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 When procuring for innovative products, the focus should be on the total landed cost, which is the sum of all costs associated with making and delivering products to the point where they are used. This includes not only the unit cost, but also the transportation, handling, inventory, taxes, duties, and other fees associated with the procurement process. By focusing on the total landed cost, procurement can evaluate the true value of innovative products and compare them with alternative solutions. Focusing on unit cost alone may overlook the potential benefits of innovation, such as improved quality, performance, or sustainability. Lead times and lot sizes are also important factors to consider, but they are not the main focus when procuring for innovation. References : CPIM Part 2 Exam Content Manual, Domain 4: Plan and Manage Supply, Section A: Supply Management Concepts and Approaches, Subsection 2: Procurement Strategies and Techniques, Page 17.

The question is about forecasting the demand for a product, and the options are different levels of aggregation or disaggregation. The highest percentage of error will occur at the most disaggregated level, which is the field warehouses. The field warehouses are the locations where the finished products are stored and delivered to the customers. The demand at the field warehouses is affected by various factors, such as customer preferences, seasonality, promotions, and competition. The demand at the field warehouses is also more volatile and uncertain than the demand at the higher levels of aggregation, such as the market segment or the central warehouse. Therefore, forecasting the demand at the field warehouses will have the highest percentage of error, which means that the forecast will deviate more from the actual demand.

The other options are not the levels where the highest percentage of error will occur. The master schedule is not a level of aggregation or disaggregation, but a plan that specifies the quantity and timing of finished products to be produced in a given period. The master schedule is based on the forecasted demand, the customer orders, and the production capacity. The master schedule does not have a percentage of error, but it may have a variance or deviation from the actual production output. The market segment is a level of aggregation that groups the customers or products based on their common characteristics or needs. The market segment is a higher level than the field warehouses, and it has less variability and uncertainty in demand. Therefore, forecasting the demand at the market segment will have a lower percentage of error than forecasting at the field warehouses. The central warehouse is a level of aggregation that consolidates the inventory from different sources and distributes it to different destinations. The central warehouse is a higher level than the field warehouses, and it has less variability and uncertainty in demand. Therefore, forecasting the demand at the central warehouse will have a lower percentage of error than forecasting at the field warehouses.

The master production schedule (MPS) and final assembly schedule (FAS) are most closely linked in the assemble-to-order (ATO) production strategy. ATO is a production strategy that producescustomized products or services by assembling standardized components or modules according to customer specifications. The MPS is a plan that specifies the quantity and timing of finished products to be produced in a given period. The FAS is a plan that specifies the quantity and timing of final assembly operations to be performed in a given period. In the ATO strategy, the MPS and FAS are closely linked because the MPS determines the demand for the finished products, and the FAS determines the demand for the components or modules. The MPS and FAS are synchronized to ensure that the components or modules are available when needed for the final assembly, and that the finished products are delivered on time to the customers.

The MPS and FAS are not closely linked in the other production strategies. Make-to-stock (MTS) is a production strategy that produces standardized products or services in advance of customer demand, and stores them in inventory until they are sold. The MPS is based on the forecasted demand, and the FAS is not relevant for this strategy, as there is no customization involved. Make-to-order (MTO) is a production strategy that produces customized products or services from raw materials or components after receiving customer orders. The MPS is based on the actual customer orders, and the FAS is not relevant for this strategy, as there is no assembly involved. Engineer-to-order (ETO) is a production strategy that produces customized products or services that require engineering design or modification after receiving customer orders. The MPS is based on the actual customer orders, and the FAS is not relevant for this strategy, as there is no standardization involved. References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.1: Supply Planning Concepts, p. 23; Master Production Schedule; Final Assembly Schedule; Assemble to order.

 Capable-to-promise (CTP) is a method of order promising that considers both material and capacity availability. CTP is more appropriate than available-to-promise (ATP), which only considers material availability, in environments where the production process is complex, customized, or resource-intensive, and where the demand is uncertain or variable. CTP can provide more accurate and realistic delivery dates, as well as optimize the use of resources and reduce inventory costs.

Among the options given, specialty chemicals packaged and shipped to order is the most suitable environment for CTP. This is because specialty chemicals are often produced in small batches or on demand, according to the specific requirements and preferences of each customer. Therefore, the production process requires high flexibility and customization, as well as careful coordination of materials and capacity. The demand for specialty chemicals may also vary depending on the market conditions and customer needs. CTP can help the company to promise delivery dates that take into account the availability of both materials and capacity, as well as the production lead time and transportation time.

