Harnessing the value of data with data monetization

Businesses around the globe are using new technologies to change the world. But this wouldn’t be possible without the use of sensitive data such as Personal Identifiable Information (PII) and Protected Health Information (PHI) to drive advancements in personalization and sophistication. However, if companies are using data that typically is associated with medical records and insurance claims, this bodes the question, is personal data secure?

It is possible to balance data privacy with gleaning the value of the information through a data modernization strategy that enhances and accelerates digital transformation efforts.

Unleashing data’s potential with data modernization

The data companies have collected for years is a gold mine of opportunity. However, at the same time, new regulations and compliance requirements have made it challenging for companies to reap the benefits of this data.

Data modernization, which is a series of processes aimed toward unleashing the potential of data, is transforming companies into data-driven entities by generating actionable insights and outcomes from secure data that is stored in silos.

Benefits of data modernization

By eliminating data silos and enabling internal and external data sharing through data modernization, businesses can benefit from the ability to innovate further while customers benefit from an improved experience.

In addition to these benefits, data modernization identifies and mitigates sensitive data risk while delivering persistent and baseline data security across the data ecosystem and supply chain. With this comes enhanced regulatory resilience and stronger business continuity plans and processes, while accelerating data uses for AI, analytics and BI. Data modernization aims to remove data-driven barriers so companies can develop and market new products and services.

Strategic approach to data modernization

To establish a foundation for data modernization, data governance is critical for providing agile, secure, and remote access to data using data platforms, catalogues and tools. With this in mind, data modernization must be approached strategically, factoring in risk and compliance concerns to ensure resilience to the evolving threat and privacy landscape.

To develop a strategic approach to data modernization there are several key questions for companies to consider. Firstly, they need to identify and understand what the risks to the business will be. Secondly, they need to determine how they can apply data governance. Finally, it is important to know what regulatory requirements apply to data processes to effectively adhere to them.

The components of a data modernization strategy

An effective data modernization strategy relies on several components, the most important aspect being the quality of the data, as what you put in is what you will get out. As such, companies must integrate the data across multiple sources and then ensure the datasets are accurate, valid, concise and error-free by cleaning it. Further, the data must be made accessible to be used. This is achieved by establishing succinct data structures to improve cloud and on-premise accessibility.

With clean and easily accessible data, companies will benefit from using various tools and programs such as business intelligence, analytics, and AI/ML to derive valuable insights from the data. However, it is critical that data remain secure and data governance policies, procedures and processes must be in place to ensure data is protected at all times.

Finally, companies should incorporate cloud-based data platforms and tools to simplify data management and offer cost-effective solutions for scaling the data as needed.

Barriers to executing a data modernization strategy

In addition to these “must do” components of a data modernization strategy, companies need to be aware that there are also several barriers to overcome. A primary challenge for many organizations is aligning IT, security, and data teams to achieve mutually beneficial outcomes, and this alignment is crucial for ensuring all stakeholders are working toward a common goal.

Another significant hurdle is that of making sensitive data both secure and accessible to teams that can leverage it to enhance outcomes, experiences, and product development. This is particularly challenging as evolving privacy and data regulations dictate stricter controls and more rigid processes be put in place, thereby limiting access to specific data.  

To overcome this and continue innovating, companies need to balance data protection with usability to succeed in data modernization efforts without taking on too much risk. However, modern data security requires going beyond access controls to include encryption to protect sensitive data using fine-grained controls. In doing this, businesses are able to distribute, analyze and use data in a protected state while maintaining regulatory compliance.

Data modernization for commercial gain

Data is money, with many businesses already making money off their data. But they could benefit more from digging deeper into their data stores. Making data more accessible, without compromising on security, opens up creative ways to utilize data and advance analytics endeavors. This is where companies will reap the benefits and see the real monetary gains.

With a data modernization strategy in place combined with supporting architecture and tools to measure data outcomes, companies benefit further from the ripple effect which influences optimized internal data flows, new product development, and empowers sales teams in evolving markets.

To fully leverage and monetize their data assets, businesses must embrace data modernization and move beyond technology upgrades to reimagine how data is shared, accessed, and governed across their organizations.

Image credit: Gunnar Pippel/Shutterstock

Alasdair Anderson is VP at Protegrity.