Making the case for data lifecycle management A must-have element for business transformation in a data-driven world
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Introduction According to the 2012 IBM CEO Study, technology takes the top spot on executive officers priority lists. 1 And it s no surprise: since the IBM CEO Study series began in 2002, technology has progressively risen on CEOs radar, to the point where it now ranks above the economy. While CEOs are invigorated by the opportunities presented by emerging technologies, they also fear falling behind, given the accelerated pace of change. The information explosion is fueling both the focus on technology and fears of being left out: Two-anda-half quintillion bytes of data are created each day, and 90 percent of the data in the world was created in the last two years. 2 Eric Schmidt, CEO of Google, reports that every two days the world creates as much information as it did from the dawn of civilization up until 2003. 3 The biggest risk we face is technological. If we fail to anticipate a huge technology step, we might go out of business. CEO of a French industrial products firm, 2012 IBM CEO Study: Leading Through Connections Unfortunately, many CEOs say their organizations operate below par in terms of deriving value from data. CEOs expressed frustration about their inability to capitalize on available information. Like many of his peers in the IBM CEO Study, a consumer products CEO from North America acknowledged, We have lots of data, but only 10 percent of it is useful information. And even within that 10 percent, we are not using it effectively. Impactful analytics is not in our genes. 3
Introduction 3 This data bounty and the burden it creates affects every business and IT function across the enterprise. But despite the importance of producing new insights from big data, many business leaders continue to see IT as an internal process and a cost of doing business, not a business enabler. In the most recent IBM CIO Study, it was revealed that only 6 percent of top business leaders view CIOs as critical to the business and organizational vision (see Figure 1). 52% 28% Business view of IT Provider of fundamental technology services Facilitator of organizational process efficiency This viewpoint must change on both sides. CEOs must realize that the heaviest responsibility for accommodating this data and seizing the opportunities generated from explosive data growth falls on the CIO. And CIOs need to focus externally, creating an IT environment that is agile and responsive to external business pressures rather than internal operations alone. Most important, collaboration is required to turn new insights into competitive advantage with tangible external business benefits. 14% 6% Provider of industry-specific solutions to support business Critical enabler of business and organizational vision Source: The 2011 IBM CIO Study Figure 1: Few business leaders see IT as a critical enabler of the business. As the creation, collection and analysis of data rises in importance, so too will the importance of the CIO role. CIOs must embrace a prominent role both inside and outside the business, with a focus on clients and results, and successfully extract insights from structured and unstructured data. In today s economy, those insights mean the difference between winning and losing. 4
Empower IT executives to drive business results CIOs and other IT executives are rewarded for spending less to deliver the same or similar IT capabilities. Business leaders might accept a slight performance degradation if it means retiring high-cost application instances or using less hardware. With relentless global competition and a challenging economy, there is no time for nice-to-have projects. CIOs might play a stronger role in the business if they could make a compelling business case for IT projects. However, producing that business case is challenging. For example, how do you demonstrate the business value of a data archiving project? What business outcome can be tied to masking sensitive data? What is the business value of migrating to the next-generation business analytics platform when the older system is sufficiently meeting requirements? What is the cost structure of a development and test environment? How can IT leaders transform these perceptions? The answer starts with a strong information integration and governance strategy. 5
A vision for aligning information with action Leading CIOs are turning to information integration and governance strategies to change perceptions of IT. Information integration and governance describe the overall management and control of information. These solutions help manage the people, processes, policies and technologies involved with understanding, correcting, completing, securing and accessing data throughout the enterprise. Defining an information integration and governance strategy An information integration and governance strategy must set out a vision for information aligned with corporate business strategy objectives and priorities. The implementation should focus on areas that help contribute to achieving high-priority business goals. A successful information integration and governance strategy will bridge the gap between business and IT executives by delivering the right data to business leaders, when they need it, while establishing policies for people and budgets that business and IT executives can share. Leading IT executives have been better able to demonstrate the business value of IT projects after implementing an information integration and governance strategy. They can easily understand and more clearly articulate the cost structure and business value of IT initiatives. Of course we need better information and insight; what we need most is the capability to act on it. Kim Salkeld, Head of Efficiency Unit, Hong Kong SAR Government, 2012 IBM CEO Study: Leading Through Connections 6
