Indian Telecom PolicyUsage Of Network
Resources
Indian Telecom Regulator overlooking efficiency part of the Network Usage
This describes pricing as a tool for regulator to bring in efficiency by
optimizing deployment of Telecom Network resources. In absence of
this approach the Network capacity deployed to handle the busy
hour traffic (peak traffic intensity) is underutilized in non-busy hours.
The pricing discrimination and revenue management were used by
About The
Thesis
the operators with the sole objective of profit maximization. Pricing
as a tool for improving Network utilization was never explored. In
fact the TRAI, the Indian regulator never focused on Network
Utilization, assuming competitive market forces will automatically
take care of Network efficiency. The operators were able to pass on
the inefficiency to the users and not took much initiative to
overcome this inefficiency and only regulator can force them to for
greater network traffic harmonization.
• Operator Deploy Excess Network Resources/ Capacity to meet
the Network KPIs ( also to take care of future growth and take
advantage of economy of scale and scope).
• Pricing approach adopted by the regulator- forbearance
Background/
Purpose of
The Study
• Efficiency part of the network is overlooked by the Regulator
• Peak/busy hour and off-peak NW utilization differ widely –
“M” curve
• Operator collude indirectly and pass on this inefficiency to the
consumers
• Telecom Regulatory Authority of India Consultation Paper
onReview of Policy of Forbearance in TelecomTariff 6th
February 2012 , Page 8 “The level of tariff increase
affected by the telecom access providers as well as the
timing of such hike points towards the possible prevalence
of coordinated price activity behind the increase in tariffs
Background/
Purpose of
The Study
•
•
•
•
•
•
•
•
•
TRAI Focus Area
Call Drop
Other KPIs
Radiation Norms ( EMF)
Rollout Obligation ( MRO)
Implementation of MNP
Spectrum sharing/ trading
Infra Sharing
Law full interception
Net. Neutrality
• Efficient Network Usage
Objective
•
•
•
•
•
•
•
•
•
Quality
Quality
Quality/Public Safety
Network Reach/Penetration
Competition
Efficient usage of spectrum
Efficient usage of infra
Security
Free/ inhibited growth of
internet
• Social benefit
• The Regulator is overlooking the efficiency part of the
deployed network. Responsibilities of TRAI “Measures to
promote and efficiency to promote growth of telecom services”
- page 32 , The Telecom Revolution in India- Technology,
Regulation and Policy by Vardharajan and Sridhar 2012
Problem
Statement
• Hypothesis 1: Network resources (capacity) are not being
utilized efficiently during off peak hours and differ widely
• Hypothesis 2: There is scope of distribution of traffic in nonbusy hours by Regulator by implementing pricing tool.
• Hypothesis 3: Regulator, by adopting pricing tool can make
traffic distribution relatively uniform, and off load peak traffic
• Effort should be made to utilize more off peak period
• Automatically done in a fully competitive market ( TRAI
assumed it is competitive market)
What more
can be done
by TRAI?
• The Regulator can frame policy/ guideline so that the
operators focus more on Network Utilization in off peak
hours.
• Forcing operators to more utilize the off peak period
• Pricing tools ( mandatory implementation off peak
tariffs)
• By KPIs ( enforcing penalty for violation of KPIs)
• Economics, Quality of Service or Regulatory enforcement
Division of TRAI (out of ten divisions), may take the initiatives.
• The Regulatory intervention - implementing KPI - Peak Vs Non Peak
utilization ratio may increase the Network Utilization and efficiency.
• Available literatures do not specify any such ratio which is
optimal
• It may differ with technology, usage, and different stages of
growth journey
• Further study may be required , scope of future research
Options
Available To
Regulator
• Peak Pricing tool may be another option. Is it possible? If Yes, How?
• Lot of studies had been undertaken on peak load pricing on
Capacity Constrained Network for social welfare maximization
• Customers will be benefitted
• Operators benefitted
• Increased growth and penetration
• Studies have shown the network traffic is quite sensitive to
pricing ( positively related)
• Few of the operators ( Airtel) implementing “Happy Hour” usage
in isolated manner to maximize the revenue ( focus is not on
efficiency)
The Indian
Telecom
Services
Performance
Indicators
January 2 G- March,
2015
The Indian
Telecom
Services
Performance
Indicators January 3 GMarch, 2015
The Indian
Telecom
Services
Performance
2018 -19
The Indian
Telecom
Services
Performance
2018 -19
Typical Traffic Distribution on a Cellular System
100%
90%
SUN
80%
MON
70%
TUE
60%
50%
WED
40%
THU
30%
FRI
20%
SAT
10%
0%
Hour
Typical “M” Curve (Source: Zte Presentation)
• Focus of operator to meet KPIs (more on quality
oriented)
• Operators deploy resources based on the busy hour
usage (traffic), differ from off peak usage
Operators’
response to
the KPIs
• Operators deploy resources based on busy hour usage +
traffic growth in near future
• Off peak hour Network usage grossly underutilized
• Existing KPIs neglect efficiency part
• “M” curve indicates traffic pattern, flatter curve indicates
more uniform usage, no KPI to monitor this dimension
• The Regulator has no KPI to monitor deployed resources
vs utilization of resources
• The Regulator most probably thought market forces will
take care of this utilization issue
• Excess Resources deployment costs Operator in terms of
Capex Expenditure
• Excess Resources result inefficient usage of Network –
Operation cost Increases
• Presently the Regulator has adopted the tariff
forbearance
Disadvantage Underutilization
• If all Operators continue to operate in the same mode (
collude) the in-efficiency will be passed on to the
customers ( users)- Pay relatively high charges
• It has been proved Network Growth and usage (traffic) is
sensitive to price – Usage and growth increases with
decreased price (Piyush JAIN, 2003, Jain, Muller, and
Vilcassim,1999 , Bewley & Fiebig, 1988; Craver, 1976;
Craver & Neckowitz, 1980; Lago, 1970; Rea & Lage, 1978;
Schultz & Triantis, 1982; Yatrakis, 1972)
What
Regulator
can possibly
do?
