1. Ediscovery & Forensics

Blue Dragon has experience in advising regulators and clients in litigation and regulatory support matters.


  • Data mapping
  • EDRM advisory
  • Information governance
  • Forensic Collection
  • Forensic analysis
  • Affidavits
  • Filtering of data
  • Processing
  • Hosting
  • Analysis & analytics
  • Productions
  • Regulatory advisory
  • Software advisory


  • 2. Case studies


    Blue Dragon operated as technical consultant for a HK regulator with staff embedded in the Regulator. We assisted with ediscovery and EDRM process advising at all stages of the regulatory process using the Relativity® software but also collection including EnCase® & Nuix®.

    Blue Dragon advised an Indian client on Ediscovery process and managed a large case in Relativity out of Hong Kong and London.

    Blue Dragon managed a employee fraud investigation including affidavits and discovered the forensic report supplied by a third party had been wrongly suggestive of guilt.

    Blue Dragon conducted forensic examination of a computer to discover and IT Director’s role in a recent data breach at his firm.

    Blue Dragon were involved in a multi-site Taiwan and China data collection, processing and onsite review case using EnCase, Relativity, Nuix. We helped advise on the creation of an on-site review solution.


    3. Practical Guidance

    We have discovered over the years that several time-honoured principles are generally applied to scenarios which have an ediscovery flavour. These include the following:

  • When you collect data, you must consider the end goal. If it is a pure litigation, all parties are normally informed of the nature and purpose of the collection. If the situation is more in the nature of an internal investigation, the element of surprise can be important, as potentially some of the persons whose data is to be collected may have bad motivations. In this case, it is best to collect evidence widely even if the eventual analysis is done on only a small subset of the data.
  • Keywords are a useful means of cutting down a data set, but many studies have demonstrated the erroneous nature of keywords, and how infrequently using keywords can direct all relevant materials into a subset. There are other means of culling data, including using file filters, date filters, NIST, boolean operators, technology assisted review tools, predictive coding based on iterative learning.
  • If there must be an examination of potentially legally privileged materials, this is time consuming and a strategy should be discussed early on for how to handle the review.
  • There are other sets of data short of privilege that might need to be considered. These might be confidential, subject to a non-disclosure agreement with a third party, or liable to cause some other issue (subjecting a third party to risk, or involving the disclosure of personal data). There may be an overrriding interest to disclosure of such information.
  • Hong Kong courts are not very familiar with a lot of the technologies to do with ediscovery. It is good to ensure someone senior on the vendor side has overseen the whole process so that person is qualified to write an affidavit on the matters concerned and also appear in court if need be as an expert witness.
  • The guidelines in the HK practice direction will help guide through many of the main questions parties should be considering, even if the practice direction does not apply to the case.

  • 4. Proportionality in ediscovery

    Ediscovery is often driven by the need for what one English judge called "rough justice" as opposed to perfect justice. In our daily case work, we discover that not every issue can support the same level of data interrogation. For example, the departure of one employee who may be about to begin a competing business in breach of a restrictive covenant is not going to attract the same depth of investigation, without good reason, that the investigation of a major contractual dispute with liability in the millions or billions of dollars. Hence, we adapt our collection and filtering techniques to the size of the case and the issues at hand.



    Date Created: 1 June 2017   |   Date Modified: 28 December 2017   |  Author: Dmitri M A Hubbard