Dashboards show metrics. Leaders make decisions.

Posted by Mike O'Brien on September 23, 2025 in Digital Qualifications, Education, Postcards from the digital frontier | Leave a comment

Why We Must Stop Rewarding Description in Marketing Education

Why does education matter? It’s not because students can memorise models or copy dashboards. It’s because we want them to make better decisions – the kind that drive businesses forward.

But here’s the mistake we’ve been making for too long: We reward description.

The comfort of description

Think about most marketing reports you’ve read – whether from students or even junior staff. They look impressive: charts, dashboards, screenshots from GA4. But then you get to the end and ask:

“So what?”

And too often, there isn’t an answer.

Description is safe. It’s the comfort zone. It shows activity, not impact. Employers know it. Students hide behind it. And unless we change how we teach, we reinforce it.

The power of interpretation

Interpretation is riskier – but it’s where value lives. Interpretation means saying:

• “This 20% drop in conversions isn’t just a number – it signals a shift in consumer behaviour we need to address.”
• “This channel looks efficient on paper, but the attribution model suggests hidden costs we must factor in.”
• “The AI recommends this campaign, but psychology tells us it could backfire.”

Interpretation connects the dots. It moves from data to decision. It has the courage to commit.

What we should reward

If we keep marking student work based on how well they report data, we’ll graduate analysts who can’t advise, strategists who can’t lead, and marketers who get outcompeted by AI dashboards.

Instead, we should reward:

1. Decisions – Did the student recommend a clear course of action?
2. Recommendations – Are those actions justified with evidence and insight?
3. Impact – Do they show awareness of business consequences (ROI, ethics, customer experience, sustainability)?

This is where human judgement beats machine automation every time.

What this looks like in teaching

• Case-based assessment: Give students messy, real-world data. Reward their decisions, not the prettiness of their charts.
• AI-augmented assignments: Let them use ChatGPT and/or Looker Studio. Then grade their ability to challenge, refine, and humanise the outputs.
• Boardroom simulations: Replace the “report” with a pitch to a CMO. Test clarity, confidence, and consequence.

The opportunity ahead

AI can already generate the perfect dashboard. That’s not the future of employability.
The future belongs to graduates who can take those dashboards and say:

• Here’s what this means.
• Here’s what we should do.
• Here’s the impact we can expect.

That’s the difference between description and interpretation. And that’s the difference between employability and leadership.

So, let’s stop rewarding students for repeating what AI already does better. Let’s start rewarding them for the one thing AI can’t do: making sense of it all in human terms.