Development of “System Dynamics-based” Flexible Strategy Game-card:
Exploring Future Performance of the Indian Telecom Service Providers
Neetu Y adav! and Sushil”
1Senior Research Fellow and Research Scholar, Department of Management Studies,
Indian Institute of Technology Delhi, New Delhi, India.
? Professor, Department of Management Studies, Indian Institute of Technology Delhi, New
Delhi, India.
Abstract
India has emerged as one of the fastest growing telecom markets in the world and witnessed a
teleconmunication revolution in the last two decades. In the recent time, the Indian telecom
industry is experiencing a najor transformation with stagnating revenues, declining ARPU’s, and
stiff competition, which is overall impacting its performance. The present study seeks to explore
the future growth perspectives for telecom service providers by identifying other revenue options
and their impact on performance. The integration of system dynamics methodology with a recent
developed performance management framework helps to bring the issue further in a case context
by developing a system dynamics based performance management model portraying the impact of
data based services on the performance with the help of many scenarios. STELLA 10.0 software
package has been used for model and scenario developments. The study proves the integration of
system dynamics methodology improves the holistic understanding of telecom operating system
showcasing the integration of subscribers’ view and data based services create the future of
telecom service industry in this transforming business environment.
Keywords: Flexible Streay g game-card, System Dynamics, Indian telecom service providers,
Performance measurement and management
1, Introduction
“There is always room for improvement, you know-it’s the biggest roomin the house.”
Louise Heath Leber
Every system changes/improves over time and the future behavior of the system can be created
fromwithin. This holds true for the field of performance measurement and management which has
witnessed enormous developments in last two decades. Lot of transformations has been made in
terms of incorporating integrative perspective of performance from merely looking from financial
perspective. These developments suffered from some criticism highlighted in the literature, as the
lack of cause-effect relationships, dynamic view of the performance, integration of customers’
viewpoint related to performance etc. There are some recent developments related to performance
Management frameworks intending to overcome some of the major criticisms highlighted in the
literature. Flexible strategy game-card is one of those developments that look the performance
dominantly from two perspectives, i.e. enterprise perspective and customer perspective.
This is well received in the literature that the application of system dynamics (SD) methodology
with balanced scorecard (BSC) which is one of the most popular frameworks, help to overcome
some of the criticisms and help to use it in dynamic business environment. Thus, it can be stated
that the integration of SD methodology with performance management frameworks/systems lead
to better understand the dynamics of strategic interventions and performance results. This provides
the motivation to carry out the present study which seeks to explore the linkages of flexible strategy
game-card and system dynamics methodology in the context of performance of the Indian telecom
service industry which has experienced transformation in the last few years. So understanding the
future performance of Indian telecom industry with the help of integration of SD and game-card
sets the agenda of present study.
The present study seeks to integrate flexible strategy game-card and SD to achieve the following
objectives:
RO1: To determine the strategic indicators related to dimensions of game-card to
develop the dynamic structure for the Indian telecom service providers;
RO2: To mapping the stock and flowdiagramto simulate and analyze the dynamics
of performance in the future;
ROB: To find out and analyze the key policy parameters which create future
performance of the enterprises and to suggest policy directions to enhance the
performance of the Indian telecom service providers in a case context.
To achieve the above stated objectives, the study has been structured in the following way: After
delineating the research background and objectives in section1, section 2 deals with literature
review detailing the available research related to dynamics in performance management systems,
description of flexible strategy game-card and brief about SD methodology. Section 3 highlights
2
the conceptual research framework by integrating game-card and SD. The main body of the paper
describes in section 4 by detailing the model construction and testing. Section 5 brings out the
discussion related to development of different scenarios which help to analysis different policy
parameters related to future performance of telecom operator. The last section carries out
discussions and contribution of the study.
The expected outcome of the study is development of a SD based performance management model
for the Indian telecom service providers leading to analyzing effect of key policy parameters on
future performance.
