On CorrelAid: Data Science for Social Good. Q&A with André Lange
Q1. What is CorrelAid and what is your role in it?
CorrelAid (www.correlaid.org) is a Germany-wide network of c1.000 volunteer data scientists. We offer project-based analytics consulting for non-profit organizations. In a nutshell, we are data scientists who are doing good by helping organisations that are doing good to do it more effectively or efficiently. We are doing this with what we do best and what we enjoy: data science.
Because we anticipate a growing demand for data analysts in the public and non-profit sector, we are also educating our analysts in project management, data security, data ethics, and science communication.
We saw a great potential to establish local CorrelAid chapters because it allows us to be closer to the social organisations and to better nurture the data scientist community. So since November 2018 I have started to establish the local Rhein-Main chapter for CorrelAid. Currently, c110 of our c1000 data scientists are in the Rhein-Main area, and we are running 2 local projects with another 2 projects under discussion.
Q2. How can we leverage data science and its tools to solve real-life problems for social ‘good’?
We can help an organisation become more efficient for example by improving their internal processes. We can also help an organization to become more effective, for example with analyses that identifies the right activities, the right needs, or groups of people for the organisation to focus on. Often we do both. For example, we are currently in a project where we support the Weltladen Dachverband e.V. (head organisation of the German fair-trade shops) to conduct a survey more efficiently than they have done in the past. We also aim to allow Weltladen to get more from the survey, for example by enabling them to analyse the data better than before. This will hopefully allow them to be more effective in tailoring their offerings.
Q3. In fact, how do you define “social good”?
Hhmm, that’s a tricky one. I would try the equivalent to Justice Potter Stewart’s “I know it when I see it”-definition: a cause is helping the “Social Good” when we can motivate enough data scientists of our network to do pro-bono work for it. That means, for example, that we would refrain from actions where the impact of our volunteering work would mostly benefit a commercially oriented stakeholder of an organisation.
We set ourselves further guidelines such as that we are trying not be part of activities where we are supporting a specific political party. However, strengthening the democratic institutions is certainly one of our objectives.
Q4. What are the main challenges you have encountered to perform data-projects for the Social Good?
As in the private sector, it is often that there is not sufficient data available which is often connected to the lack of understanding of how beneficial big data and advanced analytics for social causes could be. We can currently observe how widely commercial activities re-orient themselves towards data-driven business models and benefit from that. (Even if you think that this is just hype you will accept that some business models will survive and be profitable.)
I would like to see the same urge for change in social organisations because they could benefit from the same drivers.
I would like to see this not just in the social organisations itself but also in the institutions that support them. Therefore, one of the main goals of CorrelAid is to initiate a dialogue on the value and benefits of data and data analysis for civil society.
Q5. What are the main lessons you have learned with CorrelAid?
That it often needs very little to create a positive impact, and that this impact is in the social sector very often right from the beginning both significant and relevant.
Working for CorrelAid, I was lucky enough to get familiar with many initiatives with a positive impact. They created something that would not have been there without the drive and initiative of the people behind it. As part of CorrelAid, I have learned that every little volunteer work counts, and it is great to see how we as a team work together.
Q6. What are the most “successful” projects for Social Good you have done so far? How do you define “success” in this context?
In Business Manager terms I must define “success” as having the highest leverage in terms of getting the biggest social impact for the amount of volunteering work that we put into the project. A successful project is also one in which our data scientists learned a lot from the project team and from the organisation that we do the project with.
However, neither of the above is easy to measure. Therefore, please forgive me again for partially dodging a question by listing projects that are somehow exemplary for the wide range of CorrelAid projects:
European Youth Parliament:
– The Schwarzkopf Foundation, together with the European Youth Parliament, promotes European thinking and brings together young people from 40 countries.
– Our solution: Analysis of member data
– Our Impact: The insights gained from our analysis will help the foundation to specifically target disadvantaged regions in order to increase their representation in the European Youth Parliament.
GoVolunteer
– GoVolunteer connects volunteering projects and social initiatives with people who want to help.
– Our solution: Development of a dashboard for all relevant steering information
– Our Impact: GoVolunteer can react more quickly and based on better information. Also, time saved on manual compilation of information can be used more meaningfully.
Q7. How do you acquire the skills needed to perform data science projects with social impact?
As CorrelAid we have many activities to enlarge our network of data scientists, for example we are presenting at Meetups and are also holding technical courses at universities. When we staff projects we try to balance – among other aspects such as gender – different skill levels so that the cross-training within the project team is the highest.
Q8. What is your role at Commerzbank?
I am working in the unit that is responsible for managing Commerzbank’s market, counterparty, and liquidity risks. There, I am responsible for the Business Management team and the Strategies, Regulations & Processes team. The latter team is responsible for the group’s market and liquidity risk strategies, the internal governance framework including policies, process management, and the internal control system.
Q9. Do you benefit in your Commerzbank work from your activities with CorrelAid?
Yes, definitely, and this is also one of the drivers to be engaged with CorrelAid. Firstly, I could gain more real-live data science experience.
Secondly, in CorrelAid projects I have learned new tools and ways of working that I could apply at Commerzbank. For example, for our communication in projects and for our internal coordination we always use Slack. I found it much more efficient than using emails. I could transfer a lot of what I learned in the projects to my workplace.
Last but not least, I think that the start-up mindset at CorrelAid infected me a bit and made me experiment more.
Qx Anything else you wish to add?
Thank you, Roberto, for this opportunity to talk about CorrelAid. It would be great to get feedback and ideas from your readers to improve or potentatial areas where we can get involved. Please contact me: rhein-main@correlaid.org
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André Lange, Team Head in Group Market Risk Management at Commerzbank and Local Chapter Manager for CorrelAid X Rhein-Main