• Peak pricing traditionally used to maximise social benefit in
capacity constrained industries where product or service is
technologically not storable Like Power, Airport etc.
“From an economic standpoint the problem is to find an
appropriate price policy that leads to the correct amount of
physical capacity and its efficient utilization, and that also
covers the full social costs of the resources used.” PEAK
LOADS AND EFFICIENT PRICING - PETER 0. STEINER (1957)
• The regulator can use pricing as a tool for increasing off peak
usage of Network. Reduced off peak charges may increase off
peak Network usage
• It has been observed telecom traffic ( usage) is sensitive to
tariff ( pricing), usage increases with reduction in tariff.
• It can also use KPI in terms of ratio of peak to off peak usage of
Network (Present paper does not focus on it, may be scope of
future study)
Policy
Making Body
and
RegulatorIndia
• Ministry of Communication & IT
• DOT ( Department of Telecom) 1985
• Telecom Board/ Telecom Commission ( 1989) Sam
Pitroda
• TRAI (Telecom Regulatory Authority of India)
1997
• TDSAT (Telecom Dispute settlement and
Appellate Tribunal - TRAI Amendment Act,
2000
Decision
Making
Process for
Telecom
Policies TRAI
Either Suo Moto or
request from DOT
Stake Holders’
opinion
TRAI Posts Pre
consultation
Post Consultation
paper
Submits recomnd. to
DOT
Telecom Commission (TC)
Examine recommend.
Source : The Telecom Revolution in India – Technology
Regulation and policy By Vardharajan, Sridhar Oxford
University Press 2012
Conduct open-house
Sessions
TC submits policy
proposals to Ministry of
Comm. and IT
Ministry Finalizes Policy
and gets cabinet
approval, if required
Objective of
Telecom
Policy
Early 1985
• Rapid growth of telecommunication sector
• World class Telecom Infrastructure for rapid
Economic growth.
• To attract private capital to upgrade and
expand telecommunication and services –
competition& liberalization
• Formation of DOT ( Department of Telecom)
1985
• Telecom Board/ Telecom Commission ( 1989) Sam
Pitroda
Post 1990 (First National Telecom Policy Declared-1994)
• Implementation of earlier plan
Objective of
Telecom
Policy
• Introducing a regulator (Almost similar to global approach,
split in functionality) to liberalize the market Formation of
TRAI – 1997
• TRAI Amendment Bill 2000 : Formation of TDSAT
• Implementation of National Telecom policy - 1994
• Connectivity on Demand
• Increase Teledensity and penetration
• All villages should be covered
• Quality of Telecom services should meet world standard
• Introducing the state of art technologies
• To protect defence and security interest of the country
VISION : “To provide secure, reliable, affordable and high quality converged
telecommunication services anytime, anywhere for an accelerated inclusive socioeconomic development.”
MISSION
National
Telcom Police
2012(Excerpts
from the
policy)
1.
To develop a robust and secure state-of-the-art telecommunication
network providing seamless coverage with special focus on rural and
remote areas for bridging the digital divide and thereby facilitate socioeconomic development.
2.
To create an inclusive knowledge society through proliferation of
affordable and high quality broadband services across the nation.
3.
To reposition the mobile device as an instrument of socio-economic
empowerment of citizens.
4.
To make India a global hub for telecom equipment manufacturing and a
centre for converged communication services.
5.
To promote Research and Development, Design in cutting edge ICTE
technologies, products and services for meeting the infrastructure needs of
domestic and global markets with focus on security and green
technologies.
6.
To promote development of new standards to meet national requirements,
generation of IPRs and participation in international standardization bodies
to contribute in formation of global standards, thereby making India a
leading nation in the area of telecom standardization.
7.
To attract investment, both domestic and foreign.
8.
To promote creation of jobs through all of the above.
