Many people overcomplicate analytics.

You've got four types of questions you can ask with data. That's it. Four.

What happened?

This is descriptive analytics. How much did we sell? How many people cancelled? What's the revenue for Q3?

People think this is boring because it feels basic. But you can't skip it. If you don't know what actually happened, you're guessing at everything else.

The work is simple: figure out your question, grab the data you need, analyze it, show the answer. Job done.

Why did it happen?

Now you're doing diagnostic analytics. Cancellations went up in March, okay, but why?

You start connecting dots. Customer comments around that time. Pricing changes. Which demographics were affected. What else was going on.

This is where you stop reporting and start investigating. You're looking for the anomalies, the patterns, the relationships that explain what you found in step one.

What will happen?

Predictive analytics. Can we forecast next quarter's sales? Which customers are about to churn?

This isn't fortune-telling. You're working with probabilities based on what you already know. Sometimes you're right, sometimes you're not, but at least you're planning with information instead of hope.

What should we do about it?

Prescriptive analytics. This is where you take everything you've learned and turn it into action.

You know what happened, why it happened, what's likely to happen next. Now what? Should you adjust pricing? Change your marketing approach? Allocate resources differently?

This uses optimization, simulation, decision analysis to recommend specific actions. Not just "sales will probably drop," but "if you want to prevent that drop, here are your three best options and the trade-offs for each."

Many organizations never arrive here because they're too busy mired in the first three stages. But this is where data actually becomes useful beyond just knowing stuff.

The actual insight

Teams either get stuck running endless descriptive reports or they try to build predictions without understanding the basics first.

The question isn't which type of analytics is better. It's which question are you actually trying to answer right now.

Figure that out first, then pick your approach.

Everything else is just noise.