Category Archives: Information Management

CCPA and GDPR UPDATE: Unstructured Enterprise Data in Scope of Compliance Requirements

An earlier version of this article appeared on Legaltech News

By John Patzakis

A core requirement of both the GDPR and the similar California Consumer Privacy Act (CCPA), which becomes enforceable on July 1, is the ability to demonstrate and prove that personal data is being protected. This requires information governance capabilities that allow companies to efficiently identify and remediate personal data of EU and California residents. For instance, the UK Information Commissioner’s Office (ICO) provides that “The GDPR places a high expectation on you to provide information in response to a SAR (Subject Access Request). Whilst it may be challenging, you should make extensive efforts to find and retrieve the requested information.”CCPA GDPR

However, recent Gartner research notes that approximately 80% of information stored by companies is “dark data” that is in the form of unstructured, distributed data that can pose significant legal and operational risks. With much of the global workforce now working remotely, this is of special concern and nearly all the company data maintained and utilized by remote employees is in the form of unstructured data. Unstructured enterprise data generally refers to searchable data such as emails, spreadsheets and documents on laptops, file servers, and social media.

The GDPR

An organization’s GDPR compliance efforts need to address any personal data contained within unstructured electronic data throughout the enterprise, as well as the structured data found in CRM, ERP and various centralized records management systems. Personal data is defined in the GDPR as: “any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person.”

Under the GDPR, there is no distinction between structured versus unstructured electronic data in terms of the regulation’s scope. There is a separate guidance regarding “structured” paper records (more on that below). The key consideration is whether a data controller or processor has control over personal data, regardless of where it is located in the organization. Nonetheless, there is some confusion about the scope of the GDPR’s coverage across structured as well as unstructured electronic data systems.

The UK ICO is a key government regulator that interprets and enforces the GDPR, and has recently issued important draft guidance on the scope of GDPR data subject access rights, including as it relates to unstructured electronic information. Notably, the ICO notes that large data sets, including data analytics outputs and unstructured data volumes, “could make it more difficult for you to meet your obligations under the right of access. However, these are not classed as exemptions, and are not excuses for you to disregard those obligations.”

Additionally the ICO guidance advises that “emails stored on your computer are a form of electronic record to which the general principles (under the GDPR) apply.” In fact, the ICO notes that home computers and personal email accounts of employees are subject to GDPR if they contain personal data originating from the employers networks or processing activities. This is especially notable under the new normal of social distancing, where much of a company’s data (and associated personal information) is being stored on remote employee laptops.

The ICO also provides guidance on several related subjects that shed light on its stance regarding unstructured data:

Archived Data: According to the ICO, data stored in electronic archives is generally subject to the GDPR, noting that there is no “technology exemption” from the right of access. Enterprises “should have procedures in place to find and retrieve personal data that has been electronically archived or backed up.” Further, enterprises “should use the same effort to find information to respond to a SAR as you would to find archived or backed-up data for your own purposes.”

Deleted Data: The ICO’s view on deleted data is that it is generally within the scope of GDPR compliance, provided that there is no intent to, or a systematic ability to readily recover that data. The ICO says it “will not seek to take enforcement action against an organisation that has failed to use extreme measures to recreate previously ‘deleted’ personal data held in electronic form. We do not require organisations to use time and effort reconstituting information that they have deleted as part of their general records management.”

However, under this guidance organizations that invest in and deploy re-purposed computer forensic tools that feature automated un-delete capabilities may be held to a higher standard. Deploying such systems can reflect intent to as well as having the systematic technical ability to recover deleted data.

Paper Records: Paper records that are part of a “structured filing system” are subject to the GDPR. Specifically, if an enterprise holds “information about the requester in non-electronic form (e.g. in paper files or on microfiche records)” then such hard-copy records are considered personal data accessible via the right of access,” if such records are “held in a ‘filing system.” This segment of the guidance reflects that references to “unstructured data” in European parlance usually pertains to paper records. The ICO notes in separate guidance that “the manual processing of unstructured personal data, such as unfiled handwritten notes on paper” are outside the scope of GDPR.

GDPR Article 4 defines a “filing system” as meaning “any structured set of personal data which are accessible according to specific criteria, whether centralized, decentralized or dispersed on a functional or geographical basis.” The only form of “unstructured data” that would not be subject to GDPR would be unfiled paper records like handwritten notes or legacy microfiche.