The National Communications Policy aims to
accomplish the following Strategic Objectives by 2022:
National
Telcom
Police 2018
1. Provisioning of Broadband for All
2. Creating 4 Million additional jobs in the Digital
Communications sector
3. Enhancing the contribution of the Digital
Communications sector to 8% of India’s GDP from
~ 6% in 2017
4. Propelling India to the Top 50 Nations in the ICT
Development Index of ITU from 134 in 2017
5. Enhancing India’s contribution to Global Value
Chains
6. Ensuring Digital Sovereign
TRAI –
Statistics
TRAI
Statistics
2018-19
TRAI –
Statistics
• Out of total Teledensity 88% wireless
contribution is 86%
• Focus of study centre around wireless
• All data collection and analysis centre
around wireless/mobile communication
Literature
Review Studies
Effect of price on traffic:
• In developing countries like India, price elasticity
of demand for telecommunication services is
very high (Piyush JAIN, 2003) and plays an
important role for traffic growth and uses
pattern
• Kyoung Cheon Cha et.al in their paper
―Managing and modeling the price reduction
effect in mobile telecommunications traffic‖
(Kyoung Cheon Cha a, p. 2008), an individuallevel usage model for telecom services (for a
Korean mobile telecom service provider) was
developed and the effects on usage of a price
reduction were analyzed
Literature
Review –
Studies…
Contd.
• Optimal sequence of free traffic offers in mixed
fee-consumption pricing packages‖ (Maurizio
Naldi, 2010) discusses about pricing strategy
based both on a fee and on a consumptionbased rate (with a free traffic level included in
the bundle), to prevent churn, assuming that
the customer's demand is statistically known
and described by either the exponential or the
Rayleigh probability distribution
• Christoph Stork et.al in their paper titled ―Link
between termination rates and retail prices in
Namibia, Kenya and South Africa‖ (Christoph
Stork, 2014) discuss the link between mobile
termination rate reductions and retail prices in
South Africa, Namibia and Kenya
Literature
Review –
Studies…
Contd.
• Benchmarking telecoms regulation – The
Telecommunications Regulatory Governance Index
(TRGI) (Leonard Waverman, 2011) - It attempts
benchmarking an index of the effectiveness of the
institutional design of telecommunication regulators
for 142 countries that belong to the International
Telecommunications Union.
• In the article ―Technology, efficiency and
sustainability of competition in the Indian
telecommunications sector‖ (Das, 2000) the author
discusses the choice of any reform policy as the
trade-off between the loss of scale and scope
economies and cost saving from the reduction in
inefficiency of the incumbent monopoly facing
competition
Literature
Review –
Studies…
Contd.
• OECD Communication Outlook 2013 (OECD, 2013) :
The report was prepared in the relation of the
OECD’s work on the analysis of communication
policy in member countries. The report has one
section on ; Main Trend in Pricing; “During the
monopoly era, operators priced services using
factors such as time of day or day of the week to
determine which customers would pay higher prices
and which were more price sensitive, employing
efficiency-enhancing effects to manage peak loads
on their networks. They also employed factors such
as distance for much the same reason, regardless of
what could have been dictated by directly
attributable costs. Following liberalisation,
competition increased and these types of pricing
attributes largely disappeared in many markets”
Literature
Review –
Studies…
Contd.
• The effect of price on dial-up Internet traffic
has been described by Vannucci et.al (D.E.
Vannucci, 2003). South African data was
gathered on residential subscribers who
were making use of cheaper off-peak rates
for dial-up Internet service outside business
hours. Traffic intensity was found to be
heavily dependent on the call tariff.
• The present scope is limited to cellular services (Wire line
connectivity has declined to 2% refer TRAI press release
26/2016 ).
Scope &
Methodology
• Also in cellular in services we have limited our study to voice
traffic (for data traffic the throughput of data is reduced due to
congestion in peak hours, in contrast to voice traffic where it is
lost completely. Analysis on data traffic can be part of future
scope) :
1. Data usage is growing at rapid rate over voice
communication ( increased smart devices and
application even voice is an application over data, world
is moving towards IP connectivity)
2. It will be easier for the service provider and user to
develop and choose application for data - off peak hour
use of network
• For Hypothesis 1 : Analysis of the Network Capacity utilization
of three leading operators are carried out
• Aircel – PAN India;
• Vodafone –Andhra Pradesh
• Airtel – Kolkata
Methodology
….Contd.
• Based on the available data it has been observed that peak
average utilizations 70% for Aircel, Vodafone 62% and Airtel
67% at BBH [Bouncings Busy Hour, which is busiest hours of
the day].
• Data is collected related to usage during busy hours
1. There are no events and incidents so that there is no
abnormal increased usage of data and non-busy hours.
2. During an event when there is surge of traffic so called “
Black out Day”
Methodology
….Contd.
• We have also collected hourly data for prolonged
duration from different circles and plotted “M”
curve ( the curve that depicts hourly variation of
traffic) for Mumbai and Punjab circles of Aircel.
• Exception has been analysed in one instance called
blackout day having excessive traffic because of
festival and other activities and non-busy hours.
• We have analysed whether the busy hour traffic is
significantly different from non-busy hour traffic.
