Abstract
A unique project by Mistra Urban Futures to test the draft targets and indicators of the proposed Urban Sustainable Development Goal (Goal 11) in five diverse cities in Europe, Africa, and Asia revealed numerous complexities and differences in data availability, potential accessibility, and relevance. Deploying the findings from Kisumu and Cape Town, we highlight the particular challenges posed by widespread urban informality. Similar issues apply across the global South. The targets and indicators rely on official/formal data, which are often of questionable reliability and exclude unregulated activities. The particularly problematic conceptualization of the slum/informal settlements indicator is examined in depth, along with indicators on transport and waste management.
Introduction
As part of the United Nations’ (UN’s) post-2015 development agenda, the Sustainable Development Goals (SDGs) will replace the Millennium Development Goals (MDGs) from 2016 to 2030. Whereas the MDGs have been focused on tackling poverty in poorer countries, the 17 SDGs will apply to all countries in recognition that transitioning to more sustainable development globally in an interdependent world requires commitments and substantive changes to the status quo by each country, regardless of its current state of economic and social development. For the SDGs to become effective policy tools for ensuring and monitoring sustainable development, the availability of reliable and robust data at comparable scales is crucial. The UN Secretary General’s Independent Expert Advisory Group (IEAG) argues for a data revolution in which statistical systems must be strengthened at local, national, and international levels and new means of collecting data of high quality and coverage are promoted (IEAG, Citation2014, p. 8; Simon et al., Citation2015).
A key innovation within the SDGs is the introduction of a sub-national Goal for the first time, focusing on urban areas, which have undeniable importance to sustainable development everywhere in today’s predominantly urban world. Inevitably, this presents both a potential political challenge to national governments and practical question marks over the practicability of Goal 11: To make cities and human settlements inclusive, safe, resilient and sustainable. This article is based on a pilot study conducted by Mistra Urban FuturesFootnote1 aimed at assessing the measurability of the proposed targets and indicators (see Table ), their relevance to the participating cities, and the possibility of annual reporting as required. Five cities across three continents participated, including two in Africa, namely Cape Town and Kisumu. Similarities and differences between these two cities (and the other three, i.e. Gothenburg, Greater Manchester and Bangalore) emerged in terms of data availability and deficiencies, the ease of filling such gaps, and the perceived relevance of some targets and indicators.
Table 1. UNSC (Citation2015).
One of the project’s key findings centers on the notion of informality, in this article loosely understood as being beyond the framework of state regulation, yet without accepting a dichotomous understanding that suggests informality to be separate from and parallel to, formal activities. Indeed, there are often strong, complex, and dynamic complementarities and interrelationships between formal and informal activities (Groenewald et al., Citation2013). These have been analyzed from numerous different theoretical perspectives over time (Simon & Birch, Citation1992), including modes of production and regulation, neoliberalism, a spectrum of income-earning opportunities; (sustainable) livelihoods approach, and survivalist lived experience. Various forms of informality are widespread in urban areas of low-income and many middle- income and transitional countries, in extreme cases such as Kinshasa, Mogadishu or Addis Ababa actually accounting for the great bulk of economic activity. In such contexts, informality is normal and familiar, not deviant and somehow unnatural (Simon, Citation2011, Citation2015). Even in many high-income countries, unrecorded or ‘black’ activities mean that official data underreport the total size of the economy to some extent. Although informality is frequently connected to poverty, this is too simplistic and needs unpacking. A proliferation of policy recommendations from respected institutions and academic outputs nevertheless still relies on homogenizing and dichotomous understandings of informality,Footnote2 which in turn result in misleading data collection (e.g. Lucci, Citation2014) and ultimately uninformed policy or decision-making.
In this context, the current draft targets and indicators within Goal 11 do not cater adequately for substantial informality and its implications for the availability and reliability of official data. Almost by definition, this would be very difficult to do but does not gainsay the reality of the problem. For purposes of this Special Issue, we examine issues of informality and their implications with particular reference to the two African case studies in the pilot study, focusing primarily on Kisumu, where the extent of unregulated activities is greatest, and drawing parallels to Cape Town as appropriate. Naturally similar issues appeared in Bangalore but drawing parallels to these is outside the scope of this article. Highlighting these concerns is not intended to undermine support for the objective of Goal 11 or the SDGs in general but to raise awareness of the challenges for at least two important reasons. First, expectations of Goal 11 should not be unrealistically high and, second, in the light of these findings, focused strategies and capacity building programs might warrant being formulated to assist local authorities in such contexts to enhance data collection and reporting as tools to promote the intended transitions towards sustainable urban development.
