CPIM-Part-2 Questions and Answers

A control chart is a tool that shows process changes and random variation over time. A control chart is a graph that plots data points over time and shows the mean and the upper and lower control limits of the process. The mean is the average value of the data, and the control limits are the boundaries of the normal variation of the process. A control chart can help monitor the stability and performance of a process by detecting any unusual or non-random patterns in the data, such as trends, cycles, or shifts. A control chart can also help identify the sources of variation in the process, whether they are common causes (inherent to the process) or special causes (external factors). A control chart can be used for both variable data (measured on a continuous scale) and attribute data (counted or categorized).

A check sheet is a tool that collects and summarizes data in a structured way. A check sheet is a simple form that records the frequency or occurrence of specific events or problems during a process. A check sheet can help organize and analyze data by showing patterns, trends, or relationships among the data. A check sheet can also help identify potential causes of problems or areas for improvement.

A histogram is a tool that displays the distribution of data in a graphical way. A histogram is a type of bar chart that shows how many times each value or range of values occurs in a data set. A histogram can help describe and compare data by showing the shape, center, spread, and variation of the distribution. A histogram can also help identify outliers, gaps, or clusters in the data.

A Pareto analysis is a tool that prioritizes problems or causes based on their frequency or impact. A Pareto analysis is based on the Pareto principle, which states that 80 percent of the effects come from 20 percent of the causes. A Pareto analysis uses a combination of a bar chart and a line graph to show the relative importance of different factors in a process. The bars represent the frequency ormagnitude of each factor, and the line represents the cumulative percentage of the total effect. A Pareto analysis can help focus on the most significant problems or causes and allocate resources accordingly.

References := Control Chart - Statistical Process Control Charts | ASQ, A Guide to Control Charts - iSixSigma, 2 Tools to Understand Variation in Your Improvement Journey, Understanding variation | Turas | Learn

The poka-yoke technique of process design is a method for preventing or detecting errors and defects in the manufacturing process. Poka-yoke means “mistake-proofing” in Japanese, and it aims to eliminate human errors by creating systems that either make it impossible for a mistake to occur or make the mistake immediately obvious once it has occurred1. One way to implement poka-yoke is to use part attributes, which are physical features of a part that ensure it can only be assembled or used in the correct way2. For example, a part attribute can define the correct orientation of a part, such as a notch, a hole, a shape, or a color, so that it can only fit into the matching component. This prevents the operator from inserting the part incorrectly or using the wrong part.

The other options do not illustrate the poka-yoke technique of process design. Reducing the number of types of fasteners is an example of standardization, which is a method for simplifying and streamlining the production process by minimizing variation and complexity3. Customized containers that hold mixed sets of parts are an example of kitting, which is a method for organizing and delivering parts or materials to the point of use or consumption in the production process4. An andon is a visual or audible signal that indicates the status of a machine or process, such as normal,abnormal, or emergency5. An andon can be used to alert operators or supervisors of problems or issues, but it does not prevent or detect errors by itself.

References: Lean Six Sigma Tools: What is Poka-Yoke? - Villanova University; What is Poka-Yoke? Mistake & Error Proofing | ASQ; What is Poka-Yoke? [Examples, Principles, Methods]; Standardization - an overview | ScienceDirect Topics; Kitting - an overview | ScienceDirect Topics.

Input/output control (I/O) is a type of tool that is used for monitoring a capacity plan. A capacity plan is a statement of the resources needed to meet the production plan over a medium-term horizon. A capacity plan can be stated in different units of measure depending on the type of manufacturing environment, such as hours, units, tons, or dollars. Input/output control (I/O) is a method of measuring and comparing the actual input and output of a work center or a production line against the planned input and output. Input is the amount of work that is released to the work center or the production line, and output is the amount of work that is completed by the work center or the production line. Input/output control (I/O) helps to monitor the performance and efficiency of the work center or the production line, and to identify any deviations or problems that may affect the capacity plan. Input/output control (I/O) also helps to adjust the input or output levels as necessary to maintain the balance between demand and supply, and to achieve the desired throughput.

References: CPIM Exam Content Manual Version 7.0, Domain 6: Plan, Manage, and Execute Detailed Schedules, Section 6.3: Monitor Detailed Schedules, Subsection 6.3.2: Describe how to monitor input/output control (I/O) (page 60).

Developing flexible operations is the best action that supports a company’s strategic focus on delivery speed to improve competitive advantage. Flexible operations are the ability to adapt to changes in customer demand, product mix, quality standards, and delivery schedules1. Flexible operations can help a company achieve faster delivery speed by enabling it to respond quickly and efficiently to fluctuations in the market, reduce lead times, optimize resource utilization, and avoid bottlenecks2. Flexible operations can also help a company gain a competitive edge by offering a wider variety of products or services, different volumes or quantities, and varying delivery dates to meet customer needs and expectations3.

Some examples of flexible operations are:

• Volume flexibility: the ability to produce different quantities or volumes of output3
• Delivery flexibility: the ability to change the timings or modes of delivery3
• Product flexibility: the ability to produce different types or variants of products or services4
• Process flexibility: the ability to use different methods or technologies to perform a process4
• Resource flexibility: the ability to use different inputs or resources for a process4

Some strategies for developing flexible operations are:

• Using modular design: designing products or services that consist of interchangeable components or modules that can be easily assembled or disassembled5
• Implementing automation: using machines or software to perform tasks that would otherwise require human labor6
• Adopting lean principles: eliminating waste and non-value-added activities from processes, such as overproduction, inventory, defects, waiting, transportation, motion, and overprocessing7
• Applying agile methods: using iterative and incremental approaches to deliver products or services that meet changing customer requirements and feedback
• Cross-training workers: training workers to perform multiple tasks or roles within a process or organization

References: 1: Operations Flexibility Definition 2 2: Why flexibility is critical when planning an operations - KPMG 4 3: Performance Objectives - What Are the 5 Business Objectives? - PeopleGoal 1 4: Competitive Priorities in Operations with Examples - StudiousGuy 5 5: Modular Design Definition 6: Automation Definition 7: Lean Principles Definition : Agile Methodology Definition : Cross-training Definition

 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 ….

A sales forecast that is based solely on shipment history is a method that uses past sales data to predict future sales. This method assumes that the sales pattern will remain consistent over time, and does not account for any changes or fluctuations in demand or supply1. Therefore, this method can be distorted by any factors that affect the availability or delivery of the products, such as material shortages.

Material shortages are situations where the supply of raw materials, components, or finished goods is insufficient to meet the demand. Material shortages can be caused by various reasons, such as natural disasters, supplier issues, transportation disruptions, quality problems, or demand spikes2. Material shortages can have a negative impact on the sales forecast that is based solely on shipment history, because they can reduce the amount of products that can be shipped to customers, and thus lower the sales revenue. Material shortages can also create a backlog of orders that cannot be fulfilled in time, and thus create a gap between the actual and forecasted sales3.

The other factors listed in the question typically would not distort a sales forecast that is based solely on shipment history, because they do not affect the shipment history directly. Labor rate changes are changes in the wages or salaries paid to workers. They may affect the production costs and profits, but not necessarily the sales volume or revenue4. Currency exchange rates are the rates at which one currency can be exchanged for another. They may affect the competitiveness and profitability of international sales, but not necessarily the sales volume or revenue5. Customer demands are the needs and preferences of customers for products or services. They may affect the sales potential and market share, but not necessarily the sales volume or revenue.

Finite loading is a capacity planning approach that considers adjustments to plans based on planned capacity utilization. It does not allow overloading of resources and schedules operations only when there is enough capacity available. Finite loading creates a more realistic schedule for the production processes than other approaches, such as infinite loading, that ignore the capacityconstraints and assume that the due dates of orders are absolute. Finite loading is not highly dependent on advanced computer software, although it can benefit from it. It is not only managed by shop floor supervisors, but also by planners and schedulers. It can use historical information, but it is not the only approach that can do so. Therefore, the fundamental difference between finite loading and other capacity planning approaches is that it considers adjustments to plans based on planned capacity utilization. References := CPIM Part 2 Exam Content Manual, Domain 6: Plan, Manage, and Execute Detailed Schedules, Section B: Schedule Production Activities, Subsection 1: Develop a detailed production schedule (p. 28)

Scrap allowance is a percentage or quantity of material that is expected to be lost or wasted during the production process. Scrap allowance is usually applied to the component items in a bill of materials (BOM), which is a document that lists the materials, quantities, and relationships required to produce an end item. An increase in the scrap allowance in an assembled item will result in replanning of the component items in material requirements planning (MRP), which is a system that calculates the timing and quantity of materials and resources needed to meet the production plan. Replanning of the component items in MRP means that the system will adjust the planned order releases, order quantities, and due dates of the component items to account for the increased scrap allowance. Replanning of the component items in MRP will ensure that enough material is available to meet the demand for the assembled item, and to avoid shortages or excess inventory.

References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.2: Implement Supply Plans, Subsection 4.2.1: Describe how to implement material requirements planning (MRP) (page 38).

Adopting a lean approach to manage supply chain throughput rather than a more traditional approach means that more capacity may be required. Throughput is the rate at which a system produces or processes its output. A lean approach is a philosophy that aims to eliminate waste and improve efficiency by focusing on customer value, continuous improvement, and pull systems. A traditional approach is a philosophy that relies on forecasting, push systems, and large batch sizes. A lean approach may require more capacity because it reduces inventory levels, buffers, and safety stocks, which may expose the system to more variability and uncertainty. More capacity may be needed to cope with fluctuations in demand or supply, and to maintain high service levels. A lean approach does not necessarily require less training, as it involves empowering employees, cross-training them, and involving them in problem-solving and improvement activities. A lean approach does not necessarily require more inventory, as it aims to minimize inventory and its associated costs. A lean approach does not necessarily result in longer cycle times, as it strives to reduce lead times, setup times, and waiting times. References: CPIM Exam Content Manual Version 7.0, Domain4: Plan and Manage Supply, Section 4.2: Supply Planning Methods, p. 26; Lean Manufacturing; Throughput.

Option overplanning is a technique used in an assemble-to-order (ATO) environment to address uncertainty in the product mix. An ATO environment is a production strategy where products are assembled from components or subassemblies after receiving customer orders1. Option overplanning is the practice of planning and stocking more components or subassemblies than the expected demand, based on historical data or forecasts2. The purpose of option overplanning is to increase the flexibility and responsiveness of the production system, by allowing the manufacturer to meet a variety of customer orders with different options or features. Option overplanning can help reduce the risk of stockouts, improve customer service, and capture new market opportunities.