We have also plotted “M” curve which gives a
pictorial view of hourly traffic variation relative to
peak traffic. While analysing we come across to a
very interesting fact that, non-busy hour average
network utilization is less than 5% of the installed
capacity
• For Hypothesis 2: We have conducted an
experiment (Annexure – Traffic Sensitivity) in which
free talk time (of Value 5) added (in Denomination
of 70) to be used in non-busy hours to observe
traffic trend.
Methodology
….Contd.
• We observed that the talk time credit and free talk
time impact increased the traffic, also it is
statistically significant. Hence tariff of the service
impacts traffic at busy hour and by changing tariff
plan busy hour traffic can be diverted to non-busy
hour, thereby freeing of resources at busy hour.
• Hypothesis 3: It is natural fall out of Hypothesis 1
and Hypothesis 2
• Primary Data Collection
Source of
Data
Collection
• Aircel – Pan India data collection
from OSS ( Operating Support
System) & Sales Report
• Airtel – OSS report
• Vodafone – OSS report
• Secondary Data Collection
• TRAI Released reports
• Hypothesis -1 : Network resources (capacity)
are not being utilized efficiently during off
peak hours
Data
Collection for
Hypothesis 1
• Data collection from Aircel related to Mumbai,
Punjab circles for peak and off peak traffic were
performed, to demonstrate that peak and off
peak traffic are different. Data is also collected
for a Black out day in Mumbai circle
• Data collection from Aircel – PAN India, AirtelKolkata and Vodafone- AP circles are also done
to understand Network Utilization in Peak and
Off Peak hours.
Time(hrs) 23-May-17 24-May-17 25-May-17 26-May-17 27-May-17 28-May-17 29-May-17 30-May-17 31-May-17 1-Jun-17
Mumbai Aircel
(Black out day)
Traffic (Erlangs)
Analysis
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
12375.46
6678.39
3423.54
1922.10
1329.34
1701.11
4468.30
10397.98
17591.18
22878.91
26788.68
29035.64
29297.88
31334.41
29436.28
25408.72
24681.02
25716.11
28708.16
34233.46
40334.56
39581.94
32294.64
21475.55
11965.58
6256.93
3365.78
1802.54
1356.52
1760.79
4511.08
10167.48
17472.40
23236.69
26499.13
28277.67
28767.72
31365.25
29475.25
25065.03
24597.93
25919.54
28680.78
34201.62
40232.02
39868.61
32678.22
21796.86
12261.32
6443.95
3460.11
1844.16
1365.69
1748.84
4449.51
10133.91
17543.77
23319.67
26800.89
29038.51
29257.71
31700.16
29665.20
25483.97
24869.12
26214.90
29063.41
34271.44
40409.75
40159.93
32587.48
21657.60
12183.30
6186.11
3377.94
1904.25
1334.81
1692.84
4287.83
9893.12
16994.05
22641.62
26448.86
28665.42
28097.97
27433.97
28117.51
25966.24
25343.17
26604.10
29467.92
34788.47
40738.04
39734.93
32139.70
21287.47
12387.73
6637.20
3507.28
1983.81
1351.03
1668.56
4321.67
9845.05
16959.88
22633.86
26171.37
27948.08
27620.52
29477.24
27710.14
24553.27
23827.51
25341.87
28368.67
34942.26
41350.24
38727.84
32148.19
21943.05
11922.79
6579.54
5108.31
5364.95
4564.91
2874.93
4432.47
8835.96
14753.03
19908.65
23455.77
26097.33
27270.39
27224.73
26239.22
24003.33
23424.42
24214.89
26092.38
30140.91
44919.35
40197.72
32781.80
21937.97
12217.53
6699.67
4523.53
4335.15
3812.08
2731.40
4376.71
9037.43
15718.68
21610.98
25953.58
28151.55
29075.37
30660.25
28972.00
25892.39
24625.95
25224.79
26589.65
30971.63
43926.77
39589.76
32402.84
21297.37
11792.78
6364.41
4553.39
4208.99
3710.22
2880.41
4520.47
9454.43
15983.98
21571.99
25515.06
28267.58
28715.95
34142.94
31034.18
26785.79
25341.97
26079.32
27350.08
31410.41
43842.47
40046.35
32719.36
21561.34
11950.00
6330.26
4509.91
4103.06
3470.02
2885.96
4645.28
9591.91
16337.33
22012.29
25796.96
28153.35
28934.61
30411.42
28691.23
25293.76
24465.01
25121.89
27028.83
30911.91
43158.57
39988.34
33189.49
22485.42
12551.48
6857.80
4663.97
4134.93
3530.33
2964.68
4619.39
9411.20
16146.98
21175.11
25132.08
27915.35
28693.70
30515.76
28521.33
24789.62
24243.92
25646.99
27231.53
30712.64
42835.84
39618.37
32106.87
21176.98
2-Jun-17
11728.93
6434.11
4391.08
3961.68
3481.68
2879.46
4621.81
9230.06
15717.52
20672.84
24996.19
27516.24
27642.67
26826.89
28172.03
26115.86
25787.32
26703.17
27748.56
30775.42
42964.65
39502.72
32792.94
22095.45
3-Jun-17
4-Jun-17
12344.03
6822.48
4509.64
3963.79
3537.48
3004.20
4810.06
9625.50
16097.45
21323.66
25115.58
27130.78
27906.19
29988.27
28034.21
24683.91
24173.76
25159.90
26881.42
30508.86
42016.55
38343.25
31421.52
21611.86
12296.32
7020.02
4756.23
4195.59
3563.94
3229.56
4720.30
8872.85
14716.52
19321.33
22671.94
25574.17
26887.36
27467.99
26614.05
23701.90
23214.30
23088.91
25666.92
27543.89
42732.71
41124.90
33706.34
22925.51
10 am to 364556.86 362950.55 366934.99 361406.60 356039.01 343280.44 359633.69 368532.10 357955.88 355857.13 354751.72 349942.68 336289.04
10 pm
0am to 10
am and 136536.50 136370.87 136816.01 133923.04 135387.31 139065.31 138763.37 139321.77 141510.93 139339.72 138007.56 139071.67 139324.51
10pm to
Average Traffic A
STD Dev S
STD Error E =S/(N)^.5
Average Peak P
23-May-17 To
5-Jun-17
04-Jun-17
12327.00
6562.90
4392.41
3771.23
3273.05
2877.36
4537.23
9211.99
15733.37
21079.45
25359.70
27769.08
28707.73
30610.09
29154.76
25618.72
25028.91
25365.71
27146.58
30671.99
42417.07
39862.25
32574.12
21550.40
356779.28
362924.30 357712.59
137956.81
141511.82 137890.51
20614.00
12128.22
2475.66
42266.27
t - Peak (A-P)/E
t- statistic value is beyond lower
limit
13299.27
7318.76
5091.96
4214.91
3407.04
2841.05
4561.22
9224.89
15709.60
21098.34
25569.40
28303.65
29300.14
31308.83
29650.88
25910.66
25306.45
25574.14
27398.81
31206.47
43160.45
40234.42
32860.70
21884.08
12152.10
6562.37
4165.44
3363.46
2800.62
2463.29
4521.91
9576.68
16310.21
21715.97
25488.16
27828.59
28320.62
29888.41
28514.05
25211.06
24507.34
25464.34
27606.02
31954.84
42266.27
39729.59
32536.11
21788.65
6-Jun-17
Degrees of
freedom =
24-2
Critical value for 95% confidence (one sided)
Lower limit
-8.75
22
1.717
Designed Capacity = 81000 Er
Time(hrs)
Mumbai Aircel
(Black out day)
Traffic
(Erlangs)
Analysis
Peak Utilization
10/18/17
12217.53
6579.54
4509.91
4335.15
3812.08
2885.96
4619.39
9625.50
16337.33
21571.99
25132.08
28153.35
28715.95
30515.76
28172.03
25293.76
24243.92
25224.79
27350.08
30971.63
43842.47
39618.37
32148.19
21937.97
20742.28
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Average
59%
10/18/2017 (%)
10/19/17
0.28
0.15
0.10
0.10
0.09
0.07
0.11
0.22
0.37
0.49
0.57
0.64
0.65
0.70
0.64
0.58
0.55
0.58
0.62
0.71
1.00
0.90
0.73
0.50
1898.47
1254.81
1052.63
9125.76
8976.45
7743.54
10746.36
15729.46
23593.23
29796.54
33605.47
35345.44
36574.81
38157.72
37138.74
32566.70
32285.72
31278.75
33657.43
36477.22
47567.27
46760.38
39827.26
28372.73
25813.87
Non-Peak Utilization
1%
10/19/2017 (%)
10/20/17
0.04
0.03
0.02
0.19
0.19
0.16
0.23
0.33
0.50
0.63
0.71
0.74
0.77
0.80
0.78
0.68
0.68
0.66
0.71
0.77
1.00
0.98
0.84
0.60
10 am to 10 pm
357234.19
441415.65
359093.77
0am to 10 am and 10pm to 12pm
140580.54
178117.24
140104.14
Testing for significance Black out day - 19/10/2017
Peak traffic at 20.00 hrs P=
Average Traffc A
Standard Deviation S
Standard Error E = S/(24)^.5
t (Black out)=( A-P)/E
Critical value for 95% confidence
(one sided)
Degrees of freedom = 24-2
limit
10/20/2017 (%)
12551.48
6434.11
3507.28
3963.79
3530.33
2874.93
4619.39
9625.50
16146.98
21571.99