The other options are less suitable for CTP, as they are more likely to use standard or mass production processes, where the products are made in large quantities or in advance, and where the demand is more stable or predictable. In these environments, ATP may be sufficient to promise delivery dates based on material availability alone, without considering capacity constraints.

References : What is a Capable-to-Promise System (CTP System … - Techopedia; Order promising - Supply Chain Management | Dynamics 365; Capable to Promise (CTP) (MRP and Supply Chain Planning Help) - Oracle; Calculate sales order delivery dates using CTP - Supply Chain ….

The cash-to-cash cycle time is a financial metric that measures the time it takes for a company to convert its cash outflows into cash inflows. The cash-to-cash cycle time is calculated by adding the days of inventory outstanding (DIO), the days of sales outstanding (DSO), and the days of payablesoutstanding (DPO), and then subtracting the days of payables deferred (DPD). The cash-to-cash cycle time can be shortened by reducing any of the components, except for DPD, which should be increased. Reducing which measure by 10% would contribute most to shortening the cash-to-cash cycle time depends on the relative values of each component. However, given the information below, reducing accounts receivable by 10% would have the greatest impact.

The current cash-to-cash cycle time is:

Cash-to-cash cycle time = DIO + DSO + DPO - DPD = 60 + 90 + 30 - 15 = 165 days

If accounts receivable is reduced by 10%, then DSO becomes 81 days (90 x 0.9). The new cash-to-cash cycle time is:

Cash-to-cash cycle time = DIO + DSO + DPO - DPD = 60 + 81 + 30 - 15 = 156 days

The difference is 9 days, which is the largest reduction among all the measures.

If inventory value is reduced by 10%, then DIO becomes 54 days (60 x 0.9). The new cash-to-cash cycle time is:

Cash-to-cash cycle time = DIO + DSO + DPO - DPD = 54 + 90 + 30 - 15 = 159 days

The difference is 6 days, which is smaller than reducing accounts receivable.

If accounts payable is reduced by 10%, then DPO becomes 27 days (30 x 0.9). The new cash-to-cash cycle time is:

Cash-to-cash cycle time = DIO + DSO + DPO - DPD = 60 + 90 + 27 - 15 = 162 days

The difference is 3 days, which is smaller than reducing accounts receivable and inventory value.

If cost of capital is reduced by 10%, then it has no direct effect on the cash-to-cash cycle time, as it is not a component of the formula. However, it may affect the profitability and liquidity of the company indirectly.

Therefore, reducing accounts receivable by 10% would contribute most to shortening the cash-to-cash cycle time, given the information below.

References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.2: Implement Supply Plans, Subsection 4.2.3: Describe how to implement financial management techniques (page 40).

The bullwhip effect is a supply chain phenomenon that causes fluctuations in demand to amplify as they move upstream, from the consumer to the retailer, to the distributor and then to the producer1. The bullwhip effect can result in inefficiencies and costs such as excess inventory, lost revenues, superfluous capacity and poor customer service1.

One of the activities that would be effective to mitigate the bullwhip effect is to reduce lead times, which are the time intervals between placing an order and receiving the goods2. Reducing lead times can help to reduce the uncertainty and variability in demand, as well as improve the responsiveness and flexibility of the supply chain2. By reducing lead times, the supply chain partners can order less frequently and in smaller quantities, while still meeting customer demand. This can reduce the need for safety stock, cycle stock and pipeline stock, and thus lower the inventory carrying costs and risks2.

The other options are not effective activities to mitigate the bullwhip effect. Implementing track and trace technology, which is a method for tracking the origin, history, location and status of a product or its parts throughout the supply chain3, may help to improve the visibility and transparency of the supply chain, but it may not reduce the demand fluctuations or inventory imbalances caused by the bullwhip effect. Using a push system, which is a production system where goods are produced based on forecasted demand rather than actual customer orders4, may increase the risk of overproduction or underproduction, as well as create more inventory and waste in the supply chain. Increasing inventory, which is the stock of goods or materials held by a company to meet customer demand5, may increase the inventory carrying costs and risks, as well as tie up cash flow and working capital.

References : Lead Time Reduction: Definition & Benefits; The bullwhip effect: causes, intensity, and mitigation - Academia.edu; What is Traceability in Supply Chain Management?; Push vs Pull System: What Is The Difference?; Inventory Definition.

 One of the trade-offs that should be evaluated when determining where to place inventory in a multi-echelon supply chain network is the transportation cost and delivery time. A multi-echelon supply chain network is a system of interconnected stages or echelons that perform different functions, such as production, distribution, and retailing, to deliver products or services to the end customers1. Inventory placement is the decision of how much and where to hold inventory in the supply chain network to balance the costs and service levels2.

Transportation cost is the expense of moving products or materials from one echelon to another in the supply chain network. Transportation cost depends on factors such as distance, mode, volume, weight, fuel, and tariffs3. Delivery time is the duration of moving products or materials from one echelon to another in the supply chain network. Delivery time depends on factors such as speed, reliability, frequency, and congestion3.

There is a trade-off between transportation cost and delivery time when determining where to place inventory in a multi-echelon supply chain network. Generally, holding more inventory closer to the customers can reduce the delivery time and increase the service level, but it can also increase the transportation cost and the inventory holding cost4. On the other hand, holding less inventory farther from the customers can reduce the transportation cost and the inventory holding cost, but it can also increase the delivery time and decrease the service level4. Therefore, finding the optimal inventory placement requires balancing the transportation cost and delivery time trade-off.

Some of the methods or tools that can help evaluate the transportation cost and delivery time trade-off are:

Network optimization: a technique that uses mathematical models to optimize the design and configuration of a supply chain network by minimizing the total costs (including transportation and inventory costs) while satisfying the service level requirements.

Multi-echelon inventory optimization: a technique that uses mathematical models to optimize the allocation and sizing of safety stocks across multiple echelons of a supply chain network by minimizing the total costs (including transportation and inventory costs) while satisfying the service level requirements.

Simulation: a technique that uses computer software to mimic the behavior and performance of a supply chain network under different scenarios and assumptions. Simulation can help evaluate the impact of different inventory placement strategies on the transportation cost and delivery time.

Therefore, transportation cost and delivery time is one of the trade-offs that should be evaluated when determining where to place inventory in a multi-echelon supply chain network.

References: 1: Multi-Echelon Inventory Optimization 2 2: Inventory Placement Definition 3 3: Transportation Cost Definition 4 4: The Tradeoff Between Inventory Costs And Transportation Costs : Supply Chain Network Design: Applying Optimization and Analytics to … 1

Point-of-use storage is a stock location system that places inventory close to where it is needed in the production process, reducing transportation and handling costs and improving efficiency. It is often used in repetitive manufacturing, lean environment, where the demand is stable and predictable, and the inventory is replenished frequently. Fixed location and central storage are stock location systems that store inventory in a designated area, which may require more space and movement. Floating location is a stock location system that assigns inventory to any available space, which may cause confusion and inefficiency. References: CPIM Exam Content Manual Version 7.0, Domain 5: Plan and Manage Inventory, Section 5.2: Inventory Management Methods, p. 32.

 A balanced scorecard is a performance measurement approach that involves linking financial and non-financial performance measures to organizational goals. According to the web search results, a balanced scorecard is a strategic planning and management system that organizations use to communicate what they are trying to accomplish, align the day-to-day work with strategy, prioritize projects, products, and services, and measure and monitor progress towards strategic targets1. A balanced scorecard focuses on four key perspectives: financial, customer, internal business process, and learning and growth2. Each perspective includes objectives, measures, targets, and initiatives that are aligned with the organization’s vision, mission, and strategy3. By using a balanced scorecard, organizations can balance the short-term and long-term objectives, the financial and non-financial outcomes, and the internal and external stakeholders.

A part that is sold as a service part and also used as a component in another part is called a dual-sourced item. A dual-sourced item has two sources of demand: the external demand from the customers who buy the service part, and the internal demand from the parent part that uses the component. The planning for a dual-sourced item should include both sources of demand in the gross requirements, so that the net requirements can be calculated correctly. The service part demand can be included in the gross requirements by using a planning bill of material, which is a special bill of material that shows the relationship between a parent item and its service parts. A planning bill of material allows the system to explode the service part demand to the component level and generate planned orders for both the service part and the component.

The other statements about the planning for this part are false. Its low-level code is not zero, because it is not an independent item. It has a higher low-level code than its parent item, because it is a component of another item. The material requirements for the part will not be understated, if both sources of demand are included in the gross requirements. It should have some safety stock, to protect against demand and supply uncertainties. References: CPIM Part 2 Exam Content Manual, Domain 4: Plan and Manage Supply, Section 4.2: Material Requirements Planning (MRP), p. 22-23.