The Resolution Layer · Case Study in BriefEKOM
Farm & construction equipment.
A cold read of the new and used machine inventory of a multi-store equipment dealer group — where one listing is one physical machine, and a buyer decides on its hours, its condition and its price before anything else. One of a set of anonymized EKOM analyses — what surfaced, and where it leads.
Lead finding · machines whose own record cannot be true
A new tillage disk with 57,220 hours — first in the inventory's hours sort.
A current-year implement, flagged new, publishes a meter reading of 57220 Hours, and sorting the whole inventory by hours puts it ahead of every tractor and combine. Two large square balers read some 35,000 and 29,000 "hours" — the size of bale counts, with the secondary-meter field beside them empty. On 31 machines, all on order, the displayed reading and the stored hour value are different numbers: one tractor shows 900 hours on its page and 12 in the field a filter would read. The hour count is the number the price is negotiated on, and on these machines the record gives two.
Also surfaced
Priced above the former price
Six clearance machines — tractors, an excavator, a dozer — whose asking price exceeds the price they were marked down from, by up to some $37,000. Wherever both prices are read together, the markdown reads as a markup.
Widths in inches, labeled feet
A 96-foot snow blade, an 84-foot grader box, a 168-foot pusher: 33 blades whose inch widths sit under a label that says feet. A contractor filtering for eight feet does not find them.
Missing from the industry filter
71 machines carry no Agriculture or Construction value, clustered in six equipment types — applicators, spreaders, compact loaders, toolbars, harrows, levelers. Six type-level rules would cover 69 of them.
New machines carrying working hours
896 machines flagged new carry an hour reading, 14 of them over 1,000 hours. Demonstrators and rental returns are a policy question, not a defect — and the report holds it as one for the dealer.
How EKOM read it. The engine read the dealer group's own public equipment search cold — no file, no credentials, no integration — and re-read every machine named in the findings live six days later. It profiled what each field is for from how the inventory itself uses it, then held every machine against itself: the hours against the condition flag, the two hour fields against each other, the size against the model name, the asking price against the former price. Every extent is an analyst's recount of the full inventory, not the automated pass's own count.
From diagnosis to channel-ready. Most of the 13 findings read as five upstream mechanisms — one meter field for every kind of meter, two copies of the hour count kept apart, a size stored as a number with the unit chosen by type, an industry assigned by type with types missing from the map, and an identifier copied into the field beside it. Fixing the findings fixes the findings; fixing the mechanisms fixes every machine that has already passed through them and every one that will. Then the same intelligence holds the line at intake, so the next bale count filed as hours is caught the day it is listed.