We are not very good at fi guring out what unstructured information costs. The Big Data deluge is upon us. If we hope to manage—and, more important, to monetize—
this deluge, we must form cross-functional teams and challenge the way our organi- zations think about unstructured information. The fi rst and most important step is developing the ability to convincingly calculate what unstructured information really costs and then to discover ways we can recue those costs and drive value. These are foundational skills for information professionals in the new era of Big Data. In this era, information is currency—but a currency that has value only when IG professionals drive innovation and management rigor in the unstructured information environment.
CHAPTER SUMMARY:
KEY POINTS
■ The business case for IG programs has historically been diffi cult to justify.
■ It takes a commitment to the long view to develop a successful IG program.
■ The problem of unstructured IG is growing faster than the problem of data volume itself.
■ IG professionals must be ready with new models that calculate the risks of storing too much of the wrong information and also the benefi ts of clean, reliable, accessible information.
(continued)dd
■ Key steps in driving information value are: (1) clean; (2) build and maintain;
and (3) monetize.
■ The information calorie approach and information cap-and-trade are two new models for assisting in IG.
■ Legal risk is reduced through improved IG, and legal costs are reduced.
■ Leveraging newer technologies like predictive coding can improve the ef- fi ciency of legal teams.
■ Adherence to retention schedules means that records and documents can be discarded at the earliest possible time, which reduces costs by eliminating unneeded information that no longer has business value.
■ RIM functions will operate with more effi ciency and in compliance with laws and regulations under a successful IG program.
■ A compliant RIM program helps to build the organization’s corporate memo- ry of essential “lessons learned,” which can foster a KM program.
■ KM programs can facilitate innovation in organizations.
■ Focusing on business impact and customizing your IG approach to meet business objectives are key best practices for IG in the IT department.
■ Effective data governance can yield bottom-line benefi ts derived from new insights, especially with the use of business intelligence software.
■ IT governance seeks to align business objectives with IT strategy to deliver business value.
■ Using IT frameworks like CobiT 5 can improve the ability of senior manage- ment to monitor IT value and processes.
■ Identifying sensitive information in your databases and implementing data- base security best practices help reduce organizational risk and the cost of compliance.
■ By securing your electronic documents and data, your information assets will be safeguarded and your organization can more easily comply with privacy laws and regulations.
■ We are not very good at fi guring out what unstructured information costs. To thrive in the era of Big Data requires challenging the way we think about the cost of managing unstructured information.
CHAPTER SUMMARY:
KEY POINTS
(Continued)
Notes
1. International Data Corporation, “The 2011 Digital Universe Study,” June 2011. www.emc.com/
leadership/programs/digital-universe.htm (accessed November 25, 2013).
2. Richard B. Schmidt, “The Cyber Suit: How Computers Aided Lawyers In Diet-Pill Case,” Wall Street Journal , October 8, 1999. http://webreprints.djreprints.com/00000000000000000012559001.htmll 3. Nick Bilton, “At Davos, Discussions of a Global Data Deluge,” New York Timess , January 25, 2012,
http://bits.blogs.nytimes.com/2012/01/25/at-davos-discussions-of-a-global-data-deluge/; Alex Pent- land, quoted by Edge.org in “Reinventing Society in the Wake of Big Data,” August 8, 2012, www .edge.org/conversation/reinventing-society-in-the-wake-of-big-data; World Economic Forum, “Per- sonal Data: The Emergence of a New Asset Class” (January 2011), http://www3.weforum.org/docs/
WEF_ITTC_PersonalDataNewAsset_Report_2011.pdf
4. James Manyika et al., “Big Data: The Next Frontier for Innovation, Competitions, and Productivity,”
McKinsey Global Institute, May 2011, www.mckinsey.com/insights/business_technology/big_data_
the_next_frontier_for_innovation
5. Janna Quitney Anderson and Lee Ranie, “Future of the Internet: Big Data,” Pew Internet and American Life Project, July 20, 2012, http://pewinternet.org/~/media//Files/Reports/2012/PIP_Future_of_
Internet_2012_Big_Data.pdf
6. Louis Columbus, “Roundup of Big Data Forecasts and Market Estimates, 2012,” Forbes s, August 16, 2012, www.forbes.com/sites/louiscolumbus/2012/08/16/roundup-of-big-data-forecasts-and-market- estimates-2012/
7. McKinsey Global Institute, “Big Data: The Next Frontier for Innovation, Competitions, and produc- tivity,” May 2011.
8. U.S. EPA, “Making Solid Waste Decisions with Full Cost Accounting,” n.d., www.epa.gov/osw/
conserve/tools/fca/docs/primer.pdf (accessed November 25, 2013).
