Turning Data into Better Decisions

Every organisation collects data, but not every organisation knows how to turn that data into meaningful action.

In this episode of EmpowerTech, Iyari Cevallos sits down with data and analytics leader Dr Ellen Manning to explore how organisations can move beyond reporting and use data to drive smarter decisions, stronger strategy, and better business outcomes.

With a background spanning data science, analytics leadership, and a PhD in astrophysics, Ellen shares practical insights into the role data plays in modern organisations, why data literacy matters, and how leaders can unlock more value from the information they already have.

The conversation dives into predictive analytics, AI, machine learning, data quality, bias, and strategy, while providing practical examples of how data-driven organisations can improve decision-making and create a competitive advantage.

Whether you're a business leader, analyst, technology professional, or simply curious about how data and AI shape decision-making, this episode offers an accessible introduction to the opportunities and challenges of modern data analytics.

Episode Highlights

01:02 – What a data and analytics leader actually does and why the role is often about bridging the gap between business and technology.

02:31 – Why many organisations still see data teams as reporting functions rather than strategic business partners.

05:03 – The difference between being "data-driven" and simply having access to dashboards and reports.

05:54 – A practical example of using data analytics to measure marketing effectiveness and guide investment decisions.

08:30 – What happens when data-driven recommendations conflict with intuition, experience, or organisational assumptions.

10:44 – Data literacy, data quality, and why both are essential for effective decision-making.

12:46 – The four types of analytics explained:

• Descriptive: What happened?

• Diagnostic: Why did it happen?

• Predictive: What is likely to happen?

• Prescriptive: What should we do about it?

15:25 – Understanding the relationship between traditional analytics, machine learning, and generative AI.

17:35 – What happens when organisations don't collect the right data and why measurement often starts long before reporting.

20:20 – Building a data strategy that aligns with business objectives and future decision-making needs.

22:14 – How increasing visibility of data helps leaders improve decision quality and organisational performance.

23:54 – Understanding bias in data and why "garbage in, garbage out" remains one of the most important principles in analytics.

24:26 – What synthetic data is and how organisations use it to improve models and reduce bias.

26:45 – Examples of external data sources, including government open data, census information, and property market datasets.

28:05 – Emerging opportunities with satellite and geospatial data and how organisations may use these insights in the future.

30:22 – Why centralised data and analytics functions often create stronger governance, consistency and outcomes.

31:46 – Treating data as a strategic business asset rather than an operational by-product.

32:55 – Practical advice for selecting the right AI and analytics tools for specific business problems.

34:16 – Data privacy, AI governance and why organisations need to think carefully about information shared with generative AI platforms.

35:56 – The importance of understanding where AI models get their training data and how poor-quality data can influence outcomes.

36:39 – Ellen's practical advice for experimenting with AI while remaining safe, informed and effective.

Key Takeaway

Data alone doesn't create value. The value comes from asking the right questions, collecting the right information, and using those insights to inform meaningful decisions.

As Ellen explains, organisations that treat data as a strategic asset, invest in data literacy, and build strong foundations for analytics are far better positioned to leverage emerging technologies such as AI and machine learning. Meanwhile, leaders who understand the strengths and limitations of data are more likely to make confident, informed decisions that drive long-term success.

One of the strongest messages from this conversation is that being data-driven isn't about having more reports. It's about creating a culture where information, evidence, and context help shape better outcomes.