Trust is a top-line initiative
Trust has been important to businesses for many years, mostly focused on transparency into business processes, and having a strong ethics program and code of conduct. However, these activities were often siloed within the organization.
Recently, we’ve seen a shift in how companies approach trust, as they recognize the advantages of building dedicated trust initiatives and making trust a top-level priority. This fundamental change has prompted organizations to reevaluate their approach, breaking down silos between privacy, security, ethics, and ESG. By connecting teams, data, and processes and the power of automation, companies can proactively foster trust as a powerful differentiating factor.
A new paradigm for data security
Every organization wants to use their data to become more competitive, make informed decisions, drive innovation, build solutions better attuned to their customers’ needs, and even develop and design AI. Yet, the unprecedented volume of data created and stored each day means companies are facing a new problem – data sprawl.
Data sprawl is the proliferation of data created, collected, stored, shared, and analyzed by businesses, primarily at the enterprise level. Today, organizations are managing their data across four-to-six platforms to manage data, on average. With more data spread across more platforms, the new concern is that many organizations don’t know what data they have or how it’s being used. Coupled with the rapidly evolving data, privacy, and compliance landscapes, new threats and challenges begin to emerge.
Why more data means more problems: A definitive guide to data discovery
While organizations have historically considered external bad actors and hackers as major threats to their data, data sprawl and lack of visibility into growing datasets and sensitive data adds another layer of risk. Without an understanding of an organizations’ data and where it resides, data becomes a risk. Can the organization confirm that sensitive and personal information is being protected adequately and used in a way that reflects consumers’ preferences and expectations, the right policies are set and enforced, deletion and retention requirements are met, and they have a solid understanding of the risks associated with their data? The inability to answer these questions means companies are more likely to suffer from potential regulatory enforcement, loss of trust, reputational damage, and financial consequences.
Building a fabric of trust
To address this issue and mitigate the risk of data, a trust fabric must be woven into the organization's architecture, continuously confirming that data is being used ethically and responsibly across the business. Businesses must consider their needs and goals when using data, across every team and department that is processing or controlling that information and regardless of structure. This infrastructure should be designed to monitor data usage, implement governing policies, and safeguard personal human rights and data rights. As more companies design and develop AI systems, having this infrastructure in place can help understand risks posed by AI across privacy, ethics, security, and more.
By focusing on purpose, transparency, choice, governance, security, and ethical considerations in their data, companies can establish themselves as responsible stewards of data. Responsible data use is now a business imperative, and the companies who embrace systems and processes rooted in responsible data use will have a competitive advantage in building and measuring trust.
Learn how to de-risk data and drive responsible data use across your organization: Join OneTrust at InfoSecurity Europe from June 20-22