Organizations currently use a combination of online forms and spreadsheets to learn about how product owners collect and process personal data. In this way, organizations identify data processing activities and data attributes that can cause privacy violations and manually guide product owners to address or mitigate that risk. Through this mechanism, organizations have to track and manage hundreds of spreadsheets and several data attributes, and continuously evaluate their current risk levels. Organizations also need to determine if the product owner has implemented remediation steps such as stopping collecting data that is risky.
In agile product development, organizations may not always have the most current or accurate view of what data is being collected. New features are added faster than privacy officers can track and address previous risks through this outdated model. Privacy Ops Maturity Level 1 is the right solution for small companies with one or two products looking to avoid the pitfalls caused by these manual mechanisms for compliance.
Maturity Level 1 of PrivacyOps involves a basic level of the system of collaboration, record, engagement, and semi-automation.
PrivacyOps platforms provide a built-in system of secure collaboration that minimizes data sprawl caused by sensitive personal data distribution. Instead of spreadsheets, organizations can use an online portal to develop assessments too. PrivacyOps envisages the use of intelligent and collaborative portals that automatically extract critical details from assessments such as data store owner name, contact information, retention policy, security measure, sensitive data attributes, data residency, etc. PrivacyOps platforms allow organizations to track and maintain a clean data catalog of every data asset in their environment. Suppose organizations identify a highly risky data attribute. In that case, they can automatically trigger a response to invite product owners to justify collecting such data or asking for details about the security measures used to protect this data. This process automates many of the organizations’ tasks, reduces data sprawl, and allows organizations to manage data privacy efficiently.
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