E-Discovery Tools

Electronic discovery or e-discovery refers to discovery in legal proceedings such as litigation or government investigations where the information sought is in electronic format. The ever increasing amount of litigation, greater volumes of data and a move toward adding in-house e-discovery capabilities require strong tools for e-discovery.

Data is scattered throughout companies and has become progressively more difficult to manage. Companies are dealing with big data, data in shared repositories such as Box.com, data on mobile devices, etc.

Data must be protected during e-discovery just as it does when it is a part of any other business activity. The degree of security risk depends on the nature of the data. Standard business contracts might not be highly sensitive and thus create minimal risk, but exposure of intellectual property that represents the crown jewels of a company could be a major risk.

When legal hold is used effectively, companies can meet their preservation duties, then do targeted collections as needed in the case. Good hold process plus targeted collections can significantly reduce the amount of information that must be reviewed by attorneys, which accounts for 70 percent of e-discovery costs.

Another value proposition in using an automated legal hold solution that is integrated with collections and first-pass review is the ability to re-purpose a collection.

Cloud offerings could be used to centralize all this data in one place for efficient reuse and risk management.

Several trends are contributing to strong growth in tools for the e-discovery. In addition to a group of large e-discovery vendors, many smaller vendors have products that are working well for their customers, and there is also room for new entrants that improve performance or address specific needs.

Each product has particular strengths, and that wide array offers options that can be used very selectively or in conjunction with each other to meet a company’s goals.

Sometimes, legal holds are required. Legal holds are required when a company might reasonably expect litigation and therefore should not delete information that might be relevant to the litigation.

Legal Hold Pro

This application has templates for the system and the database with the contact information for employees who are custodians of data. The system can also be used to track the information and people affected, automate the interviews with custodians, send reminders and release holds when appropriate. It allows to check the information of terminated employees to see if it might be subject to hold, and review responses from custodians to create the collection plan.

The same collection and review tagging could be used again by adding only the incremental data generated since the original one.

As a cloud product, Legal Hold Pro is quick and easy to launch, and is updated frequently.

Technology-assisted review (TAR)

Once a set of documents is located that may be responsive to the e-discovery request, it needs to be searched. The effective use of human skills in conjunction with computer capabilities is a key ingredient in lowering down the volume of data that needs to be reviewed by attorneys or other legal professionals.

Technology-assisted review (TAR), also called predictive coding, is a method for training a computer to spot documents that may be relevant and distinguish them from those that are not.

Catalyst

Catalyst provides e-discovery software and services.

Catalyst Insight is a secure cloud-based platform where clients can search, review, mark and produce documents. It can be augmented with Insight Predict, a predictive ranking TAR 2.0 solution that uses continuous active learning (CAL) to speed the review process by allowing technology to work alongside the judgments that human reviewers make. The solution brings the most relevant documents to the top of the list rather than working in a linear fashion.

The company’s TAR 2.0 software is specially designed for e-discovery. Some of the early TAR products were re-purposed machine learning tools. They can work in situations where the target documents are a large proportion of the total, but if you are looking for the one percent that are ‘hot docs,’ then they are not as effective. With TAR 2.0, attorneys and legal professionals who are subject matter experts do the initial coding for relevancy. Each of their judgments about the relevancy of a document is fed back to the system as a means of “training” to identify others that also might be relevant.

In the case of earlier versions of TAR, adding new documents caused the random sampling assumptions to no longer be correct. Unlike earlier products, which had a finite learning phase and then a production phase, TAR 2.0 allows new coding to be immediately incorporated into the algorithm for searching the document repository so that it is correctly tuned to the current problem domain.

It allows every decision made by an attorney to be put to maximum use, allowing humans to do what they do best, and then let the computer do what it does best, which is to quickly surface the relevant documents.

One practical limitation of early versions of TAR was that it could not handle small volumes of documents because the usual percentage of samples did not provide enough examples from which the computer could learn. This became improved in later versions of the tool.

