Category Archives: Enterprise eDiscovery

Want Legal to Add A LOT More Value? Stop Over-Collecting Data

blog-cassting-net

The 2019 CLOC (Corporate Legal Operations Consortium) Conference ended last week, and by all accounts it was another great event for an organization that continues to gain relevance and momentum.  A story in Thursday’s Legaltech News entitled “Why E-discovery Savings Is About Department Value for Corporate Legal” summarized a CLOC session focused on “streamlining e-discovery and information governance inside corporate legal departments.”  At the risk of sounding biased, that seems like a perfect topic to me.

The article’s conclusions from the panel session, namely adding value by wresting control of eDiscovery from outside counsel, consolidating hosting vendors and creating a “living data map”, were all spot on and certainly useful.  One way for legal to add enormous value, however, was NOT discussed: collecting far less data as part of the eDiscovery, investigatory and compliance processes.

As we highlighted on an insightful webinar with our partner Compliance Discovery Solutions last Tuesday (which can be viewed here), the way most eDiscovery practitioners conduct ESI collection is remarkably unchanged from a decade ago, an example of which is shown in the infographic below: consult a data map, image entire drives from each and every custodian (e.g. with EnCase), load these many images into a processing application (e.g. Nuix), process these huge amounts of data (most of which is entirely irrelevant), then move this now-processed data into a review application (e.g. Relativity).

blog-legacy-collection-infographic

This legacy collection process for GRC (Governance, Risk & Compliance) and eDiscovery is wildly inefficient, disruptive to the business and costly, yet many if not most practitioners still use it, most likely because it’s the status quo and change is always hard in the legal technology world.  But change here is a must, as this “image everything à then process it all à and only then begin reviewing” workflow causes myriad issues not just for legal but for the company as well:

  • Increases eDiscovery costs exponentially. The still-seminal Rand study on eDiscovery pegged an overall cost-per-GB for identification through production of $1,800/GB.  While some elements of this price have come down in the intervening 6-7 years, especially processing and hosting rates, data volumes and variety have grown by at least as much thereby negating these reductions.  Imaging entire drives by definition collects far more data than could ever be relevant in any given matter – and the costs of this overcollection multiply every step thereafter, forcing clients to pay hundreds of thousands if not millions of dollars more than they should.
  • Is extremely disruptive to employees. Forensically imaging a drive usually requires gaining physical access to the laptop or desktop for some period of time, often for a day or two.  Put yourself in each of those employee’s shoes: even if you are given a “loaner” machine, you still don’t have all of your local information, settings, bookmarks, etc. – which is a major disruption to your work day and therefore a significant drag on productivity.
  • Takes far too long. With forensic imaging of drives requiring physical access to a device, each custodian’s machine must be dealt with.  In many collections, custodians are spread across multiple offices, or on vacation, or remote employees, which often extends the process to many weeks if not months.  All of this time lawyers are unable to access this critical data (e.g. to begin formulating case strategy, negotiating with opposing counsel or a regulator, etc).
  • Creates unnecessary copies of data that could otherwise be remediated. An often-overlooked byproduct of over-collection is that it creates another copy of data that is outside of most (if not all) data remediation programs.  For companies that are regulated and/or encounter litigation regularly, this becomes a major headache and undermines data governance and remediation programs.
  • Forces counsel to “fly blind” for months. Every day the IT and legal teams are spending forensically imaging each custodian’s drives, then processing it, and only then loading it into a review or analysis application is a day in-house and outside counsel are flying blind, unable to look at key data to begin constructing case strategy, conduct informed interviews, negotiate with opposing counsel (e.g. on the scope of a matter, including discovery) or interact with regulators.  This is incredibly valuable time lost for no value received in return.
  • Using forensic tools for non-forensic processes is unnecessary overkill. The irony of this “image everything” approach is that it is extreme overkill: it would be like a doctor whose only procedure to get rid of a mole was to cut off the arm.  Forensic images can always be utilized on a one-off basis in narrow circumstances where there are concerns about possible spoliation of evidence, but for the vast majority of circumstances, a forensic image is completely unnecessary.

As was a focus at the recent CLOC conference in Las Vegas, corporate legal operations are quite correctly focused on showing the value legal is bringing to the business.  However, there is still a fundamental change they need to make to how they handle the collection of ESI for eDiscovery, GRC and privacy purposes that would be an enormous value-add to all parts of the company, including legal: ending the systematic over-collection of data.  How this can be done quickly and cost-effectively has been the subject of previous blog posts, but will be addressed in detail in the next few weeks as well.

