12 Months of Parts Tracking Data. What It Revealed.
Case study: remote underground mining operation | hydraulic workshop | 12-month reporting period.
434
zero points
Parts trending toward empty shelf
194
parts tracked
Single room, single terminal
33
at zero 7+ days
Extended stockouts recorded
346
HV road hours
Estimated retrieval travel exposure
WHAT THE DATA FOUND
Over 12 months, 434 Zero Points were recorded – moments where a part was trending toward an empty shelf and required replenishment to avoid running out.
That averages more than 8 Zero Points per week, across a single room, at a single terminal.
33 parts remained at zero stock for 7 or more consecutive days. Without LYIT, these patterns would have gone undetected – nobody reviews a year of emergency orders looking for trends. LYIT made it visible so minimum stock levels can now be adjusted.
WHAT LYIT MAKES POSSIBLE
The warehouse records what it dispatched to the remote store. What happens after that – what actually leaves the shelf at the point of use – goes untracked.
That’s the gap LYIT fills. The 12-month dataset identifies which parts repeatedly trended toward zero at shelf level and where small adjustments to warehouse minimum levels are likely to have the greatest stabilising effect.
That is information most sites do not have, and without it, the same gaps repeat year after year.
346 hrs
Additional Heavy Vehicle Road Exposure
173 events are estimated to have required a dedicated retrieval trip to the surface warehouse – 346 hours of additional HV road time.
On remote sites, HV/LV interaction is a recognised safety risk. Adjusting minimum stock levels for high-use parts reduces unnecessary trips and cuts exposure on those roads.
Model Your Site's Exposure
THE OPERATIONAL CONTEXT
434 Zero Points were recorded across the monitoring period. This is real shelf-level data captured because LYIT was tracking what was happening after the warehouse.
Not every low-stock event causes a breakdown delay. But a portion will align with active breakdown work and when they do, the cost of sourcing a missing part on a remote site is significant.
Most sites don’t have this data to work with. The model below uses your site’s figures to show what that exposure could look like – based on 434 real Zero Points recorded at a remote underground mining operation.
Adjust the sliders below to reflect your site’s conditions.
DELAY & DOWNTIME COST MODEL
“Before LYIT, it was daily checks, word of mouth and writing stock codes on a notepad. Now the trigger is all by email – quicker and easier to order. Parts management has improved 10-fold.
Without it you get less productivity and more complaints from the boys on the floor. Everybody needs to be on board to make this system work and the underground workshop teams have really bought into it.”
Warehouse minimum levels
Parts trending toward zero may need higher minimum stock levels at the warehouse. One year of LYIT data shows exactly which parts and where to adjust.
Restocking Frequency
High-use parts with frequent Zero Points may need more regular replenishment cycles. LYIT makes this pattern visible over time, without relying on memory, manual tracking, or a single person’s knowledge.
Extended Zero-Stock Parts
33 parts sat at zero for 7 or more consecutive days. LYIT made this visible for the first time, allowing minimum stock levels to be adjusted. Without that visibility, the pattern would have continued undetected.
See if LYIT fits your site
A short call to talk through your site and whether LYIT makes sense.