Developing institutional mechanisms for continued use of data in policymaking requires a multi-pronged approach that involves establishing clear processes, building capacity and fostering a culture of evidence-based decision-making. This article will take policymakers through the scope and benefits of different types of institutional mechanisms – at the local, national and international level. Closely linked to building data partnerships, it provides guidance on what’s worked for different governments in establishing such coordination processes.
Institutional mechanisms provide frameworks for continuous use of data in decisions, allowing organizations to identify trends, evaluate performance, and make informed adjustments promptly. This promotes agility and the ability to adapt strategies and operations based on real-time information. What goes wrong without institutionalising use of data in decision making?
Remember the challenges faced by all governments globally around collecting data during the COVID-19 pandemic? Most of you may have heard about discrepancies in the reported COVID-19 statistics, such as the number of confirmed cases, deaths, recoveries, testing rates and other related data, coming from different sources or authorities within your country. While there were many reasons for this given the scale and uncertainty of the challenge, inter-stakeholder coordination was indeed one of the major issues that significantly impacted the accuracy and consistency of COVID-19 data reporting. The involvement of multiple stakeholders, such as different government agencies, health departments, local authorities, healthcare providers, laboratories and other organizations, in collecting and reporting COVID-19 data can lead to a huge challenge of coordination in almost every country.
Before we go into what a good coordination mechanism may look like in situations like these, let us look at how human capacities are currently being utilized in different existing institutional mechanisms. Do you really need to build another mechanism for coordination? Or can you leverage existing ones? Therefore:
There’s no one right way of establishing institutional mechanisms. However, some practices have specifically worked well for policymakers trying to coordinate policy decisions at local, national and international levels.
Multistakeholder working groups on specific themes and subjects bring together individuals with specialized knowledge and expertise to address specific challenges, initiatives or projects. Most recently during the COVID-19 pandemic, many countries established task forces dedicated to pandemic response and management. These task forces included experts from various fields, such as infectious diseases, epidemiology, public health and healthcare delivery. They worked together to develop strategies, guidelines and protocols for testing, contact tracing, vaccine distribution and overall pandemic response. Some of these mechanisms indeed need to be developed ad-hoc with the nature of the issue in hand. However, establishing such working groups/task forces around various issues means more cross-functional collaboration and pre-existing mechanisms that enable rapid response and agility. This article further focuses on things to keep in mind while establishing and utilizing such task forces for data-driven decision-making.
To ensure that data is shared in a transparent, accountable and secure manner in such coordination groups, it's crucial to establish a governance framework. This framework should define roles and responsibilities of each member of the group, data sharing agreements, privacy protections and other key considerations.
Members are typically assigned specific roles and responsibilities based on their expertise, experience and the objectives of the task force. Common responsibilities include a) leading overall direction of the task force (chairperson), b) sharing subject matter expertise and data, c) planning initiatives and next steps, d) stakeholder liaison and e) communication and outreach. It’s good to establish a meeting frequency and other terms of reference while keeping in mind that some operational flexibility is needed.
Specifically for data, establish data sharing agreements that outline the terms and conditions of data sharing. This includes identifying what data will be shared, who will have access to the data and how the data will be used.
To ensure consistency and accuracy in data exchange between different stakeholders, it's important to establish data standards and protocols that specify what data should be shared and how. This includes defining data formats, data dictionaries and data quality standards.
Monitor, evaluate and institutionalize these groups (make them an integral part of your functioning) such that they’re a part of the data collection and management process. Consider practices shared in "Monitor policy implementation" and "Evaluate policy impact".
Establish dedicated data centres or similar units within the government organization. These centres can serve as hubs for data-related expertise, research and collaboration, providing consultancy services and support for data-driven initiatives across the government. They can invite, as needed, subject matter experts while dealing with specific issues.
At the national level, institutional mechanisms for data-driven decision-making typically involve the establishment of dedicated entities, frameworks and processes that facilitate exchange of data and more uptake in decisions. This involves various federal agencies, non-government partners that can come together to create systems that enable open data sharing. Examples include having data labs and intelligence units as a part of the government machinery. These are in many cases very impactful at the national level as it helps align national priorities, streamline data collection efforts and promote data integration across different sectors. Note that when it comes to the overarching vision of promoting more data integration, the national statistical offices are often an important starting point given the amount of data they host.
Establishing institutional mechanisms for data-driven decision- making isn’t a one-size-fits-all approach. It can vary depending on the context, objectives and specific needs of an organization or government. The process of establishing institutional mechanisms can be fluid and adaptable to suit the unique circumstances. For example, as an immediate response to the onset of the COVID-19 pandemic, many coordination mechanisms were established at the local, national and international levels – all having a strong element of data-informed decision-making. Various approaches are taken:
While different approaches may be suitable depending on the issue at hand, remember - establishing institutional mechanisms for data-driven decision-making is an iterative process that involves learning from experiences, feedback and adjustments. It allows for continuous improvement and adaptation based on lessons learned and changing needs. For instance, an organization may start with a small working group focused on specific data projects, learn from their successes and challenges and gradually expand efforts into a more comprehensive institutional mechanism.
Open data portals are also an important institutional mechanism for promoting data-driven decision making and fostering transparency and accountability. They serve as centralized platforms for governments, organizations, and institutions to publish and share their data with the public but also with each other. Some common benefits of having such standardized portals:
Collaborative platforms or frameworks bring together multiple countries and stakeholders to promote the use of data for decision-making processes at an international level. These mechanisms aim to enhance data sharing, knowledge exchange and coordination among participating countries and stakeholders to support evidence-based policies and actions. Below are some of the elements being actively considered in such cross-country mechanisms.
To ensure you’re on track for implementing institutional mechanisms for data-informed decision-making, consider the following indicators:
Initiating institutional change requires a comprehensive and strategic approach, along with sustained commitment and support from leadership and stakeholders. Strategies around building data culture, improving data capacities facilitating collaboration and partnership – all contribute towards this institutional change. To learn more, see the “foster culture change” section.