Data & AI strategy in Public Sector – extending citizens understanding and ensuring data readiness
Advisory
Public sector
MEA
Dominik Zuk
Co-Founder at Innsyte
Author’s historical experience before founding Innsyte
In the public sector, leveraging AI is no longer just about efficiency — it’s about transforming the way citizens interact with services. With the right AI ideation and advisory, public institutions can personalize citizen experiences and streamline data-driven decision-making processes. By focusing on “Reasonable AI” and “Ethical AI advisory,” public sector organizations can ensure that AI solutions are both impactful and aligned with their core values. This blog post delves into how AI ideation can be the cornerstone for building a robust AI strategy that not only meets operational goals but also enhances citizen engagement.
Please consider that the company as of 2024 still extends the approach and execute the strategy having fully dedicated team.
Please consider that the company as of 2024 still extends the approach and execute the strategy having fully dedicated team.
Improved Data & AI capabilities
Innovation boost
Strategy continues to be executed in 2024
Problem: untapped potential about citizens information
The public sector, especially in regions like MEA (Middle East and Africa), is under increasing pressure to improve how social programs are managed. These programs are critical as they cover financial guidance, empowerment, and activation for citizens. The challenge lies in assessing eligibility, which depends on various factors such as location, family size, and income. Currently, this assessment process is limited by outdated systems that lack integration, leading to inefficiencies and delays.
For instance, the information needed to evaluate an applicant’s wealth is only available after their submission to the dedicated system. This not only delays the process but also leads to inaccuracies in decision-making. There is still a disconnect between various data sources like ERP, CRM, and bank systems. This fragmented data landscape hinders the ability to deliver personalised services to citizens and limits the scope of advanced analytics.
The opportunity here is immense. By harnessing the power of AI ideation, public sector entities can integrate these disparate data sources into a cohesive system. This would not only streamline the process of determining eligibility but also allow for more accurate and timely decision-making. Moreover, by redesigning reporting frameworks and introducing AI and advanced analytics, organizations can gain deeper insights into citizen behaviour and needs, ultimately improving the effectiveness of social programs.
Solution: Advisory which built an AI strategy and planned ecosystem to personalize citizens’ experience
To address these challenges, one of our co-founders in his professional expertise proposed a comprehensive AI ideation process, designed to build a robust AI strategy and plan an ecosystem that personalises citizen experiences. This process was around creating a data ecosystem, a key component in unifying various data sources into a single, trustworthy data repository.
- Data ecosystem implementation: the core of the solution involved integrating data from predefined sources to establish a unified repository. This modern data warehouse was crucial in ensuring that all relevant data—ranging from ERP systems, CRM platforms, to bank reports—were accessible in one place. This not only improved data quality but also facilitated the automation of core processes such as wealth assessment for social program applicants.
- AI use-cases discovery: building upon the data ecosystem, we developed several advanced analytics use cases. For instance, we implemented a “Family & Members 360 View,” which provided a holistic view of each citizen’s engagement with social programs. This was crucial for monitoring their behaviours and ensuring that the services provided were both relevant and timely.
- Data governance and cloud framework: a significant aspect of the solution was the implementation of a complete cloud governance framework. This ensured that all data processes were secure, compliant, and aligned with the organization’s ethical standards. Additionally, we introduced a data storage and integration layer that streamlined the flow of data between different systems, reducing redundancies and improving overall efficiency.
- Data visualization and reporting: to make the data actionable, we designed intuitive data visualization tools and reports using Power BI. These tools provided public sector officials with real-time insights, enabling them to make informed decisions quickly. The redesigned reporting framework included up to 15 reports, with four new reports developed specifically to address the gaps identified during the ideation process.
- Automation and process optimisation: finally, we focused on automating several key processes, including the classification of expenses and the proactive management of potential beneficiaries. By leveraging AI, these processes were not only faster but also more accurate, allowing public sector entities to focus on more strategic initiatives.
The AI ideation process was a critical step in laying the foundation for a sustainable AI transformation. It ensured that all aspects of the solution, from data governance to analytics, were aligned with the organization’s goals and ethical standards.
Impact: scalable platform to manage talent potential in HR
The impact of this AI ideation and strategy was profound. Firstly, it provided the public sector entity with a clear and actionable roadmap for their AI transformation journey. The data ecosystem became a pivotal asset, enabling better data management, data analytics, and AI implementation.
“Data is the cornerstone of any successful Analytics & AI transformation. By building a robust data ecosystem, we not only enhance the current capabilities of the Data & Analytics team but also pave the way for future innovations that will significantly improve citizens’ experiences. With a clear Data & AI strategy in place, public sector entities can ensure that their services are both data-driven and compliant with regulations, leading to more personalised, effective, and ethical interactions with the citizens they serve.”
Dominik Zuk, Co-Founder at Innsyte
Lessons learnt from Data & AI strategy for Public Sector
Stakeholder engagement is crucial
The success of ideation depends heavily on the involvement of all relevant stakeholders. Limited inputs from business stakeholders can hinder the ideation process. Following our AI projects lifecycle guarantees it.
Feasibility study is required in each Data & AI project
Data & AI projects often require more resources than initially anticipated. Ensuring a realistic budget from the start is essential for the success of the initiative. AI feasibility study provides clear guidelines to mitigate it.
Prioritisation of engagement
Not giving enough priority to the engagement can lead to misalignment between the AI strategy and organisational goals. Regular check-ins and stakeholder alignment are key to maintaining focus. Executive buy-in is must-have.
Data readiness is crucial for success
Advisory highlighted that data readiness is key to public sector AI success, especially for personalising citizen experiences. Unified, reliable data improve decision-making and insights providing actionable results.
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