TBM Mini Project 091030

8/7/2019 TBM Mini Project 091030

1/19

MINI PROJECT REPORT

ON

BUSINESS INTELLIGENCE SOLUTION FOR TELECOM

SUBMITTED TO

MIT PUNEs

MIT SCHOOL OF TELECOM MANAGEMENT

BY

CHAWANDKE ROHIT SURYAKANT

PRN: 091030

Batch: 2009-2011

SUBJECT: TELECOM BUSINESS MANAGEMENT (TBM)

SPECIALIZATION: SYSTEMS


2/19

Introduction

The Telecom Industry An ever changing and competing market

place. With all the business and data management challenges, many of the

industry executives still feel that their organization is not ready for a BI solution. A

typical BI solution with a strong process orientation is presented to understand its

importance and need to the organization. The inherent advantages of the solution

are highlighted.

Market Dynamics- Analysis

The urge to be a leader, to be best in service and to possess

maximum customer base for each enterprise within this industry has resulted in a

dynamic market place. The Indian market is seen as a high potential market with

densely populated geographies. A wide variety of customers and customer

segments make a market an interesting place. The dynamics are influenced by

three players Customer, Organization and Competitor.

CustomerCustomers now have more choices, better offers and more flexibility

for access to information. Service providers are mere facilitators. The industry

needs to align to the needs of the customer. With the increasing needs and

expectations, customers tend to accelerate the competition in the marketplace.

With better choices and varied options, customers are more inclined

to look for better services. Acquisition comes with no barrier of binding the

customer to the service provider. It has now become important to focus on

customer retention than customer acquisition. The cost of customer acquisition as

compared to customer retention is now reducing.

Organization

Infrastructure: Investments in infrastructure are at its peak. There has been a

continuous drive to reach the lowest level in the geography with high data

availability. Latest technology for efficient data transfer and network availability


3/19

facilitate in propagating the service to the lowest customer segment.

Technology Adoption: Now you can access the Internet on your mobile,

Connectivity- anywhere, anytime Exciting for techno savvy people. This kind of

advertisement indicates advancements in technology. Technology has been fastadvancing from the days when mobile phones were being used only as voice

communication devices to today, when they are used as cameras and internet

kiosks and for data exchange by Bluetooth. Technology is progressing and

organizations need to adapt to the change quickly.

Innovative Services:Introduction of Fixed Wireless Phones with advanced value

added services have enabled customers to enjoy the benefits of wireless technology

at cheaper rates. This innovation has now eliminated wire connectivity for voice and

data communications. It could be viewed as an innovation in service offering. Such

kind of innovative offers often create a wave of excitement among customers, thus

impacting the market place.

Mergers and Acquisitions: With competition at its peak and a risk of saturation

of the customer base, mergers and acquisitions are seen as a viable option. It helps

in increasing the customer base of the organization and in taking a step towards

establishing their monopoly in the region. For example, recently the US market has

seen two big mergers of Cingular-ATT and Verizon-MCI. Mergers and acquisitions

usually bring in a mixed impact on customers, but create a great ripple in industry

dynamics. It is a greater threat to the players, of either being taken over or losing

customers. This has not been evident in the Indian market, but the day is not too

far for mergers and acquisitions to start off.

CompetitorCompetition is evident all over. Advertisements, pamphlets, marketing

calls and other media provide information about the increasing competition in the

market. A race to offer low, affordable prices and customized services has created

turmoil in the market place. Relaxation of regulations by the regulatory bodies has

helped penetrating the market. In the recent past, introduction of cheaper prices

attracted a huge customer base to an organization, leading to a serious competitive

environment in the Indian telecom market.


4/19

With all these factors adding to the dynamics of the market,

organizations need to be agile in managing their operations and offerings, and in

meeting customer expectations. Dynamics tend to impact the customer and the

organization. A comparison shows that though there are a few gains and losses tothe players in the game, they tend to balance.

Impact of Dynamics

Business Focus

The game requires intelligence, proactive thinking and quick

adaptability and strategies to welcome the change. Every organization strives to be

a market leader. Some of the general focal points of the game are explained in the

sections below.