The principle of global applicability
The complexities involved in developing a set of targets and indicators for the SDGs, that are to be universal and applicable to all countries, are well illustrated through the Mistra Urban Futures’ pilot study, aspects of which are reported here. Although Goal 11 cannot be implemented in isolation from the other SDGs, one of the main difficulties is that there are no standardized metrics for measuring the complex domain of urban development in which local and national governments are only two of many actors alongside the private sector, non-governmental organizations and citizens. There is not even a universal definition of what constitutes an urban area. A major concern is, therefore, how to strike a balance between universally and locally appropriate definitions and thus ensure meaningful translation into policy and planning.
The principle of global applicability entrenched in the SDGs has been difficult to achieve even across the five cities studied due to varying practices of data collection and capacities to process the data, along with discrepancies between local definitions, which taken together greatly complicate cross-city comparison. In one of several reports on how to localize the targets and indicators, it is suggested that data constraints are more pronounced at the sub-national level than nationally (UCLG, Citation2014, p. 9). The stand-alone urban Goal 11 is therefore expected to mobilize and empower local and regional authorities and other urban actors through local ownership (UCLG, Citation2014, p. 7). However, implementation of Goal 11 is thus very likely to face substantial political and operational challenges due to conflicts of interest but also since the level of reporting will be hard to identify and coordinate across multiple scales of government (ICSU, Citation2015, p. 55).
One such example is the proposed unit of urban agglomeration, comprising of the built-up area forming a continuous settlement, which has long been proposed by UN-HABITAT (Citation2012) as the standard area of reference since it addresses the problem of varying definitions of cities across the globe. Using the unit of urban agglomeration deals in part with the contextual sensitivities around what constitutes a city and thus acknowledges the continuum between urban, peri-urban and rural. Still, it proved difficult to collect and compare data across municipal boundaries in our pilot study. Although certain geospatial data can easily be made available for this unit, it is frequently a challenge to match this with, for instance, census-based population data which are not readily available at this level. The principle of global applicability thus remains a real challenge.
Although Goal 11 requires multi-sectoral, multi-scale and multi-actor involvement, it became apparent in our pilot study that local authorities need to be directly involved in the implementation and reporting processes for the targets and indicators to have real impact on policy-making. Still, this is far from straightforward due to a wide variety of challenges and capacities of cities to do so. These include, but are not limited to, frequent top-down reporting practices, limited survey samples, and the lack of local coordination, capacities, and funds. The relationships between national statistical agencies and local authorities are not always aligned and frictionless. As will become clear below, this applies particularly in Kisumu.
Launching a data revolution
The pilot study shows that the data for the proposed indicators vary considerably among the cities and the respective targets. Data gaps and quality, compliance with methodological standards, and non-availability of disaggregated data are among the major challenges identified. The findings also point at how the targets and indicators are not always well aligned and are at times considered difficult to operationalize. There is, accordingly, a danger of measuring what is measurable rather than what is actually relevant. For the IEAG’s proposed post-2015 ‘Data Revolution’ of achieving better, faster, and more accessible data to become a reality, there is a trade-off between drawing from existing statistical frameworks and the need for new and improved data sources. The UN Statistical Commission stresses the urgent need for investments to enhance national statistical capacity in order to measure progress towards the post-2015 development agenda at national, regional and global levels and to enable national statistical offices to play a leading and co-ordinating role in this process (UNSC, Citation2015). A report by the Sustainable Development Solutions Network similarly highlights the crucial role of non-state/governmental organizations in the potential success of the data revolution, but also emphasizes how the growing role of civil society organizations and businesses offer unprecedented opportunities for using new types of complementary metrics and data (SDSN, Citation2015).
