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4 Top Prescriptive Analytics Examples in Wood Products Manufacturing

October 31, 2019 | By Cheryl Hammer

For forestry and wood products manufacturers, future uncertainties such as natural disasters and economics make accurate planning an ongoing challenge. Take, for example, the crisis in U.S. hardwood lumber exports to China, which have dropped 40% this year as a result of the ongoing trade wars.

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.

Application #1: Product Mix and Bid Support

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:

  • Thickness and type of log
  • Value of the log
  • What price or range of log pricing is feasible?
  • Log allocation, (e.g. optimal cuts, sorting, and mill distribution)
  • Harvest plans, like which species and what to sell

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.

Application #2: Production Planning

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.

Application #3: Capacity Planning

wood_productsCapacity planning, another supply chain optimization software application, enables companies to prioritize their resources based on marginal economic impact. Companies can then make medium- to long-term decisions that establish a firm’s overall level of resources. Resources primarily include production and labor but ideally should also include inventory and storage.

Making capacity decisions affect a company’s ability to compete via:

  • Product availability/customer service levels
  • Production lead times
  • Customer responsiveness
  • Operating costs

The advantages are significant with the ability to consider trade-offs between capacity, inventory build-ahead, service level, and financial performance.

Application #4: Production Allocation           

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.

     Example: Wood Products Manufacturer Gains $5 Million in Annual Value

A wood products manufacturer with hundreds of SKUs                

With River Logic, the company now optimizes monthly planning, considering variables, such as:

  • Shift schedules
  • Mill production schedules
  • Freight
  • Production cost forecasts, and more

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:

  • Volumes
  • Throughput/hours
  • Cross-shipping costs
  • Production costs
  • Raw material costs
  • Downgrades

Extending the Application for More Strategic Use

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:

  • Capacity expansion and improvement
  • CAPEX
  • Demand manipulation for profit optimization
  • Understanding National Pollutant Inventory (NPI) impacts

The overall impact? With River Logic, the company can:

  • Identify the best shipping destinations from each plant so that demand is met in an optimal way
  • See recommended SKU substitutions as needed, such as substituting higher-grade products from another plant to meet demand, which prevents losing profitability overall
  • Limit delivery methods, such as customer pick-up only, for lower-margin products in order to decrease the types of product orders that deplete capacity

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:

  • How to transport products?
  • What's the optimal location for production lines and product storage warehousing?
  • What are the best methods for delivering goods to customers?

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.

Closing Remarks

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. 

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