Civil society organisations in Germany need to be directly empowered to use data, in order to maintain their scope for action in a digitalised world.

The rise of data-driven decision-making has made huge impact on government and business over the past decade. Major shifts in society and economy driven by technological advances in the collection, analysis and use of large data sets has become commonplace. Debates over the use of social media data to effect democratic elections, the rise of the data-driven FANG corporations (Facebook, Netflix, Amazon and Google) and the use by governments in the West of large data sets to guide policy making have fundamentally changed the way we understand and interact with human relations. Secondary effects, including the flourishing of innovation techniques based around iteration and immediate feedback inspired by Silicon Valley (Design Thinking, “Lean Startup” methodology, agile approaches) further shape the way that audiences, consumers and citizens are understood and served. Civil society organisations will need support to keep pace with developments in the private and public sectors, so that they can continue to mediate between increasingly complex social groups and sectors in a digitalised future.

 

Many civil society organisations have been exposed to the collection and analysis of large data sets through the application of impact-oriented methodologies to make civil society activities more efficacious. Organisations like Phineo in Germany, NESTA in the UK and Ashoka globally advocate for more impact orientation and more impact measurement, to increase transparency, efficaciousness and purposeful social change. Funding decisions will be increasingly based on the ability of civil society organisations to prove their impact qualitatively, or even more convincingly, quantitatively. However, currently the vast majority of civil society organisations are unprepared for the importance that data collection and analysis will play in the future- in a recent survey from the BetterPlace Lab only 25% of civil society organisations in Germany felt prepared for the increasing influence of impact measurement on funding decisions[i]. Perhaps even more crucially, civil society organisations are not prepared to take advantage of the potential of big data to increase, or even just to maintain, their current sphere of action.

 

Specifically in Germany, awareness of data protection topics is pronounced. Civil society organisations normally know how important the protection of personal data is, and have developed the relevant competencies to do so. There is also a good understanding of simple data manipulation tasks, such as with Excel. Many non-profits have, however, a very limited understanding of the potential of data in their work, and the competences that they would need to do so. For example, abilities in the use of external sources of data, the connection of multiple sources of data together, the interpretation of data and the recognition of complex relationships in data, the visualisation of data and the use of large data sets are very limited” (Helene Hahn, Open Knowledge Foundation Deutschland e. V.[ii] (translated by the author)

 

The production, analysis, and criticism of data-based policy, the representation of the interests of civil society actors and their beneficiaries in a data-driven polity, and the development of innovative, robust and scalable solutions to social problems will all increasingly require a data literacy from civil society organisations that is currently not there. Organisations that I work with are all currently performing these crucial roles in society, but their ability to mediate between state, business and communities is becoming more and more dependent on their ability to use data.

 

Through my work with civil society organisations I see the potential for data collection at every scale, as well as the barriers that organisations have to taking advantage of this potential. As an example, working with a consortium of small, neighbourhood organisations supporting a struggling inner-city primary school in Berlin, we developed a simple quantitative tool, including questions for parents, teachers, pupils and civil society stakeholders. We translated the questions into, along with German, Arabic and Turkish, on order to reach all of the important stakeholders. With relatively little effort we were able to identify five clear areas where the local organisations and the school could work better together, as well as indicators of which activities could potentially affect the most change. With the clear indications produced by the statistics, we were able to convince all important stakeholders of the necessity for action.

 

The challenges faced by these actors are very common in big cities in Germany, and a scaling of this tool would almost certainly lead to improvements in education and neighbourhood solidarity. More importantly the questions we asked indicated major problems on a regional and a national level, most importantly around migration and integration, but also in terms of urban development, which local actors could not solve. However, if this tool was used by twenty schools throughout a single Bundesland, or through the whole of Germany, we would have enough data that could be used to effect policy change on a national level.

