Telecom. White Paper. Enterprise Information Management. An Enabler to Business Growth

Transcription

1 Telecom White Paper Enterprise Information Management An Enabler to Business Growth

2 About the Author Shantanu Sinha Shantanu is a telecom business intelligence (BI) solution architect with the telecom practice at TCS. He is experienced in telecom BI consulting, solution architecting, telecom BSS solutions, business development, project management, and project delivery for various BI engagements and projects. He has over 17 years of experience in the IT field.

3 The competitive markets today view telecom networks, services and products as commodities. Telecom companies regard data assets related to these commodities as an IT necessity used to support operations and service delivery. This view has evolved with changing market dynamics and companies have now realized that these data assets are critical to their success. It, thus, becomes crucial to have organization-wide sponsorship and involvement to control, manage and exploit internal and external data. This paper explains how Enterprise Information Management (EIM) plays a key role in understanding data assets from a holistic point of view, how it applies to both IT and business divisions of an enterprise, and how a reliable EIM framework can turn a telecom operator's data assets into powerful enablers to drive business growth.

4 Contents Introduction 5 EIM and its Relevance 5 Business Challenges 10 EIM: Acceptance and Implementation 12 Conclusion 13

5 Introduction Telecom operators, today, face a challenging scenario where their networks, products and services are increasingly becoming commodities with shrinking margins. Most, if not all their major business functions, such as network performance optimization, customer relationship management (CRM), billing, fulfillment and assurance, marketing offers, campaign management, and fault prevention are information driven. Reliable management and governance of data will enable telecom operators to succeed in the market by improving these major business functions. How effectively operators manage and use data drives their efficiency, flexibility and profitability. Operators also need to be aware of the importance of the variety of data sources and types, in addition to data growth. Typically, IT systems across business functions are developed in silos, on an as-required basis, thereby growing in a monolithic, in-house fashion. Functionally, they are service-line specific fixed, mobile and broadband. With service line convergence in terms of operations and subscribers today, it is essential to effectively integrate, manage, and use the data across service lines to get consolidated and consistent information. Operators approach their business intelligence (BI) capability with more advanced analytics functions making it imperative to embark upon EIM. It helps manage and provide a critical foundation by integrating both IT and business assets to enable more tangible business benefits. A properly planned and executed information management platform can also help significantly reduce Capital Expenditure (Capex) and Operating Expenditure (Opex). EIM and its Relevance Enterprise Information Management (EIM) combines both IT and business perspectives to build efficient and agile information management operations. EIM, in a nutshell, comprises a few core functions that are manifested through several activities and processes. Figure 1 depicts the EIM framework. In the figure, the functions surrounding the core depict how these are implemented. 5

6 Create right insights for decision making Comply with regulations and policies Master Data Management Common data definition for unit data, KPI, metrics Data Architecture and Modeling Provide consistent view of Information Integrate structured and unstructured content Control and manage influx of data efficiently and effectively Ease of locating and navigating information Increase revenue through better decisions Protect security and privacy of information EIM Elements and their Advantages Master Data Management (MDM) Data Governance Metadata Management Data Security Maintain high quality of data Figure 1: EIM Framework Data Quality Management Improve business agility Accelerate products/ services launch Standardize BI architecture Control operational expenses optimally Results in a single focal point for master data Accelerates new product development Introduces targeted offers Maximizes customer lifetime value and effective marketing campaigns or promotions Data Architecture Modeling Helps in adopting an industry-standard data model Standardizes usage of tools and BI architecture Metadata Management Standardizes data definitions Creates integrated reporting Standardizes transformation rules 6

7 Data Quality Management (DQM) Enhances quality of enterprise data across subject areas and systems Leads to build up of trust and reliability for IT system data Data Governance Establishes roles and responsibilities of information custodians Establishes processes Complies with the organization's goals and policies Leverages tools and technologies Data Security Measures Enforce processes to safeguard information Ensure the information is accessible to the designated people EIM and Communication Service Providers Trends reveal that many important communication service provider (CSP) requirements are associated with different EIM elements. Some of these requirements and how EIM can help are: Managing Data Influx Organizations are witnessing the influx of various forms of data generated from different sources into their IT systems, making it imperative to manage the data efficiently and effectively. From the EIM point of view: Right data architecture based on need enables efficient data usage and storage. Effective DQM helps in enhancing data reliability and reducing confusion. Proper data governance processes help in managing operational data growth. MDM and Metadata management help in removing redundancy and creating common definitions. Generating the Right Insights for Decision-Making¹ For information effectiveness, it is important for enterprises to generate the correct business insights that will be able to help them increase revenue, sell more products and services, enhance customer experience and lower operational expenditure. So, right information access is required for the right set of people at the right time to make the right decisions. 1 A Framework For Information Management And Consumption Technology, Forrester by Gene Leganza, September 27,

