A good solution (software combined with a best practice) is key to a successful E-Discovery project. However, there is no such thing as a perfect E-Discovery solution. There are many different software tools on the market, some of which have been introduced very recently in the US, Australia or in Europe. Also, a software tool requires a best practice and E-Discovery projects have many different facets that require different solutions. Storage, processing, review and even analysis require a cost-benefit analysis involving scale, complexity, available time and budget.

Early Case Assessment

Identifying relevant iformation at the start of an E-Discovery project is an important milestone. Too often it is decided that it is better to collect more information than strictly necessary. Even if Information that is not relevant is filtered out during processing, then still the time (and cost) required for the collection, copying and initial processing stages is not in proportion to result. In such situations it may be useful to consider the use of an Early Case Assessment tool. This is a tool that is able to make information accessible much faster. It delivers less detail but enough to identify what sources are relevant, or not relevant or to determine if important sources are missing before entering the collection or processing stage.


Processing electronic information in an E-Discovery project is reasonably straightforward. Surprisingly, there are many different solutions on the market and there is no single solution that is perfect for all projects. Typicsl questions that must be answered are: What is the volume of information that needs to be processed, what file formats need to be supported, is deduplication necessary, is filtering necessary and if so what types of search queries need to be supported and how fast does processing need to be finished in time for review? What is the best solution to process all data completely and on time with the desired result?


In many projects review of processed documents and emails is the most expensive part of an E-Discovery project. An experienced reviewer can review approximately 500 messages per day with a professional review solutions. For small reviews with a few hundred documents a single-user solution is sufficient. However, a review of 10,000 messages by a single reviewer will take 20 days and review projects can easily get to a multiple of this or even hundreds of thousands of messages. That type of project requires a platform that supports collaborative review so that a team of reviewers can simultaneously review batches. This type of system is expensive and success is not guaranteed. Without a good strategy, proper coordination and quality control reviewers may be reviewing the same documents or apply tags in an inconsistent manner.


Storage of electronic information an E-Discovery project largely determines the processing speed, the amount of manual labor and the project quality. In small, infrequent E-Discovery projects and with strong discipline for procedure in a small project team, it is well possible to work with cheap external storage. For larger projects in which data has to be accessible from more than one workstation it is recommended to store data on centralized fileserver or SAN storage. When faced with the specs of E-Discovery tools storage vendors will try to sell oversized enterprise storage solutions. Such solutions are not cheap and a solution for 10Tb or 20Tb effective storage may cost several ten thousands or hundred thousands of euro's. When taking the underlying process into consideration, it is possible to reduce cost because not all stages in the E-Discovery process require super fast storage.


E-Discovery aims at the discovery of relevant electronic information. After the automatic processing stages have completed, a final filtering stage is implemented with human reviewers. With the continuously growing flow of information and increasing diversity this is too expensive or takes too much time. Henseler Forensics has experience in combining techniques from pattern recognition and data forensics to discover new relations between, for instance, email, invoices and records in the financial administration. This enables the prioritization of information so that reviewers and investigators can focus on important information while progress is better monitored with more meaningful intermediate results.