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  • Writer's pictureKarolis Duoba

5 steps of data-driven decision making in the public sector

Updated: Aug 23, 2023

Understand where you stand as an organisation with a five step guide to data-driven decision-making.

As the world becomes increasingly data-driven, the public sector is no exception. Data-driven decision making (DDDM) is the practice of using insights derived from verified data to make informed and validated decisions, rather than relying on assumption or intuition.

The use of data in decision-making has the potential to greatly improve the citizen experience while reducing costs, but many government organisations are still at the beginning of their DDDM journey.

To help you get started and understand where you stand as an organisation, here are five steps to data-driven decision-making.

Step 1: Define the Question

The first step in data-driven decision-making is to define the question you want to answer. This is where you identify the problem or opportunity that you want to investigate. Start by asking yourself what you want to achieve and what data you need to achieve it.

Step 2: Identify Data Sources

Once you have defined the question, you need to identify the data sources that can help you answer it. This may involve gathering data from internal systems, such as the GovMetric CX panel, your CRM or financial management software, conversations with front-line staff or external sources, such as social media or public datasets.

Step 3: Analyse Data for Insights

Once you have collected the data, the next step is to analyse it to extract insights. This involves using statistical and machine learning techniques to identify patterns and trends. This step helps to provide evidence-based insights that can inform decision-making.

Step 4: Take Action

The next step is to act based on the insights obtained from data analysis. This may involve changing business processes, introducing new policies, or investing in new technology. The important thing is to take action that will improve the situation or address the problem identified.

Step 5: Measure Results

The final step is to measure the results of the actions taken. This involves collecting data and analysing it to determine whether the desired outcomes have been achieved. If the results are not satisfactory, the process can be repeated, starting with a new question.

Data Maturity Model

As with any improvement journey, it is important to track your progress as you go.

To help organisations do this, a data maturity model can be used. This model assesses an organisation's level of maturity across a range of areas, such as data management, analytics, and decision-making. By rating yourself against this model, you can identify areas where your organisation needs to improve and create a roadmap for your data journey.

Data maturity model

To assist with data-driven decision making in the public sector, solutions like GovMetric CX can be utilised. We have been helping public service providers to design and deliver better services for their citizens and communities for over twenty-six years.

Our leading CX management solution is designed exclusively for the public sector and is trusted by dozens of local authorities as well as housing associations, police forces, and national agencies.

The journey towards data-driven decision-making in the public sector can seem daunting, but by following these simple five steps and tracking your progress, you can start to harness the power of data to improve the citizen experience and reduce costs.


Karolis Duoba is the Marketing Manager of GovMetric, home of the leading Citizen Experience Management solution for the public sector.

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