8 From the EIM point of view, there should be: Business-aligned IT data architecture to create effective information output for decision makers. DQM to help improve data reliability. MDM to ensure consistent and coherent data output. Controlling Operational Expenses Optimally It is necessary for organizations to minimize operational expenses by creating an optimal IT infrastructure that is conducive to business growth. From the EIM point of view: Right data architecture and choice of technology is important to optimize IT spends. Proper data governance processes are required to reduce rework, redundancy, confusion and, hence, cost. Creating IT Systems to Support Business Operators generally build upon legacy IT systems over time, depending on business and department needs within an organization. This leads to a large number of redundant, high maintenance systems. It becomes imperative to optimize costs by creating and maintaining the ideal number of systems. From the EIM point of view: Right IT architecture and system design can prevent unreliable output. Delayed decisions and longer time-to-market can cause inability of IT systems to support business needs. Securing Confidential Data Confidential data misuse, high security data leakage and other malpractices are common threats to organizational data security today. Organizations have attributed these mainly to growing data volumes. Data security and maintenance of confidentiality become immensely important in this context. From the EIM point of view: Data security measures, processes and practices must be enforced to control mishandling of enterprise data. Lack of appropriate access rights and security can lead to vital information falling in the wrong hands. Sustaining Competition by Smart use of Data Consistent, coherent and integrated data will lead to strong analytics and business insights while the lack of these may handicap the decision makers severely. From the EIM point of view: MDM, metadata management, and DQM, enable mining of hidden insights on customer data for new revenue streams and business growth. 8

9 Impact of Poor EIM Culture Some operators do not see the need to control and manage data, and do not put any EIM initiative into practice, leading to many problems that affect both IT and business organizations. While it impacts IT systems first and directly, it also has a considerable impact on the way operators carry out their business. Some problems that may arise due to the lack of EIM and the related challenges include: Absence of Master Data Data Problem Areas Potential Business Challenges 1 IT systems have multiple copies of products. There will be no flexibility in service bundling. 2 Lack of clean centralized customer data for crosssell, up-sell, managing faults, and follow-ups. It will impact assurance and fulfilment processes. 3 There are disparate exchange sites and geographic locations across the enterprise. There will be fallouts and loss of manpower in service assurance. 4 Dearth of integrated information of service impacts in case of network faults. There will be no link between customer, service and network fallouts data. Unreliable Information due to Data Impurity Data Problem Areas Potential Business Challenges No validation of customer address information that is manually entered in CRM systems. Lack of validation of invalid network equipment information that flows from the source system into the BI platform. Absence of common Data Quality principles followed in Operations or Business Support Systems (O/BSS) and BI systems. Credit check operations may return failure status during service provisioning. Workforce personnel will not be able to locate the required site equipment, thus rendering analytics results useless. Enterprise-wide data integrity and reliability issues will crop up when decision makers have to depend on data stored in BI systems. Non-standard Data Definition across IT Systems Data problem areas Lack of a common billing account number or a standard format for billing account numbers for both mobile and landline services for a customer. Non-standard data and exceptions in data range, type and length across operational systems. Lack of common data dictionary across business and IT organization. Potential business challenges this may lead to This may lead to the failure of the sales team to cross-sell and up-sell as the same customer cannot be identified. It leads to confusion for the data consumer and loses usability as it flows in the enterprise from one system to another. This may lead to situations where requirement analysis, service design and modelling and scope definition for new IT initiatives become challenging and timeconsuming. 9

10 Business Challenges Observations reveal that most operators do not control and manage the volume of their enterprise data appropriately. The factors leading to this include: Development and maintenance costs Company culture and senior management attitude Lack of clarity on the business impact of data Figure 2 highlights the most common business challenges faced by current telecom operators and how data management can help address these. Business challenges linked to data challenges Reduce operating costs Enhance customer experience Differentiate services Generate new revenue streams Top business objectives Appreciate data as business asset to fuel growth Consolidate data silos Bring in customer centricity in data management strategy Embrace subscriber data management Invite flexibility in information management Ownership and initiative taken by both business and IT Capitalizing on data is key to market success Major segments of telecom companies data IT implementation with full business support Raw network data Operational data Contextual data Market research data Data consolidation Data validation Data quality Data standard Data architecture Data governance Figure 2 Business and Data Challenges To achieve these objectives, it becomes necessary that both the business and the IT system appreciate certain areas of information management (as indicated in Figure 2). 10

