BUSINESS INTELLIGENCE SYSTEMS IN INDIAN TELECOM INDUSTRY
Introduction
Growth of Indian Telecom Industry is a major part these days. Different software systems are used for the benefit in different areas and segment of the industry. It is very important that the software used is really has ability to fulfill the various requirements of the industry. It is a very tough decision to take. Business Intelligence Systems are widely used for decision-making problems. This research will investigate various business intelligence software selection decisions, awareness & benefits involved. The objective of this research is to analyse the impact of Business Intelligence Systems in Telecom Domain, rising requirements & management of different activities practiced by the Telecom Organizations in India. The aim of the research is to identify significant factors involved. The research will take both technical and managerial factors under consideration. It will also include different modes & possibilities for the growth of Telecom Industry in India using Business Intelligence Systems. This research will also check attraction of different software organizations using Business Intelligence Software's for the growth of Indian Telecom Industry. Business intelligence technologies cover areas, like Data Warehousing & Data Mining, OLAP & Reporting, and Performance Management.
Business intelligence (BI)
Mainly refers to computer- based techniques used in identifying, extracting and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, bench-marking, text mining and predictive analytics. A Data Warehouse is one of the most valuable things for Business Intelligence System or Data warehouse rises and effective use can help decision-making intelligently that can improve the operations of Business Intelligence System or Data warehouse rises notably. It provides a collection of integrated data for on- line analytical processing (OLAP).
A data warehouse is "a subject-oriented, integrated, non-volatile, and time- variant collection of data in support of management's decisions".
Here, Business Intelligence System or Data warehouse is:
- 'Subject-oriented' means the data are arranged and optimized to provide variety of analysis requirements from diverse functional departments within an organization.
- 'Integrated' means the data warehouse combines operational data derived from different departments & strategic business units of the organization. It can use consistent naming conventions, measurement standards, encoding structures and data attribution characteristics.
- 'Time-variant' means the data are periodically loaded to the data warehouse, all time-dependent aggregations need recomputed.
- 'Non-volatile' means Data warehouse are static. Data in the warehouse system are read-only generally; data in the database are rarely changed. Data in the warehouse database are updated or refreshed on a periodic, incremental or full refresh basis.
Information is one of the most valuable assets of Business Intelligence System or Data warehouse rises and when utilized properly can help Decision making intelligently that can improve the operations of Business Intelligence System or Data warehouse rises significantly. Data Warehousing is a technology that allows information to be easily, efficiently, timely and accurately accessed for decision-making purposes. A data warehouse can be viewed as a very large database that integrates the data stored in several different operational data sources. The operational data sources are usually maintained separately to support daily on- line transaction processing (OLTP).
Need of Business Intelligence for the Telecommunications Industry
This data says that till end of 2011 global cellular phone service subscribers will be doubled. Competition in the telecommunications industry is intense and several factors are forcing major changes. A continual effect worldwide on Internet and wireless technologies will continue to advance rapidly quickly changing customer preferences, disrupting traditional communication methods and forcing prices downward. The telecommunications industry encompasses many technology-related business sectors including:
• local and long-distance telephone services
• wireless communications
• Internet
• fiber-optic
• satellites
• cable TV systems
Customer satisfaction: customers are the first step in that direction. To arrive at the overall profitability of a customer, vendors must quantify the costs associated in serving the customer over a period and the revenues realized from them during that period. The results of customer profitability analysis can help identify why some customers are not as profitable as others. For example, a customer might be unprofitable because the products used by them do not match their risk profile. Customer profitability analysis can significantly help in developing new offerings, customizing existing offerings and helping to target market segments for future growth.
Product Development: Under Forecasting to plan their networks, telecommunications service providers perform forecasting that helps operators to make key investment decisions. These decisions affect all aspects of the business including product development, launch, advertising, and pricing. Effective forecasting helps to ensure that the company will make a profit and that capital is invested wisely. BI solutions that use forecast data can help network planners decide how much equipment to purchase and where to place it to ensure optimum management of traffic loads.
Service Design and Delivery: In response to fierce competition, telecom service providers must develop new products in order to offer a wide range of new value- added services faster and more cost efficiently. Design of effective services is enhanced using BI solutions that provide information regarding the adoption and profitability of existing products and services. Business Intelligence solutions can help telecommunications service providers improve customer retention and satisfaction through the effective analysis of service fulfillment systems. Information regarding installation, upgrades and repairs to customer's service can help the business reduce the cost associated with service fulfillment.
Finance & Budgeting: The role of financial reporting has undergone a paradigm shift during the last decade. It is no longer restricted to just financial statements required by law. Increasingly, it is being used to help in strategic decision making. Many companies, in an attempt to improve financial reporting and decision making, have integrated their financial data in a data mart or data warehouse. Data warehousing facilitates analysis of budgeted versus actual expenditure for various cost heads like promotion campaigns, product development, infrastructure maintenance, investments, commissions, etc. BI tools can provide drill down capabilities whereby the reasons for cost overruns can be analyzed in more detail. It can also be used to allocate budgets for the next financial period.
