Chapter 1
Infrastructure has a direct impact on people’s lives. It provides citizens with essential services and has been associated with more than 80 per cent of the individual Sustainable Development Goals. It can shorten distances, facilitate trade, connect people, ensure access to education and health care, while also acting as a resource for job creation.
From a policy perspective, the efficient provision of infrastructure remains challenging. Poor governance, including integrity gaps and corruption, is often a blockage to effective infrastructure development.
Specific features of the infrastructure sector make projects particularly prone to governance failures and corruption. The high amounts of money at stake, the size and uniqueness of projects, the difficulties in monitoring, as well as complexity and technicality of major projects all act as challenges for the sector.
Integrity risks exist throughout the project cycle. Prior to public bidding, influence peddling and abuse of authority can bias decision-making and divert goals and priorities away from the public interest. During procurement and implementation, lack of integrity can lead to many forms of corruption such as bid rigging, kickbacks for contract award, embezzlement of public funds, and bribes to conceal low standards of work and regulatory breaches.
Decision-makers also face skewed incentives during planning and implementation. Politicians may propose unrealistic budgets to get costs approved more easily or give priority to new infrastructure instead of maintaining existing setups. Optimism bias and risk misrepresentation can also undermine infrastructure development, leading to a lack of realistic impact assessments and causing inefficiencies down the road. And the fact that “political priorities” remain the primary driver of infrastructure decision-making can open the door to many distortions emerging from biased priority setting and state capture.
Inappropriate project choice can create negative impacts beyond a bad investment choice. This includes facilitating corruption during implementation, feeding rent-seeking schemes and delivering infrastructure that fails to meet people’s needs.
Planning and implementation risk in infrastructure is a complex matter with no silver-bullet solution, but new technologies can help address these issues. Open data and e-government, for example, can facilitate the identification of red flags and are bringing significant savings to public budgets due to the deterrent effect of transparency. My research focuses on a different type of intervention: geomapping technology and its potential new uses to minimise infrastructure risks by:
Improving planning through a “systems” approach to infrastructure;
Providing objective grounds to guide and challenge project prioritisation and selection; and
Flagging inequalities and inconsistencies in the distribution of infrastructure.
Geomapping visualisations can give visibility into proposed and delivered projects, reducing the risks of “roads to nowhere” situations and planning failures. They can also shine a light on patterns and choices made, helping to identify integrity “fault lines” and improve accountability in decision-making.
I have developed three case studies to explore the potential uses of geomapping. Findings show how geomapping can trigger an in-depth analysis of decision-making, bringing to light issues of equality of distribution, population needs and political motivations.
A key takeaway of the research is the need to make infrastructure development accessible to all. Even when information is publicly available, expertise is required to understand planning decisions and the consequences that can derive from choosing one project or one region over others. Geomapping can translate complex decisions into accessible visualisations that can be understood and challenged, breaking down the technicality of the sector and helping democratise knowledge and strengthen accountability.
Chapter 2
A case study methodology was applied to the research, which was intended to explore different scenarios and compare outcomes. To cover different levels of economic development – low-, middle- and high-income – Uganda, Brazil and the UK were selected as case studies. The country selection considered different policy approaches applied to infrastructure development: (i) structured policies where infrastructure projects follow a formal process of appraisal and selection as in the UK; (ii) policies that provide general guidelines to decision-makers, with a medium-term horizon to assess political priorities as in the case of Brazil; and (iii) informal systems that, although they may appear highly regulated on paper, work on a case-by-case basis to decide on project approval, which is the dynamic in Uganda. The case study selection also took into consideration signs of integrity failures in decision-making processes and evidence of potential misalignment between policy priorities and the public interest. This was considered an important factor to test the geomapping approach as a tool to foster accountability.
Two key challenges emerged during the research process: tech-related and access-related. Tech challenges were mostly connected to the difficulties in using geographic information system (GIS) tools. This included my own lack of capability in operating sophisticated GIS tools, the high cost of paid versions of GIS tools, and limitations of open GIS sources, such as restrictions around the use of multiple layers of information in free-of-charge versions.
