One of the most common challenges I encounter when teaching people the 7 most common story angles in data journalism is confusion between variation and ranking stories. It all comes down to the difference between process and product.

That’s because both types of story involve ranking as a piece of data analysis.

We might rank the number of specialist teachers in the country’s schools, for example, in order to tell either of the following stories:

• “There are more specialist science teachers than those in any other subject, new data reveals”
• “New data reveals stark differences in the number of specialists teaching each subject in secondary schools

The first story reveals which subject has the most teachers — it is a ranking angle because it ranks teachers by subject.

The second story reveals the simple fact that variation exists, without focusing on any particular subject.

Here are some more examples (taken from the original post), with ranking angles shown on the left, and variation angles on the right. The linked angles are the stories that were published; the unlinked story angles show how an alternative angle might have been chosen for the same data.

Ranking	Variation
The part of Birmingham in top 10 UK areas worst-hit by Universal Credit advances	Welfare claimants hit by ‘postcode lottery’ of Universal Credit deductions
Construction is third most dangerous UK industry	Wide variation revealed in industry health and safety figures
The most common crimes in Sandwell – and where you’re most likely to be a victim	Some areas of Sandwell seeing twice as many crimes as others
White defendants mislabeled as low risk more often than black defendants	There’s software used across the country to predict future criminals. And it’s biased against blacks.
Milton Keynes tops the list for electric vehicle charging points	A “patchy” network of charging points is discouraging UK drivers from embracing electric cars, analysis suggests

Variation works best when fairness is expected or assumed

On the whole, ranking angles are a safer bet when it comes to data. This is because revealing who is top or bottom on a particular measure (or where your audience’s area ranks) is typically both more likely to be surprising, and more concrete.

A variation story only works if its existence is itself more important and surprising that the particular winners and losers.

So, for example, we wouldn’t tell a story revealing wide variation in how many goals teams score: we expect some teams to be better than others. But if we found wide variation in how many penalties referees award, that might be newsworthy. And it might be more important than which particular referees top the rankings on that metric.

Likewise, we wouldn’t ‘reveal’ that some people earn more than others. But a story on people earning more than others for doing the same job would be more unexpected (and ranking the top earners would not be nearly as interesting).