Relativity Highlights Its X1 Integration for ESI Collection

By John Patzakis

Recently, Relativity hosted a live webinar featuring the integration of the X1 Distributed Discovery platform with its RelativityOne Collect solution. This X1/Relativity integration enables game-changing efficiencies in the eDiscovery process by accelerating speed to review, and providing an end-to-end process from identification through production. As stated by Relativity Chief Product Officer Chris Brown: “Our exciting new partnership with X1 highlights our continued commitment to providing a streamlined user experience from collection to production…RelativityOne users will be able to combine X1’s innovative endpoint technology with the performance of our SaaS platform, eliminating the cumbersome process of manual data hand-offs and allowing them to get to the pertinent data in their case – faster.”

The webinar featured a live demonstration showing X1 quickly collecting data across multiple custodians and seamlessly importing that data into RelativityOne in minutes. Relativity Collect currently supports Office 365 and Slack sources, and Relativity Product Manager Greg Evans noted that “this X1 integration will now enable Relativity Collect to also reach emails and files on laptops, servers,” and other network sources. The webinar outlined how the Relativity/X1 integration streamlines eDiscovery processes by collapsing the many hand-offs built into current EDRM workflows to provide greater speed and defensibility. Evans also said that new normal of web-enabled collections of remote custodians and data sources was a major driver for the Relativity/X1 alliance, as “remote collections now represent 90 percent of all eDiscovery collections happening right now.”

Adam Rogers, of Complete Discovery Source, a customer of both X1 and RelativityOne, highlighted a recent major multi-national litigation where the X1 and Relativity integration was critical to the success of the project. Adam noted that the effort would have taken about 30 days utilizing traditional methods, “but with this X1 and Relativity integration, we cut it down to 3 days, because with X1, we were able to index everything in-place, search, analyze and categorize that data right away, and then release that data to Relativity for review.”

The live demonstration performed by Greg Evans highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted and efficient search and collection process, with immediate pre-collection visibility into custodial data. X1 Distributed Discovery enhances the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection.

The X1 and Relativity integration addresses several pain points in the existing eDiscovery process. For one, there is currently an inability to quickly and remotely search across and access distributed unstructured data in-place, meaning eDiscovery teams have to spend weeks or even months to collect data as required by other cumbersome solutions. Additionally, using ESI processing methods that involve appliances that are not integrated with the collection will significantly increase cost and time delays.

So in terms of the big picture, with this integration providing a complete platform for efficient data search, eDiscovery and review across the enterprise, organizations will save a lot of time, save a lot of money, and be able to make faster and better decisions. When you accelerate the speed to review and eliminate over-collection, you are going to have much better early insight into your data and increase efficiencies on many levels.

A recording of the X1/Relativity integration webinar can be accessed here.

Leave a comment

Filed under Best Practices, collection, ECA, eDiscovery, Enterprise eDiscovery, ESI

A New Framework for Defining and Approaching Information Governance

By Michael Rasmussen

Editor’s note: Today we are featuring a guest blog post from Michael Rasmussen, the GRC Pundit & Analyst at GRC 20/20 Research, LLC.

Information governance has become a critical objective for organizations. In the context of the pervasive use of information throughout the enterprise, operational reliance on information, and increased regulation and liability of information, organizations are building structured approaches to information governance. This is to ensure the proper collection, use, and control of sensitive information – intellectual property, proprietary information, regulated data, personal information – across the organizations. Privacy regulations such as the California Consumer Protection Act (CCPA) and the EU Global Data Protection Regulation (GDPR) are making information governance even a greater priority.

Over the years we have seen a lot of definitions for ‘Information Governance.’ From the straightforward, like the Information Governance Initiatives:

  • “Information governance is the activities and technologies that organizations employ to maximize the value of their information while minimizing associated risks and costs.”

To the more complex, like Gartner’s:

  • “The specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival and deletion of information. It includes the processes, roles, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.”

However, both of these definitions do not quite deliver a clear understanding to the business on what information governance is. One is too light, the other too complex.

