Sample Public Sector outcomes and the initiatives that
support them

Public sector departments and agencies have an almost unlimited number of data and AI use cases. However, with use cases you are planning or executing on now, five distinct outcomes rise to the top. All of these use cases are important to enable data accessibility, adoption and security while quickly scaling cross-functional data and AI solutions to support warfighter and business operations.

Enhance public services

Proactive citizen engagement
Service delivery optimization
Citizen feedback analysis

Drive innovation
and digital transformation

“Smart” initiative
AI-driven analytics
Digital services expansion

Deliver trusted AI
and enhance privacy

Identity management
Regulatory compliance
for data and AI
Access control policy management

Optimize operational
efficiency

Infrastructure management
Resources allocation optimization
Process automation

Promote transparency
and accountability

Open data initiatives
Streamline financial
management and reporting
Citizen feedback analysis

Outcome - optimizing operational efficiency

Optimizing operational efficiency is a perennial concern. Efficient operations can lead to significant cost and time savings, freeing budgets to be better utilized in other mission critical areas. Enhancing operational efficiency also has the added benefit of improving transparency and accountability and strengthening public trust. With more efficient operations, departments and agencies can not only perform their duties more effectively, but also respond faster to the needs and expectations of warfighters and citizens alike.

Resource allocation optimization

Resource allocation optimization refers to the process of assigning and managing resources in an efficient manner to minimize costs and maximize output. This includes staff, equipment, facilities and other resources. Resource allocation optimization helps to ensure resources are used effectively and efficiently, leading to cost and time savings and improved decision-making.

Disparate data sources: Various systems are often used to track resources, leading to disparate data sources. A complete and comprehensive view of resources is difficult to achieve, leading to inefficiencies
Inconsistent data quality: Varying level of data quality can lead to inaccurate analysis and poor decision-making, severely impacting mission performance and success
Lack of transparency: Without explicit visibility into how resources are allocated, it is nearly impossible to identify inefficiencies and areas for improvement
Inefficient discovery, access and reporting: Without efficient processes for discovering and accessing data, creating reports (and the decisions that come from them) take too long, leading to sub-optimal outcomes or worse

Increased productivity: Efficient resource allocation means less waste, leading to increased productivity and an overall higher output
Decreased costs: Optimizing resources efficiently and effectively will help reduce costs and budget overages
Increase confidence in decisions: With better data and improved visibility into usage, you’ll make more informed decisions, increasing confidence in resource management decisions and allocations

Outcome - Promoting transparency and accountability

Transparency and accountability is an essential component in the public sector and always a topic of concern for both lawmakers and citizens, especially when it comes to data. Transparency ensures the proper access to information about activities, decision-making processes and spending, allowing government staff and citizens to evaluate the performance of elected officials, projects, and departments and agencies. Transparency promotes accountability, providing clear understanding of who is responsible for both success and failures. Transparency and accountability fosters greater trust and enhances viability of data and AI initiatives while helping to prevent misuse and negative outcomes.

Open data initiatives

Open data initiatives are designed to make data available to the public in an effort to increase transparency, innovation and public services. This requires making data available to the public in formats that are easy to understand and use.

Lack of API repository and known data access: Without an understanding of what APIs you have available and the data sources they connect to, it can be difficult for users to find and access the data they need, which hampers the effectiveness of open data initiatives
Lack of data transparency and usage: Lack of visibility into the data being used, who is accessing it and how it is being used raises concerns about data misuse, making it difficult for initiatives to be trusted
Data protection: There are significant concerns about sensitive data (especially PII) being well protected as to not lead to data breaches or misuse, leading to eroded trust

Increased efficiency and decreased costs: By making data readily available, organizations can reduce the time and resources required to respond to data requests
Increased productivity: By making data easy to access and use, individuals and organizations can more easily use this data to drive decision-making and innovation, leading to increased productivity
Enhanced public trust: By making data publicly available and transparent, organizations can demonstrate their commitment to openness and accountability, which can help to build trust with the public
Reduced privacy risks: By carefully managing and controlling what data is made available, organizations can ensure that sensitive information is protected, reducing the risk of privacy breaches

Outcome - Deliver trusted data, AI and enhance privacy

With the amount of data being created on a daily basis and the overwhelming surge in AI, trusted data, AI and enhanced privacy are critical. By delivering trusted data and AI to department or agency staff, significant improvements in decision-making, enhanced public services and innovative new citizen services can be achieved. However, balancing the delivery of data and AI with the right protection and privacy of data is a must. Departments and agencies need to ensure breaches that compromise citizen data, mission objectives and national security do not take place.

Regulatory compliance for data and AI

Regulatory compliance for data and AI ensures adherence to laws and regulations (both external regulations as well as internal regulations). It is critical for departments and agencies to ensure compliance with accepted frameworks, like the NIST AI Risk Management Framework, to protect citizen information, avoid legal problems, and maintain public trust.

Identifying data elements that fall under data and AI protection: Understanding what data you have, where it is located, and who has access to it, and mapping that to specific regulations and laws can be a complex task, leading to wasted time, money and potential misuse
Documenting processing activities and ensuring accountability: Failing to keep proper records on how, who and what data and AI are used can lead to significant reporting challenges and legal penalties if data and AI breach laws
Managing consent and data subject requests: Without citizens understanding and controlling how their data is being used, trust in departments and agencies can erode
Lack of data protection and encryption: The absence of comprehensive data and AI governance policies and practices makes it harder to monitor and control how data is collected, stored, used and shared
No understanding of AI models in use: A lack of understanding of what AI models are already in use make it difficult to identify data usage and potentially harmful AI models/use cases

Increased productivity: With data and AI properly managed and governed from the start, initiatives are more effective, helping streamline employee productivity to focus on other work/tasks
Decreased remediation efforts and resource savings: With active compliance comes time and cost savings, eliminating the need for corrective measures in IT, finance, legal and other groups
Decreased risk of regulatory fines or penalties: Ensuring compliance from the start is the best way to avoid fines and safeguard trust

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Ensuring productivity and efficiency for your data and AI initiatives is key. Collibra is here to help guide you with capabilities and solutions to tackle any use case your department and agency needs.

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