This trade-off is demonstrated in our pilot study as the need for reliable data. Efforts to remedy this often focus on the accuracy of traditional data rather than engaging with the potential of additional, especially non-traditional, data sources. As revealed in our study, the data collected are derived primarily from existing censuses, surveys and other administrative data. However, these sources frequently draw a firm distinction between formal and informal sectors, such as in relation to the targets and indicators on housing, transportation and waste management as examined in the remainder of this paper, and which in turn perpetuate a dichotomous relationship between the two. This trade-off and its relationship to data on informal practices therefore requires substantial attention in order to overcome this binary approach.
The most obvious example of informality is drawn from the first target on slums and informal settlements and the difficulties involved when applying the UN-HABITAT definition of a ‘slum household’, which focuses on what informal settlements lack rather than what they are or possess. In addition, the issues surrounding informality are most clearly evident in relation to the targets addressing public transportation and waste management. Accordingly, examples from Kisumu and Cape Town case studies pertaining to these targets will inform a discussion about how the notion of informality can be dealt with in a complementary rather than incompatible manner in the call for a ‘data revolution’ that helps to break with a binary and simplistic understanding of informality in African cities. One implication is the likelihood of targeted capacity building initiatives to enable local authorities and other stakeholders to undertake such enhanced data collection, not as an end in itself but as an essential tool to promote locally appropriate urban sustainability transitions.
Slums, informal settlements and security of tenure
The challenges identified in our pilot study related to informal settlements and land use include definitional issues, varying modes of data collection, land tenure and security of tenure which will all be addressed in this section.
The term slum has a long history dating back at least to Victorian times but, despite being embedded in legislation in India and apartheid South Africa, for instance, it fell into disrepute on account of its derogatory connotations. Its renewed currency can be traced from the Habitat II summit in Istanbul in 1996 and the launch of the ‘Cities Without Slums’ initiative in 1999 through the Cities Alliance, jointly funded by the World Bank and UN-HABITAT, through which the term gained international attention (Hansen & Vaa, Citation2004, p. 15). However, it is providing legitimacy for renewal in many countries of previously discredited old-style slum clearances; giving rise to expedient data manipulation in order to convey a false sense of improving shelter access; and promoting the illusion that slum-free cities are the norm and somehow attainable without transforming the basis of access to secure land tenure and appropriate housing (Gilbert, Citation2012; Huchzermeyer, Citation2011; Lucci, Citation2014; Simon, Citation2011).
Target 11.1 on housing: By 2030, ensure access for all to adequate, safe and affordable housing and basic services, including the upgrading of slums, is inherited directly from the MDGs. Although considered highly relevant across all five pilot cities, with the proposed global reach of the SDGs, as opposed to the low/middle-income country focus of the MDGs, it is nevertheless unclear why the focus rests on slums and informal settlements in indicator 11.1.1: Percentage of urban population living in slums or informal settlements. This indicator is considered complicated as all cities have struggled to provide reliable data annually. This is complicated by definitional problems and the lack of comparability.
It is this association between slums and informal settlements (which are often very different in origin, nature and appropriate policy measures) and the supposedly dangerous character of those who live there that is the most worrying aspect of the renewed use of the term ‘slums’. Essentially, it confuses poor quality of housing with the nature of the people living in it (Gilbert, Citation2012, p. 698). UN-HABITAT (Citation2012, p. 99) itself often falls into this trap, as evidenced in this recent edition of its signature biennial report, State of World Cities 2012–2013:
Slums feature the most deplorable living and environmental conditions and are characterized by inadequate water supply, poor sanitation, overcrowded and dilapidated housing, hazardous locations, insecurity of tenure and vulnerability to serious health risks – all of which have major implications for quality of life. Slums are also known for their atmosphere of fear and the social and economic exclusion of their residents.
By using such emotive language, the UN draws attention to a real problem but also evokes a response that it cannot control (Gilbert, Citation2012, p. 710).
The data reported for target 11.1 in the pilot study are collected infrequently and are based primarily on projections and estimations in the years between censuses. An estimated 10% of Cape Town’s population lived in informal settlements in 2013, excluding informal backyard dwellings in formal low-income residential areas.Footnote3 In Kisumu, the percentage is 64% based on the population of the urban agglomeration (see Figure ), excluding the more rural areas of the city (Simon & Arfvidsson, Citation2015). In the case of Kisumu, these informal settlements comprise no more than 15% of built-up urban area in the city, making these areas extremely dense and overcrowded (Steyn, Citation2012).
