Having access to accurate data has a number of benefits. It can provide a clearer picture of the reality on the ground as well as vital facts to support decision-making. It can offer pertinent evidence to make a case for action and also show where action is needed.
Unsurprisingly then, data is currently being used to try and help solve some of the world’s most intractable problems. Here are two examples in practice.
Climate change – C40 Cities
C40 Cities, a network of 94 of the world’s megacities committed to addressing climate change, provides policymakers and public servants with data to use as evidence when making the business case for introducing sustainable, local policies and projects.
According to Rachel Huxley, the organisation’s Director of Knowledge Learning, a key challenge in this context is demonstrating that climate action does not compete with, but rather complements, other political and economic goals.
C40 Cities has been using data analytics tools for some time internally to track both the progress and engagement levels of individual climate cities. But it has now also launched a Knowledge Hub to provide both its members and a broader audience with access to a wide range of content. This content includes data and research to illustrate to policymakers why it is vital to take action on limiting global warming to 1.5 degrees Centigrade. It also offers resources, such as policy briefs and technical guidance based on lessons learned, to show them how to do it.
A series of dashboards called Data Explorer applications, which are built on data analytics software provider Qlik’s platform, have also been added to the Hub to provide insights into topics ranging from air quality and waste to transport and urban planning. Most of this data is collected and provided by the C40 cities themselves, although it is supplemented by global publicly available information too. Huxley explains the rationale:
As the organisation, the number of cities in the network and the amount of data we collect has grown, it’s become increasingly important to present that data more effectively in an easier-to-measure, visual format. It not only helps us internally to track progress and see where the cities are doing well, but it also helps the cities themselves see where they are in relation to targets on topics, such as air quality, in order to incentivise action and engage stakeholders. They can also benchmark themselves against peers as the dashboards make it easier to see the data and how they’re performing, which means it’s quite powerful.
The idea behind modelling the data in this way is to help cities understand the implications of the choices open to them, which span from doing nothing to acting immediately. This information then allows public servants and policy makers to engage in “sensible and sophisticated conversations” with a wide range of stakeholders in order to affect change.
Another benefit of introducing a data analytics platform, meanwhile, is that it enables non-data specialists in public authorities trying to tackle issues like sustainable transport to easily access information in important related areas, such as air quality, that it is unlikely they would have found in the past. Huxley explains:
Some people have data analysis skills, but a lot don’t, so having a platform that makes information very easy to use unlocks a whole new set of opportunities. On the one side, there’s the world of data and research and, on the other, there are the busy folk in the cities, who know a lot about their areas. So one of the massive value-adds of the network is taking cutting edge research and knowledge and making it understandable and accessible to them. A key challenge is helping the cities navigate all the information that’s out there, so our aim is to bring it all into one place to connect people with the right information.
Due to the inevitable data gaps that occur when relying on the cities themselves to collect climate-related information though, a key aim for the future is to introduce remote sensors to collect relevant data globally and employ machine learning software to analyse it. Although work has yet to begin here, Huxley says she is “excited by the possibility”, not least because it will “fill our data gaps without burdening the cities”. She continues:
Good data is very important to us, but data alone doesn’t move things. It’s about how you use it that makes an impact, in other words, how you get it into the decision-making process - and that’s where tools like Qlik’s come in.
Distributing aid in Lebanon – Medair
International humanitarian organisation Medair is leading a project to map informal settlements across Lebanon in order to facilitate and coordinate aid distribution.
The initiative started in 2013 as a result of Syria’s civil war, which saw refugees flooding into Lebanon to escape the fighting. The aim in mapping the location of the informal settlements was to make it easier to provide help with suitable water, sanitation and hygiene, shelter and health facilities to those who needed it. A subsequent drop in funding means the focus is now on offering people shelter and healthcare. But as Reine Hanna, Medair’s Information Management Project Manager, says:
There was no mapping system in Lebanon, even for existing houses, so we had no street names or addresses. But it was a huge challenge as the informal settlements are in the middle of nowhere, with some 45 minutes from the closest road. This meant we had problems finding and identifying them and if we called one of them ‘06’, for example, another NGO would call it something else, so it caused a lot of confusion when trying to coordinate things.
Medair works with two other NGOs, Solidarites International, which focuses on the north of the country, and CISP, which looks after the south, while it collects data in the Baaka Valley, Beirut, Mount Lebanon and Saida (Sidon). A team of about a dozen people visit each of the 9,000 informal settlements every four months to collect and confirm coordinates as well as record basic information, such as the number of structures and latrines plus how many children are attending school.
Each site is identified by a ‘P’ or ‘placement’ code that is directly linked to its location. All of the data collected about each settlement is verified and then given to the United Nations’ Refugee Agency (UNHCR), which, as the lead coordinating agency, shares it with all of the other NGOs working under its umbrella. This data enables the NGOs to plan how many teams to send and what is required before going out into the field. Moreover, says Hanna:
The mapping data is used for coordination purposes as we only need to share the ‘P’ code with another NGO rather than have to try and tell them how to get to the destination. But we also use all of the other data too for reporting – the UNHCR has a platform where we all share information about what we’ve done and that allows us to analyse any gaps just using the ‘P’ codes.
As for the benefits gained as a result of having access to such information, she believes they are multiple:
In the case of emergencies, having ‘P’ codes and a map that enable you to get to a site really fast rather than trying to work out where it is, is key. Having access to previously collected data can save lives. For example, internet access isn’t that good in Lebanon, especially in the field, so giving the Lebanese Red Cross, which handles the country’s ambulances, access to an offline version of the mapping data makes all the difference.
The other information that is collected also helps the NGOs to understand their beneficiaries. Each individual and family is registered and, using Qlik’s data analysis tools, an assessment team can evaluate what their requirements are. Hanna explains:
The answer to each of the questions we ask is given a score so we can calculate what kind of shelter is needed, for example. This enables us to respond to people’s real needs rather than just what we, or they, think they are, so it’s less subjective.
Using software for data entry and verification rather than having to do it manually has also enabled the NGOs to “collect a lot more information in a lot less time and with a lot less staff”. In fact, while it used to take 55 minutes to register each household, which includes collecting and recording data in the field, data entry and analysis, the figure has now dropped to eight minutes.
The cost of doing so has also fallen from $70 to $4, not just due to the amount of time saved, but also because things like car rental and petrol costs have fallen as well. Moreover, each team is now able to assess 300 households per week rather than the previous 36 with no increase in the number of staff required to do so.
A final but equally important benefit is that the data helps Medair to plan more effectively. As Hanna concludes:
By analysing gaps and understanding people’s needs, we can create better project proposals and use data to back them up. We can actually demonstrate objectively that we require something. This means we definitely wouldn’t be as effective without either technology or data.