Evidence

JSON is not a document, it is data… and lots of it!

By:  Trent Livingston

Modern eDiscovery deals with much more than just documents. In 2020, people created 1.7 MB of data every second, and most of that data was likely stored in a database. Now, newer applications like Facebook, Twitter, Slack are storing copious amounts of data ranging from tweets, wall posts, and chats.

Many of these artifacts are stored with complementary data that can include file links, reactions (such as “likes”), and even geolocation information. Accessing this modern data in order to leverage it for a discovery request often requires some sort of archive process from the originating application, and that is when JSON enters the picture.

JSON stands for “JavaScript Object Notation”, but that doesn’t mean you need to know how to write JavaScript (or any code for that matter)!  If you’ve ever dealt with discovery surrounding any of the aforementioned applications, you’ve likely come across a few JSON files. In a nutshell, think of JSON as a relational spreadsheet where one column of data in one tab of your spreadsheet is defined by another column of data in another tab in another spreadsheet.

For example, you might have a column called “Address” in a spreadsheet and that column contains a series of numeric “id” values that reference another tab in that same spreadsheet. In this secondary tab, each address is broken down into values for that address that may include things like “country”, “zip”, or “street”.  All those values that have the same “id” belong to the “address” reference in the previous tab. Simply put, this is structured data. JSON data is no different. However, JSON can contain a multitude of data structures varying from simple to complex.

The problem with JSON is while there are multiple JSON viewers and formatters online, they do not understand the defined data structures within.  Each platform defines these data structures differently, and while the vehicle may be the same, the defined structure is usually different from application to application (as well as the application’s version).  Therefore, the data within the JSON often comes out in an unexpected format when using a generic formatting tool, and the relationships between the data are often lost or jumbled. (By the way, you should never use any online “free” tool to format potentially confidential or privileged information).

Therefore, it is important to work with someone who understands JSON as an eDiscovery data source.  A single JSON file just a few megabytes in size may represent hundreds, if not thousands of messages, contain numerous links to files, as well as key data relevant to your investigation or litigation. Contained within a JSON file could be any number of nested data formats, including:

  • Strings: a sequence of zero or more Unicode characters, which could include emojis in a Unicode format, usernames, or an actual text message.
  • Numbers: a numeric value that can represent a date, intrinsic value, id, or potentially a true/false value represented as “1” or “0”.
  • Objects: a series or collection of one or more data points represented as named value pairs that create meaning as a whole, such as longitude, latitude, elevation, rate of speed, and direction that make up the components of a device’s location.
  • Arrays: a collection of values or elements of the same type that can be individually referenced by using an index to a unique identifier, such as the choices of a color of a car on a website or a set of canned response values listed in a software chat application.

The thing to remember is the JSON file is actually one big “object”, which is the parent to all of the named value pairs beneath it.  Within this object, you can have more objects that contain numbers, strings, arrays, and yet even more objects. Confused yet?

Not to worry! It is understandable that all this JSON data can quickly become a source of frustration!  The question that remains is, “How do I make sense of all of this structured data and present it for review in a reasonably usable format?” 

Here are some tips:

  1. Make sure you do not overlook JSON as part of your electronic discovery protocol
  2. Leverage an experienced team to help you understand the JSON output
    • Document the source application whenever possible (some JSON include access keys that can expire or be terminated at any time, such as Slack)
    • Preserve the JSON file as you would any other evidentiary data source
    • Document the chain of custody for the JSON file (originating application and version of that application, who conducted the export, as well as any access keys that may be transitory or temporary and their date of expiration)
    • Treat each JSON file and associated content as a potential source of PII, confidential, and/or privileged information given the breadth of data that each may contain
  3. Work with a team and a product that can parse, ingest, and subsequently present JSON data in a usable format for review and production

While there is not an off-the-shelf solution for every JSON file in existence, CloudNine ESI Analyst is a platform designed for the multitude of data types that can be extracted from just about any JSON file out there. Many of which can be easily mapped to a data type construct within our SaaS application that allows for presentation, review, and production in a reasonably usable format.

Contact us today for a demonstration and further detail!

Three Use Cases to Navigate Modern Data in eDiscovery

In litigation, knowing the full picture is the only way to effectively represent your clients. The only problem is most of the story is often stored on electronic devices like smartphones, laptops, or tablets.

While eDiscovery can be dated back to 1981 and the first substantial use of email in litigation (Governors of United State Postal Service v. United States Postal Rate Commission), integrating newer, modern data types like text messages, computer activity, and financial data, has been a bit more challenging. These challenges relate back to how eDiscovery has historically worked and why modern data sources don’t fit nicely into that process. 

When eDiscovery was introduced with email and electronic documents as the primary source of information, simple messages and documents were sufficient to tell the story in a linear document review workflow. But, with sophisticated technology like Slack, chat applications and smartphone messaging where communications occur in real time, the conversion to documents for review hinders a proper evidence analysis.

Making sense of all that data only works when it is presented in the way it was originally communicated. The old documentation process simply doesn’t provide the insight you need to leverage modern data in litigation.