2. Literature Review
In order to integrate flexible strategy game-card and SD methodology and application in context
of the Indian telecom service providers, it is imperative to detail out the existing literature on these
issues. This section highlights the literature related to flexible strategy game-card, SD
methodology and growth trends of the Indian telecom service industry.
BSC, one of the most dominantly used strategic performance management system highlighted by
the practitioners, suffer the criticism of being static and lack of causality. The concept of causality
which is not extensively explained and very often such causal relationships are assumed to be
unidirectional in BSC (Norreklit, 2000). The other criticism highlighted is that it lacks dynamics
and does not consider time-delays between cause and effects (Bianchi and Montemaggiore, 2008).
The last one decade showed enormous interest related to explore dynamics of BSC, some of the
mejor studies are: Ritchie-Dunham (2002); Akkermans and van Oorschot (2005); Strohhecker
(2007); Bianchi and Montemaggiore (2008); Capelo and Ferreira Dias (2009) and Bamabe(2011),
who have conducted case studies and simulation based experiments for the development of
“dynamic scorecard” taking into consideration feedback approach. These studies had explored that
SD based scorecard comparing to traditional BSC specifically improve strategic architecture by
using mapping tools, better representation of causal structure of the system, and helps in analysis
of systematic structure in tens of relationships between structure and behavior (Bamabe, 2011).
Thus, it is well established fact that the integration of SD modeling and simulation techniques help
to give better results with performance management systems/frameworks.
Flexible strategy game-card (Sushil, 2010), whichis one of the evolving performance management
frameworks, emphasizes two perspectives of performance, i.e. enterprise perspective and,
customer perspective. The enterprise perspective covers all the major stakeholders, while customer
perspective exclusively considers the customers’ view point related to performance of enterprise.
Enterprise perspective deals with situation-actor process-performance related parameters, thus
covering the extemal environment as well as intemal environment. The strategic indicators related
to extemal and intemal situations, actors, processes are dealt under this perspective. Financial and
norr financial indicators are considered related to performance. The customer perspective deals the
performance of the enterprise from customer’s perspective which is linked to value in offerings
and relationships to the customers. The structural overview of Flexible strategy game-card has
been demonstrated in Figure 1.
Performance Measurement
Enterprise Perspective Customer Perspective
Performance
or
}¢——>|
i | Actor «>| Process |
| Strategic
| Interventions Relationships
! Situation
1
f
i T
1
' 1
i
1
I 1 Review and
! | Performance Gaps
1
f
1
Figure 1: Flexible Strategy Game-card (Adopted from: Sushil, 2010)
This framework supports the full cycle of strategy development, execution, strategic interventions,
and corrective actions, thus supporting the LAP (Leaming-Action- Performance) framework, and
this provides it an edge to existing performance management frameworks. The LAP framework
provides the dynamism to this framework via considering the causal thinking and feedback loop
leaming. This framework has a strong theoretical background supported by strategic management
theories, as stakeholder theory, contingency theory, dynamic capabilities view and resource-based.
view (Yadav et al., 2012).
Looking toward the literature related to SD, it is a well-established methodology for understanding
the behavior of the system and it has been widely used in various fields. SD is a quantitative
method which is based on the theory of feedback control and takes the computer simulation as a
mean to study the complex systems (Su, 1988). ). The unique characteristic of this methodology
is that it helps to understand the complex systems by the way of developing causal loop diagrams
and stock and flow diagrams. These elements help to study the behavior of the system. SD employs
both qualitative and quantitative approach for understanding the system The problem
identification, definition, system conceptualization and development of stock and flow diagrams
and causal loop diagrams are part of qualitative approach; while developing mathematical
equations, simulation and sensitivity analysis and scenario building are the part of quantitative
approach. Thus this methodology is more than just technical tool to develop models for
mathematics, physics and engineering but can be explored to social sciences and management.
The modeling process proposed by Sterman (2010) provides a whole picture of development and
implementation of model for real world problem which is exhibited in Figure 2, and it consists of
following steps (This study follows these steps for model development):
Articulating the problem to be addressed;
ii Formulating a dynamic hypothesis about the causes of the problem;
iii | Formulating a simulation model to test the dynamic hypothesis;
iv. Testing the model until satisfied that it is suitable for the purpose;
v. Designing and evaluating policies for inprovement.