11 Data Challenges Enterprises fail to understand the link between business and data challenges. An enterprise-wide practice of information control and management can help streamline business decisions and operations. Both business and the IT department of the enterprise must appreciate the importance of different kinds of data processed through their IT systems, by embracing these data management needs:² Appreciate Data as Business Assets: Operators need to realize that all enterprise data together forms a strategic asset that needs to be harnessed to enhance potential for business growth. It does not involve just IT projects data consolidation and integration initiatives in silos but also addresses the enterprise business objective. Ensure Customer Centricity in Data Management Strategy: Customer data is of key importance in business planning and initiatives for telecom operators. Access to varied customer-centric data will be conducive to developing products and services specific to their needs, thereby attracting new sales, winning back churned subscribers and helping control churn. Consolidate Data Silos: Telecom operators tend to develop assets in disparate silos. Operators must invest in data quality tools, MDM, and data integration tools in order to build a robust unified platform that is a reliable source of information. Embrace Subscriber Data Management: Operators should combine subscriber data with operations, network, services and product data to help augment revenue. Understand Agile Nature of Information Management: Operators must use real-time insights and up-to-date information about subscriber and network updates to help in analyzing context-specific usage behavior and in making informed decisions. At an IT implementation level, this overall enterprise information must be managed by different aspects of EIM, namely data consolidation, data validation, data quality, data standard, data architecture and data governance. Information Challenges Telecom operators often struggle to reduce hardware storage cost, simplify IT operations and produce enhanced business insights to increase sales revenue. The more IT departments struggle with data, the lesser the chance for producing meaningful business information. The enterprise then begins to sideline data management problems. Some of the implementation challenges with today's operators are: Data Architecture and Modeling Data architecture is siloed and not conducive for information management. Architecture design is IT project delivery centric and does not have executive management involvement and sponsorship. 2 Dialling into telco data, Ovum by Madan Sheina, Shagun Bali, September

12 OSS/BSS Application Integration There are integration issues with respect to volume throughput, latency, storage and capacity. Time-to-market gets delayed for new product and service development due to lack of organized enterprise information. MDM, Metadata, and DQM There is no enterprise view from MDM, metadata and DQM. Data quality standards are lacking on internal or externally generated data. Data Access and Consumption There exists a disparate set of technologies for implementing the same processes in different departments. Data is not accessible to the right set of people. EIM: Acceptance and Implementation For an operator to start an EIM initiative, the first step is realizing that implementing the EIM framework is a gradual and phase-wise process. We recommend the following steps for implementing a successful EIM framework: Stage 1: Identify an overall vision, strategy and measurable metrics for the individual elements of EIM. The sponsorship and drive have to come from the top-level management and should not be a bottom-up approach. Stage 2: Identify a governing body and steering committee once the strategy is established at the organization level. They should have specific roles and responsibility for individuals within both IT and business organizations. Stage 3: Form separate programs to work on individual areas of EIM MDM, metadata management, data quality, data architecture and modelling, data security and data governance. Define processes, policies and outcomes for both intra and inter-program interactions. Stage 4: Create an action plan for individual programs with a defined set of activities, roles, responsibilities and deliverables. Discuss and agree between the program leads as the execution of the programs will be interdependent. Once this agreement is done, the high-level EIM steering committee must review this so that an 'umbrella' review and ownership board is formed. Stage 5: Identify one business domain as part of the action plan for each program, so that the actual set of activities can be started. You can take up the plan for the next domain, once the implementation for one domain nears completion. 12

13 Conclusion EIM is not mandatory for telecom businesses to survive but the absence of it will lead to challenges that include dealing with large volumes of data, without being able to exploit its advantages. The outcome of not adopting EIM may include operations and service management going out of control, sky-high expenses, no new and innovative services to offer, churned and dissatisfied subscriber base and depreciated business revenue. At the same time, competitors who might have invested in EIM can have full control and management on their data, generate business leads out of the analytical insights and use that to explore new products and service development opportunities, optimize operations, enhance customer experience and drive further revenue growth. Investing in EIM, therefore, is the way forward for telecom companies. 13

14 About TCS Telecom Business Unit The TCS Telecom Business Unit is one of our largest verticals in terms of revenue contribution. With a dedicated pool of professionals, ongoing associations with world-class Telecom service providers and equipment manufacturers and experience in working with leading global telecom players, TCS has acquired a deep understanding of the Telecom domain and its market dynamics. 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. We help customers differentiate themselves from their competitors with instant access to industry solutions, best-in-breed technology, assets, and frameworks. Contact For more information about TCS consulting services, contact global.telecom@tcs.com Subscribe to TCS White Papers TCS.com RSS: Feedburner: About Tata Consultancy Services (TCS) 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 and TM 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 IT Services Business Solutions Consulting 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 2013 Tata Consultancy Services Limited TCS Design Services I M I 09 I 13