In terms of accessing information, the challenges were linked to a lack of information on project location, which required some projects to be excluded from the analysis, and databases that were siloed and non-interoperable, which posed difficulties with overlaying information in the same platform. After trials and iterations, the research exercise was developed using Google Maps, given its user-friendly interface and accessibility.
The research has limitations. The geomapping exercise covered only a small sample of projects, limiting the insights that could be generated from a quantitative study. From a technological standpoint, more sophisticated GIS tools could have been used to produce high-quality, multilayered visualisations. In addition, there may be small imprecisions in instances where complete addresses were not included in the public sources. In these cases, the name of the municipality, instead of the exact project location, was used to generate the maps. Since the purpose of the research was less a “tech test” and more an exploratory exercise to assess potential uses of geomapping, the choices made, although imperfect, did not compromise the analytical exercise developed and the critical assessment of the information generated.
Each case study focuses on a specific infrastructure sector: water, sanitation and hygiene (“WASH”) in Uganda, logistics infrastructure in Brazil and health care in the UK. The focused approach was used to facilitate data collection and simplify the visualisations. Given the complexity of running the exercise across the entire Brazilian territory, an option was also made to focus on a sub-national entity: the state of Piauí in the northeast of Brazil. Further detail on the case studies and how geomapping provided relevant insights for infrastructure development can be found below.
Chapter 3
Statistics show that 8 million people lack access to safe water in Uganda and approximately 27 million do not have access to adequate sanitation. This is a widespread issue in the country, but some regions are particularly exposed to water and sanitation challenges. Karamoja, in northeastern Uganda, is behind other regions in terms of latrine and handwashing coverage.
Karamoja also falls behind in other indicators. The region concentrates the worst social-economic conditions across the country: these are the poorest counties, with the highest poverty rates and lowest life expectancy, and health indicators that are below the national average and the average of western and central regions.
Sanitation and hand-washing coverage is also lower in Karamoja. During the Covid-19 pandemic, a vulnerability map prepared by the Ministry of Health confirmed the local frailty, showing that Karamoja and Teso, both located in the northern part of the country, had the lowest percentage of households with access to WASH facilities. The vulnerability map assessed four other dimensions – hospital coverage, population out of poverty, lower-risk demographics and connectivity – and again Karamoja (the sub-counties of Napak, Nakapiripirit and Kotido) and the neighbour region of Teso (Katakwi sub-county) were the most vulnerable sub-counties across all dimensions of vulnerability assessed by the Ministry of Health.
Integrity Issues
The World Bank estimates that, globally, between 20 and 40 per cent of public investment in the water sector is lost to corruption. This corresponds to annual losses in excess of US $75 billion. Corruption in the water and sanitation sectors manifests in many ways: from small bribes paid by consumers to have water systems connected, to collusion in the procurement of infrastructure projects and top-level embezzlement schemes involving private and public agents. In Uganda, the diversion of public resources has contributed to delays in expanding adequate water and sanitation coverage in the country.
A key challenge to integrity in the sector is the lack of planning. Without technical assessment of needs and solid reasoning to decide where and how to invest, corrupt practices can emerge and compromise decision-making. Undue influence in resource allocation can cause more than inefficiencies in the use of public funds; it can also perpetuate unequal patterns of investment and divert resources away from where they are most needed.
The mapping of new water points built in Malawi between 1998 and 2002, for example, indicated that half of the new points have been placed in areas that had already reached the recommended coverage density, while other areas, with pressing needs and issues, continued to lack access. Looking at local demographics and their needs can help target the unserved population and improve equality in access and provision of WASH services.
The Mapping Exercise
The responsibility for water and sanitation in Uganda falls within the remit of the Ministry of Water and Environment (MWE), which has the mandate to develop policies for management of water and environmental resources, provide safe water-supply and sanitation facilities in urban and rural areas, and deliver strategic planning of the sector. In some urban centres, the ministry shares regulatory and managing powers with the National Water and Sewerage Corporation, a public utility company that operates in 258 towns.
For the purpose of this exercise, I focused on infrastructure projects delivered by the MWE in order to cover urban and rural areas across the country, and I used the database of infrastructure projects provided by CoST – the Infrastructure Transparency Initiative to extract project information. Data available on the CoST portal is disaggregated by procuring entity which allowed a search for MWE projects. The database also includes reference to the geographic location of projects.