Option overplanning is not used to verify appropriate inventory levels, schedule detailed production, or compensate for forecast bias. Verifying appropriate inventory levels is a function of inventory management, which involves monitoring and controlling the quantity and quality of materials and products in stock. Scheduling detailed production is a function of detailed scheduling, which involves allocating resources and setting priorities for specific tasks or orders in the production process. Compensating for forecast bias is a function of demand management, which involves adjusting the forecasts based on the difference between the actual and predicted demand.

References: Assemble-to-Order (ATO): Overview, Examples, Pros and Cons - Investopedia; Assemble-to-Order - Overview, How It Works, Advantages; [Assemble-to-Order (ATO) Definition | Operations & Supply Chain Dictionary]; [Assemble-to-Order (ATO) - MBA Skool-Study.Learn.Share.]; [InventoryManagement - Definition, Types, Objectives and Examples]; [Detailed Scheduling - an overview | ScienceDirect Topics]; [Forecast Bias - an overview | ScienceDirect Topics].

Standardized containers are containers that have uniform dimensions and specifications, such as pallets, crates, boxes, etc. Standardized containers can facilitate transportation efficiency and inventory management by reducing the handling time, increasing the loading capacity, improving the space utilization, and simplifying the packaging and labeling processes. Standardized containers can also enable the use of automated storage/retrieval systems (AS/RS) and other technologies that require consistent dimensions and weights of the items. References: CPIM Part 2 Exam Content Manual, Domain 7: Plan and Manage Distribution, Section 7.1: Distribution Network Design, p. 38.

To successfully empower individuals to drive change, an organization should ensure everyone can clearly articulate the business’s vision and strategy. According to various sources, such as Forbes, Mercuri Urval, and LSA Global, one of the key factors for effective change leadership is to communicate a powerful and compelling change vision that inspires and motivates employees to support the change. A change vision is a statement that describes the desired future state of the organization after the change is implemented, and how it aligns with the overall business vision and strategy1. A clear and consistent change vision can help employees understand the purpose and benefits of the change, as well as their roles and responsibilities in the change process2. A change vision can also help create a sense of urgency, direction, and alignment among employees, as well as foster a culture of empowerment and participation3.

The other options are not sufficient or necessary to successfully empower individuals to drive change. Conducting thorough training programs for all levels of employees is important, but not enough to empower them to drive change. Training can help employees acquire the skills and knowledge needed to perform their tasks in the new situation, but it does not necessarily influence their attitudes, beliefs, or behaviors toward the change1. Aligning performance appraisals with the business’s vision is also helpful, but not essential to empower individuals to drive change. Performance appraisals can provide feedback, recognition, and incentives for employees who demonstrate the desired behaviors and outcomes related to the change, but they do not address the underlying motivations, emotions, or barriers that may affect employees’ willingness or ability to change4. Establishing and tracking broad change metrics on a quarterly basis is also useful, but not critical to empower individuals to drive change. Change metrics can help measure the progress and impact of the change initiatives, but they do not necessarily engage or involve employees in the change process or give them a sense of ownership or autonomy over the change5.

References: CPIM Part 2 Exam Content Manual, Domain 8: Manage Quality, Continuous Improvement, and Technology, Section 8.2: Continuous Improvement Concepts and Tools, p. 61-62; 5 Ways To Empower And Engage Employees To Lead Change - Forbes; How to successfully drive change in your organisation - Mercuri Urval; Empower Employees to Effect Change - 4 Ways | LSA Global; Empowering Teams to Drive Change Sustainably; Change Management Metrics: How To Measure Your Change Management Project.

According to the CPIM Exam Content Manual, a make-or-buy decision is a strategic decision that involves choosing between manufacturing a product or service internally or purchasing it from an external supplier1. A make-or-buy decision is based on a cost-benefit analysis that considers various factors, such as quality, cost, capacity, lead time, technology, and competitive advantage2.

Some of the potential reasons to make instead of buy a product may include:

• Maintain quality: Making a product internally may allow the firm to control and ensure the quality standards of the product, which may affect customer satisfaction and loyalty. Buyinga product from an external supplier may involve quality risks or uncertainties, especially if the supplier is located in a different country or has different quality systems3.
• Reduce cost: Making a product internally may reduce the total cost of ownership of the product, which includes not only the purchase price, but also the costs of transportation, inventory, inspection, warranty, and maintenance. Buying a product from an external supplier may incur higher total costs due to these factors.
• Keep confidential processes within the firm: Making a product internally may protect the firm’s proprietary or confidential processes that give it a competitive edge in the market. Buying a product from an external supplier may expose the firm’s processes to potential imitation or leakage.

Therefore, the correct answer is C. maintain quality, reduce cost, and keep confidential processes within the firm.

References:

• CPIM Exam Content Manual
• Make-or-Buy Decision Explained: How to Make Outsourcing Decisions
• Make or Buy Decision - What Is It, Examples, Factors, Advantages
• Make-or-Buy Decision - Overview, How It Works, Triggers
• Make or Buy Decision - Definition & Examples | Marketing Tutor

The output of the equipment on Day 6 can be calculated by multiplying the demonstrated capacity, the utilization, and the efficiency. The demonstrated capacity is given as $1,200 per day. The utilization is the ratio of the actual time that the equipment is used to the available time that it could be used. Since the utilization is reduced by 25% on Day 6, it means that the equipment is used for 75% of the available time. Therefore, the utilization is 0.75. The efficiency is the ratio of the actual output to the standard output. It is given as 110%, which means that the equipment produces 10% more than the standard output. Therefore, the efficiency is 1.1. The output on Day 6 can be found by multiplying these three factors:

Output = Demonstrated capacity x Utilization x Efficiency Output = $1,200 x 0.75 x 1.1 Output = $990

Therefore, the output on Day 6 is $990. References: CPIM Part 2 Exam Content Manual, Version 7.0, Domain 6: Plan, Manage, and Execute Detailed Schedules, Section A: Detailed Capacity Planning and Scheduling, Subsection 2: Capacity Management Concepts and Calculations, p. 37-38.

