Ask a panel mill what its recovery is and you will usually get one number. Ask which line, which shift and which log lot produced it, and the answer arrives three weeks later, if it arrives at all. That gap is not a reporting inconvenience. It is the reason the same losses recur: by the time the number is known, the logs have been consumed, the boards have been sold, and the only available conversation is about whose figure is wrong.
The root cause is almost always that the costing unit and the production unit are different things. Costing runs on a standard recovery percentage agreed at some point in the past; production runs on logs that vary by species, diameter, season and supplier. A standard is a reasonable way to value stock. It is a very poor way to find out that one press is running an old cycle time, or that a particular supplier’s logs have been quietly worse since the monsoon.
The fix is less dramatic than it sounds. Make the log lot the unit that carries cost, capture output against it at the peeler, the dryer and the press, and book glue, resin and power consumption to the same lot. Recovery then becomes an arithmetic result rather than an assumption, available per lot and per shift. Nothing here requires a new plant system — it requires the transactions you already post to agree on what they are describing.
Once recovery is measured per lot, two things follow quickly. Grade mix decisions can be taken against live margin rather than last month’s report, because you know what each grade actually costs to produce this week. And drift becomes detectable: a line whose recovery falls outside the band its own history sets can be flagged while the shift is still running, which is the only point at which anyone can do something about it.
The trap to avoid is buying analytics before fixing the unit of account. A dashboard built on a standard yield assumption will report that assumption back to you very attractively. Start with what the log lot costs, and the reporting becomes almost trivial.
