People have high expectations not only from their favorite brands but also from public services. How do you ensure the smooth handling of citizen requests? How do you set the right priorities? Fortunately, data analytics and AI are game changers for these government requests.
In a previous blog, we discussed the importance of preparing data and training people to increase an organization’s data literacy. However, even when the data is ready for analytical use cases, many organizations still struggle to embed the results in their processes. In other words, they find getting real value from their data difficult. In this respect, some public services are more mature than others.
Let’s look at some examples of AI supporting intelligent decisioning and streamlining citizen services.
Smarter and more efficient services
Government agencies need to incorporate AI-driven intelligent decisions into their operations to get value from data. Automated insights allow employees to maintain control while using their knowledge and skills more effectively. They help them make faster and more accurate decisions, reducing the workload and optimizing the service they deliver to citizens.
In the Netherlands, the Rijksdienst voor Ondernemend Nederland collaborated with SAS during the recent pandemic. Dealing with 300,000 requests for financial support, their response needed to be swift and accurate. Many entrepreneurs were in dire straits due to the health crisis. SAS supported the Dutch organization by classifying requests in terms of urgency. Cases that were not urgent or did not require input from an expert were added to a green stream; other requests that needed human intervention were collected in an orange or a red stream.
Applying automatic business rules shows how technology can process enormous amounts of data to improve workflows or set priorities. The possibilities are endless beyond this example, from streamlined inspections to fraud detection and efficient complaint handling.
Handling complaints and inspections
The same concept can be applied to guide inspections. In Belgium, customs services are using SAS to detect potential fraud. With high volumes of containers passing through Belgian seaports and airports, authorities cannot check every unit or package. In the past, they relied on experience to decide which containers needed closer inspection. Thanks to data mining and analytics, technology plays a key role in this process. As the algorithm gets more innovative, customs controls become more effective and accurate.
Intelligent decisioning is also highly effective for handling complaints. The Belgian FPS Economy, for instance, uses AI-driven decisions to manage its digital hub where citizens and companies can file complaints – whether about counterfeit products or purchases that do not meet expectations. Every year, the platform handles about 50,000 complaints. To navigate this, the 200 employees use analytics to classify complaints by theme and urgency. Additionally, the technology helps to transmit complaints directly to the appropriate person. This not only improves operational efficiency but also provides citizens with faster service.
The next step: GenAI
In the last two years, we have seen significant advancements in GenAI and large language models (LLMs), technologies capable of understanding and generating various forms of content. This progress opens new opportunities for government agencies to streamline their services. This is true for the Belgian Federal Public Service for Employment, Labor and Social Dialogue.
The organization has an extensive database with questions and answers about legal topics such as labor regulations and collective labor agreements. When employees, employers and even members of parliament ask questions, the FPS’s legal experts have to spend a lot of time and effort searching the database (with no guarantee of obtaining the desired search result).
To facilitate this process, textual analysis is used to identify relevant articles, allowing users to search for the information they need quickly. Thanks to the translation feature (Dutch/French), they don’t have to translate their search items. In addition, the tool automatically incorporates concepts and derivatives of keywords, resulting in substantial time savings and improved efficiency.
In the next phase, we’ll see LLMs unlock a range of opportunities, supporting the FPS’s legal experts with, for instance, article summaries. The technology would be able to generate sample responses. In my next blog, we’ll talk about the technology and the potential applications of LLMs for public services.
Ready to make strides toward citizen-centric services, better outcomes and more productive civil servants? Explore six considerations. Check out the e-book, Public service of the future, to learn how data, AI and generative AI in the public sector are catalysts for positive transformation.