A capacity-leading strategy is a proactive approach that adds or subtracts capacity in anticipation of future market demand. It is an aggressive strategy with the objective of improving the service level and decreasing lead time1. An advantage of adopting a capacity-leading strategy is that there issufficient capacity to meet demand, which means that the organization can satisfy customer needs and expectations, as well as capture new market opportunities. A capacity-leading strategy can also help the organization gain a competitive edge by being the first to offer new products or services, or by lowering prices due to economies of scale2.

The other options are not advantages of adopting a capacity-leading strategy. There is not necessarily sufficient demand to consume capacity, which means that the organization may face overcapacity problems, such as high inventory costs, low utilization rates, and reduced profitability3. All demand is not satisfied, and profit is not maximized, because there may be other factors that affect customer satisfaction and profitability, such as quality, price, or service4. Overcapacity problems are not minimized, but rather increased, by adopting a capacity-leading strategy, because the organization may have more capacity than needed if demand does not increase as expected3.

References: CPIM Part 2 Exam Content Manual, Domain 4: Plan and Manage Supply, Section 4.1: Supply Management Concepts and Tools, p. 33-34; Capacity Planning Strategies: Types, Examples, Pros And Cons - Toggl; Lead Capacity Strategy, Lead Demand Strategy - UniversalTeacher.com; Capacity Planning Strategies For End-to-End Supply Chain Profitability; Capacity Planning Strategies: Types, Examples, Pros And Cons - Toggl.

 A bill of distribution is a document that specifies the planned channels of inventory disbursement from one or more sources to field warehouses. A bill of distribution is similar to a bill of materials, but it applies to the distribution stage rather than the production stage. A bill of distribution helps to optimize the inventory level, reduce transportation costs, and improve customer service. A bill of distribution considers the factors such as demand patterns, lead times, costs, and capacities of the sources and warehouses.

The other options are not documents that specify the planned channels of inventory disbursement from one or more sources to field warehouses. A supply chain community is a network of organizations that collaborate and coordinate their activities to deliver products or services to customers. A supply chain community includes suppliers, manufacturers, distributors, retailers, and customers. A supply chain community helps to improve the visibility, efficiency, and responsiveness of the supply chain. Interplant demand is the demand for a product or component that is generated by another plant within the same organization. Interplant demand is usually transferred through internal orders or shipments. Interplant demand helps to balance the capacity and resources among different plants. Logistics data interchange (LDI) is a system that enables the exchange of information and documents among different parties involved in the logistics process. LDI uses electronic data interchange (EDI) or other technologies to transmit data such as orders, invoices, shipment notices, and tracking information. LDI helps to improve the accuracy, speed, and security of the logistics transactions. References: CPIM Exam Content Manual Version 7.0, Domain 7: Plan and Manage Distribution, Section 7.1: Distribution Planning Concepts, p. 40; Bill of Distribution; Supply Chain Community.

The production plan is a statement of the resources needed to meet the aggregate demand plan over a medium-term horizon. The production plan is the output of the supply planning step in the sales and operations planning (S&OP) process. The production plan relates to a firm’s financial planning because it is used to identify future cash needs. Cash needs are the amount of money that a firm requires to operate and grow its business. Cash needs can be influenced by various factors, such as sales revenue, cost of goods sold, operating expenses, capital expenditures, inventory levels, accounts receivable, accounts payable, and taxes. The production plan can help to estimate the cash inflows and outflows associated with these factors, and to determine the optimal balance between them. The production plan can also help to identify the potential sources and uses of cash, such as borrowing, investing, or paying dividends. By identifying future cash needs, the production plan can help to improve the firm’s liquidity, profitability, and solvency.

References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.1: Develop Supply Plans, Subsection 4.1.2: Describe how to develop a production plan (page 36).

Liability risk in the supply chain is the risk that a company may be held legally responsible for damages caused by its products or services, or by its business partners, such as suppliers, subcontractors, or customers1. Liability risk can result in financial losses, legal penalties, reputational damage, and customer dissatisfaction1.

One way to mitigate liability risk in the supply chain is to require traceability for components, which means the ability to track the origin, history, location, and status of a product or its parts throughout the supply chain2. Traceability can help a company to identify and prevent potential quality issues, defects, recalls, counterfeits, or frauds that may cause harm to the customers or the environment2. Traceability can also help a company to comply with regulatory standards, customer requirements, and social responsibility expectations2. Traceability can be achieved by using various methods, such as barcodes, RFID tags, serial numbers, blockchain, or cloud-based platforms3.

