BI Solution for TelecomA Lifeline to Sustain & GrowThis paper highlights the dynamics and challenges for the telecom industry in the Indian market. It provides an insight about how a BI solution would address ‘Data management’ need and challenges along with business analytics.

White Paper

2

About the Author

Srikar Chilakamarri

Srikar Chilakamarri, a senior consultant with TCS and specializes in Business Intelligence solutions. He has a Bachelors degree in Mechanical Engineering.

Srikar has been the architect of BI solutions for some of the leading telecom service providers. He has worked in various roles of solution architect, presales consultant and program manager. He now heads the BI- telecom solutions for TCS. He has authored tBIDS (TCS’ BI domain solution for Telecom) and has led a few complex BI implementation programs.

3

Table of Contents

1. Introduction 4

2. Market Dynamics - Analysis 4

3. Business Focus - Tactics of The Game 6

4. Business Challenge - Data Management 6

5. The Solution 8

6. Business Intelligence Solution 9

7. Data Service - Process Flow 11

8. Business Intelligence Solution - Addressing Challenges 12

9. Business Intelligence - Approach 13

10. Proposition 15

11. TCS-BI Proposition for Telecom 15

Introduction

Market Dynamics- Analysis

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.

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 infl uenced by three players – Customer, Organization and Competitor.

Customer

Customers now have more choices, better offers and more fl exibility 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 effi cient data transfer and network availability 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 fast advancing 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 benefi ts 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,

4

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.

Competitor

Competition 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.

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 to the players in the game, they tend to balance.

“Dynamics impact all the participants of the game. Those who win continue to exist and losers are forced to quit”

5

Dynamics Customer Organization

Customer Centricity More options, better choices and independent of service excitement and of retaining provider customers

Infrastructure Availability of services at Market penetration and remote locations and better customer acquisition services at offered locations

Technical Adoption More features, increase in Increase in customerexpectation for service and expectation. value for money Increase in data volume and

business complexities

Innovative Services New features and better Customer excitement and service at affordable rates market expansion

Mergers & Acquisitions Little or no impact. More Increase in customer base and psychological impact a step towards establishing

monopoly.

Competition Affordable prices and value Business expansion and for money a market penetration

Challenge of creating customer

Table 1: Impact of Dynamics

Business Focus – Tactics of the game

Business Challenge - Data Management

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.

n Customer centricity: The business is driven by the ’Customer‘– a fact that necessitates knowing the customer better. Business has to be customer centric. Customer centricity means to understand and be informed about:

o Customers’ requirements and expectations.

o Customers’ changing behavior, demographics and psychology

o Customers’ behavior pattern and activities, and the external factors which impact the customer

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

n Product Pricing: A true distinguisher between a competitor and a leader is to 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 customer while maximizing its profit is the prime focus.

n 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.

n Manage Information Flow: ‘Be informed’. The information flow within the organization 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.

n Competitor know-how: Understand, know and predict the competitor behavior. 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.

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 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.

6

7

’Word of mouth‘ is an excellent marketing technique with no cost. It can be leveraged to its best by addressing this challenge.

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.

Figure 1: Data Management Life Cycle

Data Acquisition: Data acquisition is focused on the operational needs. There is a huge gap in the data acquisition requirement. Analytics and intelligence to support the business 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.

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 serving applications. 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 an understandable format. Operational systems are loosely tied up with each other with less synchronization of data. Different representations of a business entity/element refl ected in the reports create chaos in data assimilation. Today a lot of time and effort is spent on data assimilation activities within an organization.

DataQuality Data

Integration

DataExploitation

DataAcquisition

DataManagement

8

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. It’s a continuous improvement process which leads to efficient data management”

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.

Figure 2: 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.