25115.58
28153.35
28693.70
30660.25
28521.33
26115.86
24243.92
26703.17
26881.42
30971.63
42835.84
40197.72
32792.94
22485.42
20799.91
47567.27 Erls
20771.10 Erls
11964.11
2442.16
-19.48
22.00
1.72
t- statistic value is beyond
lower limit
0.29
0.15
0.08
0.09
0.08
0.07
0.11
0.22
0.38
0.50
0.59
0.66
0.67
0.72
0.67
0.61
0.57
0.62
0.63
0.72
1.00
0.94
0.77
0.52
Time(h
30-May-17 To 11-Jun30-May-17 31-May-17 1-Jun-17 2-Jun-17 3-Jun-17 4-Jun-17 5-Jun-17 6-Jun-17 7-Jun-17 8-Jun-17 9-Jun-17 10-Jun-17 11-Jun-17
12-Jun-17 13-Jun-17
rs)
17
Punjab Traffic
(Erlangs) Day
Wise Analysis
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1906.55
1024.82
532.36
395.75
382.84
819.68
2329.82
4566.19
6053.64
6905.75
7614.58
7878.93
7288.09
7934.24
7097.14
6528.33
6778.68
7352.63
7889.42
8489.52
10278.75
10309.84
7263.75
3830.87
10 am 95440.15
to 10 pm
0am to
10 am
36012.02
and
10pm to
1796.31
925.83
450.53
350.75
294.82
759.19
2109.90
3915.87
5676.67
6946.63
7552.98
7752.76
7449.27
8063.26
7169.65
6714.10
6859.35
7585.27
7952.46
8201.02
10189.43
10079.62
7352.24
4072.80
1841.69
936.97
509.02
395.14
366.99
794.30
2306.35
4525.13
5946.39
6687.18
7493.47
7831.92
7560.73
8301.59
6995.68
6482.09
6754.08
7515.21
7867.71
8087.79
9930.39
10350.01
7515.25
4047.90
1973.58
951.64
502.99
411.64
360.96
815.30
2441.84
4617.61
5967.30
6807.52
7497.22
7775.33
7391.22
8002.25
7030.05
6395.99
6992.19
7287.97
7148.11
8205.62
9968.86
10210.09
7342.73
3985.08
1898.20
929.41
520.64
398.25
407.11
885.27
2440.88
4549.80
5948.45
6704.55
7377.30
7548.54
7355.28
8219.21
6760.66
6134.73
6743.68
7130.64
6989.77
7905.14
9705.50
10130.14
7228.98
3927.63
2067.19
1006.72
633.62
436.97
429.06
1012.78
2569.80
4497.46
5736.79
6366.03
7003.06
7492.72
7006.20
6811.04
6307.15
5893.96
6281.08
6833.45
7165.96
7651.28
10145.20
10159.51
7057.84
3750.55
1709.36
866.62
429.87
337.70
332.47
818.64
2293.90
4266.48
5755.21
6453.12
7315.70
7755.91
7431.34
7989.53
6837.64
6301.84
6598.97
7145.56
7757.08
7943.46
9628.87
9510.06
6796.13
3399.87
1604.10
831.49
479.92
353.52
324.00
802.40
2215.82
4351.85
5743.75
6566.31
7221.35
7485.56
7066.74
7646.16
6423.48
5947.46
6415.63
7096.44
7153.39
7804.85
9652.62
9578.30
6338.54
3371.19
1639.19
683.34
375.62
278.47
296.15
564.96
1544.86
3483.20
5018.84
6297.32
7064.02
7365.25
7193.63
8053.71
7106.70
6497.73
6604.07
7098.38
7474.15
7813.94
9629.88
9823.50
7303.16
4080.25
2005.21
978.07
512.72
354.29
332.64
785.38
2343.49
4498.64
5776.54
6359.46
7127.49
7388.74
7231.48
8015.57
7014.72
6310.49
6605.92
6890.13
7463.77
7951.23
9750.99
9906.34
7136.54
3887.72
1780.80
833.67
457.25
326.83
317.13
738.89
2196.53
4220.21
5634.61
6140.56
7135.69
7316.64
7153.68
7829.91
7000.15
6411.07
6675.82
7094.59
7705.86
7941.22
9896.91
10239.09
7566.57
4221.44
1948.71
950.23
557.96
367.50
360.78
826.87
2371.54
4496.25
5721.60
6114.63
6590.60
7175.89
7011.10
7863.59
6726.53
5997.05
6427.55
6794.34
7730.22
8010.31
9684.00
9575.25
6917.09
3650.58
1746.98
814.56
455.64
372.79
373.72
773.15
2154.69
4105.06
5530.46
6272.59
7168.13
7400.72
7121.52
7152.64
6482.74
6151.10
6694.36
6744.38
7385.59
7983.76
10233.11
10539.00
7756.56
4134.30
1839.84
902.57
493.70
367.66
352.21
799.75
2255.34
4314.90
5731.56
6509.36
7243.20
7551.45
7250.79
7837.13
6842.48
6289.69
6648.57
7120.69
7514.11
7999.16
9899.58
10031.60
7198.11
3873.86
1927.40
972.72
483.56
351.66
351.92
853.73
2347.53
4459.60
5917.23
6715.68
7346.34
7404.36
7475.50
8234.51
6943.50
6339.60
6771.36
7263.48
7791.35
7978.96
9969.49
10295.16
7491.19
4062.18
1965.47
957.46
467.50
337.06
338.85
891.99
2494.07
4747.19
6031.88
6750.09
7502.32
7713.63
7310.82
8083.39
6948.76
6233.23
6680.97
