Why does sawmill accounting software rarely match the mill?

Often because log cost enters the books in one unit and lumber value leaves in another, and the conversion between them moves with the log mix. Where the cost system holds that conversion as a standard factor, inventory is valued at a cost that is right only in an average month, and margin by product shifts with the logs rather than with prices or performance. Where it costs each period on actuals, most of that goes away, but an average across log sources and products can still hide which logs pay. This applies to mills that buy logs on a board-foot log rule and sell lumber by tally.

What the usual answer says

The pages that rank for this question are mostly software directories, forum threads and vendor home pages. They list features and rarely explain the mismatch at all. Where an explanation appears, it is manual entry and disconnected systems, which integration fixes. Integration helps. A fully integrated system that converts scale to tally with a fixed factor will still disagree with the mill, only faster.

The conversion is not a constant

Ed Thomas and Neal Bennett, in a 2017 study in the Forest Products Journal, simulated sawing 32 scanned hardwood logs and compared the lumber with what common log rules predicted. They "saw underruns as low as -31.9 percent and overruns as high as 159.4 percent depending on log rule and log characteristics". They also note that "the log rules commonly in use today were all developed over 100 years ago", and that the more efficient a mill is, "the less the scaling methods reflect the actual volume recovery and the greater the overrun factor".

A state board that sets scaling practice puts the point plainly: "In the final analysis, scale is simply a standard for measuring log volume whose application is independent of lumber yield." It lists the factors that move overrun: "log sizes, taper of the logs, efficiency of milling machinery, and accuracy of the scaler".

What that does to the accounts

Most mills already track overrun as a production figure. The question is what the cost system does with it. If it uses a standard overrun to value lumber in inventory and cost what was sold, three things follow. Inventory carries a cost that is right only in an average month. Margin by product moves with the log mix. And the gap between standard and actual turns up as a variance at month end, spread across products by a rule.

If it costs each period on actuals, log cost consumed divided by lumber produced, the period's real overrun is in the unit cost. Our reading is that the problem then narrows to allocation. One average cost per thousand board feet across all log sources and products shows the mill's average, and hides which log sources and which products carry the margin.

The other gaps

Timing and definitions add to it. The mill counts production by shift, and the accounts recognise it at close. Grade changes at the trimmer or in the planer may never become a transaction. And reports can simply be wrong. From Quarri's own work with a sawmill: a join error was hiding about half of finished inventory from reporting. Before blaming the conversion, check that every record reaches the report.

How to reconcile them

Reconcile through the conversion rather than around it. For each period, total scale in and tally out by log source, species and product line, and compute the measured overrun. Put that beside whatever the cost system uses, a standard or a period average. Where the two differ, the variance has a name and an owner, and it can be tracked month to month. Where management reports need margin by product or log source, cost on the measured overrun for that source, so margin follows the logs that produced it.

When it doesn't apply

Mills that buy logs by weight or true cubic volume and cost consistently in that unit avoid the log-rule problem, though weight-to-tally conversion varies too, with moisture and species. Very small mills with one product and one log source may find a single factor good enough. And the 2017 figures come from simulated sawing of hardwood logs, so they show how wide the range can be, not what any one mill will see.

Quarri for sawmills is built around how a sawmill runs, from log intake to shipped order.

Quarri is an AI-native data platform for the timber supply chain. It connects buying, production, sales and inventory for forest management, sawmill, wood products and pulp, paper and packaging operators.