Richard L. Reiter and Adam L. Sheps ()
With the advent of the Internet of Things (IoT) and Big Data, the days of producing paper discovery are coming to an end. What has grown with the transition from paper to electronic discovery is the amount of information being produced. IoT is the network of physical objects that feature an IP address for Internet connectivity, and the communication that occurs between these objects and other Internet-enabled devices and systems. As the IoT continues to mature, the sheer magnitude and complexity of information will become more difficult to govern. As a result, it is important that businesses properly manage their data to avoid incurring unnecessary litigation costs that can consume valuable employee time, funds and other corporate resources. Through internal and external collaboration, businesses can intelligently and efficiently manage the flood of information generated by IoT to ensure that they do not drown in avoidable litigation costs.
IoT Data Is Viewed as the Key to Understanding Consumers and Achieving Increased Profits. Over the past few years there has been substantial investment in IoT by businesses because of the increased profits associated with knowing consumer behavior. As the use of and reliance on devices such as smartphones and home electronics, tablets and mobile health trackers continue to rise, the amount of data accumulated is growing exponentially. These smart objects continuously generate data that is transmitted over the Internet. Businesses use these multiple data points along with Big Data to create a more personal bond with their consumers. By strengthening their relationships with consumers, businesses believe they can create value that will result in the creation of additional revenue and corporate profits.
A prime example of IoT generating new profits is seen in the tale of Jane’s delayed purchase of a new blouse. Jane saw the blouse in the store window of her favorite national clothing retailer on her way to work and entered the store to consider purchasing it, but decided not to because she did not want to pay full price. End of story? No, IoT can persuade Jane to purchase the blouse. The following morning as Jane walks to work, she approaches the retailer’s storefront and her smartphone vibrates. Aware of her interest in their product through geo-location software, the retailer sent Jane a personalized discount via text message that reads: “Just for you, today only, receive 15 percent off your purchases.” Jane looks up and sees the blouse. She enters the store, uses the discount and walks out a satisfied customer. The retailer is similarly satisfied with its IoT success.
The benefits of IoT are considerable. How many times have you been lost and needed directions? How many times have you wanted a cup of coffee but didn’t know if there was a coffee shop in the area? IoT devices make it easy for you to type in your request or simply ask your new best friends—Siri, Alexa, Cortana and Google Assistant—for the answer. Within seconds, a kind and reassuring voice acts as your gateway to IoT to satisfy your immediate desires and reinforces your relationship with the business.
Growth of IoT Explodes With a Corresponding Increase in Costs of Discovery. According to Gartner’s forecasts, IoT will continue to explode. It is estimated that in 2017 there will be 8.4 billion connected devices in the world, a 31 percent increase from 2016. Shockingly, Gartner expects the number of connected devices to more than double over the next three years as connected things increase to 20.4 billion by 2020. By 2018, Gartner reports that 70 percent of mobile professionals will conduct work on personal smart devices. Correspondingly, the costs of litigating will rise with the increase in new IoT-generated data as businesses struggle to catalog this information, store it and access it again when needed.
Businesses also will need to rethink their document retention/destruction policies to manage the flood of information inundating their servers. Awareness of the types of data being collected, the length of time for data retention, the location of the data and efficient data management is essential in the competitive marketplace. Failure to properly account for the data could result in businesses wasting significant resources searching for data during the course of litigation that could have been easily located if properly maintained and cataloged.
To avoid incurring unnecessary discovery costs due to poor data management that can result in litigation costs exceeding damages, businesses should engage in internal and external collaboration. Open dialogue with internal departments, partners and vendors is essential to success in the IoT environment. Although costs can be mitigated through products such as insurance, ultimately there is no substitute for sound, proactive information governance. Even if a business has insurance coverage in place for a claim, its financials will likely be impacted by a significant increase in premiums if IoT data causes insurance claim expenses to skyrocket, including discovery and other litigation costs. Businesses must intelligently balance their data management and costs to protect their profitability and long-term financial welfare.
