Sexy job, sense of humor, slogan
By Peter Horner
They already have the sexiest job of the 21st century according to a Harvard Business Review article by Tom Davenport and D.J. Patil. Now, it turns out, data scientists also have a great sense of humor. Who knew?
The Institute for Operations Research and the Management Sciences (INFORMS) will hold exams for its Certified Analytics Professional program according to the following schedule:
Campus of University of MD, Baltimore County
University of Colorado Denver
University of Washington
Eastside Leadership Center
Bellevue, Wash. (suburb of Seattle)
Queens School of Business
Toronto, Ontario, Canada
Jan. 11, 2014
ITPG Education Center
Vienna, Va. (suburb of Washington, D.C.)
Jan. 29, 2014
University of Alabama
Business Analytics Symposium
March 6, 2014
Drexel University James E. Marks Intercultural Center
March 29, 2014
INFORMS Conference on Business Analytics and O.R.
Westin Boston Waterfront
March 30, 2014
Gartner BI & Analytics Summit
Venetian Resort Hotel & Casino
June 21, 2014
INFORMS Conference on The Business of Big Data
San Jose Marriott
San Jose, Calif.
To apply, click on https://www.informs.org/Certification-Continuing-Ed/Analytics-Certification/Apply-for-Certification
For more information, click on https://www.informs.org/Certification-Continuing-Ed/Analytics-Certification
March 30 - April 1, 2013
2014 INFORMS Conference on Business Analytics & Operations Research
June 22-24, 2014
2014 INFORMS Conference on the Business of Big Data
San Jose, CA
December 15, 2013
AnyLogic Conference: Multimethod Simulation & Modeling
Special ArticlesOnline map illustrates importance of global competence for U.S. students
Nearly 1 million data points have been collected to prove what parents, businesspeople and policymakers already know: American students must be globally competent to succeed in the interconnected 21st century. “Mapping the Nation: Linking Local to Global,” a new online resource from Asia Society, the Longview Foundation for Education in World Affairs and International Understanding, and analytics leader SAS, makes a compelling case for a globally competent workforce and citizenry.Read More
Industry NewsTrade Extensions completes large pipeline project
The Trade Extensions sourcing and optimization platform recently completed its largest project ever. The project, sourcing all the elements associated with constructing a large European gas pipeline, highlights how e-sourcing and optimization are becoming the norm for large-scale projects.Read More
Industry NewsWi2, Accenture offer analytics services platform in Japan
Wire and Wireless Co., Ltd. and Accenture have launched an analytics services platform for consumer companies in Japan that delivers context-based customer insights and supports in the creation of new, personalized services. The platform will allow businesses across a range of consumer-facing industries to identify relevant target groups, better understand where and how these customers purchase products and services, and engage them on their mobile devices with tailored offerings and promotions.Read More
Chief Data Officer: New seat in the C-suite
Why and how to provide the executive stewardship your data assets deserve.
| || |
By Rich Cohen (LEFT) and Ara Gopal (RIGHT)
Most companies and leaders realize that data is a vital enterprise asset and spend quite a bit of time and money on data initiatives. However, few companies manage data with the same amount of diligence and commitment as other enterprise assets, such as people, finances, facilities and intellectual property.
One only needs to look at the organizational structuring, planning and accountability that goes into managing the other vital asset – money. Even though the finance function does not own all the money in the enterprise, it is responsible for the overall management of the company’s finances. Most importantly, the chief financial officer (CFO) is empowered to set forth the parameters and guidelines regarding the allocation, consumption, management and accounting of financial assets. The chief executive that owns each enterprise asset is empowered to make decisions regarding the quality (e.g., human resources skills in the case of chief people officer: CPO), availability (e.g., expense budgets in the case of chief financial officer: CFO), efficiency and useful life of the asset (e.g., laptops, desktops in the case of chief information officer: CIO). In most organizations, data assets do not get this level of attention.
