Agriculture: Bridging Public and Private Sector Needs

Data in the agriculture sector are highly fragmented, collected by both public and private sector, and too rarely shared effectively in a timely and harmonized way. DG’s work in fertilizer – together with the International Fertilizer Development Center and The African Fertilizer and Agribusiness Partnership – and seeds systems – together with The African Seed Access Index – has focused on bringing these disparate strands of data into meaningful analyses of agricultural inputs. Key data gaps in agriculture center on retail-level (e.g agro-dealer) information, as well as disaggregation of data by gender. Data governance challenges include 1.) identifying ways for private sector data to be shared and reused while protecting commercial confidentiality, 2.) and generating subnational data while preserving land – and other – rights of smallholder farmers.

Tobacco Control: Providing Data Users Can Trust

Tobacco Control data suffer from a similar dispersion as agriculture, although differ in one key characteristic: the perceived reliability and impartiality of data sources. The tobacco industry has invested heavily in generating its own data and evidence – ranging from support for new products like electronic nicotine devices (ENDs, or more commonly eCigarettes) to touting the economic benefits of tobacco farming – to discourage tobacco control legislation and enforcement. Governments, and their civil society counterparts, need access to a trusted source of data on key areas including: tobacco prevalence, use of new and alternative tobacco products (e.g. ENDs, shisha), economic and health impacts of tobacco use, and revenue impacts of excise and other taxes, among others. Finding these data, vetting sources, filling gaps, and presenting data in a validated and trusted manner all present their own unique challenges. Finally, capturing new data to fill gaps often calls for household surveys and other individual-level collection of sensitive data, requiring strict measures to collect data ethically and protect it effectively.

Open Contracting (OC): Getting to Impact

Each year, governments spend approximately $13 trillion through public procurement – 97% of this spending is not transparent or open to the public who fund government budgets. Governments themselves often lack the tools and analytics to assess how effective they are in spending public resources, as they seek to save money and efficiently procure services. DG’s support to governments from Chile to Makueni County, Kenya has helped to improve their procurement processes, saving time and money. The key gaps moving forward are improving government and civil society capabilities to assess the impact of improved procurement on service delivery – an area where DG is partnering with Hivos and the government of Makueni County – and the ability to perform more sophisticated analysis on pricing and competitiveness. Still, far too much procurement data live on paper, and there are significant gains to be made from continued digitization and standardization. Linking open contracting with beneficial ownership, while considering commercial confidentiality and individual privacy concerns, is a further frontier issue for OC data governance.

Extractives: Reversing the Flow

For nearly 20 years, the Extractives Industry Transparency Initiative (EITI) has called for and supported greater transparency from national governments and private companies on the deals and dollars of the extractives sectors. However, the flow of these data have been primarily oriented toward global transparency and reporting, while we have identified significant unmet needs for timely, transparent, and actionable data at the country level. Developing better local tools for data aggregation, standardization, reporting, and analysis has the potential to significantly improve the impact of EITI and EI data for decision-making. Additionally, evaluating the needs of women’s and indigenous groups – and weighing them more evenly with powerful constituencies within government and private sector – requires a rethinking of the extractives transparency movement to ensure that these resources are benefiting the communities from whom they are being extracted.

Moving Forward

While we have made strong contributions within each of the spaces above, we recognize just how much we still need to learn. As we share our reflections, we will also be reaching out to various partners, funders, and experts within each to see what we are missing, and inform our next steps in our refreshed strategy.

Photo credit (clockwise from top left): Vinisha Bhatia-Murdach, Ayotunde Oguntoyinbo,  Robina Weermeijer, Taryn Davis

In this paper, we have identified six components for the design and operationalization of institutional data strategies: This work aims to distill lessons learned from Development Gateway’s research and collaboration, designing data strategies with development and humanitarian agencies. In the current ‘data revolution’ era, data and digital are both a strategic asset and a source of institutional risk.