Case Study 1: Tackling Disparate Modern Data from Multiple Sources

No matter how small or large your case is, reviewing modern data can be challenging. Between smartphones, laptops, social media apps, and other connected devices, there’s a plethora of data to sift through to find the evidence you need to support your case. This process becomes even more complicated when the data is presented through the lens of traditional eDiscovery meaning, in traditional document format. What once worked for simple electronic communications no longer tells the whole story within complex, real-time and editable messaging technologies like WhatsApp, Slack and social media.

So what happens when you have to produce data from hundreds of international sources, and need it to tell the story of what actually happened? Let’s look at a case study of a construction company who had to do exactly that.

The Problem:

One of the largest construction companies in the world required the collection of modern data from 300 international sources. While the sheer number of sources was a challenge in itself, the real difficulty was working with disparate data from so many different sources.

Each business unit within the company used different technology so data had to be collected from a vast number of sources – local desktops, laptops, smartphones, tablets, and backup servers.

Plus, because so many BYOD devices were used, legal, data privacy, IT, and risk & compliance departments had to be consulted throughout the collection and review process to ensure no U.S. or international privacy laws were broken.

The Solution:

Ultimately, our client needed to understand who said or did what, and when. Basic documents with communications from readily available sources wouldn’t be enough, because they couldn’t easily identify the critical timeline of events or the intentions of each party. In the end, CloudNine ESI’s actor normalization function was the key to finding the evidence needed.

The Results:

By matching specific individuals to different aliases and phone numbers, attorneys were able to identify a handful of photos shared from the vast amount of data collected that proved the construction company was at fault. These photos were presented to the court in the form of inline bubble messaging that was easy to read and view.  To learn more about this use case, click here.

Case Study 2: Overcoming the Personal Device eDiscovery Challenge

There’s an expected, inherent trust between a company and its employees which means employees typically won’t do work that’s a conflict of interest with their current employer. Unfortunately, that trust is sometimes broken by actors that take advantage of their position.

The Problem:

When a heavy equipment manager became the target of a moonlighting case that cost his company money, attorneys were discouraged when they couldn’t find any evidence of wrongdoing. There were no documents, emails, or invoices to be found through traditional eDiscovery.

The Solution:

Fortunately, the key to the case was the manager’s smartphone.

By gaining access to his phone, attorneys were able to secure tens of thousands of text messages directly related to the case. This helped them discover how he operated his illegal side hustle. They also learned he was sharing confidential, copyrighted, and proprietary information through photos sent via text message.

The Results:

Through CloudNine ESI Analyst, attorneys were able to create conversation threads which were easy to review and produce. These threads not only helped them identify other involved parties, but let them produce messages, including embedded images, videos, GIFs, and emojis.

Without the ability to review and analyze the bad actor’s smartphone data, the case likely would not have gone forward.  

To learn more about this use case, click here.

Case Study 3: Protecting Company Data with Modern eDiscovery

The average American holds 12 jobs in their lifetime so it’s safe to say you will lose employees from time to time. Whether purposeful or accidental, the odds are good their personal devices will contain confidential or proprietary information when they walk through the door for the final time.

So what if you could examine their devices and remove all sensitive material before they left?

The Problem:

An employee spent six months working from home on a personal laptop before announcing his resignation to work for a competitor. If the employee was allowed to leave without a device review, he’d likely be leaving with documents that would benefit both him and his new employer.

Whether he would ever used those documents or not, chances are he’d find himself in the middle of a long, expensive trade secrets case which would also impact his new employer.

The Solution:

The representatives of the employee’s current company needed a way to access his personal laptop and identify any confidential or proprietary documents to be destroyed before he went to work for their competitor. They sought out a solution to easily identify these risks to protect their company, the employee and the employee’s future company.

The Results:

With CloudNine ESI Analyst, company representatives were able to access his personal laptop, create a chain of custody and review the data found on it. This allowed them to find confidential and proprietary data and remove it before the employee left for his new position, protecting all parties involved.

By doing this in advance, you preserve the data and protect it without relying on your employees to remember if they have sensitive information on their devices or not.

To learn more about this use case, click here

CloudNine ESI Analyst – A Modern eDiscovery Solution for Modern Data Review

While most law firms, corporations, and LSPs are challenged to review modern data through traditional eDiscovery tools, they struggle to pull the true value out of the data. Each text and corporate chat message are recreated as stand-alone documents, leaving you to piece them all together like a giant legal jigsaw puzzle with missing pieces and others that simply don’t fit the storyline.

With a robust and flexible modern eDiscovery tool like CloudNine ESI Analyst, you have access to alternative data to help you put the puzzle together through linear storytelling that creates a digital trail of evidence, including some of these popular sources:

  • Text messages (SMS and MMS)
  • Call logs
  • Voicemails
  • Messenger applications (Slack, Teams, WhatsApp, Messenger, etc.)
  • Computer activity
  • Financial transactions
  • Geolocation

Modernize your investigations and litigation by effectively managing the data in a single platform instead of wasting time managing a menagerie of documents in siloed systems.

Every case is unique and requires you to find the facts and context to tell the complete story. Contact CloudNine and learn how we can help you leverage all the data to get to the truth of the matter. Contact us to learn more.