7427.00
7807.08
8131.87
10130.50
10124.43
7437.75
3941.10
95569.17
95170.67
93904.90
92000.59
88750.61
92215.96
89491.98
91724.96
91656.87
92400.63
89586.43
91057.05
92228.46
93813.61
94094.00
34651.54
35872.31
36178.19
35839.17
35564.81
33459.37
32982.89
31565.36
34970.70
34434.49
34283.74
34490.50
34638.85
35934.40
36360.41
t- statistic value is beyond the limit
Average Traffic A
STD Dev S
STD Error E =S/(N)^.5
Average Peak P
t - Peak (A-P)/E
Degrees of freedom = 24-2
Critical value for 95% confidence (one sided)
limit
5286.14
3122.879
637.4550299
10031.60
-7.44
22
1.717
Punjab –
Hourly Traffic
(Erlangs)
utilization
Aircel PAN India Utilization
Total designed Radio Peak Radio Traffic
Capacity (23 circles) (BBH)
Aircel PAN
India
Utilization
WK 3Jan
WK 27Dec
WK 20Dec
Dec'17
Nov'17
Oct'17
Sep'17
Aug'17
Jul'17
Jun'17
May'17
Apr'17
Mar'17
Feb'17
Jan'17
Dec'16
Nov'16
Oct'16
Sep'16
Aug'16
Jul'16
Jun'16
May'16
Apr'16
Mar'16
Feb'16
Jan'16
2015
2014
K Erlangs
2,450.4
2,438.5
2,434.2
2,437.0
2,449.9
2,476.8
2,476.7
2,507.0
2,536.3
2,554.7
2,578.2
2,586.0
2,606.6
2,617.7
2,616.1
2,608.0
2,597.2
2,592.0
2,592.9
2,604.7
2,568.0
2,539.7
2,589.8
2,587.5
2,555.2
2,546.7
2,525.3
2,495.0
2,370.8
Average Utilzation BBH
Total Radio Traffic
(NBH) (23 circles)
K Erlangs
1,596.3
1,609.8
1,649.3
1,636.3
1,690.8
1,641.9
1,642.8
1,645.8
1,658.5
1,684.9
1,713.7
1,764.0
1,814.2
1,834.4
1,779.6
1,722.8
1,752.8
1,791.3
1,863.0
1,853.0
1,865.5
1,908.7
1,944.4
1,935.9
1,925.4
1,924.6
1,815.5
1,817.0
1,683.5
70%
Radio Network
Utilisation (%) BBH
K Erlangs
1,392.5
1,429.6
1,460.5
1,450.6
1,495.8
1,470.3
1,476.2
1,482.8
1,490.4
1,518.5
1,546.8
1,580.5
1,629.7
1,650.1
1,590.8
1,524.7
1,574.6
1,605.2
1,675.0
1,677.0
1,687.5
1,719.7
1,738.5
1,726.1
1,718.9
1,740.1
1,626.6
1,630.0
1,493.7
Max
76%
Min
65.1%
66%
68%
67%
69%
66%
66%
66%
65%
66%
66%
68%
70%
70%
68%
66%
67%
69%
72%
71%
73%
75%
75%
75%
75%
76%
72%
73%
71%
65%
Radio Network
Utilisation (%) NBH
56.8%
59%
60%
60%
61%
59%
60%
59%
59%
59%
60%
61%
63%
63%
61%
58%
61%
62%
65%
64%
66%
68%
67%
67%
67%
68%
64%
65%
63%
Voda Utilzation- AP
AP traffic
utilization Business
Busy Hours
1-Sep-17
2-Sep-17
3-Sep-17
4-Sep-17
5-Sep-17
6-Sep-17
7-Sep-17 8-Sep-17
9-Sep-17 10-Sep-17
BBH - Erlangs
100962.2619 97125.74181 92018.08104 92817.21563 92041.76621 97147.41155 102539.8424 103344.975 104924.2443 104942.3806
Capacity - Erlangs 159086.98 159172.35 159269.51 159303.61 159303.62 159368.19 159405.13 158785.27 158727.99 158849.42
Utlization
63.5%
Average
61.0%
62.1%
57.8%
58.3%
57.8%
Max 66% Min 58%
61.0%
64.3%
65.1%
66.1%
66.1%
Kol - Airtel Utilization
Total designed Peak Radio
Total Radio
Radio
Traffic (BBH) Traffic (NBH)
Capacity
K Erlangs
Airtel
Utilization Kolkata
WK 3Jan
WK 27Dec
WK 20Dec
Dec'17
Nov'17
Oct'17
Sep'17
Aug'17
Jul'17
Jun'17
May'17
Apr'17
Mar'17
Feb'17
Jan'17
Dec'16
Nov'16
Oct'16
Sep'16
Aug'16
Jul'16
Jun'16
May'16
Apr'16
Mar'16
Feb'16
Jan'16
2015
2014
K Erlangs
222.2934
162.53
244.2393257
175.30
251.94015
176.50
277.5777
194.55
219.0177417
151.40
206.2408065
135.58
205.0281708
134.96
208.2366677
132.27
235.8099857
154.77
245.802144
163.38
236.44021
162.59
232.3280922
157.51
206.259061
136.79
200.7194175
135.02
209.9184974
137.15
214.4919953
145.22
222.7702883
155.36
218.753609
155.50
214.2306814
141.40
212.45835
147.29
198.744086
140.59
170.987544
121.56
174.797896
125.63
177.5242543
125.48
164.7840915
110.36
165.7470844
116.58
164.3009028
109.79
156.5933489
110.32
143.1403648
99.48
Average BBH Utilization
Max
Min
Peak
Radio
Traffic
(BBH)Utiliz
ation %
Total
Radio
Traffic
(NBH)
Utilization
%
Weekly
Weekly
K Erlangs
144.53
154.15
169.42
180.21
144.20
