(2003) Bezemer – Not with a bang, but with
a whimper
Literature review:
Seminal Works: Forrester's studies in the late 1950s and early 1960s focused on the impact of
market demand changes on supply chains, highlighting the role of delays in managerial decisions and
policies.
Recent Focus: Recent publications have explored delays in supply chains, with studies on topics such
as upstream supply chain volatility and demand amplification in various industries.
This research highlights the significance of delays in supply chain performance and the evolving
understanding of how managerial decisions and policies can impact supply chain dynamics.
Research Method:
Need for Exploratory Research: Due to the insufficient understanding of this topic, exploratory and
theory-building research methods were deemed necessary to shed light on the delays in supply
chain dynamics.
Opportunity in Market Dynamics: The boom-and-bust cycle of 1999-2001 in the semiconductor
industry provided a unique opportunity to study the effects of demand fluctuations on supply chain
performance, making it an ideal real-world scenario for analysis.
Supply chain model:
Goods Flow Structure: The goods flow is divided into two stages separated by the die-bank, known as
the Customer Order Decoupling Point. It operates as a hybrid push-pull system with limited
production capacity. Cycle-times are affected by capacity utilization, with queue-times increasing at
higher levels. Raw cycle-time is exogenous, while queue-time is endogenous and modeled under the
"practical worst case."
Order Flow and Customer Demand: The downstream stage operates as a pull system based on
current demand signals, with order acceptance limited to production capacity. Customer demand is
endogenous and influenced by industry trends and customer satisfaction. Delivery performance is
crucial and depends on order acceptance and on-time delivery.
Capacity Management and Key Performance Indicators: Pressure to change capacity is driven by
perceived supply chain performance. The model distinguishes between available and desired
capacity, with actual capacity aligning with desired capacity after a delay. Key performance
indicators include delivery quality (CLIP), cost (total inventory and capacity utilization), timeliness
(stacked lead-time and delivery delay), and flexibility (RLIP).
Conclusion:
Market Volatility: The semiconductor industry faces major market surges and downturns,
necessitating flexible supply chains to handle such volatility effectively.
Trade-Offs: Responding promptly to market changes is crucial, but it comes with trade-offs like
disappointing some customers to satisfy others or investing more in buffer stocks at higher costs.
Challenges in Decision-Making: Decision-making in semiconductor firms involves navigating complex
trade-offs, often with limited visibility into all relevant information and interrelations.
Variability in Response Periods: The length of response periods to market changes can vary
significantly, ranging from a few quarters to several years, depending on factors like customer
satisfaction criteria or costly production capacity adjustments.
a whimper
Literature review:
Seminal Works: Forrester's studies in the late 1950s and early 1960s focused on the impact of
market demand changes on supply chains, highlighting the role of delays in managerial decisions and
policies.
Recent Focus: Recent publications have explored delays in supply chains, with studies on topics such
as upstream supply chain volatility and demand amplification in various industries.
This research highlights the significance of delays in supply chain performance and the evolving
understanding of how managerial decisions and policies can impact supply chain dynamics.
Research Method:
Need for Exploratory Research: Due to the insufficient understanding of this topic, exploratory and
theory-building research methods were deemed necessary to shed light on the delays in supply
chain dynamics.
Opportunity in Market Dynamics: The boom-and-bust cycle of 1999-2001 in the semiconductor
industry provided a unique opportunity to study the effects of demand fluctuations on supply chain
performance, making it an ideal real-world scenario for analysis.
Supply chain model:
Goods Flow Structure: The goods flow is divided into two stages separated by the die-bank, known as
the Customer Order Decoupling Point. It operates as a hybrid push-pull system with limited
production capacity. Cycle-times are affected by capacity utilization, with queue-times increasing at
higher levels. Raw cycle-time is exogenous, while queue-time is endogenous and modeled under the
"practical worst case."
Order Flow and Customer Demand: The downstream stage operates as a pull system based on
current demand signals, with order acceptance limited to production capacity. Customer demand is
endogenous and influenced by industry trends and customer satisfaction. Delivery performance is
crucial and depends on order acceptance and on-time delivery.
Capacity Management and Key Performance Indicators: Pressure to change capacity is driven by
perceived supply chain performance. The model distinguishes between available and desired
capacity, with actual capacity aligning with desired capacity after a delay. Key performance
indicators include delivery quality (CLIP), cost (total inventory and capacity utilization), timeliness
(stacked lead-time and delivery delay), and flexibility (RLIP).
Conclusion:
Market Volatility: The semiconductor industry faces major market surges and downturns,
necessitating flexible supply chains to handle such volatility effectively.
Trade-Offs: Responding promptly to market changes is crucial, but it comes with trade-offs like
disappointing some customers to satisfy others or investing more in buffer stocks at higher costs.
Challenges in Decision-Making: Decision-making in semiconductor firms involves navigating complex
trade-offs, often with limited visibility into all relevant information and interrelations.
Variability in Response Periods: The length of response periods to market changes can vary
significantly, ranging from a few quarters to several years, depending on factors like customer
satisfaction criteria or costly production capacity adjustments.