— Real World
Decisions
(Organizational
Experiments)
1, Problem Articulation
a (Boundary a
5. Policy
Formulation
& Evaluation
Information
Feedback
2. Dynamic
Hypothesis
a
3. Formulation,
4. Testing
Strategy, Mental
Structure, Models of
pecan meres “— Real’ World
Figure 2: Modeling Process in System Dynamics (Source: Sterman, 2000)
The last part of literature review section seeks to characterize the performance of Indian telecom
industry. Indian telecom industry, which is one of the performing industries since its inception has
witnessed more than 965.52 million subscribers as on end of June, 2012 (TRAI report, 2012). The
major growth trends of the industry can be summarized as follows:
= India is the second largest wireless network in the world after China.
= The overall tele-density has reached to 79.58 as on 30" June, 2012, where the rural tele-
density has increased to 40.66.
= Total intemet subscribers has reached to 23.01 million as of June, 2012.
= Growth revenues (GR) and adjusted growth revenues (AGR) for telecom industry for QE
June-12 has reached to 52512.10 cr. and 35499.01 cr. respectively thus employing an
increase of 6.64 per cent in GR.
The industry has shown a saturation in voice based services, as the Average Revenue per User
(ARPU) has shown a declining trend, so the prospective growth and revenue sources are value
added service (VAS), wireless and broadband services. With this reference, it witnesses the
appropriateness of selection of the industry to investigate the research objectives.
3. Research Framework
On the basis of the two perspectives, and six dimensions of flexible strategy game-card, the key
variables of the study has been identified through conducting semi-structured interviews with
industry experts, academicians and telecom subscribers. SD methodology has been used to
understand the behavior of system of telecom service providers and the simulation of the key
decision parameters help to identify new strategic interventions and develop business plans for
improved performance results. Figure 3 exhibits the conceptual framework of the research which
has been followed to conduct the study.
roe ee eee eee eee eee eee eee eee 1
L Il
Flexible Strategy Game-card {
!
Performance Offerings '
Identification Simulation ! Improved
of Strategic Actor. Process |«—»>| and : Performance
Factors Finding >) Results and
related to —_—- Key Policy 1 | corrective
Performance Situation Relationships Parameters | 1 actions
l
Enterprise Perspective Customer Perspective sD }
!
Figure 3: The C onceptual Framework of Research
The scope of the study is limited to the wireless and value added services provided by one of the
telecom operators and its impact on the performance. As already mentioned that there is saturation
in voice-based services and ARPU is declining, the impact of wireless, VAS and intemet based
services on the performance of telecom service providers are examined in the study.
The five steps given by Sterman (2010) for development of SD modeling has been followed in the
study to develop SD based performance management model. STELLA 10.0 software package has
been used for the development of the model and to run the simulation.
4, System Dynamics Model C onstruction and Testing
The main part of this paper is about the discussion of SD model construction and testing has been
placed in this section. One of the Indian telecom service providers have been chosen as the case
context to investigate the research issues and achieve research objectives. The case company is
part of one of the biggest business group of India. The company aims to provide end-to-end
telecommumnications solutions for business and residential customers across the nation. It covers a
full range communication services including, voice based services, connectivity based services,
and location based services, and market to market based services. It is one of the largest mobile
service operators in India and has a reach to many towns and villages of India with its 2G and 3G
services. As there is stiff competition in the market, and revenues from voice service are declining,
the scope of data based service is enormous contributing to revenues which is going to be examined
through this performance management model which is developed in following steps.
For model development, five step process of Sterman (2010) has been followed, the discussion in
details is as below:
Step I: Problem Definition, Variables and Scope
The objective statements of present study is clearly stated as development of system dynamics
based performance management model exclusively looking the impact of data based services. The
overall impact of key policy parameters and govemment policies has been attempted to figure out
through the study.
