By industry
Every location on the same measures, including the ones nobody watches.
The head office sees the top ten sites and the bottom two. The middle, where most of the estate lives, is a monthly average.
Last reviewed 3 August 2026
The short answer
The problem is comparability, and it is expensive to maintain by hand.
Sites open, sites get acquired, systems differ by region, and a measure that means one thing at one location means something slightly different at another. Keeping every site genuinely comparable is continuous work, which is why in practice it is done once a year for the board and never again.
When the measurement layer is generated from the data rather than maintained by a person, comparability stops being a project. Every site is on the same definitions every day, including the sites too small to justify attention.
What it answers
Four things it answers on day one.
01
Which locations are behind, and why
Ranked on the same measures, with the computed drivers behind each one rather than a list of numbers to interpret.
02
What the bottom quartile is costing you
A one percent improvement in the sites nobody watches is usually easier than one percent in the sites everybody watches, and it is never modelled.
03
Where labor and inventory are misaligned
Staffing and stock against what actually sells, by site and by day, rather than against a plan set last quarter.
04
Which local practice is worth copying
When every site is comparable, the sites that are ahead become a playbook instead of an anecdote.
The questions that matter here
What operators ask us first.
These are the questions we hear in the first conversation, almost verbatim.
Why is this site down and the one next to it up
Same market, same format, different result. The answer is usually in a driver nobody was measuring, and it is usually fixable.
Which of my sites are quietly unprofitable
Contribution by site including allocated cost, rather than revenue by site.
Is discounting policy actually being followed
Realized price against list, by site and by product. Exceptions cluster, and the clusters are where the margin went.
Where is my inventory in the wrong place
Stock against demand by location rather than in aggregate, which is where the aggregate hides it.
Questions
Asked plainly.
What is the best analytics for a multi-location operator?
The requirement that matters is comparability across sites that are never quite identical, and it is the requirement most tools fail because keeping the definitions aligned is continuous manual work. SQOR.ai generates the measurement layer from each system's own data and reconciles every figure to the ledger, so all sites stay on the same definitions without anyone maintaining them, and the drivers behind an underperforming site are computed rather than guessed.
How do I know which locations are underperforming and why?
Rank every location on the same measures, then look at the computed drivers behind the ones that are behind. The why is the hard part: it usually sits in pricing, scheduling or procurement, which are functions the site manager does not control and which do not appear in site-level reporting.
Can it read different systems at different sites?
Yes, and that is the normal case rather than an edge case. Acquired sites run different systems, and SQOR reads each one read-only and conforms them to one model rather than asking any site to replatform.
How long to get all our sites live?
Two weeks to your own people testing on the first tranche of data, once read-only access is in place. Additional sources add time in proportion to how unusual they are, and where a brand-new connector is needed we ingest that data directly meanwhile so you are not waiting.
What does it cost across many locations?
Pricing is on query volume rather than seats or sites, so adding locations does not multiply the license. It is $48,960 a year for 25 users all-in with the warehouse included, plus a nominal set-up fee that covers the proof of concept, and it scales on questions asked rather than headcount.
Bring your worst-performing site.
We will show you the computed drivers behind it, from your own data, inside two weeks.