Projects that did not provide information on location or did not involve WASH infrastructure despite being procured by the MWE were excluded from the analysis. The list of infrastructure projects considered for the exercise comprises a total of 72 projects procured between 2016 and 2021 with a value of UGX 405 billion (approximately US $115 million), and is available in Annex A. The geo-map produced has been collated against a map of Uganda’s subregions for ease of reference (Figure 1).
Findings and Implications
A first reaction to the mapping is that the area between Kampala in the Central subregion and the district of Jinja in East Central concentrates a relevant portion of the WASH projects procured by the MWE. From a policy and political standpoint, the decision to locate a big share of the projects in this area is justified by the higher population density of the region. But the discrepancy in the distribution of projects does not go unnoticed. Whereas other regions received the lions’ share in the distribution, Karamoja received only one project out of the 72 – a water and sanitation supply system in the town of Amudat (Figure 1).
WASH allocation using population density is an important metric to bring objectivity to decision-making. It is a way to look at demand and allocate provision accordingly. But alone it can create distortions. Note for example the national atlas developed by the MWE in 2017. According to the source, Karamoja is shown as one of the subregions with the highest percentages of people with access to safe water-supply. This is because the atlas considers WASH coverage based on the region’s low population density, which produces a high average for Karamoja. However, when additional factors are considered – for example, the vulnerability mentioned above – the misrepresentation of the local conditions becomes apparent, as well as the gaps in accessibility faced by the population.
Issues in data reporting, where information may suggest a better representation of the reality, can mask local nuances and be misleading about the reality on the ground. It is considered in the literature as an integrity failure that can compromise an efficient and fair resource allocation. Inaccurate reporting can have bigger consequences in fragmented and siloed sectors such as WASH. When projects are implemented across multiple government departments and bodies, inaccuracies in data reporting can go undetected under the many layers of bureaucracy, reinforcing deficiencies and avoiding necessary changes towards more sustainable and equitable patterns of investment.
Decisions on project location and prioritisation require in-depth assessment and appraisal of local conditions, which includes consideration of needs, the beneficiary population, the benefits to be created by the project, as well as issues of equality and distribution effects. Accurately assessing the needs of the population is a vital part of the analysis so that there is value for money but also value for many. By cross-analysing population data, socioeconomic indicators and recorded vulnerabilities, inconsistencies in project allocation can emerge. The visualisation of Karamoja infrastructure worked as a first step to recognise discrepancies. The empty quadrant in the northeast of the country triggered a deeper understanding of provision versus needs in Karamoja.
The geomapping visualisation also provides an objective basis to question established decision-making processes. Historically, Karamoja’s remoteness has created a political dynamic where public services have mostly been provided by international entities and NGOs, which has lessened pressure on the government to direct resources to the region. The provision gaps identified in the mapping can help inform an objective new dialogue on investment reprioritisation in Karamoja and the role of the state in improving social conditions.
Concluding Remarks
WASH infrastructure is a serious constraint to sustainable and human development. Global events such as the Covid-19 pandemic and climate change are reminders that access to safe water and sanitation remains a widespread health challenge. Despite being a common good, water is often managed in siloes and with low transparency, which poses difficulties for policymakers to deliver consistent planning throughout the sector. Siloed approaches can perpetuate inefficiencies and inequality in the access and use of water and sanitation services.
An integrated view of infrastructure helps to visualise gaps in provision and in data reporting, compare demand and needs, and decide according to vulnerabilities. Geomapping is a tool that can offer a systemic view of infrastructure, particularly in sectors with high institutional fragmentation. It can be a way to question inaccurate reporting and identify instances where prioritisation assumptions may have become outdated, providing technical grounds to review political choices that may not be aligned with the urgent needs of the population.
In the water sector, poor project selection has critical consequences – taps run dry, toilets are not provided and hygienic standards are not maintained. Communities that feel the most severe impacts are the poorest and most vulnerable ones, where water provision is already deficient. This can cost lives and spread diseases. Geomapping can leverage the power of digital technologies to improve planning for a critical sector in society.
