Future Session #3: Key insights from the Data Journey Methodology (Akvo)

How can organisations make optimal use of the Data Journey methodology?

agenda May 9, 2019

On April 30th, 2019, The Spindle, in collaboration with the Humanity Hub, organised Future Session #3 of the year about the Data Journey Methodology. The session was facilitated by not-for-profit Akvo, which supports organisations with data tools and services. The workshop featured an overview of the data process and two interactive exercises. The participants worked on solutions to their data-related challenges, with the data journey methodology in mind.

The data process is often extensive and hard for many to grasp. This introductory session zoomed out on the entire data journey and shed light on questions such as: what steps can and should we take to improve the effective use of data to contribute to positive impact in our programmes?

The data journey methodology
The session started with a presentation outlining the importance of looking at the entire data process, and not just the often over-focused phases of capturing and analysing the data. What do we want to measure? What actors do we involve? How are we going to manage the data? And so on, all important questions to focus on. To structure the data process Akvo outlined their data journey methodology, which breaks the entire process down in four core phases – design, capture, understand, act – and various sub-steps in each of these phases. This is an iterative process in which each of these phases must be addressed in order to create an efficient data (and information) flow and optimal results. Akvo walked us through these phases and outlined what to focus on to improve. An in-depth open-source document outlining this methodology can be found on Akvopedia.

What can we learn from this methodology?
After the presentation, the participants worked together and mapped and discussed challenges and potential solutions for their data processes. Inter alia, some of the key learnings were:

  • Involve important stakeholders early on in a participatory design. This can mitigate risks of people feeling left out and increase the quality of your outcome in the Act phase (i.e. take action based on data).
  • A considerable amount of data might be already out there – conduct data research guided by a specific question!
  • Agree on definitions so that you know which data you can and cannot use and what data you are capturing and using.
  • Focus already on the design phase on the key success factors of the Act phase.
  • Collaborate with others to improve your data process and data quality.
  • Involve data scientists in the design phase as they will not be able to solve your design flaws later.
  • Share your data (but structure it) if at all possible to help others out and save costs.

Additional information about this session and its outcomes can be found here.

Interested to discover more about important trends and their relevance for the future of development cooperation? Join us in the next Future sessions! The upcoming one will be on Economic Perspectives on Urban Futures and Resilience and will take place Tuesday, May 28. Please sign-up! 

Future Session #2: Mapping Impact through Earth Observation & Big Data Analysis

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Future Session #1: Data, Machine Learning and Artificial Intelligence

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Future Session #10 Open Innovation & Open Design

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