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Document Management Systems: Application and Integration

We recently covered the basics of document management systems (DMS). A DMS is an important tool for an organization of any size, and in a world where the amount of digital data multiplies seemingly every day, they will remain a necessity. This necessity has already led to standardization of documentation practices, and even to government regulations of document management.

The necessity of DMS has also naturally led to market competition, with enterprise-level DMS such as NetDocuments, SharePoint, Box, and iManage among the best-known examples. Many of these systems are hosted on the cloud, thus increasing accessibility options and flexible data storage beyond past enterprise systems that were more restricted by localized infrastructure.

An Analogy for DMS

A DMS keeps track of document metadata, and can index documents based on their metadata and other embedded keywords. Eric Detterman, VP and Head of Global Products here at LexPredict, provides a useful analogy for understanding what a DMS accomplishes, by way of MP3 music files and the data they carry alongside the music itself:

Let’s say you have 500,000 songs in MP3 format in a single folder on your hard drive. You want to find all songs that are either “genre=reggae” or “artist=Bob Marley”. Tools exist that can identify that info by “listening” to the song hundreds of times faster than a person. We set the metadata (e.g. genre and song) on each file. The end result is that you can now search for the songs you want.

Document management systems consist of, at a base level, an underlying file and some metadata about that file that are connected some way. So a DMS will not only have a link to the raw file, but will also have a set of structured data about that file.

Eric Detterman

Examples of DMS

There are dozens of document management systems, each with their own strengths and weaknesses. Below, we introduce a few of these widely-used systems.

NetDocuments

NetDocs is a cloud-based document management and email management platform. It’s designed for security-minded professions like medicine, finance, and law. NetDocs has certifications in multiple jurisdictions across the English-speaking world and also provides encryption at the document level.

SharePoint

Microsoft SharePoint is a browser-based collaboration and document management platform. It uses Microsoft’s OpenXML document standard for integration with Microsoft Office. Document metadata is also stored using this format. SharePoint uses various APIs, such as REST, SOAP and OData-based interfaces.

Box

Box is a cloud-based document storage and management system. It’s built to be able to comply with various industry-specific security protocols (e.g. GDPR, HIPAA, FedRAMP). It also has some machine learning integration.

iManage

iManage runs on SQL databases and SQL servers. It requires a lot of server infrastructure to run well, but has both on-premise and cloud options. It has a windows-esque document management interface, with storage, search, and retrieval. It incorporates email management, and also has OCR capability for handling scanned documents.

DMS Integration

The power of a DMS also lies in its integration with other programs – think Adobe and Microsoft products – to make labeling, storage, retrieval, and search more seamless. Whichever DMS your organization uses, we’ve designed ContraxSuite and LexNLP to be able to integrate with it.

Many document management systems are browser-based, so the overall goal is to integrate ContraxSuite and LexNLP with a DMS to help firms get insight into their documents without having to export those documents and then re-import them.

Use Case: Extracting Settlement Amounts from a DMS

Let’s turn now to a common use case we’ve encountered. Legal organizations often wish to build models in order to predict litigation outcomes. Such prediction can lead to better-informed decisions about settlements, and the proper amounts for settlements.

Let’s say we wish to predict settlement agreements for wrongful termination suits. A client sues their former employer, and they then settle for $498,000 for one type of damages, and $84,000 for another type of damages. The settlement agreement that has that information on it – employer agrees to pay former employee X amount of dollars for the specific damage types – needs to first be identified as a settlement agreement. But in a DMS, that document might not be properly tagged yet. Now multiply this problem by however many settlement agreements might be in the DMS.

First, we need to be able to identify all documents in the DMS that are settlement agreements (and, additionally, identify the documents that aren’t). A DMS is a great tool to organize documents by client and/or by matter, making search and retrieval easy. But search and retrieval are only as good as the initial input, which is prone to all kinds of human error (e.g. what if someone accidentally misspells “settlement” when running a search on a large document corpus?). LexNLP, the natural language tool at the heart of ContraxSuite, can catch those sorts of errors. But uploading the contents of an entire DMS into a separate software suite doesn’t sound very appealing, either. That would require a lot of computing resources and manpower. And more human error can occur in the process of exporting, importing, running an analysis, then re-exporting and re-importing.

Simplify with Integration

Software integration reduces all that extra traffic in data, and the many errors that may come with it. Integration allows ContraxSuite to structure information from a DMS, and have LexNLP analyze it, then send it back to the DMS all without having to migrate data from one system to another and back again. “Typically, we ask a client to give us all of their settlement agreements as their DMS had them classified. We then build a model to see whether that’s the full list or not, and then we go through and extract out the information from the actual settlement agreements,” says Detterman. But with software integration, this process becomes much more efficient. Currently, LexPredict builds predictive models based on data supplied by our clients. In an ideal situation, clients could instead integrate their large DMS directly with ContraxSuite, streamlining their processes and workflow.

Conclusion

We at LexPredict are making it possible to integrate a DMS with ContraxSuite. This is the next logical step in bringing greater functionality, and greater analytic insight, into legal. Contact us today for more information about how you can implement ContraxSuite and LexNLP into your organization’s DMS, and start getting the most from your data.

 

About LexPredict

LexPredict is an enterprise legal technology and consulting firm. Our consulting teams specialize in legal analytics, legal data science and training, risk management, and legal data strategy consulting. We work with corporate legal departments and law firms to empower better organizational decision-making by improving processes, technology, and the ways people interact with both. We develop software and data tools, and also offer execution and education services.

LexPredict has a number of software and data products, including LexSemble, ContraxSuite, CounselTracker, and LexReserve. These products assist organizations with early case assessment and decision trees, contract analytics and workflows, outside counsel spend management, and case valuation. LexPredict also offers advisory and capital services for legal tech startups through its LexGen Ventures arm.

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