Leave a comment

Filed under Best Practices, collection, compliance, Data Audit, eDiscovery, Enterprise eDiscovery, Uncategorized

Government Regulators Reject “Paper” Corporate Compliance Programs Lacking Actual Enforcement

By John Patzakis

Recently, US Government regulators fined Stanley Black & Decker $1.8m after its subsidiary illegally exported finished power tools and spare parts to Iran, in violation of sanctions. The Government found that the tool maker failed to “implement procedures to monitor or audit [its subsidiary] operations to ensure that its Iran-related sales did not recur.”

Notably, the employees of the subsidiary concealed their activities by creating bogus bills of lading that misidentified delivery locations and told customers to avoid writing “Iran” on business documents. This conduct underscores the importance of having a diligent internal monitoring and investigation capability that goes beyond mere review of standard transactional records in structured databases such as CRM systems. This type of conduct is best detected on employee’s laptops and other sources of unstructured data through effective internal investigations processes.Law Journal2

The Treasury Department stated the Stanley Black & Decker case “highlights the importance of U.S. companies to conduct sanctions-related due diligence both prior and subsequent to mergers and acquisitions, and to take appropriate steps to audit, monitor and verify newly acquired subsidiaries and affiliates for….compliance.”

Further to this point, the US Department of Justice Manual features a dedicated section on assessing the effectiveness of corporate compliance programs in corporate fraud prosecutions, including FCPA matters. This section is a must read for any corporate compliance professional, as it provides detailed guidance on what the USDOJ looks for in assessing whether a corporation is committed to good-faith self-policing or is merely making hollow pronouncements and going through the motions.

The USDOJ cites United States v. Potter, 463 F.3d 9 (1st Cir. 2006), which provides that a corporation cannot “avoid liability by adopting abstract rules” that forbid its agents from engaging in illegal acts, because “[e]ven a specific directive to an agent or employee or honest efforts to police such rules do not automatically free the company for the wrongful acts of agents.” Id. at 25-26. See also United States v. Hilton Hotels Corp., 467 F.2d 1000, 1007 (9th Cir. 1972) (noting that a corporation “could not gain exculpation by issuing general instructions without undertaking to enforce those instructions by means commensurate with the obvious risks”).

The USDOJ manual advises prosecutors to determine if the corporate compliance program “is adequately designed for maximum effectiveness in preventing and detecting wrongdoing by employees and whether corporate management is enforcing the program or is tacitly encouraging or pressuring employees to engage in misconduct to achieve business objectives,” and that “[p]rosecutors should therefore attempt to determine whether a corporation’s compliance program is merely a ‘paper program’ or whether it was designed, implemented, reviewed, and revised, as appropriate, in an effective manner.”

With these mandates from government regulators for actual and effective monitoring and enforcement through internal investigations, organizations need effective and operational mechanisms for doing so. In particular, any anti-fraud and internal compliance program must have the ability to search and analyze unstructured electronic data, which is where much of the evidence of fraud and other policy violations can be best detected.

To help meet the “actual enforcement” requirements of government regulators, 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. 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 investigation, compliance, and eDiscovery requirements.

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 either a central location, or uploaded directly to Relativity, using Relativity’s import API where all data is seamlessly ready for review. Importantly, all results are tied back to a specific custodian, with full chain of custody and preservation of all file metadata. Here is a recording of a live public demo with Relativity, showing the very fast direct upload from X1DD straight into RelativityOne.

This effort described above — from iterative, distributed search through collection and transmittal straight into Relativity from hundreds 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, and could even dwarf collection costs through unnecessary attorney review time.

In addition to saving time and money, these capabilities are important demonstrate a sincere organizational commitment to compliance versus maintaining a mere “paper program.”

1 Comment

Filed under Best Practices, Case Law, Case Study, compliance, Corporations, eDiscovery & Compliance, Enterprise eDiscovery, Information Governance

In addition to TAR, CAR Can Dramatically Reduce Attorney Review Costs

eDiscovery efforts are often costly, time consuming and burdensome. The volume of Electronically Stored Information is growing exponentially and will only continue to do so. Even with the advent of technology assisted review (TAR), the costs associated with collecting, processing, reviewing, and producing documents in litigation are the source of considerable pain for litigants. The only way to reduce that pain to its minimum is to use all tools available in all appropriate circumstances within the bounds of reasonableness and proportionality to control the volumes of data that enter the discovery pipeline.

