Profit Optimization helped an Oregon lumber producer to greatly improve their production planning process.  Optware Enterprise provided the insight for the company to optimize its mix of cutting patterns and product allocations at its two sawmills.  The mills cut a mix of Hemlock and Douglas-fir.

The Problem

The forestry staff is actively involved in buying logs across Oregon and Washington and even into Canada.  Various scaling and grade specifications are involved making the decision process more difficult.

The two mills use sawing optimization within the mill to improve recovery.  However, they still see the need for a more comprehensive tool to maximize overall profitability.  There are just too many trade-offs.

The vast majority of production is sold to traditional west coast markets including big box stores.

Planners formerly used spreadsheets to evaluate production alternatives.  Determining the mix of profiles and product requirements that will best satisfy market demand is a complicated process.  After the data entry, planners worked for weeks evaluating various combinations based on experience, instinct and calculations.  They never had enough time to look at more than a small fraction of the choices available.  Decision-makers were forced to settle for a reasonable alternative rather than seeking an optimum decision.

The Solution

Facing these challenges, management looked to profit optimization to improve the quality and timeliness of the decision process.  This technology uses mathematical tools to consider impacts of raw materials, product mix and production efficiencies on manufacturing schedules, product prices and market opportunities.  Forest products companies benefit from this technology because their supply chains are quite complex, from forest-to-mill-to-market.

The client company remains firmly committed to investing in data and data systems.   A core set of log tests at all sawmills were conducted early-on to establish recoveries and product mixes.  Portions of these tests were “refreshed” from time-to-time as mill capabilities changed, and selective tests conducted as needed to explore new cutting options, product line changes, or other ideas that look good on paper but need hard data to back them up. 

Optware Solutions worked with the client to use existing company data to build the business model.  The customized model describes the mill’s operations in considerable detail.  The model incorporates sawing options for each diameter-length sort.  It also includes raw materials options and prices, finished product options and prices, labor rates and other variable and fixed costs.  The client runs the model with limited constraints that reflect forecasted market demand.  The model’s solution optimizes mill profitability based on current prices.  Planners and sales staff then decide whether it really is possible to sell the optimum product mix.

There is a sound working relationship between the company’s annual budget/plan and the optimization model.  Much of the information developed for the budget, including hourly sawmill costs, operating hours, product volumes by major category, log volumes and prices, and product outsourcing volumes and prices are used as initial inputs to the model and for comparisons to model runs as the year unfolds.  As events occur during the year, the model is run to assess the broad-brush impacts and to evaluate alternatives. 

The model estimates the cash impacts of the alternatives, and provides a dynamic, and detailed picture of how each alternative affects operations than the budget is designed to do.  The budget, for it’s part, provides a baseline for measuring company results and ties into the company’s financial reporting system.  By sharing some data and by covering different levels of detail, the annual budget and the model together provide a better compass for managing operations than either one by itself.

The Results

This Oregon lumber business now has much greater insight into product mix and the impact on profitability.  This knowledge has lead to an improved procurement strategy, improved product allocations between plants and a significant increase in profitability!