Strategies should be designed using:

•  a holistic approach,
• intentional leadership positioning, and
• a focus on the “right” investments.

Strategies should be operationalized through:

• responsible data practice,
• shared data use practices, and
• an appropriate governance plan.

We are continuously learning from our partners across various agencies, and hope this will be a useful starting point that may be adapted by organizational leaders to drive effective digital and data strategies in their institutional contexts.

Feedback about the approach outlined in this paper is welcome! Continue the conversation on social media using #DataStrategyPlaybook or by tagging @dgateway.

The development world is buzzing with excitement over the idea that new and emerging applications of artificial intelligence (AI) can supercharge economic growth, accelerate climate change mitigation, improve healthcare in rural areas, reduce inequalities, and more. But what does this look like in real life? 

Here’s an example of this technology in action: WorldCoin, a cryptocurrency and digital identity platform, wants to scan the irises of every person in the world to develop an AI-powered system to tell robots from humans. This sounds like the beginning of a dystopian tale, but it’s not science fiction. 

WorldCoin has already used its signature orb to collect biometric data from millions of people. And not surprisingly, the U.S./Germany-based company has run into regulatory troubles in many countries. In Kenya, for example, WorldCoin paid people around 7,000 shillings (just over $50 USD) to turn over their personal data, a practice which Kenya’s communication and data protection authorities labeled as “border[ing] on inducement.” WorldCoin’s activities were suspended in Kenya but are set to start again after a year-long government inquiry was recently dropped.

Regulatory challenges to the company’s activities are the highest profile example of what the Global Partnership for Sustainable Development Data’s network of partners are grappling with every day: namely, how to ensure that AI is deployed in development contexts in ways that help and don’t hurt people. Complementing these regulatory challenges are practical ones that arise in DG’s implementation work, for instance, how to audit a particular AI tool’s terms of reference and training datasets to assure its appropriateness for use in a development setting. 

The Global Partnership and DG recently hosted a series of discussions with development practitioners on the real-life applications of AI and related technologies in international development. Eighty-four participants from local non-profits, international NGOs, and philanthropic and academic institutions attended the online sessions from around the world.  

The purpose of these dialogues was to create a space for partners to share how they are thinking about AI and related technologies, including the opportunities and challenges they’re facing and practical examples of these tools on the ground. The three sessions were focused on distinct topics, namely: agriculture, climate, and health; conventional and new media; and Digital Public Infrastructure and digitization—three areas where we knew of existing examples of practical applications of AI among our partners. Across sectors, concerns emerged about the challenges of adapting digital technologies to development contexts and the power imbalances inherent to these activities, as illustrated in the WorldCoin example. But, overall, partners expressed a sense of optimism for the potential of AI-powered tools to provide solutions tailored to specific contexts, if we can overcome three key challenges. 

What we mean when we talk about “AI in development”?

When we talk about AI, we’re often referring to a broad range of computer-based systems that can perform complicated tasks that we would normally expect humans to do, like solving problems, diagnosing illnesses, reasoning, and generating novel images or text. (Here’s a brief explainer from the Simon Institute for Long-Term Governance.) During the online dialogues, participants shared examples of applying AI, machine learning, and related new tech tools in their sectors. Some examples included: AI-powered chatbots for healthcare workers using Large Language Models, forecasting technology trained on historical data to alert farms to upcoming shocks, using machine learning to analyze geospatial data for national agricultural policy, and more.

Three challenges emerged during the dialogues to building and using AI to advance development goals. These were: 

1. The push to develop and apply AI to development challenges largely ignores questions about when—or whether—AI is useful. 

Participants described sensing pressure—whether from policymakers, development partners, or funders—to seek out applications of AI in their fields. But they cautioned against seeing AI as a one-size-fits-all solution. In fact, there are limited situations where AI tools can currently provide helpful solutions. For example, chatbots that can help people without access to healthcare receive diagnoses and recommend treatments do not guarantee that medication or treatment will be available, accessible, or affordable. Because AI tools are best applied in the context of larger development efforts, there’s a need to make sure AI development is demand-driven with the needs of end users in mind and deployed in the context of wider, well-resourced programs. 