Customer Centricity:The business is driven by the Customer a fact thatnecessitates knowing the customer better. Business has to be customer

centric. Customer centricity means to understand and be informed about:

1. Customers requirements and expectations.2. Customers changing behaviour, demographics and psychology3. Customers behaviour pattern and activities, and the external factors

which impact the customer

Business has to focus more on customer retention and customer care. Agreater challenge lies in influencing the customer to be with the organization.


5/19

Product Pricing: A true distinguisher between a competitor and a leader isto be a Leader in setting competition. Businesses always strive to set a

competitive price in the market place well before the competitor thinks of it.

Being proactive in customizing the offerings to offer value to the customerwhile maximizing its profit is the prime focus.

Manage costs: Every organization has a drive internally to reduce the cost.It could be the cost of customer acquisition, retention or the launch of a new

product/ service. A single dime saved is a dime earned. Cost reduction by

means of increasing productivity of employees, increasing efficiency of

existing network or expense reduction alternatives have taken priority.

Manage Information Flow:Be informed. The information flow within theorganization has to be healthy in terms of accuracy, availability and usability.

Right information available at the right time helps in taking quick strategic

decisions. A successful player is always equipped with the right information at

the right time.

Competitor know-how: Understand, know and predict the competitorbehaviour. Analyze the impact and strategize business decisions. Know when

is the right time to launch a new product, acquire new customers, acquire the

competitor and predict the risk of being acquired. Organizations always keep a

watch on the competitors. After all it is a tactic of the game.

To win a game, a player has to be well informed and should make

quick, wise decisions. Decisions are effective and accurate if the player understands

the other players and their next moves well. This is facilitated by data and

intelligence.

Users of Business Intelligent System:

Typical users of a Business Intelligence system inside an ICT Service Provider are

all the departments that have to take business decision. Main users taking advantage of Business

Intelligence are:

Marketing Sales Operation Network Planning Customer Care Service


6/19

In their daily work the department in charge of sales and marketing

need to access to both synthesis and detailed data on customer expenditure, on

actual usage of base and value added services, on CRM efficiency and effectiveness

e.g. of Call Centres, both traditional and IP Contact Centre. Call and Contact Centrein turn take advantage from reporting provided by Telco Business Intelligence (TBI)

system to improve their internal process. The following figure tries to sketch a

synthesis of TBI users and advantage they can get.

Main Users of Business Intelligent System

Inside a Telco Business Intelligence System

The Telco system works in an effective way. This can be summarized

in the sentence Business Intelligence is a process to turn information into actions

(decisions) To get such goal a good Business Intelligence solution must satisfy

some fundamental requirements:

Precision

Speed

Data validation both for input and output information

First requirement is easy to understand if we take into account that BI

system is somehow the equivalent of the company neural system. On second and

third requirements, its worth spending a few words. The process and function

played by a Business Intelligence system have to be carried out anyhow into a


7/19

company since they are vital to support business. A Business Intelligence system

actually boosts the speed of taking and making effective decision which give an

advantage on competitors.

A Business Intelligence system is as good as it can provide requestedoutput based on valid input data. This lead to consider the requirement of

information validation on input data as well as during processing and on synthesis

output data delivered to the BI end users. The large amount of data collected by

network elements, by Operation Support and IT System, as well as the one from

human operators, like in Call Centres, can easily result in data inconsistency and

mismatch. If not properly dealt, these inconsistencies can make the BI system un-

effective. This is well described by the aphorism: Garbage in garbage out. Hence

Business Intelligence must to clean out as far as possible data inconsistency and

validate both input and output data.

Input Data and Users of Telco Business Intelligence

Business Challenge - Data Management

New players are seen emerging in the market. A high potential market

and very less time to attract customers are forcing the players to accelerate their

offerings. Data Management has taken a back seat and is not a priority. This has

led to a lot of chaos and dissatisfaction among the customers. Customers often

complain about inaccurate billing, unavailability of network and frequent disruption


8/19

of their service. Analysis of the problem results in poor data in the operational

systems. Data management has become difficult due to its volume, rapidly

changing business and quick implementation of the IT systems to support business

in the market place.Data management life cycle is a closed loop which starts from data

acquisition and reaches the data exploitation state before starting off with data

acquisition. The cyclic nature is due to business maturity and growth.