118.21
117.52
116.31
136.85
143.83
143.42
138.37
120.81
118.89
121.01
127.00
135.07
132.98
139.35
143.57
123.26
108.49
113.33
107.64
106.63
109.89
97.68
101.35
93.59
68.6%
73%
65.30%
73.1%
71.8%
70.1%
70.1%
69.1%
65.7%
65.8%
63.5%
65.6%
66.5%
68.8%
67.8%
66.3%
67.3%
65.3%
67.7%
69.7%
71.1%
66.0%
69.3%
70.7%
71.1%
71.9%
70.7%
67.0%
70.3%
66.8%
70.4%
69.5%
65.0%
63.1%
67.2%
64.9%
65.8%
57.3%
57.3%
55.9%
58.0%
58.5%
60.7%
59.6%
58.6%
59.2%
57.6%
59.2%
60.6%
60.8%
65.0%
67.6%
62.0%
63.4%
64.8%
60.6%
64.7%
66.3%
59.5%
64.7%
65.4%
Conclusion
1. We have seen that the peak traffic is
different than the off-peak hour traffic for
Mumbai and Punjab cases in normal days
2. This is true for Black Out Day in case of
Mumbai
3. Utilization of Network in off peak hours is
very much less than the Peak hours (as
below).
• Aircel ( Max 76%, Average 70%, Min 65%)
• Airtel ( Max 73%, Average 69%, Min 65%)
• Vodafone ( Max 66%, Average 62%, Min 58%)
Data
Collection for
Hypothesis 2
Hypothesis -2 :There is scope of distribution of
traffic in non-busy hours by Regulator by
implementing pricing tool
• We are demonstrating that traffic is sensitive
to price; hence pricing can be used to divert
peak traffic to non-peak hours
• We have conducted an experiment to prove
traffic is sensitive to price. This we have done by
adding free talk time ( in a prepaid Mobile
recharge denomination), to an existing package,
with a condition that the package is valid during
non- busy hours only. This is effectively reducing
price of talk-time per minute – in off peak hours.
We have collected sales data pre and post
scenario and analysed the changes if any.
Traffic Sensitivity
Testing of
significanceTotal Traffic
after
introduction
of Free TT
t- statistic value is beyond the limit
Conclusion –
Hypothesis 2
• We have seen that the null hypothesis “
Average TT/Denomination pre and Post
changes are same” was rejected.
• It indicates that with reduction in tariff in off
peak hours, has increased the traffic in off
peak hours.
• The post changes recharge which is valid in
off peak hours has increased average
TT/Denomination as whole ( Total Traffic as
whole and increase in off peak hours in
particular).
• Hypothesis – 3 : : Regulator, by adopting
pricing tool can make traffic distribution
relatively uniform, and reduce peak traffic
Hypothesis 3
• This is a logical fall out of Hypothesis-1 and
Hypothesis -2
• Hypothesis-1 : Network resource (capacity) utilization
is different in peak and non-peak hours. There is,
therefore, has scope to divert peak hour traffic to
non- peak hours.
• Hypothesis -2 : Traffic is sensitive to price; hence
pricing can be used to divert peak traffic to non-peak
hours
• Peak traffic is significantly different from the non - peak traffic.
• Installed capacity of the operators are underutilized(non –peak
hour slots are worst in terms of utilization).
• Underutilized network incurs more cost in terms of Capex and
Opex, Presently underutilized network cost is passed on to the
customers.
Conclusion
• Traffic is sensitive to price, by charging peak price some of the
traffic can be diverted to non- peak slots and requirement of
Network capacity can be reduced for serving similar group of
• There is no KPI by the regulator for the utilization of the installed
capacity by the operators.
• The assumption -in a competitive market forces will take care of
the utilization cost, is not a reality and there is collusion among
operators and aberration in competition in the industry.
• It was concluded that the regulator TRAI needs to revisit its tariff
policy of forbearance and focus on Network Utilization.
Thanks