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Gathering Early Case Intelligence: Becoming a Digital Archaeologist

Written by Annie Malloy

Updated:

Authors

Matthew Verga, Esq.

Director of Education

About Author

Matthew Verga is an attorney, consultant, and eDiscovery expert proficient at leveraging his legal experience, his technical knowledge, and his communication skills to make complex eDiscovery topics accessible to diverse audiences. A fifteen-year industry veteran, Matthew has worked across every phase of the EDRM and at every level, from the project trenches to enterprise program design. As Director of Education for Consilio, he leverages this background to produce engaging educational content to empower practitioners at all levels with knowledge they can use to improve their projects, their careers, and their organizations.

More from the author

Summary
Despite popular depictions of swashbuckling adventure, archaeological excavations are actually painstaking processes with plenty of documentation and very few whips or fedoras.  Searching for a mixture of the expected and the unknown, excavations involve a range of tools and techniques, from grid searches and traditional hand excavation, to trenching and sampling for stratigraphy, to machine stripping of archaeologically insignificant layers.  All of these methods and more are deployed by archaeologists to uncover important materials, the context of those materials, and the history of the place they were found.

As the volumes of electronically-stored information (ESI) generated by organizations have grown, early case assessment (ECA) has turned, more and more, into a kind of digital archaeology in search of actionable intelligence: trenching and sampling and sifting through enormous digital dig sites trying to map out the layers, find the key players, determine the important facts, unearth the hot documents, and begin curating your case.

Today, it’s not enough for lawyers to know the law and to know our clients, we must also know how to be competent digital archaeologists.  We must be familiar with the range of tools and techniques available to us, so we can know when to sift, when to sample, when to strip, and when to call for the expert assistance of Dr. Jones.

In this White Paper

  • The three early case intelligence activities and goals
  • Sampling and searching tools and techniques
  • Structural analytics, conceptual analytics, and AI tools

Key Insights

  • The importance of identifying unknown unknowns
  • The value of accurate measurement and estimation
  • The nuance of process planning and goal prioritization

Summary
Despite popular depictions of swashbuckling adventure, archaeological excavations are actually painstaking processes with plenty of documentation and very few whips or fedoras.  Searching for a mixture of the expected and the unknown, excavations involve a range of tools and techniques, from grid searches and traditional hand excavation, to trenching and sampling for stratigraphy, to machine stripping of archaeologically insignificant layers.  All of these methods and more are deployed by archaeologists to uncover important materials, the context of those materials, and the history of the place they were found.

As the volumes of electronically-stored information (ESI) generated by organizations have grown, early case assessment (ECA) has turned, more and more, into a kind of digital archaeology in search of actionable intelligence: trenching and sampling and sifting through enormous digital dig sites trying to map out the layers, find the key players, determine the important facts, unearth the hot documents, and begin curating your case.

Today, it’s not enough for lawyers to know the law and to know our clients, we must also know how to be competent digital archaeologists.  We must be familiar with the range of tools and techniques available to us, so we can know when to sift, when to sample, when to strip, and when to call for the expert assistance of Dr. Jones.

In this White Paper

  • The three early case intelligence activities and goals
  • Sampling and searching tools and techniques
  • Structural analytics, conceptual analytics, and AI tools

Key Insights

  • The importance of identifying unknown unknowns
  • The value of accurate measurement and estimation
  • The nuance of process planning and goal prioritization

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