2. Access to appropriate training data is a barrier to creating AI tools to serve the most vulnerable.

Developing AI tools requires large amounts of training data. Ensuring that this data is representative of end users is a key challenge in development, especially because many of the people who are targets of development efforts do not have access to digital tools to generate data to train AI models. AI-powered tools generate analytics, text, or images based on the data they are trained upon. So, if you’re not in the data, the solution proposed by an AI tool won’t necessarily apply to your situation. One way to approach this, participants proposed, is by using intermediaries to collect data in the field. For example, having farmers use mobile (not smart) phones to text data to an intermediary that collects this data and transforms it into data for AI. But this is time consuming and costly. Data sharing could be one answer to this problem. But much of the existing data that could be used to develop AI tools is held by organizations, companies, or governments who are not incentivized or equipped to share it.

3. Decision-makers lack the knowledge needed to regulate and deploy AI tools.

Participants described a gap in skills and knowledge between the people who understand and develop this technology and the policymakers who have to make the decisions about whether and how to deploy and govern it. Bridging this gap requires democratizing information about AI tools, participants said, but most organizations don’t seem interested in funding or engaging in this work.

Moreover, policymaking silos structured around traditional sectors such as health, agriculture, or climate inhibit the potential deployment of AI tools to help identify trends across sectors. A case in point relates to climate change trend analysis and forecasting, which requires inputs from multiple sectors. If the policy and institutional structures are not designed to facilitate data sharing, then the opportunity to apply automated analysis and tools to solve cross-cutting problems such as climate change may well be missed.

How can we ensure AI tools are developed and used in fair and human-centered ways?  

As governments and organizations grapple with how best to regulate AI, it’s clear that many people feel left out of these conversations and are concerned with putting safeguards in place to protect people and prevent harm before it’s too late. As one participant put it, “AI cannot be a positive force without addressing issues of ownership and inclusion.” 

This is an especially complex question within development contexts, as the WorldCoin example above highlights. Can individuals anywhere in the world, who have very little understanding of complex AI systems, truly consent to their personal data being used to train algorithms? How should people be incentivized to contribute much-needed data to AI training? When do financial incentives become ‘inducement’ to participate? How do we measure or balance the benefits of AI tools against potential harms? 

These are complex questions that require inclusive and participatory exploration on a context-by-context basis. Involving practitioners, like those who joined the AI Dialogues Series, is one step in the right direction to ensure AI can become a useful tool. We invite you to weigh in on these questions or to suggest some of your own. Please reach out to jmclaren@data4sdgs.org and torrell@developmentgateway.org to stay connected to this work. 

These conversations will continue in 2024 through a series of online peer exchanges focused on AI for inclusive development that will be open for anyone to join. To ensure you receive an invitation to register, make sure you’re signed up for the Global Partnership’s listserv. You can join by emailing info@data4sdgs.org. 

The IMF predicts the global economy will shrink by 4.9% this year as a result of the Covid-19 pandemic. According to a Gartner market analysis, the global IT market will shrink by 8% in the next year as a result of the recession.

However, the government technology market is expected to be more resilient, shrinking by only 0.6%. In fact, two government technology sectors – IT services and software – are predicted to grow in 2020 despite the severe global economic downturn.

How is government digital transformation growing, rather than shrinking?

As governments look to “build back better,” we can expect an influx of government spending to stimulate the economy, and a shift in priority goods and services to purchase. As the world transitions from emergency response to recovery, governments’ focus will shift from using technology to procure other products (as we described in our first blog in this series), to procuring technology products themselves. For example, Covid-19 has underscored the need for digital governance: not only digitizing government processes and workforces, but also the services provided to citizens — including education, health, registration authorities, housing and citizenship applications, etc.

