SEIU logo trademark belongs to Service Employees International Union (SEIU).
The Service Employees International Union (SEIU) was founded in 1921 with a mission to improve working conditions and healthcare for service sector employees. Today, this union encompasses 1.9 million members who utilize various services at institutions collaborating with SEIU in almost all U.S. states. Essentially, this union operates as a private healthcare provider, working on a model similar to our social security system. SEIU receives contributions directly from employers, ensuring its members have access to healthcare services. The organization consists of numerous smaller units called “Chapters”. Our experience includes the development of a service portal for the New York division and the overall data lake and data processing for the entire SEIU organization, aiming to ensure service quality and reduce manual labor.
Digitize existing processes to enable users to access services provided by the organization without needing SEIU employees' intervention.
Ensure the quality of digital services, considering both the organization's members and the organization itself, to guarantee timely payments for treatments or procedures.
Prevent misuse of new digital capabilities by users, maintaining integrity and fairness in the use of these services.
Develop tools that allow users to obtain all relevant information without having to physically visit the SEIU office or use SEIU employees' time.
The project faces critical technical challenges, including low digital maturity, limited computer literacy among members, poor data quality, outdated IT infrastructure, lack of data management policies, and an over-reliance on third-party data providers. These issues underscore the need for comprehensive training, data system overhaul, and process standardization for a successful digital transformation.
Lack of digital maturity and specific competencies needed for this type of digital transformation within the organization.
The average SEIU member has limited computer literacy experience.
Previously held and managed data were often unreliable, incomplete, or outdated.
Outdated and inefficiently managed IT infrastructure with security gaps and various technical limitations.
Absence of data management policy and responsible individuals; data was generally under the IT department's control without clear ownership for each data product.
No established standardized processes and environments for accessing, working with, or analyzing data.
Dependence on third-party data providers and inefficiently implemented data exchange processes.
The project entailed developing a comprehensive service portal integrating health and social security features, alongside creating a robust data lake and unified data model for organizational use. It emphasized secure data management in line with HIPAA, efficient IT infrastructure for handling large data volumes, and tools for data auditing and addressing third-party data issues.
Developed a service portal with functionality similar to a combination of E-health and Social Security systems, integrating not only members' health information but also helping to find the right specialist, allowing to view and manage one's insurance plan and accrued pension, and providing information about benefits and various taxes.
Created a data lake and a unified data model architecture that allows data to be used not only for portal needs but also to enable the organization's daily functions.
Established data "logistics" to ensure that data is flawlessly and continuously fed into the data lake, maintaining its freshness. Data is collected from other insurance companies, clinics, hospitals, rehabilitation centers, nursing homes, opticians, and dentists.
Developed a data management and protection architecture ensuring the security of people's personal health data in compliance with HIPAA regulations. Also implemented a model for employee data access that safeguards personal information even from the organization's internal staff.
Built an IT infrastructure capable of handling large data volumes, with a strong focus on optimizing cloud service costs.
Developed methods and tools for data auditing at all levels and stages of the data processing process.
Created tools and processes to respond to and manage errors or technical issues from third-party data providers.