Commodity price optimization for consumer products
What to make when, for whom and at what price?
How does your consumer products business respond to changes in commodity prices? Whether you’re producing grains, meat or produce, many factors can affect commodity pricing in a hyperconnected market—escalating feed or fertilizer costs, weather, oil prices, natural disasters and even geopolitics. In the past, processes assumed stable commodity prices, but this is no longer suited to today’s environment. Consumer products companies may find it more difficult than ever to determine optimal price, mix and supply plans. The commodity price optimization solution from IBM allows organizations to turn commodity market volatility into opportunity. It is designed for clients who want to maximize margins, improve account- or channel-level visibility, and proactively manage price fluctuations.
The parameters of smarter sales management
The commodity price optimization solution provides an instrumented approach by ingesting continuous real-time data from all the key sources—internal and external—that go into configuring the right deal with customers. Data is made available through an interconnected approach, using dashboards to provide integrated recommendations that incorporate market forecasts, production capacity conditions, underlying cost parameters and margin. Overall, commodity price optimization offers an intelligent solution with powerful mathematical models that enable consumer products companies to proactively optimize sales operations by balancing market, production and margin variables in the creation of the “right” deal with customers.
An analytics-based pricing engine
The commodity price optimization solution can enable consumer products companies to transform from a supply-chain model to a market-driven model capable of quickly responding to changing market conditions in the most profitable manner. The solution offers:
- Daily price and demand forecasts at stock keeping unit (SKU) and channel level with an integrated forecasting process.
- A system in which price acts as the lever to shape demand toward the most profitable product, customer and channel mix—on a daily basis.
- Modeled price-volume relationship per product and segment to help enable supply clearing.
- Relevant and appropriate decision modeling with constraints that can be added in the latest possible time window to maximize flexibility.
- Real-time integration and insight across the business to help you react at the speed of the market.
- Support for an integrated end-to-end pricing process through a single platform.
- The ability to identify commodity price trends over time and to understand how seasons impact prices using historical as well as projected prices for each commodity.
Analytics for up-to-the-minute insights
The commodity price optimization solution works within the IT landscape that you have today. Components can include:
- IBM® SPSS® predictive analytics software: Uncover patterns and associations, and develop models to guide front-line interactions.
- IBM Cognos® Business Intelligence: Explore and interact with virtually any data, in any combination, all in a unified workspace with reporting, dashboards, scorecards, what-if analysis, predictive analytics, statistical analysis and more.
- IBM SmartCloud: Take advantage of enterprise cloud technologies and service offerings for private, public and hybrid clouds based on IBM hardware, software, services and best practices.
- IBM WebSphere® application integration software: Connect everything inside and outside your company, enabling your service-oriented architecture (SOA) to deliver reliability and security with high performance and high availability, spanning newly developed web services and complex heterogeneous environments.