Foster a culture of using data in policymaking

The fundamental challenge for governments these days - breaking the ‘data silos’, bridging legacy systems, organizational, operational, functional, and infrastructure gaps – all come down to enabling a culture of data-driven policy ecosystems. This article aims to provide tailored guidance to you on embedding a data-driven policymaking culture in your government. It includes aspects on: (i) Why is a culture change needed? (ii) What are the pre-requisites to designing/redesigning a data-driven policymaking culture within governments? (iii) What steps to take to build an inclusive and effective data-driven policy culture.

Foster a culture of using data in policymaking

Why build a data culture?

In the realm of data-driven decision making, it's crucial to recognize that the culture within your department or the government plays a pivotal role. While technical aspects, such as data infrastructure and analytical capabilities, are undoubtedly important, it’s the culture that ultimately determines the success of integrating data into policymaking. A data-driven culture encompasses mindsets, behaviours, and values that promote evidence-based decision making, collaboration, curiosity, and learning. A data culture means considering data and evidence by default in the policymaking process as well as the functions and functionaries linked to it. The power of evidence-based decision making doesn’t  merely translate into functional gains within the policy ecosystem but can also be quantified in the form of return of investments. An analysis of recent investments in data shows an average economic benefit of US$32 for every dollar invested.

Imagine farmers are protesting in a particular region, complaining of crop wastage and getting underpaid due to overproduction. The minimum cost being offered by government for their produce isn't acceptable to them. How would you have handled this situation using data? If your department (agriculture) used data, your field officers would have been able to visualize the trend/pattern of declining demand of a particular crop in a particular region. Data blended with local and socio-economic intelligence from field officers would have helped you anticipate the unrest and take proactive measures like organizing awareness camps for farmers using this data before cropping cycle, suggesting alternative crop options, allocating advance budgets for additional support for a particular region where the data shows high impact on livelihood of farmers, etc.However, is it possible to solve for this issue with a one-time intervention? Will such an approach be sustained? The success of this approach only materializes when governments systematically embed the culture of data-informed decision making in their day to day operations.

Key Terms

Data Mindset: A data mindset refers to the way individuals or organizations approach and perceive data. It involves recognizing the value of data as a strategic asset and embracing data-driven approaches to decision making. A data mindset encompasses attitudes, beliefs, and behaviours that prioritize the collection, analysis, and utilization of data to gain insights and make informed choices.

Data Behaviour: Data behaviour refers to the actions and practices individuals or organizations engage in when interacting with data. It encompasses how data is collected, managed, analysed, and utilized. Positive data behaviour involves adopting best practices for data collection, ensuring data quality, employing appropriate analysis methods, and using data to inform decision making. It also includes sharing data responsibly and respecting data privacy and security.

How to get started

How would you define a data-driven culture within a government? When a citizen interacts with the public sector on a digital interface, either directly or indirectly, it leaves data as a digital footprint. Lots of data gets generated within the public sector, but remains unutilized to the best of its potential. As you may be aware, different ministries provide different sets of public services, and in most developing countries,  multiple public service delivery platforms (digital and physical) are being used in silos with limited functional coordination and data sharing interventions.  

Each department has their own IT/Data Officer whose responsibility is to ensure data for that department is stored, compiled, and presented for measuring progress and impact on relevant KPIs, whereas the other officials in the department have limited access as well as low data literacy to use data in the day-to-day business of the government to enhance public services. The central IT/Statistics Ministry in most cases continues to battle with the challenges of data homogeneity, credibility, and policy coherence as well as coordination with multiple line ministries to enable collective impact using data.

Globally, governments have shared their experiences and advantages of fostering a data-driven culture within the systems. But the biggest challenge still lies in the status quo today - as a policymaker, are you aware of the value of fostering a data driven culture within your system? Is data only the domain of your IT/Data Officer? Is your team data literate enough to add value to your policies and programmes in real-time? How does it help you take evidence-based decisions? What does it bring for you, in terms of incentives and growth?  