The lack of strategic management of data assets can undermine the very purpose of the extensive data gathering companies have put in place. Organizations and leader makers can drown in the data deluge that not only makes decision-making less effective but can have more serious consequences. In the case of the U.S. military, data deluge has turned out to be life threatening. The New York Times recently reported that since the attacks of 9/11, the amount of intelligence gathered by remotely piloted drones and other surveillance technologies has risen 1,600 percent. A recent military investigation into collateral civilian deaths in Afghanistan uncovered information overload as the underlying cause the operators were not able to quickly sort through the deluge of data being fed from the drones .
This paper examines why enterprise data assets increasingly need the executive stewardship of a chief data officer (CDO), how to build an effective organizational structure, and how to make the position of the CDO impactful.
Why a CDO and why now?
The current economic, regulatory, technological and social changes sweeping the globe present businesses with unprecedented challenges. More importantly, they present businesses a specific set of opportunities that require smart management of data assets more than ever before.
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.
Figure 1: The Digital Universe.
Source: IDC Digital Universe study, sponsored by EMC, May 2010.
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.
“Business owns the data and IT owns the applications” has been a widely accepted notion over the last decade. However, it is time for companies to challenge this truism. In most organizations, business does not want to own the data and business is not equipped to manage the data. However, a CDO can provide the top-down, data management rigor that enterprise data demands.
Roles and responsibilities of the CDO
The chief data officer, as part of a company’s executive management, plays a pivotal role in the following areas:
- 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.
Table 1: Model of two contrasting ways of structuring the CDO function.
How to develop the organization structure
As with other enterprise-wide initiatives, having a suitable organizational structure is critical to the effectiveness of the CDO initiative. While every organization has particular traits, certain characteristics drive the type of data governance structure that can work better for an organization. The CDO function should be developed keeping in mind how these characteristics influence the effectiveness of enterprise data management. Characteristics to consider:
- Size and footprint – number of countries/markets in which the company operates, number of businesses the company is in, number of separate business units or subsidiaries within the company, and number of employees and customers that the company serves.
- Industry – complexity of the data and the extent to which data is critical to core business processes (e.g., financial services on the one hand and manufacturing on the other); number of customer interactions that generate data or depend on high quality data (e.g., retail and e-commerce on one hand and industrial products or processing on the other); degree of regulatory oversight (e.g., finance and health care on one hand and hospitality and entertainment on the other).
- Information technology (IT) organization – Is IT a shared service within the organization or does each major business unit manage its own IT needs? Are IT budgets centrally managed or does each business unit pay for its own technology needs? Does the CIO report to the CEO or to the CFO; in other words, is the IT organization seen as an integral part of the corporate strategy or it is seen as a cost center that enables day-to-day business operations?
- Maturity of data management practices – extent to which the pillars of enterprise data management, such as data governance, data quality, master data management and data security are prevalent in the organization; degree to which methodical data analysis drives executive decision-making; presence or absence of documented data management policies and procedures; extent to which industry standards have been adopted; and most importantly, the level of executive support for data management initiatives.
As is evident from the above considerations, the possible choices for an effective operating model range from a highly centralized one to a highly de-centralized one. Most organizations often pick a model that falls somewhere in the middle of this continuum – high degree of centralization in one area is usually offset by decentralization in another. Therefore, each organization has to carefully choose the model that can enable the CDO function to have meaningful impact on the business.
How to get started
Even the best planned governance efforts can fail without support and participation from pertinent stakeholders. Organizations should pay special attention to the following aspects of when launching the office of the CDO.
Secure total backing of the rest of the C-suite: The primary role of the CDO is that of championing an area that, historically, hasn’t been a top-of-the-mind issue for executive management. It is therefore critical to have the understanding, buy-in and active participation of the entire C-suite. The executive leadership should agree on the vision, roles and responsibilities of the CDO and be willing to provide resources from their respective organizations to build out the data organization.