As already mentioned, the present study has taken flexible strategy game-card as a theoretical
basis, so the key variables which are strategic factors related to performance have been identified
for two perspectives, i.e. enterprise perspective, and, subscriber perspective. Despite using the
Classical method of literature review for identification of factors, semi-structured interviews have
been conducted with senior level management and telecom subscribers. They were asked to list
performance related factors as per the game-card dimensions; these interviews have been analyzed.
using ‘thematic content analysis, and themes from the qualitative data have been identified.
There is very limited understanding available related to customers’ view point about the enterprise
performance, here, it is very well taken care of by discussing and interviewing the telecom
subscribers about their perception of strategic factors related to telecom operators performance,
and thus, the strategic factors related to customer perspective have been captured (For detailed
analysis of identification of strategic factors, see Yadav et al., 2012). The strategic factors
identified from this analysis are illustrated in Table 1.
Table 1: Key Dimensions and Variables
Dimensions Main Variables
Situation PE1: Competition level
; PE2: Govemment policies
i ; Actor PE3: Customer satisfaction
BS PE4: Employee productivity
Process PES: Business process efficiency
Performance PEG: Profitability
PE7: Revenue growth
PE8: ARPU
Customer
PE: No. of subscribers
: Value in offerings PC1: Quality of telecom services
} PC2: Call tariff
PC3: VAS offerings
Value in relationships PC4: Brand image of operator
PC5: Customer support services
Step II: Formulation of Dynamic Hypothesis
“The dynamic hypothesis is a preliminary sketch of the main interaction and feedback loops that
could explain observed and anticipated behavior’ (Morecroft, 2007). The dynamic hypothesis
examined in the study are:
H1: The integration of subscribers’ view point lead to future performance of telecom service
provider.
H2: The application of data based services create the future performance of telecom service
provider.
For examining these dynamic hypothesis, causal loop diagrams (CLD) have been developed both
for enterprise factors and subscribers’ factors through group discussions with company experts,
industry experts, academicians as well as subscribers. As the emphasis of the study lies on
discussing the transforming scenarios of telecom industry, changing trends of mobile usage for
subscribers, and otherrevenue options forthe industry were major discussion points. An integrated
CLD showing the interaction of enterprise related factors and subscribers’ related factors have
been developed, which is exhibited in Figure 4. An innovation has been done in CLD by adding
the interpretations of all the links of CLD and thus making it an ‘interpretive CLD’.
Heavy expense of fees
adversely affect profits
_... ofVASandvoice ° f
1
Process ( VAS architecture | Offerings VAS ‘i
investments ~_| i ae
_ Pf offerings
7 icensing vain cetay
ee x offerings of VAS
ee : ity of
Revenue sharing hese telecom services
aan ere nah ieee tls aie
A RSD and other
: Competition eats 1
investi lead! Subscribers
good quality services
Situation
Government
decides per cent of
revenue sharing .- Govt. policies
Government decides
the licensing fee
investments
Positive word of
No. of mouth
Actors
Employee
productivity
Customer
satisfaction index
Number of
Operators
cestes oS Se |
Effective a L_
handlings
Figure 4: Interpretive Causal Loop Diagram (CLD) integrating Enterprise and Subscribers’ Perspectives
9
Integrated CLD portrays that subscribers’ related factors give feedback to actors as well as
performance. Govemment policies give a guideline about the per cent of sharing of revenues
between the goverment and the company, and the licensing fee. So, these are exogenous factors
for telecom operator and it has to realign its’ strategies to cope up these factors. As already stated,
there are many sources of revenues of company which are coming fromvoice based services, data-
based services and some other services. For providing ample number of value based services, the
company is making investments in VAS architecture, there will be a delay in the investments and
the VAS offerings, which is exhibited by a straight line cutting the loop. There are other
investments as, R&D investments, infrastructure investments, tower investments, which will help
to enhance the services.
The subscribers’ related factors, as high brand image index leads to positive word of mouth and
will attract more subscribers, customer support services lead to increase customer satisfaction
index and employee productivity and thus integration of subscribers’ view point give feedback to
lagging indicators of performance.
