Will predictive analytics become the hero in eDiscovery?
eDiscovery is an expensive business problem. I recently did some research on analytics and what I found was that predictive analytics is being touted as the next ‘breakthrough’ technology to solve eDiscovery. Based on research, many text analytics vendors are turning to eDiscovery as the new cash cow. Don’t blame them. It is a very time-consuming, risky, and expensive activity.
What are some of the snippets I found?
- Fortune 500 companies will have, on average 125 lawsuits at any given time (National Law Review)
- The average cost in US dollars is $1.5M – $3M
- eDiscovery is expensive, time-consuming, and risky
- Keyword search captures only 33% of relevant content resulting in the retrieval of potentially a large amount of documents that are not weighted nor ranked based upon their relevance (IDC)
- Legal professionals are less than 20% to 25% accurate and complete when searching and retrieving information from a heterogeneous set of documents. (David C. Blair & M.E. Maron)
- 47% of organizations admit that their email retention and hold policies expose them to risk (AIIM)
- Only 12% of organizations feel confident they store only what they need to store (AIIM)
- 42% of organizations are not confident about what to delete (AIIM)
All in all, eDiscovery is a mess of a task. Although simple is not always the best approach. I do wonder about using predictive analytics? It does not appear to be an end user tool, but maybe that’s not what organizations need.
What do you think?
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