Considering ECA?

In considering the many recent discussions in the legal blogosphere on Early Case Assessment (ECA), the following post is provided for those who may be interested in yet another way of considering ECA – that is considering it as a pre-processing electronic discovery stage of Analytics.

Considering Analytics?  A Short, High Level, “Maybe Not Yet School Book Approved” Definition and Discussion of Electronic Discovery Analytics

While much has been written and presented on “electronic discovery analytics” within the past several years, it appears to be difficult to find both a commonly accepted concise definition of electronic discovery centric analytics as well as a contextual example of where analytics fits within the field of electronic discovery. I by no means claim that I have the “school book approved” answers for these two items, but I would share with you the following thoughts that may help you – as they have helped me – put electronic discovery centric analytics in perspective.

What is Analytics?

Although not listed in either of the EDRM or Sedona Conference glossaries, a definition that seems reasonable for describing analytics in relation to electronic discovery is as follows:

Electronic Discovery Analytics: The leveraging of Electronic Stored Information (ESI) through the use of a particular functional process to both provide context-specific insight that is actionable and to allow for the defensible reduction of ESI volume as early in the discovery process as appropriate.*

Key elements within this definition include:

  • A Particular Functional Process
  • The Provision of Actionable, Context Specific Insight
  • A Defensible Reduction of ESI Volume

A Particular Functional Process

The definition of analytics, while written in a manner that does not narrowly define functional process (thus invalidating the definition with the introduction of new processes), alludes to at least five specific elements that form the “particular functional process” mentioned in the definition. These specific elements include but are not limited to:

  • Indexing – making a list of all the ESI available in the data set.
  • Filtering – getting rid of data that appears to be irrelevant to the case.
  • Near Deduplication – getting rid of “like” data that appears to be available more than once in the data set.
  • Sampling – looking at the ESI on a small scale to determine results that should be indicative of the entire data set.
  • Search Term Scoping – seeing what search term keywords might best be recommended and used for the purpose of searching the data set for responsive files.

Whether employed individually or collectively, these elements appear to be some of the key elements utilized today to help provide actionable, context specific insight and to help defensibly reduce ESI volume for legal professionals.

Where does Analytics fit in the field of electronic discovery?

In seeking to understand analytics within the context of the electronic discovery process, the Waterfall Model of Electronic Discovery appears to be a new, intuitive and easily understood model that positions electronic discovery analytics at the front end of the core electronic discovery elements.

Taking into account the very well respected Electronic Discovery Reference Model, the Waterfall Model of Electronic Discovery designates analytics as an actual stage in the electronic discovery process (vs. the EDRM stage of analysis – which some view as an implied task to be conducted within each stage of the EDRM). This  analytics stage in the Waterfall Model occurs after the actual collection of ESI and prior to the actual processing of ESI and is inclusive of the “functional process” elements mentioned earlier.


While there are other “schools” of thought concerning analytics – this definition and positioning of analytics  as a stage within electronic discovery may help in explaining the overall benefit of analytics – benefits which consist of a reduction of time, risk and cost in the conduct of electronic discovery.

What is the benefit of Analytics?

Time: The Need for Speed

The use of analytics can help legal professionals quickly gain an understanding of potential evidence and seize the initiative in the conduct of litigation. In practical terms, the quicker a legal team can gain an understanding of available ESI, the quicker they can make early case assessments in relation to key questions to include:

  • Does it appear that opposing counsel has an evidential basis for pursuing the case?
  • What type of electronic discovery resources will be needed to conduct a complete document review?
  • Based on FRCP 26(f)¹, what are the timeline requirements for “Meet and Confer” preparation?
  • Based on potential evidence and resource requirements, will it be more cost effective to settle or pursue?

By quickly being able to answer these questions quickly, legal teams can gain the “litigation high ground” and ensure they are making informed client recommendations as early as possible in the litigation process – thus ensuring economy of effort without sacrificing the ability to achieve a desired outcome. Additionally, understanding provided by analytics can also help ensure counsel is prepared to proactively shape the direction of handling ESI during the federally mandated “Meet and Confer” process.

Risk:  More than a Board Game

Litigation is inherently rife with risk, and the complexity of discovery of ESI only increases this risk based on the intricacies of digital data, the continually growing volume of data available, and evolving ESI related law. Managing this complexity requires an understanding of what is an acceptable risk in relation to the time available and the financial resources available. In determining acceptable risk, three of the key concerns of legal professionals are:

  • Will the electronic discovery approach reduce the risk of missing potentially responsive documents?
  • Will the electronic discovery technologies used minimize risks associated with the transfer of data between organizations and platforms?
  • Will the electronic discovery effort be conducted in a legally defensible manner?

In viewing traditional electronic discovery approaches, and with these risk considerations in mind, it appears that time available and financial resources determine the level of acceptable risk and that risk can be reduced though the use of analytics to help reduce the risk of missing potentially responsive documents.

Cost: Show Me the Money

The economics of electronic discovery are such an important factor in litigation that, in some cases, they may drive counsel recommendations as much, if not more, than the actual evidentiary position of the client. Additionally, based on the current economic conditions worldwide, many law firms and corporations have been significantly impacted financially and while litigation related to the financial crisis may be on the rise, there is also a corresponding decrease in the number of discretionary litigation efforts due to cost constraints. With this economic importance in mind, legal professionals not only want to but need to be able to conduct as thorough electronic discovery effort as possible at the lowest monetary cost possible. Key questions needing to be considered when evaluating the financial factor of electronic discovery may include:

  • Based on time requirements and acceptable risk, what is the best electronic discovery approach congruent with firm and client financial resources and cost management objectives?
  • Do we have the electronic discovery systems and expertise in place to conduct the electronic discovery tasks using the best electronic discovery approach congruent with client financial and cost management objectives?

Through an understanding of why the factors of time, risk, and costs factors of electronic discovery are important and how analytics impacts each of these areas, one can truly can see how the use of analytics can have an incredibly significant impact on electronic discovery.

1 Federal Rules of Civil Procedure, Rule 26(f),

* Gartner Research version of Analytics definition adjusted for electronic discovery specific activities.

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