Chapter 4
Located in the northeast of Brazil, the state of Piauí has one of the worst socio-economic conditions in the country. Data from 2019 showed that more than 43 per cent of the population in Piauí live under the poverty line and 15 per cent remain in extreme poverty.
Inequality in the distribution of income is also extreme. An 18-fold gap exists between the top 10 per cent of earners and the bottom 40 per cent – the biggest such gap in the country. Urban patterns also differ from the rest of Brazil, with 34 per cent of the population – twice the national average – living in rural areas, and 74 per cent of the urban population located in small-sized cities.
Between the 1950s and the 1990s, Piauí was the poorest state in Brazil. After large-scale agriculture took hold in the regions of Tabuleiros do Alto Parnaíba and Chapada das Mangabeiras in the southwest of the state, income levels saw unprecedented growth that exceeded the national average as well as that of other states. However, inequality in growth is a noted pattern as most of the regional development is centred on the capital Teresina and in the southwestern portion of the state. Lack of connectivity and isolation are critical obstacles to more equal patterns of development in Piauí.
Integrity Issues
Corruption in Brazil is a long-standing problem. In 2014, the federal operation Lava Jato brought to light a sophisticated corruption scheme involving the highest political and economic elites in the country. Procurement fraud in infrastructure projects, illicit campaign contributions, money laundering and undue influence were some elements of the investigation.
The ties and alliances uncovered by Lava Jato are not new in Brazilian history. Wealth and political powers are so closely entrenched in the country that a specific term is used for this form of engagement – a “capitalism of ties”, a type of crony capitalism where the state apparatus is used to favour political and economic elites.
The infrastructure sector is particularly prone to this form of corruption. The high sums at stake and the close linkages between contractors and politicians can give rise to undue relationships to compromise adequate infrastructure development.
Brazilian media outlets have recently exposed events that indicate how this quid pro quo works in practice. According to sources, the Governor of Distrito Federal allocated BRL 7 million (approximately US $1.4 million) of the federal budget to renovate roads where his family owns properties in the south of Piauí. This allocation of money is part of the “secret budget” scandal that erupted in 2020, with allegations that President Bolsonaro had been illegally trading the public budget to secure political support. Infrastructure projects have been one of the main bargaining chips in the scheme.
The Mapping Exercise
For the mapping exercise, I used two databases. First, the publicly available record of projects delivered under the Federal Infrastructure Policy PAC that ran between 2007 and 2018. The PAC database allows users to search projects by state and by type of infrastructure, also providing information on project location. Given the issues of connectivity reported in Piauí, I focused on logistics infrastructure and excluded projects that did not contain information on location. A total of 11 projects, involving roads, ports and airports, with projects totalling BRL 13.8 billion (approximately US $2.6 billion) were identified through the exercise. The list of projects can be found in Annex B.
The second database refers to projects that had been approved in 2020 as part of the alleged “secret budget” scheme. The project list was obtained by accessing the government open data portal. Using the available project list, I filtered logistics projects in the state of Piauí in order to extract a sample. Projects procured by public entities in Piauí that did not contain reference to the location were excluded from the mapping. A total of 29 road projects with a total amount of BRL 158 million (approximately US $30.5 million) were used for the mapping. The list of projects is available in Annex B.
Three maps were produced for this case study – one for PAC and two for the 2020 “secret budget” (part I and II) – , and they have been collated against a map of Piauí (Figures 2 and 3). The separation in three maps was needed to accommodate the Google Maps layering limitations, but findings and implications are assessed together.
Findings and Implications
The first impression from the mapping is that despite two different governments and administrations, the pattern of distribution of infrastructure projects seems to have followed the parameters noted in the literature: in and around the capital Teresina, located in the region of Entre Rios, which received 30 per cent of the investment, and the regions of Tabuleiros do Alto Parnaíba and Chapada das Mangabeiras, where modern agribusiness is the core activity, that accounted for 21 per cent of the projects.
