Imagine trying to view the entire night sky by looking through a straw. It’s impossible. Yet for many business leaders, that’s how they view their organization’s data — in pieces and largely incomplete. These disparate, piecemeal views can prevent organizations from realizing data’s value and identifying underlying risks.
Many industry leaders already understand that data is foundational for an enterprise to function effectively, communicate, make strategic decisions and ultimately help drive revenue. The marketplace already expects companies to use data for those purposes — and to do so holistically, safely and wisely, with an articulated strategy. But it’s not often happening.
- A chief data officer may be focused on data governance and quality.
- A chief financial officer may focus on reliable data to inform planning and decision-making.
- A chief risk officer may be concerned about data integrity and the accuracy of risk reporting.
- A chief information security officer may be concerned about classifying, encrypting and preventing the loss of sensitive data.
- A chief compliance officer may focus on data privacy and protection but also needs to think about how to marshal multiple departments together to help address various data management and compliance requirements.
What these corporate leaders may be missing: Their siloed views mean that their data is functionally at a dead end. When it’s not incorporated into one ecosystem, data can undermine the foundation for business operations, transformation and growth.
That could mean anything from endangering large-scale migration from legacy systems, hindering the adoption of artificial intelligence (AI) capabilities, inhibiting the ability to expand a product portfolio, or diminishing reporting, intelligence and innovation. If data cannot be protected and collected in a safe manner, a lack of focus on these risks can also affect regulators and consumer trust.
Full stop: Data is a business imperative
There are signs that some industry leaders are starting to realize what’s at stake. In PwC’s 2025 Global Digital Trust Insights Survey, 48% of the business executives responding told us they’re prioritizing data protection and data trust investments over the next year, ahead of technology modernization and enhancement.
But if leaders understand data’s criticality and risks, why are they still falling short? Why do organizations still view data risk as a technology issue handled by the IT department, rather than an enterprise-wide business problem? Data risk is likely becoming everyone’s concern, no matter where they sit in the C-suite.
Those business leaders need a holistic strategy to help them align on the risks. Traditional data governance alone, while still important, is no longer enough.
Managing data risks and gaining an enterprise-wide view of data can require an elevated and more encompassing approach. Moreover, a company that executes its data strategy well may be on the receiving end of greater trust from stakeholders in the marketplace — be they regulators, consumers, investors or other companies.
Yes, data risk can be a complex business problem, but solving it doesn’t have to be. It starts by understanding data risk in its many forms.
- 1. Know what data risk really is
- 2. Go for overall (not some) visibility into your risks
- 3. Rally your teams and help build up their skills
- 4. Start (and keep) asking the right questions
- 5. Stop treating data risk as an afterthought
1. Know what data risk really is
So, what exactly is data risk? At its core, data risk can be described as the exposure to financial or reputational harm caused by loss, limitations (e.g., inaccurate and poor data quality) and related issues to an organization’s ability to acquire, store, transform, move, protect and use its data assets.
While the concept of data risk is not new, the standards and expectations for mitigating risk to help maintain data quality and trust have only intensified in recent years due to many factors.
- Stricter data compliance: There’s been a steady stream of global and state regulations — the Consumer Data Privacy Act, EU Data Act, California DELETE, Protecting Americans’ Data Act (PADFA) — that require businesses to prioritize data privacy or face potential legal consequences if they fail to comply.
- Accelerated cloud transformation: 72% of “top performers” surveyed in PwC’s 2024 Cloud and AI Business Survey are prioritizing data modernization and migration to the cloud.
- Integration of AI capabilities: In the same survey, 69% told us they’ve implemented cloud data modernization to power AI and help unlock insights for all areas of the business, from various data sources.
Treat data risk as a business risk — otherwise, it can snowball quickly out of an IT silo into general business operations with unintended impacts. Here are some of the types of data risks that may be affecting your business.
| Risk type | Examples | Business impact |
| Data quality | • Data entry errors • Technical errors • Missing or misclassified data • Inaccurate or incomplete requirements • Poor system integration |
Relying on poor data quality can lead to compliance issues, uninformed decision-making and financial loss |
| Data protection | • Improper handling of customer data • Data breaches from third-party vendors • Poor data encryption practices • Unsecured APIs or integration points |
Opening the door to privacy and security vulnerabilities that could compromise customer data and lead to reputational damage, ultimately losing trust |
| Data loss | • Cyber attacks • Inadequate backup and disaster recovery plans • Less reliable storage and availability |
Experiencing an outage or downtime without access to important data to stay up and running, adding to possible response costs and putting customer relations at risk |
| Data compliance | • Non-compliance with third party data privacy regulations • Failure to identify and classify important data for disclosure, reporting, audit and retention |
Facing regulatory scrutiny on data use and sourcing along with possible fines and disciplinary actions |
| Data exposure | • Trade secrets or intellectual property theft • Insider threats and employee misconduct • Shadow IT and unsanctioned data usage |
Losing a grip on access rights and controls and putting your competitive advantage at risk |
No matter the type of data risk, you should have a cohesive strategy so you can be better prepared to inventory the data, assess the risks, apply governance and protection according to the risk levels, and establish appropriate ownership. Enhanced visibility can be the key.