Modern Data Discussions by Leading Experts at The Master’s Conference in DC

Last week, CloudNine Senior Director Rick Clark, VP Rob Lekowski and industry thought leaders convened in Washington, DC for The Master’s Conference first in-person event since early 2020. The two-day event tackled the latest challenges in eDiscovery, cybersecurity, and information governance. Managing modern data was the most popular recurrent topic with four distinct panels on the subject.

Smartphones, collaboration apps, and social media platforms all store a plethora of relevant information and is where today’s most important evidence resides. By avoiding or mismanaging this evidence, lawyers miss out on critical insights. So, how should legal teams incorporate modern data into investigations? Rick Clark addressed this question and more during the panel titled “Telling The Full Story: Leveraging the Data Between the Documents” with panelists Dave Rogers, Kroll; Kevin Albert, PAE; and Sonya Judkins, T-Mobile.

Here are three key takeaways from the panel discussion:

Modern data types can no longer be ignored – Emails and traditional documents are always going to be a part of discovery and investigations, but key data has moved away from these platforms. Conversations in Slack, MS Teams, device chat applications and text messages are additional communications needed to follow the conversation. Nowadays, modern data expands above communications into geolocation, social media posts, user activities and offer the largest insights. Recent case decisions have proven that judges are open to admitting modern data so long as the evidence is relevant and properly authenticated.

 Data shouldn’t be treated like documents – One reason why legal teams avoid modern data is linear document review. Imaging and exporting modern data leads to issues like missing metadata, families, threads, and file types. This method also requires legal teams to review evidence without any threading, deduplication, or link-analysis tools. Instead, large volumes of data are analyzed document by document. Linear document review is tedious, inefficient, and time-consuming but most important is legal teams who use linear document review also run the risk of overlooking important details. By opting for link analysis, litigants can connect various data points together to find relevant information faster.

“There just isn’t a good solution out there” – NOT TRUE – Four panels at the Master’s Conference discussed the challenges of modern data, but only Rick Clark’s panel offered a solution. CloudNine ESI Analyst is the only software that renders modern data in a near-native state. The platform uniquely offers users the ability to ingest and investigate multiple data sources within a single platform. Attendees of the CloudNine breakout session were given a full demonstration of ESI Analyst’s capabilities. Through timelines and 24-hour threads, ESI Analyst enables native analysis of communications, transactions, and computer activities.

Missed the Washington, DC event? Join us May 18th, 2022 for the next Master’s Conference in Chicago, Illinois.

Click here to learn more about how CloudNine ESI Analyst can help you manage your modern data.

Generate More Revenue For Your Law Firm with Modern eDiscovery

One of the biggest challenges for any business is discovering new revenue streams once your growth reaches its zenith. For most law firms, this creates a welcome opportunity to offer new and better solutions while bringing more revenue into the organization.

As technology evolves, so does the diversity of new data types.  By expanding your firm’s ability effectively and accurately collect and analyze emerging data types, you create new opportunities to meet the changing needs of your clients.

Hit the eDiscovery Bullseye: The Latest Trends in Data Types

Electronically stored information (ESI) evolves every time new software is created. Whether it’s an updated version of current data or an entirely new data type, ESI is constantly changing.

To operate successfully, your law firm needs the ability to effectively process these modern data types. Consider the following statistics from two popular messaging applications – Microsoft Teams and Slack:

  • Teams has 145 million daily active users
  • Teams is used by more than 500,000 organizations as their default messaging platform
  • Slack has 10 million daily active users
  • Slack is used by 43% of Fortune 100 businesses

The sheer volume of modern data users creates an unmatched treasure trove of data vital to your client’s litigation. Other popular communication platforms like Google Meet, Zoom, GoToMeeting, and WhatsApp also contribute to the unparalleled growth of modern data types.

However, only recently have legal professionals begun to see the benefits of reviewing these data types since their reliance on traditional data types was easy and typically, sufficient.

Everyone in the legal profession can benefit from the ability to collect and analyze messages and metadata from communication platforms.  However, law firms and forensics companies in particular now understand the true value of other modern data like computer activity, geolocation, and financial transactions because it’s critically important to the success of their investigations.

Read a case study to learn how CloudNine is helped reconstruct conversations across multiple file types.

Why Modern Data Doesn’t Work Well with Traditional eDiscovery Platforms

Traditional data is typically straightforward in the form of Word documents, spreadsheets, and emails converted into PDF. The biggest issue with collecting and analyzing modern metadata on a traditional eDiscovery platform is compatibility.

Modern data transmitted by web clients and web servers is usually found within JavaScript Object Notation (JSON) files. JSON files are the preferred format for almost every public web service available today, including Teams and Slack.

HTML is another popular file type used by websites and social media applications like Facebook and Twitter to create individual pages.

JSON and HTML cause problems with traditional eDiscovery because traditional platforms cannot extract the content and metadata and organize it into an easy-to-review format. The result is usually very difficult to read, let alone review for eDiscovery.

Another challenge is simply the cost. In Zubulake v USB Warburg, the courts found the defendants were required to provide all relevant data files related to the case at their own expense. If your client is a large corporation, this could mean a large volume of devices to be collected for eDiscovery, which will naturally raise costs.

