One of the biggest challenges for modern eDiscovery is the sheer volume of Electronically Stored Information (ESI) most organisations have in play. This volume has made the traditional method of Early Data Assessment (EDA) – whereby custodians are first identified, and all their data collected and ingested into a review platform before EDA begins – almost prohibitively time consuming and expensive.
Thankfully, today’s technology offers a much better alternative, known as in-place EDA.
What is in-place EDA?
Where old-school EDA requires data collection before assessment, in-place EDA enables investigators to perform all the necessary EDA workflows without moving the data from its original location and being exposed to the associated risks and costs in doing so.
To a large extent, it is the very fact that the likes of Microsoft 365 provide a platform-based approach, containing much of the common business data, that makes in-place EDA so viable. Whereas previously data would need to be collected from multiple sources, it is now largely in one place, enabling large portions of typical ESI to be analysed without being uploaded elsewhere first.
Tools like Microsoft Purview eDiscovery (Premium) can now be used to identify persons of interest and their data sources, apply legal holds to ensure data preservation, and even conduct preliminary deduplication, filtering (by keyword and other parameters) and clustering without moving or copying so much as a single file.
Read more on the current capabilities (and common pitfalls) of EDA, here.
Key benefits of in-place EDA
One of the biggest benefits of in-place EDA is that it can be performed much earlier in the broadly accepted Electronic Discovery Reference Model (EDRM) timeline, as it doesn’t require any preliminary data collection.
This enables organisations to more accurately predict the amount of potentially relevant ESI that will need processing and review – a valuable data point for budget purposes that can also directly affect decisions on case viability during Early Case Assessment (ECA).
In-place EDA’s ability to deduplicate, focus and organise large datasets for more efficient collection, processing and review can also significantly reduce the overall cost of eDiscovery.
Let’s not forget risk, either. Retaining data within the organisation’s Microsoft 365 security and compliance boundaries means the appropriate protections remain in place, throughout – a potentially significant benefit for high-risk/highly-regulated industries.
In-place EDA capabilities in Microsoft Purview eDiscovery (Premium)
Microsoft has become an increasingly competitive relevant solution provider in the eDiscovery space. Microsoft Purview eDiscovery (Premium), in particular, offers some astounding features for EDA.
Our favourite capabilities include:
- reconstructing Microsoft Teams conversations
- collecting Cloud-based content shared through links or modern attachments
- collecting from third-party sources imported/archived in Microsoft 365 by data connectors
- importing external custodian data from file servers, PCs and laptops
- performing deep indexing and Optical Character Recognition (OCR) of unindexed content
- leveraging sensitive data types and trainable classifiers (e.g. gifts & entertainment, harassment, money laundering or threats etc)
- monitoring custodian activity within Microsoft 365
- identifying themes and concepts in the data
- identifying potentially privileged content
- providing machine learning algorithms to help identify relevant content
While not strictly an EDA capability , Microsoft Purview eDiscovery (Premium) also supports in-place custodian- and non-custodian-based litigation/eDiscovery holds. This is invaluable for preventing intentional and inadvertent spoliation, before, during and after EDA is completed.
Adam Bown, Salient Discovery’s Head of Forensics and eDiscovery, gives an overview of Microsoft Purview eDiscovery in our recent webinar – watch it here.
Machine learning in Microsoft Purview eDiscovery (Premium)
Microsoft Purview eDiscovery Premium’s machine learning capabilities deserve separate mention for their ability to safely – and often dramatically – reduce the amount of data identified during EDA for processing and review.
Thanks to capabilities like review set queries, smart tags, analytics and technology assisted review tools, investigators can cast a much wider initial search net before culling data back to the most relevant results only.
This helps build a far more comprehensive picture of the matter at hand, while subsequently streamlining the review process for more effective – and cost-effective – eDiscovery.
Ready to explore how in-place EDA could drive down eDiscovery costs in your business? Check out our Microsoft eDiscovery training session.