Figure 1. Informal settlements in Kisumu (Ombara, Nyambuga, & Oloko, Citation2015).
The data collected nevertheless remain unreliable and the research teams in Cape Town and Kisumu share a common concern about the UN-HABITAT definition of informal settlements not being applicable, in part since it is not widely used in each respective national census. The data provided by the two cities are therefore not necessarily comparable since they are based upon the respective local definitions.
The UN-HABITAT definition portrays informal settlements and slums in exclusively negative terms, by what they lack: access to improved water; access to improved sanitation; security of tenure; durability of housing; and sufficient living area, rather than what they are (Durand-Lasserve, Citation2006, p. 1). This definition lumps together a range of settings and housing types that are depicted as opposite to the mainstream, normal and desired.
The term informality raises the same definitional problems for human settlements as when it is applied to economic activities and employment: it is defined negatively (Durand-Lasserve, Citation2006; Simon, Citation2011). A settlement with particular characteristics regarding land use, urban planning strategies, and housing standards can consequently be considered either as formal or informal.
This description is at odds with local contexts and realities since when referring to such a wide variety of conditions of precarious urban existence, a substantial part of cities in low-income countries can fall into this category. Indeed, if the UN-HABITAT definition were applied to Kisumu, our partners report bluntly that most of the city would be considered a slum since almost all residential areas suffer one or more of the five deprivations (Ombara, Nyambuga, & Oloko, Citation2015). As in most former European settler colonies, the reasons for this in Kenya are a complex mix of historical legacy, land tenure and political economy (Gatabaki-Kamau & Karirah-Gitau, Citation2004). In the South African context, the definition is also considered too broad to be analytically useful (Groenewald et al., Citation2013, p. 102), but the main problem with a negative definition is that it leads to a perception of residents of informal settlements as lacking dignity.
Another complexity in South African cities with considerable relevance to the accuracy of slum/informal dwelling data is the distinctive and widespread backyard shack phenomenon in high-density ‘townships’. Stats SA distinguishes between these and other informal dwellings but backyard shacks are excluded from official slum/informal reporting (Moodley et al., Citation2015, p. 7). These backyard dwellings have historically been overlooked by housing policies that focus on upgrading and/or eradicating informal settlements. Previously, backyard dwellers
… were perceived as marginalised, living in appalling conditions and exploited by cavalier landlords. However, the post-apartheid provision of state-funded housing for the poor has altered the nature of backyard housing, creating a new class of cash-poor homeowners who are dependent on income from backyard dwellers’ rent, thus ensuring a more equitable power pendulum between landlord and tenant. (Lemanski, Citation2009, p. 472)
To demonstrate its supposed effectiveness in eradicating informal settlements in attempting to meet the MDG slum reduction target, the South African government narrowed its definition of informality. This had the consequence of enabling many such settlements to be reclassified from informal to formal without substantial physical upgrading or improvements to service delivery (Groenewald et al., Citation2013, pp. 106–107). Hence the impression given of progress against the MDG target is misleading and ultimately unhelpful. It exemplifies the problem of a target-based performance measurement culture, where target achievement rather than the intended service or quality of life improvements becomes the principal objective. This is comparable to the way in which UN-HABITAT treats basic needs improvements that address one or more of the so-called five deprivations in slum areas as lifting those areas and their inhabitants out of slum conditions (Lucci, Citation2014). This issue exemplifies clearly that ‘data are never simply just data; how data are conceived and used varies between those who capture, analyse and draw conclusions from them’ (Kitchin, Citation2013, p. 11).
Much of the dualistic thinking on informality discussed in the Introduction is based on the valorization of tenure security and its links to poverty alleviation, as reflected, for instance, in the way that UN-HABITAT and the MDGs portray improving lives of slum dwellers by arguing for tenure security as a prerequisite for development and inclusion. This view was popularized by Hernando de Soto, with the argument that certificated security of tenure of individual plots was essential to enable poor urban residents to use their land/home as collateral for construction or home-improvement loans. Yet, this is not the only possible solution, since various alternative options exist, including with various versions of communal or collective tenure. More nuanced and locally appropriate understandings are needed in order to capture the variety of possibilities in unregistered settlements (Groenewald et al., Citation2013, p. 103). In Gilbert’s (Citation2012, p. xiii) words,
… rather than providing a panacea for poverty, he [de Soto] is simply pushing a populist myth. It is a sad fact that improving people’s housing and removing them from the ranks of the poor is a lot more difficult than merely giving it to them with a piece of paper.
