Myths are paradoxical. They often start with a kernel of truth, and the most fertile ground in which a kernel sprouts and grows, is a field of confusion. The more complex a topic, the more likely it is that myths will spread vigorously like weeds.
Case in point? Information governance. Everyone has his or her own take on the exact definition of information governance, and in reality, “ideal” governance will be different for every organization. But, the rise of file share analysis tools has only further complicated a very multifaceted business challenge. Here are some common myths about file analysis, and their respective truths.
Myth #1: File analysis = information governance
Analysis alone of a file share environment is not information governance; it is a snapshot assessment of content at a given point in time. It’s a report instead of a real-time dashboard. However, file analysis certainly can be used as part of an overarching information governance program.
Increasingly, this is exactly the case with file shares, which have often been neglected in governance efforts. Analysis offers a first step for businesses that simply don’t know where to start with their sprawling file environments.
The process of information governance, however, is a journey, and the first step will only get you moving. The process that follows the initial analysis – deciding what to do and then doing it – is what pushes the data down the path of information governance. This process, called data remediation, is not an inherent part of many governance tools.
Myth #2: File analysis will classify, sort, and manage data
File analysis alone cannot make business decisions— only the business can. So before initiating a file analysis effort, the organization needs to be clear in determining what the objectives and desired outcomes are.
File analysis for file cleanup is like walking into a messy room and creating a detailed list of what’s there; the cleanup process itself isn’t provided by the initial assessment. The decisions of what to move, discard, rearrange, lock away in cupboards, or wipe down with cleaner all still have to be made. And the act of doing those things is again yet another step.
File analysis is no different. Most file analysis tools will generate an initial report, but the decisions and heavy-lifting remain. If there is a need to move, discard, re-arrange, classify, or otherwise manage the analyzed files, the organization needs to ensure plans for the next steps have been made.
Some file analysis tools offer integration with information governance or records management products, and some existing governance platforms can natively analyze file environments. Make sure the business understands what options exist long before a purchase is made.
Myth #3: File analysis is a one-time project
For many organizations, file analysis IS treated as one-time project. However, unless something is done with the analyzed content, it becomes necessary to eventually repeat the effort.
Just as in our messy room example, file shares are a living ecosystem. There are constantly new items, changes and revisions. The clean shirt in the closet today may be dirty and tossed on the floor tomorrow. If file analysis is used as the first step in a one-time cleanup approach, it’s akin to doing spring cleaning… and no more cleaning for the rest of the year.
Singular file analysis followed by singular cleanup must become a recurring project in order to maintain control over data, negating the concept of “singular.” This is where information governance comes into play; with the right architecture, it’s possible to conduct full-scale analysis of files once, actively categorize data or get rid of it and then perpetually analyze the changes and activity in order to manage any subsequently modified or created content. In the end, a file analysis project can be conducted once… but it’s likely not what you’re looking for.
Myth #4: File analysis can only analyze metadata
Part of the selection process for a file analysis method or tool is deciding how deep the analysis needs to be in order to achieve desired business objectives. Many file analysis products rely on metadata rather than content. While metadata alone can provide a wealth of critical information commonly used to classify and manage content within a records or governance program, it doesn’t give the full picture.
Often, the most important data is hidden within document content. Take, for example, sensitive information such as Social Security numbers or financial information. In order to reliably tell if these have been stored within a public file share or other unsafe location, the content of the files need to be assessed. If an organization desires to use file analysis as part of an effort to increase data security, content analysis is critical. It does exist, but the business needs to conduct due diligence to ensure that the tool being purchased offers content capabilities.
Myth #5: File analysis is an IT problem
File analysis, used properly within a comprehensive information governance strategy, is an “everyone problem.” The failure to reign in control of files affects nearly every business unit.
While IT teams may be key facilitators in the initial file analysis process, the downstream stakeholders are spread across the organization. End users benefit from increased efficiency of file access and productivity. Legal teams benefit from the defensible removal of junk. Compliance and risk managers benefit from better access controls and protection of sensitive content. And IT, of course, benefits from a more streamlined and secure file environment. File analysis should never be conducted simply because of an IT driver.
The file analysis market offers more options than one might expect, but care is required to ensure that complexity doesn’t muddle decision-making. The trick is fitting file analysis into a comprehensive governance roadmap. To do so requires not only a deep assessment of business objectives, but also cohesion between business stakeholders. Like a garden, information governance requires ongoing care. Just make sure myths don’t take root and spoil the harvest.
(About the author: Kon Leong is president, CEO and co-founder of ZL Technologies)
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