Modelling Market Opportunities for Telecommunications in
the 21st Century
Alison Brady, Ann Matthews, Frederic Lagacherie,
BT Laboratories,
Martlesham Heath, Ipswich, IP5 3RE, England.
Tel: +44-1473-642758. Fax: +44-1473-620455
e-mail: alison.brady @bt.com.uk
ABSTRACT
The previously secure position enjoyed by established telecom operators is currently being threatened
by the liberalisation of their markets. Competition now comes from a range of network and service
providers. It is therefore important for telecoms operators to be able to model possible threats and
opportunities and so plan their market strategies.
This paper analyses one of the biggest challenges currently facing established fixed line telecoms
operators; namely how to measure, and hopefully reduce, the number of customers that might cease
their fixed line service in preference for using a mobile phone for all their telecommunications.
Parameters examined include call-cost tariffs and usage patterns.
As their market share for voice calls decreases, fixed networks need to compensate by encouraging the
telecoms market for other services to grow. This paper assesses the delicate balance between tariffs,
services, and the resultant customer base obtained by fixed-network and mobile operators. In this way,
fixed network operators can begin to understand how customer numbers and revenue generation for
other services must be increased to at least compensate for this loss.
A Systems Dynamics model has been created which acts as a powerful scenario simulator. The model
itself is described and results are discussed. Although the analysis considers the balance between the
fixed network and the mobile phone markets, the systems thinking technique is generic. This technique
can be reapplied to other types of competition, such as that offered by Internet Service Providers.
1 INTRODUCTION
With the ever increasing rate of change of the products and services provided in the
telecommunications arena, it is beneficial for a service provider to view how these changes may affect
the size and value of its consumer base. This knowledge is imperative when allocating company
resources to best support and maintain these consumers, at the same time as actively encouraging new
users, and increasing profitability.
In particular, the telecoms operator needs to understand the delicate balance between the costs incurred
by the customer, the demand for services and churn. Residential customers are particularly sensitive to
price, so varying the tariff structure is one very strong way of influencing customer demand. It can be
used to grow or restrict a particular market according to a company's ability to service that market.
However, it can be difficult to holistically appreciate how the changes to one market sector would
affect another.
As one way of responding to this position, a generic Systems Dynamics model, using the 'Powersim'
tool, has been constructed. This allows the dynamic effects of tariffing, market demand and most
importantly, product substitution to be assessed.
2 DESCRIPTION OF MODEL
In this paper, we shall consider the product substitution between mobile and fixed telephony. It is
possible that as mobile tariffs continue to fall, some customers will cease their fixed line, in favour of
only using a mobile phone, (mobile-only).
We shall consider a fictional metropolitan community with a fixed population of 1 million customers.
The market has been separated into two different types of phone users: fixed+mobile' and mobile
only’. The nature and size of the market groups that have been used within the model are:
Students (12%)
Young Professionals (15%)
Young Families (41%)
Teen Families (8%)
Middle-Aged Couples (14%)
Senior Citizens (10%).
Fictional average tariffs of ECUs per minute have been used for each of the fixed and mobile service
offerings. These tariffs are different for each market segment to reflect their different patterns of usage.
In an attempt to replicate many of the dynamic factors that a strategist or market forecaster would want
to vary, different factors were set up as variables within the model. These can be changed or flexed to
assess their elasticity within the market place. For example, the proportion of fixed to mobile calls has
been varied for each of the market segments to reflect different types of use. For example, in the
scenarios explored in this paper, Young Professionals are deemed to make twice as many mobile calls
as fixed whilst senior citizens use fixed lines fifty times more than mobile.
This paper concentrates on flexing just one of these variables, namely tariffing, and the impact this has
on the numbers of customers for fixed+mobile and mobile-only.
' Customers with fixed and mobile telephony are specified as definitely subscribing to fixed telephony.
They may or may not also subscribe to mobile services.
? Mobile-only customers definitely have mobile telephony and do not have fixed telephony.
