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지난 4월 LG CNS?‘엔트루월드(Entrue World) 2012’를 개최하였습니다. 이 때?토마스 데이븐포트(Thomas H. Davenport) 밥슨대학(Babson College) 교수가 The Era of Analytics and Big Data라는 주제로 강연을 하였습니다. 데이븐포트 교수는 3대 경영전략 애널리스트로 손꼽히며, 국내에서도 <분석으로 경쟁하라>, <관심의 경제학> 등의 번역서로 널리 알려져 있다고 하네요.?이 자리에서 데이타경영의 우수사례로?매리어트호텔, 로열뱅크오브캐나다, 테스코, 카지노 게임사 시저스 등을 소개하였습니다.
빅데이타가 기술의 영역을 지나 경영의 영역에 다가가고 있습니다. 보통 해외의 흐름이 탄생하고 기업에 도입될 때 겪는 의례적인 경로입니다. 기술의 영역이 아니라 경영의 영역이면 도입을 위한 의사결정이 빠를테니까요.?데이타경영이라고 하지만 하늘에 뚝 떨어진 새로운 것이라고 생각하지 않습니다. 과거에도 한계가 있지만 데이타를 이용하여 판단하고 결정하였기때문입니다. 덧붙여 데이타 자체가 진리는 아닙니다. 데이타를 어떻게 해석할지는 전적으로 인간의 능력에 따릅니다.?데이타 경영을 폄하할 생각도 능력도 없습니다.
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그럼 왜 ?데이타 경영을 이야기하였을까요? CDO때문입니다. Credit Default Swap은 아닙니다.(^^) Chief Data Officer입니다. 앞서 데이타 경영이 시대의 조류로 등장하면서 새롭게 등장한 C직함입니다. 미국 월스트리트도 CDO의 중요성이 점점 커지고 있다고 합니다.
Four years after the financial crisis, institutions are still struggling to get a 360 degree view of their data,” Stephen Engdahl, senior vice president of product strategy for GoldenSource in a statement. “Relying solely on mapping instrument data to security masters is no longer an option. It is essential to risk management, regulatory requirements and operational efficiency that data management is viewed as a business function, whose quality and governance apply across the enterprise. … Appointing data stewards and Chief Data Officers to galvanize governance as a shared service across these firms will be crucial to success.”
Of those who participated in the survey, 80% of clients in the Americas, 60% in Europe, and 50% in Asia Pacific are already structuring their organizations in a way that empowers an enterprise wide data officer.
Chief Data Officer’s Role Growing in Importance중에서
왜 지금 CDO가 등장할까요?Chief Data Officer: New seat in the C-suite는 다음과 같이 분석합니다.
Data deluge: According to an International Data Corporation (IDC) study, between 2009 and 2020, the information in the Digital Universe will grow by a factor of 44, the number of “files” in it to be managed will grow by a factor of 67, and storage capacity will grow by a factor of 30. Yet the staffing and investment to manage the Digital Universe will only grow by a factor of 1.4. Companies are generating ever-larger volumes of data through both internal and external interactions. The desire for information-driven decision-making has led companies to measure and monitor specific aspect of their business. Companies are drowning in data. Finding the needle of relevant information in the exabyte-sized haystack of enterprise data is increasing the cost and complexity of information driven decision-making.
Changing nature of data: Enterprise data is no longer black and white. An eclectic mix of data sources, data types and information-sharing mechanisms are replacing dichotomies such as structured and unstructured, internal and external and enterprise and social applications. It is not uncommon for today’s enterprise to interact with customers and partners through text messages, social networks, mobile advertising, viral videos and mobile apps. Even internal communications are much more than memos and e-mails ? today’s workplace empowers employees through instant messaging, blogs and wikis. Although much of this data is user-generated, because the data passes through enterprise infrastructure, the enterprise becomes responsible for managing and protecting this data. According to an IDC study, while enterprise-generated content only accounts for 20 percent of the Digital Universe, enterprises are actually liable for 80 percent of the content . This has left businesses with the need to manage, mine and protect multiple types of data related to their internal processes, their customers, employees and the competition.
Few businesses, however, are organized to methodically exploit this plethora of data types and translate that knowledge into meaningful business insight.Competitive pressures: In almost every industry, the company with keen insights into its business and its customers holds the competitive edge. Several leading companies across various industry segments have demonstrated that effective use of data can be a true competitive advantage. The need to progress from a reactive view of business to a proactive one and eventually a predictive one is driving investments in business intelligence and analytics capabilities. However, not many companies protect these investments with a supporting organizational function. Companies can usually win a battle in the market with such periodic, targeted investments. However, in order to win the war, they may need an organizational construct that over the long term can own, manage and uphold the strategic value of the underlying data assets.
Regulatory pressures: Recent regulatory reforms have placed an even higher emphasis on data accuracy and the risks associated with the lack of end-to-end visibility. In responding to requests for detailed information about their businesses and portfolios, most Wall Street firms realized that they did not have a broad enough view of their underlying risks. This presented not only a reporting problem, but also a risk assessment problem. A company that does not know its data cannot measure its risk adequately. Risk that is not measured cannot be managed effectively.
Rapid technological evolution: As companies seek to exploit the new opportunities presented by technological advancements such as mobile devices, cloud computing, SaaS models and on-demand computing, they are grappling with new data management challenges. For the first time ever, organizational data can potentially reside outside the enterprise, including mobile devices. Applications can potentially be owned by third parties. By 2020, more than a third of information will either live in or pass through a cloud based service. This presents a whole new set of challenges, which require focused attention from the business. However, most companies are not in the business of managing data ? the skills needed to meet these challenges and deliver meaningful results should be developed as part of an organization that is exclusively focused on these issues.
그러면 CDO의 역할은 무엇일까요? 같은 논문은 다음과 같이 이야기합니다.
Be the voice of the data provide executive stewardship, champion and implement data management strategies and standards, institutionalize data quality management.
Measure and manage data risk develop capabilities to measure and predict risk, influence enterprise risk appetite at the executive table.
Influence corporate strategy enable better analytics for decision-making, help refine corporate strategy using insight gained from effective analysis of data.
Improve the top line increase revenue, customer approval ratings, customer retention, and market goodwill through the effective governance and use of data.
Improve the bottom line lower the cost of quality and cost of compliance, improve productivity through availability of timely and correct data.
아래 기사도 데이타 경영을 자세히 소개하고 있습니다.
[Mckinsey Report] 세 전문가가 제시하는 데이터 경영 전략…데이터에 성공의 기회가 있다
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트레이딩의 성격이 변화하면서 CTO가 아니라 CLO=Chief Latency Officer라는 역할을 전사적으로 요청받고 있습니다. 경영 환경이 변화하고 기술이 발전하면서 ?CIO가 아니라 CDO라는 역할도 필요로 하는 상황입니다.
CDO라는 역할이 중요하게 부각되면 될 수록 Big Data Project들이 늘어납니다. 자본시장IT는 준비를 하여야 합니다. 이를 위해 참고할 행사가 있었습니다. ?FISD Real-time Technology Roundtable가 지난 1월 런던에서 행사를 개최하였습니다.??아래는 이 때 발표한 자료입니다. Big Data를 자본시장이라는 관점에서 현실성을 검증한 자료(Reality Check)입니다.
‘Big Data’ and other techniques for handling today’s huge data volumes’을 놓고 토론도 ?하였습니니다. 토론 내용은 아래를 참고하세요. “쉽지 않다”고 이야기합니다.
FISD Panel: Big Data Poses Both Challenges and Opportunities