Tip the Scales of Justice with a Modern eDiscovery Platform

As applications like Teams and Slack make modern data more common, it has become more acceptable to be used in litigation. In the past, attorneys would argue to have modern data dismissed, and more often than not, the judge would allow it. Today’s judges have a better understanding of the value of emerging data so they require it for eDiscovery.

Modern eDiscovery platforms can collect a variety of modern data and accurately prepare it for review. Data types under this umbrella include:

  • Communication from messaging applications
  • File sharing applications
  • Metadata from video conferences
  • Mobile messaging including text, SMS, and MMS
  • Computer activity including the movement and alteration of files
  • GeoLocation
  • Social media posts
  • Financial transactions

In addition, by leveraging a modern data review platform, you can collect communication across multiple applications and devices. Based on the metadata, you can create pristine communication threads that flow from one platform to another, giving you a more complete picture and the context to understand how people were behaving and why. That simply isn’t possible in a traditional eDiscovery platform.

Stay up to date on how CloudNine is revolutionizing eDiscovery by signing up for our regular eDiscovery updates and best practices.

How Law Firms Use Modern eDiscovery to Offer Better Solutions

When you have the ability to review modern data, you can manage your case more effectively and efficiently by consolidating the workflows of multiple processes using a single SaaS platform.

  • Early Case Assessment. With CloudNine’s people and platforms, you are enabled to collect, cull, process and organize large amounts of modern data, to provide the needed insight to your case investigations to predict costs more accurately.
  • Unified Review Workflows. A simplified and consolidated workflow allows you to process, sort, review, tag, and produce traditional and modern data quickly and accurately.
  • Higher Level of Data Organization. By leveraging the metadata and conversation content, you can analyze and review all data types easier and more efficiently. This “Data NOT Documents” approach allows you to quickly narrow in on key conversations faster than traditional document review.
  • Context to Understand the Whole Story. Following digital conversations across multiple platforms along with computer activity, geolocation, social media and financial transactions, you create a more complete narrative to add the context needed to understand the whole story.

With these benefits, you can now demonstrate maximum efficiency and offer unparalleled service to your clients.

Your clients are looking to you to provide the best legal advice and management of their data, regardless of data types, modern or traditional.

By offering a solution giving them equal access to both traditional and modern data types with CloudNine eDiscovery solutions. Request a free demo and let us show you how CloudNine can help you generate more revenue while better preparing your clients for litigation.

Emerge From Data Chaos With eDiscovery Built For Today’s Data

Did you know in 2020 alone, the average person created 1.7 MB of data every second? (source).  Now consider this in the context of your latest eDiscovery case:  from cell phone forensics to computer user activity, the amount of digital documents to review is massive.  For example, here’s a glimpse of the daily counts of electronically stored information (ESI) including traditional and modern data types:

  • 4 billion emails (source)
  • 7 billion text messages (source)
  • 100 billion WhatsApp messages (source)
  • 4 billion Snapchat photo messages (source)

And, this doesn’t even include other traditional data types like documents or spreadsheets. Nor does it count modern data types like computer user activity, geolocation tracking, corporate chat applications, financial transactions, or social media posts.  While eDiscovery review platforms are designed to process traditional data types, you need a better, more efficient way to analyze the sheer volume of digital discovery types.

To provide a comprehensive view of all data types, CloudNine has introduced a modern data review experience to enable the analysis of existing and emerging data types, from a single eDiscovery solution platform.

Synergize eDiscovery of Today’s Data with CloudNine

Current eDiscovery review platforms were developed to support traditional data types like emails, Word documents, spreadsheets, and PowerPoint as evidence in litigation. The problem is they rarely provide the context needed to tell the whole story because they miss potentially relevant data found on mobile devices and corporate chat applications like Microsoft Teams or Slack. 

Without this nuanced data, you don’t have the ability to show behaviors, actions, or communication across different platforms, making it more challenging to prove your case as it’s very difficult to show context if you’re working exclusively with traditional file types.

Using Cellebrite UFED, a digital tool for extracting data from mobile devices, we can quickly collect cell phone data and inject it directly into the document review platform.

In addition, CloudNine’s modern data review platform can create timelines to organize relevant data in a linear outline to tell a story from beginning to end. Combining this with the ability to track digital conversations across multiple platforms, you’ll have better insight into:

  • How subjects were behaving
  • What they were doing
  • Where they were going
  • Who and when they were communicating with

CloudNine’s modern data solution expands your ability to understand the whole story in ways your competition can’t. The ability to collect and review this type of data allows you to better understand the facts surrounding your litigation, applying context so you’re able to tell the whole story.

Our solution for today’s data is suitable for both large and small data sets. It’s robust enough to handle the largest cases with extremely large data sets while remaining nimble to give attorneys the ability to view data quickly and easily on much smaller cases.

Regardless of the case or file types your team is reviewing, your eDiscovery team can get to the truth much faster.

