Dearest readers,
It has come to my attention that—much like the juiciest gossip—a shocking amount of data goes missing.
Yes, missing!
While some gaps are glaringly obvious, like Lady Featherington’s ballgowns (think: entire rows of blank spreadsheet cells), the more insidious kind is silent missing data. The sort that slips by unnoticed, like whispers behind a velvet fan—shaping decisions in all the wrong ways.
Take for example a small pocket of households that fail to report solar usage for months. Tiny, yes—but that absence distorts the entire dataset. And the longer it goes unnoticed, the more its quiet influence grows.
This is precisely what happens in health and social care. Even with the rise of real-time dashboards and AI-fuelled insight engines, we are still only as good as the data we collect—and just as blind to the data we do not.
The dangers of missing data
As Caroline Criado Perez rightly warns in Invisible Women, missing data is not merely inconvenient—it is dangerous. When the lived experiences of women, rural communities, people with disabilities, and culturally diverse populations aren’t captured, we design systems that ignore them. Not out of malice—but out of silence.
The $6.5 billion rural health underspend shared at the National Rural Health Conference last year made headlines. But dig a little deeper, and you will find the real scandal: analysts could not factor in allied health or community service spending. The data simply didn’t exist in a usable form. Nor could they estimate the knock-on effects of poor GP access on Medicare or NDIS-funded allied care. The Pharmaceutical Benefits Scheme was included—but even then, they questioned whether medications were simply standing in for the supports people actually needed.
And here lies the heart of it: the data we do not collect keeps us from seeing the people we do not serve.
How unplexi™ turns whispers into action
At unplex, we aren’t just observers of this scandal—we are rewriting the plot.
Our software, unplexi™, is built to collect and connect both loud and silent data in real time. It has been co-designed with industry to collect and connect data specifically for vulnerable and complex individuals. By aligning our data capture with the International Classification of Functioning (ICF), we capture rich, nuanced snapshots of individual needs—not just once, but over time.
We don’t stop at what is easy to measure. We also shine a light on what is missing.
Our system tracks changes in client needs across the four ICF domains—impairment, activity, participation, and wellbeing—then uses AI to make care and workforce recommendations based on actual need, not just historical habit or funding rules. And when data is not available, unplexi™ flags these silent gaps, prompting users to explore what is going unsaid.
But it gets better: unplexi™ doesn’t just use this data for others—it uses it to train itself.
By learning from every data point, every trend, and every gap, unplexi™ evolves. It becomes smarter over time, offering more accurate suggestions for care pathways, staffing models, and service redesign. It adapts not just to the data that is given—but to the absence of data that reveals structural blind spots.
So, whether you’re a support worker or practitioner trying to understand the individuals you serve, a manager rethinking workforce mix, or a policymaker dreaming of a more equitable system—unplexi™ gives you a way to hear and act on the full story, not just the loudest parts.
Because true reform doesn’t happen in the headlines. It starts in the footnotes, the margins, the quiet. And we, dear reader, are listening.
Yours most scandalously,
The team at unplex (with a respectful courtsey to Lady Whistledown)