The Solution

Market-ExternalFactor

Business Strategies

Service

n Data Quality Servicen Metadata Servicen Information Servicen Analytic Servicen Intelligence Service

Business Process

n Existing Processesn New Processesn Change in Processes

Data Process

n Monitor Servicesn Mentor Servicesn Derive Intelligencen Algorithms

Solution Framework for Telecom

Impacts Contributes

Support Necessities

SupportDrives

9

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:

n Service 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.

n Data Process layer:

o Interacts with the operational systems for continuous monitoring and mentoring.

o Derives intelligence with inbuilt business and data processing rules

o Helps identify the obscure market behavior with predefined algorithms

o Ensure feedback to the service layer for continuous improvement

The internal and external dynamics creates turbulence in the organization’s 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 (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”

Business Intelligence Solution

10

Figure 3: BI Solution

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

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, 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’

Analysis and Intelligence Service: The analysis and intelligence layer supports the business 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:

Analysis & Intelligence Service

HR

IS/IT

SCM

Networking

Finance

Sales

CustomerCare

MarketingOLAP

OLAP

OLAP

OLAP

OLAP

LogicalFramework

DataQuality

ConsistentMIS

ComplianceReporting

Meta Data

Data Service

PreparedData

Analytic Model

11

n Call centers about the customers for better customer facilitation

n Executives about the current trends and forecasted data

n Decision options and the impact of each option

n Identification of fraud and corrective measures based on historical trends

n Create awareness to the business about the upcoming events based on historical trends.

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 fl ow and its components which helps in providing efficient data service.

Figure 4: BI Process Flow

The challenges like data quality and data integration have to be rectifi ed 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.

n Data quality check performed in ETL provides data quality reports that indicate where the source systems are deviating from the set standards. This helps in making immediate corrective actions at the source.

n Data Integration process defines the standards across the organization. The feedback at this stage should be tapped to achieve standardization of data elements across the business.

Data Service - Process Flow

Data Quality

Data CaptureData

Integration

Data Reconciliation

Reports

DataCorrection

Recommendation

DataStandardization

Feedback

Data Acquisition Requirements

Information &Intelligence

DataQuality Feedback

Data Flow

Data Management Feedback

12

n Data quality and integration reports on reconciliation provide data correction methodologies. Reconciliation process collates all the reports and validates against the business rules to provide data correction recommendations.

n BI program, built on proper methodology, feeds back the data acquisition requirements 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.

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.

Business Intelligence Solution – Addressing Challenges

Industry Challenges & Issues Solution Component Solution Details

Data Volume due to Increasing Customer base

Data Completeness and exploitation

Increase in business complexities

Understand all business elements in systems

Information mismatch between operational systems

Error in data processing at source

Timely bill generation and dispatch

Analytics for business functions

Customer know-how and Intelligence

Informed Business strategies

Logical Framework

Logical Framework

Logical Framework

Logical Framework

Data Service

Data Service

Data Service

Analytics & Intelligence Service

Analytics & Intelligence Service

Analytics & Intelligence Service

Scalable framework and efficient data growth estimations

Encapsulation of business critical data elements

Provides a well defined process and models to cater to the change in business processes

Metadata Services

Periodic report from reconciliation process for timely corrective actions

Reconciliation report to minimize and avoid processing errors

Provides a report after each bill cycle to indicate errors.

OLAP and Analytic models

Data completeness and algorithms for data mining

OLAP layer providing timely information access

Table 2: Industry challenges and BI solution

13

Business Intelligence - ApproachA BI solution is a process constituting of methodologies, infrastructure, tools and technology.

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

n Infrastructure – Define and procure infrastructure to support the solution

n Tools and Technology – Tools and accelerators that can be plugged in, to catalyze the process

Figure 5: BI- Solution Approach

Methodology

Methodology – A framework definition. 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:

n Key performance indicators for the organization. The key performance indicators define the roadmap for the organization. This ensures completeness of the analytic and reporting requirements.

n Definition of the metrics – All the key performance indicators defined at the lowest level. This determines data elements that the organization would need to align to their vision.

n Operational challenges – Define the operational challenges faced by the organization, data management and data dissemination challenges.

n Roadmap for implementation – Would a step by step implementation help the organization or can it go for a full fl edged DW in a single step? This is based on each organization and can be decided at an

APPROACH

Methodologyn

n Defining of Metricsn Data Management Challengesn Roadmap for Implementationn Steps and Guidelines for

Implementation

Key Performance Indicators

Infrastructuren hardwaren Softwaren Network Availability &

Connectivity

Tools & Technologyn Data Processn intelligent & Robust ETLn Data Volumen Data Storagen Data access & Retrievaln Secured Data Access

14

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.

n Guidelines for implementation – Set up a clear guideline. Step 1 to Step n of the 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 requirements.

