Justify Your Data Needs

Martyn Rhisiart Jones

Oxford University, Sunday 11th January 2026

Should All Business Data Requirements Be Justified in Business Terms?

A Pseudo-Debate

Motion: All business data requirements must be justified in business terms. Potential business utility should be a deciding factor in whether they are fulfilled.

For the Motion: Sir Afilonius Rex
Against the Motion: Martyn Rhisiart Jones

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Round One – Opening Statements

Sir Afilonius Rex (For the Motion)

Ladies and gentlemen, businesses today drown in data yet starve for insight. We collect, store, secure, and process mountains of information, often without stopping to ask the most basic question: Why? My position is simple. If a data requirement cannot be justified in clear business terms, then it should not be pursued.

Data is not free. It carries costs: technical infrastructure, human effort, compliance risk, cybersecurity exposure, and opportunity cost. Every new data requirement competes for finite resources. Therefore, potential business utility must be the deciding factor. Data should either reduce risk, increase revenue, improve efficiency, or support strategic decisions. If it does none of these, it is not an asset, it is clutter.

Furthermore, unjustified data collection creates danger. The more you collect, the more you must protect. Unnecessary data expands your attack surface, increases regulatory exposure, and complicates governance. Businesses that cannot articulate why they collect specific data will struggle to defend themselves legally, ethically, and operationally.

In short, purposeful data is powerful. Aimless data is a liability. Business justification is not bureaucracy, it is discipline.

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Martyn Rhisiart Jones (Against the Motion)

Sir Afilonius Rex makes an orderly argument, but business is not built solely on what can be immediately justified. Many of the most valuable datasets in modern organisations were not originally collected for a clear, measurable “business use case.” They became valuable later, sometimes years later, when new technologies, regulations, or market opportunities emerged.

Requiring every data requirement to pass a strict business-utility test risks strangling innovation. Discovery depends on curiosity, exploration, and sometimes collecting information before we know exactly how it will be used. The future is not always predictable, and insisting on formal justification for all data discourages experimentation.

Moreover, not all value is easily quantified. Cultural insight, long-term trend analysis, and training AI systems are beneficial. Improving organisational learning is also advantageous. These benefits are real but not always reducible to immediate business metrics. A narrow definition of “business utility” may bias organisations toward short-term thinking and away from long-term resilience and innovation.

Data should be governed, yes, but not constrained so tightly that it prevents growth, creativity, and future competitiveness.

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Round Two – Rebuttals

Sir Afilonius Rex Responds

Mr Jones raises the familiar banner of innovation and future possibility, but he conflates justification with certainty. I am not arguing that every dataset must have guaranteed returns. Instead, it must have a plausible, articulated business rationale.

“Maybe useful someday” is not a strategy; it is a storage policy. Organisations can absolutely justify exploratory or experimental data collection. They must define their purpose: research, innovation, product development, AI training, or regulatory preparedness. These are legitimate business reasons.

What I oppose is unmanaged, undocumented, unowned data accumulation. That kind of data does not foster innovation, it creates technical debt. The companies that truly innovate do so intentionally, not accidentally. They fund research programs, define learning objectives, and allocate budgets accordingly. That is justification in action.

Future value does not excuse present irresponsibility.

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Martyn Rhisiart Jones Responds

Sir Afilonius assumes that all future-oriented value can be cleanly framed as a business case. In reality, many breakthrough insights arise from patterns discovered in data that no one originally intended to analyse. Retrofitting “justifications” after the fact may be possible. However, demanding them in advance can deter data collection that feels uncertain, experimental, or exploratory.

There is also a human factor: requiring formal business rationales for every dataset increases administrative friction. Teams may stop collecting potentially valuable data simply because the paperwork is too heavy or the benefits too speculative.

Yes, data should be governed and protected, but governance must leave room for curiosity. Not all business value announces itself in advance.

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Conclusion

This debate exposes a real tension in modern organisations:

• Sir Afilonius Rex champions discipline, accountability, and risk control, arguing that data without justification is a liability.
• Martyn Rhisiart Jones defends flexibility, experimentation, and future-oriented discovery, warning that strict justification may suppress innovation.

The core question is not whether data should be governed, it must be. Instead, it asks whether governance should require formal business justification for all data. Alternatively, should it allow for merely responsible stewardship with room for uncertainty?

The answer may define how organisations balance safety and innovation in the data-driven age.

Many thanks for reading.

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