Ipsos Data Council Report
Data literacy and culture How skills gaps and cynicism prevent data-driven decisions
Ipsos Data Council Report
Data literacy and culture How skills gaps and cynicism prevent data-driven decisions
Ipsos Data Council Report
Data literacy and culture How skills gaps and cynicism prevent data-driven decisions
Context
Building a data-driven culture takes more than just splashing out on the latest tools and technologies – it’s about making sure people have the skills and mindset to embrace data as part of their daily work. And right now, that’s easier said than done. It’s not just about being good at your job anymore – it’s about being able to make sense of data, spot trends, and turn numbers into meaningful actions. And then there’s the technology itself: from dashboards to AI-powered tools, the sheer variety can feel overwhelming for people used to more traditional approaches.
People don’t just need to work with data – they need to figure out what matters, what doesn’t, and what they can trust. That’s a big leap for many, especially for those who aren’t used to thinking analytically. The workplace has evolved almost beyond recognition in some sectors and bridging the gap between where we are and where we need to be will spell the difference between those who thrive and those who fail.
Scroll down to read how Ipsos Data Labs have solved this type of challenge for clients before. View Impact Story Facilitating cultural transformation for a unified decision-making framework
Key challenges from the Data Council
Our council members shared that while there is a strong desire to build a data-literate workforce, many organisations struggle to provide the necessary training or incentives for employees to improve their skills. As a result, data tools are often underutilised by employees who would benefit the most from them. In many cases, this underuse stems from a lack of proper training, while in others, employees simply aren’t motivated to engage with the tools without clear incentives or leadership support.
4 in 10 of our interviewees mentioned that some employees have the confidence and skills to use data, but a significant minority still do not. And when it comes to training, the situation is concerning – around 4 in 10 described their organisation's data and analytics training as poor.
The problem is further compounded by the lack of clear policies or standards around data use. 7 in 10 said there are no clear standards or policies that specify when and where data should be used in decision-making. This lack of structure leaves employees unsure about how to integrate data into their day-to-day work. One interviewee explained, “Some people have the confidence to ask for data, interpret it, and make decisions, and some people don’t. There’s a bit of a difference – people are on different maturity levels in terms of their data understanding.” Senior Digital Product Manager
Another pointed out, “If you are not data literate and if you are not using insights to explain your business or your function, then you don’t stay very long.” Strategy, Operations & Supply Chain Director
Finally, there are concerns around self-service data tools. One of our members cautioned, “People interpret data in different ways. We need to be careful about self-serve because while we want people to be self-sufficient, we also don’t want them to draw the wrong conclusions.” Senior Digital Product Manager
This reflects the challenge of empowering employees with data tools while ensuring they use them responsibly, consistently and accurately.
People don’t just need to work with data – they need to figure out what matters, what doesn’t, and what they can trust.
Source: Ipsos Data Council,Oct 2024-Jan 2025 Base: 28 Ipsos Data Council members
“Some people have the confidence to ask for data, interpret it, and make decisions, and some people don’t. There’s a bit of a difference – people are on different maturity levels in terms of their data understanding.” Senior Digital Product Manager
Ipsos Data Labs learnings
To foster a true data-driven culture, organisations must prioritise upskilling their workforce. But it’s not just about offering training sessions - it’s about making sure the process is something employees can deeply engage with.
People often feel overwhelmed by the idea of diving into data, so the goal should be to break down those barriers - simplifying the complexities, offering clear pathways to improvement, and, importantly, providing motivating incentives to make the effort worthwhile.
Leadership plays a pivotal role in making this shift a reality. When senior leaders actively engage with data, setting an example by making data-driven decisions, it creates a ripple effect for the entire organisation. But it’s important to remember that being truly data-driven doesn’t mean decisions always start and end with data. Rather, data enhances decisions, aids understanding of the context, but it doesn’t overshadow intuition, experience, or other important strategic factors.
One of the key aspects of this transformation is changing how people perceive data - from burden to enabler. And this is easier if there is access to high-quality data. So, picking the right tools is crucial – don’t force employees to use systems or data that aren’t relevant to their work. For example, it might be tempting to implement a solution that aids decision-making in order make operations more efficient, but for simple and objective decision-making, a solution that decides for you may be better.
To really reinforce this cultural shift, organisations might consider appointing data champions within teams. These individuals would act as the go-to resource for data questions, offer support to colleagues and help integrate data-driven practices into everyday workflows.
Ultimately, building a data-driven culture starts with leadership, but it needs to be reflected across the entire employee lifecycle – how organisations hire, onboard, train, and incentivise their people. Emphasising data democratisation ensures that everyone has access to the right data when they need it, helping to root a data-driven culture throughout the organisation, not just in small pockets.
When senior leaders actively engage with data, setting an example by making data-driven decisions, it creates a ripple effect for the entire organisation.
Source: Ipsos Data Council,Oct 2024-Jan 2025 Base: 28 Ipsos Data Council members
Key takeaways
Be thoughtful about what new tools you implement
Getting the right tools in place is absolutely key. You really do need to be improving things, not making life harder or outcomes worse.
Be the change you want to see
A data-driven culture can only be built when leadership prioritises data literacy, addresses concerns, incentivises adoption and provides the necessary training to close skill gaps.
Thought starters
What would you score your organisation out of ten for adoption of data as part of decision-making processes? What fears might lie behind any reluctance?
Which systems or processes are most complained about or disregarded?
What training or initiatives would most effectively close the skills gap in your organisation? How can leadership better incentivise data literacy and model adoption of data tools?
Discover how Ipsos Data Labs have solved this type of challenge before
Impact story Facilitating cultural transformation for a unified decision-making framework
The challenge
A global consumer tech company were facing challenges with each individual market operating in silos with their consumer business decision-making. They all had access to pockets of sales, marketing, digital and supply chain data, however there was no 'one source of truth' and no ability to benchmark performance and facilitate best practice. They needed to go from an in-market approach to a global approach, whilst ensuring senior leadership buy-in and driving cultural change.
Our solution
We collaborated with the client to implement a data solution that transitioned their focus from individual markets to an EMEA-wide strategy, eventually expanding to a global scale. This involved evaluating their existing data framework, integrating new tools and technologies, and developing a comprehensive platform that provided a unified resource for all markets. A critical aspect of the project was change management, which involved securing senior stakeholder buy-in and conducting platform training for their teams to encourage adoption.