Data Management Life Cycle

Data Acquisition:

Data acquisition is focused on the operational needs. There is a huge

gap in the dataacquisition requirement. Analytics and intelligence to support thebusiness is heavily dependent on the data being captured within the system.

The Customer centric' business focus has created a demand of the

customer data within organizations. Organizations are not geared to have effective

analysis on customer demographics and preferences. They need to bridge the gap

between operational data and analytic data.


9/19

Data Quality:

There is a constant struggle and steps are being taken in the IT

section of this industry to overcome this challenge. Data quality challenge is

everywhere data collected from customer facing applications to customer servingapplications. This has resulted in customer dissatisfaction thus impacting the image

of the player in the market place. A simple example being subscribers

activation/inactivation with incorrect dates (variation in year) resulting in incorrect

billing. This results in loss of revenue to the organization and/or in the loss of

customer confidence. Data quality to ensure accurate, timely, meaningful and

correct data poses a great challenge.

Data Integration:

Data is present in various operational systems but they do not

synchronize in anunderstandable format. Operational systems are loosely tied up

with each other with less synchronization of data. Different representations of a

business entity/element reflected in the reports create chaos in data assimilation.

Today a lot of time and effort is spent on data assimilation activities within an

organization.

Data Exploitation:

The data utility index utilization of data in the organizations is low.

Each data element has to be completely utilized by analyzing its relevance and

importance. This ensures minimal redundancy and presents uniformity of data

elements. It brings in new data requirements triggering off the cycle of data

management.

An external factor which controls and contributes the data

management loop is Change in Business processes. This is not very frequent but

inevitable. Increasing competition, mergers and acquisitions and new offerings

demand change in the business processes.

In an ideal world, it is impossible to achieve data completeness and

correctness in an organization due to its cyclic nature. Data Management is not a

problem but a continuous challenge which needs to be managed. Its a continuous

improvement process which leads to ancient data management.


10/19

The Solution

Every problem has a solution and every challenge can be alleviated.

To address data management issues with the change in the business strategies and

processes is a bigger challenge for an organization. An intelligent support layer for

the operational system can lend a support to business by providing quality data and

business analytics.

Solution

Market is an external factor that impacts the business strategies from

time to time. It is a game wherein the organization and the competitors compete to

maximize their market share Business strategies are aligned to meet customer

expectations and challenge competitors in the market place. These strategies

impact the market place with its innovative, new and competitive offerings.

Business strategies define the business processes within an organization.Business Processes are existing processes that support the

organization in the market place. The existing processes change with the expansion

of business either through market expansion, enhancements in service offerings or

mergers and acquisitions. New processes often get defined to support new products

or services. The solution for the changing business strategies and processes

necessitates two supporting layers a Service layer and a Data Process layer that

are described below:


11/19

Service: This layer supports the business strategies with data, metadata,information and analytic services. This layer is driven by the business

processes. Changes and introduction of new business process enhances it to

adapt to the business needs. Data Process layer:

Interacts with the operational systems for continuous monitoring andmentoring.

Derives intelligence with inbuilt business and data processing rulesHelps identify the obscure market behaviour with predefined algorithmsEnsure feedback to the service layer for continuous improvement

The internal and external dynamics creates turbulence in the

organizations data management process. The solution has to be intelligent and

flexible to support the business needs and the operational data management

challenges. The solution should be a well defined methodology directed by vision

supporting business with right information and intelligence and provide feedback for

efficient data management. A process which collates, validates, integrates and

defines rules for quality data.

Business Intelligence Solution

Business Intelligence (BI) solution is not a mere data warehousing

solution that encapsulates data to provide analytics, derived intelligence and easy

access to information. It is a process that extracts, collates, validates, reconciles

and integrates the data to provide intelligence to the business as well as to the

operations. It is the intelligence of the process that can help in providing guidance

to mitigate the challenges within an organization. BI solution advantage is two fold

one to provide intelligence about the operational systems and facilitate data

management, and the other to support the business with its analytics and

reporting.

BI solution is a service oriented process. The two fold benefit has data

service and analysis and intelligence service in a chronological order. The logical

framework, nucleus of the solution encapsulates data requirements and a well

defined process. Data requirements facilitate capture of all data elements required


12/19

by the business for its operations and analysis. Data process helps in churning out

the intelligence for the business and operations.