Given that new forms of poverty, vulnerability and marginalization attached to rapid urbanization do not exist exclusively in informal settlements and on land where the occupants have only insecure tenure, indicator 11.1.1 would become more inclusive, relevant, and comparable across the globe if slightly reformulated. Since the focus of the target is on adequate, safe and affordable housing, our pilot study proposes that the focus on slums and informal settlements is replaced by ‘inadequate housing’. The notion of inadequate housing and insecure tenure would, in turn, address access to basic services, security of tenure, overcrowding and quality of housing, but without singling out slums and informal settlements in a dichotomous rendering of cities.
Transportation
Target 11.2 on transportation: By 2030, provide access to safe, affordable, energy efficient and accessible transport systems for all people and goods, improving road safety and expanding public and non-motorised transport, with attention to the needs of those in vulnerable situations, is regarded as fundamental to achieve sustainable development. However, several concerns were raised in the pilot study since the proposed indicators are deemed to be insufficiently aligned with the proposed target. In relation to this article, the concern about how the indicators favor formal means of public transportation is significant since this perpetuates a dichotomous understanding of formal and informal transportation modes in a manner analogous to that discussed above with respect to housing and tenure. This has also been apparent especially with respect to Kisumu.
For indicator 11.2.1: Percentage of people living within .5 km of public transit [running at least every 20 min] in cities with more than 500,000 inhabitants, it remains unclear whether informal public transportation such as minibuses and tuk-tuks should be included. The distance parameter is relatively easy to measure across the five cities, whereas the frequency parameter has proved much more difficult to produce reliable data for. The Cape Town researchers argued that sustainable public transport needs to be demand driven. Minimum frequencies should therefore be dependent on demand and not specified. In applying this indicator, the Cape Town research team replaced ‘running at least every 20 min’ with ‘scheduled public transport’, as they assumed this was the intention behind the indicator. They further argued that Transport for Cape Town (TCT) would not be able to include minibuses for this indicator. Based on this differentiation, TCT states that 83% of the population have access to all forms of scheduled public transportation within .5 km distance (Moodley et al., Citation2015).
The calculations made for the distance parameter in Kisumu are based on rough estimations since there is no detailed information available on the locations of the public transit stops. In some cases, these stops change on an ad hoc, demand-driven basis and it is difficult to keep the data updated. The major transport routes were identified, digitized and buffered against the population by the Kisumu research team. Based on these estimations, 55% of the population have access to public transportation, which in the case of Kisumu includes tuk-tuks (tricycles), matatus (minibuses), boda-boda (motorbike taxis), and piki-piki (bicycle taxis) (Nikulina, Citation2015; Ombara et al., Citation2015).
Kisumu has sprawled out over a large geographical area, with some peripheral areas having relatively low residential densities. As a result of this spatial organization, transportation services are vital to the city’s territorial cohesion. However, Kisumu’s public transport system is highly informal, with minimal regulation by the City Council or other authorities. The Kisumu research team thereby draws attention to the lack of formal and scheduled public transportation in the city and urged more clarity on how to account for its privately/informally run public transportation system in which different actors compete for the use of the ill-maintained and undersized road transport network; what modes of transport to include; and how to measure the frequency aspect without access to timetables.
The various routes used by the matatus have been created over the years based on passenger habits. Public transport operators stop as need arises either to drop off a passenger on request or to pick up a new passenger, often causing traffic jams or even accidents. Due to lack of control and the inconvenience that may arise, many people tend to turn to individual motorized transport solutions as soon as they can afford it, causing ever more traffic congestion in the city. Kisumu has also witnessed the phenomenal growth of boda-boda and piki-piki taxis as an unregulated coping response to the mobility needs of the majority of Kisumu’s residents. These informal alternatives provide cheaper and more flexible public transportation and are also a source of income for young people from the poorest areas of Kisumu deprived of any means to find formal employment. Accordingly, the recommendation from our project is that the final version of this indicator should state clearly whether and how informal or semi-formal forms of public transportation such as matatus, tuk-tuks and boda-bodas should be included.