A vision for aligning information with action 6 As shown in Figure 2, there are five key aspects of an information integration and governance strategy: Information integration Data quality Master data management Data lifecycle management Privacy and security This e-book focuses on data lifecycle management, which is the process of managing business information throughout its lifecycle, from the creation of requirements through the retirement of data. This lifecycle crosses different application systems, databases and storage media. Information integration and governance Information integration Data quality Master data management Data lifecycle management Privacy and security Understand and collaborate IBM information governance unified process Figure 2: Information integration and governance provides a framework for business and IT collaboration. 7
A vision for aligning information with action 6 To improve data lifecycle management, organizations should focus on four tasks: Understand and define: Understand where data resides, what domains of information exist and how data is related across the enterprise. Define policies and standards for data management. Develop and test: Create database structures and reusable database code to enhance productivity and team collaboration. Create efficient test and development environments to support application delivery schedules. Optimize, archive and access: Ensure optimal performance of applications and databases, and archive historical data to manage data growth. Ensure business users have effective access to the data both production and archived. Consolidate and retire: Rationalize the application portfolio. Consolidate and decommission applications that are redundant or no longer current while maintaining access to the data per data retention rules, long after the application has been retired. Data lifecycle management solutions give organizations the agility to respond quickly to change. They enable cross-role collaboration. And they help accelerate delivery and performance of applications, upgrades, consolidations and enhancements to support business growth and compliance. 8
lifecycle management By implementing effective data lifecycle management as part of an information integration and governance strategy, organizations can support business goals and reduce risks by becoming better prepared for the doubling of data every 18 months. The following scenario illustrates how data lifecycle management has the power to transform businesses. Test data management at a US insurance company The director of software quality was fed up. Almost daily, lead project managers and quality assurance (QA) staff were complaining about the amount of time spent acquiring, validating, organizing and protecting test data. Complicated front- and back-end systems consistently caused budget overruns. Contingency plans were built into project schedules because the team expected test data failures and re-work. Project teams added 15 percent to all test estimates to account for the effort to collect data from back-end systems. Ten percent of all test scenarios were not executed due to missing or incomplete test data. The result: costly production defects. With 42 back-end systems needed to generate a full end-to-end system test, the business could not confidently launch new features. Testing in production was becoming the norm. In fact, claims could not be processed in certain states because of application defects skipped over during the testing process. IT was consuming an increasing number of resources, yet application quality was on a rapid decline. The insurance company clearly lacked a test data management strategy aligned to business results. Something had to change. 9
lifecycle management 9 The IT director assembled a cross-functional team and asked some tough questions: What is required to create test data? How large of a cost is test data creation? How far does the problem extend? How is the high application defect rate affecting the business? Finding the answers to these questions was an involved process. No one had a complete understanding of the full story. Through the analysis process, the team discovered that requests for test data came too late, with too many redundancies. There were no efficient processes to provide test data for all of them. Teams would use old test data because of the pain involved in getting new test data, but using old test data resulted in a high number of defects. In addition, the security risks of exposing sensitive data during testing were rampant. After fully analyzing the problems, the team concluded that with every USD14 million in new deliveries, a hidden USD3 million was spent on test data management. Sources of the hidden costs included: The labor required to move data to and from back-end systems and to identify the right data required for tests The time spent manipulating data so it would work for various testing scenarios The storage space for test data The cost of production defects not tested because test data was not available The cost to mask sensitive data to protect privacy The costs of skipped test scenarios After implementing a process to govern test data management, the insurance company reduced the costs of testing by USD400,000 per year. 10