I am proposing a new definition for information governance which is a modification of the official definition of GRC (governance, risk management, and compliance) by the Open Compliance and Ethics Group (OCEG) . . .

  • Information governance is a capability to reliably achieve the objectives, while addressing uncertainty, and act with integrity in the collection, creation, use, storage, and disposition of information throughout the organization and its extended business relationships.

Information governance is essentially what we could call Information GRC. It starts with governance being the capability to reliably achieve objectives of information. After all, information is collected and stored for a purpose. In this context, the organization needs to manage the uncertainty to this information (risk and exposure) throughout its lifecycle. Finally, the organization needs to act with integrity to ensure the information is used for it authorized and intended purposes and not misused. However, the modern organization is not about brick and mortar wall but involves an extended array of third-party relationships that interact with that information as well and information governance extends across traditional business boundaries and into these third-party relationships as well.

What needs to change is more than a definition, but also the framework and process of information governance. Reactive, manual, and ad hoc approaches to information governances result in the inevitability of failure and exposure of information. Organizations need a cohesive information governance strategy, process, and supporting technology architecture to govern and manage the lifecycle of information.

Technology plays a critical role in enabling information governance in this vision. The right technology should make the organization more:

  • Efficient in the human and financial capital resources to monitor and manage information.
  • Effective in the proper cataloging, monitoring, control, disposition, and meeting legal and regulatory requirements of information.
  • Agile in the ability to keep up with information governance in the context of business, regulatory, legal, and risk changes.
  • Visible where access and understanding of information and data is and how it is used.
  • Consistent where the information source is understood and those that can access, manipulate it, and use to ensure its integrity.
  • Available where the information is accessible to those that are authorized to use it when they need it.

The foundational step to information governance is discovery. Organizations need to know where their data is and from there, they can control it and take action on it. A critical element needed is the ability to access the data and analyze the data in-place wherever it resides so the organization can then take action on it. This allows the organization to act on any given use-case to the information (e.g., internal policy, data audit and regulatory adherence). To be able to access, analyze and act on data in-place provides immediate insight into critical information empowering faster decisions and resolutions. It also empowers information governance teams to respond to eDiscovery collections as well as data audit and compliance initiatives quickly and effectively.

Leave a comment

Filed under Uncategorized

Compelling Case Study for Remote eDiscovery Collection in a High-Stakes Litigation

By John Patzakis

While our personal and business lives will hopefully return to normal soon, the trend of an increasingly remote and distributed workforce is here to stay. This “new normal” necessitates updated workflows enabled by the latest technology to comply with legal, privacy, and information governance requirements.

We have all sat in on many COVID-themed webinars and read just as many articles and blog posts discussing the new challenges in the abstract. But Mark Anderson, UK Director of Complete Discovery Source, recently provided welcome actual insight with a case study from the field on how he and his firm addressed remote collection challenges in a high-stakes multi-national litigation involving approximately 100 custodians and data sources spanning several countries.

Speaking in a live webinar, Anderson first noted that the legacy manual collection workflow involving travel, physical access and one-time mass collection of custodian laptops, file servers and email accounts was a non-starter going forward, given the high cost and logistical challenges under the new normal of remote workforces, current travel restrictions, and social distancing. According to Anderson, in previous cases “it was very difficult and very expensive to be on site that long to travel to those locations, to be very intrusive to a business, all for collecting data in an eDiscovery case.”

For CDS Legal’s recent major litigation matter, three key priorities needed to be addressed: 1) Gaining insight to the data to determine its potential relevance, which had to be determined remotely prior to collection; 2) Addressing privacy considerations pre-collection as the custodians were EU residents, and; 3) Collecting the data remotely and transmitting it directly from the endpoints to a load file or review platform.

Anderson noted that X1 Distributed Discovery, which is specially designed to search, analyze and collect data from remote and dispersed workforces and data sources, uniquely fulfilled these requirements. To enable early data insight, Anderson said that X1 indexed many terabytes of client data remotely and in place behind the client’s firewall, which “allowed us to search those indexes remotely very quickly, very effectively and very easily.”

