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Capital Intensive Hi-Tech Supply Chains: Capacity Allocations Issues and Potential Solutions

The Supply Chain in Hi-tech and Semiconductor industry vertical is characterized by globally fragmented value chain partners with product design happening in Silicon valley, foundries and fabrication units spread throughout south east Asia region, software development happening in Bangalore and assembly and testing being conducted in Malaysia.

On the other hand the high capital equipment and setup cost with operational challenges ranging from high demand volatility to product line and manufacturing complexity with product life cycle spanning from less than one year for cell phone chips to ten or more years for semiconductors for automobiles, makes it imperative for Hi-tech manufacturers to not only take a microscopic look at their capacity management process but also consider a coordinated capacity investment and allocation decisions with their supply chain partners.

High-Tech companies are realizing that in order to sustain their customer base and seize revenue opportunities, they must be able to manage rapid technological innovation effectively and appropriately structure capacities in their supply chains to respond over time to the demand surge from new product introductions and market up-side. At the same time have operational maturity to absorb short-term decline due to technological migration and market downside.


Capacity investment in high-tech industry typically involves substantial cash exposures, volatile market demand and changing supply (technological) specifications. The cost drivers often are not material related, but rather are related to equipment depreciation. This makes resource utilization (both equipment and manpower) extremely important. At an operational level, defining capacity planning decision support models, which can be applied across different manufacturing production models and product life cycle stages suggesting optimum capacity allocation numbers (design/trial capacity, production ramp-up capacity, In-line production capacity) is extremely difficult. In addition justifying those models and criteria (based on product demand patterns, cost-benefit analysis) with capacity investment choices to overcome operational roadblocks invite unique management questions for key process stakeholders involved in solving this problem systemically.

The same management problem gets pronounced when business dimension of process structure/process life cycle stages are considered concurrently (see Figure 2) in these decisions with interdepartmental stakeholders (such as product marketing analysts, sales managers, strategic planners) from across global business units start participating and influencing production capacity allocation decisions to achieve their individual business unit goals.


All the above aspects converge towards making decisions regarding capacity investment, expansion and utilization, which in turn affects and influences supply chain planning and delivery efficiency and a Hi-tech firm's ability to manage capacity at strategic, tactical and operational level, which today is arguably the most critical factor for its long-term success.

Hence a systemic solution of incorporating a concerted capacity planning approach, with capacity allocation, collaboration and capacity simulation/assessment process functions is recommended to address the complex nature of the problem with the intent of timely identifying the process bottlenecks, tracking capacity utilization and taking proactive action when needed to change the share of business across starving or overloaded manufacturing entities and level load them with the objective of building a "Profit maximizing Product Mix" as per corporate business needs and goals.

Capacity allocation and simulation capabilities will help in carrying out near/mid/long term capacity assessment and decision making process regarding product-mix changes, volume enhancement or switching share of business among  suppliers, in-house or contract manufacturing entities by implementing rule-based allocation algorithms across product families, strategic business unit and manufacturing process steps dimensions.

Global visibility and collaboration strategies have often proved to reduce unnecessary uncertainty introduced into the supply chain when supply chain partners second guess each other rather than share information. As an example typically, Wafer Fabs (front end) and Assembly/Testing facilities (back end) work in relative isolation. Wafers are manufactured and probed in one facility and then shipped to another facility, often thousands of miles away. These facilities have separate factory planning organizations and so by sharing information, a company can improve capacity management between the two facilities. In that respect having a system-driven capacity collaboration capability will not only help facilitate real-time capacity information exchange among key value chain partners for better planning and negotiations but also will reduce human errors caused by manual workflows.

From a process perspective capacity planning plays the role of Master Planning at the corporate level. It results in making the key decisions of allocating the capacity to each participating divisions (internal and external), assessing capacity requirements for demand and forecast profile across product lines, and time capacity expansions. Given that it takes a while before one can add additional, expensive production test capacity when demand picks up, or suffer low utilization in times of low demand, a coordinated systemic capacity planning approach will help Hi-tech companies improve their aggregate capacity planning decision making capabilities. Consequentially they will move towards achieving operational excellence and becoming a high performance integrated supply chains driving increased customer service levels with improved inventory turns and reduced obsolescence.

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