Data Management Challenges Lawyers Face
Never like now have we witnessed the generation of volumes of such impressive data and never before have so many private companies and public bodies been so exposed to rapid changes in technology and radical and unexpected changes in the environment as they are today. Legal services firms, corporate legal departments and independent attorneys are not exempt from this phenomenon and have as a great challenge to become data-driven attorneys (data driven lawyers). Also called the "new oil" data, it offers enormous untapped potential to create competitive advantage, new wealth and jobs; improve health care; keep us all safer and, in some way, improve the human condition. This is the promise of data, but is data really capable of delivering on this promise? The reality is that data alone cannot deliver on that promise. There is a lot to do for this.
If something characterizes the lawyers' union, it is the amount of documents they have to handle. Today, law firms are faced with the reality of the great diversity of documents that are already being digitally generated, which have to be used in combination with historical physical documents, so traditional practices of handling physical documentation must necessarily evolve, which poses new challenges:
- Changing Consumer Expectations: Many Corporate Consumers of Legal Services Are Changing Their Expectations, hoping that different law firms can work in collaboration, sharing knowledge, which implies the use of practices and technologies that allow data and information to be shared safely.
- Efficiency in Internal Processes: A recent study shows that 60% of surveyed law firms face great challenges in making their internal processes efficient. The location and management of evidence whether in the form of documents, images, videos or audios has become critical, accompanied by the challenge in the consistent and effective management of document and content classification keys.
- Changes in Consumption and Work Habits: The situation we are experiencing as a result of the COVID19 pandemic is forcing us to adopt new remote work schemes, which implies stricter security measures to share information and work collaboratively at a distance.
How does Data Management help to face these Challenges?
When you hear the term data monetization, you generally think of the economic value that can be obtained by selling data or generating a new line of business, however, there are many other lines of action by which tangible value can be obtained from proper use. of the data. There are several challenges you face when you want to exploit the volumes of data that accumulate all the time. Is the data really aligned with the strategic objectives of the firm? Is the data available with the opportunity that lawyers need to obtain reliable answers to the questions that are asked in the firm? Is the data correct to produce information reliable? Are expectations of the data met? We continually hear data scientists express their frustration at not being able to focus on data mining, in "make them talk«, For having to spend much of his time«Cleaning»Incorrect data, which does not meet the expectations of them. It is precisely the lack of adequate data quality that is the main obstacle reported by 200 European companies surveyed by BARC (Business Application Research Center). This survey indicates that one of the main ways to monetize data is by using it to make internal processes more efficient.
How do you bridge the gap between the amount of data being generated and being able to make the data deliver on its promise of value? The answer is in the Data management, a set of disciplines that, formally applied, allow to have correct, reliable and safe data to make it available to those who should be able to use it. A reference to understand what all the disciplines of Data Management imply is the DMBoK (Data Management Body of Knowledge), Knowledge Guide for Data Management that WOMEN (Data Management Association) International has integrated to support the development of Data Management professionals, IT professionals, business executives, educators and researchers. DAMA describes in its framework, how the Data Governance is related to the other areas of knowledge of Data Management: Data Architecture, Data Modeling and Design, Data Storage and Operations, Data Security, Integration and Interoperability, Document and Content Management, Master and Reference Data, Data Warehousing and Business Intelligence, Metadata Management and Data Quality.
There are two analogies that help to understand Data Management, one is the analogy of Iceberg Data Management, in which the tip of the Iceberg represents the visible and attractive part of data usage: advanced analytics, data mining, machine learning, IOT (internet of things), data visualization, BIG DATA and data science. However, this, which is what most companies want to do, requires many other fundamental functions that are represented by the part of the iceberg that is submerged: data architecture, data modeling and design, data security, data governance, metadata management, and data quality management. All of these features are unappealing, they are not usually the ones that reflectors have, but without them the features at the tip of the iceberg are sure to take longer, be more expensive, and require more rework.
The second analogy is one that sees Data Management functions as the foundation of a building. It turns out to be one of the most expensive stages of construction; It is what we do not see of the building; If the necessary resources are not dedicated to the foundation or if the cost or quality of the foundation is spared, there is a risk that the building will collapse in a strong earthquake. The same can happen with organizations that do not have an adequate Data Management base, and it may even disappear.
Document and Content Management
If we are to say which of the various disciplines of Data Management are most relevant to firms in the legal sector, perhaps the most relevant is that of Document and Content Management, discipline closely related to Metadata Management, Data Quality Management and Data Governance.
Top business drivers for Document and Content Management include regulatory compliance, the ability to respond to litigation requests, and electronic discovery. Good records management can also help organizations to be more efficient. The places website Well-organized and searchable that result from effective management of ontologies and other structures that facilitate search help improve customer and employee satisfaction.
Laws and regulations require organizations to keep records of certain types of activities. Most organizations also have policies, standards, and best practices for record keeping. The records include both paper documents and ESI (Electronic Stored Information - Information Stored Electronically). Good records management is necessary for business continuity. It also allows an organization to respond in the event of litigation.
El Electronic Discovery is the process of finding electronic records that could serve as evidence in legal action. The ability of an organization to respond to an electronic discovery request depends on how it has handled records such as email, cats, sites website and electronic documents, as well as raw application data and metadata. Technology it has become an engine for more efficient electronic discovery, record retention, and strong information governance.
A fundamental aspect within Document and Content Management is the control of the records that must legally be kept as evidence that actions and decisions were taken in accordance with established procedures. For proper records management it is convenient to follow the principles GARP (Generally Acceptable Recordkeeping Principles), generated by HARP (Association of Records Managers and Administrators).
It is estimated that up to 80% of all stored data is kept outside of relational databases. This unstructured data does not have a data model that allows users to understand its content or how it is organized; they are not labeled or structured in rows and columns. Unstructured data is in various electronic formats: word processing documents, emails, social media, cats, flat files, spreadsheets, XML files, transactional messages, reports, charts, digital images, microfiche, video recordings, and audio recordings. There is also a huge amount of unstructured data in paper files. The use of digitization techniques for physical documents and textual analysis of these digitizations and all other types of unstructured data becomes essential to speed up and optimize the work in legal firms. Textual analysis allows us to convert unstructured data into structured data that can be analyzed more easily. 
Ethical Data Management
"Doing things right when no one is looking" is the basic premise when we talk about Ethical Data Management. Three essential concepts must be taken into account: the impact on people, the potential misuse of the data and the economic value of the data.
Three principles, based on the Belmont principles, govern the Ethical Management of Data:
- Respect for people: This principle reflects the fundamental ethical requirement that people be treated in a way that respects their dignity and autonomy as individuals. It also requires that where people have "diminished autonomy", special care be taken to protect their dignity and rights.
- Charity: This principle has two elements: first, do not harm; second, maximize potential benefits and minimize potential harm.
- Justice: This principle considers the fair and equitable treatment of people.
Adequate Data Management should be seen as a cornerstone in the transformation strategy of all law firms. There can always be an approach that responds to the needs, size and culture of each law firm. Whether it is a question of firms or professionals in the legal field, 3 practical recommendations could help them to keep in mind the subject of Data Management:
- Check the Data Manifesto for Leaders
- Have as reference the DMBoK
- Explore options for Textual Analysis
Marilú López, Regional Coordinator of DAMA International for Latin America
 Statistics on by Christo Petrov https://techjury.net/blog/big-data-statistics/#gref