Take the Rediscovery Out of Your eDiscovery: CloudNine’s ESI Analyst is the Perfect Complement to Enhance CloudNine Review

While CloudNine Review brings a fast, secure and easy-to-use platform to load and export data quickly and efficiently, the addition of a modern data solution adds a new layer of context and complexity to your litigation.

Now, when you receive your data, you can upload all the data sources into our modern data platform, perform eDiscovery and then import your modern and traditional data directly to CloudNine Review for a simplified and streamlined review.

Most legal firms and LSPs are forced to shoehorn modern data into traditional legal document review platforms. This can lead to confusion about the importance of what role specific text messages play in the story.

However, by letting you review every type of data more accurately, you get a more efficient solution that addresses both traditional and modern data, providing more insight and clarity into the factors behind the litigation.

A perfect example of this is the ability to analyze financial data and computer user activity. While collecting and reviewing financial data means you can track transactions and payments easier, tracking computer activity through registry files or event logs lets you see actions taking place on a digital level.

For example, if an employee copies a confidential document onto a thumb drive and walks out the door with it, you’ll be able to see that action in the data records.

As an organization, we are committed to evolving in the same way eDiscovery evolves. Stay up-to-date on the latest CloudNine updates by signing up to receive our latest eDiscovery news delivered to your inbox.

Don’t Fall Prey To Ingestion Congestion: The Ease of Integration and Deployment with CloudNine

Simple Deployment:  While the technical aspects of integrating CloudNine’s modern eDiscovery review platform is incredibly easy, the important thing to know is how simple it is to deploy the solution for your staff. Training for your administrators to operate the platform can be completed in an hour while training your review team for a specific case takes as little as 15-30 minutes.

Searching and Batching: By creating a series of searches based on specific keywords or phrases, you can pull data batches to assign to your team so they can review and add custom tags for relevant data. This is a valuable tool for anyone using this modern data eDiscovery solution, whether you have the resources to employ a litigation-support team or if you’re a smaller office with only one or two attorneys.

Superior Support:  If there’s any questions or problems, support is just a phone call away. If you don’t know how to use a particular feature or tool, we can schedule a quick online training session and walk you through the process. Plus, there are over a hundred resource articles in our library to help you learn how to better use CloudNine’s solution.

By offering solutions that empower you to collect, review and analyze both traditional and modern data types, you can streamline your eDiscovery process and capture information that tells the whole story through different platforms.

To complement your existing eDiscovery solution and combine both traditional and modern data types into a more complete narrative, contact CloudNine to find out how we can seamlessly fold our self-service, SaaS application designed for all data types into your eDiscovery process.

What Happens When You Don’t Have a Modern Data Solution?

Why a Modern Data Review Platform is Critical to eDiscovery

When legal professionals first incorporated electronically stored information (ESI) into their eDiscovery document review process, it opened the door for a variety of digital data types to be used in investigation and litigation. 

It didn’t take long for eDiscovery to begin taking in ESI like emails, documents, spreadsheets, databases, CAD/CAM files, digital images, and websites. These have remained the primary sources of digital discovery data used by legal professionals. 

However, as technology continues to evolve, new modern data types are becoming increasingly vital in litigation. These new modern data types fall under five primary categories, in addition to traditional eDiscovery: 

  1. Communication
  2. Computer/User Activity 
  3. Geo-location tracking (location tracking software)
  4. Financial Transactions
  5. Social Media

These modern data types have their own unique uses and their associated metadata allows you to create a chronological list of events and user activities so you can gain context where it did not exist in traditional discovery. 

Here are just a few examples of how it works:

  • By gathering data on computer activity, you’re able to see when individuals upload documents to Google Drive or download them onto thumb drives. 
  • Geolocation lets you determine where a computer activity took place so you know if they were at home, in the office, or at another location.
  • By using the metadata associated with different communication applications, you can track and document relevant dialogue between two parties as they carry their conversation from one device or application to another. 

With these additional data types, you’re able to tell a complete story through your legal review when combining traditional and modern data, in one unified eDiscovery platform

As more modern data forensic artifacts emerge, CloudNine is doing our part to help your eDiscovery team gain the context and confidence you need to solve your cases. Sign up to receive updates on our offerings here.

Reconstructing Digital Conversations To Unveil The Full Picture

In a modern data eDiscovery solution, you can do things that simply aren’t possible or are too difficult or costly to do in a traditional document review-centric platform. 

In a traditional legal document review platform, communication between two individuals would be collected and stored as individual documents. This means the context of the whole conversation including text before and after the individual messages could lose context in the conversation, leaving a void in the interpretation.

A modern data review platform allows you to collect data from multiple devices and applications including traditional ESI and loose files. By using the metadata associated with the collected data, you can select two individuals and review all communication between them in a chronological timeline. Now you have the context to perform the smartphone forensics and short message discovery you need to follow a conversation that began in Slack but transitioned to text messaging before concluding in WhatsApp.

Cell Phone Discovery: Reviewing Text Messages In a Modern Data Review Platform

Traditional legal review platforms are often inefficient when reviewing text messages. In a traditional platform, text threads are converted to PDF requiring each thread to be reviewed, text-by-text. In this case, five individuals in a group text messaging thread, means you’ll see the same message collected five times. This results in a lot of time and money wasted redacting large parts of the text thread, irrelevant to the topic. 

