In 2022, no one needs to be convinced of the importance of data to organizations. It is their lifeblood. Most organizations derive great value from the data they hold. It allows them to interact with customers more efficiently, delivering value and personalized service across multiple channels. Well-capitalized startups lose money for years, subsidized by venture capitalists, in the hopes of disrupting traditional industries and achieving market dominance based on the value of the data they accumulate.
But managing that data poses technical challenges and business risks. Organizations must understand their data landscape both to wrest new insights from it, but also to mitigate the potential downsides of data breaches and regulatory actions. Now more than ever, they must transition from being “data aware” to “data intelligent” and turn the data from a liability into an opportunity.
Technical Challenges of Enterprise Data Management
On the technical side, data resides across technology platforms, from smartphones and laptops to network servers and cloud software platforms, and across departments, from finance and human resources to marketing and sales. It often lives in places many of us aren’t even aware of, either due to tribal knowledge that has long since left the organization or a lack of documentation and maintenance of important data sources. It’s not feasible for enterprise-level organizations to manage data through human insight into the organization’s infrastructure.
Organizational Risks Posed by Data
The responsibilities tied to the data organizations hold have changed. Since GDPR went into effect in 2018, the world has witnessed an unprecedented revolution in the regulation of data. Transnational bodies, nations, states, and other jurisdictions have passed laws governing various types of data faster than most organizations can respond and comply. In the US, five states have posed comprehensive data privacy and protection laws:
- The CCPA and CPRA in California
- The VCDPA in Virginia
- The CPA in Colorado
- The UCPA in Utah
- The CDPA in Connecticut
As the laws are not uniform, compliance with each set of requirements demands deep understanding of the data organizations hold, consent obtained to collect it, purposes it may be used for, and how it is processed—just for starters. And the proliferation of threats to data also includes increasing frequency data breaches and ransomware attacks, as well.
Completing a data inventory is the first step. Without an intelligent, accurate, up-to-date data inventory, organizations can’t achieve their data privacy goals. Today, while the data privacy function leads the data inventory exercise, the legal department, cybersecurity team, and IT can and do benefit from the output with proper planning.
Strategic Benefits of a Comprehensive Data Inventory
An intelligent data inventory is, by definition, tied to the outcomes that the organization is seeking, whether it’s risk mitigation, regulatory compliance, data minimization, or some other set of business goals. With a data inventory, organizations can:
- Reduce Risk: Minimize material risk with a harmonized inventory that truly operationalizes and contextualizes data retention requirements and other legal and business processes. Help your organization by deleting redundant, obsolete, or trivial (ROT) data while retaining data that has a business use or falls under a regulatory regime.
- Access Deep Data Insights: Utilize rich, contextual understanding of organizational data to defensibly substantiate your privacy compliance decisions, litigation strategy, and risk management actions.
- Ensure Defensibility: Be ready to respond to any regulatory enquiries or civil litigation discovery requests, and legally defend organizational decisions and actions with documented business processing activities of ongoing lawful usage and storage of personal and/or relevant information.
- Orchestrate Efficient Processes: Leverage built-in robust processes to gain efficient and timely access to data and accomplish easy ongoing inventory maintenance. Apply insights gleaned from data to business decisions quickly and effectively.
