The Balancing Act: Data Privacy, Security, and Analytical Insights
On October 3 and 4, I had the chance to attend Information Builders' "Analytics in the Public Ecosystem Symposim" in Niagara Falls, ON, which brought together professionals from healthcare, government, and law enforcement. I will admit that I had wanted to attend the event well before joining Information Builders, as I have a fascination, bordering on obsession, with how analytics are deployed within law enforcement and healthcare. Additionally, I think the way our personal information is leveraged for healthcare and within government – having to balance services and care with privacy – provides personal examples of the importance of how data accessibility and analytics need to be balanced with security frameworks that ensure people’s privacy and safety. Simply put, the way organizations, governments, and non-profits manage data affects us directly, especially when evaluating the way information is stored and leveraged within the public ecosystem.
The discussion surrounding security and data privacy is not new. As more organizations leverage cloud-based platforms it becomes more important to build a strategy that takes into account how information will be stored, used, and protected.
With social media analytics, access to sensor data, globalization, location intelligence, etc., the balance between gaining insights and protecting privacy becomes tenuous. Irrespective of where data is stored, more personal details are being collected on a regular basis. Finding the balance between the two can impact a company’s ability to serve customers and can potentially save lives.
Within retail and e-commerce it helps companies provide better products and services by understanding how products (i.e., appliances, cars, etc.) are being used. Preventative maintenance can help keep products running better, quality control issues can be identified before they become a problem, and organizations can focus on providing better service to their customers. Within healthcare, sharing data between providers and being able to identify broader trends and enable earlier diagnostics and better treatments through machine learning has a direct impact on patient outcomes. It also provides a more complete view of the patient and supports better care. In each of these cases, there needs to be a balance between pattern identification, providing better services, and invading individual privacy.
For instance, with appliance use, smart meters, and smart homes in general, the ability to connect to a home can provide information regarding when people are away, leaving a house vulnerable. Individual health records can lead to potential fraud or have insurance implications. The list is endless. At the same time, by looking at anonymized data, patterns in disease and treatments can be identified, utility companies can gain insight into usage, and organizations can identify what works best for their customers.
The reality is that we live at a time where there a fine line exists between accessing data for analytics to provide value added products and services, and having too much data at our fingertips. Legislation and potential legal implications will provide general guidelines, but organizations still have flexibility to create their own data and security strategies that walk the fine line between gaining insight and protecting privacy. These types of challenges, the ones which combine data and analytical insight and impact our personal lives directly, are the ones that require the greatest responsibility, but also give us insight into future opportunities.