Most institutions have one: the person who became the Power BI expert by accident. They were good at Excel, which in most teams is enough to get you volunteered for anything involving data. Someone needed a dashboard, they had a go, and it worked. Then they had a go at another one, and that worked…
A few years ago, Amazon quietly scrapped an AI tool it had built to sift job applications. The tool had been trained on ten years of the company’s own hiring decisions, the idea being that it would learn to recognise a good candidate the way Amazon’s best recruiters did. It learned something else. It taught…
Most institutions already know where their data problems are. What they don’t always have is the time, the headspace, or an outside pair of eyes to do something about them. That’s the gap Sparkline Consulting works in. We work with universities, colleges and smaller providers across higher and further education on the practical end of…
Ask an admissions team whether they’re ready for AI and the conversation almost always turns to tools. Which platform, which features, which pilot, which vendor everyone else seems to be talking to. It’s a reasonable instinct. It’s also the wrong place to start. Readiness isn’t about the tool you bolt on. It’s about the conditions…
Genuinely. If you work in higher education, you’ll know that this time of year carries a particular kind of weight. The months of assessment, marking, moderation, and quality assurance that culminate in an exam board aren’t just administrative processes. They are the moment where years of student effort become an official outcome. Getting that right…
The Data Goddess has started a company. Today Sparkline Advisory officially launches – a consultancy for universities and colleges that want to manage their data well, meet their regulatory obligations without drama, and adopt AI with something other than panic or blind enthusiasm. If you have followed my work for a while, very little about…
There is a particular kind of discomfort that comes from looking at what an AI system has learned and recognising, in its outputs, something uncomfortably human. Not a glitch. Not a malfunction. Not the robot going rogue. Just a very accurate reflection of the world we gave it to learn from. The algorithm that learned…
“Data-driven” has become one of those phrases that organisations put in strategies, say in meetings, and include in job descriptions without anyone stopping to ask what it actually means in practice. It has the comfortable quality of sounding rigorous without committing to anything specific. And that, unfortunately, is usually where the trouble starts. Let’s be…
There is a scenario that plays out somewhere in the HE sector almost every year. A small institution is approaching the Student Record return cycle. The person who has managed the return for the last several years is unavailable – on long-term sick leave, has left, is managing a concurrent crisis, or simply cannot remember…
“Data-driven” has become one of the safest phrases in higher education. It appears in strategies, board papers and funding bids. We reassure ourselves that we are data-driven. We celebrate dashboards. We track metrics. We monitor trends. And all of that is positive. It signals seriousness about accountability and performance. But there is a subtle distinction…