As a policymaker, familiarizing yourself with the culture change process is essential for driving the transformation towards evidence-informed policymaking.  

Figure 1: Culture Change Process I Adapted from Walker & Soule

Secure high level political/ bureaucratic will

Measures to nuture political will

  • Engage political leaders and high-ranking officials in discussions about the benefits and importance of data-informed decision making.
  • Secure buy-in from your political leadership by organizing learning and sharing sessions with countries having strong evidence-based decision making culture.
  • Encourage leaders to champion data-driven initiatives and integrate them into their policy priorities and agendas.
  • Give leaders the visibility in global dialogues and publish success stories and whitepapers on how they’ve facilitated data to policy culture in their country’s development.

The UAE Government began their journey of embedding data and foresight in their policymaking process two decades ago. Data-driven insights by policymakers and experts with a strong political leadership in the countries has resulted in UAE’s Future Roadmap leading to policies/vision until 2071. Using data and foresight, the government has been able to prioritize and allocate budget to the most critical challenges for UAE and foster an open data culture within the government. There have been substantial investments on data literacy and capacity building of officials to achieve their mandate of data-driven policies and future-fit UAE. In light of implementing national strategies, the Dubai Government has become one of the first governments in the world to be 100 percent by digitizing all public services as well as fostering a data and digital culture within their systems.

Identify early adopters

Early adoption is a crucial phase in the process of scaling a culture of evidence-informed policymaking. During this phase, a subset of policymakers/government officials embrace and champion evidence-based practices, serving as pioneers and change agents. Are you one of the early adopters? Try to liaison with more early adopters.  

Early adopters are individuals who are among the first to adopt new practices, technologies, or approaches. They proactively seek out and incorporate evidence and data into their decision making processes. They’re enthusiastic about utilizing evidence to inform policy choices and are willing to take risks to experiment with new approaches.

For the process of scaling, early adopters serve as living proof that evidence-informed policymaking is feasible and beneficial. By showcasing successful examples, they inspire and motivate others to adopt similar practices. Their experiences and outcomes provide tangible evidence of the value and impact of evidence-based approaches.

As an integral part of the Internet of Things (IoT), smart and connected sensors are emerging information and communication technologies that collect and transmit real-time data from various urban domains to inform decision making. While smart sensors and IoT technologies have great potential to transform public service provision, their adoption in the public sector seems to be slow and incremental. Using cross-sectional data of 65 large and mid-sized cities in the United States on what affects local governments' adoption of smart and connected sensors showed that the local governments' early adoption of smart sensors is likely to stem from their needs in specific policy domains. It was found that a local government's historical path with urban sustainability and data-driven decision making practices can predict its trajectory of sensor deployment, in terms of the scope and the integration of smart sensors across different urban domains.

Demonstrate quick wins while keeping a long-term perspective

Both quick wins and a long-term perspective are important in fostering a culture of data-driven decision making. Quick wins generate tangible and immediate results, demonstrating the value of data-driven decision making. They help build momentum and generate enthusiasm among stakeholders, making them more receptive to further cultural changes. For instance, consider a school in your constituency that wants to enhance reading proficiency among elementary school students. A quick win would be to collect data on student reading scores from assessments or standardized tests. Analyse the data to identify trends, patterns, and areas of weakness. Look for factors that may contribute to low reading proficiency, such as attendance, access to resources, or teaching methods – and finally, decide on some high priority, measurable actions in the short- and medium-term. Such pilot interventions and learnings should be actively communicated among other schools of the constituency to attract interest and buy-in. This serves as a catalyst for long-term cultural change.  

Ultimately, keeping a long-term perspective is crucial in building a culture for evidence-informed policymaking. Building a culture takes time and sustained effort. A long-term perspective allows for gradual and meaningful shifts in how decisions are made, emphasizing the value of evidence and data. In the example above, this means expanding slowly, the number of schools that would take this data-driven approach in improving the results. Eventually, your goal is to embed data integration as a standard practice within the education system. This involves a) establishing systems and protocols for data collection, storage, and analysis across different aspects of education, such as academic performance, attendance, student well-being, and teacher effectiveness and b) motivating continuous learning in this space by identifying champions, incentivising innovation in solutions using data while building skills will all contribute to building the culture.  

