For years, concept search in electronic discovery has been like concept cars at auto shows: Cool. Slick. The thing that everyone is talking about.
But not ready to move to the assembly line and be put into production.
Like a concept car, concept search has been based on a lot of good ideas and shown a lot of promise. However, it has failed to move beyond a few edge use cases and reach mass adoption in the e-discovery market. Why is this the case?
It’s not been because it’s an unproven idea or that the basic technology hasn’t been available. In fact, the core algorithm that underlies most existing concept search technologies has actually been around since 1988, when latent semantic analysis (LSA) was first patented by a team from Bell Labs. Over the last 20 years, dozens if not hundreds of companies have sprung up to apply concept search to the broad area of enterprise search and to e-discovery in particular.
To understand why concept search has never taken off, it’s always interesting to look for parallels, and the parallel du jour is social networking. Readers of David Kirkpatrick’s excellent book The Facebook Effect and (perhaps to a lesser, more fictionalized extent) viewers of the movie The Social Network understand that Facebook was far from the first social networking site (remember MySpace? You won’t admit it, but I know you do). But, despite being several years late to the party, Facebook somehow took the core of the social networking idea and presented it to users in a way that really allowed it to “cross the chasm” to the mainstream market.
What are these unmet customer needs?
Ease of use: Historically, concept search has been relatively easy to use in the strictest sense of the word – you type in some terms that represent your concept, and you get a set of search results back, along with some related terms and/or clusters of related documents. Simple, right? The issue is that in most cases that’s not what the user really wants to do. Because concept search is inherently “fuzzy”, users want to be able to refine their concept based on the feedback that they got from their initial search. Concept search, just like keyword search, is an iterative process, and prior-generation technologies have not allowed for that form of iteration.
Precision: Traditional concept search increased recall when compared to just keyword search, but it came at the cost of precision. The refinement process addresses this issue by allowing intelligent human input to guide the concept search process. You get the best of both the recall and precision worlds with vastly diminished time and effort.
Defensibility: Even more important than ease of use and precision is defensibility. Defensibility, for those new to the term, isn’t so much about whether the way the algorithms work is known and able to be understood. They are, and aren’t that complicated. Rather, defensibility is about reasonableness: was the concept search a reasonable way of determining which documents are responsive?
Without the ability to define your concept in an interactive manner, we believe that the answer has historically been “no”, making concept search nice in theory but unusable in actual legal practice. Transparent Concept Search promises to change that. The end result is a more defensible search process that yields both greater recall and greater precision, enabling users to more quickly analyze case facts, rapidly identify key documents that may have been missed, eliminate irrelevant documents, and prioritize the most relevant documents for review.
Low cost: Finally, never underestimate the value of “free” in helping meet the ever-important unmet need of cost predictability and control. Historically, vendors have charged price premiums (often substantial) for concept search. Trying to charge a premium in e-discovery for something that doesn’t fully meet the customer use case and isn’t defensible, and it’s a recipe for low adoption. However, provide a highly useable, effective, and defensible capability as part of the core functionality of today’s leading e-discovery platform, and it starts to look very attractive indeed.