Structured information is key Olegl Golovneiv
Today, businesses in all sectors have to manage an enormous amount of information. IDC estimates that 2.7 zettabytes of digital data is stored around the globe – a 48% increase from 2011. Furthermore, an estimated 80 per cent to 90 per cent of this data is unstructured (email, social media, documents, phone conversations, etc). This increase in unstructured data can be particularly challenging for in-house legal departments and their law firms as they are required to find, preserve, review and disclose information in short time frames when requested by a court or a regulator.To overcome this challenge, law firms and their corporate clients have to establish best practices to manage the growing amount of unstructured data their cases involve by leveraging an effective information governance strategy.
The ability to gain control over data volumes in order to manage and understand data correctly can mitigate risks, reduce costs and save time.
No neat fit
However, unstructured information doesn’t fit into neat rows or columns within databases like structured data; this makes for an extremely complex environment in which to employ effective information governance policies. Complicating matters further, there is currently very limited understanding about what information governance really is. It should be thought of as a cross-departmental framework consisting of policies, procedures and technologies that are designed to optimise the value of information, while simultaneously managing the risks and controlling the associated costs. It requires the coordination of eDiscovery, records management and privacy/security disciplines to make data easily available to employees in order to advance the business, while identifying data that holds no value and actually creates risk by failing to comply with applicable laws and regulations.
Traditional models are sinking fast
Manual approaches to information governance are failing fast. Incumbent document management systems are barely keeping up with growing data volumes, and were not designed with the current variety of unstructured data in mind. In addition, employees are wasting time and money searching for information and recreating content they are unable to find. If a law firm and its staff do not know what documents and data exist within its clients’ in its own infrastructure (including hosted and cloud infrastructure) it cannot interrogate and utilise the data effectively.
As a result, lawyers cannot respond quickly or accurately as required to litigation or regulatory demands. As clients are increasingly demanding better value for money, law firms are under increasing pressure to deliver results within fixed time and budgetary constraints. The traditional approach of employing an army of paralegals to search through information is no longer a viable option. Therefore, it is critical to discover better ways to find, index, understand and act on the vast amounts of information.
A crucial element of information governance is the ability to effectively map data. Law firms must understand where data is stored, and the context of that data, in order to manage it. Then, information must be accurately categorised – without this, it cannot be managed.
However, determining the best approach to categorisation doesn’t come without its challenges. Initially, there seems to be the straight choice between self-categorisation and system categorisation. Self-categorisation depends on employees to declare the type of document they’ve created and decide where to save it. This is an ineffective process as it doesn’t take into account inevitable human error, much less intentional mis-categorisation. In addition, by putting up a barrier in front of a relatively straightforward task, people become disengaged and often do not follow the process. One US lawyer commented, “until they make [document management systems] as easy and as intuitive as saving to your hard drive, people will save to their hard drive.”
Traditional system categorisation isn’t much better. Without human expertise, the system’s capabilities are limited by basic keyword search technology. The shortcomings are obvious – each term is treated as a separate entity so the semantic relations between words and the overall concept of the data are ignored. As such relevant documents can be mis-categorised and lost, or simply not found when searching.
A new approach is required to categorisation, one that combines the best elements of self-categorisation – human judgement – and machine learning technologies. By bringing together the subject matter understanding of legal professionals and machine learning software, the categorisation engine can learn from human confirmations of their suggestions to then automatically categorise new data as it is created. This approach requires minimum effort from the user, providing suggestions for which documents fit which category. It will enable law firms to automate tasks such as data review, analysis and collection, as well as retention, migration, management and deletion.
Categorisation enables effective governance
It is only once information has been successfully and accurately categorised, that policies can be put in place to effectively govern its retention. One of the biggest legal risks occurs if you can’t find all the data an opponent is looking for or if someone inadvertently deletes it. This can translate into allegations of spoliation and destruction of evidence which can lead to losing a winnable case and serious penalties. With effective information governance and categorisation, legal teams can find relevant data quickly and easily, as well as set appropriate retention and ‘defensible disposal’ policies on data.
The key to this process is identifying valuable and valueless information not subject to regulatory retention or legal hold, with enough certainty to be able to delete that data in an automated fashion. By categorising information correctly and implementing retention policies on valued data, law firms can dramatically cut costs on data storage, as well as time spent looking through and reviewing non-relevant data.
By adding intelligence to the information governance process, in house legal teams and their lawyers can reduce litigation costs, minimise regulatory risks and the strain of information overload, whilst ensuring they can effectively meet any eDiscovery requests in a timely manner.
By adopting a strong stance on information governance, legal departments and law firms will be able to establish where data resides and the context of that data, to apply policies for management, retention and deletion. Firms simply cannot rely on humans or software alone. Instead, it is vital that firms look for a solution that provides a better workflow and machine based learning to help drive efficiency. Finding responsive data faster while using fewer resources in the discovery process will lead to more accurate information, quicker resolution of problems and reduced manpower spend.
Dean Gonsowski is Global Head of Information Governance at Recommind