Should a forest products company build its own data platform or buy one?

Buy the plumbing; almost everyone does. Storage, compute and connectors to common systems are commodities now. The real decision is about the layer on top: the timber meaning. That means units and conversions, random-length tallies, scale to tally, stand, sale and contract keys, and the rules that reconcile tickets to invoices and inventory to scale. That layer is where a data platform earns its value or fails. The question is who builds it, who owns it, and who will still understand it in three years. Quarri sells a platform, so it has an interest in this answer, and the evidence below points less firmly than vendors tend to say.

What the usual answer says

The pages that rank for this question are software directories and vendor pages, including forestry ERP vendors selling their own systems. None addresses build against buy directly. The general advice elsewhere is familiar: build if you have strong data engineering and unique needs, buy if you want speed and support. It skips the question of what the customisation is and who will keep it working.

What the evidence says

The most-discussed recent evidence comes from AI projects, not data platforms. MIT's Project NANDA, in its 2025 report on AI in business by Aditya Challapally and colleagues, reported that in its interviews "external partnerships with learning-capable, customized tools reached deployment ~67% of the time, compared to ~33% for internally built tools". The figures come from 52 organisational interviews and are self-reported. The tools were generative AI tools, and the comparison was with teams that "Build and maintain GenAI tools fully in-house". The authors add that "The correlation between external partnerships and success does not necessarily prove causation." Companies that buy may differ from companies that build in risk appetite and technical capacity.

Maintenance is a burden whichever way a company goes. Matillion, which sells data integration software, commissioned a survey of 307 data decision-makers in January 2025. It found 64% of organisations reported their data teams spent more than half their time on repetitive or manual tasks, and 70% rated pipeline management as somewhat or extremely complex. The sponsor has an interest in selling automation, and the survey doesn't separate teams that built from teams that bought. It shows that data work is mostly upkeep, which is the point that matters for the timber layer.

Where the value sits

For a timber business, the plumbing is the easy part. A cloud warehouse and connectors to an accounting package are available off the shelf. The hard part is making the data mean the right thing. That means converting board feet, pieces and lineal feet correctly, keeping a tally as a tally, and joining scale tickets to contracts and stands. It means computing overrun by period, and reconciling a haul-rate accrual against what was invoiced.

In our experience that knowledge lives in a few people. A platform built in-house encodes it in their code, and it walks out when they do. A platform bought from a general vendor arrives without it. A platform from a timber-specific vendor may arrive with some of it, and that claim can be tested.

There is also a case for keeping the timber layer in-house. It is the business's own definitions of overrun, recovery and cost, and a vendor that encodes them where the business can't see them creates a deeper lock-in than any infrastructure choice. The answer is to own the definitions, whoever writes the code.

How to decide

Ask who will maintain the timber layer, by name, and what happens when they leave; if the answer is one analyst, building is a key-person risk. Ask whether a vendor can show its timber logic on your own data within weeks, using your scale tickets, your tallies and your ledger, with a reconciliation that ties exactly. And whatever you choose, make sure the definitions, keys and rules are yours, in a form you can read and export.

When it doesn't apply

A company with a standing data team that already maintains timber-specific logic, and plans to keep it, may reasonably build and own the whole stack. Very small businesses may need neither, if their accounting package and a few well-kept spreadsheets answer their questions.

Quarri for finance and strategy teams is built for the people who close the month, explain the margin and answer the board.

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.