Data Strategies 4 Change

Data strategies for emancipatory change

Often we NGOers see Big Data as a threat – often rightly so, because corporations like Google and Facebook want to spy on and manipulate us.

At the same time, many NGOs rightly fear missing opportunities by not using existing data, not collecting accessible data and not using new data science methods.

Data analysis and proper metrics can significantly improve the effectiveness of our work in the non-profit sector. - And that’s what we’re all about: How can we have the greatest possible impact? How can we best change the world?

The four levels of data use

Basically, data analysis can help you on four levels:

  1. Strategic

    1. Understanding what your supporters want. What is your donor base?

    2. steering Setting strategic goals and measuring success quantitatively and communicating them visually to the organisation can help teams unite behind these goals.

    3. Evaluating What worked well? What action was worthwhile? What impact did our activities have?

  2. Operative
    concrete design and wording decisions: Who gets the mailing? Is it better to ask for one-off donations or for memberships? Which is the best argument to get someone to sign a petition?

  3. Content
    Data analyses strengthen our content-related concerns and create a basis for communication. This is why data journalism is also an increasingly important field.

  4. Communicative
    Data can be used to communicate concerns, e.g. to make clear to supporters what effect their voluntary or financial support has had. Skilful visualisation of data is often the most important building block for this.

We are happy to contribute to all these areas.

What do we offer?

Our approach is to develop the specific analyses in a dialogue. Tell us what questions you want to answer and we suggest how to get that out of the data. We do both the conceptualisation and the implementation in concrete code.

Examples of services :

  1. strategic data consulting, e.g. development of metrics

  2. individual data analyses, e.g., creating a machine-learning model from your data to determine who to best sent fundraising letters to

  3. development of software to create automated reports and dashboards

  4. help in communicating numbers in an understandable way. E.g. creation of an understandable financial report

  5. conducting and analysing surveys

  6. reviewing your analyses. - we am happy to give you an expert opinion on an existing analysis

  7. long-term support in the interpretation of your data analyses

It is important to us that the analyses produce practical results. This is not about academic work, but about concrete decision-making aids. To this end, the results must be clearly communicated. The best analysis will not advance good decisions if it is not understood within the organisation.

Our approach here is to automate as much as possible and make the analyses as understandable as possible. We want reports and dashboards to be automatic, because only what can be determined regularly with little effort and is understandable makes decisions better in reality. This is also the great advantage of evaluating data via programme code instead of Excel spreadsheets.

Principles of our work

Free software and data sovereignty. The data is yours. The software we write we provide to you. You are not dependent on us, as we use common tools (programming languages: python and R, visualisations: plotly) and document the code in English.

Data Security We do not upload your data to the cloud, but work with it only on our own local linux machines with encrypted hard drives. If you want we can build you docker files so you can run automatic data analyses easily yourself on any (linux/windows/mac) machine of your chosing.

Let’s get talking

Curious? Then let’s talk. Via video or gladly in person in Berlin or Bielefeld: