the two



projects and declare that the new technology provides a certain amount of virtual

savings. Although business unit leaders like this style of argumentation, financial

directors are normally not happy with virtual savings, they would like to see only real

savings. Real savings are based on historical data and not on comparing two future

predictions. In IMS services historical comparisons would be impossible in most

cases. However, if we go up to a project portfolio level this may start making sense.

However, such financial modeling activities we leave to the financial controlling

department and do not consider as part of our current scope.

Another potential benchmarking possibility would be some kind of intensity

measures for comparing how much resources we used up for providing an IMS ser-

vice for a certain amount of subscribers and for a specific level of SLA. Although

this kind of data is not available yet for benchmarking, we will put such KPIs into

our financial models to keep this option open.

4.6 Proposed Modeling Tools

4.6.1 Available Modeling Tools

In our company SAP is the only available tool for financial engineering be-

sides the Excel worksheets. Cognos, STEM or any other more sophisticated system

were not available. None of them could solve our problems as discussed in 3.3.2

Modeling Software.

The existing business case models in Excel were not standardized, so practi-

cally almost nothing can be reused directly from previous projects. This led us to

design the IMS service business case models brand new, only taking into account

some basic recommendations from our financial directorate.

4.6.2 Excel Workbook Requirements

In this section we summarize the major requirements that we took into ac-

count when designing the Excel workbooks for our IMS service models. The inter-

ested reader may find further details in the Appendices.

An IMS service business case model shall be composed by modular work-

sheets that guide the workflow of the necessary analysis steps and provide the needed

structure for proper access controls. It is important to support transparency with well

designed scorecards and graphical presentations. Peer-to-peer review and consensus



finding is an efficient tool for improving the reliability of predictions and mitigating

potential cheating or fraud.

All worksheets shall be organized such that financial data could not be en-

tered by non-financial departments. They should only use natural measures for input

data. All financial values will be calculated automatically or modeled by a profes-

sional financial analyst. Each workbook shall include a RACI and a CRUD list that

would match with the officially approved process modeling system (e.g. ARIS). The

natural measure inputs shall checked graphically against product cycle experiences.

The worksheets must include a mandatory revenue breakdown structure to fa-

cilitate easier comparisons with other projects or historical data. It should also de-

scribe revenues in terms of major market segments. As a minimum: retail and bus i-

ness customers shall be separated.

The worksheets must include a mandatory cost breakdown structure for simi-

lar reasons to the revenue breakdown. Costs must be grouped into two major catego-

ries: CAPEX (capital expenditure) and OPEX (operational expenditure).

CAPEX would include such items as technology acquis ition costs paid to

vendors, internal implementation and system integration costs, project management

human resources costs derived from the MPM time sheet reporting system. Every-

thing else should be added here, that would become part of the asset activation in the

accounting system.

OPEX covers such technology implementation related cost factors as vendor

technical support, training, human resources for service operations, leasing of under-

lying infrastructure, energy and cooling, data center renting, and spare buffers for

fixing unforeseen problems.

OPEX shall also cover business implementation related cost factors related to

marketing, sales, customer relationships. The major items would include customer

acquisition, marketing campaigns, churn, customer termination, sales costs, customer

care and provisioning costs, etc.

The project business case evaluation summary sheets shall be supported by

graphical charts helping to interpret the various values on the scorecard. Internal fi-

nancial calculations should be also presented through graphical means. This would

give some tools to both the analyst and the auditor to detect errors. NPV tables might

have a NPV/discount rate profile displayed in graphical form, where the various in-



terest rates could be marked. This would help to handle the IRR correctly as a sens i-

tivity measure instead of a return on investment KPI.

4.6.3 Software Technology Requirements

All the Excel sheets must avoid the usage of VBA code, since these tables

will be used by non-programmers, and big VBA libraries would totally destroy the

goal of transparency for all stakeholders. In our Excel workbooks even the usually

hidden global variables might be found easily, since they are just normal cells.

Not using VBA code requires a move away from classical procedural pro-

gramming as used in almost every financial modeling spreadsheet we could study

(either taught by textbooks or sold as commercial tools). We have to build upon the

principles of functional programming (like LISP), and finite recursions, even for ma-

trices, with head-and-tail traversal.

Our design goal is to handle a maximum of few hundred projects in the capi-

tal budgeting portfolio, so Excel tables could accommodate the number of items. We

rely on the exponentially growing memory and CPU capacities to enable a literate

programming style, where we always focus on the clarity of the calculation for other

human beings. We leave to optimization to the Excel platform. By using functional

programming we also let the underlying software to decide on how to make parallel

threads in the computation. Since multi-core processors are quick becoming the

norm, we should not worry too much about suboptimal algorithms. However, by us-

ing more auxiliary cells for interim calculations we could even easily optimize the

CPU usage, too. Memory is very cheap indeed, so we do not try to spare with it.

Another new requirement, compared to older Excel models, is the intensive

use of colors, fonts, and graphics to guide the human reader. In many cases, Excel

worksheets has to be printed, so for a long time the laser printer limitations discour-

aged the use of these features. Everything had to be designed for black-and-white.

Today we have cheap color printing (even in A3 size) and huge 24- inch color moni-

tors at a very affordable price. So we have no reason to stick to the old outdated limi-

tations.



4.6.4 Reference Implementation

We have attached a reference implementation of our IMS services financial

modeling concept. It includes Excel templates for project evaluation and budgeting.

The templates are also used for illustrative examples in IMS service projects dis-

cussed in more details in the next chapter. All the data used in the examples are syn-

thetic and not based on actual values of any operators. The goal of the examples is to

demonstrate the usage of the modeling tool and not to give real life profitability

analysis.

Each workbook follows a similar architecture. One sheet is used to summa-

rize the results of the calculations for peer-to-peer review. Separate sheets are used

for inputs and outputs. The rest of the sheets are used for calculations and modeling.

In the NPV calculations we use separate lines for the discount factor making

recursive formulas easier to handle. We use a fix calendar for each project, but with a

shifting window based on the actual analysis date entered as an input. The milestones

of the product cycle are taking into account in the self-auditing tools, so no one could

enter revenues before the service is launched, and no one could add costs once the

service is terminated and all equipment is impaired.

The major NPV and NFV analysis tables have a variable time scale at the top.

However, for many purposed we need equally spaced timelines, too. So we added

auxiliary table at the bottom to generate for example controlling charts. In sensitivity

analysis we use the dynamic chart concept [Holden 2007] to display the KPIs as we

change the input parameters.

In each template there is an explanation of color coding. Wherever it was ap-

propriate we included some self-auditing features. It is the assigned maintainer’s

responsibility to fix all auditing problems before passing the file further in the work-

flow.

The interested reader should refer to the Appendices for further information

on how we implemented the requirements described in previous sections.

4.6.5 Modeling workflow

The Excel models shall be organized according to data ownership, or revenue

and costs responsibilities.



First of all the general market scenario descriptions shall be composed includ-

ing the analysis of value proposals and market segments. Based on this a market

forecast shall be assembled in Excel format. This shall be expressed in such meas-

ures that could be charged in the underlying technology. We also have to determine

the various service components of the project. The traffic calculations shall be cross-

checked by the technology experts, but the accountability must stay with the market-

ing or business development departments.

After this the pricing policies could be determined. In real life the price bun-

dles might be extremely complex, so usually in financial modeling we have to make

some compromised and use some type of average values and simplified schemes.

Based on the proposed prices we transform the forecasted traffic into estimated reve-

nues. The revenue responsibility shall be at the business side, technology has only

the role to assist in having a proper rating simulation.

The next step is to calculate the major resource needs to implement the pro-

posed service. This is primarily in the domain of the technology departments. The

cost estimates shall be based on capacity numbers determined from the marketing

traffic forecasts. In most cases the supplier prices are fixed by longer term contracts,

sometimes even a price erosion formula could be added in the field of IMS services.

Usually the first few years of vendor technical support costs could be covered by a

guarantee, so OPEX could be relatively low while the service is just taking up.

Sometimes vendor pricing is based on a revenue sharing model. However, one of the

financial goals of migrating to IMS/NGN is to get rid of this scheme as much as pos-

sible and force the supplier into a cost based pricing policy.

Other general operational costs, such as marketing, sales, administration, etc.

could be added based on some historical activity-based costing schemes probably by

the business development or the financial controlling department.

The modeling workflow is summarized in Figure 4-3. The input data tables

from various departments are organized into separate workbooks for easier access

control. One workbook combines these inputs into a financial business case model.

This investment project plan file is maintained by the financial controlling depart-

ment.



Figure 4-3. Modeling workflow overview

Start modeling

Analyze market Market

forecast

Establish pricing

Business Development

Forecast traffic

Design technology

Identify resources

Traffic?

Technology resources

Technology

Apply vendor prices

Procurement

Vendor price catalog

Revenues

Costs

Assemble business

case Controlling

Service feasibility

study

Send to portfolio planning

Business Case

Pricing policy

Usage estimates

Plan ca-pacities

Traffic?

Financial policies



5 Application of Financial Models for IMS Services

5.1 General Templates for IMS Services We have attached on the accompanying CD some illustrative examples how

our new Excel business models could be used for making better founded decision on

investment proposals for new IMS services. In the next few sections we briefly ex-

plain the underlying market situation and emphasize the special features of each case.

Each example business case is organized as a new project under consideration

for the annual CAPEX budgeting process. Each project has its own Excel work-

books, and the results are fed into the CAPEX planning workbook.

In the attached examples for IMS services we also demonstrate how to take

into account the specific features and the technology architecture. The breakdown

structure for each type of service extends the common project templates. Once we

want to fill these worksheets with real life data, we would benefit from this embed-

ded expert knowledge. The attached examples are just illustrating the usage of the

Excel tools and cannot be considered as a real life scenario analysis for any real

product.

For further details the interested read shall refer to the Appendices.

5.2 Video sharing The very first demonstration of IMS services was peer-to-peer video sharing

from Nokia. Almost all N and E series phones have this function embedded. It is a

very primitive service, since it is based on the information stored in the local address

book and do not require any AS on top of the IMS core [Figure 5-1]. First a CS voice

session is opened using a phone number from the CS domain. While talking on this

connection a parallel IMS session could be opened for video sharing using another

phone number from the PS domain. In contrast, the Ericsson weShare solution is

based on an AS architecture that requires a downloadable client and is not supported

by embedded terminal software.

In our business case example for video sharing we illustrate a costs and reve-

nue breakdown structure for the Nokia peer-to-peer approach. Our estimates are

based on the announcements of video sharing from TMN Portugal, TIM Italy, and

AT&T Wireless USA.



Figure 5-1. Video sharing architecture

5.3 Presence and network address book Presence is mainly an enabler for instant messaging applications in the Inter-

net. It is used to indicate of someone is willing to take part in a chat. In classical te-

lephony the availability of the partner is only checked at call setup time, and if there

are some problems with it, we will get back various tones. Redirecting unsuccessful

calls to a voice mail system became its own market called “call completion” services.

A recent example is the notification SMS sent about missed calls in mobile networks.

Presence in IMS is taking over the classical instant messaging idea and ex-

tends it to all session based services. The OMA XML Document Management Server

(XDMS) enabler is used to manage the information database behind the presence

services. Presence in most cases implemented together with group and list manage-

ment, or OMA resource list server (RLS) features on the same server, although logi-

cally they are not strongly related [Figure 5-2]. As we later describe it presence is a

critical underlying service for instant messaging, push-to-talk, next-generation te-

lephony, and combinational services. It could be utilized as a standalone service, too,

just for communicating important information without any further integration. Pres-

ence as a standalone service already requires a maintenance of user data, so adding a

network based address book is very natural. Once we have this directory, further ex-

PLMN

IMS Core

IMS Core

A B

PLMN

1

2

3

4 5

6

7 8



tension by group and list management is also a good idea. This leads to a full XDMS

enabler implementation.

The big issue is with presence that it can generate a lot of traffic if not con-

trolled properly. If a customer wants to have real- time status information for thou-

sands of items on a large buddy list, then it will generate a huge amount of traffic

depending on the method of status updates. Of course, the operator wants to get a

compensation for this resource usage, while the customer does not to pay for it. Ven-

dors are still struggling to find out a compromise to make large scale commercial

launch possible.

Figure 5-2. Presence architecture

In our example business case for the presence service we assume a full ne t-

work address book extension with group and list management included. We provide

a detailed structure for the typical cost elements and for the possible rating schemes.

Our modeling worksheets enable the designer to check the effect of fine tuning the

information synchronization parameters.

5.4 Instant messaging Instant messaging is not a new service. It is already well established globally

on the Internet and also getting a widespread acceptance on mobile phones in USA

[Walton, 2007]. There are multiple competing technologies, such as Web based,

XMPP, OMA IMPS (Wireless Village), pure SIP/SIMPE, and IMS SIP/SIMPLE

[Figure 5-3] or session-based.

IMS Core

IMS Core

A B

4

XDMS Presence

AS Network Address

Book

1

2

3

5

6

7

8



One of the biggest problems with instant messaging that it could take away

revenue from SMS and thus a lot of operators are reluctant to introduce or endorse.

However, the big Internet players (Google, Yahoo, MSN, etc.) are moving into the

mobile phones through both the handset vendors and some other operators. Accord-

ing to [Walton 2007] in Europe the GSMA preferred Personal Instant Messaging

(PIM) solution will be preferred, and in many case marketed as a natural continua-

tion of SMS under the name of SMS+.

Figure 5-3. IMS PIM architecture (SIMPLE)

The future of IMS based personal instant messaging is quite uncertain, al-

though instant messaging in general is clearly the future. This is because the IMS

based IM is little bit late in the market and the others are already so well established,

that it would be difficult to replace them. However, there are a lot extra features of

IMS based IM that would make it more attractive and give it a chance. It could reuse

both the IMS infrastructure and the common XDMS enablers, so marginal costs

could be minimal on the server side. It may have a lot synergy effects with other ap-

plications such as push-to-talk, general network based address book, location based

services, mobile portals, m-commerce, and combinational services with classical

telecommunications resources. The mobile operator could also leverage its bran and

special customer relations.

The biggest deal in instant messaging is network address based, presence en-

abled new graphical user interface (GUI). It is believed by many in the industry, that

this will be the only surviving user interface in the near future. Every multimedia

IMS Core

IMS Core

A B

1

XDMS OMA Pres-ence AS

Network Address Book

PIM Instant Messaging

AS 2

3

4

5



communications, even simple phone calls, would be started from this single inte-

grated GUI. Using this integration to full extent is available only for mobile opera-

tors, so probably they could win back some lost market share if they stop hesitating

and start rolling out IMS based instant messaging finally. According to the latest

roadmaps of handset vendors the first commercial grade embedded multimedia in-

stant messaging clients will be available in the first half of 2008. In our opinion, this

would not be good enough to handle all legal and regulatory problems with manag-

ing personal information properly, so the earliest commercial launch would be most

likely delayed to the Christmas season of 2008.

The blocking factor of handset problems for instant messaging is not serious

as with other IMS services, since the majority of currently used handsets are already

equipped with Wireless Village clients, and IMS based instant messaging could be

made backward compatible with these clients. Embedded clients are thus much eas-

ier to find for instant messaging. As [Figure 5-4] illustrates the downloadable clients

will be not very popular with operators, since the logistic and servicing of customer

installed clients is very difficult. Ignoring the pre-IMS Wireless Village clients could

be a big mistake, even if we opt for an IMS based instant messaging vision.

It is possible to introduce two types of services: a premium service with more

capable IMS terminals, and a normal service with old IMPS clients, but all within the

same community and providing a smooth migration. This can be even extended with

a mobile portal based access, too. Of course, text based chatting is not really new or

sexy, but having a community established, and adding multimedia session capabili-

ties through the IMS clients give a clear advantage to those who could not afford to

utilize IMS. Another big opportunity is to link into existing social network sites. For

example, Magyar Telekom owns already iWIW, the bigger Hungarian community

site. If they could create some synergy between iWIW and the instant messaging

service, then it would give a big incentive for the customers to prefer the T-Mobile

instant messaging service.



Figure 5-4. IM client enabled handsets forecast

These changes in technology and marketing initiatives mean that we are just

in time for creating new investment business cases for IMS based personal instant

messaging. Our example Excel workbook illustrates that effect of infrastructure re-

use. Here the specialty is that besides the IMS core, the XDMS enablers (presence,

group and list management) is also an important factor in the calculations. If we have

excess capacity in these components, then marginal costs could very low. If we need

to go to the next capacity level in the enablers just because of this service, then cost

would go significantly higher, but still better then with vertical silos, since most of

the integration costs could be still spared.

Our pricing models are based on the corridor of mass method [Kim and

Mauborgne 2005]. This is a significant change form the current European or Hungar-

ian practice. However, if we look at the policies of T-Mobile USA, they use to the

extreme: each message have the same price, independent of the technology (SMS,

MMS, e-mail, IM). This pushes usage to the more innovative, newer, and cheaper to

operate solution, with causing any problem for the user in the migration process. In

the uptake curve estimation we use the data from [Walton 2007] with some correc-

tions based on our own experience.

5.5 Push-to-talk Push-to-talk is a half-duplex voice service for peer-to-peer and group-based

communications similar to a walkie-talkie radio, but using normal mobile phone and

the mobile network. Basically, it would work even on GPRS, but when users really

pick it up, the network might crash. It became very popular in the USA and failed



miserable in Europe [Mavrakis and Kamal-Saadi 2006]. In the USA it was used

originally because of the lack of SMS services.

Figure 5-5. IMS OMA PoC architecture

The early adopters in Europe, such as T-Mobile, have a difficult time now

with the first generation of Push-to-talk Over Cellular (PoC). Although the PoC ve n-

dors prepared for IMS based solution in 2005, the lack of IMS infrastructure and

proper IMS terminals moved them into pre-IMS proprietary solutions. The most

characteristics example is the Nokia PoC offering. Both the servers and the clients

are proprietary, and only a small number of handsets could be used, and the service

enablers are organized into a vertical silo, totally in contradiction to the IMS concept.

It also required a dedicated APN, so no other IP based services could be used in par-

allel with PoC. This is a big marketing issue, since PoC alone is not so attractive than

as a part of multi-service bundle. There were also a lot of other problems with the

marketing strategy of PoC. So the costs skyrocketed, and the revenues did not come,

a total disaster was happening. Termination of PoC services is in the air, and some

disgruntled high-profile customers will generate a significant churn in the near fu-

ture.

[Mavrakis and Kamal-Saadi 2006] forecasts that probably a new start will

happen once OMA PoC compatible solutions could be deployed. We agree fully, that

the new IMS based OMA PoC [Figure 5-5] would look much better in the business

case. However, the previous failure will make deciding managers very cautious, so

the financial investment calculations will be challenged strongly. We also have to

IMS Core

IMS Core

A B

1


Network Address Book

OMA Push-to-talk

AS

6 7

2

3

4

5



note that PoC could evolve into a Push-to-anything service [Figure 5-6] that gives a

much bigger marketing potential with only adding some software updates to the PoC

clients and the PoC AS.

Figure 5-6. Push-to-anything roadmap forecast

What would be the big difference in our new PoC business case proposal?

There are a lot of significant cost savings: no need for extra SIP proxy, no need for

dedicated group and list management, no need for a very expensive charging system,

just a small little application server on top of the existing IMS infrastructure. The

only problem is the push by the vendor for recovering the lost revenues with the pre-

vious supply. But if we ignore Nokia and go with smaller vendors, then we could

easily put together a one magnitude (!) cheaper solution.

The blocking factor currently is the lack of IMS OMA PoC capable terminals.

Nokia is still putting proprietary clients into their phones that could work over IMS,

but not with an OMA PoC AS. Currently, up to 10% of the customer terminals are

Nokia PoC enabled in Hungary, but it is very risky to go with a Nokia terminal only

marketing strategy. So we have to wait another 1-2 years before we could even think

launching IMS based OMA standard PoC again on a larger scale. And then comes

the last, but most important question: is it possible that instant messaging with pres-

ence could kill PoC altogether?

Our example PoC business case demonstrates the advantages of the IMS phi-

losophy. The major cost driver is the OMA PoC terminal and the OMA PoC applica-

tion server licenses. Server hardware costs are relatively small, and integration costs



are kept to a minimum. We propose a significant change in the pricing policy based

on the corridor of the mass strategy [Kim and Mauborgne 2005]. We definitely need

lower prices than we had with the first pre-IMS PoC introduction.

We can estimate from the business model how many subscribers we need for

becoming profitable. This makes it much easier to control the marketing effort and

establish a gradual introduction to the market with a lot of control points where we

can manager the inherent risks.

5.6 Presence based IP telephony (voice and video) The original focus of IMS development for UMTS Release 5 focused on re-

placing the basic voice telephony service with a packet-switched version. As it

turned out this was not very attractive, especially that Release 4 solutions were

priced very competitively. No marketing manager could be convinced by an IMS

based pure voice over IP services. They do not see any advantage of doing it, while

the voice telephony ARPU is declining 10-20% each year [Merry 2007]. They are

struggling to find new revenue sources instead of accelerating the price erosion fur-

ther by endorsing VoIP. Some operators even tried to filter out Skype and other in-

dependent VoIP players and modified the service contract to disallow mobile VoIP at

all. In many countries this is against the regulations, so they introduced an artificial

jitter practically rendering the concurrent services useless. This is a never ending

game, so probably it would better to make different product, that does something

much better then independent VoIP providers could do.

We propose one possible way out of this problem. IMS based telephony

should be a flexible multimedia offering with rate adaptation and presence built in

[Figure 5-7]. It should open the call control rules to the customer through a self-care

interface that is accessible by the Web, WAP, and some function even with in- line

signaling. The user could setup rules how to process incoming calls for multiple

identities and multiple terminals, and the rules might take into account calendars and

time schedules, too. It is also a basic proposition to have this service on any access

technology, only full FMC solutions have a chance in the future.

