Demand Management - JDA Software: The Supply Chain Company

By: Jda  09-12-2011
Keywords: supply chain, Forecasting

True Demand-Driven Accuracy

Accurately Predicting Customer and End-Consumer Demand in an Ever-Changing Market

Today's companies are especially challenged to accurately predict demand for their products and services. Some of these factors include increasingly demanding customers and end consumers, multiple channels, frequent promotions, fluctuating pricing strategy requirements, shortened product lifecycles and expanding product options — whether for expanding retail assortments or for expanding configuration options in discrete manufacturing. Seasonality, halo and cannibalization effects and the inherently variable nature of demand further complicate the forecasting process. Methodological considerations like correctly interpreting demand history, applying the most appropriate forecasting method and tuning forecasting algorithms add even more complexity.

It's no easy task, but to be successful, companies must have the ability to accurately anticipate not only which products will sell, but also when they will sell and at what price point. Costly mismatches of demand and supply can result in missed sales opportunities, lost profits, excessive expediting costs, too much or too little inventory, lost market share and poor customer service. To address these issues, industry leaders are embracing the reality that demand drives the customer-driven supply chain, and in many industries this demand extends down to the consumer level. Companies are increasingly striving to align their operations with customer and end-user demand signals as the primary driver of optimized supply and demand chain decisions — requiring a solution that provides one synchronized view of demand across their organizations. Moving to this integrated planning framework requires a robust solution that can deliver a consolidated forecast with the highest accuracy.

Optimizing Supply Chain Decisions with Clear Demand Visibility Using Advanced Demand Management

The JDA Demand Management solution suite provides a comprehensive answer to these complex challenges and helps you better prepare for future demand — down to the lowestlevel demand signals in your supply chain.

Increasing demand visibility across the entire trading network, the solution's multiple forecasting methods enable you to accurately predict demand across all product types — including fast- and slow-moving, lumpy, short lifecycle, trending, steady, highly seasonal and causal-driven. JDA Demand Management can help your company:

  • Create an accurate, consensus demand plan for each of your products and make large volumes of products manageable and predictable
  • Rapidly respond to shifts in demand from new product introductions to end of life, driving high customer satisfaction levels
  • Leverage multiple history streams, forecasting algorithms, promotional information and event data, improving forecast accuracy, minimizing inventory-carrying costs and reducing lost sales
  • Classify your products based on demand patterns, apply the appropriate statistical forecasting algorithm and automatically assign the parameter settings based on the product's demand behavior
  • Differentiate demand resulting from external factors (such as price effects and promotions) from demand history, providing the foundation for a more accurate baseline forecast

Moving to a Synchronized View of Demand

The first step to achieving one synchronized view of demand is an accurate statistical forecast that also incorporates human and event intelligence. By facilitating and incorporating this consolidated view into your supply chain, the solution enables you to better satisfy your customers and end consumers with lower total supply chain costs.

Making Better Business Decisions with a Consensus Demand Plan

Features and Benefits

Superior forecasting performance

  • Improved forecast accuracy up to 20-25 percent by leveraging statistical analysis capabilities, demand stream segmentation and forecasting at multiple hierarchical levels
  • Increased demand visibility across the trading network with consensus demand plans that align trading partners with a shared forecast
  • Addressed localized seasonal demand variations throughout the selling season or fiscal year

Inventory investment optimization

  • Reduced supply chain cost with a more accurate, stabilized forecast, driving inventory management efficiencies
  • Optimized inventory levels for bottom-line savings:
    • Decreased safety stock 4-15 percent
    • Decreased overall inventory 4-8 percent
    • Lowered on-hand inventory 1-4 percent
    • Reduced overstocks and out-of-stocks
  • Improved service levels 0.5-5 percent while reducing lost sales 5-12 percent

Revenue and profit goal realization

  • Increased sales up to 5 percent by better predicting and shaping consumer response to seasonality and trends
  • Increased inventory turns 5-8 percent by smoothing demand variations across trading network for increased synchronization and inventory availability
  • Improved pricing and promotions strategies throughout a product lifecycle by helping planners determine which promotions to run for the most profitable results

Process efficiencies

  • Enabled business planners to focus on what's most important by decreasing the cycle time for forecasting and planning
  • Decreased required resources to manage detailed data such as itemand location-level profiles, statistical algorithms and parameters
  • Reduced data storage and maintenance requirements by minimizing the need for multiple demand models
  • Represents actual results realized by JDA customers.

Keywords: Forecasting, supply chain

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