More than ever, business leaders today are challenged to do more with less. That's evident from the recent survey published by IBM Business Consulting Services. The findings show that while more than 80 percent of the CEOs surveyed cited revenue growth as their main focus, more than two-thirds also said that cost reduction was a critical focus area. In the same survey, more than half the CEOs reported that reducing product design and development times and expanding "voice of the customer" programs was key to achieving their corporate goals.

How can CEOs respond to these challenges? One promising way is through a framework called the Demand Driven Supply Network (DDSN). DDSN is a system of coordinated technologies and processes that senses and reacts to real-time demand signals across a network of customers, suppliers, and employees. It enables organizations to improve operational efficiency, streamline new product development and launch, and maximize margin. In short, the DDSN is a roadmap for developing the next-generation supply chain.

Integrated processes lie at the heart of the DDSN. These processes must be capable of generating a credible demand signal, sharing that signal across trading communities, and coordinating work flow and activity among all partners. Moreover, the network must be transparent enough for participants to get a common view of business performance. Exhibit 1 gives an overview of the DDSN framework.

This integration, however, won't come easy for many companies. Most supply chain project implementations to date have focused on getting the processes right within the four walls. Collaboration, or building dependencies outside of the enterprise, typically has ranked low on the list of priorities. Supply chain leaders, however, are moving quickly toward collaborative relationships, expediting the evolution of a Demand Driven Supply Network. Exhibit 2 summarizes the differences between traditional supply chain management and the DDSN identified in our research. These differences form the underpinnings of the DDSN framework.

The DDSN is not just about being more responsive and flexible to demand. It's also about managing the demand more proactively to increase the supply chain yield. The DDSN framework identifies five key capability areas (keyed in Exhibit 1) in which successful companies prioritize process improvements.

1. Event-Driven S&OP. Most companies hold regular forecasting meetings today. But the current processes usually do not meet the proactive and bidirectional supply-demand synchronization required by the DDSN framework. In most cases, the process is frequency based and companies manage major exceptions outside of the sales and operations planning (S&OP) process. This results in expedited but suboptimal plans.
   Advanced companies are moving from frequency-based to needs-based S&OP, initiating a formal process when a major exception occurs and is detected in the demand-supply activity. One high-tech manufacturer, for example, has used this process effectively across its supply network, cutting inventories by more than 45 percent and reducing cost of goods sold.
2. Undistorted demand signal and demand intelligence. Companies following the DDSN framework combat demand-signal distortion in one of two ways. First, they use undistorted demand signals and pass the relevant information upstream rapidly. One high-tech original equipment manufacturer (OEM) combines the undistorted, customer-provided forecast with its own revenue-based, marketing forecast to rationalize the internally generated marketing forecast. This approach helps resolve any constraints or supply-demand alignment issues.
   The second approach is to use this demand intelligence to detect exceptions to plan and align supply accordingly. These exceptions are managed in a structured resolution process. For example, a consumer packaged goods (CPG) manufacturer uses a short-term, downstream demand-intelligence signal (consumption data from retail) to compare against its initial demand forecast. This enables the company to detect shifts in demand and align the product distribution according to that shift. It also monitors sell-through data at the store level for its largest customer to identify trends, customer preference, and potential out-of-stocks.
3. Integrated product introduction and phase-out. Different industries derive demand signals in different ways, particularly when determining the sales forecast for new products or predicting consumption at the product's end of life. In the CPG industry, promotional tactics coupled with continual new product introductions and line extensions shape demand. In this case, past history becomes a predictor of future performance. In the high-tech industry, by comparison, the demand stimulus could come from introducing a new technology or directing a product at a different market segment, such as finding new applications for end-of-life products.
4. Risk-based supply flexibility (replenishment). A Demand-Driven Supply Network must be flexible and responsive. However, in an event-driven S&OP environment, achieving flexibility through inventory positioning is not enough. To maximize the yield across the supply chain, leaders are using risk-based approaches to set supply network strategies.
5. Mixed-mode segments aligned to POPs. For a DDSN to be successful, multi-product companies must view their supply chains in segments and optimize each segment's flow based on market/product/channel characteristics. They need to understand the placement of points of postponement (POPs) along the segmented supply chains and optimize them for the best performance.

Leaders are creating winning strategies in different markets by transforming their supply chains to DDSNs. Companies working with these leaders—or competing against them—must start thinking about transforming their own supply chains. Transforming a traditional supply chain into a DDSN is a major task and requires alignment with the business strategy. But the competitive realities are such that companies cannot take too long to begin the journey.