For the very important privacy review requirement, Anderson reported that “By using X1, we were able to push the (search results) to the client on the machines that did the indexing and allowed them to review the data and flag it for release to us, so that we could collect it to a central location.” Anderson recounted how before using X1, CDS Legal would have to employ a much more time-consuming and cumbersome workflow, involving manual over-collection of data and then temporary installing a review platform on site, and having the client conduct their own review of a much larger subset of documents and emails with their own ad hoc searches.

For the final collection step, Anderson said that the targeted and privacy-reviewed client data transfer was effectuated with X1 remotely in an automated manner. Anderson also lauded X1’s ability to upload data straight into Relativity as being a “real time saver,” that is “a cleaner workflow in terms of the direct connection to Relativity rather than the manpower needed to transfer data.”

A recorded copy of the 30-minute webinar featuring Complete Discovery Sources’ case study can be accessed here.

X1 Distributed Discovery (X1DD) enables enterprises to quickly and easily search across up to 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. The key to X1’s scalability and remote collection capabilities is its unique ability to index and search data in place, thereby enabling a highly detailed and iterative search and analysis, and then only collecting data responsive to those steps. To learn more about this capability purpose-built for remote eDiscovery collection and data audits, please contact us.

Leave a comment

Filed under Uncategorized

Facebook Download Your Information Function Omits Significant Amounts of Evidence

By John Patzakis and Brent Botta

Facebook provides a “Download Your Information” (“DYI”) function to allow users to download to their computer data they have posted to their own accounts. The output is in the form of a compressed ZIP file.  But is DYI useful or defensible for eDiscovery?

In making that assessment it is important to understand that the following key information is not included in Facebook’s DYI:

  1. The only content that is collected using DYI is what the user posts or comments. Comments to user’s post, as well as posts and comments the user responds to are excluded. As such, the collected portion of the conversation is one-sided with no context available to understand the conversation.
  2. The one-sided posts and comments that are collected are not structured by conversation – they are arranged by date of each individual post or comment. As such, DYI intermingles posts and comments from different conversations, thereby stripping out the context to each actual conversation.
  3. Facebook DYI omits Most Metadata Fields. Facebook contains over 20 unique metadata fields, all of which can be very important as substantive evidence or as information that helps establish an evidentiary foundation, which is particularly important for social media evidence. 

In contrast, X1 Social Discovery (“X1SD”), the leading software used by several hundred law firms, government regulatory agencies and litigation support consultants world-wide for the preservation, analysis and authentication of social media and other internet-based evidence. X1SD aggregates comprehensive social media content and web-based data into a single user interface, while preserving critical metadata, all inline comments, and other user interactions not possible through image capture “screenshot,” simple computer screen printouts or the Facebook Download Your Information (“DYI”) functionality.

One of the many benefits of X1SD is the comprehensive nature in which it collects and displays Facebook ESI. With X1SD, you can collect, preserve and review what a custodian posted, received and responded to. You can also see all the comments from other users in response to a post made by a custodian. Another of the key advantages of X1SD is its ability to preserve the parent child relationship within comments and posts which maintains the critical context and meaning to the content. This preservation is kept intact through the export process. This is opposed to the DYI method that breaks apart comments and posts and lists the Facebook ESI in a manner that prohibits the ability to associate the comments and posts with one another.

For instance, below is a screenshot of a DYI export of a comment to a post by the user illustrating its very limited context and exclusion of all other comments made by others in the conversation and other key information, such as metadata. The DYI export does not even provide the original post to which the user’s comment is made.