The other options are not effective ways to mitigate liability risk in the supply chain. Negotiating lower component cost may reduce the procurement expenses, but it may also compromise the quality and safety of the components, which may increase the liability risk. Pushing inventory to supplier locations may reduce the inventory carrying costs and risks, but it may also increase the dependency and vulnerability on the suppliers, which may expose the company to more liability risk. Using LTL shipments more frequently may reduce the transportation costs and emissions, but it may also increase the handling and damage risks of the products, which may affect the customer satisfaction and liability.

References : Understanding Supply Chain Risk: Liabilities | Avetta; What is Traceability in Supply Chain Management?; How to Achieve Supply Chain Traceability.

Up-to-date information about production order status is required to calculate the cost of work in process (WIP). WIP is the inventory of unfinished goods or partially completed products that are still in the production process1. The cost of WIP is the sum of the costs of the materials, labor, and overhead that have been incurred in the production process but have not yet been transferred to the finished goods inventory2. To calculate the cost of WIP, we need to know how much of each production order has been completed and how much remains to be done. This information can be obtained from the production order status, which is a report that shows the current status of each production order in terms of its quantity, start date, end date, completion percentage, and variance3. By using the production order status, we can determine the amount of WIP for each production order and for the entire production process. This can help us monitor and control the production efficiency, profitability, and quality4.

References: 1: Work In Progress (WIP) Definition 2 2: Work-in-Process (WIP) Accounting 3 3: Production Order Status Report 5 4: How to Calculate Work in Process Inventory 6

A move from acceptance sampling to 100% inspection would be caused by the circumstance of downstream operators encountering recurring defects. Acceptance sampling is a quality control technique that uses statistical sampling to determine whether to accept or reject a production lot of material. It is employed when one or several of the following hold: testing is destructive; the cost of 100% inspection is very high; and 100% inspection takes too long1. 100% inspection is a quality control technique that examines every item in a production lot for defects or nonconformities. It is employed when the cost of passing a defective item is very high; testing is nondestructive; and 100% inspection does not take too long2.

Downstream operators are the workers or machines that perform the subsequent operations or processes on the products after they have been inspected or tested. Downstream operators encountering recurring defects means that the products that have passed the acceptance sampling or testing are still found to be defective or nonconforming by the downstream operators. This can indicate that the acceptance sampling or testing is not effective or reliable in detecting or preventing defects or nonconformities. This can also result in negative consequences, such as rework, waste, delays, customer complaints, or safety issues. Therefore, this circumstance would cause a move from acceptance sampling to 100% inspection, as it would require a more thorough and rigorous quality control technique to ensure that no defective or nonconforming products are passed to the downstream operators.

The other options are not circumstances that would cause a move from acceptance sampling to 100% inspection. History shows that the quality level has been stable from lot to lot is not a circumstance that would cause a move from acceptance sampling to 100% inspection, but rather a circumstance that would support the use of acceptance sampling. Quality level is the proportion of conforming items in a production lot. Quality level being stable from lot to lot means that there is little variation or fluctuation in the quality of the products over time. This can indicate that the production process is under control and consistent in meeting the quality standards or specifications. Therefore, this circumstance would support the use of acceptance sampling, as it would reduce the risk of accepting a defective lot or rejecting a conforming lot.

The company uses one of its qualified suppliers is not a circumstance that would cause a move from acceptance sampling to 100% inspection, but rather a circumstance that would support the use of acceptance sampling. A qualified supplier is a supplier that has met certain quality, delivery, and service standards and has been approved by the company to supply goods or services without inspection or testing. A qualified supplier is expected to maintain a high level of performance and reliability, as well as to report any issues or deviations that may affect the delivery process. Therefore, this circumstance would support the use of acceptance sampling, as it would reduce the need for 100% inspection by relying on the supplier’s quality assurance system.

The percent of defects is expected to be greater than 5% is not a circumstance that would cause a move from acceptance sampling to 100% inspection, but rather a circumstance that would require a change in the acceptance sampling plan. The percent of defects is the proportion of defective items in a production lot. The percent of defects being expected to be greater than 5% means that there is a high probability of finding defective items in the production lot. This can indicate that the production process is out of control or inconsistent in meeting the quality standards or specifications. Therefore, this circumstance would require a change in the acceptance sampling plan, such as reducing the acceptable quality limit (AQL), increasing the sample size, or decreasing the acceptance number, to increase the likelihood of rejecting a defective lot.

References := Acceptance Sampling - an overview | ScienceDirect Topics, What Is Acceptance Sampling? Definition And Examples

 An outlier is a data point that falls outside of the expected range of the data, i.e., it is an unusually large or small data point1. Outliers can have a significant adverse impact on the forecasts, as they can skew the data distribution and distort the statistical analysis2. Therefore, it is important to detect and remove outliers from the demand data before generating forecasts.

One of the techniques that can be used to detect outliers is to use the standard deviation of the data, or the equivalent z-score, to determine the outlier limit3. For example, one approach is to set the lower limit to three standard deviations below the mean, and the upper limit to three standard deviations above the mean. Any data point that falls outside this range is detected as an outlier.

However, detecting outliers is not enough. The most appropriate next step would be to screen the outlier for manual review. This means that the detected outlier should be examined by a humanexpert to determine whether it is a true outlier or not, and whether it should be corrected or not4. This is because not all outliers are erroneous or irrelevant. Some outliers may be valid observations that reflect real changes in demand, such as seasonal peaks, promotional effects, or market trends. In such cases, correcting or removing the outliers may lead to inaccurate or biased forecasts.

