By Jim Gill
Data mapping used to be a dirty word in e-discovery. But as data becomes more dispersed and voluminous across organizations, having a centralized resource for quickly identifying where certain electronically stored information (ESI) resides is extremely valuable. Still, data mapping is complex and challenging. Many companies start data mapping projects only to abandon them before completion.
So what makes data mapping so difficult? Here are four common challenges and shortcomings associated with data mapping and how they can be mitigated.
Too time consuming to build:
Any time a company seeks to map their entire data environment the work involved is going to be immense
. However, there are ways to significantly ease the data mapping burden. It starts by defining a process for gathering information. In most cases, systematic interviews with data stewards are the most efficient way to collect info for a data map. These interviews should be simple and template based so that responses can be quickly interpreted and immediately incorporated into the overall plan. There are systems that can automate the interviews so that follow ups, reminders and update questionnaires can be pre-scheduled and responses automatically logged. It also helps to start with what you know and build out. IT teams are responsible for managing a company's data environment for operational purposes so they will have a lot of useful information that can be used as a starting point.
Impossible to keep information up to date:
Think of a data map as a product, not a project. Like a product, it should be constantly evaluated, updated and assessed for quality. Failing to take this approach usually results in a data map becoming outdated before it provides any real value to the company. As mentioned above, having a defined, automated process can keep information coming in on a more consistent basis so that it doesn't feel like every update has to be its own, tedious new project. Another way to ensure the data map stays updated is to make sure that it is fully integrated with the company's HR and asset management systems so that the map reflects current employee and systems information.
A common mistake organizations make with data maps is that they omit important information and therefore render the data map far less useful than it should be. Before any data mapping initiative gets off the ground, project organizers should assemble all the key stakeholders and gather feedback on what information needs to be included. For example, a company's general counsel will want to make sure the data map includes retention schedules, litigation risk profile and accessibility constraints of particular data sources. Meanwhile, a chief privacy officer will likely want to know which data sources contain sensitive customer information that must be carefully protected. Understanding how different business units plan to interact and use the data map will help guide the information gathering and make the process of building the map far more efficient.
For a data map to be effective, it has to be comprehensive. In today's digital world, that means it must account for things like mobile devices and cloud-based applications, including social media, since ESI from these sources is increasingly being sought in litigation. It is critical to identify how and by whom these sources are used and any relevant ESI that may exist on them (customer service records, marketing materials, etc.). In the case of mobile devices, it's important to identify any relevant data that is specific to the device versus that which can be accessed from a more traditional ESI source, such as an email server. When it comes to mapping social media use, it's imperative that the information be updated on a regular basis since usage trends tend to evolve very rapidly.
For more information on data mapping and other preservation strategies, Download Exterro's Comprehensive Guide to E-Discovery Preservation.