Chronicle 2.2's Guided Normalization makes it even more ridiculously easy to normalize names, create clearer privilege narratives, and reliably reuse work product.
There are a lot of exciting features packed into Chronicle 2.2 that are designed to end the frustrating experience of normalizing the same names over and over again. Let's start with a short video explaining Guided Normalizations before examining some use cases and technical capabilities.
Explore Use Cases for Guided Normalizations
There are many reasons for normalizing names. You may be building a notification list for a data breach, improving your entities for easier identification during document review, or getting the names correct for constructing a privilege log.
Before beginning any sensitive info task, it is essential to consider the full scope of the use case and the situations where tasks might be repeated down the road – or, in this case, down the Relativity workflow.
Each Chronicle Guided Normalization use case above involves managing personal information that may be sensitive or, in the case of a privilege log, is privileged!
Here are other use cases:
Each case corporate counsel works on involves employees at the company being represented
A law firm hosting many cases in Relativity has the same lawyers' names and information show up on privileged documents across unrelated cases
Multiple workspaces for different audiences are involved in the same extended review and need the same normalizations in each case
Regardless of the scenario, if names are shared across workspaces, using Chronicle is the best way to avoid repeating the same manual work repeatedly.
Walking Through Guided Normalization Mappings
Chronicle's display minimizes noise around extracted names, pairs them with new or existing normalized names, and offers simple ways to correct them. This makes it incredibly easy to get started using Chronicle and focus on the unifying threads connecting otherwise fragmented information.
As names are normalized, relationships build between the values in document fields and the name being mapped to. A unique "pairing" is constructed behind the scenes between the document, document field, original field value, and the value it should be normalized to. Chronicle then provides several ways to view this association's core mapping between the original, incorrect, or shorthand name – thus ensuring the proper version is used in privilege logs, data breach notifications, or privileged reviews.
When "Tim Randall" is normalized to "Timothy Randall," that decision typically impacts the entire case and will be needed anywhere else "Tim Randall" appears.
In Chronicle, such a mapping is considered the work product of the Name Normalization project, and clicking on a normalized name from the Normalized Values table on a project will display all of the original values mapped to that name in a modal window.
Creating Reusable Work Product with Guided Normalizations
The flexibility of Chronicle will vastly reduce the time you spend managing normalizations with the Manage Normalizations tab. This area provides a table with every pair of original values and normalized values in the workspace, regardless of the number of projects.
Chronicle users can filter, review, export, or import new values right from this page!
It's just as easy to reuse Guided Normalizations in another workspace. All it takes is a simple export and import.
Returning to the Manage Normalizations tab, an Export button is at the top of the table. Clicking this button gives options for exporting all mappings from the case in either CSV format (meant for import/export) or Excel format (meant for manipulating and reporting in Excel).
Clicking Export all data to CSV will immediately download a CSV of every mapping in the workspace. This file can be opened in any text editor or Excel for further review. It contains all the names extracted from your documents and the normalized version your team has mapped it to!
Don't forget that this file should be considered sensitive and protected per your organization's data protection policies.
With this file, we can now navigate to a second case and import it. This process will automatically create the mappings in the second case and immediately apply to any active or upcoming project that contains the mapped original values in that case.
After navigating to the second case and selecting the Managed Normalization tab, we can click import and select the CSV downloaded previously.
Clicking upload will begin the import process! After the upload, a message is displayed letting you know if the operation was successful. This process performs extensive validation, ensuring duplicate or erroneous mappings aren't created. If they are, details of the import are available immediately for review.
After the import, new or upcoming projects will automatically reflect the imported mapping with no additional work!
Watching Guided Normalizations Pull It All Together
The process of using Guided Normalizations is a tremendously powerful way to significantly reduce the manual effort required to normalize names in your cases.
Whether normalizing your legal team's names or importing mappings for common AM Law 100 names, you'll save your team precious time to focus on the outliers!
Maybe your client gives you some common pseudonyms for the custodians in the case, or maybe you need to build a report of all the unique normalized names in the case – it's all made easier with Chronicle!
Comentarios