Intended audience: DataKind Volunteers
Just like in the Discover Stage, you may be faced with the decision to pause, discontinue, or even decline a potential project during the Design Stage of the scoping process. While you will need to make the decision to either continue with the partner organization or not, the job of Scopers is to think about what the team is missing and communicate that to the organization. This article will help you think about these decisions and communicate them with the partner organization.
So how do you know if the potential project is not a fit during the Design Stage? Assessing a project’s feasibility and fit is different at this stage than during the Discover Stage, since you have already determined that the organization is mission-aligned with DataKind and identified a potential data science-able solution. You also should have completed the Discover Checkpoint and launched the Design Stage with signing data sharing agreements.
Here are some examples of projects during the Design Stage that should be either discontinued, paused, or declined. Remember that you may be faced with the decision to pause or discontinue a project at any stage, this is not an exhaustive list.
| Situation | Scoper Action |
|---|---|
| Too many ethical concerns have been identified which cannot be responsibly mitigated against. | Be prepared to identify and communicate additional ethical considerations that have risen during the Design Stage (e.g., the data audit or project risk assessment). In this case, a project is not recommended and we communicate the reasons and opportunities to the team. |
| The available data doesn’t support the proposed data science solution. Additional data sources would need to be acquired, which doesn’t fit within the project timeline. | If you’ve identified the need for additional data sources, which would take longer than a reasonable timeline to create or acquire, communicate that the project would need to be declined or paused. |
| There isn’t available infrastructure or computational resources to support the execution of available data. | When a large amount of data is required to conduct a highly intensive project, for example training a machine learning model, it can require a significant amount of computational resources, which is expensive. Present to the organization which computational resources are needed and the anticipated cost, communicating whether you believe the project should be paused until these resources are acquired, or declined. |
As you evaluate your project based on these criteria, it is important that you communicate responsibly and professionally as to why the problem and solution may not be a good fit for a DataKind project. We recommend that you customize your email communications to the specific partner and their context (and please get in touch with DataKind staff support if you have any questions or concerns!). However, here are a few tips and best practices we recommend:
- Find templates in our One Stop Shop for scoping email templates
- Just like during Discover Stage, try to find a way to provide value to the organization if possible. They’ve spent time talking with DataKind, and we want to ensure that they leave the process with lessons learned and guidance for next steps. We recommend providing the partner with a proof of concept outlining ways in which their data or infrastructure could be improved for project readiness, and/or creating a summary document of action items that the organization could implement to improve their idea.
- Always communicate in a professional and responsive manner. It is important that you immediately communicate issues to the Project Champion and DataKind staff throughout the scoping process.
Contributer(s): Caitlin Augustin, Mitali Ayyangar, Benjamin Kinsella, Emily Yelverton, Arina Igumenshcheva, Mallory Sheff, Rachel Wells
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