The isolation of some areas is also apparent. Take the example of the three regions with the lowest shares of projects allocation: Vale do Canindé, Vale do Rio Sambito and Carnaubais. Based on the vulnerability data provided by the Piauí Economic and Social Research Centre, Vale do Canindé has 60 per cent of its population rated as highly vulnerable and 12 per cent as very highly vulnerable; Vale do Rio Sambito has 33 per cent of its population rated as highly vulnerable and 33 per cent as very highly vulnerable; and Carnaubais has 62 per cent and 25 per cent respectively. Despite these levels of vulnerability, only two municipalities in each region had logistics infrastructure among the assessed projects.
Differences in population density do not explain the investment priority. It is true that the region of Entre Rios where the capital Teresina is located is home to 43 per cent of the population, but there is an equal population distribution between the other subregions. In reality, Tabuleiros do Alto Parnaíba, in the agribusiness portion of Piauí, has less than half the population of the regions that received the lowest investment shares: 46,675 inhabitants, in contrast to 106,753 in Vale do Canindé, 105,057 in Vale do Rio Sambito and 160,214 in Carnaubais. Considering how important logistics infrastructure is to connect people to new markets and jobs, as well as to basic services such as schools and hospitals, the lack of adequate logistics in the most vulnerable regions of Piauí can perpetuate and exacerbate local inequalities.
The geomapping also prompts additional questions about priorities and decision-making. PAC involved 11 logistics projects worth BRL 13.8 billion (approximately US $2.6 billion), and the 2020 budget included 29 projects at a total of BRL 158 million (approximately US $30.5 million). These are large and high-profile projects that have been prioritised. An alternative approach to connectivity could have been to spread the investment so that more areas could be integrated into the national economy. Smaller projects could also stimulate local participation in bids as small and medium-sized contractors are most likely prevented from bidding for large projects. Given the rural characteristics of Piauí and the small size of its economy, unbundling projects and covering more areas could have been a valid alternative to assess and compare connectivity outcomes.
The size of infrastructure also has an impact on integrity. Large-scale projects have a high risk of becoming white elephants. They also create more opportunities for corruption and require adequate planning to ensure value for money and value for many. The construction of the Trans-Northeast Railway (“Transnordestina”) illustrates the risk. Budgeted to cost of BRL 13 billion (approximately US $2.5 billion), it is still under construction, despite the project beginning in 2007. Multiple inquiries are ongoing to investigate irregularities in the project, including bidding issues and a threefold cost increase. Despite its strategic relevance for Piauí, as the railway will increase cargo capacity and connect grain producers to relevant ports, poor planning has been noted throughout the project, from illegally breaching protected areas to the impossibility of using one of the selected ports due to climate conditions. Regardless of planning and integrity deficiencies, the project has continued to receive funds from Brazil’s successive administrations since 2007.
Concluding Remarks
Challenging decision-making processes in infrastructure matters requires technical knowledge to question public priorities. Geomapping can provide initial steps to support civil society to “ask the right questions” and demand accountability from decision-makers. Looking at the distribution and size of projects and questioning alternative approaches is a line of accountability that geomapping can support. Assessing alternative project options is part of a project appraisal process, and red flags emerge when there is no solid evidence that different options have been considered.
Logistics infrastructure provides more than roads and pavements. Studies show the importance of connectivity to break hierarchical relationships, alter bargaining powers and improve outcomes for the poor. Bad connectivity, due to poor logistics, can create isolation and reduce the ability of citizens to access external markets, perpetuating inequalities and forcing dependence on local patrons. Having the technical grounds to challenge project priorities is a starting point to changing power relations and better equipping communities and civil society.
Chapter 5
The Covid-19 pandemic exposed vulnerabilities in health-care systems across the globe. Mistargeted policies and underinvestment affect everyone. But the poor and most vulnerable are especially affected by unequal access and opaque decision-making.
Mortality rates illustrate the unequal impact on disadvantaged populations. Comparison of data on mortality and vulnerability shows that higher levels of social and economic deprivation are linked to higher Covid-19 death figures. The Index of Multiple Deprivation (IMD), used to assess social and economic vulnerability, is an overall measurement of deprivation based on a number of metrics, such as income, employment, health, education and crime. According to the Office for National Statistics, the least deprived area in England recorded a Covid mortality rate of 58.8 deaths per 100,000 population whereas the most deprived area recorded a mortality rate that was 118 per cent higher, at 128.3 deaths per 100,000 population.