How to continue building a data culture

Embedding a culture of data-informed decision making in governments can be a challenging endeavour. Change management is a persistent challenge when introducing a data-informed decision making culture in governments. There may be resistance to new approaches, scepticism regarding the value of data, and even concerns about potential job disruptions. While there’s no one size fits all solution, we provide for you here, a menu of measures that have worked for various policymakers in different countries.  

Build a network of champions

Champions are individuals who are passionate about data-driven approaches and can serve as advocates and role models for others.

Identify Potential Champions

  • Identify individuals within your teams who have a strong interest in data, analytics and evidence-informed decision making.
  • Look for individuals who have demonstrated a willingness to explore data-driven approaches in their work or have a track record of success in utilizing data for decision making.

Provide Leadership Support

  • Gain support from senior leaders and decision makers within the government to create an environment that values and supports data-informed practices.
  • Encourage leaders to actively promote and champion data-driven decision making by integrating it into strategic priorities and performance evaluations.

Empower and Train Champions

  • Offer specialized training and professional development opportunities to champions, focusing on data literacy, analytics and communication skills.
  • Provide access to resources, tools and technologies that enable champions to effectively analyse and utilize data in their work.
  • Foster a learning environment where champions can continually enhance their knowledge and skills through workshops, seminars and networking opportunities.

The Data Champions Network was established by the Department of Customer Service in 2018 and brings together data experts and enthusiasts from across the New South Wales Government (NSW). The network exists to improve coordination of the NSW Government data policy and practice, as well as promote best practices in data use, management and sharing.

The Data Linkage Champions network from the UK Government aims to improve the data linkage landscape across government.

Recognize and Reward Data-Informed Practices

  • Give room for incentivization by establishing recognition programs to acknowledge and celebrate individuals that demonstrate exemplary data-informed practices.
  • Incorporate data-driven performance metrics into evaluation frameworks for government officials.
  • Develop indexes to rank the high performing teams to build a positive, competitive spirit.

In India, the Ministry of Panchayati Raj has designed the Panchayat Development Index as a comprehensive index based on performances of rural local bodies. There's a ranking of the best performing local bodies every year that's awarded by the Prime Minister. This index is multidisciplinary and focuses on measuring progress through critical development indicators and enables capacity building of local governments. The index has been evolving over the past decade and fostering an incentive-based data-driven culture within local governments and rural development departments across the states as well as at the national level. It also encourages evidence-based planning and budgeting actions by rural local bodies, state governments and national government.

Encourage learning and knowledge sharing by showcasing success stories and best practices

  • Showcase success stories and case studies that demonstrate the impact of data-informed decision making within the government organization.
  • Leverage internal communication channels, such as newsletters or intranets, to share success stories and inspire others to follow suit.
  • Capture testimonials and success stories from individuals directly involved in data-driven initiatives, such as policymakers, government officials or community members.
  • Engage with media outlets to highlight success stories related to data-driven decision making. The more the citizens know about this, the more there’s a demand to include comprehensive data in decision making!

Build basic data skills in your teams

Skilling is time and money intensive, and it may not always be possible (or even required) to train all your team members with data skills. However, building basic data skills in your teams will promote an overall culture of innovation. Organize learning sessions or other easier to implement formats to build a basic understanding of data and its benefits in your team. Learn more about building data capacities here.

While it’s important for you to invest in getting your relevant team members trained in data literacy and collection, it’s equally important to bring a ‘whole of government’ perspective to your team and involve them in the entire process of the use of data - from collection to providing feedback loops to enhance the process and quality of data for better results, e.g. in the USA, significant improvements in the quality of data and processes have been observed, by involving community health workers in collecting and providing feedback loops across the complex data ecosystem of the healthcare system of the country.

What’s next?

Once a data-driven culture has been established, it’s important to continue investing in such culture and to regularly reflect if the culture is still a good fit for the organization.

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