Counsel Should Proactively Attempt to Limit Unnecessary Data to Reduce Litigation Costs. One way to manage IoT discovery issues is for counsel to collaborate with one another at the beginning of the lawsuit. By clearly defining the parameters of discovery, the parties may narrow the pool of relevant data and avoid incurring unnecessary costs associated with sifting through information immaterial to the dispute. If the parties are unable to reach an agreement regarding the scope of discovery, judicial intervention may be necessary.
Minimizing Discovery Costs Through Proportionality Arguments and Technology. Courts have provided guidance on how an IoT discovery dispute involving a significant volume of data may be resolved. Federal courts, pursuant to Rule 26, will weigh the burden and benefits of producing the information under the “proportionality” test. However, just because the amount of information demanded for discovery may be substantial and expensive to produce does not mean that the court will absolve the parties from producing the requested discovery. See John B. v. Goetz, 879 F. Supp. 2d 787 (M.D. Tennessee 2010) (applying the “proportionality” test in a class action lawsuit, the court held that the factors weighed in favor of ordering the production of electronic data that defendant claimed would cost $10 million to produce). Therefore, there can be no absolute substitute for a business efficiently managing its data to avoid significant discovery costs.
There are mechanisms available to assist businesses in efficiently managing discovery costs if production of extensive IoT information is required. Historically, parties use electronic solutions that reduce human time to expedite the discovery. By employing keyword searching, concept searching and predictive coding, counsel are able to narrow the number of documents responsive to discovery demands. Predictive coding is a software-driven machine learning process that takes human-entered information and applies it to a larger dataset to identify and eliminate irrelevant and non-responsive documents. These tools will assuredly be incorporated into IoT discovery as businesses struggle to manage the increased data volume.
The explosion of data from IoT will result in the implementation of new marketing strategies to maximize revenue and profitability. The impact of the anticipated data aggregation on discovery will be substantial. We already have witnessed IoT discovery in legal battles. Recently, in an Arkansas criminal action the government sought the production of recordings made by Amazon’s Echo smart speakers as part of an investigation as to how a 31-year-old man died in a hot tub in a friend’s backyard. Amazon initially opposed the production of the IoT information, claiming that it required a valid and binding legal demand to be properly served and that the government’s demands were overly broad and inappropriate as a matter of course. However, Amazon ultimately produced the information when the defendant authorized Amazon’s release of the recordings. Interestingly, investigators also are using information from a smart water meter as evidence that the defendant’s increase in water usage in the middle of the night suggests a possible cleanup around the crime scene.
Information Governance and Insurance Can Help Mitigate IoT Discovery Costs. Much like businesses seeking to create a consumer profile to close a sale or law enforcement looking to bring a criminal to justice, plaintiffs’ counsel will surely attempt to aggregate IoT data to support their claims. Businesses must be ready with strong information governance protocols in preparation for well-funded plaintiffs pursuing multiple IoT data sources in an effort to hold the business liable.
There is little doubt that IoT discovery will plague the legal world into the foreseeable future as plaintiffs incorporate this new data source into their discovery plans. The question is how businesses will respond. Will businesses be ready when discovery requests in a discrimination action against a manager demand the production of recordings made by a smart thermostat that recorded the manager making discriminatory statements outside of the office? Or when a smart TV records a senior manager’s statements about misappropriating funds? Or when a smart car records a marketing director discussing a new advertising campaign that the plaintiff claims is a false advertisement? Litigation is about to get significantly more personal and expensive as new data sources percolate into discovery.
To the extent these costs cannot be avoided, businesses will need to manage these new expenses and work with their insurance brokers to ensure that their coverage mitigates the costs associated with IoT discovery as businesses adapt their information governance in response to this evolving discovery platform. Ultimately, though, there is no substitute for good information governance practices.