Litigators and commentators often pine for the advent of a systemized, uniform and defensible process for custodian self-collection. Conceptually, such an ideal process would be where custodians are automatically presented with a set of their documents and emails that are identified as potentially relevant to a given matter through a set of keywords and other search parameters that are uniformly applied across all custodians. This set of ESI would be presented to the custodian in a controlled interface with no ability to delete documents or emails, and only the ability to review and apply tags and annotations. The custodian would have to comply with the order and all documents responsive to the initial unified search would be collected as a default control mechanism.

With X1 Data Audit and Compliance (XDAC), the option for a defensible custodian assisted review (CAR) is now a reality. At a high level, with XDAC, organizations can perform targeted search and collection of the ESI of thousands of endpoints over the internal network without disrupting operations. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%), thereby bringing much needed feasibility to enterprise-wide eDiscovery collection that can save organizations millions while improving compliance. XDAC includes X1 Insight and Collection for pure eDiscovery use cases.

As a key optional feature, XDAC provides custodian assisted review, where custodians are presented with a listing of their potentially relevant ESI in a controlled, systemized and uniform identification process for their review and tagging. Instead of essentially asking the custodians to “please rummage through your entire email account and all your documents to look for what you might think is relevant to this matter,” the custodians are presented with a narrow and organized subset of potentially relevant ESI for their review.

screenshot

While the custodians are able to assist with the review, they cannot impact or control what ESI is identified and preserved; this is controlled and managed centrally by the eDiscovery practitioner. This way, custodians can apply their own insight to the information and even flag personal private data, all while effectuating very cost-effective and systematic ESI collection.

Powerful Analytics Engine

TAR features powerful algorithms that cluster documents and otherwise work their magic. CAR also relies on a powerful analytics engine — the human brain. Custodians know a lot about their own documents and emails. This is particularly true in technical or other complex matter where the custodians are engineers or other professionals who simply better understand the dynamics and the nuances of their information. With the X1 process, the custodians provide a key data point, where their input is used to inform the secondary review.

The process is very defensible as the exercise is logged and documented, with all metadata kept intact and a concise chain of custody established. Best of all, the custodian-applied tags and annotations are preserved and retained through the review process with X1 integration with Relativity. I could describe this very important feature a lot further, but candidly the best way to get a full picture is to see it for yourself. I recommend that you view this recorded 9 minute demonstration of X1’s custodian self-review feature here.

We believe X1’s functionality provides the optimal means for enterprise eDiscovery preservation, collection and early data assessment, especially with the key additional (and optional) feature of custodian assisted review. But please see for yourself and let us know what you think!

 

Leave a comment

Filed under Best Practices, compliance, Desktop Search, eDiscovery & Compliance, Enterprise eDiscovery

eDiscovery Collection 3.0: Much Better, Much Faster, Much Cheaper

In his recent blog post, X1 CEO Craig Carpenter discussed the inability of any software provider to solve a critical need by delivering a truly scalable eDiscovery preservation and collection solution. As Craig pointed out, 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.

Desktop_virtualization

Craig outlined how endpoint forensic imaging are still employed on a limited basis. Many companies have also tried network crawling methods with repurposed forensic tools. (A “collection 2.1” method, if you will).  While this can be feasible for a small number of custodians, network bandwidth constraints coupled with the requirement to migrate all endpoint data back to the forensic crawling tool renders the approach ineffective. For example, to search a custodian’s laptop with 10 gigabytes of email and documents, all 10 gigabytes must be copied and transmitted over the network, where it is then searched, all of which takes at least several hours per computer. So, most organizations choose to force collect all 10 gigabytes. The case of U.S. ex rel. McBride v. Halliburton Co.  272 F.R.D. 235 (2011), illustrates this specific pain point well. In McBride, Magistrate Judge John Facciola’s instructive opinion outlines Halliburton’s eDiscovery struggles to collect and process data from remote locations:

“Since the defendants employ persons overseas, this data collection may have to be shipped to the United States, or sent by network connections with finite capacity, which may require several days just to copy and transmit the data from a single custodian . . . (Halliburton) estimates that each custodian averages 15–20 gigabytes of data, and collection can take two to ten days per custodian. The data must then be processed to be rendered searchable by the review tool being used, a process that can overwhelm the computer’s capacity and require that the data be processed by batch, as opposed to all at once.”