Therefore, screening the outlier for manual review can help verify the cause and validity of the outlier, and decide on the best course of action. Some of the possible actions are:

• Correcting the outlier: replacing the outlier with a more typical value based on historical data or expert judgment. This can smooth out the data and reduce the noise.
• Separating the demand streams: splitting the data into two or more series based on different factors that influence demand, such as product type, customer segment, or distribution channel. This can isolate the outliers and allow different forecasting methods to be applied to each series.
• Adjusting the forecasting model: modifying the parameters or assumptions of the forecasting model to account for the outliers, such as using a different smoothing factor, trend component, or error term. This can improve the fit and accuracy of the model.

References: 1: Outlier Definition 1 2: How to Forecast Data Containing Outliers 2 3: How to Detect Outliers in Machine Learning – 4 Methods for Outlier Detection 1 4: How Outlier Detection and Correction Works 4 : How to Understand What is an Outlier in Forecasting 3

Mixed-model scheduling is a production technique that allows for the simultaneous production of different products or features on the same production line or system. Mixed-model scheduling can help reduce lead times, inventory levels, setup times, and material shortages by increasing the flexibility and responsiveness of the production process. One of the benefits of mixed-model scheduling is improved demand response, which means the ability to meet customer demand without delay or stockout. Improved demand response can enhance customer satisfaction and loyalty, as well as reduce the need for safety stock or buffer inventory. By using mixed-model scheduling, a company can produce products or features according to the actual or forecasted customer demand, rather than producing large batches of standardized products or features. This can help avoid overproduction or underproduction, which can result in excess inventory or lost sales. Mixed-model scheduling can also help adjust the production output quickly and easily when there are changes or fluctuations in demand, by using flexible automation, lean production techniques, or quick response methods.

The other options are not benefits of mixed-model scheduling. Increased inventory is not a benefit of mixed-model scheduling, but rather a drawback. Increased inventory can increase inventory costs, such as holding costs, transportation costs, or obsolescence costs. It can also reduce inventory visibility and control, as well as increase the risk of quality issues or spoilage. Mixed-model scheduling can help reduce inventory by producing products or features in small batches or single units that match customer demand. Fewer setups are not a benefit of mixed-model scheduling, but rather a requirement. Fewer setups mean less time and resources spent on changing or adjusting the production system to produce different products or features. Fewer setups can increase the efficiency and productivity of the production process, as well as reduce the setup costs and waste. Mixed-model scheduling requires fewer setups to enable the simultaneous production of different products or features on the same production line or system. Fewer material shortages are not a benefit of mixed-model scheduling, but rather an outcome. Fewer material shortages mean less disruption or delay in the production process due to the lack of materials or components needed for production. Fewer material shortages can improve the quality and reliability of the production process, as well as reduce the material costs and waste. Mixed-model scheduling can result in fewermaterial shortages by reducing the lead times and inventory levels of materials or components, as well as by improving the communication and coordination with suppliers.

References := Mixed Model Scheduling - Mountain Home Academy, Reduce Lot Sizes, Mixed Model Scheduling - Academic library, Introduction To Mixed Model Production …{Strategos}

Offering digital downloads only may result in an increased possibility of loss of intellectual property, as this exposes the online retailer to the risk of cyber theft and piracy. Digital downloads are easier to copy, distribute, and modify without authorization than hard copy books, and the online retailer may lose control over its IP rights and revenues. Cyber thieves may hack into the online retailer’s network and steal its IP assets, such as the content, design, and format of the books. Pirates may also offer illegal copies of the books to consumers at lower prices or for free, undermining the online retailer’s market share and profitability. According to Deloitte Insights, IP cyber theft has largely remained in the shadows compared with more familiar cybercrimes such as the theft of credit card, consumer health, and other personally identifiable information1. However, IP cyber theft can have serious consequences for a company’s future, as IP is the heart of the 21st-century company, an essential motor driving innovation, competitiveness, and the growth of businesses and the economy as a whole1. The WIPO Magazine also notes that digital technology has made IP theft easier, as Bad Actors use technology to flood the online market with pirated and counterfeit goods2. The impact of IP theft on the economy can be significant, as it can result in loss of legitimate sales, reduced tax revenues, lower employment opportunities, and diminished incentives for innovation3. Therefore, an online retailer that moves from delivering hard copy books to offering digital downloads only should take appropriate measures to protect its IP from cyber theft and piracy. This may include using encryption, digital rights management, watermarking, authentication, and monitoring technologies, as well as educating consumers about the value and benefits of legal downloads

 Apush system is a production system that operates based on planned or forecasted demand, rather than actual or current demand. In a push system, work orders or tasks are released to the work centers according to a predetermined schedule, regardless of the availability of capacity or resources at the work centers. This means that work centers may receive work even if they are already overloaded or have no idle time, which can result in long lead times, high inventory levels, and poor customer service1.

The other options are more likely to occur when using a pull system, which is a production system that operates based on actual or current demand, rather than planned or forecasted demand. In a pull system, work orders or tasks are released to the work centers only when there is a need or a request from the downstream work centers or customers. This means that work centers are scheduled using finite capacity planning, which is a method of allocating capacity and resources based on the actual availability and constraints of the work centers2. Work centers also operate using decentralized control, which means that each work center has the autonomy and authority to make decisions based on the local conditions and signals from the environment3. Work centers also signal previous work centers when they are ready for more work, which is a way of synchronizing the flow of materials and information along the production process4.