Human Resource: Business Intelligence can significantly help in aligning the HR strategy to the overall business strategy. It can present an integrated view of the workforce and help in designing retention schemes, improve productivity, and curtail costs.
Challenges
Data Management is the Business Challenge for telecom organizations. 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. As we can see 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. 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 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 that indicate 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. The feedback at this stage should be tapped to achieve standardization of data elements across the business. 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. 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.
Business Intelligence for Sustainable Competitive Advantage
The model is unique in the sense that it has been developed based on the data obtained from 10 interviews in 4 different Telco organizations. Although no formal propositions are developed in this paper, the model can still be taken as a research model for further investigation. A causal modelling approach such as structural equation modelling (SEM) can be undertaken to test the model. The combined model has 9 factors and 34 variables. It is observed that the basic determinants, which are obtained from the literature, apply quite effectively in the successful BI deployment. Its determinants are Quality BI Information, Quality BI Users, Quality BI Systems and BI Governance, which falls under firm's unique resources. Organization Culture, Business Strategy and Use of BI Tools are considered moderators between successful BI deployment and the use of BI-based knowledge for sustainable competitive advantage. Organizations especially in telecommunication related industries which are planning to embark on BI can consider these variables as criteria of successful deployment. However, these criteria may not be applicable to all industries as careful analysis is first needed to select the appropriate criteria for the company. A multiple criteria modelling approach can then be undertaken to access the suitability of the company for BI deployment
Inclusive Growth and Various Impact Facts in India
The trend toward evidence-based decision-making is taking root in commercial, non-profit and public sector organizations. Driven by increased competition due to changing business models, deregulation or, in some cases, increased regulation in the form of new compliance requirements, organizations in all industries and of all sizes are turning to business intelligence (BI) and data warehousing (DW) technologies and services to either automate or support decision-making processes. An increasing number of organizations are making BI functionality more pervasively available to all decision makers, be they executives or customer-facing employees, line-of- business managers or suppliers. Pervasive BI results when organizational culture, business processes and technologies are designed and implemented with the goal of improving the strategic and operational decision-making capabilities of a wide range of internal and external stakeholders. Despite the fact that the term Business Intelligence was first coined in 1958 and the first BI software tools emerged in the 1970's, BI is not truly pervasive in any organization. As organizations identify more stakeholders who can benefit from improved decision-making capabilities, they are choosing to deploy BI and thus come increasingly closer to achieving pervasive BI. For organizations struggling with changing organizational structure and culture, business and IT processes and technologies, several lessons can be learned by examining the best practices organizations employ on their path toward achieving pervasive BI, It includes various benefits like time & cost. Knowledge is becoming more and more synonymous to wealth creation and as a strategy plan for competing in the market, place can be no better than the information on which it is based, the importance of knowledge and information in today's business can never be seen as an exogenous factor to the business. Organizations and individuals having access to the right information at the right moment, have greater chances of being successful in the epoch of globalization and cut-throat competition. Currently, huge electronic data repositories are being maintained by businesses across the globe. Valuable bits of information are embedded in these data repositories. The huge size of these data sources make it impossible for a human analyst to come up with interesting information that will help in the decision making process. Commercial enterprises have been quick to recognize the value of this concept, as a consequence of which the software market itself for data mining is expected to be in excess of 10 billion USD. Business Intelligence focuses on discovering knowledge from various electronic data repositories, both internal and external, to support better decision making. Data mining techniques become important for this knowledge discovery from databases. In recent years, business intelligence systems have played pivotal roles in helping organizations to fine tune business goals such as improving customer retention, market penetration, profitability and efficiency. In most cases, these insights are driven by analyses of historical data.
Conclusion
Business Intelligence (BI) is a business management tool, which consists of applications and technologies that are used to gather and analyze information about business. Business Intelligence systems are used by telecom companies to analyze the factors (or data from inside and outside the organization) affecting the telecom business, so as to help them in making a decision. Various tools and applications of Business Intelligence include query reporting & analysis tools, data mining tools, data warehousing tools, etc. Business Intelligence tools enable the telecom companies to make real time decisions at all levels; i.e., strategic, tactical and operational, using advanced analytics and powerful data mining tools. Further, these tools provide single integrated enterprise solution for reporting; thus, reducing the time consumed in reporting. Telecom companies operate in a highly competitive environment. As a result, a lot of pressure exists on them to increase their profit margins by introducing new product and deploying new services. Further, these telecom companies are facing issues of infrastructure up-gradation as large amount of data exists in data sources, which are incompatible. This data that remains underutilized can lead to loss of business opportunity. Further, utilization of this data will help generate businesses resolve technical issues related to customer care, billing, network engineering, product design, and marketing. With the shift in focus of the telecom industry; from technology to customers, there has been an increasing demand for customization of Business
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