The public sector is increasingly employing data analytics solutions to serve its citizens better, decrease costs, and enhance business processes. As the digital experience is frequently changing, and new technologies and artificial intelligence (AI) capabilities are emerging, government entities must become aware of, and prepared to adapt to, upcoming data analytics trends.
Gartner predicts that by 2026, government entities that develop purpose-driven AI are over 80% more likely to have their AI innovations succeed than those who don’t. This level of success is expected because data analytics capabilities are developing a strong track record for rapidly streamlining government processes and providing fact-based information for enhanced decision-making.
As we have recognized in recent years in our data-driven world, greater and greater quantities of data are becoming available, and having the ability to distill such a vast array of data down to accurate information is critical in the public sector.
A variety of data analytics trends will continue to impact the public sector. These must be addressed and prioritized to drive productivity, effectiveness, information security, and citizen-centric services.
Here are some top data analytics trends that are set to skyrocket in 2023:
Gartner predicts that by 2025, AI data models will replace 60% of existing centralized data architectures. But not all such models are the same. Does your government entity review AI-specific data management problems, such as bias in coded algorithms? Bias in algorithms can have a major impact on underrepresented communities. Organizations can help address this and other issues by adopting data-centric AI, which incorporates machine learning and other techniques that enable the AI to learn from the data rather than relying on algorithms. Data-centric AI also drives improved data-collection and labelling methods. Data-centric AI is becoming a component of the data management strategies of many government organizations.
Another major trend is the use of context-enriched analytics to optimize the relationship between data points and deep analysis. Such analytics take into account the medium users are employing to interact with the content, such as a Web browser, a mobile phone, or a tablet. Context-enriched analytics can be embedded in business applications to better correlate analytics reporting to the context of the business need. By embracing context-enriched analytics, government entities can gain a deeper understanding of user behavior, and thus be able to improve, and often customize, the citizen experience.
Challenges with Data Literacy
Another data analytics trend we anticipate in 2023 in the public sector is a continuing shortfall in data skills and literacy, primarily due to heightened competition for talent and an increase in virtual workplaces. It will be important for government entities to hire and retain resources with the ability to read, write, and communicate data within the organization to properly leverage data analytics to support the business strategy. Due to the increasing cost of, and competition for, quality data-literate personnel, it will likely become more and more difficult for government entities to maintain the data literacy necessary to meet their business goals.
Increased Data Sharing
Data sharing has always been a critical aspect of data analytics. We expect to see increased capabilities across enterprises to share data at scale with safety and security measures in place. Increased access to large volumes of data will enable deeper and more refined data analysis. By improving data sharing within and across departments and agencies, government entities can enhance collaboration, uncover new insights, and better align data to specific tasks.
Another trend we anticipate in the coming years is the use of data analytics solutions to enhance business governance for the public sector. The solutions that will be most effective are those that orient their data and analytics governance practices around the business rather than just the data. By prioritizing business outcomes and identifying clear business metrics to define success, organizations can focus on the data analytics that help them better achieve those desired outcomes. Also, by establishing governance of data and analytics across functions, departments, and agencies, governments can improve the quality, consistency, and completeness of their data, which will help paint an accurate picture of the health of the organization and its effectiveness in serving the public.
Data analytics solutions will continue to advance in the upcoming years, bringing improved governance, data sharing, context-enriched analytics, and data-centric AI capabilities. Data analytics solutions will continue be leveraged to deliver timely information to enhance decision-making and drive enterprise-wide improvements.
At Synch-Solutions, our expert team can help your government entity better leverage your data and provide predictive analytics for reporting, strategic planning, and decision-making. If you would like to learn more about how our data analytics solutions can benefit your government entity, contact us today.