News & UpdatesAlmuruna One did not begin with AI. It began with frustration
We had more and more HR systems, more and more data and ever better dashboards. And yet I still spent a striking amount of time searching, checking and reconstructing. Not because the information was not there. Because it rarely came together at the moment it was needed.
Björn Slegers ·
I spent years working in HR director roles in organisations where more and more was being digitalised.
New HR systems. Better payroll solutions. Recruitment software. Performance tools. Dashboards. BI. Later, AI too.
On paper, we were becoming increasingly data-driven.
And yet the same thing kept surprising me.
When a decision really had to be made, the reconstruction work often began first.
Why does this figure differ from payroll? What role did this employee hold when that decision was made? When exactly was that contract changed? Why are we seeing an increase in absence here? Is that new, or had it been happening for longer? What do we know about staffing levels in that team? Where is the context from the previous conversation?
The data was usually there.
It just was not all in one place.
That sounds like a technical problem. To me, it increasingly became an organisational problem.
We had no shortage of software
My frustration was never that HR had too little technology.
Quite the opposite.
In many organisations, we actually had a great many systems. And often they were good systems in their own right.
A social secretariat that processes payroll reliably. A recruitment tool that tracks candidates effectively. A BI environment that produces strong reports. Microsoft 365 for collaboration. A performance platform. A time-recording system.
The problem was not necessarily that any one of those systems worked poorly.
The problem arose between them.
Each system knew one part of the reality.
Recruitment knew why someone had been hired, but that context largely disappeared as soon as onboarding began.
Payroll knew the salary, but not necessarily the reasoning behind a historical deviation.
Performance knew the objectives, but not always the context in which a role or responsibility had since changed.
A dashboard could bring information from different sources back together afterwards, but by then someone had already spent hours checking, interpreting and correcting it.
That was where an uncomfortable question began for me.
If our systems know so much, why do people have to reconstruct reality over and over again?
Digitalising is not the same as connecting
For a long time, we started with processes.
Recruitment had to become more digital.
Payroll more efficient.
Performance more modern.
Time recording more accurate.
Compensation easier to understand.
A solution emerged for every issue.
That improved a great deal. But in doing so, we also built digital islands.
And we do not automatically solve that by putting all the data in a data warehouse afterwards.
That is valuable, but it is something different.
A report can show perfectly what happened after the event. The question is how much context was lost in the meantime as work moved from one process to another.
In my view, that is where an important next step for HR technology lies.
Not trying to force everything into one system.
But ensuring that the same employee, the same contract, the same role and the same organisational context do not become a different reality again in every process.
That distinction matters.
Today, I believe even less than I used to in the idea that an organisation must replace all its existing technology to become digitally mature.
Why would you replace a good social secretariat? Or a BI environment that already holds a great deal of expertise? Why would you not use a specialist AI environment, calendar or note-taking tool when it does something particularly well?
The world of software will probably not become simpler.
It will become richer.
There will be more specialist applications, not fewer.
So the challenge will not be to replace everything.
The challenge will be to connect without fragmenting again.
And then came AI
When generative AI suddenly became much more powerful, that old frustration only became more relevant to me.
Because AI has a particular characteristic: it can give exceptionally convincing answers based on incomplete information.
That makes context more important than ever.
Suppose a system sees that overtime in a team is increasing.
On its own, that says little.
Perhaps there is a temporary deadline.
Perhaps the team is understaffed.
Perhaps hours are being recorded differently.
Perhaps there is no problem at all.
Add absence, scheduling, team staffing levels, contractual hours and historical patterns, and a much richer picture emerges.
Still not a conclusion.
But a better question.
To me, that is a fundamental distinction.
I do not believe AI should tell an organisation who will leave, who is at risk of going off sick or which manager has a problem.
People are too complex for that. So are organisations.
But AI can help make something visible a little earlier.
That several signals are changing at once.
That a situation differs from what is normal.
That information from different processes comes together to form a pattern that no one had seen in isolation.
And technology can then help bring the context together for a person.
That is something very different from taking over the decision.
It is preparation.
And that is precisely where I see enormous value.
That became Almuruna One
Almuruna One therefore did not begin with the idea that the world needed another HR platform.
It began with frustration.
With the feeling that, as HR professionals, managers and executive teams, we were losing too much time bringing back together information the organisation actually already knew.
With dashboards that answered the questions we had thought of in advance, while relevant connections often lay between those dashboards.
With processes that were individually becoming increasingly digital, but not necessarily smarter collectively.
So the first question was not:
Which modules should we build?
The question was rather:
What happens when all those processes can use the same context?
What if a change in one process does not disappear as soon as the next one begins?
What if information about roles, contracts, the organisation and employees does not have to be reconstructed over and over again?
What if, as a result, AI does not feign greater certainty, but can instead use better context to make relevant signals visible?
One grew out of that.
Today, there is a great deal of technology around it. Core HR, Recruitment, Onboarding, Time, Pre-payroll, Pay Transparency, Performance, Reward, Compliance, People Intelligence and Executive Intelligence.
But to me, the list of functionalities is not what matters most.
The underlying idea is.
Coherence.
Not less humanity. More room for human work
In HR, technology is quickly set in opposition to humanity.
As though more technology automatically means less humanity.
I see it differently.
What is human about an HR professional having to spend half a day comparing spreadsheets to work out which version is correct?
What is human about a manager having to prepare for a difficult conversation without context?
What is strategic about a CHRO having to have management questions reconstructed over several days before a conversation can take place?
No one should have to lose time on that.
If technology can bring information together, flag deviations and structure context, it frees up space.
For something technology finds much harder.
Listening.
Interpreting.
Doubting.
Understanding an exception.
Explaining a difficult decision.
Having a conversation when you do not know in advance how it will end.
That is why one of the guiding principles of Almuruna One is simple:
Data and AI signal. People decide.
Not because people are always better at calculating.
But because the consequences of a decision are ultimately borne by people and organisations.
Perhaps this is still my most important criterion
That is why, when I look at HR technology today, I ask less often how many functionalities a system has.
The number of AI features also tells me little on its own.
I prefer to ask a different question.
How much time does this technology give back to people that is currently lost to searching, checking and reconstructing?
And then:
what can they do with that time?
If the only answer is that we can process even more administration, then we have gained little.
If it means that HR can see earlier where attention is needed, that a manager goes into a conversation better prepared and that an executive team can make decisions based on a more coherent picture of the organisation, then technology becomes interesting.
Not because it replaces human work.
But because it finally allows us to lose less time on work that was never all that human to begin with.
About Almuruna and its founders