References: Push System vs. Pull System: Adopting A Hybrid Approach To MRP; Push Systems vs. Pull System: Definitions and Differences; JUST-IN-TIME MANUFACTURING | SpringerLink; 9 Just-In-Time and Lean Systems - Seneca College.

 A queue is the number of hours that a work order sits in front of a work center before it starts. It also includes the move time required to physically move partially completed items from the previous operation to the next work center1. A queue is used to provide a buffer between the time that a component arrives at a machine or work center and when the operation actually starts2. A queue can help to neutralize delays in previous operations and to reduce the waiting time and flow time of the work orders3.

An order that moves into a work center on schedule following completion of a previous operation will move into the queue in priority sequence. This means that the order will be placed in the queue according to its priority level, which is determined by the priority control technique used for the production system. A priority control technique is a method of determining the sequence and timing of production orders in a manufacturing system4. Some examples of priority control techniques are first-come, first-served (FCFS), shortest processing time (SPT), earliest due date (EDD), and critical ratio (CR). Depending on the priority control technique, an order may move to the beginning, end, or middle of the queue.

An order will not necessarily move to the end or the beginning of the queue, as these positions depend on the priority level of the order and the other orders in the queue. An order will not move into the queue when there is capacity available, as this implies that there is no queue at all. Capacity is the amount of time or resources available for production at a work center5. Capacity can be affected by factors such as machine availability, labor skills, setup time, and maintenance. Capacity planning is a function of determining and adjusting the optimal level of resources needed to meet the demand5.

The priority rule that is most consistent with the objective of meeting due dates is slack time per operation. Slack time per operation is a priority rule that assigns a priority index to each job based on the ratio of the remaining slack time to the remaining number of operations. Slack time is the difference between the due date and the expected completion time of a job. A lower ratio means a higher priority, as it indicates that the job has less slack time per operation and is more likely to be late. Slack time per operation is a dynamic priority rule, as it updates the priority index after each operation is completed. Slack time per operation can help minimize the number of tardy jobs and the average tardiness of jobs, as it gives preference to the jobs that are closer to their due dates and have more operations left.

First-come-first-served (FCFS) is not a priority rule that is consistent with the objective of meeting due dates. FCFS is a priority rule that processes jobs in the order of their arrival or release times. FCFS is a simple and fair rule, but it ignores the processing times and due dates of jobs. FCFS can result in poor due date performance, as it can delay urgent or short jobs behind long or non-urgent jobs.

Shortest processing time (SPT) is not a priority rule that is consistent with the objective of meeting due dates. SPT is a priority rule that processes jobs in ascending order of their processing times. SPT is an effective rule for minimizing the average flow time and work-in-process inventory of jobs, as it clears out small jobs quickly and reduces congestion in the system. However, SPT does not consider the due dates of jobs, and it can make long or urgent jobs late.

Fewest operations remaining is not a priority rule that is consistent with the objective of meeting due dates. Fewest operations remaining is a priority rule that processes jobs in ascending order of their remaining number of operations. Fewest operations remaining is a rule that can reduce the variability and complexity of jobs, as it tends to complete jobs faster and reduce their flow times. However, fewest operations remaining does not take into account the slack times or due dates of jobs, and it can make urgent or short jobs late.

References := Priority Rules - Tripod, Dispatching rules - Oxford Reference, Sequencing Rules and Due-Date Assignments in a Job Shop - JSTOR

In a lean environment, the batch-size decision for planning “A” items would be done by lot-for-lot (L4L). A lean environment is a production system that aims to eliminate waste and maximize value by applying the principles and practices of lean manufacturing1. “A” items are the most important items in an inventory system, based on the Pareto principle or the 80/20 rule, which states that 80%of the effects come from 20% of the causes2. Lot-for-lot (L4L) is an inventory ordering policy that orders exactly the quantity needed to meet the demand for each period3.

The reason why L4L is the preferred batch-size decision for planning “A” items in a lean environment is because it minimizes the inventory holding costs and reduces the risk of obsolescence or deterioration of the items3. L4L also supports the concept of pull production, which is a key element of lean manufacturing. Pull production is a method of controlling the flow of materials and information by producing only what is requested by the downstream customers or processes4. L4L aligns the production and consumption rates of “A” items, which are typically high-demand and high-value items, and avoids overproduction or underproduction. L4L also enables faster feedback and learning, as well as better responsiveness to customer needs and expectations.

The other options are not as suitable for planning “A” items in a lean environment. Least total cost is an inventory ordering policy that orders the quantity that minimizes the sum of ordering costs and holding costs5. However, this policy does not consider the demand variability or customer service level, and may result in large batch sizes that increase inventory levels and waste. Min-max is an inventory ordering policy that orders a fixed quantity whenever the inventory level falls below a minimum level6. However, this policy does not reflect the actual demand or consumption rate, and may result in excess inventory or stockouts. Periodic order quantity is an inventory ordering policy that orders a variable quantity at fixed time intervals. However, this policy does not synchronize the production and consumption rates, and may result in mismatched supply and demand.

References: Lean Manufacturing - Definition & Principles - ASQ; Pareto Principle - Definition & Examples - Investopedia; Lot-for-Lot (L4L) Definition | Operations & Supply Chain Dictionary; Pull Production - Definition & Examples - ASQ; Economic Order Quantity (EOQ) Definition - Investopedia; Min-Max Inventory Management: Definition & Examples - Video & Lesson Transcript | Study.com; [Periodic Order Quantity (POQ) Definition | Operations & Supply Chain Dictionary].

