Despite Singapore’s ambitions to become a leading data-driven economy, a new survey has found that fewer than one in four employees feel confident in their ability to read, interpret and act on data. The finding, from a joint study by SAS Institute and the Singapore Economic Development Board, points to a data literacy gap that is quietly undermining organisations’ digital transformation investments.

The survey of 1,800 employees across financial services, healthcare, manufacturing and the public sector found that while 78% of respondents agreed that data was important to their work, only 24% said they felt “confident or very confident” working with data tools, interpreting data outputs or using data to inform decisions. Among non-technical roles, the confidence level dropped to just 16%.

The HR dimension

For HR leaders, data literacy is both an internal challenge and a strategic priority. Internally, as HR increasingly relies on people analytics, workforce planning tools and AI-assisted talent management systems, HR professionals themselves must develop data fluency. Externally, HR is the function most responsible for building organisation-wide data capability through learning and development programmes.

“This is not just a technology problem — it’s a learning and culture problem,” said one Chief People Officer. “We’ve invested in the tools. We’ve done the data governance. But if people don’t feel equipped to use the data, we’ve achieved very little.”

Root causes

The study identified several reasons for the data confidence gap. Many employees had received no formal training in data tools since joining the workforce. Others had attended courses but found them disconnected from their day-to-day work context. A significant proportion cited a cultural barrier — a fear of being “wrong” with data, or a sense that data analysis was a specialist’s job, not theirs.

What works

Organisations with higher data literacy scores shared common approaches. They embedded data skills training into specific role contexts rather than offering generic data literacy modules. They created “data champions” in non-technical business units who could translate data concepts into language relevant to their colleagues. And their senior leaders modelled data-driven decision-making visibly and consistently, normalising the use of data across the organisation.