New Study: Only 22 Percent of Information Management Professionals Confident in their Organization’s Approach to Privacy
Nov 15, 2018
Results reflect widespread concerns with new privacy regulations
MILPITAS, Calif., Nov. 15, 2018 (GLOBE NEWSWIRE) -- ZL Technologies, Inc. (ZL), a leader in information governance, today released the results of a new survey which found that information management professionals are overwhelmingly unconfident in their organization’s approach to privacy and information management.
The survey was conducted in partnership with the MER Conference, an organization renowned for addressing the legal, technical and operational issues of managing electronic records. Information management professionals were polled in August through October of 2018, with respondents spanning several verticals, including: education, energy, finance, government, legal, pharmaceutical, and transportation industries. The job titles of respondents included Information Governance Analyst, Records Manager, Compliance Specialist, Director of Information Management, and Vice President of Data Governance.
Respondents were polled with the simple question: “Do you think executives in your organization have sufficiently addressed information management and privacy needs?” 59.9 percent of the respondents said “no,” 18.6 percent said they were “unsure,” and only 21.5 percent said “yes.” These findings are potentially cause for concern, particularly considering they reflect the opinions of professionals with deep insight into their organization’s information management strategies.
“The siloed nature of today’s IT architecture renders many organizations unprepared for compliance with new privacy regulations,” said Kon Leong, CEO, ZL Technologies. “We’re seeing more and more IT and information management professionals come to terms with that, as reflected by these findings.”
To assess an organization’s level of preparedness for new regulations, Leong suggested asking the following questions:
- What types of searches would you execute to find the various types of personal data that exist in most organizations?
- Could you efficiently and consistently perform searches across the enterprise, including data silos that use different engines?
- How would you readily associate personal data with the data subject?
- When assessing whether to delete personal data, how would you quickly check its other functions, including “legitimate interests” that would prohibit its deletion?
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