Data warehousing is a strategy used to
empower employees with access to information about market,
customers, vendors, and so on. How relevent is it in telecom?
Competition drives innovation. And no industry
today is seeing competition as fierce and change as dramatic as
telecommunications. Deregulation, mergers and acquisitions, and
technological advancements have brought dramatic changes to the
telecommunications industry. Needless to say, this has emerged as
one of the hotly contested global markets. Traditional
telecommunications providers not only face competitive threats
from each other, but also from cable, wireless, satellite, and
private network providers. In response to the on going and
ensuing competition, telecommunications companies are rethinking
their fundamental business models. They are shifting resources,
exploring new market opportunities, and re-examining their
business processes and are re-engineering to increase revenues
and decrease costs.
They rely on new technologies and opportunities
to gather more and more information about each customer, while
reducing overheads in legacy, proprietary, and inflexible
mainframe environments. And more and more, they are implementing
cost-effective, enterprise-wide systems on parallel, scaleable,
and open database technologies.
In an industry like telecommunications, the
winners will be those that can adapt quickly to new market
opportunities. In this backdrop, telecommunications providers
need mission-critical informational technology solutions that can
combine performance and scale-ability with flexibility and
Criticality Of Data
Warehousing In Telecom
In today’s fast-paced
deregulated telecom world, an operator’s business can no
longer revolve around the network, it must revolve around the
customer. When customers are free to pick and choose their
service provider at will, things tend to change. Improving
network infrastructure is no longer an end in itself, but a means
to retain profitable customers and attract new ones. Carrying out
this customer-driven view of the business as opposed to the
network-driven one is the whole point of data warehousing.
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Data warehouse is a pivotal technology that
enables a carrier to gather and apply market intelligence on
customer behaviour and network usage. It is a strategy which
gives employees robust access to information about customers,
markets, suppliers, financial results, etc., which enable them to
strategically learn from the past, adapt to the present, and
position for the future.
A data warehouse is subject-oriented,
integrated, non-volatile, time variant, collection of data that
is used in the support of management’s decision process.
This is one of the commonly accepted definition of data
Demands From The Telcos
acquisition and retention
Dealer analysis and
Network utilization and
Subject-oriented, because information is
classified and stored in the data warehouse based on those
subjects that are of interest to the enterprise.
Integrated, as there should be
consistency in the naming convention, physical attributes of
data, etc. because the source of data going into the data
warehouse is from diverse segmens like customer care and billing
system, the F&A system, the MIS system, and third party
demographic data. The basic concept behind integration lies in
the fact that the data stored in the data warehouse should be in
a singular, globally-accepted fashion. So, when the Decision
Support System (DSS) analyst looks at the data warehouse, his
focus would be on using the data in the data warehouse, rather on
wondering about the credibility and consistency of the data.
Non-volatile, because unlike an
operational environment, where in regular updates, inserts,
deletes, and changes happen, the data that is once entered into a
data warehouse remains unchanged. Besides this, the information
in it is both detailed and summarized.
Time variant, because the data in the
data warehouse is historical in scope, often spanning a number of
years, to be used in identifying and evaluating trends.
Key To Successful Data Warehousing
One thing that has to be
understood clearly is that data warehousing is not an of-the-self
product. It is an enabling technology, where the bulk of the cost
involved is in consultancy and implementation of the data
warehouse, which can go up to as high as 60 percent of the total
project cost. Any data warehouse is only as good as the people
who make it.
Systems integration is the key to data
warehousing project. Among the easier steps in the implementation
process is deciding on the software tools to use. Among the most
difficult things to do is to arrive at the “business
rules” that will drive the entire design process. All data
warehousing projects need and must start from the user, for it is
his requirements that the data warehouse is created to address.
Data Warehousing SI Partner
points that have to be taken into consideration include:
For this to happen, the Systems Integrator (SI)
should, at a very basic level, understand the user’s
business both from the business and IT perspectives. The
integrator should have worked on and have an under-standing of
the clients operational systems.
Mostly, the SI will act as the user’s
one-point contact in data warehousing implementation. It is
normally not wedded to one tool vendor but maintains relationship
with a host of tool vendors and, as a result, gives the users an
unbiased feedback on the software tools available.
Deciding On What To
Warehouse In Telecom
Over the last two decades,
extensive computerization has led to the creation of large
volumes of transaction data in organizations, yet decision makers
have been unable to use this data effectively. With
liberalization of the global economies, the very survival of
organizations may depend on their ability to transform their past
and current transaction data into useful information in order to
make fast, well-informed, decisions.
In today’s competitive scenario,
technology must provide information (not mere data) that leads to
the development of a strong knowledge base. This information must
be accurate, timely, and supportive of the organization’s
mission. Information from various sources must be integrated to
enable efficient and effective decision making. It is around this
axiom that the Decision Support System (DSS) be built thereby
enabling organizations to achieve their goals and objectives.
