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The World Economic Forum recently released the Global Gender Gap Report for 2021. The United States isn’t even in the top 20 for gender equality. Women only make up 14% of cloud computing jobs and 32% of data and AI positions.

Data-driven organizations understand that their data is a strategic asset and to properly harness its power it must be supported by a sophisticated data strategy.

Siloed data hinders collaboration and can cause serious downstream issues affecting multiple departments such as enrollment, claims and reimbursement. This data fragmentation stops the payer’s ability to get a 360° view of their customer, making it difficult to provide a more personalized experience.

In order to implement automation applications and other machine-based processing, data must follow an agreed-upon structure and standardization. The global healthcare community believes they are close to achieving this with Fast Healthcare Interoperability Resources (FHIR).

It is important that payer organizations continue to seek ways of improving their HEDIS scores year-to-year. One certain way of doing this would be to implement a proper data management system.

Many c-suite executives are perplexed at the amount of money their organizations spend implementing and integrating data and software applications with limited evidence that they will even align with desired business outcomes.

Master Data Management (MDM) allows you to manage data assets better. MDM’s goal is to implement best practices that will help you optimize the management of your organization’s data assets.

Today, many organizations have numerous applications and systems in which data, spanning multiple departments, quickly becomes fragmented, duplicated, and even outdated.

A well-known issue with legacy data platforms is what’s known as the garbage in, garbage out (GIGO) obstacle. As data began to flourish due to cheap storage options and increased digitization, data quality issues and fragmentation proliferated, creating GIGO issues that affected an organization’s business intelligence.

To progress to a future state of mature Data Governance and analytical capability, decision-makers should focus on starting with the integration of the data across an entire enterprise. A Data Governance program will be critical to support the continued growth of an organization.

Data is at the center of People, Process, and Technology, representing a crucial asset used by all three. Simply put, people should embed data in any project to ensure that organizations follow a defined road map around enterprise data governance; technology can also help enhance and automate several processes and transactions.