Converged operators have another advantage of providing a smooth migra-

tion path from CS to PS domain in both the fixed and the mobile networks. These

companies are installing such service delivery platforms (SDP) that may control from



the same application both the CS and PS telephony service. One example in Hungary

is the T-Mobile Telematrix solution. By default, rerouting CS calls while the call

setup is in progress is not available for independent VoIP providers, they have to

become a full classical telecommunication company to be able to do this.

Figure 5-7. IMS presence based telephony architecture

One missing technology is a standardized Voice Call Continuity (VCC) solu-

tion [Merry 2007], but this might be finished in 2007, so in the near future this block-

ing factor will be eliminated. Another problem is the lack of QoS support in the PD

domain implementations. This may need another 2-3 years to be solved. Yet another

issue is the lack of commercial grade IMS multimedia telephony clients. Nokia al-

ready deployed a basic IMS voice telephony client in all of their N and E series

phones. In 2008 we expect that Nokia will release a video telephony component and

other vendors will also follow with full presence enabled multimedia IMS phones.

Our IP telephony business case example takes into account these require-

ments and guides through these special elements in estimating the costs. The uptake

of the service reflects the fact that although the priced will further erode, the minutes

of usage (MOU) still have some space to grow.

5.7 Mashup services One of the new trends in the Web services spaces is to provide the user a spe-

cial portal where she can mix up existing services with new service to create a com-

plex combination of many different elements. These user controlled combinational

IMS Core

IMS Core

A B

1


Network Address

Book IP Teleph-ony AS

6

7 8

9 10

11

2

3

4

5

Self-care



services are called “mashup” and recently becoming almost as trendy as the Web 2.0

mark. One of the first examples was opening up Google Earth as a mashup platform.

A similar, but more classical approach is called “OSA-Parlay”. This provides

a standard API for accessing all telecommunications services independent of the un-

derlying vendor specific solutions. It has a Web service variant called “Parlay-X”

that extends with the necessary security control and charging elements to open up the

telecommunications network to third-party developers. With the latest SDP platforms

the CS and PS domain services could be accessed through a single interface.

There is a huge untapped potential for telecommunications companies to open

up their whole infrastructure even to individual customers through a mashup portal.

The challenges are big in security and charging, but if we could solve these, then the

users would get a revolutionary new experience. Because IMS unifies the underlying

security and charging components, now we have a chance to have an efficient pla t-

form to support mashup services. For example, Microsoft and AT&T have already

shown public trials for these combinational solutions using the Microsoft Connected

Service Framework (CSF) and the Ubiquity IMS AS gateway [Mavrakis and Kamal-

Saadi 2006]. Commercial rollouts are expected in 2008.

Mashup portals could be used to test new product ideas. Simple user assem-

bled solutions might not scale to a large number of users, but professional program-

mer resources can be focused on already proven services. A new combinational ser-

vice will start on a mashup portal, then it may move to the operator SDP, and if

scales up to millions of user then it would be transformed into a dedicated IMS AS.

Mashup technology will change how services are developed and launched. It will

become similar to an evolution and less disruptive as the typical pattern today.

Our example business case for a mashup service platform illustrates the ad-

vantages of combinational services. We provide guidance for correctly taking into

account all important cost drivers.

6 Summary

6.1 Current Practice in IMS Financial Modeling Financial modeling of new services is usually done with Excel spreadsheets

at big telecommunications companies. The main reason is the flexibility of work-

sheets. However, there are problems with transparency, peer-to-peer review, consis-



tency, and reliability of the estimates. The models are used mainly for filtering, ac-

tual capital budgeting decisions and preferences are not really influenced by these

models. This creates a negative feedback, so they try to minimize the efforts to make

these business case calcula tions better. From the technology departments this whole

process appears as a blocking factor that should be circumvented as much as possi-

ble. The focus is on creating alibis and protection against auditing and not a real sup-

port for improved decision making.

These problems do not cause real business issues until the market is growing

quickly and errors and suboptimal decisions would not stop the overall success of the

company. However, as of today there are important signs of market saturation and

possible declines in critical revenue streams, so we should try to change the current

approaches and transform the business case tool into a really useful helping hand for

decision makers.

6.2 Proposed Financial Modeling Solution We have proposed a significantly improved way of creating new business

case calculations for planned IMS services. It is based on consistent, easier to under-

stand templates that facilitate transparency and peer-to-peer review thus making the

estimates less uncertain. We have illustrated the usage of these templates on some

new IMS service examples and a capital budgeting decision organizing workbook.

We have also demonstrated the advantage of applying modern software development

paradigms such as self-auditing and functiona l programming.

We have also analyzed what performance indicators should be used in evalu-

ating the investment business cases. In contrary to the current practice, we have sug-

gested to put more emphasis on the profitability index (PI) and give a different inter-

pretation to the IRR. In the modeling tools we took care about taking into considera-

tion other than pure financial aspects in CAPEX and OPEX budget allocation deci-

sions not to limit the flexibility of the responsible manager. However, the new solu-

tion guides the decision maker to better decisions by inducing a careful review for

those items where the final decision differs from the suggestion given by the finan-

cial modeling.

Our proposed modeling tool also manages such problems as normalizing dif-

ferent time-scale projects for comparison, or the issue of sunken costs contradictions



between investment decisions and past performance evaluations. We have main-

tained a financial scorecard for each project that is based on more dimensions than

used before. This may further improve making informed decisions and reduce incon-

sistencies in the project portfolio.

