Now, imagine trying to account for the variables that will occur in the years ahead.
Industry pros know even the slightest change can cause raw materials to fall short of demand. Plans have to be in place for when these shortages occur, and profits cannot be sacrificed. Alternatively, softer pricing is a potential risk when conflicting events converge, like planting incentives and new innovations, weakening demand for one product type over another.
And what about changes outside the industry? Recent oil industry news about a possible $30 per barrel price could slow housing starts and capital spending projects. These events, which can happen quickly, make sophisticated solutions critical in dodging unforeseen impacts and keeping plans profitable and efficient.
So, what does it take to optimize wood industry operations?
We’ve picked four of prescriptive analytics’ best applications that have produced outstanding results for this vertically-integrated industry. These applications optimize from a business perspective rather than real-time decision-making in day-to-day supply chain operations. River Logic, for example, operates at the highest level of optimization, focusing on resource allocation, product mix, strategic decisions, and more — from tactical to strategic planning. With an all-inclusive perspective of the entire business, profits and inefficiencies in the company’s unique value chain are identified. Ultimately, it’s about optimizing across the enterprise.
Profits are found when you understand the granular details of an optimized product mix . This capability considers seasonality, logistics costs, raw material costs, and more, initiated with procurement metrics such as:
Each business has unique inefficiencies in the value chain. Optimizing across the business provides the best plan of action for knowing which tracks of trees to harvest for what customer mix. These insights are especially helpful as housing starts shift in makeup, catering to a broader spectrum of buyer demographics.
For companies that both harvest trees and manufacture wood products, routine production planning has been a staple in minimizing costs with real-time decision-making, as referenced earlier. However, the business perspective takes a holistic view, inclusive of other processes, such as bid support, customer mix, capacity constraints, demand forecasts, demand shaping, and more.
With constrained demand forecasts, what type of wood should go to which sawmill and for what purpose minimizes overall business costs instead of only reducing costs at the sawmill level.
Making capacity decisions affect a company’s ability to compete via:
The advantages are significant with the ability to consider trade-offs between capacity, inventory build-ahead, service level, and financial performance.
When it comes to integrating production allocation and distribution, River Logic can determine the most profitable short- and long-term strategies for demand fulfillment in a matter of minutes, delivering immediate value to the bottom-line. Below is an overview of how one customer uses this application as part of its integrated business planning approach.
A wood products manufacturer with hundreds of SKUs
With River Logic, the company now optimizes monthly planning, considering variables, such as:
The company runs scenarios gauging the impact on mills and inventories based on higher or lower demand and considers every decision on forward-looking financial, commercial and operational metrics and constraints. Executives are now able to come together on a regular basis to appropriately account for the following complexities within and across the 12+ U.S.-based manufacturing plants, and review:
The manufacturer also uses the application’s use to support an annual planning process that looks at profitability by mill, plant, product, customer, region and channel, to support the analysis of decisions around:
The overall impact? With River Logic, the company can:
This strategic approach operates like a supply chain network design since it determines the best mix of locations, logistics and production facilities for optimizing product manufactured and distribution, answering questions such as:
Other strategic uses of prescriptive analytics applications that get the best-prescribed courses of action for additional plant acquisitions include the best time to purchase and the return on investment for each.
In each use, substantial, financial benefits were gained for the immediate and continue to provide cross-enterprise optimization for ongoing financial gains.
Most solutions in the wood industry are dedicated point applications, making it impossible to view the impact of unit decisions on the entire business. A good example of this is the lack of product mix optimization, which requires advanced analytics for its ability to integrate data and computational power.
Prescriptive analytics is versatile in use, addressing risk mitigation, private-labeling and outsourcing, mergers and acquisitions, how to minimize taxes with profit maximization, and more.
For a decision support system that eliminates the ‘wait and see’ approach, prescriptive analytics provides numerous applications that optimize the business as a whole.