The ubiquity of data has the world community of privacy and security professionals in splits. While one side considers it as a boon for the digital world we all dream about, others consider it as an invitation to unimaginable risks. Consequently, digital product owners have a tough road to trek with generating enough data for analytics and ensuring privacy at the same time.
Over the years, data privacy management has emerged as a standalone vertical in an organisation’s technology landscape, says Yash Mehta, an IoT and Big Data Science specialist. It is worth it because 45% of American internet users faced data theft in some capacity. In all honesty, these numbers didn’t worsen only because red flags against privacy issues were raised and acted upon. However, enterprises continue to struggle either because of ineffective policies or due to a lack of resource expertise.
Here’s a round-up of 3 key challenges in data privacy that enterprises face.
Challenge 1: The propelling of data & advanced technologies
Data will continue to grow. After all, that’s the foundation of a digitally strong world. That’s why the concerns must shift from ‘more data’ to ‘managing more data’. Since the dependency upon digital solutions has increased due to the pandemic, the propelling of data generated in real-time is inevitable. In April last year, Netflix’s user count increased by 16 million. This is a testimony of the average user across devices consuming more data.
The challenge of ensuring privacy for big data gets tougher in wake of maturing advanced technologies, Internet of Things (IoT) for example, is adding millions of devices (hence the data) to the web. Not only is it the fastest growing technology around but also the most preferred gateway for hackers to prey on user data. Besides poor make, poor privacy policies make it easier for the attackers to tamper.
Add to it, the IoT vendors lag in releasing timely security patches for the installed devices and yet there’s no check on the rising number of connected devices.
Challenge 2: Design challenges in automation workflows
The need to implement sustainable design to systems with data privacy was always imperative. However, with propelling incoming data and a swathe of regulation hassles to comply with, automation has to take the centre stage and govern the privacy principles. To begin with, privacy decision-makers must embed the latest privacy policies in the core design. While for legacy systems, privacy principles should be built on the top of the core system. At the same time, ensuring seamless usability and fine-tuning it with deep privacy is the challenge in focus here.
Despite the awareness around new policies and user privacy concerns, many companies are locking horns with passive privacy designs. Not only has this affected their prospects of excelling in the digital space but also debarred them from geographic expansion.
This is largely because the lack of accessible industrial expertise continues to be an unresolved bottleneck for many of these service providers. To resolve the bottleneck, an operational data fabric provider, K2View promises an accurate aerial view of the system landscape to perfectly identify the issues.
Through their data privacy management solution they automate the complete lifecycle of data privacy. Unlike most solutions that partially automate the Data Subject Access Request (DSAR) Workflow, K2View streamlines from start (data incoming) to completion. This includes end-to-end collection, updating and deletion of user’s Personally Identifiable Information (PII) data sets.
There are others that provide inventory tracking, integration, consent verification and monitoring of policy violations. The idea is to fortify the user-sensitive information as soon as the data is collected into the system followed by a data compliance checklist that outlines the privacy objectives.
Challenge 3: A long list of regulations and documentation to follow
The GDPR implementation in 2018 has had a ripple effect with more regions including those in the US following up. These include Nevada, California, Washington and Vermont that have proposed to frame their own data privacy legislation. In fact, California’s CCPA is already enforced in July 2020.
While non-compliance with any of these laws could attract large fines and even jail terms, enterprises have a greater responsibility of implementing exclusive data privacy laws as per the change in the region. Unlike previously, they have to adhere to the laws of every state no matter how lengthy and tedious the process is. Besides overhead costs, this could have a direct impact on the design thinking strategies.
Regardless of location or region, all companies in the world will be affected in some capacity by at least one of these regulations. That is why compliance is no more just another ‘legal formality’. In all honesty, the fate of your digital products and services are depending upon these.
As per a recent eBook on surviving the avalanche of data privacy, the most common factors influencing data privacy are hovering around regulatory compliance management software in one way or the other. So be it the ‘Right to Data Portability (enabling user to move out of a service without any hassle) or the ‘Right to Consent’ (clearly explaining how the customer data would be used), compliance readiness is a key metric to evaluate a product’s survival in the business.
More data on the way!
Despite an abrupt halt to global corporate processing, data generation didn’t suffer. Thanks to cloud-based solutions that plunged at the opportunity and provided an on-demand digital alternative to almost every process and activity. Despite the world recovering, it is expected that digital consumption will not go down. Therefore, service providers have a critical task in hand of not only manage their customers but also prepare for unexpected signups in the future.
The author is Yash Mehta, an IoT and Big Data Science specialist.