What does it cost to leave forestry data on paper?

The cost of paper forestry records comes in three layers, and the one usually quoted is the smallest. The first is handling: keying, filing, chasing and approving each document by hand. The second is exceptions: tickets, settlements and invoices that do not match, found weeks later because nobody could compare them sooner. The third is the questions never asked. Records on paper are rarely read together, so the patterns in them stay invisible. In our judgement that third cost is the largest, though no benchmark measures it.

What the usual answer says

The case for digital tickets is usually made on handling time. A forestry ticketing vendor promises to "Reduce admin time by 50%+. Reduce field operations time by ~25%. Eliminate ticket errors." A forest planning software company's blog, the top result for this question, argues that "paper tickets don't just slow things down, they remove your ability to prove what actually happened." The ticketing figures are the vendor's own, and neither page gives a figure a reader could check.

Handling time matters, and it is the easiest of the three costs to measure. It is also the easiest to overstate as the whole case.

The measurable layer

A usable public benchmark for handling cost comes from accounts payable, which processes the same kind of paper a forestry office handles: invoices, settlements, statements. Ardent Partners' 2025 metrics report, sponsored by the e-invoicing company Pagero and based on 212 survey responses, found that "The average AP organization spends $9.40 to process a single invoice," all costs included. The average invoice took 9.2 days to process. The report also gives $2.78 for its best-performing fifth and $12.88 for everyone else. Those figures don't reconcile with the $9.40 average, which is the safer number to use.

The survey spans more than 24 industries. Its smallest band is companies under $250 million in revenue, 16% of the sample, which is still far larger than most forestry offices, so the per-document costs may not scale down. The best performers are also chosen by cost and speed, not by whether they have left paper. So the gap between the segments is an upper bound on what better processing is worth, not a measure of paper. The method still carries over: document count, times a cost per document, is a first estimate of the handling layer.

The exceptions layer

The same report found that 14% of invoices raised exceptions in 2024, flagged for "coding errors, missing information, approval bottlenecks, lack of purchase order data, etc." On paper, an exception is found only when someone compares two documents. Once both records are data, the comparison can run on every load as it arrives, rather than when someone has time.

Our reasoning is that the cost of an exception grows with the time it takes to find, because a repeated error is repeated on every record until it is caught. The error itself has nothing to do with paper. The delay before anyone sees it does.

The layer nobody sees

The third cost is the analysis that never happens. A filing cabinet of contracts, tickets and statements holds the answers to questions about volume, rate and yield, but nobody reads a thousand documents to ask them.

From Quarri's own work with a timberland manager: 140+ timber sale documents were read with every scanned page recovered, and the owner's own ledger turned out to be under-counting volume on some properties. No handling benchmark would have priced that.

How to estimate it for your operation

Start with the documents that carry money: contracts, trip tickets, scale slips, settlements. Estimate the handling cost from their volume and the benchmark. Estimate the exceptions from the corrections booked last year. Then take one set of paper records, a single year of one contract type, and have it read and compared with the ledger. What that comparison finds is the first real measure of the third cost.

When it doesn't apply

Many of the documents that carry money may already be digital, where scale systems store weights and mills settle electronically. There, the cost sits less in paper than in digital records that aren't joined to each other, and the same comparison applies to them. Records that nobody will ever need to query, such as historical correspondence, cost little to leave on paper. A small operation with a handful of contracts a year may find the whole comparison can be done by one careful person. And digitising only to file, as scanned images nobody reads, removes some handling cost and none of the third.

Quarri for forest management is built around how a forest operation runs, from the cruise to the settled account.

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.