Big Data in Citizen Experience: Implementing a Data Driven Strategy in Public Sector

The Public Sector & Data

The public sector has access to huge amounts of data, most of which is stored in different systems and formats. We know that this data can unlock many benefits, from improving citizen service to preventing errors, but how do you go about accessing the real value in all that data? 

We recommend that public sector clients implement an organisation-wide Data Driven Strategy. This strategy can be simple and easy to implement and doesn’t need to become a large task in itself. 

The 7-Step Approach

Once you have a strategy, your organisation can treat data as an asset that you utilise and enhance in the future. We recommend the following seven-step approach: 

1. Define Clear Objectives: Understand your business goals and how data can help achieve each goal. This involves meeting with senior leadership to align on priorities.  It is useful to have senior management “buy-in” to your project – so they need to clearly understand the outcomes the project will deliver. When possible, it is extremely useful to have a senior management level sponsor and a simple mission statement, e.g. will we improve educational outcomes by 5% because of this project. 
2. Assess Current Data Landscape: Evaluate your existing data assets, infrastructure, and usage. It is not unusual for organisations to have data quality problems, and many are even embarrassed by the quality of their data. This is where you can identify gaps and areas for improvement.   There is no need to be embarrassed or to let this hinder your progress as data quality is a challenge in most organisations. 
3. Data Collection and Integration: Ensure you have robust systems for collecting and integrating data from various sources. This might include upgrading technology, enhancing data collection and improving data access.  StableLogic support many clients with the development of an ETL processes.  ETL, which stands for Extract, Transform, Load, is a process used to collect, clean, and prepare data from multiple sources into a single, consistent format for analysis. 
4. Data Quality and Governance: Implement policies to maintain high data quality and establish governance frameworks to ensure data integrity and security.  This includes requirements to protect individuals’ data and regulatory requirements.  
5. Analytics and Insights: Use advanced analytics to derive actionable insights from your data. This can involve machine learning models and AI to predict trends and optimise operations.  Analytics is the detailed analysis of past data, which can spot trends.  Many organisations use tools such as PowerBI and Tableau to visualise the analytics into dashboards.  Next, use Machine Learning (ML) to make future predictions, e.g. to use our education example, forward model educational outcomes.  Finally Artificial Intelligence (AI) can make suggestions based on the large data set, to improve results. 
6. Foster a Data-Driven Culture: Encourage a culture where data is central to decision-making. Provide training and resources to improve data literacy across your organisation.  Not everyone needs to learn how to use the tools, but they do need an understanding of the benefits data can provide to end service users.  A strong data culture is not about creating fancy graphs for management, it should be about driving real world outcomes. 
7. Monitor and Iterate: Continuously monitor the effectiveness of your data strategies and adjust as needed. Regularly review metrics and outcomes to ensure alignment with business objectives.   

Putting Your Plan into Action

Using the data you already have can drive surprisingly significant improvements in service delivery to citizens.  For examples of how your organisation can benefit, please contact us. We are highly experienced at delivering data strategies, from the start of the process to developing ETL processes, visualisations and AI.