Rules like those proposed through Bill C-27 and required under Law 25 mean organizations must understand more about the data lifecycle and gaps that could be putting personal information at risk. This becomes even more critical in organizations with sophisticated operations, where data feeds multiple databases, platforms and systems that run concurrently. Information oversight can be particularly challenging in those scenarios, especially if teams operate in silos.
And the potentially negative impacts aren’t limited to any one corner of the organization. Poor data privacy practices can significantly affect many areas of the business. Without effective data mapping, full cooperation of all stakeholders and a fulsome plan to meet regulatory standards, compliance can be compromised. The repercussions can be challenging and include significant regulatory fines as well as costly reputational damage.
Working as a team can strengthen data privacy programs, policies and processes
A cross-collaborative, agile approach is critical to establishing a privacy management plan and fostering a privacy culture. Centralizing expertise through a privacy office that collaborates internally and externally — and supporting that team with the right technology platforms and tools — can help businesses gain that kind of clarity.
To be truly effective, though, data officers require stakeholder support from all those who touch personal information as it moves through the organization itself. This includes business units like cybersecurity, IT, human resources, marketing and more. Whether establishing a governance framework, data lineage across multiple systems, or putting policies and controls in place, each of these groups will have unique and specific priorities. By working collaboratively, cross-functional teams will be able to redefine outdated narratives that support legacy models — the mindset that privacy is legal’s responsibility, brand belongs to marketing alone and so forth.
Working as a team empowers business units to share critical knowledge and learn from one another’s experiences. This helps more effectively reduce risk, optimize resources and enable the organization to adopt necessary behavioural changes that respond to today’s evolving privacy requirements. The privacy engineer can become the cohesive role that brings these multiple players together, connecting privacy rules with business needs and tools that can help automate the privacy program.
Automating the right processes can strengthen privacy management and the bottom line
We know the world is going through a significant cycle of distrust.⁵ Put simply: the world has witnessed how dangerous misinformation can be, making trust the ultimate currency for customers.⁶ Safeguarding data builds stakeholder trust. Gaining that knowledge requires time, resources, optimally configured data discovery tools and, above all, a clear framework that seamlessly connects these activities and capabilities.
Successfully integrating data management and governance tools with the operationalization of privacy programs helps simplify processes, reduces repetition and eliminates resource competition. For example, a governance and risk compliance (GRC) or integrated risk management (IRM) system can make it more efficient to manage a privacy risk register or deal with risk considerations tied to third-party relationships. Along similar lines, a process mining tool can help by identifying opportunities to make privacy processes more agile, reducing costs and aligning activities to regulatory expectations.
Embracing this approach also allows cross-functional teams to identify opportunities to automate privacy tasks, freeing people up to spend more time on other strategic initiatives. What could that look like from day to day?
Consider your IT help desk ticketing system. When an employee reaches out with a request, they might trigger privacy tasks — like the initiation, management and response to an individual request to exercise privacy rights. That same ticketing system can be used to initiate and manage the flow of execution for a privacy impact assessment.
Privacy engineers play a pivotal role in connecting these tools to the privacy program and enabling the organization to effectively tackle privacy challenges. Intelligent privacy engineering can configure solutions unique to your organization’s business model, resulting in significant operational efficiencies and a solid support for trust generation and preservation.
How can privacy engineers help organizations unleash automation to improve privacy management?
1. Understand the value of privacy. Privacy is a key channel through which organizations can differentiate themselves. Properly protecting personal information and exercise rights helps gain, restore or maintain trust. Privacy engineers who embrace this thinking and use it to gain stakeholder buy-in across the organization can help unleash privacy’s true power as a competitive edge.
2. Confirm your understanding of personal information processing activities. Every organization needs to understand the personal information they process so they can confirm that it’s only for the legitimate reasons individuals agreed to and only for the necessary timeframe, that it’s protected against exposure and managed in a way that allows individuals to exercise their own privacy rights. Privacy engineers can help by using existing information systems and connecting them to new specialized tools to generate accurate and up-to-date personal information inventories that will help the privacy office clearly identify those elements that need to be protected and that will be the object of individuals exercising their privacy rights.
3. Identify where your privacy program has automation needs. Organizations must identify high-risk activities, as well as transactions that take place at high volumes or are particularly complex. Privacy engineers can help by combining a risk-based approach with a focus on user experiences. Doing so allows these leaders to spot key activities where automation can reduce risk, cost and operational complexity while freeing human resources to focus on other ways to preserve or generate trust. The automation a privacy engineer can propose would reduce time and resources devoted to the execution of privacy management activities, thus helping the organization respond to privacy requirements in a more agile way.
4. Identify tools to respond to those needs. Once you know which activities to automate, you’ll need to explore which tools can make the greatest impact. Clearly understanding and validating corporate requirements is an important part of that process. Privacy engineers can lead the way by looking for off-the-shelf privacy management platforms, as well as other tools that can be modified to help automate privacy management activities. Getting this right requires privacy engineers to analyze which existing tools can also be applied or repurposed before bringing new solutions into the mix.
5. Design and orchestrate your model. Once individual tools have been selected to automate one or multiple privacy management activities, the privacy engineer can work on harmonizing the ecosystem to have these tools not only support each other, but also communicate with the same or other solutions supporting the operation of the overall enterprise risk management model.