Covid-19 has accelerated government digitization efforts across the globe as Ministries of Education shift to online learning, Ministries of Health roll out telemedicine services, and government employees continue to telework and access secure government servers via the cloud. Digital transformation is no longer a choice, but a core need. Working on extremely short timelines, to meet an entirely new set of needs, governments have relied heavily on existing and new digital solutions to meet increasing demands. However, longer-term investments in government digital service delivery require more rigorous procurement and design considerations.

Digitalization to support and rehabilitate local economies

Increased government spending on digital and IT services will not only streamline public service delivery, but also stimulate the economy. Redirecting government spending to domestic IT suppliers and local SMEs provides the added benefit of supporting local economies as they begin to rebuild from the initial shock of Covid-19. This presents a ripe opportunity to create jobs and stimulate the economy – but understanding who well-qualified domestic IT suppliers are, and the barriers they face to engaging with public procurement processes, is critical for making sustainable and effective investments. For example, the Indonesian Ministry of Health and National Standardisation Agency are relaxing noise restrictions on ventilators so that domestic manufacturers can speed up production. Adaptive and flexible procurement policy reforms such as these can help ensure efficient government spending during, and after, an emergency. Created in partnership with the Global Digital Marketplace Programme, DG’s indicator framework is a tool that can help governments understand and take smaller steps from their current “as-is” state to get to their desired “to-be” state of digital procurement reform.

The path – and the tools – to rebuilding responsibly

Moving forward, global government buyers that seek to procure digital solutions must take lessons from Covid-19 into account regarding user needs and holistic approaches.

Fortunately, the body of resources for governments looking to build resilient digital solutions is growing. For example, buyers can refer to OECD research and digital strategies to consider how policy compliments digitization; draw on knowledge from Australia and the United Kingdom which have both put together criteria/codebooks on digital service delivery; and prioritize user-centered design principles to ensure that digital solutions are used, useful, and build resilience.

The Emergency Procurement Report: Lessons Learned from Covid-19 report and indicator framework are key resources for country governments looking to responsibly adapt procurement operations to address Covid-19. We encourage wide use of the tool to identify where to strengthen procurement responses during emergencies, sustain government services, and support the economy during and post-crisis.

With citizens’ lives on the line and government spending at record highs, ensuring accountability to citizens is imperative to maintaining trust and effectively managing KEMSA’s procurement in response to COVID-19. Open procurement data can help in improving the efficiency of emergency procurement and support civil society groups to detect corruption and monitor the effectiveness of service delivery.

“This level of transparency and through the use of technology will go a very long way in ensuring that we have the confidence of our people that those placed in institutions are able to manage the resources of the Kenyan taxpayer plus our development partners in an open and transparent manner” – President Uhuru Kenyatta

Much can be learned from Makueni County in Kenya, a county that publishes and uses open, accessible, and timely information on government contracting to engage citizens and businesses. The Makueni Open Contracting Portal is an interactive site built by Development Gateway (DG) that provides detailed information on each step of the tender, award, and contract implementation process at the county level. These steps are now recorded within the interactive Makueni Open Contracting Portal – making information available for citizens at each step of the process. The county plans to go a step further to publish all implementation data such as community monitoring reports, also known as PMC reports and supplier payment vouchers.

The goal of the portal is to improve the efficiency of public procurement management and support the delivery of higher-quality goods, works, and services for residents of Makueni County through enhanced citizen feedback.

What We Learned from Makueni County

Lesson 1: Public Data Improves Efficiency

The primary role of the Ministry of Health and KEMSA in Kenya during an emergency situation is to provide citizens timely, affordable, and efficient supplies and services. Digitizing and publishing procurement data will provide the Ministry insights on whether funding and services are reaching intended beneficiaries. 

Publishing procurement data will also encourage better monitoring from relevant state and non-state actors. The Ministry of Health and KEMSA will have the opportunity to aggregate non-state actors’ feedback and state actor insights. This feedback will enable them to make data-driven decisions that will improve service delivery to citizens, promote efficient allocation of resources and ultimately saving costs.