BI Solution

Data Service facilitates high quality prepared data for the reporting

and MIS of the organization. This layer is focused on attaining operational

excellence within the organization. There is a continuous feedback mechanism

involved in the process to ensure appropriate correction at the operational systems.

BI solution builds a highly sophisticated ETL (Extract, Transform, and Load) process

encapsulating business rules. Intelligence as data quality and integration rules can

be churned out of the process. This information if tapped properly provides rich

source of data correction methods.

The process can churn out the differences between the systems (out

of sync), non- conformance to standards, integration issues. ETL process functions

of cleansing, integrating and standardization leading to high quality data, the rules

can be re-used to apply back to the operational systems. Data Acquisition

requirements can also be driven by the BI solution. This necessitates the solution to

be designed and aligned with the vision. BI-DW can act as a single source for data

acquisition recommendations. Details are discussed in the section Business

Intelligence Approach. The analysis and intelligence layer supports the business


13/19

with its needs of reporting and analysis. Intelligence is usually referred to

derivations of business metrics. OLAP analysis and reporting is a known function of

BI solution. A step ahead of it, which BI solution intends to achieve, is High End

Analytics.High End Analytics: Data mining or identification of hidden trends is required to

completely understand the business and its events/facts. This technique is very

rarely adopted and seen as the next step after Data Warehousing (DW). BI solution

acts as foundation to support and facilitate high end analytics. Algorithms can be

devised to derive intelligence and provide online support to:

Call centres about the customers for better customer facilitation Executives about the current trends and forecasted data Decision options and the impact of each option Identification of fraud and corrective measures based on historical trends Create awareness to the business about the upcoming events based on

historical trends.

Data Service - Process Flow

Business decisions need historical data, trends and intelligent

analytics. Operational systems need mentoring for data management. Two facets of

the requirements necessitates in setting a process within the organization. Figure 4

below depicts the BI process flow and its components which helps in providing

efficient data service.


14/19

BI Process Flow

The challenges like data quality and data integration have to be

rectified at the source level. Get to the root and fix it. BI process comprising of

data capture, data quality check and integration can provide continuous feedback to

the source systems.

Data quality check performed in ETL provides data quality reports thatindicate where the source systems are deviating from the set standards. This

helps in making immediate corrective actions at the source.

Data Integration process defines the standards across the organization. Thefeedback at this stage should be tapped to achieve standardization of data

elements across the business.

Data quality and integration reports on reconciliation provide data correctionmethodologies. Reconciliation process collates all the reports and validates

against the business rules to provide data correction recommendations.

BI program, built on proper methodology, feeds back the data acquisitionrequirements to the source systems. Additional attributes and metrics required

to be captured are passed back to the source systems to ensure data

completeness in the organization.


15/19

Business Intelligence Solution Addressing Challenges

The challenge for the business is to keep pace with the market and

address the internal data management issues. A quick validation of the BI solution

components against the critical industry challenges today is depicted in Table 2

below.

Industry challenges and BI solution

Business Intelligence Approach

BI- Solution Approach


16/19

A BI solution is a process constituting of methodologies,

infrastructure, tools and technology.

Methodology A framework which is aligned to organization vision. Acomplete roadmap to the journey of intelligent support

Infrastructure Define and procure infrastructure to support the solution Tools and Technology Tools and accelerators that can be plugged in, to

catalyze the process

Methodology

BI solution needs to be driven by the executives and analysts of the

organization. This ensures that the solution has an enterprise wide approach

backed up with vision of the organization. A methodology should define the

following in a chronological order:

Key performance indicators for the organization. The key performanceindicators define the roadmap for the organization. This ensures completeness

of the analytic and reporting requirements.

Definition of the metric: All the key performance indicators defined at thelowest level. This determines data elements that the organization would need

to align to their vision.

Operational challenges: Define the operational challenges faced by theorganization, data management and data dissemination challenges.

Roadmap for implementation: Would a step by step implementation help theorganization or can it go for a full fledged DW in a single step? This is based

on each organization and can be decided at an interaction level with the

executives of the organization. It is suggested to have a Build step by step

approach backed with a complete EDW vision.

Guidelines for implementation: Set up a clear guideline. Step 1 to Step n ofthe complete life cycle. Support it with templates and use cases.

At this stage the solution should not be influenced by data availability,

data quality and integrity issues. This would lead to convergence of the solution.

Methodology definition should be based on business requirements, data

management challenges and vision of the business. Correct and complete

identification of the key performance indicators facilitates effective data acquisition


17/19

Tools and Technology

Tools facilitate in accelerating the process. Organizations need to have

well defined models and tools which enable them to drive towards business

excellence.

Operational Data store: A data store that houses operational data. It is thelayer that ensures capture of base business elements, data quality and data

integration. This tool would help in citing the data quality issues and

application of business rules to integrate the data.

Analytics: A data store which captures all the required metrics identified askey performance indicators for the business. This tool helps in providing end

to end view of the customer and the business at an aggregated level. Provides

OLAP capabilities for power users and dashboards for the executives.

Data mining and high end analytics: Derived intelligence from the behaviourof business elements over a period of time. This tool helps in understanding

and forecasting the trends of the business and customer over a period of

time.

Canned reports: Static piece of information for information consumers. Thistool facilitates in providing health check measures and details of the daily

transactions. Could consist of transactional, historical data or certain derived

metrics of the business

The BI technology stack chosen for the program has to be

meticulously evaluated. The tools and technology should support complete end to

end data processing to:

Ensure timely availability of data Manage huge data volumes efficiently Support efficient load and retrieval process Check and integrate proficient and efficient data quality Intelligent processes Supporting rich metadata and alerting capability Ease data access Secured access to information


18/19

Infrastructure

The solution needs to be backed up with infrastructure. It is

imperative that the investment is based on evaluation of tools and technology in the

market. Requirement of infrastructure is the final step before going into the design

and development phase. Delay in infrastructure availability impacts the ROI (Return

on Investment) of the solution. Thus, it has to be judiciously planned and executed.

The infrastructure components required for the BI solution are:

Hardware: The nature of data storage, data processing and volume of thedata defines the requirement of the hardware.

Software: Data processing, data security and retrieval drive the softwarerequirement

Network availability and connectivity: The network availability and connectivityhave to be ensured. The data volumes and processing time determines the

bandwidth requirement.

There is a great risk of failure of the solution if the infrastructure

support is not appropriate. Upgrade of infrastructure is feasible but as it relates to

capital investment, there is always a delay in procurement. This results in

degradation of user community dependability and data integrity issues around the

organization. It is suggested to have infrastructure planned with projections and

procured in a timely manner without inhibiting the advantages of the solution.

Proposition

The urge to excel in the market place has been driving organizations.

Data management and exploitation have not been on the priority list. This hasresulted in dissatisfaction of customers and has also led to organizations slowly

tending to reduce their market share. BI solution has been interpreted as an

expensive and time consuming effort. The inherent advantages of the intelligent

processes are rarely analyzed and weighed. Especially in the telecom industry, data

management challenges have engulfed the environment. It needs a process to be

in place to suggest continuous improvement. BI solution has always been viewed as

an analytic/ reporting solution and hence is given less or least priority. A BI solution


19/19

can eliminate many intermediate and quick solutions being designed and developed

in the industry. The processes formulated in the BI solution could be reused to

ensure proper utilization of time and investment. A guided approach to the solution

could facilitate achieving business and operational excellence for the organization.

Conclusion:

BI solutions are based on Business Intelligence Decision Support

(BIDSTM), a complete framework definition and the process flow for a BI

implementation. The methodology offering encapsulates not only the framework

and the guidelines but also the templates which guide the implementation process

step by step.

For the telecom vertical, tBIDS- Telecom BIDS- a packaged solution

encapsulating a logical model backed up with analytical templates for reporting and

analysis has been developed. A continuously maturing model helps in plugging in

the package and reducing a substantial effort of requirements and design. The

package details out all the critical attributes data elements required by the industry

vertical supported with rich metadata.

A service model, Business Intelligence Competency Centre (BICC),

provides end to end service solution to its customer. The competency centre

facilitates the customer in providing services like methodology definition,

infrastructure requirements, solution research, and vendor liaison, technology

centre of excellence, competency and knowledge management. The centre acts as

a single point of contact in the organization for business, IT and vendors (service

and infrastructure) facilitating in guided approach to the business intelligence

program.

Documents

TBM Mini Project 091030