“Data Privacy can unlock innovation and revenue
for your organization.
But you need to tear down the roadblocks
that encumber your access.”
– Luk Arbuckle, Chief Methodologist, Privacy Analytics Inc.
At the 2018 MIT CDOIQ Symposium – Exploiting Data Capital for Organizational Performance, Privacy Analytics’ Chief Methodologist Luk Arbuckle and Andrew B. Lambert MBA, Vice President Sales, Marketing and Business Development, addressed big data thought leaders, including those in the emerging role of Chief Data Officers.
Privacy Analytics’ presentation “Privacy Is A Roadblock: Tear It Down!”, delivered by Mr. Arbuckle and Mr. Lambert, and their insights gathered during the symposium, are available in an on demand webcast [CLICK HERE].
As Mr. Arbuckle, co-author of Anonymizing Health Data: Case Studies and Methods to Get You Started (O’Reilly Media, 2013) notes, “CDOs know their organizations need to prove they can manage the risk of using their data, not only for monetization, but for the public good. Privacy is seen as a roadblock. This perception is getting in the way of your business. To tear down the privacy roadblock, maintain your competitive edge and unlock the full value of your data trove, you need unencumbered access. De-identification speaks directly to these problems, delivering win-win solutions that reduce regulatory risk while increasing security, harmonizing data assets, and driving innovation.”
Having developed its technologies in rigorous academic and healthcare environments, Privacy Analytics’ expertise, commercial solutions and services have been leveraged beyond the health care space by cross-functional enterprises in a variety of business sectors including workforce automation, telecommunications and consumer credit.
Hot topics such as the impact of big data on the bottom line, and the urgency for organizations to transform themselves, have been examined in ‘must-read’ articles by leading analysts such as Gartner Group and McKinsey & Company.
But how will CDOs justify the investment in Data Privacy Best Practice? What roadblocks must they identify within their own ranks? What action must they take? What factors determine success or failure? These questions are just a few of the many are raised in this webinar. And the answers are complex.
Andrew Lambert observes, “Future-facing companies are using data to reshape a hyper-competitive business landscape. The task of de-identification while maintaining the public’s trust is getting tougher. Changes in regulatory policy, such as GDPR, are affecting how personal information can be accessed and re-purposed. Today, privacy is the ‘cousin’ of data. Personal information, and sensitive information, are the core asset. Protecting these while leveraging these, is the core issue.”
To access the webcast, register by clicking HERE.
PRIVACY IS A ROADBLOCK: TEAR IT DOWN!
What you will learn in this presentation:
- How leading companies drive business outcomes in key contexts through intelligent privacy design, and how these innovations promote excellence
- Why privacy roadblocks must be identified to measure the full value of data, and enable it to become revenue-positive
- Case studies: how risk-based expert determination methodology has helped enable organizations unlock the full value of their data trove, while assuring the highest level of security through data anonymization
RECOMMENDED READING: PRIVACY ANALYTICS’ CASE STUDIES
Case Study One: diversified global organization
A $30B global company generating massive data (50+ tables, 40-150GB, plans for 3-5 TB) needed to unlock value from medical claims datasets while protecting privacy and complying with regulations.
Case Study Two: workforce automation
A leading human resources data analytics company providing talent recruiting solutions to 10,000 professional partners in 150+ countries, needed to anonymize and preserve its data assets which were threatened by imminent changes in privacy legislation.
Case Study Three: financial technology
A leading data aggregation platform partnering with over 1,000 financial institutions and financial technology innovators manages a massive data network associated with tens of millions of consumers using platform-related personalized apps and services. This organization required data evaluation to assess leakage issues.
Case Study Four: telecommunications + mobility
A leading national telecommunications provider required expert advice on how to productize its customer data while protecting the privacy of its subscribers.
Case Study Five: personal health information
A healthcare analytic solutions and services company focused on improving support systems for health plans, hospitals, integrated delivery networks, physician practices and employers engaged in value-based arrangements, needed to better identify and manage risk, utilization and costs.
Case Study Six: global pharmaceutical
One of the world’s largest pharmaceutical multinationals wished to establish benchmarks via the deployment of a third-party re-identification attack on a Clinical Study Report (CSR); and subsequently anonymize the data to meet and exceed standards defined by the European Medicines Agency (EMA) Policy 70 document releases.
Case Study Seven: consumer credit
One of the ‘big three’ global consumer credit reporting agencies, which aggregates information on over a billion consumers, sought to maximize their data utility from specific line item individual files to further the agency’s engagement with its partners in banking, mortgage and institutional lending.
Privacy Analytics offers risk-based de-identification & anonymization solutions compliant with GDPR, HIPAA and other global regulations. Visit us on the web: www.privacy-analytics.com
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