Halliburton represented to the court that they spent hundreds of thousands of dollars on eDiscovery for only a few dozen remotely located custodians. The need to force-collect the remote custodians’ entire set of data and then sort it out through the expensive eDiscovery processing phase, instead of culling, filtering and searching the data at the point of collection drove up the costs. As such, this network crawling based architecture is fundamentally flawed and cannot scale.

What is needed is the ability to gain immediate visibility into unstructured distributed data across the enterprise, through the ability to search and collect across several hundred endpoints and other unstructured data sources such as file shares, and return results within minutes instead of days or weeks. The approaches outlined above and by Craig Carpenter do not come close to meeting this requirement and in fact actually perpetuate eDiscovery pain.

Solving this collection challenge once and for all is basis for X1 Insight and Collection, which is our eDiscovery collection 3.0 solution.  X1 Insight and Collection (XIC) 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. Built on our award-winning and patented X1 Search technology, XIC is the first product to offer true and massively scalable distributed data discovery across an organization. XIC replaces expensive, cumbersome and highly disruptive approaches to meet enterprise discovery, preservation, and collection needs.

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 XIC, 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 XIC by simply hitting the “collect” button. The responsive data is “containerized” at each end point and automatically transmitted to either a central location, or uploaded directly to Relativity, using Relativity’s import API where all data is seamlessly ready for review. Importantly, all results are tied back to a specific custodian, with full chain of custody and preservation of all file metadata. Here is a recording of a live public demo with Relativity, showing the very fast direct upload from XIC straight into RelativityOne.

This effort described above — from iterative, distributed search through collection and transmittal straight into Relativity from hundreds 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, and could even dwarf collection costs through unnecessary attorney review time.

XIC 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.

As Relativity Product Manager Barry O’Melia said in the live X1/R1 integration demo, it is something you have to see for yourself to believe. So please check out the demo here, or contact us to arrange for a private demo.

Leave a comment

Filed under Best Practices, Case Law, Case Study, eDiscovery, Enterprise eDiscovery, Uncategorized

X1 Insight and Collection & RelativityOne Integration: Testing and Proof of Concept

Editor’s Note: The following is a blog post published by eDiscovery expert Chad Jones, Director at D4 Discovery, regarding D4’s extensive testing and validation of the integration of R1 and X1 Insight and Collection.  It is republished here with permission. 

Discovery is a complicated business. For a typical litigation, there are at least five separate stages, collection, processing, review, analysis, and production, and while the average discovery period lasts eight to ten months, the matters themselves can run for years. During the lifecycle of a common eDiscovery project, these five stages are usually performed by several different parties, which further complicates the process by introducing a variety of hand-offs and delays between organizations and individuals.

The proof of concept that follows was designed to validate Insight and Collection, a product created by X1 Discovery, Inc, and that now features a direct upload to Relativity and RelativityOne. With this product, X1 proposes to streamline the five-stage process by allowing enterprises to search locally, collect those search hits, process the results and push them directly to RelativityOne in a matter of minutes.

To evaluate the viability of the X1 Insight and Collection, D4, LLC. designed and executed the following Proof of Concept (POC). A leader in forensic collection services and a seven-time Relativity Best in Service, Orange Levelhosting partner, D4 staff leveraged its expertise in end to end eDiscovery to implement the workflow and document the results.

Background

Project

eDiscovery is a multi-stage process with a series of hand-offs between disconnected parties. This process can be extremely expensive and error prone. In addition to the costs, the time to review can often span weeks or even months to complete.

Stakeholders

Those who stand to benefit from X1 Insight and Collection are business and organization leaders looking to manage and control the cost and risks of discovery.

Solution Features and Benefits

There are several features of the X1 Insight and Collection: search-in-place, early case assessment visualizations, remote collection, processing on demand, publish to review in RelativityOne. Searching in place on the local machine has several benefits. It prevents needless over collection and saves the end user from the hassle of turning over her machine and losing productivity. It also gives case teams the opportunity to iterative refine search terms and review search hits on the fly.

Finally, searching in place replaces the need to collect data and load to a master repository for indexing and searching. This includes email containers – the ability to index, search and collect all email in place on the custodian’s computer or the corporate Exchange server without the need to migrate the entire container or full account is a strong and unique capability. With X1’s remote collection, once users target the specific files and emails they need, they can immediately collect and process that information. Once collected and processed, enterprise users have the option of creating standard load files or sending text, metadata and native files directly to RelativityOne.