It is common for the other executives (and their subordinates) to view the office of the CDO as one that intrudes on their “turf.” Organizations must take steps early on to replace this view with one of collaboration and joint success. This outlook should originate at the top levels of the organization and permeate throughout the other levels.
Piggyback on large business problems: In most organizations, it can be difficult to secure executive backing unless the CDO initiative is seen as a direct response to a burning business problem. For example, financial companies that recently were under increased regulatory scrutiny may be much more receptive to the idea of strategic management of data and risk. Similarly, the health care industry is being challenged to move toward standardized electronic patient records and this is an issue that can get the attention of most business executives.
Organizations must look for such large “heart of the business” problems in their industry or market place and then articulate how a dedicated data management organization can help the business meet these challenges. Data governance initiatives without specific business benefits will more often than not fail in infancy.
Recognize the specific combination of skills that a CDO should possess: Effective CDOs are those individuals who possess a balance of technical skill, business knowledge and people skills to smoothly navigate the technical and political hurdles of shepherding valuable corporate data . Having the person with the required combination of skills can often make the difference in data management initiatives. The CDO cannot be purely a technologist like the CIO or the CTO because an extensive understanding of the business, the industry and the marketplace is essential for strategically leveraging the power of information. On the other hand, an experienced business professional without solid technology skills will not be able to plan and execute the IT projects necessary to manage the data. A person who has both these skills may need the ability to smoothly collaborate with various groups within the enterprise and overcome the political resistance that is often part of such initiatives.
Clearly define responsibilities for the CDO: The roll out of the CDO function should be coupled with a clear definition of the roles and responsibilities. The early adopters of the CDO function were large Wall Street companies with a focus on risk management and compliance. In other industries the primary focus of this function may be on analytics, supply chain visibility or customer facing initiatives. Companies should set clear objectives and outcomes when launching the CDO function – this not only can provide clarity to the role but can also increase alignment with the rest of the organization.
Empower the CDO with execution authority: Without the authority and resources to execute data management and governance initiatives, the CDO may play a mere advisory role and can struggle to have real impact on the business. The CDO organization should be staffed with the IT and business resources that can plan and execute special projects that are exclusively focused on strategic priorities pertaining to enterprise data management.
The data deluge in the past decade and the increasing need to gain business insight has meant that enterprise data demands to be managed with the same diligence accorded to other enterprise assets. While most companies realize this, very few have the dedicated executive stewardship and organizational structure to effectively manage their data assets. Organizations need a chief data officer who can be the champion of enterprise data at the executive table and can provide the leadership and stewardship required to effectively manage data assets. Organizations should carefully evaluate characteristics such as size, footprint, organization structure and maturity of data management practices to arrive at the optimum way to structure the CDO organization.
In order to be effective, the CDO needs to have the full backing of his/her C-suite counterparts and should be provided the authority and resources to execute strategic data initiatives. The CDO must also possess a particular blend of technical skills, business acumen and political savvy too, in order to have a direct impact on risk management, business performance and long-term strategy. Before instituting a CDO function in their organization, companies should set clear enterprise data management objectives in the context of a larger business problem.
Rich Cohen (email@example.com) is a Houston-based principal with Deloitte. Ara Gopal (firstname.lastname@example.org) is a manager with Deloitte based in Foster City, Calif. This article contains general information only and is based on the experiences and research of Deloitte practitioners. Deloitte is not, by means of this publication, rendering business, financial, investment or other professional advice or services. Copyright © 2011 Deloitte Development LLC. All rights reserved.
- Richtel, Thom and Shanker, Matt, “In new military, data overload can be deadly,” New York Times, Jan. 17, 2011.
- Gantz, John and Reinsel, David, “The Digital Universe Decade: Are you Ready?” (accessed online May 2010).
- Griffin, Jane, “The Role of the Chief Data Officer,” Data Management Review, 2008.