Insights

5 min read • Analytics Strategy

The Frequency Fallacy: Why More Reports ≠ Better Decisions

We've all seen it: weekly reports that nobody reads, monthly decks that gather dust. The assumption that more frequent reporting leads to better insights is costing organizations time, money, and attention. The real question isn't "how often should we report?" — it's "how often do we actually make decisions?"

Key insight: Match data frequency to decision frequency. Some strategic assessments require quarterly evaluation periods to be meaningful. Stop sending data — start sending decisions.

More Insights

3 min read • Executive Reporting

Every Report Should Answer Three Questions

Before you build another dashboard, ask yourself: does it tell executives what changed, why it matters, and what action to take? If not, you're building a data graveyard.

The framework: What changed? Why does it matter? What should we do?

4 min read • Data Culture

Stop Sending Reports. Start Sending Decisions.

The shift from "here's your data" to "here's what the data is telling us to do" is the difference between analytics as overhead and analytics as strategic advantage.

The challenge: Push decisions, not data. If your report doesn't recommend action, it's just noise.

3 min read • Communication

The 90-Second Rule for Executive Insights

If your executive can't understand the key insight in 90 seconds, your analysis isn't done. Complexity is easy. Clarity is hard work.

Practice: Lead with the insight, not the methodology. Save the "how" for the appendix.

6 min read • Analytics Leadership

Signs Your Analytics Function Has Outgrown Its Infrastructure

Ad hoc requests piling up? Analysts stuck in report factories? Data definitions that change by department? These are symptoms of analytics maturity gaps — and they're fixable.

Watch for: Metric disputes, request backlogs, and "it depends on who you ask" answers.

4 min read • Career Advice

The Skill That Separates Good Analysts from Great Ones

It's not Python. It's not SQL. It's the ability to translate between technical teams and business stakeholders — to speak both languages fluently.

Develop this: Practice explaining your analysis to someone outside your function. If they glaze over, simplify.

5 min read • AI & Analytics

LLMs Won't Replace Analysts — But Analysts Using LLMs Will Replace Those Who Don't

The rise of AI tools like ChatGPT and Claude isn't a threat to analytics professionals — it's an amplifier. The analysts who learn to leverage these tools will outpace those who ignore them.

Start here: Use LLMs for code generation, documentation, and first-draft analysis. Keep human judgment for strategy.