Compared to the average: the Location Quotient, explained simply
A number on its own tells you little. 2.7× the London average tells you a lot. Here is the formula behind 'Compared to the average' (the Location Quotient), worked through with cafés in London.
An area in London has 1.5 cafés per 1 000 residents. Is that a lot? You genuinely cannot tell. It depends entirely on what is normal for London - and that is the one thing a plain number never tells you.
Compared to the average fixes that with one division. It takes the area's rate, divides it by the city's rate, and hands you a multiple: 2.7× the London average. Now you know. That multiple has a name in the field - the Location Quotient - and it is probably the most useful formula on the map that almost nobody outside economic geography has heard of.
Compared to the averagethe field's term: Location Quotient
Cafés per 1 000 residents, compared to the London average. Red areas have more than their fair share of cafés; blue areas have fewer. The centre is a solid café district.
The idea, in one sentence
Does this area have more than its fair share? If cafés were spread across London exactly in proportion to where people live, every area would sit at 1×. Anything above 1× has more cafés than its residents alone would explain; anything below has fewer.
0.4× - a gap
Only 40% of its fair share. Plenty of people, not many cafés. Depending on what you are planning, that is either a warning or an opportunity.
1× - the fair share
Exactly the London average. Not a café district, not a café desert. Most of any city sits somewhere near here.
2.7× - a café district
Nearly three times the normal amount. Cafés cluster here for reasons beyond the residents - offices, footfall, a high street.
Switching it on
Every map MapBees can draw is a row in the Map type picker, at the top of the map. Each row names the formula twice - plain words, then the field's own term - and says which question it answers. Fair share is the one you want here.
The Map type picker. The formulas are grouped by the kind of legend they produce, so everything under 'Compared with' reads the same way: a diverging scale with a middle that means 'neither'.
Pick Fair share, choose a metric, and decide how to count it. You never set the comparison separately - choosing the map is choosing it.
Where to click
Map type
Fair share
Cafe
Count as: Per 1 000 residents
The panel is titled with the map you are on - Fair share - and its question. The badge reads 'Compared to the average · Location Quotient', the sentence spells out what is being drawn, and the coverage line says how many areas have an answer.The badge names the formula in both registers. Under it, two ways deeper: 'Show the maths' for the arithmetic, and 'Read the guide' - which opens this article.One dropdown is left, and it is the half the map type does not decide: whether the average is London's or that of an area you drew.
Counting per 1 000 residents matters. Comparing raw counts with the average would only tell you where the big areas are; comparing rates tells you where cafés are unusually common for the people who live there.
Reading the map
The legend is fixed around 1×, and that is deliberate. On most maps the middle colour is whatever the median happens to be; here the middle is always the fair share, so grey means the same thing in every city and for every metric.
The steps are multiples, the same in both directions: 1.1×, 1.5×, 2× and 3× the average on the red side, and the mirror of those (0.9×, 0.67×, 0.5×, 0.33×) on the blue side.
Hover any area and the card leads with the multiple, then gives the rate behind it. The rate is the fact; the multiple is what the fact means.
One area south of the river: 1.5 cafés per 1 000 residents, which is 2.7 times what London as a whole manages.
The maths, honestly
Two rates and one division. The numbers below are illustrative; the shape of the sum is exactly what the app runs.
Cafés in one London area, compared to the average
London's rateall cafés ÷ all residents × 1 000
0.55 per 1 000
This area's rateits cafés ÷ its residents × 1 000
1.5 per 1 000
Compared to the average
1.5 ÷ 0.55 = 2.7×
Read it as: this area has 2.7 times its fair share of cafés. A value of 1.0 would be exactly the London average.
'Show the maths' is one click under the badge. It names the method, states the division, admits the small-numbers adjustment and cites the data release.
One thing to keep in mind
A multiple is only as honest as the rate under it. An area with three residents and one café would show a wild rate, so MapBees pulls tiny bases toward the city's value before comparing - the “adjusted for small numbers” line you see on some areas. The per 1 000 residents post explains that adjustment.
Why not just rank the areas?
Because a rank throws away size. “Top 5% for cafés” sounds impressive, but it is true of an area with 41 cafés and an area with 40, and it tells you nothing about how far either is from normal. 2.7× the average is a size. It is something you can put in a sentence to a landlord, compare between two cities, and act on.
It also needs no ranking step at all: the number comes out already meaning something, which is why it is the comparison the gap analysis is built from as well.
Compared to the average = this area's rate ÷ the city's rate. That multiple is the Location Quotient.
1× is the fair share. Above it, more than its share; below it, fewer. The legend is pinned there on purpose.
Count per 1 000 residents first, so you are comparing how well people are served, not how big the area is.
Grey is average, red is more, blue is fewer - and the steps are the same multiples in both directions.
Hover for the multiple and the rate behind it; open 'Show the maths' for the method and the source.
Quick questions
What is a Location Quotient?
It is a local rate divided by the city-wide rate. 1.0 means an area has exactly its fair share of something; 2.6 means it has 2.6 times the city average; 0.4 means 40% of its fair share. In MapBees it is the 'Compared to the average' option.
How do I make a location quotient map without GIS software?
Open the Map type picker in MapBees, choose 'Fair share', pick a metric and count it per 1 000 residents. The map colours every area by how many times the city average it is, with 1× pinned in the middle.
What do the blue and red areas mean?
Grey is about average (the fair share). Red is more than its fair share, deepening at 1.1×, 1.5×, 2× and 3× the average. Blue is fewer than its fair share, at the same steps in the other direction.
Why is a location quotient better than a ranking?
A rank says an area is in the top 5%; a location quotient says it has 2.6 times the normal amount. The second is a size you can act on, and it needs no ranking step at all.
Can I compare with an area I drew instead of the whole city?
Yes. Draw an area, then set 'Average of' to 'Your drawn area'. Every value is then compared with that area's average rather than London's.
See it on a real map
The best way to understand the score is to play with it. The full app is on a free tier, with no sales call.
Builds MapBees's location-intelligence pipeline end to end — census and Overture Maps ingestion, H3 hex scoring, and the map interface — and writes the methodology behind every number on the site.