We have included various KPIs into our financial models that could be used

in the future for benchmarking the efficiency of service development and operations

activities.

6.3 Further Study There are a lot of possible ways to further study the modeling problems and

improve on the modeling tools. Here we just emphasize the most promising direc-

tions:

• Creating business models for each IMS service using the business model on-

tology and tools by [Osterwalder 2004], and then aligning our financial mod-

eling tools with these business models;

• Extending the business case templates for evaluating real options with proper

controls that cross-check the validity of the assumptions and avoid assigning

too much value too a real option;

• Improving the suggestions for budget allocation with integer programming;

• Applying the latest results in fuzzy modeling for handling the uncertainties of

the estimates in a better way [Carlsson and Fuller 1999];

• Integrating the Excel tools with the ERP environment and the teamwork sup-

porting portals and automating the whole annual CAPEX and OPEX man-

agement process;

• Migrating proven models out from Excel into more scalable commercial

business simulation tools (using the spreadsheets as prototypes for the final

solutions).

We should also investigate in the next few years if the investment suggestions

provided by our modeling tools were justified by the real life movements of the ICT

market. Interesting and challenging times are before us…


Bela Varkonyi Financial Models for IMS Based Services I

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Bela Varkonyi Financial Models for IMS Based Services A-1

8 Appendices

8.1 Implemented Financial Models We demonstrate our proposed financial models for IMS services by a set of

Excel files. The illustrative examples are organized into two major groups: planning

and estimation, historical facts and forecasts.

The planning and estimation is done with a variable time scale. We assume a

12-year calendar for each service. The calendar starts with the business year when

the project is proposed and the beginning of execution is planned. The first two years

have a monthly granularity to match with CAPEX and OPEX planning processes.

The next two years build upon a quarterly time scale to be in harmony with vendor

and product roadmaps. The remaining 8 years are planned on a yearly basis, since

estimates are uncertain in this long term.

The analysis for investment decisions might be done in any months of the

first two years. This reflects the practice of quarterly (or monthly) reviews and plan

modifications. The time scale always starts with the beginning of the first business

year to accommodate comparisons and aggregation. If we have to go outside from

the first two years, then a totally new project proposal and a connected business case

shall be created.

Once the natural measure inputs are estimated, the spreadsheets calculate the

expected revenues and costs. Based on these results both a NPV and an NFV analysis

are done. Three calculative interest rates are used in parallel: WACC, project specific

costs of capital, and varying cost of capital. The project specific rate could express

the special risks associated with the revenue estimations. These three scenarios are

displayed alongside in all summary sheets and charts.

Once the project proposals are ready to evaluate, the user has to establish the

links with the CAPEX and OPEX portfolio planning tools. These spreadsheets will

rank the projects based on one of the selected NPV values. Other KPIs, such as the

profitability index are added to the approval spreadsheet. The decision is done by a

manager manually, based on the ranking, the KPIs, and other aspects not included

here. After the decision is done, the model calculates the approved budget and pro-

vides guidance for further budget allocation. Once the available budget is exhausted

and all decision makers agree with the plan, the plan shall be frozen and treated as a


Financial Models for IMS Based Services Bela Varkonyi A-2

baseline for next review rounds. At each review cycle a new version of the planning

files shall be created. Previous plans must be protected and remain read only after

final approval.

Based on the capital budget allocation the OPEX plans will be also assembled

automatically by the modeling tools. One of the most important results is the cash-

flow needs calendar. The output of the final CAPEX and OPEX plans could be fed

into the ERP system for further processing and controlling.

When the planned business year starts for each project a facts and forecasts

file set shall be opened. The facts shall be entered form the ERP system or from the

data warehouse. If some data is still missing than other sources could be added, too,

manual entry is always available in our Excel files. The facts spreadsheets are always

based on a monthly time scale. They might have a long life-time. Our illustrative

templates and example files use a 12-year calendar.

Once the factual data is entered, the modeling tools will calculate various

KPIs taking into account the time value of money. EVA is computed for the current

analysis year. MVA is determined by compounding the past cash-flows. CFROI is

also derived from the historical data. These KPIs are also forecasted for future mile-

stones. The structure for discounting and compounding is the same as in the planning

files for easier comparison. Based on this similarity the controller may easily add

variance calculations to the facts files.

The financial analyst may also enter forecasts that are based not on some

vague expert opinion, but rather on the already collected historical data. These fore-

casts could be more reliable then the previously planned values. When a plan review

is ongoing, the systematically forecasted values could be used for revising the expert

estimates in the new revision of the project plans.

The factual data and systematic forecasts are also summarized into the

CAPEX and OPEX portfolios. The performance KPIs could be uploaded into the

ERP system for further processing (for example calculating the bonuses for the in-

volved managers).



8.2 Users Guide

8.2.1 Workbook structure

Each workbook is composed by multiple worksheets that follow a common

structure. The following table explains the usual sheets and their purposes:

Table 8-1. Standard worksheets

Worksheet name Explanation Target audience Summary Summary of critical tuning parameters

and KPI results Human reader, decision makers

Input Major inputs from other files or en-tered here

Analysts

Output Major outputs to other files Analysts Usage Service usage data sheet based on a

standard calendar Internal, data collec-tion

Pricing Service pricing schemes based on a standard calendar

Internal, data collec-tion

Revenues Calculated revenues based on a stan-dard calendar

Internal, analysts

Costs Calculated costs based on a standard calendar

Internal, analysts

FCF Free cash-flow analysis based on a standard calendar

Internal, analysts

Catalog Price catalog for resources to be pur-chased

Internal, analysts

Calendars Pre-computed calendars with various time-scale and life-cycle marking

Internal

_Aux Auxiliary calculations Internal

Beside the standard worksheets other sheets could be added for special calcu-

lations or documentation.