“Remember – Do not let the data drive you, drive the data according to business”

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.

n Operational Data store: A data store that houses operational data. It is the layer 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.

n Analytics: A data store which captures all the required metrics identified as key 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.

n Data mining and high end analytics: Derived intelligence from the behavior of 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.

n Canned reports: Static piece of information for information consumers. This tool 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 (to name a few):

n Ensure timely availability of data

n Manage huge data volumes efficiently

n Support efficient load and retrieval process

n Check and integrate proficient and efficient data quality

n Intelligent processes – Supporting rich metadata and alerting capability

n Ease data access

n Secured access to information

BI is no more an expensive and time consuming technique. There are many vendors who have this as a

15

tool (“tBIDS” from TCS, Telecom solution by Teradata and IBM). Along with the BI tools stack, solution accelerators are also termed as tools in the current market.

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:

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

n Software: Data processing, data security and retrieval drive the software requirement

n Network availability and connectivity: The network availability and connectivity have 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.

The urge to excel in the market place has been driving organizations. Data management and exploitation have not been on the priority list. This has resulted 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 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.

TCS has a wealth of BI solutions in place, which are being explored by many industry verticals across the globe. The solutions are focused in providing valued services to its customers by addressing their challenges. These solutions undergo modifications/ changes based on the market changes.

BI solutions are based on Business Intelligence Decision Support (BIDSTM), a complete framework

Proposition

TCS-BI Proposition for Telecom

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 Center (BICC), provides end to end service solution to its customer. The competency center facilitates the customer in providing services like methodology definition, infrastructure requirements, solution research, vendor liaison, technology centre of excellence, competency and knowledge management. The center 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.

16

All content / information present here is the exclusive property of Tata Consultancy Services Limited (TCS). The content / information contained here is correct at the time of publishing. No material from here may be copied, modified, reproduced, republished, uploaded, transmitted, posted or distributed in any form without prior written permission from TCS. Unauthorized use of the content / information appearing here may violate copyright, trademark and

other applicable laws, and could result in criminal or civil penalties. Copyright © 2011 Tata Consultancy Services Limited TCS

Des

ign

Serv

ices

M

07

11

II

I

IT ServicesBusiness SolutionsOutsourcing

ContactFor feedback on this article and more information, please contact us at: global.telecom@tcs.com

About TCS Telecom Industry Solution UnitTCS’ Telecom Business Unit is the second largest vertical contributing higher percentage to the overall TCS revenues. With a dedicated pool of professionals and an accumulated experience and ongoing associations with world-class Telecom service providers and equipment manufacturers, TCS has acquired unparalleled understanding of the Telecom domain.

TCS helps wireline, wireless, broadband, and cable service providers redefine their markets with innovative solutions that help them become more agile, reduce fixed operations costs, and introduce next generation services. TCS sets customers apart from their competitors with instant access to industry solutions, best-in-breed technology, assets, and frameworks.

About Tata Consultancy Services (TCS)

www.tcs.com

Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match.TCS offers a consulting-led, integrated portfolio of IT and IT-enabled infrastructure, engineering

TMand assurance services. This is delivered through its unique Global Network Delivery Model , recognized as the benchmark of excellence in software development. A part of the Tata Group, India’s largest industrial conglomerate, TCS has a global footprint and is listed on the National Stock Exchange and Bombay Stock Exchange in India.

For more information, visit us at

Subscribe to TCS White PapersTCS.com RSS: http://www.tcs.com/rss_feeds/Pages/feed.aspx?f=wFeedburner: http://feeds2.feedburner.com/tcswhitepapers