Recommind

In 2006, the federal rules for discovery changed to include discovery of electronic information. E-discovery includes the collection, processing and analysis of e-mail and other electronic documents that might be relevant to a case, including determination of whether the documents are indeed relevant.

What sets Recommind apart from many industry solutions, is the ability to prioritize records and pull together similar records.

Recommind’s Axcelerate product can research, collate and assemble electronic records into reports. The electronic records for a single case can sometimes number into the millions.

Axcelerate’s adaptive batching expedites the feedback loop on search or analytics-based document sets, making continued batching not just automatic, but also conditional on the relevancy found through sampling. That enables a law firm to determine by batch if certain records are indeed relevant to a case, rather than reviewing them individually.

Magnum Software

It allows to quickly search, annotate and link to portions of documents. The collaboration capability is quite robust. Users can share their work product with any other users or groups of users via a one-click e-mail alert.

The alert automatically includes a direct link to the note and passage so the recipient can log in from anywhere, review the remarks and continue the discussion thread within Opus 2 Magnum. Additionally, multiple users can “chat” within the application.

The application works much better with smaller files than loading them all to a large database, but Magnum can also scale for larger file sizes.

Exterro

This in an excellent tool for eDiscovery. It provides eDiscovery and other records management needs in a single platform. Genome data mapping module can be added which will create an excellent solution for the data mapping.

With the increasing number of records and need to keep track of them and pull them together efficiently, the demand for KM technology for records and information management will continue to grow.

Galaxy Consulting has 17 years experience in ensuring that ediscovery process is going smoothly.

Five Trends of Knowledge Management

Many issues affect knowledge management. The five most important are big data, cybersecurity, mobility, social analytics, and customer engagement.

The availability of big data has opened many options for understanding everything from customer preferences to medical outcomes.

Amidst all that data, concerns about security have grown, so cybersecurity is taking on new importance. Mobility has become pervasive and affects nearly every element in KM, while social analytics is providing insights at a personal level that were never possible before.

Finally, although those four factors feed into many KM objectives, enhancing customer engagement has taken a place at the top of the priority list for virtually every company and is likely to remain there for some time.

Big data

The most dramatic trend impacting knowledge management is harvesting and analyzing big data. An esoteric phenomenon just a few years ago with a new set of technologies and terminology, big data is now wrapped into the strategic plans of many organizations, and not just the big ones.

There are few applications to help with this challenge.

One of them is Hadoop. It can help to integrate complex sets of data to make business decisions and marketing efforts.

Actian Analytics Platform is a big data analytics solution that is accessible and affordable for small businesses, but also scalable to large ones. It can be used to target right customers. It can also be used to generate an economic case for potential buyers.

For example, Yahoo uses Actian to segment millions of users across 10,000 variables, looking for clues that will help predict customer behavior. Amazon uses Actian to provide the core technology components for its cloud-based data warehouse.

The technology can pull together diverse data in near real time as it flows through the data pipeline, marketing, customer engagement, risk assessment and many other applications. At both ends of the spectrum, from startups to large-scale users, big data is the central force in converting large amounts of data to decision-supporting information.

Cybersecurity

With so much information at large, unauthorized access to it has the potential to be destructive. Knowledge management is focused on information. What makes KM so important is that people can get information and analyze it better. In the past, it was hard to find out who was buying products and how they felt about them. Now an enormous amount of information is available, which has benefits. The information can be stolen and used financial gain.

The cybersecurity market is expected to increase from $95.6 billion in 2014 to $155.7 billion by 2019, resulting in a 10.3% per year increase during that time period. This amount includes network, endpoint, application, content and wireless security as well as many other types of technology. Innovative products are emerging in response to increased threats.

The volume of data, including an entire new collection from the Internet of Things, the challenges of mobile devices, greater use of the cloud for data storage and the broad impact of consumer concern are all sparking the growth.

Cybercrime comes in many forms, from stealing credit card numbers out of a merchant’s database to identity theft of consumers. A common strategy is for a cyberthief to obtain some publicly available information about an individual and use it to open an account or figure out a password that provides them access to an account. Users need to be vigilant about changing their passwords and making them strong. Technological safeguards can be put into place, but security depends a great deal on the human effort.