DG has developed interactive M&E dashboards to support analysis currently used by Makueni County. The series of charts and visualizations provide helpful data insights – such as top suppliers that received contracts and the percentage of awards that go toward the Access to Government Procurement Opportunities (AGPO), which requires tenders to be awarded to women, youth, and people with disabilities.

Since the start of the use of the Makueni open contracting portal in 2019, improved resource utilization and efficiency in procurement has been identified by the County leadership. Governor Kivutha Kibwana cited that the County has saved Kes. 30,000,000 from the Roads department as a result of using the portal.

Lesson 2: Building Trust is Essential to Combating Corruption

The complexity of emergency responses such as COVID-19 requires cooperation between the private sector, national, and county government to ensure timely delivery of supplies. KEMSA publishing data will promote feedback and engagement of business and citizens further building trust and collaboration. Publishing procurement data also equips civil society and citizens with the information needed to help combat corruption. For example, reporting counterfeits, frauds, and scams – which has been a key corruption issue identified globally in COVID-19 response procurement, particularly PPEs.

DG has implemented its corruption risk dashboard in Makueni, which uses high powered analytics and global research to identify risk profiles for potential corruption in procurement. KEMSA can adopt the corruption risk dashboard as a red-flagging tool to assist in identifying procurement activities that merit in-depth auditing of corruption risk – including fraud, collusion, and process rigging – over time. These analytics will allow the organization to address cases of corruption before taxpayer money is lost.

Lastly, publishing Beneficial ownership data can enable governments to quickly perform minimal standards of due diligence on companies they are buying goods and services from. As well as reducing the immediate risk of corruption, beneficial ownership data provides a valuable trail for future audit.

Over the last six years, Development Gateway: an IREX Venture, together with its partners AfricaFertilizer (AFO), an initiative of the International Fertilizer Development Center, and Wallace & Associates, collaborated to implement the Visualizing Insights on Fertilizer for African Agriculture (VIFAA) Program, which created dashboards and tools that improve, manage, and visualize fertilizer data in Africa. Sub-Saharan Africa (SSA) has the lowest fertilizer usage in the world, which needs to be improved to replace soil nutrients lost through crop production. VIFAA partners have worked with the public and private sectors to strengthen data collection, analysis, and use, encouraging informed fertilizer use across the region.

In the program’s final year (2024), leading up to its conclusion in November, the team undertook a “program learning process” to reflect on outcomes, challenges, and successes through internal interviews. This blog captures five key learnings, which we hope will guide similar programs aiming to bridge data gaps in agricultural development.

1. Participatory Approach as a Success Driver

VIFAA’s success is rooted in its participatory approach, involving stakeholders from the fertilizer sector from the outset of the program in each design and implementation phase. Rather than a one-size-fits-all solution, VIFAA emphasized co-design and customization to meet the specific needs of each of the 8 countries it supported. Fertilizer Technical Working Groups (FTWGs), organized by our local partner, AfricaFertilizer (AFO), facilitated this process. These groups brought together the private sector, customs, non-profit organizations, and the government to define relevant data indicators and validate data for each country’s dashboard.

The result is that each country’s VIFAA dashboard reflects local needs and realities. For instance, the Mozambique dashboard includes transit data visualizations to support fertilizer flow through trade corridors, while Nigeria’s dashboard displays locally blended NPK (nitrogen (N), phosphorus (P), and potassium (K)) data. This tailored approach, though resource-intensive, strengthened buy-in from diverse stakeholders, providing a robust foundation for the dashboards’ continued use and sustainability.

Lesson: Co-designing with end users is crucial, especially in multi-country programs, as it fosters stakeholder ownership and enhances program longevity.

2. Building Trust with the Private Sector

In the sensitive fertilizer sector, private stakeholders are often reluctant to share data. Despite this challenge, VIFAA included the private sector in its participatory approach. To address this, VIFAA used non-disclosure agreements (NDAs) to ensure privacy and build trust. This was key, particularly in countries like Nigeria, where private companies comprise a significant market share.

