By Nico Dard, Director of Product Management at Privitar

 

Earlier this year, I took part in a roundtable discussion at an event where we covered the subject of how to create a culture of safe data to accelerate insights. The roundtable was packed full with industry leaders from the data and analytics world, and, although there was some predictable agreement on known objections, the session also threw up some other lesser known challenges faced by these individuals, and their thoughts on possible solutions.

I firmly believe that we can all benefit by learning from each other’s experiences, both positive and negative. In that spirit, I wanted to highlight key takeaways from that roundtable conversation.

 

Key challenges facing data and analytics leaders 

  • Finding the balance: Organizations are fine tuning the balance between extracting value from data with an eye on ethics, compliance and security. Certainly there has been a mindshift over recent years to understand the difference between data security and privacy and a move away from merely locking down the data. Enabling technologies are allowing organizations to continue to derive actionable insights from the data with much less risk than ever before.

  • Speeding up access to data: Security and privacy concerns can slow down analytical access to data. Organizations are regularly challenged by finding their sweet spot between flexibility and security.

  • Data is stored everywhere: Using data stored on-premise, in hybrid environments, or in the cloud may require different approaches. On top of that, data is usually stored in silos that are difficult to find and catalog. This makes data difficult to find, integrate, analyze and govern. It also slows down people’s ability to get the data they need to drive value in a data-driven organization.

  • Regulatory frameworks are rapidly evolving: You don’t have to look far to find legislation related to data privacy and data protection: the General Data Protection Regulation (GDPR) dominates the European Union; the California Consumer Privacy Act (CCPA) not only applies in California but has been used as a model for other states in the United States, and there are literally hundreds of regularly frameworks that are under consideration and being evolved as I write this.

  • Internal compliance: More people need to be involved than ever before– from data owners who are responsible for the safety of data under their care, to data consumers who require access to data for their analysis, and data guardians who are responsible for the organization’s ethical and legal use of data, and business leaders who want to see value derived from the data their organization has collected. Balancing their distinct needs is no small feat.

 

While there was no shortage of challenges shared among the group, there we also quite a few interesting solutions that attendees were actively thinking about or already implementing:

  • Changing the perspective: Create a culture of thinking about things from the customer’s perspective. All of the session participants acknowledged that customers are increasingly data-savvy. The only way to build and maintain customer trust and respect privacy is through transparency of processes and tools used.

  • Evangelizing and educating internally: Everyone within an organization needs to understand the benefits of data sharing, the positive impact of safe data usage, and the part they play in collaborating successfully. Requesters of data need to be clear about why they need the data and guardians of data need to positively encourage appropriate sharing. Getting everyone on the same page goes a long way toward building a successful initiative.

  • Driving consensus on strategy: Reaching internal agreement on the approach to sharing data safely is key. Having a clear strategy on your organization’s interpretation of legal and regulatory guidance is required to be able to utilize data fully. Keep the strategy consistent from the top down and ensure that there is a common terminology (and understanding) of the strategy.

  • Considering the importance of context: Protecting sensitive data for use in analytics requires you ask questions about context to balance risks with the need for data resolution and utility, and sometimes make tradeoffs. When you understand data context, and the tradeoffs you are considering, you’re well equipped to define protections that achieve the right balance of privacy and utility for your use case.

  • Managing data through risk management: With modern data privacy tools, sharing your data does not mean taking inconsiderate risks. Those tools allow you to assess the risk inherent to a data set, as well as the general context of data consumption, by taking into consideration the characteristics of the environment. For example, by looking at where the data is stored, where it’s going, the identity of the consumer,and the content of the data, it is possible to automatically apply the right set of privacy transformations, and maintain a proper level of risk.

Take a look at the illustration created during the session for a visual representation of the varied conversations, and let us know if these are reflective of the challenges you are facing or the creative solutions you are adopting.

To learn more about how to power your business through safe analytics, check out Privitar’s Safe Analytics Resource Hub. 

Data Analytics Data Sharing