References between workbooks are done in most cases with symbolic names

to have more robustness. There is one exception when we want to utilize the formula

extension features where references shall be increased automatically for rows and

columns.

Most of the worksheets have a major heading at the top and a major index at

the left. Frozen window panes are used to help the reader while scrolling through

very long tables to interpret the meaning of the data cells.

Each worksheet shall have a version number at the top left corner. The bot-

tom of a worksheet is marked with a special color “End of worksheet” line.

The core part of a worksheet is organized into sections and subsections. There

is a hierarchical identifier scheme that enables referring to a row even when printed

without the original Excel cell addresses. Each important row has a Ref.ID field that



is used to compose cell reference symbolic names. These identifiers must be unique

in the whole workbook.

Major tables are at the top of the worksheet, while explaining charts are be-

low the corresponding tables to keep the timelines as close together as possible. The

layout is optimized for large monitor screening and not for printing. These docu-

ments shall be exchanged electronically only in normal operations through a file

sharing service.

8.2.2 Naming conventions

Normally we use the A1 reference style in tables where similar formulas are

used for multiple rows or columns. This facilitates easy addition of further rows and

columns while keeping the consistency of the calculations.

For absolute reference we frequently use symbolic names to help the analyst

to understand, debug, modify, and audit the formulas used. Symbolic names referring

to cells are written with all lower case. References to worksheets start with a capital

letter and continue with lower case. Array references always begin with an underline

character.

Symbolic names may be used to invoke global or local variables. A symbolic

cell reference could be specific to a certain worksheet. This is a local variable of the

involved worksheet and we allow the reuse of meaningful symbolic names for multi-

ple sheets by defining name spaces. The symbolic name of such a cell or array is

always structured. The tags are separated by dots. The first tag is the name of the

worksheet and creates a new name space. If there is a “Ref. ID” field for the cell or

array, then this is used for second tag. A further tag could be appended to express the

time base (y: year, q: quarter, m: month, w: week, d: day). Even more tags could be

added to further distinction of certain part of a line item. Workbook global cells are

referred with simple names, but tags could be appended, too.

The naming convention is design to help the human reader to understand the

formulas. Excel takes no care about the naming conventions.



8.2.3 Color coding and other visuals

We also use color coding, font emphasis, and charts to help the analyst to un-

derstand and control the worksheets. The intended meaning of cell filling colors are

explained in the following table:

Table 8-2. Color coding

Color code Explanation Context Light Green Manual input, could be replaced with

links or formulas in later versions Input data cells or worksheets

Green-Yellow Manual input parameter Input data cells or worksheets

Light Turquoise Linked data from another location Input data cells or worksheets

Purple Forbidden cells: nothing shall be writ-ten here, no meaning

Input data cells or worksheets

Green Normal or good: value is according to rules or recommendations

Results

Yellow Warning or problem: value is getting outside of the required range

Results

Red Alarm or error: value is violating rules or recommendations

Results

Rose Attention: important information, summary

Output data cells or worksheets

Peach Minor structural item Headings, separa-tors

Gold Auxiliary structural item Headings, separa-tors

Light Orange Major structural item Headings, separa-tors

Faint Blue Meta-data, audit result, or audit separa-tor

Headings, separa-tors

Grey Internal data, auxiliary calculation Interim results

Font styles are also used to express meta- information. Characters in bold no-

tify that the cell is very important. The italics style is used to separate structural or

internal information.

For complex calendar based tables it could be quite difficult for the human

reader to see the pattern in the large number of cells. So we usually include in those

table charts that summarize those data sets in graphical form that could be the most

likely related to expert opinion and historically learned baseline patterns. If there is

an accidental mistyping or error in some of the cells, the chart can quickly pinpoint

by displaying an anomaly in the normal tendencies.



8.2.4 File linking

File linking without a strict control may cause a lot of chaos in complicate

Excel workbooks. We impose some rules how to do file linking. Based on these

well-defined rules the auditor can check the compliance more efficiency.

Inputs from another workbook shall be organized onto a single “Input”

named worksheet. Outputs to another workbook shall be collected together onto a

single “Output” names worksheet. This is especially important for larger data tables.

The “Summary” worksheet is the only place where we may have some other file

links for a more natural structure and flexibility, but this should be limited as much

as possible.

8.2.5 Self-audit tools

We propose the usage of self-audit tools wherever it seems appropriate. These

calculations are marked with a special color frame and usually located at the right or

bottom edge of the worksheet.

Typical audit calculations might include if the timing of a data item makes

sense according to a life-cycle model. For example, costs can occur between the start

date of the project and the impairment of the last allocated resources. Revenues could

be collected only after the service has been launched and before the service has been

terminated. Energy costs may appear already once the system is commissioned but

the service is not launched yet and could extend into the period when the service is

already terminated but the system is not decommissioned yet.

Life-cycle audits are based on an interval marking in the calendar and com-

bining it with some checksums of the time indexed values.

Another major type of audits is the reconciliation of multiple computing paths

that should lead to the same result. This is typically possible with totaling quarterly

or yearly aggregates.

We do not include all possible audit schemes, since this would make the

worksheets too complicated. Only a few characteristic self-audit tools added. But

even this limited audit approach may significantly reduce the number of undetected

errors from the very beginning.

The numbers of failed audit tests are summed up and color highlighted for

each worksheet into a single cell, so the maintainer can quickly check if the whole



worksheet has any major consistency problems. The human readers just have to

search for the red color.

8.2.6 Exception handling

One of the most important reasons to use Excel for financial modeling is the

flexibility of modifying and tuning calculations. By showing a lot of details of the

steps how to compute results, we enable hooking exception handling into the simula-

tion structures. This transparency also helps developing the Excel workbooks in a

stepwise refinement, with an evolution though many consequent versions.

For example, we may get a value through a complex automated workflow,

but we recognize that there must be some problem with the interim results. We can

quickly fix it by overriding the values and formulas, proceed with urgent tasks, and

solve the underlying problems later. Such workarounds are hardly possible in tightly

controlled ERP or closed commercial modeling software environments.

It is also possible to build an important model with only manual inputs and

later replace the manually entered cells with a complex model behind it, by adding

further workbooks and worksheets and then linking the interim results onto the cells

where we previously entered everything by hand.

It is easy to misuse this flexibility and create a chaos in non-trivial Excel

model. So we have to impose some rules upon ourselves and make it transparent for

the auditors helping them to find potential problems. The basic rules could be sum-

marized in the following list:

• Use the color coding to express the intention how a cell shall be used (e.g.

manual input or underlying calculations);

• Study the Excel made suggestions about inconsistent formulas and tweak the

structure and calculations until Excel would not complain;

• Keep formulas short and simple, complicated computations shall be broken

into multiple stages (memory is cheap, so do not spare it);

• If you need an exception, then use at least the comment field attached to the

involved cells for explaining the reasons;

• Follow literate programming principles, so design the worksheets for your

fellow analysts and not for the computers;



• If it helps understanding, do not hesitate including comments and explana-

tions into the surrounding cells of the exceptions occurrence;

• If the exception should become permanent, then clean-up the self-audit tools

not to give disturbing alarms.

After you managed to keep the deadlines and solve the immediate issues,

please do not forget to review your model and try to transform the exceptions into

integral features of the model. Exceptions are allowed, but they should be avoided as

much possible for convincing the decision makers that they could trust in the finan-

cial models.

8.3 Content of the Attached CD We have summarized the Excel template files on the attached CD in the fo l-

lowing table:

Table 8-3. Template files

File name Explanation Inputs Outputs Owner IMS_Service_Plan.xlt Project planning

data Marketing and technol-ogy estimates

CAPEX and OPEX portfo-lio plan

Controlling

IMS_Service_Fact.xlt Facts and forecasts ERP and data warehouse

CAPEX and OPEX portfo-lio facts and forecasts , next round of plan-ning

Controlling

IMS_Service_Mark.xlt Marketing esti-mates

Expert opin-ions

Project plan -ning

Business development

IMS_Service_Tech.xlt Technology esti-mates

Expert opin-ions

Project plan -ning

Technology

IMS_Service_Proc.xlt Vendor price cata-log

RFI, RFQ, public data

Project plan -ning

Procurement

IMS_CAPEX_Plan.xlt CAPEX portfolio plan

Project plans ERP Controlling

IMS_OPEX_Plan.xlt OPEX portfolio plan

Project plans ERP Controlling

IMS_CAPEX_Fact.xlt CAPEX portfolio facts

Service facts and forecasts

ERP Controlling

IMS_OPEX_Fact.xlt OPEX portfolio facts

Service facts and forecasts

ERP Controlling

For each project proposal an XLS file is generated from each service specific

templates. The “service” word in the template filename is replaced by an abbrevia-

tion of the proposed project name. Each project proposal contains only synthetic data



for illustration and cannot be interpreted as a real business case. The project codes

are listed below:

Table 8-4. Illustrative project codes

Project code Explanation Enablers used

Provider for

Vshare Peer-to-peer video sharing

None None

Prenab Presence and net-work address book

XDMS PIM, PoC, IP Tel., Mashup

Mpimp r Multi-media per-sonal instant mes-saging with pres-ence

XDMS None

Omapoc OMA push-to-talk over cellular

XDMS None

IPtelp IP telephony with presence

XDMS None

Mashup Mashup portal XDMS None

Since these files are currently under further development, the protections and

access restrictions necessary in a production environment are not configured yet.


Bela Varkonyi Financial Models for IMS Based Services B-1

Declaration

I declare hereby, that this master thesis is my own and original work, where

all used resources are properly referred inside the text and listed in the References

chapter.

Budapest, 5. October 2007.

……………………………

/Bela Varkonyi/

Nyilatkozat

Kijelentem, hogy a szakdolgozat a saját eredeti munkám, amelyben minden

felhasznált forrásmunkát az irodalomjegyzékben megneveztem.

Budapest, 2007. október 5.

………………………….

/Várkonyi Béla/


Bela Varkonyi Financial Models for IMS Based Services C-1

Acknowledgment

I would like to express my thanks for Zsolt Bedo, my thesis supervisor for his

special help. I am also indebted to all the MBA program teachers who made it possi-

ble for me to write this thesis work by benefiting from their successful teaching ef-

forts.

I would also like to thank my colleagues Gabor Pal and Balazs Birck at the

Financial Directorate of the Magyar Telekom MLOB (T-Mobile) to share their valu-

able experience in practical financial modeling.

A special thanks goes to my family, my wife, and my little daughter who

have survived the long hours I was spending away from them on assembling and

formulating all the materials for this thesis work.

I dedicate this thesis to my little daughter, Victoria who will have now more

time to spend with her daddy.

Documents

MBA Thesis 2007 Bela Varkonyi