The big data dream
This article first appeared in CIO Outlook Magazine November 2018.
In Education we have tracked data since the beginning of formal education, via student attendance and reporting, however, the majority of schools are hampered by the constraints of their legacy platforms to extend that capability much further. There is a sense of frustration in the sector that there are strong pockets of innovation and digitisation but until our platforms are cloud-based, the integration and lack of API’s are holding us back.
The very nature of software platforms is counter-intuitive to the agile and responsive organisations that we are aiming to build. What seems like minor requests and changes to the end-user can result in costly and lengthy projects. The frustration stems from when strategists, who are often working a few years out, are clear on where they need to be but find that the digital solutions to support their upcoming aspirations (or requirements) don’t exist.
In an ideal world, our platforms would all be SIF (Systems Interoperability Framework) compliant as this then enables systems to interact and share data securely, efficiently, and cost-effectively. Big data by definition means pulling data from multiple sources and so schools are no longer just looking at the pool of data collected on students (academic, fitness, wellbeing, operational data e.g. attendance records) but using the power of data to predict future enrolments and catchment areas to influence marketing strategy and spend. Some schools are using academic dashboards to provide teachers with insight into their class prior to the start of the school year, so that they can not only obtain the academic history of each child and gain prior knowledge of who their students are so they can adjust the curriculum to suit but also better prepare for the first parent-teacher conferences which often occur in the first few weeks of the first school term. There are also many schools already predicting the best outcome for students by providing them with data on the best mix of subjects that they need to gain entrance into the particular academic pathway they are aiming for.
The other consideration is to ensure your data source is reputable, clean and adding value. Keeping it simple and focused is one way to avoid data paralysis – where the amount of data you have, and the need to analyse which data is valuable and therefore worth mining in the first place, can paralyse the decision making process.
From an operational perspective I’ve touched on enrolments and marketing, however, staffing can also have a major influence on the bottom line. If a school’s daily organiser (timetabler) could use A.I. to predict workflows via historic staff attendance data, they could be better prepared for those weeks when schools are hardest hit by illness and absenteeism. They could also use the online curriculum delivery platforms to predict the greatest needs for touchpoints between educators and students. This modelling could report on the teaching outcomes of full time vs part-time educators, and track the use of casual relief staff, who are regularly employed by schools at great cost via staffing agencies.
In marketing, data is tracked easily using Google analytics and media monitoring tools. This data can provide excellent competitor analysis as well as providing intelligence on the gaps in the marketplace, allowing schools to position themselves in a clearly defined niche market. Spend is tracked via such metrics as click-through rates and website visit statistics, which can all then be mapped to enquiry levels and enrolments, ensuring there is a return on investment.
It’s important to note that in education the focus around data security is not around business intelligence but around data privacy and child safety regulations, as our largest data sets are connected to minors. What further complicates matters is the level of responsibility you can put on a child. In Australia they can’t vote until they are eighteen, however, they have access to and control of social media accounts from age thirteen and at fourteen the Government gives them full responsibility for their own MyGov Health Record. Like anything, education is key and we need to ensure our young people are armed with the understanding and responsibility that is being expected of them.
Purposeful data analysis has the power to take the guesswork out and whilst it’s not always personalised, its predictive capability certainly improves the odds many times over. Data can give decision-makers the confidence in knowing that risks are now measured, reassuring them that agile can work, even in the oldest of institutions.
