Using Data in Real Decisions

Ciaran Rooney

Technology and Cybersecurity Leader

Make better decisions with data by knowing when numbers should lead, when judgement should step in, and how risk, uncertainty, and role shape the right call. Learn to balance evidence with context for smarter, more confident outcomes.

Data Science

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Using Data in Real Decisions

3 mins 32 secs

Key learning objectives:

Distinguish between data-driven and data-informed decision-making
Understand how decision risk influences the weight data should carry
Recognise how different roles interact with and interpret data
Apply judgement to align data confidence with decision consequences

Overview:

Data does not determine decisions in isolation; its value depends on context, risk, and the role of the decision-maker. Effective use of data requires balancing evidence with judgement, particularly where outcomes are uncertain or difficult to reverse. By aligning confidence in data with the consequences of a decision, organisations can avoid misplaced certainty and make more robust, context-aware choices.

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Summary

What is the difference between data-driven and data-informed decisions?
Data-driven decisions rely primarily on quantitative evidence and are best suited to stable, well-understood environments where the cost of error is low.

Data-informed decisions combine data with judgement and context. This is essential when conditions are changing, uncertainty is high, or outcomes are difficult to reverse. Most strategic decisions fall into this category.

How should decision risk influence the use of data?

The weight given to data should reflect the risk of the decision. Low-impact or reversible decisions can be made using imperfect data, allowing for speed and iteration.

Higher-impact or irreversible decisions require stronger evidence and greater scrutiny. Data does not need to be perfect, but it must be appropriate for the level of risk involved.

How does the role of the decision-maker affect how data should be used?

Individual contributors should communicate what the data shows and where uncertainty remains.
Managers must recognise trade-offs that metrics may obscure across performance, risk, or customer impact.
Senior leaders should challenge assumptions and ensure confidence aligns with the strength of evidence.

What does it mean to use data well in real decisions?

Using data well means managing uncertainty rather than eliminating it. It involves recognising when data is sufficient, when it needs caveats, and when its limitations matter.

Effective decisions align confidence with consequences, ensuring data informs judgement rather than replacing it.

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Ciaran Rooney

Ciarán is the Chief Technology Officer at xUnlocked. He has over 20 years of experience in technology, cyber security and operations. Ciarán has held the role of CTO of several successful startups including; busuu, Skimlinks, and Swoon. He has also been a technical consultant, a startup mentor, a conference speaker, and the Chair of the PHP UK Conference.

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