Practical Details of POC

To test and vet the software, D4 built a mini-cloud environment, consisting of five custodian machines; one enterprise server; and one client server meeting the specs listed below:

Server 1

  • OS: Microsoft Server 2012 R2
  • CPU: 2.6 GHz minimum 8 processors
  • Memory: 16 GB RAM
  • Disk: 180 GB free hard disk space (software)
  • Disk 2: 1TB for collected data (or available network drive)

Server 2

  • OS: Microsoft Server 2012 R2
  • CPU: 2.6 GHz minimum 8 processors
  • Memory: 32 GB RAM
  • Disk: 180 GB free hard disk space (software)

Testing Desktop: (QTY 5)

  • OS: Microsoft Windows 7, 8 or 10
  • CPU: 1.8 GHz minimum 2 processors
  • Memory: 8 GB RAM

On each custodian machine we placed a mix of email and non-email data. From these data sets we ran a series of tests from which we collected data.

Although X1 Insight and Collection provides a variety of workflows allowing for a complex collection strategy, for the purposes of this proof-of concept, the collection was limited to a simple Boolean query of common football related terms across Enron data. We made two separate collections of email data: a collection to disc with load files and a collection direct pushed to RelativityOne. The terms used in the POC were: “football OR game OR trade OR QB OR league OR cowboys OR longhorns OR thanksgiving OR player.” Following the collections, the results of the load file export were test loaded to Relativity and the results of the dataset published direct to RelativityOne were evaluated in that workspace.

Test Results

The testing process considered four main areas: documenting search results; documenting upload/download times; metadata validation; and reports and exception handling. To test the search results the loaded data was indexed, and searches run to confirm the results. In both load formats, the search results remained the same as shown below.

It is important to note that in Relativity only the text was searched while in X1 all metadata was also included in the search. This is a common difference between review platforms and collection tools, as collection tools are able to search all components of the file, while review is limited to extracted metadata fields only.

Additional tests were performed to document search and exports speeds. One of the components of X1 Insight and Collection is its collection module which sits on the client server and manages the collection from a central location. In the initial test, we chose to export the files to disc and create a load file, while in the second test we leveraged X1s integration with RelativityOne and upload data to Relativity’s cloud instance via the Relativity API.

In both cases, the results proved that X1 is incredibly powerful. Each time the system executed saved searches on five separate machines, pulled the data to the client server, extracted text and metadata and then either generated a load file or sent the deliverable straight to the cloud and into Relativity – all within minutes. The results, shown below, are amazing. In both cases the system completed all steps in under 13.5 minutes. Additional tests were performed to document search and exports speeds.

One of the components of X1 Insight and Collection is its collection module which sits on the client server and manages the collection from a central location. In the initial test, we chose to export the files to disc and create a load file, while in the second test we leveraged X1s integration with RelativityOne and upload data to Relativity’s cloud instance via the Relativity API. In both cases, the results proved that X1 is incredibly powerful. Each time the system executed saved searches on five separate machines, pulled the data to the client server, extracted text and metadata and then either generated a load file or sent the deliverable straight to the cloud and into Relativity – all within minutes. The results, shown below, are amazing. In both cases the system completed all steps in under 13.5 minutes.

Further testing showed that while X1 gets the essential metadata components extracted from the data, there are some features we are used to seeing in established eDiscovery processing tools that are lacking in this product. We also found the exception reporting to be lacking. In our RelativityOne tests, we found 40 files were excluded from upload, yet when reviewing the available exception reporting we had trouble seeing what caused those file failures. These issues notwithstanding, the POC proved successful. X1 Insight and Collection proved to be a powerful search engine and collection tool, capable of collecting over 6,000 documents from five separate machines and uploading those files to RelativityOne in less than fifteen minutes!

Conclusion

X1 Insight and Collection offers multiple benefits to the enterprise user looking to take control of the eDiscovery life cycle. By simplifying the course of an eDiscovery project, X1 limits the number of touch points in the traditional vendor-driven process. Internal users can search and vet terms in real-time before collection. This not only mitigates the opportunity for error, but it greatly reduces the time to review, which is what this solution really seems to be all about. X1 seems to have been designed with the internal investigation in mind. Offering a light tagging feature, X1 gives users a light ECA option that with a couple mouse clicks becomes a collection and processing tool that connects directly to all the features of RelativityOne. When combined with Relativity ECA, Analytics and Active Learning, this might be all the solution the typical enterprise would need.

Leave a comment

Filed under Best Practices, Case Study, compliance, eDiscovery, Enterprise eDiscovery, Information Governance, reviewing