Finding it hard to keep up with this fast-paced industry?
During normal business operations, end-users inevitably duplicate files they are working on to complete their tasks more quickly or efficiently, or to work around restrictive IT policies. Who hasn’t emailed a copy of a file to a colleague to review? But while such duplication may feel harmless, even unavoidable, duplicate files can significantly impact your risk posture.
The Healthcare sector offers a vivid example of the risks of duplicate records. According to the American Health Information Management Association, the average hospital has a 10% duplication rate of patient records. These duplicate records can lead to errors in medical treatment, including incorrect diagnoses, medications, and procedures. But duplicate records create issues for all industries.
The pitfalls of duplicate records
The risk of insecurely protected duplicate records
Duplicate records can pose a significant security risk, particularly if they contain sensitive personal information. Cybercriminals may target duplicate records to gain access to valuable data or to launch phishing attacks, which can put the organization and its customers at risk.
Suppose multiple versions of the same record are stored in different locations or systems. In that case, it can be difficult to track who has access to the data, how it is being used, and whether it is being adequately protected.
Data discovery delays and errors
Duplicate records create administrative burdens for information managers and can result in delays in information processing and discovery. Duplicates hinder Freedom of Information (FOI) and Data Subject Access Requests (DSAR) processes as they create confusion and inconsistencies.
In the case of a FOI request for a specific document, if the document is stored in multiple locations with different versions, it can be challenging to locate the correct version and provide an accurate and complete response to the request.
Duplicates being shared on systems that are not being governed
Modern-day communications and instant messaging platforms such as Slack, Microsoft Teams and WhatsApp are hotbeds for sharing copies of documents and other transitory records. If these systems are not being managed, how can you even identify these duplicate records, let alone associate an appropriate retention schedule?
Increased storage costs
Duplicate data can take up valuable storage space, requiring more storage resources and increasing costs. The true cost of storage goes beyond just a simple cost per TB equation, and includes indirect costs such as replication costs, transfer or cloud egress costs, and management costs. Learn more about calculating these costs and why data minimization matters here.
Gaining control of duplicate records in your organization
The first step towards strong data governance is creating a comprehensive data inventory of all your data. It is only possible to manage and govern data effectively if an organization knows what data it has, including duplicates.
Organizations need to have the processes and tooling in place to identify and manage duplicate records continuously. By doing so, organizations can ensure their information management processes' accuracy, security, and efficiency and reduce the risks associated with duplicate records.
Why data minimization matters
Retaining redundant, obsolete or trivial data (ROT) raises costs and business risk. Data minimization is the answer, and can enable your team to achieve more.
Why create a data disposition strategy?
Once a record’s retention period ends, an organization must dispose of it. By following a retention and disposition policy, organizations can reduce the amount of data in their possession. There is no exposure risk for data you don't have in your system.
The ultimate guide to Personal Data, Personal Information, Personally Identifiable Information and Sensitive information
Organizations need to embed privacy into their systems and processes to gain an advantage and gain customer trust. But first, they need to understand the sensitive data they have, and how to classify it. This means they need to learn to separate their PI from their PII. This guide explains the differences between each of these terms.