Smartphone data discovery allows you to filter duplicate messages, and remove 20-30% of the collected data.  With a simple click of a button, modern eDiscovery review allows you to select the text messages you want to advance and remove the irrelevant text from long or group threads.

Another challenge for traditional review platforms is the inability to maintain native formats for data. By relying on screenshots or PDFs, organizations using older platforms can fall victim to doctored images that could affect the course of the litigation. 

For example, in Rossbach v. Montefiore Medical Center, a plaintiff used screenshots of a text message to attempt to prove that her former employer had sexually harassed, then fired her. The message was allegedly sent to her iPhone 5 which cannot run an operating system beyond iOS 10. A forensics investigator examined the screenshot and discovered an emoji present in the image was a version not available until iOS 13 was released.

Modern eDiscovery review platforms capture text message formats (MMS and SMS) in their native format so there’s no risk of fraudulent or altered data in the review.  A unified eDiscovery platform will combine both traditional and modern data without creating documents from modern data sources.

Learn more about how your legal team can hit the eDiscovery bullseye with every data type with CloudNine Review here.

Why Organizations Are Hesitant to Commit to a Modern Data Review Platform

Some organizations are hesitant to adopt a modern data review platform because of their apprehension to change standard operations. They’re unwilling to change their review mentality from document-based to metadata-based or a hybrid of both.  After all, if it’s working, why change it?  

Many organizations are also forced to break-out their review processes among multiple platforms – one for traditional data like emails and Word documents and one for modern data like geolocation, social media and computer activity. 

In addition, there are some objections to native file production:

  • Retrieval of native files after initial document collection would mean additional costs.
  • Redaction is difficult or even impossible with some native file types.
  • Image-based productions are often accepted in court. 
  • Static images are equally useful for analysis and review of native files.
  • Federal Rule of Civil Procedure 34 does not specifically require native formats.

However, as modern data types become more common and important, organizations are beginning to understand that using a traditional, legacy document solution to review modern data is becoming burdensome, expensive, and slow. 

How a Modern Data Review Platform Simplifies eDiscovery

Simply put, a modern data review platform like CloudNine’s ESI Analyst organizes your data more efficiently by using metadata to sort modern data types by recipients, senders, timestamps, locations, and computer activity. 

The data is then tagged under one of the following data types:

  1. Call logs and voice mails 
  2. Chat applications (WhatsApp, Telegram, Facebook Messenger, etc.)
  3. Email
  4. Corporate chat applications (Slack, MS Teams, etc.)
  5. Text Messages (SMS, MMS)
  6. Computer activity 
  7. Geolocation
  8.  Social media
  9.  Financial transactions 

In addition, with a built-in foreign language tool, you have access to more than 80 supported languages so nothing gets lost in translation.

While legacy document review solutions are limited to reviewing documents, they miss key data points like geolocation, financial transactions, and other pertinent data that does not fit in a document-centric workflow.  The CloudNine, integrated solution allows you to filter, search, tag, and review all data in one platform.  

Let CloudNine help you integrate a modern data review platform into your eDiscovery processes. We can train your case teams quickly so they’re up and running in 15-20 minutes. To learn more about how our modern data solution can make your eDiscovery processes more efficient, drop us a line

Four Tips for Successful Meet and Confers

When approaching any challenge or goal, it’s often best to start with the big picture before narrowing things down. By working backwards, you can identify the steps needed to achieve the desired result. This type of thinking can be applied to Rule 26(f) conferences (also known as meet and confers). As mandated by Rule 26(f) of the FRCP, both parties must meet at least 21 days before holding a scheduling conference. The purpose of the meet and confer is to discuss litigation details such as data preservation, privilege issues, the form of production, and expenses. To get the ball rolling, counsel can prepare a list of general questions: What data types need to be collected? How should the scope of discovery be defined? What pace is needed to meet court-established deadlines? General questions like these build a solid foundation for deeper inquiries and concerns. [1]

More Tips for Meet and Confers

  1. Initiate the conference early.

The meet and confer process is not something that can or should be rushed. Negotiation takes time, patience, and multiple attempts. Waiting until the last-minute benefits no one. Instead of frantically rushing to meet deadlines, schedule the meet and confer as soon as possible. Sometimes, counsel is hesitant to meet early because they feel that they don’t have enough information and prep time. Thus, in addition to meeting early, parties should also meet often. Multiple conferences allow the parties to fully understand and iron out the details.

  1. Identify and evaluate the accessibility of relevant data types.

Companies interact with a variety of data types on a daily basis – email, Facebook, Zoom, the list goes on. Producing each one would be burdensome, expensive, and unnecessary. Only focus on relevant data types that are proportional to the needs of the case. Companies also regularly create and destroy large volumes of information. Therefore, you must assess their data retention policies to determine what information is stored and where. Once that’s settled, consider whether the data types are too expensive or inaccessible for production.

