At ReadyTech, we build technologies that help educators manage the student experience. And with our student and learning management systems in the operational heart of TAFE, VET, international, higher ed and workforce providers, we have a lot of one thing. 

Data. 

We collect lots and lots of data. About students, staff and about providers. Providers and institutions, likewise, have a lot of data at their disposal – should they choose to use it. 

Only, there’s a problem. There are significant barriers to delivering timely, meaningful and actionable insights that actually help providers make progress on their student experience. 

The big data problem  

Often, education data is stuck inside systems that are not integrated or difficult to access.  

It can be difficult to extract. Difficult to transform into visualised insights that make sense to different users. It can be difficult to use it to empower users in real time on the front lines. 

The EdTech sector isn’t perfect at enabling this. Often, EdTech providers are collecting more data than ever, but don’t have the tools they need to distribute that data to their clients.  

To top it off, educators are not data scientists. Their job is to maximise student learning outcomes, and they are often very time poor. Digging for and using data can take a back seat. 

That shouldn’t stop us. Because in the end, as educators, we’re better off making use of it all. 

Building a basic data strategy in four steps

Getting started with a data strategy doesn’t have to be difficult. In fact, there are four steps we’d nominate as a good place to get started. And the smallest steps can begin the process of transforming student experiences, wellbeing and academic or skills outcomes. 

Step 1: The right tools 

A common misconception is you need a data lake or a data warehouse to get started. While there is a place for that – and we encourage any provider to work towards that future state - often aiming too high stops providers from starting a data strategy at all.

Start simple by using the business-critical systems and tools you have already. In our four step example, we'll reference only two platforms – the Student Management System (SMS) that collects the data, and a business intelligence (BI) tool to create the insights.

In ReadyTech’s case, our SMS example is JR Plus, while our BI tool is Octopus BI.

Part of setting up a data strategy is deciding which systems will act as your single ‘source of truth’. Start to think how you might aggregate data there. To do that, you should consider your systems as part of an ecosystem, and connect the most valuable ones with integrations.

If your SMS is already integrated with other platforms (like an LMS) in an effort to consolidate data from multiple sources, then you’re already winning. Also, ensure your BI tool has the potential to connect your frontline users to the insights you will be generating.

Step 2: Collecting the data 

They key to gathering data is to start considering it as an asset for your business. If you start to value it more, you’ll end up collecting more. And the more data you collect, the more value you’ll create.

One project we worked on that showed how data can enable value creation involved matching an international student to the right accommodation. Our provider client saw this as critical to student wellness and success, and it also meant treating students as individuals.

That meant collecting more data to enable better matching. Using some tricks to collect more data on the front-end during application and enrolment, the whole process was added to the application form and every single data point was written straight to the student’s profile.

Collecting more data means removing the negativity associated with data entry. It means putting energy into making data capture easier, through distributed data entry and integration. It means storing data logically where most users would expect to see it, like a student profile.

Step 3: Creating insights

What is an insight, really? Talk to Octopus BI, and they’ll tell you it's a new piece of knowledge derived from the data you collect. It helps underwrite decision-making. In some ways, it’s like taking a position against the data rather than simply reporting on things that happened.

Insights work best when they are easy to understand and access and when they address known business challenges. For that reason, it’s always a good start by asking questions of data that the business would like to answer, rather than ‘hypothetical’ scenarios with no immediate value.

Be aware insights often lead to more questions. For example, if you’re asking yourself which students are most at risk of failure to complete, because it's a recognised business problem, this will lead to other questions like why particular categories of students are more at risk.

Insights also work best when they are presented to users on the front lines - when they are available to those who need them. Octopus BI says too often insights are reserved for management only when they could increase effectiveness at the learner and trainer level.

Providers should consider ways of increasing adoption and utilisation of insights by connecting them to an existing business process, like accessing them via an SMS during a staff member’s regular flow of work. Also think about how you want them presented to make them easily accessible and appealing, like in graphs and charts or lists.

Step 4: Insight-led action

Insights by themselves can only take you so far. They become supercharged when they lead to action that directly impacts the lives of your students. That’s why having insights available to key staff in real time is so important, for example, making them available inside the SMS.

Using the example of student risk, having a dashboard showing risk can help administrators, academic and welfare teams work with students more actively in their interactions through the student journey, rather than waiting on static reports to filter down after the fact.

You can connect insights to actions through automations within your technology systems. For example, if students are discovered to be at risk and are tagged as such in a system, this can auto-notify your welfare teams of the problem, triggering support when it is actually needed.

Early engagement like this can help course correct students that are falling behind. By properly capturing the data it can help set even earlier interventions for students. But remember, always refine your insights and actions over time with strategic reviews and feedback loops. 

Interested in learning more about how we help providers with next generation enterprise student management technology? Learn more here.