The CCPA  

The California Attorney General (AG) released a second and presumably final round of draft regulations under the California Consumer Privacy Act (CCPA) that reflect how unstructured electronic data will be treated under the Act. The proposed rules outline how the California AG is interpreting and will be enforcing the CCPA. Under § 999.313(d)(2), data from archived or backup systems are—unlike the GDPR—exempt from the CCPA’s scope, unless those archives are restored and become active. Additional guidance from the Attorney General states: “Allowing businesses to delete the consumer’s personal information on archived or backup systems at the time that they are accessed or used balances the interests of consumers with the potentially burdensome costs of deleting information from backup systems that may never be utilized.”

What is very notable is that the only technical exception to the CCPA is unrestored archived and back-up data. Like the GDPR, there is no distinction between unstructured and structured electronic data. In the first round of public comments, an insurance industry lobbying group argued that unstructured data be exempted from the CCPA. As reflected by revised guidance, that suggestion was rejected by the California AG.

For the GDPR, the UK ICO correctly advises that enterprises “should ensure that your information management systems are well-designed and maintained, so you can efficiently locate and extract information requested by the data subjects whose personal data you process and redact third party data where it is deemed necessary.” This is why Forrester Research notes that “Data Discovery and Classification are the foundation for GDPR compliance.”

Establish and Enforce Data Privacy Policies

So to achieve GDPR and CCPA compliance, organizations must first ensure that explicit policies and procedures are in place for handling personal information. Once established, it is important to demonstrate to regulators that such policies and procedures are being followed and operationally enforced. A key first step is to establish a data map of where and how personal data is stored in the enterprise. This exercise is actually required under the GDPR Article 30 documentation provisions.

An operational data audit and discovery capability across unstructured data sources allows enterprises to efficiently map, identify, and remediate personal information in order to respond to regulators and data subject access requests from EU and California citizens. This capability must be able to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of weeks or months as is the case with traditional crawling tools. This includes laptops of employees working from home.

These processes and capabilities are not only required for data privacy compliance but are also needed for broader information governance and security requirements, anti-fraud compliance, and e-discovery.

Implementing these measures proactively, with routine and consistent enforcement using solutions such as X1 Distributed GRC, will go a long way to mitigate risk, respond efficiently to data subject access requests, and improve overall operational effectiveness through such overall information governance improvements.

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Three Key eDiscovery Preservation Lessons from Small v. University Medical Center

Small v. University Medical Center is a recent 123-page decision focused exclusively on issues and challenges related to preservation of electronically stored information in a large enterprise. Its an important ESI preservation case with some very instructive takeaways for organizations and their counsel.  In Small, Plaintiffs brought an employment wage & hour class action against University Medical Center of Southern Nevada (UMC). Such wage & hour employment matters invariably involve intensive eDiscovery, and this case was no exception. When it became evident that UMC was struggling mightily with their ESI preservation and collection obligations, the Nevada District Court appointed a special master, who proved to be tech-savvy with a solid understanding of eDiscovery issues.Case Law

In August 2014, the special master issued a report, finding that UMC’s destruction of relevant information “shock[ed] the conscious.” Among other things, the special master recommended that the court impose a terminating sanction in favor of the class action plaintiffs. The findings of the special master included the following:

  • UMC had no policy for issuing litigation holds, and no such hold was issued for at least the first eight months of this litigation.
  • UMC executives were unaware of their preservation duties, ignoring them altogether, or at best addressing them “in a hallway in passing.”
  • Relevant ESI from laptops, desktops and local drives were not preserved until some 18 months into this litigation.
  • ESI on file servers containing policies and procedures regarding meal breaks and compensation were not preserved.
  • These issues could have been avoided using best practices and if chain-of-custody paperwork had been completed.
  • All of UMC’s multiple ESI vendors repeatedly failed to follow best practices

After several years of considering and reviewing the special master’s detailed report and recommendations, the court finally issued its final discovery order last month. The court concurred with the special master’s findings, holding that UMC and its counsel failed to take reasonable efforts to identify, preserve, collect, and produce relevant information. The court imposed monetary sanctions against UMC, including the attorney fees and costs incurred by opposing counsel. Additionally, the court ordered that should the matter proceed to trial, the jury would be instructed that “the court has found UMC failed to comply with its legal duty to preserve discoverable information… and failed to comply with a number of the court’s orders,” and that “these failures resulted in the loss or destruction of some ESI relevant to the parties’ claims and defenses and responsive to plaintiffs’ discovery requests, and that the jury may consider these findings with all other evidence in the case for whatever value it deems appropriate.” Such adverse inference instructions are invariably highly impactful if not effectively dispositive in a jury trial.