The forms of public transport measured in indicator 11.2.2, Kilometers of high capacity (BRT, light rail, metro) public transport per person for cities with more than 500,000 inhabitants, are all large scale and formal. In Cape Town these networks are extensive and the data readily available on an annual basis, whereas Kisumu has no such modes of transport (Nikulina, Citation2015) and the indicator is accordingly of differing relevance to the two cities. The Cape Town researchers emphasize its importance as it identifies the development gap between different forms of transport, which in turn needs to be addressed, while the Kisumu team rather points at how a BRT system might not make much sense for the foreseeable future in a city such as Kisumu.
Waste management
Although target 11.6 on environmental impact and indicator 11.6.1: Percentage of urban solid waste regularly collected and recycled (disaggregated by e-waste and non-e-waste) do not explicitly distinguish between formal and informal waste collection, the data collected in our pilot study clearly do as almost only municipal waste collection is covered by the research teams. Solid waste management is, however, much more than simply collection as it also entails waste minimization, separation, transport, disposal and recycling. At first sight, waste management might be considered a technical issue, but as all these elements connect to a range of urban governance aspects, it is also a major political challenge. Grest, Baudouin, Bjerkli, and Quénot-Suarez (Citation2013, p. 117) suggest that solid waste management provides a lens through which broader power relations of urban management emerge. In our pilot study, this political nature of waste management was highlighted as a major concern, especially in Kisumu, stressing the risk of data manipulation. Our findings accordingly demonstrate several concerns, including the lack of reliable data, the need to better integrate complementary aspects of informal waste management into the indicator, as well as to ensure checks and balances for the data reported.
The reporting on municipal solid waste collection is problematic and misleading since the reliability of the data leaves much to be desired. In part since there are multiple actors involved in waste collection, ranging from municipal to private and/or informal collectors, the reporting structures differ greatly among the cities, thus complicating comparison. In several of the five cities in our pilot study, the waste collection is primarily municipal, whereas recycling practices are mostly private and/or informal. In Kisumu, waste collection by the municipality is estimated at 20% and by private actors at about 15%, which leaves 65% not collected by either (Ombara et al., Citation2015). These figures are based on official dumpsite records, but their reliability is questioned by the Kisumu research team since there is a tendency for waste data to be manipulated to serve the interest of particular stakeholders rather than the residents. The research team argued that waste management is a highly sensitive issue in Kisumu and the data accordingly need external checks and balances to become more reliable.
The nature of waste management in Kisumu reflects that of many other cities in low-income and many middle income countries. While the City of Kisumu has recognized that solid waste management is a major concern and despite several initiatives being put in place to ensure an effective management system, such as the Kisumu Integrated Solid Waste Management Project (Municipal Council of Kisumu, Citation2010), much of the waste remains uncollected and left out in the open by roadsides or in back streets, sometimes blocking local drainage channels and mixing with polluted waste from flooded latrines. This exacerbates urban flooding during the rainy season, an increasingly severe problem in many neighborhoods and cities. With 65% of the waste uncollected, many households, particularly in the peri-urban areas, do not have any mode of collection, and have resorted to burning of waste or digging pits to bury the waste on site. While entirely understandable, such unregulated and ad hoc activities often cause air pollution and soil and groundwater contamination to the detriment of human health and the environment.
A key challenge in relation to waste collection is still that of recognizing the importance of the informal sector, both by local authorities and in the proposed indicator, since there is otherwise a risk that the data collected will be distorted through omission or underestimation if there is not more clarity on how to include informal waste practices worldwide, since these are frequently ignored by local authorities. In Kisumu, the entire waste management sector is dominated by informal practices ranging from collection, low-level sorting and recycling at source, to transportation to dumpsite. The activities at the current landfill are informal in nature and dominated by scavengers and waste pickers, primarily street children. This is similar to how in several countries, a significant proportion of the urban poor are involved in waste collection and recycling as a source of income (Moreno-Sánchez & Maldonado, Citation2006, p. 371). Since many of these activities are labor-intensive, it provides a livelihood for many marginalized groups (Ojeda-Benitez, Armijo-de-Vega, & Ramı́rez-Barreto, Citation2002). There is a crucial need to recognize the contribution of these informal activities and practices as well as to ensure the safety of the people involved.