The lagging indicators of performance, as gross revenues, number of subscribers, ARPU and
profitability (retum on total assets) are driven through competition (number of operators), brand
image of operator, VAS offerings, and customer satisfaction index of the company. There is some
per cent of ARPU coming from VAS and some per cent of ARPU is coming from voice-based
services.
The polarity of the relationships have not been specified in the CLD, as there are some
relationships where specifying polarity found difficult. Some relationships have very clear
polarity, as licensing fee will negatively affect profitability
Step III: Formulation of Model
For development of systemdynamics based model, STELLA 10.0 software package has been used,
where stock and flow diagram has been developed. The values of parameters have been collected
from case company and focus group discussions have been conducted before developing the
model. Some of the assumptions were drawn while developing the model are as follows:
= The licensing fee and revenue sharing has been paid on the basis of gross revenue on
yearly basis.
= The cost components of telecom operator has been kept constant.
= As the competition increases (in terms of number of operators), the subscribers of case
company will reduce.
Keeping these assumptions in mind, stock and flow diagram has been developed for examining
the dynamics of investments, gross revenues, number of subscribers, and ARPU from voice and
data services. Figure 5 exhibits stock and flow diagram of SD performance management model
integrating all sub-systems.
10
eueeice frestiont
voice ARE!
eas VAS Th VAS ARFU NORE ETA
VAS INV
subscription rate compa
number of operstors
Sf ange in other INV
rate other INV
O =
3!| completion Pte
empeyée productivity
Figure 5: Stock and Flow Diagram of SD Performance Management Model
ll
Looking at the dynamics of number of subscribers, which is getting influenced by brand image
index, customer satisfaction index and exogenous factor competition. The company has a chum
rate of 15 per cent for its subscribers. Brand image index has an influence from customer support
services in terms of per cent of complaints handled, customer satisfaction index, and quality of
telecom services in terms of call completion rate. Customer satisfaction index is measured through
customer support services and per cent of VAS offered.
The other side of the model is showing the dynamics of different types of investments, VAS
offerings, ARPU gain, and gross revenues. With a delay of one year, the investments in VAS
architecture and infrastructure and R&D makes an impact on VAS offerings and quality of telecom
services. ARPU gain for the operator is from two sources, one is from data services and other is
from voice services. The operator is paying the licensing fee at 10 per cent of the gross revenues,
and revenue sharing with the govemment is 8 per cent of gross revenues. As there are many
intermediary processes have been compressed during the modeling, their combined effect has been
captured in different correction factors (C1, C2, etc.).
Thus, the integrated dynamics of data based services, investments in VAS architecture, and
feedback from subscribers’ view point to the performance of telecom operator create a SD based.
performance management model looking towards the future prospective of performance in recent
business environment.
Step IV Model Testing
It is imperative to conduct different tests for building confidence in SD models, and confidence
accumulates gradually when model passes more tests and the correspondence between model and
empirical reality can be identified. Here, the testing of model structure has been done with the help
of following tests (Forrester and Senge, 1980):
a Structure-verification test: This test encompasses the comparison of model directly with
structure of the real system that the model represents (Forrester and Senge, 1980). For
conducting this test on performance management model, the stock and flow diagram has
been discussed with some of the experts from telecom service industry and case company.
Although the model has suppressed the effects of some of the intermediary processes, yet
it doesn’t contradict with real life settings.
b. Dimensional-consistency test: This test entails the dimensional analysis of model’s rate
equations (Forrester and Senge, 1980). This is first and basis task for model testing to
check whether the equations are dimensionally consistent. Here, all stocks are calculated
onyearly basis and amount has been taken as ‘000 INR.
c. Boundary adequacy test: This test considers structural relationships necessary to satisfy
the model’s purpose. This test asks whether the model aggregation is appropriate and it
includes all relevant structure. This test involves developing a convincing hypothesis
telating proposed model structure to a particular issue addressed by a model (Forrester and
Senge, 1980). Here, performance management model hypothesizes to examine the impact
of interaction of subscribers’ view point and investment in VAS architecture on future
12
performance of case company. The model includes all those stocks and auxiliaries
capturing the impact of these issues.