There are three key takeaways from Small:

  1. UMC’s Main Failing was Lacking an Established Process

UMC’s challenges all centered on its complete lack of an existing process to address eDiscovery preservation. UMC and their counsel could not identify the locations of potentially relevant ESI because there was no data map. ESI was not timely preserved because no litigation hold process existed. And when the collection did finally occur under the special master’s order, it was highly reactive and very haphazard because UMC had no enterprise-capable collection capability.

When an organization does not have a systematic and repeatable process in place, the risks and costs associated with eDiscovery increase exponentially. Such a failure also puts outside counsel in a very difficult situation, as reflected by this statement from the Small Court: “One of the most astonishing assertions UMC made in its objection to the special master’s R & R is that UMC did not know what to preserve. UMC and its counsel had a legal duty to figure this out. Collection and preservation of ESI is often an iterative process between the attorney and the client.”

Some commentators have focused on the need to conduct custodian questionnaires, but a good process will obviate or at least reduce your reliance on often unreliable custodians to locate potentially relevant ESI.

  1. UMC Claims of Burden Did Not Help Their Cause

UMC tried arguing that it was too burdensome and costly for them to collect ESI from hundreds of custodians, claiming that it took IT six hours to merely search the email account of a single custodian. Here at X1, I wear a couple of hats, including compliance and eDiscovery counsel. In response to a recent GDPR audit, we searched dozens of our email accounts in seconds. This capability not only dramatically reduces our costs, but also our risk by allowing us to demonstrate diligent compliance.

In the eDiscovery context, the ability to quickly pinpoint potentially responsive data enables corporate counsel to better represent their client. For instance, they are then able to intelligently negotiate keywords and overall preservation scope with opposing counsel, instead of flying blind. Also, with their eDiscovery house in order, they can focus on more strategic priorities in the case, including pressing the adversary on their discovery compliance, with the confidence that your client does not live in a glass house.

Conversely, the Small opinion documents several meet and confer meetings and discovery hearings where UMC’s counsel was clearly at a significant disadvantage, and progressively lost credibility with the court because they didn’t know what they didn’t know.

  1. Retaining Computer Forensics Consultants Late in the Game Did Not Save the Day

Eventually UMC retained forensic collection consultants several months after the duty to preserve kicked in. This reflects an old school reactive, “drag the feet” approach some organizations still take, where they try to deflect preservation obligations and then, once opposing counsel or the court force the issue, scramble and retain forensic consultants to parachute in.  In this situation it was already too late, as much the data had already been spoliated. And because of the lack of a process, including a data map, the collection efforts were disjointed and a haphazard. The opinion also reflects that this reactive fire drill resulted in significant data over-collection at significant cost to UMC.

In sum, Small v. University Medical Center is a 123 page illustration of what often happens when an organization does not have a systematic eDiscovery process in place. An effective process is established through the right people, processes and technology, such as the capabilities of the X1 Distributed Discovery platform. A complete copy of the court opinion can be accessed here: Small v. University Medical Center

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When your “Compliance” and eDiscovery Processes Violate the GDPR

Time to reevaluate tools that rely on systemic data duplication

The European Union (EU) General Data Protection Regulation (GDPR) became effective in May 2018. To briefly review, the GDPR applies to the processing of “personal data” of EU citizens and residents (a.k.a. “data subjects”).” Personal data” is broadly defined to include “any information relating to an identified or identifiable natural person.” That could include email addresses and transactional business communications that are tied to a unique individual. GDPR is applicable to any organization that provides goods and services to individuals located in the EU on a regular enough basis, or maintains electronic records of their employees who are EU residents.

In additional to an overall framework of updated privacy policies and procedures, GDPR requires the ability to demonstrate and prove that personal data is being protected. Essential components for such compliance are data audit and discovery capabilities that allow companies to efficiently search and identify the information necessary, both proactively, and also reactively to respond to regulators and EU private citizen’s requests. As such, any GDPR compliance programs are ultimately hollow without consistent, operational execution and enforcement through an effective eDiscovery information governance platform.

However, some content management and archiving tool providers are repurposing their messaging with GDPR compliance. For example, an industry executive contact recently recounted a meeting with such a vendor, where their tool involved duplicating all of the emails and documents in the enterprise and then migrating all those copies to a central server cluster. That way, the tool could theoretically manage all the documents and emails centrally. Putting aside the difficulty of scaling up that process to manage and sync hundreds of terabytes of data in a medium-sized company (and petabytes in a Fortune 500), this anecdote underscores a fundamental flaw in tools that require systemic data duplication in order to search and manage content.

Under the GDPR, data needs to be minimized, not systematically duplicated en masse. It would be extremely difficult under such an architecture to sync up and remediate non-compliant documents and emails back at the original location. So at the end the day, this proposed solution would actually violate the GDPR by making duplicate copies of data sets that would inevitably include non-compliant information, without any real means to sync up remediation.Desktop_virtualization

The same is true for the much of the traditional eDiscovery workflows, which require numerous steps involving data duplication at every turn. For instance, data collection is often accomplished through misapplied forensic tools that operate by a broadly collecting copies through over collection. As the court said in In re Ford Motor Company, 345 F.3d 1315 (11th Cir. 2003): “[E]xamination of a hard drive inevitably results in the production of massive amounts of irrelevant, and perhaps privileged, information…” Even worse, the collected data is then re-duplicated one or often two more times by the examiner for archival purposes. And then the data is sent downstream for processing, which results in even more data duplication. Load files are created for further transfers, which are also duplicated.

Chad Jones of D4 explains on a recent webinar and in his follow-on blog post about how such manual and inefficient handoffs throughout the discovery process greatly increase risk as well as cost. Like antiquated factories spewing tons of pollution, outdated eDiscovery processes spin out a lot of superfluous data duplication. Much of that data likely contains non-compliant information, thus “polluting” your organization, including through your eDiscovery services vendors, with increased GDPR and other regulatory risk.

In light of the above, when evaluating your compliance and eDiscovery software, organizations should keep in mind these five key requirements to keep in line with GDPR and good overall information governance:

  1. Search data in place. Data on laptops and file servers need to be in searched in place. Tools that require copy and migration to central locations to search and manage are part of the problem, not the solution.
  1. Delete Data in Place. GDPR requires that non-compliance data be deleted on demand. Purging data on managed archives does not suffice if other copies are on laptops, unmanaged servers and other unstructured sources. Your search in place solution should also delete in place.
  1. Data Minimization. GDPR requires that organizations minimize data as opposed to exploding data through mass duplication.
  1. Targeted and Efficient Data Collection: Only potentially relevant data should be collected for eDiscovery and data audits. Over-collection leads to much greater cost and risk.
  1. Seamless integration with attorney review platforms, to bypass the processing steps which requires manual handoffs and load files.

X1 Data Audit & Compliance is a ground-breaking platform that meets these criterion while enabling system-wide data discovery supporting GDPR and many other information governance requirements.   Please visit here to learn more.

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Effective Information Governance Requires Effective Enterprise Technology

Information governance is the compilation of policies, processes, and controls enforced and executed with effective technology to manage electronically stored information throughout the enterprise. Leading IT industry research firm Gartner states that “the goal of information governance is to ensure compliance with laws and regulations, mitigate risks and protect the confidentiality of sensitive company and customer data.” A strong, proactive information governance strategy that strikes the balance between under-retention and over-retention of information can provide dramatic cost savings while significantly reducing risk.

However, while policies, procedures and documentation are important, information governance programs are ultimately hollow without consistent, operational execution and enforcement. CIOs and legal and compliance executives often aspire to implement information governance programs like defensible deletion, data migration, and data audits to detect risks and remediate non-compliance. However, without an actual and scalable technology platform to effectuate these goals, those aspirations remain just that. For instance, recent IDG research suggests that approximately 70% of information stored by companies is “dark data” that is in the form of unstructured, distributed data that can pose significant legal and operational risk and cost.

To date, organizations have employed limited technical approaches to try and execute on their information governance initiatives, enduring many struggles. For instance, software agent-based crawling methods are commonly attempted and can cause repeated high user computer resources utilization for each search initiated and network bandwidth limitations being pushed to the limits rendering the approach ineffective. So being able to search and audit across at least several hundred distributed end points in a repeatable and quick fashion is effectively impossible under this approach.

Another tactic attempted by some CIOs to attempt to address this daunting challenge is to periodically migrate disparate data from around the global enterprise into a central location. The execution of this strategy will still leave the end user’s computer needing to be scanned as there is never a moment when all users in the enterprise have just finished this process with no new data created. That means now that both the central repository and the end-points will need to be searched and increasing the complexity and management of the job. Boiling the ocean through data migration and centralization is extremely expensive, highly disruptive, and frankly unworkable as it never removes the need to conduct constant local computer searching, again through problematic crawling methods.

