The cons of being too data driven: the importance of the human element
We live in a world where data drives nearly everything - from strategic decisions to day-to-day operations.
With AI increasingly taking the wheel, it’s easy to believe that the more data we have, the better our decisions will be.
However, in our pursuit of data-led decision-making, we risk forgetting something vital: the human element.
The context, emotion, and insight that no dataset can fully capture or reflect yet remain central to effective people strategies.
Using data in isolation without context, comparison, or broader analysis becomes a serious concern in environments such as the workplace where understanding people is key to success.
Interpreting the data meaningfully
Workforce data is incredibly powerful.
It can highlight patterns in engagement, reveal pay equity gaps, or flag performance issues.
However, data alone doesn’t explain the “why”.
Consider how employee data is often presented: by age, job level, pay range, or performance.
On a dashboard, people can be viewed as numbers in a row.
But behind every data set is a real person, with emotions, struggles, and stories that no algorithm can fully capture.
For example, if an employee’s performance suddenly drops or their sick leave spikes, the data will flag it, but it won’t explain why.
If decisions are made solely on that data, without a conversation or deeper understanding, the result might be an unfair dismissal or a missed opportunity to provide support.
A simple conversation could reveal a personal crisis, a health issue, or a broader systemic problem that needs to be addressed.
Likewise, data can flag pay gaps but can’t identify the root causes.
Perhaps there are inconsistencies in job classifications.
Maybe historical pay decisions were made, with less attention to equity, for long standing employees who are on outdated pay scales.
Relying only on data, we ignore the people and the individuals that sit behind it.
We increase the risk of making decisions that are ethically or strategically flawed - such as initiating a disciplinary process when a conversation might have revealed a need for support, or failing to fix past pay injustices through policy change and cultural shifts.
To avoid this, human oversight is critical.
People must interpret, question, and, when necessary, challenge the data.
Without asking why, we risk misinterpreting information and making decisions that are out of step with reality.
The risk of data bias
One of the perceived benefits of data is its objectivity – but is it truly objective?
A hidden flaw lies in the potential for bias to be embedded in your data without you even realising it.
Take AI-driven recruitment tools, for example.
These often rely on historical hiring data. If that data reflects unconscious bias, such as a tendency to hire one gender or background over another, the algorithm may not just replicate that bias but magnify it in future decisions.
Without human oversight, the system doesn’t correct bias; it reinforces it.
Another example of this is the use of unvetted salary benchmarking data.
Relying solely on outdated or non-contextual benchmarks can result in inaccurate compensation decisions that misrepresent the market and entrench inequality.
If the data powering your models isn’t current or robust, it risks perpetuating outdated pay practices.
For HR leaders, this means potential setbacks in attracting and retaining talent, as well as falling short on pay equity and fairness goals.
That’s why human oversight is essential.
Data-driven decisions must be grounded in real-world understanding to support fair and inclusive strategies.
Left unchecked, data can lead to decisions that are out of touch, incorrect - and potentially carry legal or reputational risks.
Without people to question, interpret, and validate the data, you risk repeating the very issues you're trying to solve.
Lead with insight
Data is an invaluable asset to underpin decision making. It helps identify trends, highlight issues, and measure success.
But it is a tool - not a replacement for human judgment.
Yes, be informed by data - not driven to take decisions based solely on it.
People will have insights that data will not, so it’s important to ask questions and leave space to make decisions based on understanding and knowledge.
Our goal should always be to humanise data.
By combining robust data and analytics with curiosity, empathy, and experience, you can deliver strategies that are not only data-informed, but truly people-centred.
It’s this balance, between evidence and empathy, that will drive smarter decisions and meaningful outcomes for your organisation.
Supplied by REBA Associate Member, Turning Point
Our data and insight helps organisations build the best reward strategy for their business and people.
