Intended audience: Social Impact Professionals
One of the most important parts of the DataKind process is mapping the project to the partner organization’s desired impact and measures of success. We do this through “project statements,” which are a summary of the project’s activities, data, and impact in one simple sentence. Many people think that coming up with a data science solution or running a project is where all the action is, but we have actually found that converting a business problem into a data science-ready project is the key to success.
At this point, DataKind and the partner organization have had at least one discovery call to discuss organization and data readiness, availability, and maturity. You are in the process of scoping a couple of project ideas, and are ready to write the corresponding project statements using the following template:
“I want to (analysis) using (data) so that (behavior change) so that (impact).”
For example, “Lwala Community Alliance wants to automatically find, categorize, and summarize inconsistent or problematic data using the digital data collected by community health workers so that the data quality can be improved so that teams on the ground can make rapid, trusted decisions to improve their programs and better serve and preserve the lives of mothers and babies.” See additional examples here.
The purpose of writing a project statement is to understand and document the universe in which the partner organization operates. The project statement ultimately moves us towards quantitative and qualitative measures of success.
Developing Project Statements
Step 1: To develop the project statement, we start with the partner organization’s goals, mission, and what success looks like for them. The “so that (impact)” will be that ultimate goal that the partner organization is trying to achieve. Your project should ultimately map to this goal. It is common to start with multiple possible answers to that question that will get narrowed down to the best fit impact goal based on project ideas and the organization’s theory of change.
Step 2: Next, we go to the theory of change to better understand the process to achieve this vision. How does the partner organization map their activities to their mission? What are the outcome levels? The team discusses blockers, areas that could be improved, and pain points. With this information in hand, the team drafts options for the “so that (behavior change)” part of the project statement, identifying areas that you could address to truly make progress on a goal. As you reflect on your theory of change and programs, you’ll likely think of several options of things that could go here. Keep thinking creatively, and come up with several options. What change do you want to make that will end up completing your vision?
Step 3: Now, it’s time to start brainstorming some data science solutions to address the challenges you uncovered! At this point, we ask questions like: What data science project do you think would help you address these issues or pain points? Who will be the users of the data solution? How will they use it? Looking at these answers alongside the theory of change, we draft options for the “I want to (analysis) using (data)” part of the project statement.
Make sure all your ideas clearly map to the goal, and add any intermediate “so that” steps needed to clearly demonstrate how the data science project will map to the change. Feel free to create as many project statements as you can think of! The data audit will narrow the scope of the project to what is realistic and ethical. The Discover Stage is all about finding a great partnership and possible project ideas. Later, in the Design Stage, we will narrow down the ideas to a specific project scope, based on a close look at the data.
Clarifying the Language
That said, the one sentence version can be hard to read, so we can also frame the same information in multiple sentences. For example, this could look something like, “Organization X exists to (mission). They do this through (theory of change). They have (a project statement / hurdle to doing their work). We’re proposing to use (data) to do (analysis) that will ultimately (behavior change), leading to (impact).”
For a real life example, “Lwala Community Alliance exists to reduce maternal and child mortality among populations that live prohibitively far from healthcare facilities. They do this by empowering community health workers with digital data collection tools to monitor the health of mothers and babies. Every month, hundreds of patient interactions are logged and in spite of safeguards, inconsistent or problematic data find their way into mission-critical datasets. We’re proposing to build a solution that can automatically find, categorize and summarize errors so that the problematic data can be remediated. This solution will improve data quality and allow teams on the ground to make rapid, trusted decisions to improve their programs, in order to better serve and preserve the lives of mothers and babies.”
Every project should have a paragraph like this that all team members can understand. It informs how we measure success and what our priorities are, as the scope of the project evolves based on the results of the data audit. The project statement will be captured in the concept note, which will guide us as we kick-off the Design Stage of the project process next.
Please see other “scoping” articles for social impact organizations at the bottom of the Scoping page.
Contributer(s): Mitali Ayyangar, Cassy L Cox, Caroline Charrow, Shanna Lee, Daniel Nissani, Jake Porway, Mallory Sheff, Rachel Wells
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If you would like to learn more about us, partner with us, or get in touch, email us at community@datakind.org
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