In contrast to Facebook DYI, an X1SD collection will include the entire conversation, associated images, and metadata associated with the post. A hash value of each item is generated at the time of collection to better facilitate evidentiary authentication.  Furthermore, the output can be delivered in a load file that is of the exact same format as the timeline collections to ensure ease of uploading for the downstream review platforms. Below is a screenshot of an X1SD export with the same comment but with a much fuller context, including the actual original post being commented on, the full conversation thread, and other important additional potential evidence:

The Sedona Conference noted these limitations with Facebook DYI, including its omission of key metadata and other evidence in its recent publication  The Sedona Conference, Primer on Social Media, Second Edition, 20 Sedona Conf. J. 1 (2019)(at pp 47-48). In the same section, the Sedona Conference recommends X1 Social Discovery, stating: “One of the popular social media discovery collection tools is X1 Social Discovery, which has API collection tools for Facebook, Twitter, YouTube, Instagram, and Tumblr, along with the capability to collect webpages and email from other providers.” (at pg. 49).

To test this for yourself, you can request a free trial of X1 Social Discovery here.

Leave a comment

Filed under Uncategorized

Microsoft Breaks Search For Office 365

By John Patzakis

Last weeks’ guest blog post by Office 365 expert and independent consultant Bruce Berls clearly outlined why Windows search effectively does not work for business productivity search. Berls, from his testing, noted “I can’t find any OneDrive files when I do a search in Windows” and that any search results were “wildly inconsistent.”

Berls points out that “Microsoft has a vision of grand unified searches that return results from your own files and email, plus results from a wide variety of other places – the web, company documents, other people’s calendars, the contents of books you intend to read but haven’t gotten to yet, your senior thesis…Basically when you do a search, Microsoft will check the entire output of Western civilization and use smart AI to show you search results that are exactly what you want, whether you want them or not.”

And therein lies the problem.

In addition to being very buggy and slow, Microsoft has misapplied big data analytics to try and address business productivity search. That is a major mistake. Big data AI tools can deliver some useful business intelligence to those who are managing structured processes, and every major company has deployed some kind of AI process. But every company still has the problem of business workers not being able to find their information for productivity purposes. That is because the human brain is the most powerful analytical engine for business productivity search, and most search solutions do not effectively leverage this power. Windows O365 utilizes algorithms that try to predict things like document taxonomy classifications.  That can be useful for specific use cases, but not to enable business productively search, because AI-based search results are largely a cacophony of mostly unwanted information and “insights” that only frustrates the user.

When a knowledge professional performs a business productivity search, they generally have an idea of what they are looking for. They may be searching for a sales proposal from two years ago, a PowerPoint discussing GDPR compliance, or an email sent to the CFO last month with a proposed budget in a spreadsheet attachment.  For these very common, in fact hourly, use cases, a search solution with a user-friendly interface that allows humans to use their institutional business memory recall to iteratively search and filter through their information assets is needed. Business productivity search is not big data analytics and it is not web retrieval. It is its own use case with a workflow and interface that is tailored to the end users.

X1 Search provides the end-user with a powerful yet user-friendly and iterative means to quickly retrieve their business documents and emails using their own memory recall as opposed to generic algorithms that generate false positives and a workflow ill-suited to business productivity search. This analysis is crystalized in the accompanying chart differentiating X1’s approach to business productivity search versus big data analytics and web search.

These points are further mentioned in this testimonial from recent Nobel Prize Winner in Chemistry and Stanford professor Dr. Michael Levitt, who states: “X1 is an intimate part of my workflow — it is essentially an extension of my mind when I engage in information retrieval, which is many times an hour during my workday.” In my opinion, you will not find that level of enthusiasm by end-users for other enterprise search platforms.

Given these requirements, X1 emerges as the best choice for a business productivity search solution. The X1 Search interface is award-winning and beloved by users (try finding users that love traditional enterprise search). Business professionals can search emails, files, OneDrive SharePoint, and the other content, whether local or in Office 365, that they need to do their jobs in a single-pane-of-glass interface that enables post-search actions. Directly in the UI, users can respond to emails, for example, or forward OneDrive documents. With this kind of user interface, business workers can use their business memory recall and intuition to quickly find information. They can instantaneously filter and preview directly in the UI, providing an iterative search process, making it possible to find that critical document in a matter of seconds. And you can try X1 Search via a free trial.

Leave a comment

Filed under Uncategorized