The successful use of NDAs encouraged strong private-sector participation, granting access to critical data and leading private companies to see the value of the dashboards, resulting in financial investments in their development.

Lesson: Building trust through confidentiality measures, such as NDAs, is one approach for securing private sector participation and access to sensitive data. This trust can also lead to long-term collaboration and financial investment in data tools and platforms from private companies.

3. Adapting Engagement Strategies to Country Context

Each VIFAA country presented unique realities, shaped by its market structure and stakeholder landscape. For instance, Nigeria’s fertilizer market is primarily driven by private companies, whereas Kenya’s market is mainly government-controlled. VIFAA adapted its engagement strategies to align with these dynamics, ensuring that stakeholders across the public and private sectors were meaningfully involved.

Some environments proved more challenging than others, often due to resistance from key stakeholders. This resistance stemmed from factors such as competition over market share, concerns about data quality control, lack of trust between public and private actors, fears around data misuse, and limited understanding of how shared data could benefit the sector and individual companies. This highlighted the importance of thorough upfront scoping, stakeholder mapping, and relationship-building. 

These lessons can guide future programs decide which countries to operate in and refine early-stage interventions. Additionally, it is crucial to set clear expectations when implementing complex programs across multiple countries, recognizing that priorities, timelines, and approaches will vary. An adaptive strategy should guide the initial phases and be embedded throughout the program’s change management approach.

A key outcome of this adaptive approach was the establishment of a dedicated fund to support new data collection efforts. This enabled VIFAA to move beyond relying solely on existing data, proactively addressing critical data gaps in each country.

Lesson: Context-sensitive engagement and adaptive strategies are essential in multi-country programs to build solid and sustainable partnerships and achieve targeted program outcomes.

4. Pioneering Innovations in Data Collection

To enhance data collection efficiency and overcome the limitations of traditional methods, VIFAA employed an innovative approach combining satellite imagery and algorithmic modeling in Nigeria and Ghana. This approach was designed to create crop-specific fertilizer maps, which could be especially beneficial in markets where ground-level data collection is costly and infrequent.

While challenges remain in implementing this method, particularly with on-the-ground validation, it represents an important step toward more efficient data collection. By piloting such forward-thinking methods, VIFAA has demonstrated the potential for technology to fill critical data gaps and provide actionable insights in agriculture. 

Lesson: Programs can significantly increase data coverage and utility by integrating cutting-edge technologies, and sustained investment in local partnerships is essential for successful implementation and validation.

5. Planning for Long-Term Sustainability and Capacity Building

As VIFAA’s end date approached, one pressing challenge was ensuring that local partners like AFO had the technical capacity to maintain and expand the dashboards. While AFO has strong sectoral expertise, sustaining and upgrading complex data dashboards requires specialized technical skills. This highlights the importance of incorporating capacity-building activities from the outset to enable local ownership.

The VIFAA team began capacity-building efforts with AFO. but recognized the need to further embed technical expertise within the team to manage complex tech components independently and build on existing capabilities.

Lesson: Programs should plan for capacity-building activities from the start, including technical training and simplified processes that enable local partners to maintain and adapt tools independently.

Reflections and Takeaways

The VIFAA program leaves us with valuable lessons for bridging data gaps and driving meaningful, data-informed change in agriculture. Collaboration with stakeholders during the design process ensures tools reflect local needs, building ownership, and sustainability. Establishing trust with private-sector partners through measures like NDAs opens access to critical data while fostering deeper collaboration. Tailoring approaches to fit each country’s unique context enhances the relevance and impact of solutions. At the same time, innovative methods, such as satellite imagery and modeling, address persistent data challenges and unlock new insights. Finally, investing in local capacity from the start ensures that partners can maintain and expand tools long after the program concludes. Together, these lessons highlight the importance of collaboration, adaptability, innovation, and long-term planning in creating lasting change.