Recovery plans in the UK are focusing on infrastructure development to rebuild from Covid-19, and health-care investment is a critical part of the government’s “build back better” and “levelling up” agendas. In 2020 a new Health Infrastructure Plan was launched worth GBP 3.7 billion (approximately US $5.1 billion) to build 40 new hospitals by 2030. It is considered “the biggest, boldest, hospital building programme” to serve generations to come.
Integrity Issues
With Covid-19, a new wave of integrity issues emerged. In such emergency situations, public controls are often relaxed to expedite responses and this can provide opportunities for abuse. The chair of the UK’s Office for Budget Responsibility summarised the risk during Covid-19: “When the fire is large enough you just spray water and worry about it later.”
The health-care system faces additional vulnerabilities as the improper use of public funds can cost human lives in addition to the waste of public funds in a sector where corruption already consumes over US $500 billion a year globally.
The UK has not been immune to lapses of integrity during Covid-19. The National Audit Office identified weaknesses in the country’s procurement system, with real concerns about the lack of transparency, conflicts of interest and inadequate records of how public money had been spent.
The Mapping Exercise
For the mapping exercise, I focused on the 40 new hospitals of the Health Infrastructure Plan. As health care follows a devolution model in the UK, the new hospitals are limited to England’s jurisdiction. The list of the facilities and their respective addresses are available on the government’s website, which was used to generate the exercise map (Figure 4). A colour-code scheme was applied in the mapping to identify the political majority in the area of each project – blue in reference to the Conservative Party, red for Labour and yellow for the Liberal Democrats. The mapping considers party majority after the 2019 General Election. The complete list of the projects can be found in Annex C.
Findings and Implications
The mapping makes visible the high concentration of projects in the southwest part of the country, where 27.5 per cent of the total projects have been allocated. When adding the London area, which received a 15 per cent share, as well as the east of England, which also received 15 per cent of the projects, and southeastern England, with a 10 per cent stake, it is almost 70 per cent of the total projects located in the south of the country. This overlaps with many areas of Conservative Party majority in the 2019 election.
Although they receive a lower share of funding, the Midlands, northeast and northwest were included in the Health Infrastructure Plan, with 12.5 per cent, 10 per cent and 10 per cent respectively of the projects. These regions include major conurbations with high levels of deprivation such as Liverpool, Manchester and Leeds – traditional Labour strongholds. These are areas that have been greatly affected by the pandemic and will benefit from improved health-care systems.
Many factors come into play to guide decision-making processes related to health-care investment. The south of the country includes the largest metropolitan area, with more than 14 million people which represents 25 per cent of England’s total population. The southwest is an area where almost 30 per cent of the population is above the age of 65. These are valid concerns to drive investment allocation, particularly related to health-care projects.
As the Health Infrastructure Plan does not explain the reasoning behind the project selection, it is difficult to know which aspects were considered in the decision-making process. The plan mentions that projects have been selected from “a list of priority projects already in the pipeline” and based on “engagements with NHS England and NHS Improvement”, but the details of project selection are unclear. If internal assessments and business cases were developed, with a comparison of locations and expected benefits, it is in the public interest to gain access to these analyses so that citizens can at least understand the priorities. Dorset Healthcare, for example, which had five of its bids included in the government’s Health Infrastructure Plan, refused to clarify to the public the reasons for the successful bids – all located within less than 60 miles of each other.
The Health Infrastructure Plan recognises that “we need to get it right for the healthcare needs of today and the future”, so an opportunity exists to take account of the past, assess trends uncovered by the pandemic and respond accordingly to avoid future capacity shortages. In this vein, studies show that Covid-19 put a disproportionate amount of pressure on health services in the counties of Northumberland and Suffolk, as well as in the northwest of England, particularly Greater Manchester and Liverpool. These areas are liable to major health risks due to their older populations and the elevated levels of social deprivation. Distributing funds based on evidence of needs and short capacity can help respond to existing challenges and prevent future crises. It can also help depoliticise infrastructure investment in the eyes of the public, particularly when technical reasoning is not disclosed to justify decision-making.
