How Putting People First in Data (and MyTerms) Can Change the Hiring Game
Job hunting and recruiting have always been massive data operations. Think of it like a huge matching game where both sides are frantically gathering info and trying to figure out if they're right for each other.
But here's the thing - employment is just one of many life events when having all your key personal information complete, accessible, and accurate is an essential start point which will enable you to get your best outcome.
The Current Mess
If you're looking for your first job (or coming back after time away), you know the drill. You're running around to different websites, digging up documents, filling out the same forms over and over just to get through each step of the process.
Then? Nothing. No explanation about why you didn't get the job - or even confirmation that someone actually looked at your application. Thanks to AI screening, this radio silence has become pretty much standard. Recruiters can process way more applications than ever before, but somewhere along the way, the human element got lost.
The whole scenario kills trust and is, for the individual, deeply disheartening. What should be a conversation about people - their unique talents, their potential – seems to have become a depersonalised numbers game.
The Other Side of the Coin
Meanwhile, the "perfect" candidates - the ones with exactly the right skills ready to jump into a role - aren't even browsing job boards. Why would they? They're seasoned enough to know that all that time and effort might not actually lead to the better salary or benefits they were promised.
Sometimes great candidates just give up mid-process and stick with their current employer or go somewhere else entirely. Maybe the job requirements weren't clear from the start, or maybe they realised their reasons for applying didn't actually line up with the opening.
And then there are the real headaches for the recruiter - like finding out someone can't legally work in your country only after you've spent weeks (or months!) interviewing them, or even worse, after they've already started onboarding.
The bottom line?
Despite all the supposed efficiency gains, the current system barely works for anyone involved. It's going to take some serious rethinking to fix these problems.
Sound familiar? This is basically the same situation companies faced a couple decades ago when they realised the need to become "customer-centric", except that this time their transformation must focus on their prospective employees.
What "Candidate-Centric" Actually Looks Like
Most companies today love saying "our people are our most valuable asset" - especially with all the AI hype. But if that's true, shouldn't every potential employee feel valued from day one? Shouldn't their time investment in your hiring process be respected?
Mending this broken process starts with how we handle information:
• Personal data that's always ready when needed
• Qualifications that can actually be verified
• All the employability essentials laid out upfront
Sure, work history matters. But let's be honest - if everyone's using the same resume-building AI tools, those documents are going to look pretty similar, right?
What really makes someone a great fit - especially early in their career - is often the other stuff. Their interests, their circumstances, what makes them tick. That's why managers always ask questions like "Where do you see yourself in 3 years?" or "What would you uniquely bring to this role?"
Understanding someone's intentions can be the deciding factor, especially in today's rapidly changing work landscape.
A truly candidate-centred approach would mean actively marketing roles and reaching out to great-fit prospects at scale - not just waiting for applications to roll in.
Protecting Privacy While Moving Forward
During those early stages, candidates should control their sensitive info - current salary, personal situation, health aspects, age. They should be able to share it selectively: only with specific people, only when they're shortlisted, only when there's an actual offer on the table. The candidate’s control of this becomes reality with the adoption of the MyTerms model – proving that the recruiter values privacy from the get-go.
By the time someone gets hired, the other strong candidates have usually assumed they didn't make it and moved on. But for everyone, tracking and feedback should be standard, not exceptional.
Even better? With their permission, solid candidates should stay in the pool for future roles. The insights about what makes someone a good fit often only become clear after they've been in a role for a while - and that knowledge can shape better recruiting down the road.
Plus, in most countries, fair recruitment laws mean you need to keep assessment records anyway. So they might as well be used constructively.
Where We're Headed
There are some impressive players emerging who've recognised these issues and built smart matching capabilities. Some focus on contract work or niche industries, but there's a lot of learning happening as this space matures.
Like with any AI, it all comes down to accurate information and good feedback loops. The design challenge is building trust instead of destroying it.
That's where DataPal comes in. Our whole reason for existing is delivering personal data ownership, privacy, trust, and empowerment. The DataPal and MyTerms platforms help both candidates and organizations tap into this shift in thinking.
It's an exciting, collaborative space. We're focused on our unique piece of the puzzle - complementing the smart niche players and forward-thinking HR tech providers who are already building a better future.