9. Nicholas M. Pace and Laura Zakaras, “Where the Money Goes: Understanding Litigant Expenditures for Producing Electronic Discovery,” RAND Institute for Civil Justice, 2012. www.rand.org/content/
dam/rand/pubs/monographs/2012/RAND_MG1208.pdf (accessed November 25, 2013).
10. Accounts Payable Network, “A Detailed Guide to Imaging and Workfl ow ROI,” 2010.
11. Various sources. See, for example: Barclay T. Blair, “Today’s PowerPoint Slide: The Origins of Informa- tion Governance by the Numbers,” October 28, 2010. http://barclaytblair.com/origins-of-information- governance-powerpoint/ (accessed November 25, 2013).
12. Brooklyn Navy Yard Development Corporation, “The History of Brooklyn Navy Yard,” www .brooklynnavyyard.org/history.html (accessed November 25, 2013).
13. James Manyika et al., “Big Data.”
14. Barclay Blair and Barry Murphy, “Defi ning Information Governance: Theory or Action? Results of the 2011 Information Governance Survey,” ViaLumina, eDiscovery Journal (September 2011).l
15. Jaikumar Vijayan, “Finding the Business Value in Big Data Is a Big Problem,” Computerworld , Septemberd 12, 2012, www.computerworld.com/s/article/9231224/Finding_the_business_value_in_big_data_is_a_
big_problem
16. James Manyika et al., “Big Data.”
17. Economist Intelligence Unit, “Leveling the Playing Field: How Companies Use Data to Create Advantage” (January 2011), http://blogs.sap.com/wp-content/blogs.dir/15/fi les/2012/02/EIU_
Levelling_The_Playing_Field_1.pdf
18. Genevieve Shaw Brown, “Mac Users My See Pricier Options on Orbitz,” ABC Good Morn- ing America , June 25, 2012, http://abcnews.go.com/Travel/mac-users-higher-hotel-prices-orbitz/
story?id=16650014#.UDlkVBqe7oV
19. “Health Care Bill Requires Calories on Menus at Chain Restaurants,” USA Today , March 23, 2010, http://usatoday30.usatoday.com/news/health/weightloss/2010-03-23-calories-menus_N.htm 20. Sharon Beley, “As America’s Waistline Expands, Cost Soar,” Reuters, April 30, 2012, www.reuters
.com/article/2012/04/30/us-obesity-idUSBRE83T0C820120430
21. Stephanie Rosenbloom, “Calorie Data to Be Posted at Most Chains,” New York Times s , March 23, 2010, www.nytimes.com/2010/03/24/business/24menu.html
22. James Surowiecki, “Downsizing Supersize,” New Yorker r , August 13, 2012, www.newyorker.com/talk/
fi nancial/2012/08/13/120813ta_talk_surowiecki 23. Manyika et al., “Big Data.”
24. Blair and Murphy, “Defi ning Information Governance.”
25. International Organization for Standardization, ISO/IEC 38500:2008, Corporate governance of infor- mation technology. www.iso.org/iso/catalogue_detail?csnumber=51639 (accessed November 25, 2013).
115
By Robert Smallwood with Randy Kahn, Esq. , and Barry Murphy
Information
Governance and Legal Functions
C H A P T E R 8
P
erhaps the key functional area that information governance (IG) impacts most is legal functions, since legal requirements are paramount. Failure to meet them can literally put an organization out of business or land executives in prison. Privacy, security, records management, information technology (IT), and business manage- ment functions are important—very important—but the most signifi cant aspect of all of these functions relates to legality and regulatory compliance.Key legal processes include electronic discovery (e-discovery) readiness and as- sociated business processes, information and record retention policies, the legal hold notifi cation (LHN) process, and legally defensible disposition practices.
Some newer technologies have become viable to assist organizations in imple- menting their IG efforts, namely, predictive coding and g technology-assisted review (TAR; also known as computer-assisted review ). In this chapter we explore the need ww for leveraging IT in IG efforts aimed at defensible disposition, the intersection be- tween IG processes and legal functions, policy implications, and some key enabling technologies.