What Corporate America Really Wants From Data Scientists

The best insights don't always win. The easiest stories often do.

Author

Glenda Carnate
June 05, 2026

Read time: 2.5 minutes

The common perception of a data scientist's role is that they conduct analytics and work to resolve challenging business issues. However, the greater difficulty often lies in persuading decision-makers that the findings will actually matter once they are discovered.

A data scientist spends extensive time determining the actual cause of declining sales. They work diligently on a thorough analysis, which produces clear data and an evident solution to the problem. What does management say?

"Can you summarise it in three slides?"

How can an analysis be meaningful rather than lost in time?

1. Insight alone is no good until the stakeholders comprehend it.

If stakeholders do not understand your report, it is irrelevant (no matter how valid your data).

2. The simple is more valuable than the complicated.

A simple, actionable chart is more useful than a sophisticated model that no one accepts.

3. Storytelling is part of doing business.

Data represents what occurred, while storytelling helps to understand its significance.

4. Decision makers look for clarity on what they need to decide.

Business leaders do not seek additional variables; they seek confidence in the information they wish to gather.

5. How data is presented can change how that information is received.

When insight is presented as a chart, it might go ignored; however, when presented as a PowerPoint, it would be recognized.

6. The best analysts translate, not just calculate.

The best employees in the organization use technical information (data) in conjunction with business (action).

💡Key Takeaway: 

Too often, the issue for organizations lies not in finding an answer but in packaging it so it survives the meeting process.

Data may provide the basis for the decision, but presentation is what ultimately determines which data will be heard by the recipients.

👉 LIKE this if you have ever seen an exceptional analysis get ignored.

👉 SUBSCRIBE now to receive insight on data, AI, business strategy, and the realities of business decision-making.

👉 Follow Glenda Carnate for practical examples of how to turn complex insights into impactful real-time decisions.

👉 COMMENT your best (or most annoying) "Can you put that in a PowerPoint?" experience in the comments.

👉 SHARE this with a data scientist, an analyst, or a leader who has discovered that finding the answer to the question is 50% of the challenge!

Reply

or to participate.