Step V Simulation and Analysis
As the main purpose of the study is to visualize the impact of different govemment policies and
the future performance perspective for Indian telecom operator in the case context, the simulation
has been run for the model and dynamics of different stock variables have been captured. The base
year has been taken as 2010 and simulation has been run for next 10 years. The stocks chosen for
analyzing the model are all lagging indicators of performance, as gross revenue, number of
subscribers, customer satisfaction index and subscriber's related factors, as brand image index.
Figure 6 shows the integrative dynamics of all these stocks for the case context.
. A) 10.0
Time 9:12PM Sat, Mar 09, 2013
00
agar 2? Telecom Performance Mangement Model
Figure 6: Dynamics of Lagging Indicators related to Performance
The graph clearly highlights that there is exponential growth in subscribers’ numbers due to an
increase in brand image index and customer satisfaction index. The behavior proves that by setting
a positive brand image of operator and providing quality services, there is positive word of mouth
from the existing subscribers which influence to more potential subscribers. Brand image index
and customer satisfaction index are showing goal seeking behavior and moving toward reaching a
goal of 10. Gross revenue, which is showing dramatic growth post 2015, which is prompting more
investments in VAS architecture.
13
As the STELLA graph shows the integrative dynamics on a multi-scale, the exclusive dynamics
of each stock is difficult to understand here. Separate graphs for all the lagging indicators and
subscribers’ related factors have been drawn which are demonstrated in Figures 7 to 11.
GROSS REVENUE
—e— Gross rev (in ‘000 INR) —m— change in gross rev (in '000 INR)
18000
16000
14000
12000
10000
8000
6000
4000
2000
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Figure 7: Dynamic Behavior of Gross Revenue
Gross revenue which is shown as a function of ARPU gain and number of subscribers has shown
a dramatic growth post 2015. This implies that more investments in VAS architecture helps to
fetch more revenues to the company, as the ARPU from voice services are declining, this revenue
option widens services horizon and scope for revenues for telecom industry. Figure 7 explicitly
captures the dynamics of changes in gross revenue and simulated values of gross revenue till year
2020.
Figure 8 helps to support dynamic hypothesis H1 by showcasing the impact of subscribers’ related
strategic factors. Subscription rate, which is a function of competition, brand image index and
customer satisfaction index. The subscribers’ dynamics holds the assumption of negative impact
of competition on the subscribers’ numbers. Here, the impact of competition is balanced by brand
image of operator, quality of services and customer support services, and the dynamics shows an
exponential growth in number of subscribers.
14
NUMBER OF SUBSCRIBERS
—e— number of subscribers (in numbers) am change in subs
3000
2500
2000
1500
1000
500
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Figure 8: Dynamic Behavior of Number of Subscribers
Brand image index which has been measured on 1-10 scale, shows the impact of quality of
services, customer support services and customer satisfaction. The model shows brand image
index as a goal seeking behavior which is aspiring the goal of 10. The dynamics of brand image
index and customer satisfaction index also support dynamic hypothesis H1 by capturing the impact
of quality and prompt services to subscribers’ view point toward operators’ performance. Figures
9 and 10 exhibit dynamics of brand image index and customer satisfaction index respectively.
BRAND IMAGE INDEX
—e—Brand image index = —™—change in brand image
12
10
8
6
4
2
0
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Figure 9: Dynamic Behavior of Brand Image Index
15
CUSTOMER SATISFACTION INDEX
—e— Customer satisfaction index —m— change in customer satisfaction
oT
CHENWEREUD AE ©
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Figure 10: Dynamic Behavior of Customer Satisfaction Index
To examine the dynamic hypothesis H2, dynamics of VAS investments has been analyzed. As
Figure 11 showcases, with an incremental growth in initial years till 2014, it has shown an
exponential growth in post 2015, with some delay it shows the impact on VAS offerings and.
