Leading organizations need to use personal data to drive innovation. The successful organizations of the future will be those that implement a comprehensive privacy management strategy, enabling data use while managing and mitigating the associated privacy risk.
Those organizations using personal data without appropriate privacy controls risk a range of negative consequences, such as losing customer trust, brand damage, regulatory fines, and litigation. While organizations that lock their data away and fail to use it will fall behind their competitors.
A comprehensive approach to privacy management will ensure that personal data is used safely, building customer trust and acceptance and mitigating regulatory risk. De-identification is a key element of a comprehensive approach to privacy risk management.
De-identification reduces the likelihood that an individual can be identified in a dataset. However, it can also affect data utility and usability. Data utility and usability requirements will often be a key factor driving the choice of controls. In general, de-identification aims to protect privacy while maintaining utility. While mitigating privacy risk can reduce utility, it can allow more value to be extracted from data overall by unlocking data that may be too sensitive to use without privacy risk mitigations in place.