Using Commodity Analytics for Sales and Operations Planning of Metals

Metals and mining companies face mounting pressure to increase throughput and grow revenues. The operation and profitability of mining, smelting, treatment, warehousing, and transporting metals is greatly influenced by price volatility, freight, and energy costs. Miners, refiners, and smelters require metals software that enables the best decision making.

The Planning Landscape in the Metals Supply Chain

The use of analytics can enable metals companies to operate more efficiently in the areas of:

• supply planning
• demand planning
• sales and operations planning
• master planning
• production scheduling

Inputs and outputs to these planning functions include:

• smelting capacity
• warehouse capacity
• transport capacity and schedule
• tonnage production per day
• sales information
• customer information
• market data
• actual orders and inventory
• capacity utilization
• average inventory level
• production plans
• distribution plans
• sales orders
• confirmation dates

Complexity in Planning Functions

Planning can vary in complexity depending on the relationships between smelter and customer and the number of hubs involved in the supply chain. The level of complexity in planning varies based on several factors including:

• whether inventory planning is restricted to the smelter or is also done at hubs
• whether customers can be served by more than one hub

Some of the challenges inherent in the metals supply chain include:

• making optimal decisions based on large quantities of data
• limited ability to fulfill orders with short lead times
• additional business processes required at the hubs

Using analytics can provide these benefits:

• flexibility to change the plan late in the execution process when constraints change
• ability to fulfill orders with short lead time

Making Better Decisions in the Metals Supply Chain

The right analytics solutions will enable:

• short- and long-term planning
• "what if" scenarios
• efficient problem solving
• a clear ROI on the software

How can analytics enable metals companies to operate more efficiently in planning functions? For example, with analytics, metals companies can...

• estimate smelter capacity by conducting data mining on historical data
• forecast raw material availability and identify bottlenecks in the transportation schedule using predictive analytics
• predict sales volume by product type using time series forecasting
• balance forecasted supply, demand, and transportation using optimization techniques and running "what if" scenarios

For another use case example, see "Using Predictive Analytics Software to Enhance Throughput."

Eka's Commodity Analytics Cloud

Commodities markets are characterized by risk, volatility, and complexity, which is driving the need for advanced analytics to make better business decisions. Business users can no longer afford to wait days and weeks to understand market changes, analyze the alternatives, and make decisions. Every business user needs the power to analyze data the way they want.

Watch our free video on how to use analytics to make better supply chain decisions.

Eka's Commodity Analytics Cloud brings analytics to all business users. What makes Commodity Analytics Cloud unique is the combination of commodity specific intelligence with an infrastructure built to handle the huge volume of data typical in the commodities markets.