Litigation for the claimant is money to be won. This is the strongest business case for improving legal data intelligence. Creating workflow efficiencies and reducing legal spend are important insomuch as we continue to think about legal and compliance as just a cost center within the organization. Arguments for reducing risk are valid, but they are not compelling enough for c-suite to improve the management and investigation of legal data. The conversation needs to shift from reacting to problems, to finding opportunities. This includes identifying litigation opportunities, uncovering hidden risk, and educating business leaders to begin thinking about their data like a capital asset.
Much of the legal world is reactive. Though there are proactive litigants, a lot of what occurs within a legal department could be filed under ‘reacting to events.’ Even the legal team’s existence is a reaction to company growth. Initial labor investments are generally allocated to sales. Only when a company absolutely needs legal professionals does it begin to employee them. A company’s ability to identify opportunities to litigate for money owed is limited to the quality of its data intelligence. It also reveals some fundamental requirements for effective information governance: an accurate and current inventory, including internal and external legal data with the potential for economic benefits. Organizations without sufficient data governance are unable to leverage it as an asset.
The first mental roadblock to monetizing information is a failure to think beyond selling it. Once an organization can intelligently consider their legal data, they can identify money owed to them from other parties. This becomes an opportunity for increasing revenue. Further to the direct monetary opportunity, improving information governance reduces the cost of hosting and investigating data. When an organizations data is suitable managed, legal teams can turn the data into AI models. These models can then be deployed across the organization for a variety of use cases, including uncovering compliance and regulatory risks where a lack of awareness could otherwise result in billions in fines. The legal services industry should help its clients understand their legal data as an asset class that is replicable, highly reusable, easily transferable, and ripe with economic potential.
The truth is, you’re indirectly monetizing information only if you’re measuring its economic benefits. Measuring this value grows the business conversation between legal and c-suite. The data which corporations and law firms hold in both physical and virtual environments expands by size and type every second. With regard to legal data, much of it is dark in nature, meaning it is collected at scale during the course of business but remains in archives where it is generally not sufficiently structured for analysis. This includes emails, contracts, documents, and other intellectual property. Legal services can enhance their clients results through helping them understand their data lakes so they can eliminate ROT data, reduce hosting and storage fees, and organize the data into the context of the firm’s goals. The data can then be refined and leveraged for economic gain.
The growth in data has not only created the goldmine, it has also gone a long way to improving the quality of the miners themselves. Artificial intelligence has been busy meeting this challenge. A key ingredient for AI innovation is data. Today’s legal service provider should have access to technology which can transform your data assets into AI models that take advantage of the data’s unique characteristics. Just like a successful mining operation needs great equipment, lawyers and data analysts need AI tools that mimic the way our human brains understand language. The economic potential of legal data is too great to accept substandard solutions, so the tools service providers use should be as contextually accurate and efficient as possible.
By instituting a process that combines comprehensive governance with intelligent data mapping, companies can attribute measurable economic gain to the data itself. Generally, this takes the form of realising money owed, attributable cost savings, or reduced risks. The value of the information needs to be considered in the context the resources employed to host and explore it as well. This drives the need for effective data analysis through the creation and deployment of reusable AI models. Thankfully, the mystery of this technology has been removed for some time. AI models have been used in eDiscovery for years to learn from the features of legal data and containerizing it. The models can then be reused to reveal critical insights, saving the cold start problem for law firms and legal teams.
A failure to manage data with the same discipline as traditional assets is one big roadblock to monetizing information at an enterprise level. Few organizations have been able to complete the transformation from fixation of the tired triumvirate of people-process-technology to a digital, information-driven business. Until senior executives, and boards, go beyond merely talking about data as a key corporate asset, it will continue to be a second-class business resource. After all, if an organization managed its other assets with the same lack of discipline as its data, the executive team would find themselves under greater pressure to implement solutions.
Understanding your legal data at scale requires an intelligent information governance approach with a central focus on AI models. Legal teams need to be equipped with the most contextually accurate AI technology in order to identify litigation opportunities with confidence and ease. But presenting this as an efficiency and risk reduction project is insufficient to capturing the attention of key stakeholders across the organization. To begin this process, we need to think proactively about the activities of our legal and compliance teams. Reducing their resources will only serve to an organizations detriment as their competitors build robust connections between legal, business, and IT.
Delaying the conversation between legal and c-suite not only reduces the ability to find opportunities to litigate, but also increases the organizations exposure to compliance and regulatory risks that lurk within their pools of data. This is a failure to see beyond the obvious in a world where the risks to delay increase every moment. If the value of data is only communicated in platitudes, then there is a greater internal problem of a failure to communicate. This cannot last, and a more effective organization will understand that data has not only removed the walls defining departmental roles, but it has also opened the organization for greater awareness of how the sausage is made. A solid information governance approach starts with a vision – a vision for the possibilities of how information can add economic value, or in other words: be monetized.