Concluding Remarks
Geomapping is not a magic bullet for a complex matter such as health-care investment, but it can help policymakers and citizens to visualise the impact of infrastructure and the costs and benefits derived from each available option. Resources are limited and demands are multiple so prioritising infrastructure investment is part of political decision-making.
It is less about right or wrong decisions, and more about the hard choices to be made, which can have an impact on prioritisation of investment and equality in distribution when responding to pressing challenges. Knowing where to invest is a key step to optimise results, and a holistic approach that considers deprivation, the ageing population and health-care gaps should be an integral part of decision-making.
Chapter 6
The case studies explore different uses of geomapping to improve infrastructure policymaking, illustrating how key insights can be revealed and the power of the visualisations to further accountability and help target the unserved population. Regardless of the sector concerned, the mapping provides a new layer of information to better understand issues of accessibility and equality in the distribution of infrastructure. The findings also show that geomapping offers advantages to all stakeholders involved in infrastructure development.
For governments, there is more clarity on decision-making processes. Political priorities can be defended on objective grounds, which can leverage buy-in and support from allies, opposition and constituencies. Geomapping can improve the planning of infrastructure with a system approach where consequences and impacts of decisions are better understood and hard choices are grounded and explained with transparency. The case studies focused on specific sectors to illustrate the potential that can be unlocked. But combining different types of infrastructure is a viable approach to provide a holistic and systemic view of infrastructure, allowing better understanding of infrastructure interdependencies and fostering synergies, which are essential to minimise planning failures and “road to nowhere” situations. Digital twins and data visualisations are currently being used as tech models to improve city planning. Geomapping is a simple, affordable alternative to start the process of using geolocation to streamline planning and improve social outcomes.
For citizens and civil society, geomapping is a tool to enhance accountability. Visualisations can guide stakeholders to “ask the right questions”, using objective criteria to challenge political priorities and the choices that have been made. It is a way to flag inequalities in the distribution of infrastructure and identify patterns of investment that may not be justified or technically grounded. Given the skewed incentives existing in the sector, geomapping can help identify integrity risks and expose fragilities and biases in decision-making.
For policymakers, geomapping can be a game changer in the use of data-driven approaches to infrastructure development. It can provide an objective north to select and approve infrastructure projects, helping in appraising decisions and reducing the margin of arbitrary and non-justifiable choices. Given its low cost of use, it is an efficient technology to equip policymakers and officials with essential knowledge to propose fairer and better-targeted infrastructure policies.
In addition, geomapping can simplify and demystify infrastructure decision-making. This is a key takeaway from the analysis. Technicalities can conceal corruption and project complexity can create barriers to understanding and challenging decision-making. Geomapping visualisations can bridge this knowledge gap, “lowering the user threshold” so that information can be understood and acted on. This is particularly relevant given the asymmetries of information and power imbalances within the sector that put citizens and communities at a disadvantage when seeking to enforce accountability. But geomapping also helps to leverage the power of horizontal accountability. Developing opportunities to strengthen accountability between public entities and different bodies of the administration can improve outcomes and overcome difficulties arising from institutional fragmentation, decentralisation and power delegation.
The use of a simple, free-access tool to develop this exercise is testament to its potential. Key insights can be generated by placing project information into a digital map. The simplicity of the model demonstrates the opportunities for using geomapping to support informed policy and political dialogue. Crowdsourced geographic data and participatory mapping are being used for many purposes – for example, for disaster management and to identify the lack of public services. Applied to the infrastructure sector, geomapping can create a digital ecosystem that empowers stakeholders, fosters collaboration and enables meaningful participation.
The case study approach used in this research has limitations, but it does show the gains of using an affordable technology such as geomapping to optimise infrastructure investment and bridge the knowledge gap in the sector. And this even in contexts where infrastructure information is available and open to the public. Because of the complexities of the sector, data curation is essential to enable adequate understanding and rebalance power relations. Geomapping can translate complex data into accessible visualisations, helping democratise infrastructure knowledge and further accountability.
