How to Show Decisions that Consider Data are Less Risky

“Without data, you’re just another person with an opinion.” — W. Edwards Deming, pioneer of statistical quality control

Engineers are often baffled by management decisions. They wonder what more they could have done to convince management to make different decisions.

Here are three practical ways in which good public speaking skills can help engineers convince management that decisions without data are a gamble with bad odds.

Frame Risk in Terms of Outcomes

Engineers translate raw data into outcomes that matter to management: cost overruns, schedule slips, safety exposure, and reputational damage.

By clearly stating, “Here’s what happens if this assumption is wrong,” speakers turn data into a risk-management narrative.

Management may ignore spreadsheets, but they rarely ignore quantified downside.

This reframing shifts the conversation from opinion vs. opinion to risk vs. mitigation.

As with all audiences, including management, you need to understand what drives their decisions. You need to take what drives you and translate it into its impact on management’s agenda.

For example, “Our test data shows a 2.3% failure rate under peak load. Mean time to failure drops from 18 months to 7 months if traffic grows as forecast.” or “At current growth rates, this failure rate gives us roughly a 1-in-4 chance of a customer-visible outage this year.

Why does this work? It does because the engineer didn’t argue correctness. They translated data into probabilities, financial impacts, business risks, and clear trade-offs.

Management doesn’t approve the data. They approve risk reduction with upside.

One way to convince management that decisions made without data are highly risky is to frame risk in terms of outcomes.

Another is to use visual comparisons to expose assumptions.

Use Visual Comparisons to Expose Assumptions

Effective speakers surface hidden assumptions by contrasting data-backed scenarios with assumption-based ones.

Side-by-side visuals—trend lines, ranges, or probability bands—make uncertainty visible and lead to its consequences.

When management sees how wide the error bars are without data, intuition suddenly looks expensive.

Public speaking skills matter here: the engineer must slow down, explain the visual, and explicitly link uncertainty to business exposure (the risk of losing revenue).

Management does not want to lose revenue. Your ability to quantify risk in terms of potential revenue loss is crucial to convincing management to step back and reassess the consequences of their decisions.

Remember, when you propose your solution to an engineering challenge, you must speak in terms of management’s agenda and language.

You will likely need to convince non-technical management. They may be approaching a decision from a completely different perspective than you. Your job is to understand their perspective and appeal to it.

Two ways to convince management that decisions made without data are highly risky are to frame risk in terms of outcomes, not just numbers, and to use visual comparisons to expose assumptions.

A third way is to tell short stories, not long data lectures.

Tell Short Stories, Not Long Data Lectures

Management will get lost in long lectures about data. It is essential to draw conclusions from the data and assess its impact on company revenue.

Engineers who persuade well use brief, concrete stories: “Last time we skipped validation, defect rates tripled and recovery cost six figures.”

These stories ground abstract risk in lived experience, reinforcing why data exists in the first place: to prevent repeat failures.

Delivered clearly and confidently, these narratives give management a memory, not just a metric.

Stories about the consequences of the last time the same decision was made are facts, not fiction. It is important to often tell the same stories about previous decisions.

It reminds management why, under the same circumstances, decisions should be different this time.

Three ways to convince management that decisions made without data are highly risky are to (1) frame risk in terms of outcomes, (2) use visual comparisons to expose assumptions, and (3) tell short stories, not long data lectures.

Engineers don’t need to out-argue management. They need to calmly show that data isn’t bureaucracy—it’s insurance —and that skipping it is betting the company with borrowed dice.

Call to Action

• Translate raw data into consequences management care about: cost overruns, schedule slips, safety exposure, and reputational damage

• Surface hidden assumptions by contrasting data-backed scenarios with assumption-based ones

• Draw conclusions from the data and assess its impact on company revenue.

“In God we trust. Everyone else bring data.” — Michael Bloomberg, former Mayor of New York City; founder of Bloomberg LP

References

• Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, Random House, 2007. (On how ignoring data and uncertainty leads to catastrophic decision-making)

• Douglas W. Hubbard, How to Measure Anything: Finding the Value of Intangibles in Business, Wiley, 2010. (Demonstrates that decisions made without measurement are unnecessarily risky)

• Daniel Kahneman, Thinking, Fast and Slow, Farrar, Straus and Giroux, 2011.Thinking, Fast and Slow (Explains why intuition alone consistently fails in complex, high-risk decisions)

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