Volatility caused by the financial crisis in 2008, greater price and service consciousness
of consumers as well as ongoing concentration in the commodities market are
forcing retailers and manufacturers of consumer products to differentiate themselves from
the competition. These intensifying competitive pressures are also having an impact
on profits, especially when major market players (both retailers and manufacturers)
attempt to increase their market share through flexible pricing policies (Bartlett and
Ghoshal, 2002). The result is an even greater pressure on the already low returns. Price is not
the only component that determines success and market share. Product availability is
equally important. Combining these two factors, i.e., ensuring that in-demand and
low-cost products are always available, can provide the differentiation that is needed in
a homogeneous market. The Demand-Driven Supply Network (DDSN) concept can
help companies to become market leaders (Martin, 2006). Metrics for DDSN differ
from existing metrics. Thus, companies will no longer solely focus on
production and lowest costs per unit, instead change their metrics to focus on fast,
consumer-driven replenishment and reduction of Out-of-Stock (OOS) situations
(Simchi-Levi et al., 2008).
The DDSN is based on new adaptive Supply Network (SN) technology, such as time-phased
integrated planning, supply collaboration, synchronization of distribution requirements
and transportation activities. This implies the integration of all available information
needed to satisfy the demands of DDSN concept, since DDSN is mainly driven by
customer demands. The DDSN utilizes the pull system of supply chain unlike push system
of traditional supply chain. While the DDSN advantages on business processes are clear
the implementation of supporting systems lead to a group of challenges on how to get
this information needed in a fine granular level of details and how to manage these
amounts of data. Both challenges are related to each other since more detailed information
strongly requests sophisticated data management with the ability to analyze the data by
utilizing flexible aggregation. Movements towards Real World Awareness (RWA) by
introducing Radio Frequency Identification (RFID) support the first mention challenge of
implementing a DDSN. In addition, recent changes in data management technologies, such as
main memory databases and column-wise physical data representation enable data
management systems to handle the expected amount of data supported by light weight
compression technologies (Abadi et al.,
2006).
The DDSN intends to become the next generation of collaboration between retailers
and consumer-good manufacturers leveraging former concepts like Vendor-Managed
Inventory (VMI) (Waller et al., 1999; and Disney and Towill,
2003b), and Collaborative Planning, Forecasting and Replenishment (CPFR)
(Stank et al., 1999; Holmström et
al., 2002; and Seifert, 2003). But what differentiates this approach from other similar initiatives? |
