Social Business =Cloud + Big Data + Social Media + Mobile Computing


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Cloud Computing is an inflection point, and is the technology that enable Big Data and predictive analytics. In combination with Big Data, Social Media and Mobile Computing, it constitutes how mainstream business use Cloud

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  • Mobile to Cloud leads to Cloud to Cloud
  • Expectations re prviacy,
  • Social MediaSocial network privacy rulesFacebook controversies as an illustrativeGoogle book project Issues with treating as a copyright litigation settlement Blogging as advertising and “sponsored” content
  • Social network privacy rulesFacebook controversies as an illustrativeGoogle book project Issues with treating as a copyright litigation settlement Blogging as advertising and “sponsored” content
  • Cooperative Business Ventures Terms of use and obtaining consent Practical enforceability issues Contracts of adhesion What are current reasonable expectations? European vs. US PII (and Canada too) What data can be combined Licensing as a vehicle Combining representations and warranties with continuing covenants Indemnification for proper collection and consent
  • Social Business =Cloud + Big Data + Social Media + Mobile Computing

    1. 1. Social Business = Cloud + Big Data+ Social Media + Mobile Computing William A. Tanenbaum Chair, Technology, Intellectual Property & Outsourcing Group Chair, GreenTech and Sustainability Group Kaye Scholer LLP New York and Palo Alto Offices 60758855.pptx
    2. 2. Overview• Cloud + Big Data + Social Media + Mobile Computing = Social Business• “Cloud of Clouds”• New outsourcing• Sustainability in mainstream companies and in supply chains will be IT-enabled and make use of Cloud• Cloud vs. IT Outsourcing• Security as a service• BYOD to work (“bring your own device”) 60758855.pptx 2
    3. 3. “Old” Business Data Aggregation• Credit Reports• Background Checks• Financial industry reporting of trading activity 60758855.pptx 3
    4. 4. New Data Aggregation• What is new?• Big Data – the three “V’s” – Volume – Velocity – Variety• Computer “horse power” to handle volume• Unstructured as well as structured data• Social Media as Supply Chain – Measuring intensity• User-provided information 60758855.pptx 4
    5. 5. Hypothetical to Illustrate Key Issues• Property management outsourcing hypothetical• Underlying city map• Building locations overlay• Building interior/mechanicals overlay• Maintenance records• Mobile-to-Cloud• Cloud to legacy records and vice versa• Tenant PII – Leave vs. service agreement – Consent 60758855.pptx 5
    6. 6. Key Issues – Continued• Building sensors (and sensors to the Cloud) – Wired vs. IP addresses• Track employee location• Real-time truck re-routing• Monitor employee efficiency• Determine parts inventory levels• Supply chain coordination for just-in-time repairs 60758855.pptx 6
    7. 7. Key Issues – Continued• Customer wants historical data to evaluate maintenance and provider performance (and number of skilled employees)• Customer wants predictive analytics• Customer wants real time dashboards• Big Data needs data displays (need not be static)• Provider wants data for fine-tuning SLA’s and pricing for future projects and employee training• Predictive analytics tools/algorithms• Different levels of data roll-ups 60758855.pptx 7
    8. 8. Key Issues – Continued• Multiple outsource providers and subcontractors and IT infrastructure providers• Sustainability – Make buildings and units more energy and water-efficient – Electric vehicles – Trucks as “Rolling Storage Units” (“RSU’s”) – Power co-generation; solar/wind• Portfolio of providers• Cross-licenses• Summary: need to know your data ecosystem 60758855.pptx 8
    9. 9. Sources of Data• Customer records• Customer websites• Business partners• Third parties• Internet tracking companies• Social Media• Company submissions to portals maintained supply chain customer or jointly in an industry – ROHS as illustrative• Metadata• Clouds used by employees on “BYOD” 60758855.pptx 9
    10. 10. Owners vs. Licensing vs. Right of Access• Cannot license data you do not own or in which you do not have sufficient license rights 60758855.pptx 10
    11. 11. Customer Records• Customer records and company’s own websites – Terms of Use and Consent – Click-through agreements – Challenges to enforceability 60758855.pptx 11
    12. 12. Obtaining – and Proving – Consent• Contracts of adhesion vs. expectations privacy and use• Enforceability vs. number of screens• How record and prove consent? – Electronic signatures? – E-Sign 60758855.pptx 12
    13. 13. Business Partners and Third Party DataProviders• Anonymity – Is it anonymous if all companies use the same encryption hash? • Potentially an issue with health data in new health care electronic record ecosystems 60758855.pptx 13
    14. 14. Internet Tracking Companies• Web bugs are not the current controversy• Health care as illustrative of sensitive issues• FDA and FTC• Representations, Warranties and Continuing Covenants• Indemnities; termination remedies• Consequential damages vs. specified direct damages 60758855.pptx 14
    15. 15. Social Media• Social media as supply chain 60758855.pptx 15
    16. 16. New Role for HR Outsourcing• Problem: – Potential HR legal liability from considering information reported on Facebook and other social networks• Emerging Business Solution: – New role for Outsourcing – Outsource providers conduct social media background checks – Insulate HR departments 60758855.pptx 16
    17. 17. Potential Outsourcing Issues• Outsource providers retained to perform data analytics• Results in datasets from multiple customers which can be combined to yield valuable data asset• Outsourcing providers directly monetize or license data to third parties• How can outsource customer protect against data collected for it and data analytics on such data being used by competitors? 60758855.pptx 17
    18. 18. Customer’s Potential Solutions• Assert ownership over data• Assert exclusive rights over analytic tools• Use contact to limit combination of datasets with those of other customers, public data, or other sources of data (or other sources) 60758855.pptx 18
    19. 19. Outsourcing• Portfolio model of outsource providers• Need to structure to ensure data sharing• Licensing rights back to each provider 60758855.pptx 19
    20. 20. Revisiting Common NDA Provisions• Fact Pattern: common exclusion of protection for public domain material• Business Problem: information technically in the public domain needs to be maintained as private asset or protected because of regulatory obligations – EU PII; U.S. GLB, Health, FTC – Non-regulatory data constitutes business intelligence• Solution: modify public domain 60758855.pptx 20
    21. 21. Competitive Intelligence• Business Problem: Competitive information can be inadvertently disclosed through identification in RFP’s of subcontractors and analytics tools• Solutions: – Reduce scope of identification – Early stage use of confidentiality agreements 60758855.pptx 21
    22. 22. Cross-License Data Agreements• License terms for data• Cannot license what do not own or have license rights to• Scope of use limitations• Negative covenants 60758855.pptx 22
    23. 23. Defensive Use of Trade Secret Protection• Wal-Mart and Sustainability Consortium• Reporting requirements/requests• Can adverse information be “shielded” by trade secret?• SEC and financial statement reporting obligations• Is this public data? 60758855.pptx 23
    24. 24. Licensing and Outsourcing Terms• Outsourcing: Draft RFP’s to contract schedules to review by subject matter experts – Regulatory compliance• For IP ownership and documentation, complete pre-agreed upon assignment in recordable form, even if not recorded, and record with PTO or Copyright Office when advisable• Audit rights• Specific data deliverables• Data Managers• Timely notice of data claims 60758855.pptx 24
    25. 25. Questions and AnswersWilliam A. Tanenbaum Chair, Technology, Intellectual Property & Outsourcing Group Chair, GreenTech and Sustainability Group Kaye Scholer LLP, New York and Palo Alto 212-836-7661 60758855.pptx 25
    26. 26. William A. Tanenbaumwtanenbaum@kayescholer.comWilliam A. Tanenbaum is the international chair of Kaye Scholer’s Technology,Intellectual Property & Outsourcing Group and its GreenTech and SustainabilityGroup and works in the firm’s New York and Palo Alto offices. Chambers foundthat he “built one of New York City’s most outstanding transactional IT practices,”that he is a “well-respected attorney, with a well-informed approach [who] provideslitigation, transaction work and strategic counseling on a range of technologyissues,” that he is “efficient, solution-driven and makes excellent judgment calls,”and that he is an “internationally recognized intellectual property, technology andoutsourcing lawyer”. He is recognized as a “Leading Individual” and was awarded“Recommended” ratings in both “Technology and IT Outsourcing” and “BusinessProcess Outsourcing,” and named as a “Notable Practitioner” at the national levelin Outsourcing. He was voted one of the world’s top 250 IP strategists (IAM clientsurvey) and he was selected as one of the country’s top 25 pre-eminent ITpractitioners in the Best of the Best USA. He regularly advises clients on strategicintellectual property concerns, privacy, data security, data transfer, information lifecycle management and competitive intelligence matters, in both transactional andlitigation contexts. 60758855.pptx 26
    27. 27. William A. Tanenbaum (cont’d) Mr. Tanenbaum is the founder and co-chair of PLI’s annual Outsourcing Conference, the founder and chair of its Green Technology conference, and a regular lecturer at industry outsourcing conferences. He chairs Kaye Scholer’s GreenTech breakfast seminar series and presents webcasts on IT, IP and GreenTech topics. He has contributed to Bloomberg’s Energy Sustainability Law Report. He is a past President of the International Technology Law Association (formerly the Computer Law Association) and is listed in Who’s Who in America, the International Who’s Who of Business Lawyers, the Guide to the World’s Leading Litigation Experts and the Guide to the World’s Leading Patent Law Experts. He is the privacy and data protection columnist for the New York Law Journal, co-author of a book on privacy law and has been quoted in The Economist magazine as an expert on IP law. His articles have been used at Harvard and other law schools. He graduated from Brown University (degree with highest honors and Phi Beta Kappa) and Cornell Law School. 60758855.pptx 27
    28. 28. Chicago . Frankfurt . London . Los Angeles . New York . Palo Alto . Shanghai . Washington DC . West Palm Beach Copyright ©2011 by Kaye Scholer LLP. All Rights Reserved. This publication is intended as a general guide only. It does not contain a general legal analysis or constitute an opinion of Kaye Scholer LLP or any member of the firm on legal issues described. It is recommended that readers not rely on this general guide in structuring individual transactions but that professional advice be sought in connection with individual transactions. References herein to “Kaye Scholer LLP & Affiliates,” “Kaye Scholer,” “Kaye Scholer LLP,” “the firm” and terms of similar import refer to Kaye Scholer LLP and its affiliates operating in various jurisdictions.