The attitude of the formal or municipal waste management sector to informal recycling is nonetheless problematic. Informal waste collectors are either often ignored by city administration, despite their significant contribution to waste reduction, reuse and recycling (Grest et al., Citation2013, p. 117) or regarded in negative terms, as backward, unhygienic and generally incompatible with a modern waste management system (Wilson, Velis, & Cheeseman, Citation2006, p. 797). The association with an activity, which the public perceives to be filth related, tends to perpetuate discrimination against them (Moreno-Sánchez & Maldonado, Citation2006, p. 371). In response to these concerns, private waste collectors in Kisumu have formed organizations and are seeking more recognition from the City Council. Although this is gradually occurring, the City Council has given them recognition letters rather than licences as outlined in the Kisumu County Finance Bill 2014 (Republic of Kenya, Citation2014). Nevertheless, this does not give them a stronger bargaining power with the City Council or with other established institutions since the letters are not legally binding and are not sufficient to establish working relationships.
The informal recycling sector in Kisumu is focused mainly on plastic bottles. This is similar to many other cities since the high demand for plastic products ensures that almost all plastic is collected and recycled back into the system (Grest et al., Citation2013, p. 125). However, without reliable data on quantities recycled and diverted from formal waste management streams, the chance of convincing municipal authorities about the significant role of the informal sector remains low (Wilson, Araba, Chinwah, & Cheeseman, Citation2009, p. 632). Following from this, Kisumu highlights how the indicator 11.6.1 can potentially help put more pressure on the City’s waste management strategies, but calls for it to be modified to include how private/informal waste collection is supported by local authorities.
There is agreement among all the cities in our pilot study that the primary indicator on waste management needs to be complemented by a waste per capita indicator to account for the total amount of waste generated in order to track the overall efforts to minimize waste. This connects to the importance of efficient waste recycling strategies because when contractors are paid per tonne, they have no interest in waste reduction (Grest et al., Citation2013, p. 134). Without this additional indicator, the data on waste management will be greatly misleading. In addition, a stronger focus on how official data collection on indicator 11.6.1 account for the importance of non-municipal solid waste management is crucial for the data to reflect the complexities facing most cities in low- and middle-income contexts. Our report suggests that local authorities need assistance to collect the data required for a more complete representation of waste management practices beyond their own official statistics in order for the data revolution to be launched and new and improved data sources added.
Conclusions
This article has highlighted the need for engaging with and measuring the widespread informality present in many cities across the globe in a complementary rather than in a dichotomizing manner, if the urban SDG is to become an effective policy tool for ensuring and monitoring sustainable urban development. Informality is therefore seen as an intrinsic urban phenomenon that must be recognized by local authorities and incorporated within sustainable urban development programs and strategies to inform policy formulation and planning practices. All too often, as in Kisumu, this is still not the case (Steyn, Citation2012). The article has addressed a number of key challenges related to how the proposed targets and indicators of Goal 11 do not adequately address informality, as identified in the pilot study conducted by Mistra Urban Futures (Simon & Arfvidsson, Citation2015). The aim of the article has been not only to draw attention to these challenges, but also to raise awareness of the strategies and capacity building needed to assist key actors, including local authorities, when engaging with and measuring informality in order to ensure meaningful translation of Goal 11 into policy and planning practices.
For the IEAG’s proposed data revolution to be launched and become a reality, a combination of traditional and new data sources is required. This data revolution provides a window of opportunity to engage with informality beyond an outdated dichotomizing framework. Our pilot study has shown that alternative forms of data collection should be initiated so as to break with a binary and simplistic understanding of informality as well as the dichotomous rendering of cities. The examples highlighted in this article demonstrate a number of challenges related to informality and the proposed targets and indicators on informal settlements, public transportation, and waste management. With respect to informal settlements, the single most important adjustment proposed is to replace the notion of informality and particularly the use of ‘slum’ with ‘inadequate housing’. The reason behind this proposal is for indicator 11.1.1 to become globally relevant and draw attention to the heterogeneity of inadequate housing not simply found in particular areas depicted as slums.
