Case Study - Better Information. Better Return. (ForestCo)

ForestCo maximizes return from the forest with better inventory information and improved visibility and predictability of their business

 

Background

 

The role of the forest manager is evolving quickly in Canada. Ten years ago, a forest manager was employed by a large forest products company and was tasked with the environmental health of the forest and the economic health of the corporation. In today’s environment, the forest manager now reports to a board of directors and has many masters. The manager is now looking to create economic benefit for a large mix of business interests, from value-added remanufacturerers, to integrated base-producers of pulp and biofibre. The forest contains many products that have many potential destinations, and unlocking the the value of those products is a very complex problem that requires more information, and more analysis than traditional approaches. The managers at ForestCo, a large co-operative forest management company with several business partners, embarked on a project to improve the knowledge they had about their timber resource, and improve their ability to manage the resource for their clients.

 

 

 

The Problem

 

ForestCo manages a crown forest and currently sells fibre to several forest product facilities within the woodshed, each with their own specific log requirements. ForestCo is a co-operative company with shareholders representing the forest product mills that receive logs from the forest. The shareholders and the managers at ForestCo wanted to be able to make decisions relating to the logs available in the forest, but knew that their traditional forest cover inventory was limited in its scope and accuracy.  The existing inventory provided only model-based estimates of merchantable volume, and was accurate only at a very broad level.

 

 

The Solution

 

Improving the quality of inventory information in the forest is key to improving the quality of decisions that can be made. Getting the appropriate log mix to the correct mill, timed to meet demands of the marketplace requires data and knowledge beyond the traditional forest cover inventory.

To solve this problem, ForestCo decided to:

• Determine the population of interest over which business decisions will be made (this was the next 5 years of harvest allocations).

• Build a ground sampling program to achieve a ± 15% sampling error (at 95% Confidence Interval) of net merchantable conifer volume for each harvest block in the allocation.

• Conduct the ground sample, including electronic data capture of log grades, sizes, and net volume.

• Compile the log inventory from the field data using localized tree taper functions.

• Collect all the background information on market log, biomass, chip, and pulp prices, harvest blocks, locations, haul distances, stumpage, operational and equipment costs.

• Analyse and model a quarterly harvest block schedule that considers net revenue using allocation planning software. This model can be re-run as required as the inputs shift with market changes (pricing, operations, fuel costs and equipment availability).

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