The proverbial locker room of eDiscovery was the last place I expected to find myself when setting out to write this blog post one not-so-fine Monday morning. But alas - here I am! As such, I am taking this opportunity to answer, once and for all, the question - does size matter when it comes to eDiscovery?
Before continuing down this road it should first be said that yes, of course, size matters when it comes down to the tailoring of our services to meet your needs. The larger and more complex a problem is, the more tools, support and expertise it is likely to need. However, in general, I have found it is rarely a worry about being too big that prompts this question, so perhaps it would be better if we rephrased the issue... Is my project big enough for eDiscovery?
This then leads me to ask one very important question, how exactly do we define 'big enough'?
During my time in eDiscovery, I have learned that a 'small' eDiscovery project can be defined as small for a number of reasons. Firstly, and most commonly, your project doesn't bring your firm a lot of money in terms of your billable hours etc. (small in monetary value), secondly, you have very few custodians from which to collect data, and thirdly, you actually have very little data after collecting. In at least two of these three examples (and, more often than not, all three!) the determined size of your project actually has nothing to do with the amount of data that requires hosting and reviewing.
What is a small eDiscovery project?
While this definition appears to vary between sources, here at Altlaw we define a small project as anything with less than 3 custodians (people from whom you collect data) and 15,000 records/documents. But, does this definition mean these projects are too small for eDiscovery... of course not!
Another factor to consider when deciding whether or not to use eDiscovery tools and processes is the opposition's data. You may have a small project by both your standards, and the definitions, but the opposing team may have collected and produced far more data than you. What do you do in this instance when it comes time to exchange?