What has always been needed is gaining immediate visibility into unstructured distributed data across the enterprise, through the ability to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of days or weeks. None of the other approaches outlined above come close to meeting this requirement and in fact actually perpetuate information governance failures.

X1 Distributed Discovery (X1DD) represents a unique approach, by enabling enterprises to quickly and easily search across multiple distributed endpoints and data servers from a central location.  Legal and compliance teams can easily perform unified complex searches across both unstructured content and metadata, obtaining statistical insight into the data in minutes, instead of days or weeks. With X1DD, organizations can also automatically migrate, collect, or take other action on the data as a result of the search parameters.  Built on our award-winning and patented X1 Search technology, X1DD is the first product to offer true and massively scalable distributed searching that is executed in its entirety on the end-node computers for data audits across an organization. This game-changing capability vastly reduces costs while greatly mitigating risk and disruption to operations.

X1DD operates on-demand where your data currently resides — on desktops, laptops, servers, or even the Cloud — without disruption to business operations and without requiring extensive or complex hardware configurations. Beyond enterprise eDiscovery and information governance functionality, organizations offer employees at the same time, the award-winning X1 Search, improving productivity while effectuating that all too illusive actual compliance with information governance programs.

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True Enterprise-Wide eDiscovery Collection is Finally Here

My previous post discussed the inability of any software provider to solve a critical need by delivering a truly scalable eDiscovery preservation and collection solution that can search across thousands of enterprise endpoints in a short period of time. In the absence of such a “holy grail” solution, eDiscovery collection remains dominated by either unsupervised custodian self-collection or manual services, driving up costs while increasing risk and disruption to business operations.

So today, we at X1 are excited to announce the release of X1 Distributed Discovery. X1 Distributed Discovery (X1DD) enables enterprises to quickly and easily search across up to tens of thousands of distributed endpoints and data servers from a central location.  Legal and compliance teams can easily perform unified complex searches across both unstructured content and metadata, obtaining statistical insight into the data in minutes, and full results with completed collection in hours, instead of days or weeks. Built on our award-winning and patented X1 Search technology, X1DD is the first product to offer true and massively scalable distributed data discovery across an organization. X1DD replaces expensive, cumbersome and highly disruptive approaches to meet enterprise discovery, preservation, and collection needs.

x1dd_diagram

Enterprise eDiscovery collection remains a significant pain point, subjecting organizations to both substantial cost and risk. X1DD addresses this challenge by starting to show results from distributed data across global enterprises within minutes instead of today’s standard of weeks, and even months. This game-changing capability vastly reduces costs while greatly mitigating risk and disruption to operations.

Targeted and iterative end point search is a quantum leap in early data assessment, which is critical to legal counsel at the outset of any legal matter. However, under today’s industry standard, the legal team is typically kept in the dark for weeks, if not months, as the manual identification and collection process of distributed, unstructured data runs its expensive and inefficient course.  To illustrate the power and capabilities of X1DD, imagine being able to perform multiple detailed Boolean keyword phrase searches with metadata filters across the targeted end points of your global enterprise. The results start returning in minutes, with granular statistical data about the responsive documents and emails associated with specific custodians or groups of custodians.

Once the legal team is satisfied with a specific search string, after sufficient iteration, the data can then be collected by X1DD by simply hitting the “collect” button. The responsive data is “containerized” at each end point and automatically transmitted to a central location, where all data is seamlessly indexed and ready for further culling and first pass review. Importantly, all results are tied back to a specific custodian, with full chain of custody and preservation of all file metadata.

This effort described above — from iterative distributed search through collection, transmittal to a central location, and indexing of data from thousands of endpoints — can be accomplished in a single day. Using manual consulting services, the same project would require several weeks and hundreds of thousands of dollars in collection costs alone, not to mention significant disruption to business operations. Substantial costs associated with over-collection of data would mount as well.

X1DD operates on-demand where your data currently resides — on desktops, laptops, servers, or even the Cloud — without disruption to business operations and without requiring extensive or complex hardware configurations. Beyond enterprise eDiscovery and investigation functionality, organizations can offer employees the award-winning X1 Search, improving productivity while maintaining compliance.

X1DD will be featured in an April 19 webinar with eDiscovery expert Erik Laykin of Duff & Phelps. Watch a full briefing and technical demo of X1DD and find out for yourself why X1 Distributed Discovery is a game-changing solution. Or please contact us to arrange for a private demo.

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