Are you wondering when you should write a data science project proposal document? Or maybe you are wondering what content you should include in a data science project proposal? Well either way, you are in the right place! In this article we tell you everything you need to know about writing data science project proposals.
First, we talk about what a project proposal is and what the purpose of writing a project proposal document is. After that, we talk about when you should write a project proposal document. We follow this up with a description of what content should and should not be included in a data science project proposal document. Finally, we provide tips for writing a strong data science project proposal document.
What is a data science project proposal?
What is a data science project proposal? A data science project proposal is a document that is written when you want to propose a new data science project idea. This document should include information about the problem that you want to solve and why it is important to solve that problem, among other details.
Why should you write a data science project proposal?
Why should you write a data science project proposal? The main reason to write a data science project proposal is to ensure that you are aligned with your stakeholders on what your team should be working on. Specifically, a project proposal document should be used to align on what problem will be solved and what constraints the solution needs to adhere to. It should also be used to align on timing and whether now is the right time to work on a given project.
It is important to put your vision for the project down on paper so that it can be reviewed by your stakeholders. Putting your thoughts in writing makes it easier for stakeholders to give asynchronous feedback. It is also less common for miscommunications and misunderstandings to happen when there is a written document to reference. As an added benefit, a project proposal document will serve as a key piece of documentation that future team members can reference to understand why a project was prioritized.
When should you write a data science project proposal?
When should you write a data science project proposal? You should create a project proposal document early in the project lifecycle. Creating a proposal document should be one of the very first steps you take when starting a new project. The only activity you might perform before creating a proposal is running an impact sizing exercise to estimate the scale of potential impact.
You should make sure that you do not invest a lot of effort into a project before aligning on the project proposal. That project proposals can be rejected and or put on the back burner for later. You do not want to invest a lot of effort into a project just to learn that your stakeholders are not aligned on the need to work on the project.
What should be in a data science project proposal?
What should be in a data science project proposal? Here are some of the main topics that should be covered in a data science project proposal.
- Problem. The first thing you should include in your project proposal document is a description of the problem that you intend to solve by working on this project. It is important to put this in writing to ensure that everyone is aligned on exactly what problem will be solved.
- Reason for solving this problem now. The next thing you should include in a project proposal document is the reason that you should solve the problem now. There are likely to be many different business problems that your team could be working on at any given time, so it is important to have a justification for why now is the right time to solve a given problem.
- Constraints. The next section you should include in your data science project proposal is a list of constraints that your solution needs to adhere to. This should include both business constraints and technical constraints if possible. If you do not have enough familiarity with the technologies you will be using to understand the technical constraints they will impose without doing some exploration, you can stick with just the business constraints your solution needs to meet.
- Goals. The next thing you should include in the project proposal is a list of goals for the project. These goals should describe the criteria that needs to be met in order for the project to be considered a success.
- Non-goals. It is just as important to include information on what will not be included in the scope of a project as it is to include information on what will be included in the scope of a project. Make sure to include details on edge cases that you will not be tackling a part of the project.
- Business metrics and impact sizing (if applicable). Finally, you should include information about the business metrics that you intend to move with this project. If there is not a clear business metric that the project will move, you should reconsider whether you should be working on that project. If you are able to give an estimate of the size of the impact you might expect a project to have on a given metric, you should also include that information in the proposal.
What should not be in a data science project proposal?
What should not be included in a data science project proposal? Here are some examples of information that should not be included in a data science project proposal .
- Implementation details. Project proposals should focus on the nature of the problem that needs to be solved and the constraints that the solution needs to adhere to. They should not go into detail on what solution will be built or how the solution will be implemented. Details about how the solution will be implemented should be saved for a technical design document that should be created later in the project lifecycle. You should not have all of the details necessary to describe the solution that you will build this early in the project lifecycle.
Tips for creating a strong project proposal?
How do you write a strong project proposal that will drive alignment with your stakeholders? Here are some traits that characterize a strong project proposal document.
- Succinct. You should aim to make your project proposal document succinct and only include details that are necessary. There are multiple reasons for this. For one, it will make it easier for stakeholders to skim your document. This will increase the likelihood that any given person will actually read through your document.
- Opinionated. A project proposal document should be opinionated. It should state clearly what should and what should not be done as part of the project. The more opinionated the document is, the more likely that the alignment that is achieved in the proposal stage will carry throughout the rest of the project. Stakeholders will understand exactly what the team is and is not committed to up front.
- Accessible. A project proposal document should be written for a broader audience that contains both technical and non-technical stakeholders. It should not contain specific technical terminology or references that would make it inaccessible for a less technical audience. You should always aim to get feedback on your document from a wide variety of stakeholders with different backgrounds and experiences, so you need to avoid writing the document in a way that is only accessible to a small subset of people.
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- Data science project lifecycle
- Getting feedback on data science projects
- Data science design documents
- Data science project backlogs