3 EXAMPLES OF THE OUTPUTS FROM THE MODEL
As an example, let us consider the Young Families segment and determine which of the Fixed+mobile
or Mobile-only options is the least expensive, according to the amount of time they use telephony per
month.
Original Mobile Tariff
805
60+
=
ro)
= 404 ~~ Fixed+mobile(youngtam)
oO =X_ Mobile_only_bill(youngfam)
20+
0. + + + 1 Figure 1
0 50 100 150 200
Minutes Usage per Month
The graph in Figure 1 depicts the size of the telephony bill for a particular customer segment, (in this
case Young Families), us the total average minutes telephony per month for customers in this
segment. If all the usage currently on fixed+mobile telephony is switched to mobile-only telephony
then the equivalent bill is illustrated by the "Mobile_only_bill" in this graph.
As can be seen from the graph, using the fictitious tariffs for these services, the Mobile-only service
would only be better for them on a cost basis as long as usage remained below 25 minutes a month.
Consider next, Figure 2, which illustrates the effects on the relative bills for Young Families created by
reducing the Mobile tariffs per minute by 20%, whilst leaving Fixed and Mobile rentals and the Fixed
tariff per minute all unchanged.
Mobile Tariff reduced by 20%
50
404
= 304
=)
re)
= ~@~Fixed+mobile(youngtam)
D 491 > mobile_only_bill(youngfam)
103
Figure 2
0. + + + 1
0 50 100 150 200
Minutes Usage per Month
Reducing mobile tariffs by 20% extends the crossover point, at which using mobile-only telephony is
cheaper than combined fixed+mobile telephony, to 35 minutes. Once the usage increases beyond this,
then the extra charge incurred by having to pay two separate line rental charges becomes negligent in
terms of the high call costs of mobile phones.
Unless young families make minimal use of the phone i.e. only just over a minute a day, even with
20% discount they are better off having both a fixed and mobile package and paying the two rental
fees.
Original Mobile Tariff
80,
60+
=)
re}
W 405 = Fixed+mobile(student)
oO ~~ Mobile_only_bill(student)
204
0. + + : 1 Figure 3
0 50 100 150 200
Minutes Usage per Month
Now let us compare the effect of tariffs on Young Families bills with the effects on the bills of a
different customer segment. Consider, for example, Students. Figure 3 shows the combined effects of
the original mobile tariffing scheme, (as used in Figure 1 for Young Families), together with the usage
pattern for Students.
The crossover point for students is four times higher at 100 minutes per month, (compared to 25
minutes for Young Families). Below this 100 minutes point, students would benefit from mobile only,
above this point it would be cheaper for them to use Fixed+mobile. However, the gradients of both
lines for students are very similar making the decision to go for one option compared to the other not
an obvious one, based on cost alone.
Consider now the effects of reducing the tariffs by 20%, as shown in Figure 4.
Mobile Tariff reduced by 20%
60+
50+
s
Ss
i
2
£.
C~ Fixed+mobile(students)
Bill (ECU)
—X_ mobile_only_bill(student)
204
0. + + + 1
0 50 100 150 200 [Figure 4
Minutes Usage per Month
With the 20% reduction in mobile usage tariffs, the crossover point is moved out to 150 minutes. This
is still below the average phone usage of 6 minutes a day for the general population. Again the
gradients are similar making it not too drastic an error in terms of cost, if the student chooses the least
cost-effective option. Consequently, for students the choice between Fixed+mobile or Mobile-only,
based purely on tariffs is not obvious for the scenarios illustrated.
Now consider the effects of reducing the tariffs for Mobile-only by another 30% to give a total
reduction of 50%.
Mobile Tariff reduced by 50%
80}
60}
5)
(e)
W404 =X Fixed+mobile(student)
a ~~ Mobile_only_bill(student)
204
0 ' ; ' 1 Figure 5
0 100 200 300 400
Minutes Usage per Month
The crossover point where Fixed+Mobile becomes cheaper than Mobile-only is pushed out to 250
minutes, making Mobile-only a much more attractive option for students.
4 MARKET THREATS
One of the biggest threats for telco operators today is the churn of customers However, the
opportunities to change are easier than ever. The biggest hurdle for customers to face is often their
own lassitude. The model captures this factor by considering the propensity of a customer group to
change from Fixed+mobile to Mobile-only on a scale of 0 to 1. Students are considered to be very like
to change whilst senior citizens are regarded as being more reticent, as illustrated below in Figure 6.
High Propensity
-Students
-Young Professionals
Medium Propensity
-Young Families
-Teen families
Low Propensity
-Middle-aged couple
-Senior citizens
v
Figure 6
These propensities can be easily changed if it is desired to flex the scenarios.
The following graphs show the effect of reducing the mobile tariff by 50% on the proportion of the
customers, from each market segment, moving from one network option to another. Please note that
the magnitude of the y-axis in Figure 7 is ten times that in Figure 8. Note also that the x axis represents
the average usage of telephony for a particular market segment.
600,005
Numbers of Customers per Segment for Fixed+mobile
500,000+
g
o
€ ——Student
& 400,000+
2 ———3 3 ~~ youngprot
gi
a _ youngfam
2 300,000} 3
_,—teenfam
ol 4
g —5~— middleagecoup
200,000} ~g-sencit
5 5 5
1<6 1.6 1*6 1 Figure 7
cs im H+ 4 1
0 100 200 300 400
Average Minutes Usage per Month per Segment
60,000,
Numbers of Customers per Segment for Mobile-only
50,000}
—— =
& 40,0004 student
o
g _ youngprof
g 2
= 30,000} = youngfam
co
a See OS —4-teenfam
5 7 ——a
3 i 1———1_,_middleagecoup
20,000}
a ee —gsencit
10,0004
fo =
—=—=—_—=—=_ F5————— 5: (5 A Figure 8
$$ +e 1
Co) 100 200 300 400
Average Minutes Usage per Month per Segment
So, for instance, let us suppose that Young Families use 100 minutes of telephony per month. Then,
from Figures 7 & 8 about 380, 000 Young Families will subscribe to Fixed+mobile, whereas only
about 25,000 will use Mobile-only. Suppose we revise our estimate of the average usage per month for
Young Families to 300 minutes. Then the number of Young Families using Mobile-only will have
dropped to about 21,000, whereas the number of Fixed+mobile customers in this segment will have
increased to about 386,000.
Consider now the general shape of the trends for customers for Fixed+mobile or Mobile-only. For
each of the six segments a very small proportion of customers will switch to Mobile-only and then only
if their monthly usage is exceptionally low. So, for the scenarios considered, it would seem that
Mobile-only is likely to seize just a small market share.
So, even with a 50% reduction in the Mobile tariff, most customers choose Fixed+Mobile as their
preferred network, particularly as their monthly usage per month increases. To gain a greater share of
the market, Mobile operators need to demonstrate to customers that their tariffs are low and that it is
financially beneficial for customers to cease their fixed line.
5 CONCLUSIONS
We have developed a product substitution model of which a specific example of mobile replacing fixed
telephony has been used. It is possible to flex the tariff scales, the propensity to change, the size of the
market and the size of market segment. This means that the model can be used to ascertain at what
level of usage it becomes financially beneficial for customers to switch between the two different types
of network provision for telephony.
In addition, we have modelled the effects on the market size of each customer segment caused by the
change in one tariff-type relative to the other, (here reducing mobile tariffs, whilst keeping fixed tariffs
unchanged).
It should be noted most especially that this model is generic and so is not restricted to just
Fixed+mobile and Mobile, it can be used for product substitution in other markets.
6 ACKNOWLEDGEMENTS
We wish to thank Mike Matthews for reviewing this document and authorising its release for
publication.
Footnotes
' Customers with fixed and mobile telephony are specified as definitely subscribing to fixed telephony.
They may or may not also subscribe to mobile services.
' Mobile-only customers definitely have mobile telephony and do not have fixed telephony.