  1. Walk in with the right mindset.

Compromise is impossible to reach without flexibility from both parties. At the same time, neither party should feel obligated to concede to all proposals. Meet and confers should be thought of as open dialogues. Discuss, debate, and engage in respectful arguments when necessary. Above all, cooperate by ensuring your suggestions are reasonable and proportional. [2]  If this aspect is a concern, consider hiring a discovery expert. Through their industry knowledge, experts can assess the opposing party’s discovery systems and requests.

  1. Understand your client’s data policies and systems.

Before heading into the meet and confer, try to gather as much information as possible. Ask your client if they have any formal information governance policies. If not, probe further to identify how and where their data is stored. It’s also important to identify the person or department in charge of storing said data. The client’s IT environment must be understood as well. Inquire about the quantity and locations of company computers. Additionally, request information about the company’s software programs, backup schedules, data custodians, etc. [1]

 

[1] Ronald I. Raether Jr., “Preparing for the Rule 26(f) Scheduling Conference and Other Practical Advice in the Wake of the Recent Amendments to the Rules Governing E-Discovery,” The Federal Lawyer, August 2007.

[2] Scott Devens, “Defensible Strategies for the ‘Meet and Confer,’” Bloomberg Law, Oct. 18, 2011.

Need a Data Retention Policy? Here’s How to Build One

Now that most industries are going paperless, companies must create a comprehensive data retention policy. The purpose of a data retention policy is to establish procedures for labeling, storing, and deleting electronic (and physical) records. [1]  Most companies acknowledge the need for a retention policy, but they don’t commit to creating one. A 2000 ABA study found that 83% of the responding companies had no established protocol for handling discovery requests. Despite this unsettling statistic, 77% of the companies expected discovery requests to increase in the future. [2]  Many reasons support the need for comprehensive retention policies. One of the most pressing reasons is the explosion of ESI in recent years. For instance, corporate email alone is estimated to increase annually at a compounded rate of over 13%.  Without a data retention policy, an organization in the midst of litigation would be responsible for organizing large volumes of data with little time to do so. By proactively developing data management policies, companies will avoid the pressures of looming deadlines. Ensuring that information is properly handled also minimizes a company’s risk for sanctions. [1]  The following is a list of steps and suggestions for developing a data retention policy.

  • Do your research on relevant laws

Certain state and federal laws mandate specific preservation and deletion practices. HIPAA and GLBA are older examples of ESI regulations enacted in the late 1990s. However, states are constantly reviewing and revising their ediscovery laws, so it’s important to stay on top of any legislation changes.

  • Determine when to archive or delete data

While corporations are not expected to store every single electronic document, deletions must be orderly and purposeful. The practice of strategically deleting unneeded data is referred to as “defensible deletion.” When done correctly, defensible deletion is cost-efficient, storage-friendly, and most importantly, legal. Defensible deletion is protected by Rule 37(e) of the Federal Rules of Civil Procedure (FRCP). The rule prohibits sanctions against electronic records that were lost during good-faith deletion procedures. [3]

  • Review how your data is housed

In this step of the process, it’s important to ask what, where, and how. What data types are being stored, and how should they be classified (i.e. social media, email, transactions)? What are the retention policies for each medium? What’s the purpose of preserving this information? Where is it being stored, and does this location need to be changed to a better one? How long does the data need to be stored in order to comply with applicable state and federal laws?

  • Monitor your policy

Regularly review your policy to ensure that your company is following its outlined regulations. If you notice that your company is deviating from the policy’s storage and deletion procedure, fix the issue as soon as possible to minimize any legal risks. Routine audits also make it easier to make policy adjustments as needed.

  • Assign accountability

Determine who will be responsible for enforcing the policy throughout the company. This person or department must be well-versed on the policy’s provisions, and they must be ready to testify in court about the company’s retention procedures. [2]

  • Limit your paper trail

Consider a provision that requires electronic copies of physical documents. Some companies are still hesitant to transition to completely paperless operations. Though this hesitancy is understandable, it’s recommended to save an electronic version of all paper records. This suggestion is merely that, just a suggestion. Completely converting to electronic records is not a mandatory step in creating an effective data retention policy. However, this step would speed up the process of identifying relevant data for litigation. [1]

[1] Carlos Leyva, “Data Retention & eDiscovery,” Digital Business Law Group.

[2] “Document Retention & Destruction Policies for Digital Data,” Applied Discovery, LexisNexis, 2004.

[3] Law Offices of Salar Atrizadeh, “Electronic Discovery and Data Retention Policies,” Internet Lawyer Blog, May 18, 2020.

Understanding and Managing eDiscovery Costs

For a medium-sized lawsuit, eDiscovery costs can range anywhere from 2.5 to 3.5 million dollars. [1] This price has been exacerbated by the effects of COVID-19 on communication data. According to the International Legal Technology Association (ILTA), the pandemic has created a data explosion by encouraging frequent usage of chat applications. Meanwhile, the levels of email and other data types have remained constant. [2] As time passes, the list of communication types will continue to expand with new collaboration tools and social media platforms. On one hand, these changes have made communicating with loved ones and coworkers easier than ever. On the other hand, the influx of modern data types has created an expensive headache for legal teams.