Achieving resilient public procurement goes beyond digitization and automation: data generated through these processes must also be used by government to make smarter decisions – particularly during crisis – and by civil society to hold government accountable for those decisions. With citizens’ lives on the line and government spending at record highs, ensuring accountability to citizens is imperative to maintaining trust and effectively managing emergency response. Open procurement data can help civil society groups detect corruption and monitor the effectiveness of service delivery.

For example, In a bid to expedite PPE procurements and ensure timely availability of critical supplies, many countries moved to direct purchasing avenues that differ from traditional procurement. In some cases, “speed” has led to identified cases of corruption. In South Africa, this led to the government reverting back to its old procurement processes, and taking further steps to curb corruption and rebuild trust. These steps included publishing the identities of all winners of PPE contracts, rationale for selection, and names of losing bidders; the government also plans to publish the shareholder names of winning bidders.

The nature of Covid-19 requires rapid and informed resource allocation. Procurement data can help governments achieve this goal through understanding what priorities are; setting expectations for how much should be spent to achieve priorities; and ensuring suppliers are credible and can deliver.

First: knowing what and who to prioritize enables governments to focus scarce resources on purchasing the most critical items, and delivering them to communities most at risk.

Data from healthcare providers, sub-national and national procurement entities should be aggregated to understand needs and further inform budgeting. Publishing budget information and engaging with civil society can help authorities conduct spot-checks and ensure that funding and services are reaching intended beneficiaries.

Second: to curb price gouging, governments should publish up-to-date price lists for reference and use by all public procuring entities.

For example, as demand for personal protective equipment (PPE) soared in the early days of the crisis, so did PPE prices. Intermediary purchasers also flooded the market, looking to skim off profits by connecting desperate buyers with suppliers. Publishing information on prices, quantities of PPE distributed and engaging with civil society encourage citizens and procurement officers alike to monitor corruption risks.

Third: leveraging market intelligence – using data from existing procurement systems (such as IFMIS) and investing in new data sources – can speed up due diligence processes.

In many countries, procurement systems collect supplier data and efforts can be made to enhance this data to include financial solvency, sector qualifications, beneficial ownership information, and supplier performance evaluation(s). On its own, beneficial ownership data can enable governments to quickly perform minimal standards of due diligence on companies they are buying goods and services from. As well as reducing the immediate risk of corruption, beneficial ownership data provides a valuable trail for future audit.

Fourth: as mentioned throughout, publishing procurement data equips civil society and citizens with the information needed to help combat corruption.

For example, identifying and reporting fraudulent applications for relief funding; monitoring the use (or misuse) of emergency response funds; and reporting counterfeits, frauds, and scams. To enhance citizen oversight, the Government of Paraguay launched a mobile app that notifies users about everything the state procures during the Covid-19 emergency, from tender through award. In Makueni County, Kenya, Development Gateway is supporting the county government in enhancing the Makueni Open Contracting Portal (that publishes data in OCDS) to include Covid-19 procurement data. The County plans to tag all Covid-19 tender data in the system track and analyze this data to inform government decisions, and involve civil society and communities in the improvement of emergency procurement processes.

➙  track supplies needed against supplies procured; ➙  pool purchase orders across government administrations; ➙  identify and select suppliers quickly; ➙  extract contract data for market intelligence; ➙  open data for public oversight and transparency; ➙  protect existing suppliers and long-term economic sustainability.

Finally: while resources to build complex procurement data management systems may be difficult to mobilize, alternative data collection mechanisms can achieve much the same effect.

For example, standardized Excel templates or web forms that can be used to aggregate data from all relevant procurement entities. If open budget portals or websites do not exist, other tools and resources such as the Open Fiscal Data Package standardize the structure and the content of budget data so as to ensure data quality.

Another valuable resource for understanding how to collect and publish Covid-19 data is the Open Contracting Partnership’s guide to Covid-19 procurement data collection, publication, and visualization.