By, Robert Keeling, Partner at Sidley Austin in the Washington DC office and Co-chair of the firm’s E-Discovery Task Force
One of the most promising areas for use of predictive analytics is mergers, acquisitions, and divestitures. For many of the same reasons predictive coding has steadily gained acceptance in litigation, predictive analytics has applications for both buyers and sellers in all phases of the deal lifecycle.
For most companies, the massive volumes of data created and retained in the ordinary course of business drive up costs and risk and impair efficiency and productivity. For companies contemplating a sale, merger, or divestiture, they pose even greater challenges.
The same technologies and workflows that have gained acceptance in the litigation context can be deployed much earlier in the information lifecycle to improve information governance.
The same algorithms and other technologies that are trained to classify documents as responsive or nonresponsive in discovery can be trained to make similar distinctions in other areas, such as whether a document is a contract or not, contains intellectual property or not, is a personnel record or not, and so on.
Similar to document discovery in litigation, due diligence is often the most labor-intensive and costly aspect of legal services in transactions.
Once the relevant data stores have been indexed, the seller can use substantially the same technologies and workflows as are used in e-discovery to identify documents responsive to the buyer’s disclosure requests.
The enhanced precision that results from using predictive analytics allows the seller to expand the scope of its search while still requiring eyes-on review of far fewer documents than would be required in a traditional linear review.
By expanding the scope of its search, the seller reduces its own risk that responsive documents have been overlooked and also provides greater comfort to the buyer that its diligence needs have been satisfied.
With the advent of predictive coding and similar technologies, a buyer’s requests for specific documents today could be replaced by requests that the seller identify and provide access to data repositories likely to contain the information sought by the buyer.
Any approach that significantly increases the buyer’s access to the seller’s information should include measures designed to guard against the unintentional production of privileged documents.
Further, in return for such broader access, the seller might ask for narrow representations and warranties or more limited indemnification obligations in the transaction agreement.
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