Current Approaches to the Problem

To handle litigation costs, companies often try to cut labor costs, increase review rates, and group documents together. However, each of these approaches can only do so much. For instance, it’s risky for companies to save money through temporary attorneys or LPO companies. Though the strategy is cost-efficient, it creates new challenges surrounding logistics, data security, attorney-client privilege, and oversight. The second method was increasing the speed of review. This method holds some promise, but its efficiency depends on the type of review. Automated review is great at accelerating the process, but human review speeds are harder to manage. At best, an expert review can review 100 documents per hour. Yet, the benefit of speed comes at the chance of comprehension errors. Grouping documents isn’t an efficient solution either. The technique uses computerized technology to categorize similar documents together. Though this method is good for organizational purposes, it does nothing to minimize the volume of data. [3]

Cost-Saving eDiscovery Strategies

  1. Don’t spend too much time on search term negotiations. It’s easy for opposing parties to lose time and money while fretting over each search term; however, this practice forces counsel to work overtime to meet deadlines. Consequently, companies will have to pay higher attorney fees. The best solution would be to agree on a handful of search terms and run the data through machine learning systems for review.
  2. Avoid overusing issue coding. Though issue codes are useful for organizing documents, excessive issue coding makes the review process slower and more expensive. Consider limiting the codes to 8-10 per document.
  3. Eliminate unnecessary attachments from important documents (i.e. company logos and icons). These attachments can be eliminated manually or through a modern data processing system. [4]
  4. Engage in the discovery process as soon as possible. By contacting legal counsel early on, companies can reduce the time and money needed for processing and review.
  5. Stay prepared for the possibility of litigation by instructing employees on storing and accessing important documents. This method will save time and money by making the documents easier to find. [5]

 

[1] “Reducing eDiscovery Costs” Whitepaper, Canon Discovery Services, 2018.

[2] Sarah Gayda, “How Law Firms Can Proactively Reduce eDiscovery Risk & Cost,” Iltanet, May 21, 2021.

[3] Nicholas M. Pace, Laura Zakaras, “The Cost of Producing Electronic Documents in Civil Lawsuits,” RAND Institute for Civil Justice, 2012.

[4] Lisa Prowse, “Review is Not the Most Expensive Part of E-discovery,” KMWorld, October 29, 2020.

[5] Scott Carvo, Madelaine C. Lane, and Janet Ramsey, “Creative Ways to Cut Down on E-discovery Costs,” Grand Rapid’s Business Journal, September 4, 2020.

Document Review in a Remote World

COVID-19 has transformed the document review process. Traditionally, document review was conducted in person by experts at review centers. As COVID-19 rates increased, fears for individual health and safety mandated the transition to remote review. Though remote review became a sudden necessity, it’s not a new concept. The transition began long before the pandemic at a slow but steady pace. More and more organizations transitioned their discovery to the cloud after recognizing the financial and security benefits. Even without the pandemic-induced acceleration, the trend would have accumulated more momentum with time. Nonetheless, organization that were unprepared or on the fence were suddenly faced with new challenges and security demands. No one knows if remote review will be the new “normal.” It’s too soon to judge the permanency of the change. For now, organizations should recognize the benefits of the opportunity and adjust their review procedures accordingly.

The Benefits of Remote Review

  • Through remote operation, document review has become more flexible than ever. Talented experts from various states can provide their expertise. Organizations with remote review are not restrained by geographical limitations when seeking qualified providers. The geographic freedom also eliminates the need to pay for a provider’s travel and lodging.
  • Providers have shown increased morale and productivity due to greater flexibility with their hours and breaks. They are also spared from commute expenses. Through happier employees, organizations can raise the efficiency of their review process.
  • Through remote review, organizations gain cloud scalability. Resources and storage space can be altered to quickly meet changing demands.
  • By reducing the production of discoverable copies, remote review can offer some security advantages. Organizations can also strengthen their  security by using multifactor authentication tools. [1]
  • Remote review minimizes the risks associated with employee movement. The workforce is like a revolving door; new employees constantly join and leave their jobs. Though this cycle is normal, it often leads to the accidental corruption or destruction of valuable data. Since remote review is convenient and flexible, it often improves employee retention. [2]

Tips on Handling Document Review

  • Optimize communication among counsel, reviewers, and clients through collaboration tools and teleconferences.
  • Collaborate with your team to create a comprehensive plan tailored to your security and operation needs. This plan should address topics such as staffing, training, and oversight measures.
  • Before establishing a review plan, ask your providers about the quality of their review space and security measures. [3]
  • Consult with your clients and partners as you draft your remote review policies.
  • Keep your data secure through a VPN, multifactor authentication tool, and/or an access program. [4]

 

[1] David Greetham, “Remote eDiscovery: Pandemic Accommodation or Improvement,” Above The Law, May 29, 2020.

[2] Antonio Rega, “Understanding the E-Discovery Implications of Employee Status Changes,” Today’s General Counsel, April 7, 2014.

[3] Jonathan Hurtarte, “Insight: Covid-19 and E-Discovery Challenges With Remote Document Review,” Bloomberg Law, May 11, 2020.

[4]  SKJ Juris, “Impact of Covid-19 on Remote Document Review,” SKJ Juris, 2020.