 

The role of smaller civil society actors to effect policy change, to mediate between interest groups, the state, society and business, could be strengthened through data literacy and the ability to produce, criticize and analyse data. However, there are major barriers civil society actors need to overcome to take advantage of these possibilities.

 

Primarily, civil society actors themselves need to increase their data literacy, by learning the basics of statistical operations and understanding the terms used in the growing field of data science. This need cannot be met by pro-bono or other external advisors- in order for civil society actors to be able to analyse external data sets, to set the data agenda in their organization, and crucially recognizing the potential that data offers, they must be comfortable at least with basic concepts like statistical significance and effect size, and they should have an understanding of what machine learning, data analytics and data mining are, and which sources for data there are that are relevant to their work.

 

Additionally, many civil society organisations have serious reservations about using data that need to be settled before they can take full advantage of it. Many are concerned about data security, knowing what data they can collect and how. Many are concerned about alienating their beneficiaries, and striking the right balance between useful and usable data and maintaining trust. These concerns can be met with more training and understanding of how data can be securely collected and stored, transparently handled and how target groups can be reassured and trust can be maintained.

 

A serious issue for the collection and application of impact are the current existential fears held by civil society organisations regarding funding. Whilst impact orientation and the use of research techniques offers major benefits when it comes to funding decisions, quantitative data should be used as one of many tools for measuring social benefit, and the limitations of quantitative tools to measure, for example, culture or complex social change should be recognised. Funders need to act with sensitivity when working with organisations to carry out impact measurement activities, and organisations need to develop an understanding of what quantitative practices can achieve before quantitative impact analysis can achieve its full potential. Crucially, the use of impact measurement and quantitative impact measurement needs to be implemented internally within organisations, where it also has the potential to have the most benefit, before it is used across the board to measure success and inform funding decisions.

 

Finally, civil society organisations need digital tools designed specifically for them, developed in cooperation with them. The needs of civil society organisations in data collection, analysis and visualization are very different from academic research institutions and commercial enterprises. Flexibility is a requirement, but more than anything tools should take into account the amount of organisations working independently on the same goal, and should offer clear structure. Tools should take advantage of this local repetition and allow cooperation between organisations to create robust and representative data sets. They should try to make the most of cooperation by allowing transparency when it makes sense, whilst still recognizing the needs of organisations to have control over their data. The limited resources of civil society organisations, and the efficiency with which they work, should be taken into account when it comes to training and knowledge requirements to use the tools.

 

Civil society organisations urgently need tools and methods that empower them to use data to mediate between groups and institutions in an ever more complex society. They need to learn through doing, ideally using impact measurement as an introduction as this is a skill that they will need to rapidly learn to maintain funding. They need support that focuses on cooperation between organisations, in order to create robust data sets as well as build a more networked civil society to leverage their diverse skills and competencies and their combined size. Civil society organisations need to recognize the skills that they lack and focus on acquiring them, no small feat in the current climate of limited resources. Funders need to recognize the role that they can play, by building trust through support of supported organisations to acquire these skills and a recognition of a broad spectrum of appropriate tools to measure impact, in which quantitative impact plays an key role.

 

If civil society organisations are equipped in this way, the potential for increasing the sensitivity and responsiveness of social policy is enormous. The ability of civil society organisations to make visible and suggest solutions to social and economic problems which would otherwise be ignored can be strengthened. The increasing complexity of modern societies can be moderated by active citizenship through associations and NGOs that can marshal similar data resources as think tanks, business interests and the state. Without these key tools, and access to a language increasingly necessary for decision making, we will leave the decisions to those who can talk data.

 

Footnotes

[i] Digitalisierung in Non-Profit-Organisationen, Strategie, Kultur und Kompetenzen im digitalen Wandel, BetterPlace Lab December 2017, available here on the 13.02.2018: http://www.betterplace-lab.org/wp-content/uploads/Studie-Digitalisierung-in-Non-Profit-Organisationen-1.pdf

[ii] Ibid.