Data Projects from Go to Whoa!

Before you start any project – data related or not – it’s important to set realistic expectations and goals about what you hope to achieve. It’s key to ensure the right leadership is in place. We guide you through this with a five-point checklist to ensure your data project has the support it needs.

How often have you read that “big data is the new currency shaping our world” or similar? You might have read it on our front page. But what does it mean for your organisation?

Not-for-profit organisations can use the power of data to make more informed decisions. We’ve developed a framework – Developing data capability in your not-for-profit – as a starting point to help you identify the kinds of data your organisation may already be working with and what you can do with that data.

Attend Tutorial 1 to solidify the framework’s concepts and get a practical introduction to data science. Once you've taken it all in, contact us for guidance in your project’s initial stage.

By now, you should have developed some understanding of what data science is and some of the ways it might help your organisation to achieve its goals.

You can now assess how you are using data already and where you would like to do more, using the framework Developing data capability in your not-for-profit as a guide. Once you’ve done that, you’ll be ready to develop ideas for a data project. In particular, you’re looking for places where data might improve efficiency or effectiveness in your organisation.

To help you imagine possibilities, we’ve collated examples of other not-for-profits taking advantage of data, as well as tips on choosing a data science project for your organisation.

By this stage, you’ll have a good idea of the scope and purpose of your project and a project brief. You'll also have some knowledge about data access and quality. In the next steps, you’ll learn how to identify the resources you'll need, how to recruit from outside your organisation (if necessary), and how to put together a team.

This step is where we lay out our project in concrete terms. To speed that up, we’ve produced a budget template and a guided timeline exercise to help you map out your data project over a set period.

Data project resources can include software (i.e. computer programs or tools), hardware (i.e. computing or storage machines) or wetware (i.e. the squishy organs in the heads of whoever works on your project). And with all three, the choices and decisions can be overwhelming.

We provide recommendations for useful free or low-cost software and the equipment you may need in our software/hardware help sheet. Our wetware help sheet plots the skills needed for data projects, how to identify existing skills within your organisation and how to recruit from outside your organisation if required.

How do you go about putting together a data project squad? This step will vary depending on the size of your organisation and the skills and roles of the people working within it.

We’re developing a tutorial to guide you through each process, whether it’s hiring new talent, finding skilled volunteers, employing a consultant, or upskilling existing staff. Create your own job vacancy using our data analyst and data scientist position description templates and use our non-disclosure agreement (NDA) template to ensure clarity about the responsibility of all parties handling confidential data.

Even the most solid of project briefs can be brought undone by insights you didn’t know existed in your data. Data can be excavated endlessly, but if you want your project to lead to action – whether it’s raising more money or developing more efficient processes – you need to learn when to call it quits. As you near the end of your project, it’s a good idea to check back in with your stakeholders to ensure you’re on the same page about how your project is tracking.

Our blog post provides tips on how to know when you’re done, the importance of sticking to your initial questions, and why you need to have clear endpoints.

Congratulations, you’ve done the hard work! Now it’s time to communicate outputs and findings to the relevant stakeholders, including the data owners. Enable an open feedback mechanism to allow for suggestions and queries.

Our five-point checklist guides you through this process. It also explains the difference between "interesting" and "useful" projects and why it matters, and how to ensure the results of your project are put to good use once everything is wrapped up.

Now that you’ve completed your first data project, give yourself a pat on the back!

Then consider how to keep the momentum going: what did you learn, and how can you build on your project to improve the next one? Revisit Developing data capability in your not-for-profit – where does your organisation sit on the data capability pyramid now?

It’s worth reflecting publicly so that other not-for-profit organisations can learn from your journey. Our blog post outlines who we’ve worked with and examples of other organisations’ achievements – tell us if you’d like to be included!

Lastly: get involved with the larger NFP data world! As part of our mission to boost the social sector’s data capacity, we’ve been fostering a community of socially minded data scientists. We held Melbourne’s first Datathon for Social Good and we run the Data for Social Good meetup. We’d love not-for-profit folks to take part and make connections.