ARPU gain from VAS. The increments in VAS architecture investments give a positive feedback
to ARPU gain, and ultimately achieving high gross revenue, thus supporting dynamic hypothesis
H2 in the case context.
INVESTMENT IN VAS
—e—VAS Inv (in ‘000 INR) te change in VAS INV (in ‘000 INR)
1600
1400
1200
1000
—
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Figure 11: Dynamic Behavior of Investments in VAS
16
5. Scenario Building
To achieve research objective 3 (RO3), policy parameters affecting and creating the future
performance of case company have been identified and their impact have been analyzed. A brief
description of those analysis has been demonstrated in this section with the help of some scenarios
developed here.
= Scenario one: Policy about New Entrants
Indian telecom service industry is facing stiff competition. Recently some govemmental
regulations as, MNP (Mohile number portability) helped to attract subscribers of
competitors, but the chum rate of subscribers has also increased. The policy related to new
entrants will bring more players in the market and thus increase the competition and will
decrease number of subscribers for case company.
= Scenario two: Investments in VAS Architecture
Indian telecom industry is facing the problem of stagnated ARPU because of low and
competitive tariffs. The only other option to increase ARPU is through data based services
and VAS offerings. The more investments in VAS architecture will widen up the service
portfolio for telecom companies, and will help to increase MoU (Minute of Usage) and
data downloading.
6. Discussions and Conclusion
The behavior of existing system helps to create the future of that system. This has been studied
and analyzed in the present study. The Indian telecom industry which is experiencing tremendous
changes, the future performance can be created by studying the Indian telecom company at its
present. Thus, a performance management model integrating system dynamics methodology helps
to investigate the issue of concem. The advantage of using system dynamics methodology
experienced by authors, as interpretive CLDs’ and stock and flow diagram helps to understand and
investigate the problem effectively.
With the help of modeling the performance management system, and running and analyzing the
simulation, it gives better understanding about the major concem and drivers for creating future
performance. The exponential growth observed in gross revenue and subscriber numbers is due to
special consideration of subscribers’ related factors, giving quality and prompt services and
building a positive brand image. The SD based performance management model suggests strategic
interventions in terms of developing new strategies or making corrective actions in existing one,
as investment in training of customer care executives lead to effective complaints handling thus,
increase the customer satisfaction and brand image. The investments in R&D and infrastructure
help to build effective service platform and can help to provide better network comnectivity and
good voice quality calls and services, and help to enhance quality of telecom services.
The present study makes contribution to the strategic dimensions of telecom industry exclusively
in Indian context by suggesting some of the scenarios and their likely impacts of future
performance. Although the study is limited to a case context, yet this can be considered by other
telecom operators, as most of the Indian telecom operators are working on almost same service
7
platform The integration of SD methodology and flexible strategy game-card provide a
mechanism to develop a performance management system for any enterprise of interest, and thus
can see the likely future of their performance without any risk. The interpretation of the links of
CLD gives better understanding at the time of development of stock and flow diagram.
Some of the limitations related to present study can he listed as, many processes effecting the
lagging indicators and services for subscribers have been suppressed and combined effect has been
presented here, which impact the clarity of the model. If all the processes would have been
incorporated here, the model would become as complex as the real world. The correction factors
have been determined with the help of experts’ discussion, but there are some statistical techniques
(Eg, regression) which can be used to calculate these parameters, which gives more statistical rigor
and build confidence in the model. The retrospective validation of the model could not be
performed due to lack of availability of data related to some factors.
The model can be further validated by using the data of some other telecom service operators,
which can be considered as the future scope of the present study. Sub-systems of performance
Management systems can be modeled separately, and it helps to avoid the complexity of SD based
performance management system. As, strategic decision making is a dynamic process, the model
can be run for one year and then the impact of policy parameter can be studied, necessary changes
could be incorporated and then it can run further, thus it brings dynamics in decision making and
ultimately helps to achieve targeted performance results.
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