5 data privacy imperatives for enterprise leaders
The answer lies with data-informed decision-making and strategic execution. Achieving this is easier said than done: It requires changing how enterprise leaders think about data and how it is managed.
Enterprise leaders have been under constant pressure to sustain business and explore new opportunities for growth due to the disruptive nature of digital natives that survived through the dot-com bubble and are thriving. And then, the digital landscape snowballed, followed by a pandemic that disrupted the way the world works. These events mostly favored the digital natives that thrive with technology to become dominant players in their segment.
While enterprise leaders worked through the pandemic, the ongoing geopolitical tensions in Eastern Europe have had surprising effects on the world economy, which seemed to be recovering well from the pandemic’s impact before the conflict.
In fact, enterprise leaders have to deal with such random events now and then. For example, McKinsey estimates that enterprises can expect supply chain disruptions lasting a month or more every 3.7 years. This is a lot more to deal with, so how can enterprise leaders be ready to respond to and remediate the effects of such events?
The answer lies with data-informed decision-making and strategic execution. Achieving this is easier said than done: It requires changing how enterprise leaders think about data and how it is managed.
Here are five data imperatives enterprise leaders should think about.
Too much data collection is expensive
The imperative is to understand which data points to collect and then how to process and store them. The old-style thinking that too much data can’t be bad for business is proving wrong: as data volumes grow exponentially, the cost of managing and securing the data effectively becomes time- and cost-intensive. Hence, it is essential to think through which data points to collect and how long they should be stored.
Centralize data systems
It implies having a single source of truth and avoiding redundancies that will not work in a synchronized manner. Centralizing data systems, along with methodically choosing which data points to collect, helps various departments have seamless access to the necessary data and operate optimally — for example, understanding customer journeys across products and services to serve highly-relevant content and experiences. Further, it simplifies serving data privacy requests and helps reduce compliance risk.
Manage data as a product
Different teams in an enterprise often build data pipelines and process data as per their individual needs. This makes it difficult for another team to leverage the processed data; instead, they would need to process the same raw data per their specific needs.
To gain more value from the data system and programs, enterprise leaders should strategize managing data as a product as the next step to centralizing data systems. This helps manage data in a way that serves multiple purposes and offers more value to the whole enterprise.
Leverage technology for compliance
Enterprises already deal with a range of regulatory requirements. Additionally, the regulatory landscape around data management has been rapidly evolving. Imagine the regulations around storing and processing health data, payments data, or children’s data, among others. And then, there are regulations specifically designed to protect consumer data privacy, such as GDPR.
Positively, while the regulatory landscape has been growing, so has regtech, which helps enterprises manage compliance. Enterprise leaders should actively explore regtech platforms that align well with compliance requirements and business priorities. For example, at LoginRadius, we balance the business need for identity management with compliance requirements.
Data privacy as a competitive advantage
Today, being proactive about data privacy is a competitive advantage. It is evident in the rise of privacy-focused alternatives to popular services like Google Search, Microsoft Outlook, and Dropbox, among others.
Privacy-focused doesn’t always require a radical reshifting of how business is carried out. It can begin with a friendly privacy policy that specifies what data is collected and how it helps deliver value to consumers, followed by clearly laying out how consumers can raise data privacy-related requests and what the enterprise does to safeguard the data.
Conclusion
As enterprise leaders become well-equipped to address the current data management and privacy needs, they should explore how they can ensure their data programs across the enterprise are future-ready. It is essential because the future of business will become more and more about combining industry-specific expertise and technical know-how with data management capabilities.
Originally published at VentureBeat
Deepak Gupta