Mobile devices add another element of risk. They are much easier to lose or to steal, and often contain sensitive information such as bank passwords. Technological advances such as the ability to remotely disable a phone will continue to emerge to protect users from the impact of cybertheft. However, the result of users being careless with physical security, such as leaving a laptop in an unlocked car, remains a threat.

Companies can mitigate the impact on their customers by limiting the responsibility of users in the event of fraud or identity theft. Industries are growing up around providing insurance for such scenarios, either to the merchant or the customer.

Mobility

Although mobility brings hazards, it has brought even more advantages, and it will continue to drive the pervasiveness of knowledge management. Increasingly, knowledge management solutions, including content management, process management and analytics, have mobile versions of the solution. No longer a miniaturized version of the desktop browser, mobile apps are delivering usable KM applications.

Mobility is also forging new paths. For example, Apple Pay allows use of the smartphone as a wallet.

One mistake merchants make in designing mobile apps is to try to duplicate a physical purchase experience on a mobile device. Merchants should not necessarily automate an existing process, but instead should look at the experience holistically. Mobile experiences have to be simpler and as good as, if not better than, the non-mobile experience in order to gain loyalty from the customer.

Barriers remain in the use of mobile devices for enterprise applications, but the barriers also represent opportunities. In a study of U.S. and U.K. information technology decision makers conducted by Vanson Bourne, respondents reported that although more than 400 enterprise applications were typically deployed in each organization, only 22% of them could be easily accessed on mobile devices.

One reason for that is the diversity of enterprise applications. Some are custom, some are SaaS and some are off-the-shelf, and the technology for accessing each one is different. Therefore, development of mobile apps for such applications is needed, but organizations are hampered by the high cost. More efficient development techniques would be a big benefit.

The proliferation of mobile devices has also increased a number of other supporting sectors beside mobile application management (MAM), including mobile content management (MCM) and mobile device management (MDM). Each of them has a touchpoint to knowledge management and should be viewed in conjunction with an overall KM strategy.

Social analytics

Social analytics is a booming market which is expected to triple over the next five years to nearly $9 billion and showing a growth rate of nearly 25% per year. Initially based on simple counts of the number of times a brand was mentioned in social media, analytics has evolved to the point where it is using sophisticated algorithms that support the use of social data for targeted marketing and for initiating customer service.

Social analytics moved from hindsight to insight and now to foresight, with predictive capabilities. SAS social media solutions include integration and storage of social data, general text analytics and analysis of comments for sentiment, and a social conversation module that can work directly or integrate with third-party engagement solutions.

Real-time analysis allows marketing or brand campaigns to be synchronized with the topic threads that are emerging. Decision trees allow ‘what-if’ scenarios such as the impact of increasing the frequency of an ad, or combining customer segments. These analysis allows users to determine the relationships among various factors and to present visualizations of the relationships for better marketing decisions.

The value of social media analytics is also increased by combining it with data such as purchasing information from the data warehouse, to compare customers’ stated intentions with actual behavior. There is tremendous growth in analyzing social media information along with data from the Internet of Things which measures physical activity to build a profile not just of transactions but of tone and behavior along the customer journey.

Social media analytics should not be isolated. The information should be tightly connected to upstream data so different departments can use it to drive the customer experience.

Customer engagement

The driving force for all of the above is customer engagement - collecting and managing big data, keeping information secure, enabling mobility and analyzing social media inputs. The ultimate goal is to engage the customer, whether for marketing, customer support, participation in loyalty programs or some other outcome.

The key for customer engagement is omni-channel. Whether the interaction is initiated by the customer or the organization, customers want options in the delivery channels.

Customer engagement is not a static business area. The feedback obtained through social analytics and traditional business intelligence can be merged to explain both what customers are doing and why. That information can guide the delivery of marketing materials and help provide better customer service.

Galaxy Consulting has 17 years experience in knowledge management. We have lead knowledge management initiatives. Contact us for a free consultation.