For the target on transportation, the contexts of Kisumu and Cape Town have clearly shown a need to move beyond a valorization of formal public transportation alone in the proposed indicators. In the pilot study, the two cities measured very different modes of transportation, as Kisumu has an exclusively informally run transport sector, while Cape Town distinguishes clearly between formal and informal transportation and has chosen to report data only on the former, on scheduled public transport, in order to indicate the development gap. On the one hand, this makes comparison between the cities complicated, but on the other hand, it also treats the informal and formal sectors in a distinct rather than complementary manner. In order for all cities worldwide to be able to report on this indicator, such clear distinctions need to be avoided to allow for local contextualization and greater policy relevance.
The key challenge identified in respect of waste management is the hesitance or inability to recognize the importance of informal practices in the data collection for indicator 11.6.1. Drawing on examples from Kisumu, the pilot study calls for better integration of complementary aspects of informal waste collection and management into the indicator so as to recognize their valuable contributions as well as improve the reliability of the data collected.
By drawing attention to how the proposed targets and indicators of Goal 11 deal with informality, this article emphasizes the importance of holistic or integrated approaches that incorporate all relevant segments or actors in the relevant spheres. The key lesson is accordingly to determine clearly what adequate outcomes are for each target and indicator, irrespective of the formality or informality of urban service delivery. The indicators should then rather focus on the experience and realization of these outcomes.
Current data collections systems, whether based on administrative data from city administrations or on public surveys, are significantly limited in their ability to measure the achievement of adequate development outcomes, irrespective of formality. There is thus a strong need to explore how data collection systems can better be able to provide an even playing field between formality and informality, ideally with them integrated within holistic strategic planning processes. This will require sizeable investment and innovation in data collection systems and geo-spatial information systems that are better able to assess the achievement of outcomes in informal contexts. Failure to do so will add credence to and perpetuate outmoded and inappropriate perceptions and the policies based on them, thus impeding rather than promoting progress towards locally appropriate sustainable urban development transitions in many low- and middle-income contexts.
Notes on contributors
Helen Arfvidsson is a researcher at Mistra Urban Futures, Chalmers University of Technology, as well as a lecturer at the School of Global Studies, University of Gothenburg, Sweden. Her research interests span the fields of international relations, critical security studies, and urban politics. She previously worked with labor unions on HIV/AIDS policy in South Africa as well as on urban development and youth policy in Sweden.
David Simon is the director of Mistra Urban Futures, an international transdisciplinary research center on urban sustainability based at Chalmers University of Technology, Gothenburg, Sweden, where he is a guest professor. He is also a professor of Development Geography, Royal Holloway, University of London, UK. His principal research interests include cities and climate/environmental change; and development theory, policy and praxis. A native of South Africa, he has wide research experience across sub-Saharan Africa, parts of tropical Asia, the UK, and Sweden.
Michael Oloko is a senior lecturer and the dean of the School of Engineering & Technology, Jaramogi Oginga Odinga University of Science and Technology (JOOUST), Bondo, Kenya. He has published a number of articles in his area of research interest, i.e. water resources and environmental engineering and management.
Nishendra Moodley was previously a director of Palmer Development Group, Cape Town, South Africa and is now at City Support Program, South African National Treasury. He is a governance specialist with a strong interest in Intergovernmental Relations and Monitoring and Evaluation.
Notes
1. The pilot project to test potential targets and indicators for the Urban Sustainable Development Goal 11 was conducted between March and June, 2015 (see Simon & Arfvidsson, Citation2015). For more details on the proposed targets and indicators also see UNSC (Citation2015).
2. Perhaps surprisingly, this applies even to UN-HABITAT, as most recently exemplified by its ‘Issue Paper’ 14 produced as part of the preparations for HABITAT III in 2016 (UN-HABITAT, Citation2015).
3. Stats SA surveys distinguish between households in informal dwellings, in informal settlements and informal dwellings in the backyards of formal residential areas. This estimate is from the City of Cape Town’s Solid Waste Door Count, but only covers informal dwellings in informal settlements (see Moodley, van Niekerk, & Foster, Citation2015).
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