Food Engineering

The truths about consumer-driven supply networks

February 3, 2005
Managing your supply chain can improve bottom-line performance.

Olin Thompson
There are two moments of truth in your supply chain, according to Keith Harrison, Proctor & Gamble's chief product officer. The first moment occurs when the consumer selects the product; the second occurs when the consumer uses the product. In other words, is it on the shelf when the consumer wants it and does it meet the consumer's expectation?

As part of P&G's Consumer Driven Supply Network (CDSN), Harrison says this kind of thinking is a major cultural transformation at P&G. The company uses the supply chain management technique to manage several brands, including Folgers Coffee, Pringles Potato Crisps, Torengos tortilla chips, Millstone Arabica bean coffees and Eukanuba and Iams for dogs.

Harrison says CDSN is changing the way P&G thinks about its supply chain. The company has moved from measuring performance on internal cost and efficiency to external processes targeting consumer satisfaction at the shelf. CDSN means capturing and processing multiple sources of demand data and exception events to provide intelligence that, in turn, enables you to make smart trade-offs in production and replenishment.

AMR Research, a firm that provides practical, decisive research and actionable advice for executives who seek to improve process performance and cut costs with technology, calls the same concept Demand Driven Supply Network (DDSN). Roddy Martin of AMR defines DDSN as "the system of technologies and processes to sense and react to real-time demand signals across a supply network of customers, suppliers and employees." With DDSN, plants produce to demand, not inventory, targets.

The classic answer in dealing with demand variability has been inventory. These buffers allowed us to absorb sudden surges in demand. DDSN shortens the cycle between demand signals (POS data, movements from the back of the store to the front, or distribution center to store movements), production and replenishment. In other than seasonal items or promotions, buffer stocks are seen as proof that the demand signal to replenishment cycle can still be shortened.

With more than 15 years of experience, Kara Romanow follows the food industry for AMR. She says AMR's research shows a direct correlation between improvements in the perfect order metric (percent of all orders that are perfect) and profitability. For each 3% improvement in the perfect order measurement, AMR's model shows a 1% increase in profit margins. And a 5% improvement in perfect orders results in a 2.5% increase in return on assets (ROA).

Perfect orders are customer orders that arrive on time with the right product and right quantity. Forecast error, on the other hand, is the difference between forecasted demand and actual demand. Although DDSN drives production with "real-time" demand signals, forecasting is still very important to permit long-term decisions and ingredient and packaging purchases. Forecast error measures the amount of unanticipated demand-the demand that causes disruption in the supply chain.

For scheduling, DDSN calls for adaptive responses to unforeseen demand. For example, in case of a stock out, a plant must be able to change the existing schedule on a same-day basis to predictably produce the required product to meet retail commitments. It has to happen without creating additional problems for other customers or at least being able to recognize what problems will be caused so rational decisions can be made about the various trade-offs.

Call it Consumer Driven Supply Network or Demand Driven Supply Network, companies are proving that changing how we manage the supply chain is driving improved financial performance. This change is increasing the pressure on plants to produce to demand and to become more flexible, adaptive and predictable.