lifecycle management 9 With InfoSphere Optim Test Data Management, the insurance company easily refreshed 42 test systems from across the organization in record time while finding defects in advance. The result was a better ability to process claims across all 50 states for less money. No longer was testing in production the norm. The business value from implementing test data management included: The company also implemented IBM InfoSphere Optim Test Data Management to further reduce costs. This software offers comprehensive test data management capabilities for creating fictionalized test databases that accurately reflect end-to-end business processes. InfoSphere Optim Test Data Management solutions can: Create referentially intact, rightsized test databases Automate test result comparisons to identify hidden errors Easily refresh and maintain production-like test environments Shorten iterative testing cycles and accelerate time-to-market Mask data in tests to ensure privacy and compliance with regulations Cost savings approximately USD500,000 Improved quality Reduced labor dedicated to test data management The insurance company now has an enterprise test data process that helps it lower costs, improve predictability and enhance testing (including enabling automation, cloud testing, mobile testing and more). People, processes and technologies came together to make a real change. 11
The value of InfoSphere Optim When used as part of an overall information integration and governance strategy, InfoSphere Optim delivers must-have capabilities (see Figure 3). InfoSphere Optim amplifies the power of data lifecycle management so organizations can maximize business value across the enterprise. It provides a central data lifecycle management solution designed to scale to meet enterprise needs. And it offers centralized controls for test data management, data archiving and data privacy. Leveraging reusable data lifecycle management templates enables consistency and scalability. InfoSphere Optim supports major enterprise databases and operating systems, including IBM DB2, Oracle Database, Sybase, Microsoft SQL Server, Teradata, IBM Netezza, IBM Informix, IBM IMS, VSAM, Microsoft Windows, UNIX, Linux and IBM z/os environments. It also supports key enterprise resource planning (ERP) and customer relationship management (CRM) applications in use today such as Oracle E-Business Suite, Oracle PeopleSoft Enterprise, JD Edwards EnterpriseOne, Siebel and Amdocs CRM as well as custom and packaged applications. Business agility and resiliency Profitability and revenue Faster processing of orders, claims and customer requests Faster time-to-market Increased customer satisfaction Reduced hardware and software capital expenses Reduced operational costs: Labor Power Data center space Hardware and software Figure 3: InfoSphere Optim can deliver an array of benefits as part of an information integration and governance strategy. Increased ability to meet servicelevel agreements Increased application performance Reduced time Automation of repetitive tasks Increased visibility and clarity Data privacy and risk mitigation Improved visibility into risk exposure Controls to mitigate risk Compliance support: Sarbanes-Oxley Act (SOX) Payment Card Industry Data Security Standard (PCI DSS) Health Insurance Portability and Accountability Act (HIPAA) Corporate and other regulations 12
Resources InfoSphere Optim is a key part of the IBM InfoSphere portfolio. InfoSphere software is an integrated platform for defining, integrating, protecting and managing trusted information across systems. The InfoSphere platform provides the foundational building blocks of trusted information, including data integration, data warehousing, master data management and information governance, all integrated around a core of shared metadata and models. The portfolio is modular. Organizations can start anywhere, and then mix and match InfoSphere software building blocks with components from other vendors. Or they can deploy multiple building blocks together for increased acceleration and value. The InfoSphere platform offers an enterpriseclass foundation for information-intensive projects, providing the performance, scalability, reliability and acceleration needed to simplify difficult challenges and deliver trusted information faster. To learn more about IBM InfoSphere Optim and the value of data lifecycle management, please check out these resources: ibm.com/software/data/optim ibm.com/software/data/optim/streamline-testdata-management ibm.com/software/data/optim/managedata-growth ibm.com/software/data/information-governance/ overview.html ibm.com/software/data/optim/protectdata-privacy 13
Copyright IBM Corporation 2013 IBM Corporation Software Group Route 100 Somers, NY 10589 Produced in the United States of America February 2013 IBM, the IBM logo, ibm.com, DB2, IMS, Informix, InfoSphere, Optim and z/os are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the web at Copyright and trademark information at ibm.com/legal/copytrade.shtml Netezza is a trademark or registered trademark of IBM International Group B.V., an IBM Company. Linux is a registered trademark of Linus Torvalds in the United States, other countries or both. Microsoft, Windows, Windows NT and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries or both. UNIX is a registered trademark of The Open Group in the United States and other countries. This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates. 1 IBM. Leading Through Connections: Insights from the Global Chief Executive Officer Study. http://public. dhe.ibm.com/common/ssi/ecm/en/gbe03485usen/gbe03485usen.pdf 2 Smarter Planet Innovation Explanations: Jeff Jonas on Analytics, ibm.com/smarterplanet/us/en/innovation_ explanations/article/jeff_jonas.html 3 Tynan, Dan. Prepare for Data Tsunami, Warns Google CEO. PCWorld. August 6, 2010. www.pcworld.com/ article/202817/prepare_for_data_tsunami_warns_google_ceo.html?tk=hp_new The performance data and client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions. THE INFORMATION IN THIS DOCUMENT IS PROVIDED AS IS WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided. The client is responsible for ensuring compliance with laws and regulations applicable to it. IBM does not provide legal advice or represent or warrant that its services or products will ensure that the client is in compliance with any law or regulation. Please Recycle IMM14109-USEN-00