There are constraints to scaling up the use of geomapping – either by governments or independently by citizens as a monitoring tool. First, project information needs to be disclosed to enable the mapping. In many countries access to this data – even basic information – is a challenge, and this is a critical issue not limited to middle- and low-income countries. Without access to project information, a geomapping approach cannot be implemented or generate the intended impacts. Access to the internet and the digital divide are additional barriers to geomapping. Where internet access is lacking, intermediaries, such as civil society organisations, are required to bridge the divide and ensure the conditions exist for the data to be gathered and converted into geo-maps for the public. Political will is also key, particularly to grant access to information. Civic space to act and demand accountability is ultimately a necessary ingredient for a meaningful use of geomapping.
A final point needs to be made. Geomapping is not a panacea for all infrastructure problems. It is not a tech solution to replace participation as it should work as a channel of sharing and interpreting data to foster stakeholder engagement and not disengagement. It is intended as having a complementary role to existing accountability mechanisms, whether they are external audits, technical appraisals or public consultation processes, as geomapping adds a new layer of insights to existing methods. Geomapping can also apply in conjunction with new technologies. Blockchain and distributed ledger technology, for example, can increase transparency about project cashflows and clarify the origin of materials and services, while geomapping can highlight decision-making problems and provide a better understanding of the political and policy backstage.
Regardless of the infrastructure processes in place, a common threat seen in these case studies is how political and policy decisions on infrastructure allocation are determining the fate of local communities. Low infrastructure investment is perpetuating low social and economic conditions and creating a vicious cycle that traps people in economically challenging situations. Geomapping can shed light on these traps, helping reduce inequalities, target the unserved and connect people – exactly as infrastructure is supposed to work.
Chapter 7
Evidence from accountability initiatives shows that, in order to trigger social action, information needs to be understood and perceived as useful and actionable. More information does not necessarily translate into more democratic decision-making. Without the means to make sense of data, more information can result in less understanding, more confusion and less trust.
In the infrastructure sector, knowledge and power asymmetries are obstacles to adequate accountability – and this even in contexts where information is accessible to all. The sector’s complexity and technicality can hide integrity failures and widen the knowledge gap between powerholders and citizens.
Geomapping can help bridge the accessibility gap that exists in the sector. Meaningful access means being able to understand and react – and this is where geomapping has immense potential to guide and challenge decision-making. It is a cost-efficient tool to improve infrastructure outcomes, amplifying value for money without forgetting the value for many.
Acknowledgements
I wish to thank the CoST team in Uganda for their support in extracting data from the CoST portal; Daniel Arbix from Google for his guidance on the functionalities of Google Maps; journalist Marta Salomon for assisting me in finding information on the Brazilian transparency portal; and Gloria Prado and José Inacio Prado for their comments and insights. I also thank the Tony Blair Institute, which supported the research, and extend my appreciation to the Tech Policy team, in particular Benedict Macon-Cooney and Jess Northend for valuable discussions, Ruby Jarvis and Lucia Asanache for their thoughtful guidance throughout the process, and Robert Davies for his skilled copyediting. I am grateful to my colleagues at Engineers Against Poverty and CoST for their example of resilience to improve practises and processes in the infrastructure sector. Last but not least, special thanks to my husband Mick Smyth for his unconditional encouragement and for never refusing to proofread my work. This work is dedicated to policymakers and practitioners who believe infrastructure is more than roads and bridges, and can be a lifeline to individuals and communities.
Chapter 8
Annex A: List of Projects (Uganda)
Annex B: List of Projects (Piauí)
Annex C: List of Projects (England)
Figures
Figure 1 – Uganda infrastructure geomapping with subregions overlaying
Note: Emphasis on the only project implemented in Karamoja
Figure 2 – Geomapping logistics infrastructure under PAC
Note: Emphasis on the concentration of projects to connect the capital Teresina and to ensure agribusiness connectivity via the Trans-Northeast Railway, a project ongoing since 2007
Figure 3 – Geomapping logistics infrastructure under the 2020 “secret budget” (Part I and II)
Note: Emphasis on the concentration of projects to connect the capital Teresina and to ensure agribusiness connectivity in the southwest of the state
Figure 4 – Geomapping of the 40 new health-care projects in England colour-coded by the party majority according to the 2019 General Election (blue for Conservative, red for Labour and yellow to Liberal Democrats)
Note: Emphasis on the projects approved in the Dorset area
Lead Image: TBI