Choosing a data insights tool for a small charity doing big things

Data at Good Things

Here at Good Things Foundation we do a lot of work with data. Whether it’s managing the funding we distribute to our networks of community partners, proving our ability and capacity to potential funders, or helping us make better decisions about project management, we need data, and we need it to be accessible.

All of our internal data, which covers our online learning platform Learn My Way, and its users, as well as centre, user and funding data for the Online Centres Network in the UK, and the Be Connected Network in Australia, is held in a number of MySQL databases hosted in the cloud. Staff can access a lot of the data they need on a regular basis using MySQL reports that return data in Google Sheets. Anything else requires an ad-hoc report to be written by the Data Insights Team here at Good Things Foundation.

Occasionally we also work with external datasets (e.g. from the Office for National Statistics in the UK), as well as Google Analytics on our websites. We often use Google Sheets to pull different data sources together to produce visual dashboards for consumption by members of staff, project partners, funders etc.

As well as all of this, we also have our own “Management Information” reporting program, built in-house, which performs a nightly extract-transform-load process whilst backing up all our internal data. The results of this number crunching are then visible on our website by staff and centre partners, who can track their own progress towards delivery targets.

What’s up with that?

All of the above leads to a rather chaotic, inefficient and occasionally erroneous relationship with data. Most staff members have little direct insight into the enormous wealth of data we hold and interact with, and turn-around times for deeper insights can be slow. And because of all of this, we don’t have the capacity and the time to delve deeper into the data we have available, to find new insights and answer some of the questions that we don’t even know we want answering yet. The Data Insights Team would love to be able to dig deeper and think about those questions, but we still spend much of our time handling day-to-day requests for data reports.

We are therefore on the lookout for a better tool to help us with “business insights”. What we really need is a data insights tool that not only makes it quicker and easier to produce the day-to-day reports and return them in easy-to-analyse visualisations, but also one that allows any member of staff with an interest in the data available to be able to answer most of their data desires entirely on their own. Without the need for a data expert to connect them with the data, we’re confident that many of our colleagues would be able to find out what they want to know, and in doing so, also become more data driven as individuals. We’d heard from other organisations how the introduction of such tools has helped them, and it’s something we’ve been thinking about for a long time.

Shortlisting

We started by mapping out all the different features and abilities we might want from such a tool. Connecting to our MySQL databases is obviously a big one, as is operating in the cloud (since we don’t host and maintain any physical servers of our own). We also need something with flexibility in terms of prices and licensing, and the ability to lock-down access to different levels of data based on user permissions. And at the end of the day, whatever tool we use must make our lives easier, not harder, so it needs to be easy to use, accessible by non-technical staff, and be able to produce great visualisations. Of course, this is a long and demanding list of requirements, so we prioritised them to help with the shortlisting process.

There are lots of tools out there, from big players like Microsoft and Amazon, to lesser knowns like Alteryx. With price being a big factor (we are a charity after all!), we were able to whittle down all the options to a short-list of three or four choices. Technical limitations (such as the physical location of our cloud servers), reduced this to just two: Microsoft PowerBI and Tableau.

Putting it to the test

Our next task is to trial both of these tools, use them to conduct some of the data tasks that we regularly find ourselves doing, and get a real feel for how they work and how well they would integrate with our existing setup. We want to ensure we include various colleagues in this process, to test how well non-technical staff can interact with the tool.

Whatever the ‘winner’ is, we’re excited to start working with the new tool as soon as possible, and get closer to those interesting insights that we’re certain are waiting for us.