In the telecom scenario, there is a large
amount of data available in a variety of systems. While these are
required for billing and other operational functions, they do not
really meet the management’s information needs. A data
warehouse provides the user the key information that he would
like to have in order to affect better decisions, such as, call
usage analysis, call volume analysis, handset usage analysis,
network utilization and down-time analysis, customer
segmentation, billing patterns, churn and its reasons, customer
satisfaction and dealer analysis, receivable and fraud analysis,
and profitability analysis.
telcos in the metros have problems as under.
- Unable to meet marketshare objectives.
The primary reason for this could be that the
person does not have information needed to understand either what
the customers want or how they use the services.
He needs to be able to analyze detailed current
and historical customer data in order to fully understand how
customers are using the service and use the information to
develop customer segments and profiles. To realize this
information, he will require metrics such as customer value by
services used overtime and historical usage patterns.
- Poor customer services image.
To address to this alarming situation, he needs
to analyze customer data to understand how customers are
currently being serviced and develop strategies for optimizing
service to high-value customers.
For this kind of information to be generated,
he will require certain critical metrics such as number of
customer complaints, number of customer complaints from
high-value customers, customer satisfaction measures, industry
customer satisfaction measures, and marketshares.
- Unable to offer new services as these
cannot be justified.
In this circumstance, the executive requires
the analysis of how customers use its service, identify patterns
of usage, predict future trends of usage, and then identify the
underlying capabilities needed to support the development of new
services. He might require some further inputs on backlog of
customer demands for enhanced services, number of new services
launched by the competitors, etc.
time terms like data warehousing and data mining are
mentioned in the Indian context, the picture that forms
in one’s mind is that of dusty paper files stacked
up in a remote corner or undecipherable data
stored in some decades-old-systems/floppies. Who
will clean up these data, to begin with?
It is almost a story of data
Data warehousing and
This makes it not only
- Loosing high value customers to the
- Not meeting revenue-per-customer objective
- Ineffective promotional campaigns
- Unable to bring new services to market
Besides this, the other decision making
executives, like the CEO, top network operations executive, and
top information systems executive might face a whole set of other
issues to contend with.
Possible issues faced by the CEO
- Not meeting the profitability objective
- Not meeting revenue objective
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Size (Rs crore)
Possible issues faced by the top network
- Unable to make optimal decisions for
deployment of expensive resources
- Poor customer service
- Unable to meet demand from marketing to
provide new services
- Increasing network equipment cost
Possible issues faced by top IS executive
- Cannot respond to information demands from
- Current systems environment severely
limits access to information
In order to succeed in the changing telecom
marketplace and be able to address questions arising out of any
of the aforesaid issues, the operator needs to plunge into his
operational databases and come up with information that will
assist management in their decision support activity.
The paradoxical thing in the whole scenario is
that the carrier in most cases is generating and sitting on huge
volumes of data which he can barely manage and provide
information on. Needless to say, the carrier operates in an
industry where the number of customers are huge and the number of
transactions even larger. For example, one of India’s metro
cellular operators has a base of around 100,000 active customers
which must be generating an average 500,000 Call Data Records
(CDR) per day.
This is where an operator needs the means to
completely analyze detailed call records to identify historical
usage patterns. If an operator could fully understand how
customers were using existing services, it would be able to
define customers’ needs and predict acceptance of new
Telstra Embraces Data Warehousing
Telstra Pvt Ltd, one of the cellular service providers in
Calcutta, is utilizing Informix’s database
technology for planned data warehouse applications. The
dataware house is enabling Modi Telstra to understand
better the market place, customers, and their behavior
patterns and take a leadership position. Customers are
now analyzed and segmented by common values, needs, and
their call behaviour–not simply by the product they
In an increasingly
This is where a data warehousing solution would
come into significance. There is no denying the fact that
information and knowledge is the only sustainable competitive
The Indian Scenario
Indian telcos are witnessing
stiff competition and companies have to keep their
competitiveness at global levels. As per the current National
Telecom Policy, a rapid acceleration of telecom services is
visualized that would require supplementing the resources
allocated to this sector. In its policy document, DoT has
recognized that improving telephone services would be crucial for
the development of the national infrastructure and to lure
foreign direct investment. Which is why DoT has opened the doors
to independent service providers for both basic telephone
services and value-added services–like cellular telephones
and paging. As a sequel, this has brought in organizations with
high-capacity handling capabilities into the Indian scenario that
generate large volumes of data overtime. Therefore, there is a
concomitant demand for data warehousing in the telecom industry.
Data warehousing is still in a nascent stage
but is going to be a big market in future. Its architectures have
become popular as a mechanism to integrate dispersed data for
user-friendly queries and reports. Data warehousing
implementation is currently being undertaken on a pilot basis.
Vendors have been trying to actively promote awareness of data
warehousing concepts and solutions in India. These vendors are
entering into partnerships with leading Indian SIs–like
DEIL, Tata-IBM, Tata Infotech, and Wipro Infotech which are
actively formulating strategies for targeting this market.Â
|Players Who Matter|
Poona University campus, Ganesh Khind, Pune – 411 007;
Tel.: 0212-350507; Fax: 0212-357551/353051
NCR Corp. India