Compared to traditional supplier relationships, a more strategic view of supplier relationships would require maintaining communication based on trust. Trust is a key factor that enables effective collaboration, information sharing, problem solving, and innovation between supply chain partners12. Trust can also reduce transaction costs, conflicts, and opportunism, and increase commitment, loyalty, and performance34. Therefore, maintaining communication based on trust is essential for developing and sustaining strategic supplier relationships that can create value and competitive advantage for both parties.

The other options are not necessarily required for a more strategic view of supplier relationships, because they are either insufficient or irrelevant. Offering the supplier more business may increase the volume or frequency of transactions, but it does not guarantee a more strategic or long-term relationship. Adopting electronic data interchange (EDI) may improve the efficiency or accuracy of information exchange, but it does not ensure a more collaborative or innovative relationship. Implementing concurrent engineering may enhance the product design or development process, but it does not address the other aspects of a strategic relationship, such as quality, delivery, or risk management.

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.

Safety stock is a type of inventory that is held in excess of the expected demand to protect against uncertainties such as demand variability, lead time variability, or supply disruptions. Safety stock can help to reduce the risk of stockouts, which are situations where the inventory level falls below thedemand level and the customer orders cannot be fulfilled. Safety stock can be determined by using different methods, such as statistical models, service level policies, or empirical rules. One of the common criteria that is used to determine safety stock in a distribution center (DC) is the probability of stocking out, which is the likelihood that the inventory level will be insufficient to meet the demand during a replenishment cycle. The probability of stocking out can be calculated by using the normal distribution, assuming that the demand and lead time are normally distributed. The probability of stocking out can also be expressed as the complementary value of the service level, which is the percentage of customer orders that can be satisfied from the available inventory. A higher probability of stocking out implies a lower service level and a lower safety stock. A lower probability of stocking out implies a higher service level and a higher safety stock.

References: CPIM Exam Content Manual Version 7.0, Domain 7: Plan and Manage Distribution, Section 7.2: Implement Distribution Plans, Subsection 7.2.2: Describe how to implement inventory management techniques in distribution (page 68).

Locating service facilities differs from locating manufacturing or distribution facilities primarily because service location decisions are driven by revenue concerns, while manufacturing and distribution location decisions are driven by costs. This is because service facilities are usually closer to the customers and depend on their demand and preferences. Service facilities need to consider factors such as customer convenience, accessibility, visibility, traffic, and competition when choosing a location, as these factors affect the revenue potential and market share of the service facility1. Manufacturing and distribution facilities, on the other hand, are usually farther from the customers and depend on their supply chain efficiency and effectiveness. Manufacturing and distribution facilities need to consider factors such as transportation, labor, utilities, taxes, and regulations when choosing a location, as these factors affect the cost structure and profitability of the facility2.

The other options are not correct. Competition is a factor that affects both service and manufacturing or distribution location decisions, as it influences the market attractiveness and strategic positioning of the facility3. Real estate costs are also a factor that affects both service and manufacturing or distribution location decisions, as they represent a significant portion of the fixed costs of the facility4. Surveying customers or suppliers is a method that can be used for both service and manufacturing or distribution location decisions, as it provides valuable information about the demand and supply characteristics of the market5.

References : Service Facility Location: A Review of Applications and Methods; Facility Location - Factors Influencing the Location; Competitive Environment: Definition, Examples & Factors - StudySmarter US; Facility Location | IntechOpen; Seven Key Factors to a Facility Location - Chron.com.

Activity-based costing (ABC) is a method of allocating costs to products or services based on the activities that consume resources in the production or delivery process. ABC identifies the cost drivers, which are the factors that cause or influence the amount of resources used for each activity. ABC then assigns costs to products or services based on the amount of cost drivers they use. An advantage of ABC is that it uses cost drivers to allocate costs to products, which provides a more accurate and realistic picture of the cost structure and profitability of each product or service. ABC helps to identify the value-added and non-value-added activities, and to eliminate or reduce the waste and inefficiency in the process. ABC does not allow raw material costs to be allocated on a per unit basis, as raw material costs are usually considered as direct costs that can be traced to each product or service. ABC does not make it easier to establish standard costs, which are the predetermined or expected costs of producing or delivering a product or service. ABC does not enable overhead costs to be allocated evenly across all products, as overhead costs are the indirect costs that cannot be traced to each product or service. ABC allocates overhead costs based on the cost drivers, which may vary for different products or services. References: CPIM Exam Content Manual Version 7.0, Domain 8: Manage Quality, Continuous Improvement, and Technology, Section 8.2: Continuous Improvement Concepts, p. 46; Activity-Based Costing (ABC) Definition; Activity-based costing.

Multiple sourcing is an outsourcing approach in which products or services are contracted to various suppliers needed to conduct the business instead of using traditional single sourcing1. One of the potential advantages of multiple sourcing is that it can lower the price of the products or services, as it creates competition among the suppliers and gives the buyer more bargaining power2. Another potential advantage of multiple sourcing is that it can reduce the risk of supply disruptions, as it diversifies the supply chain and makes the buyer less dependent on any single supplier3. If one supplier fails to deliver due to unforeseen circumstances, such as natural disasters, political instability, or quality issues, the buyer can switch to another supplier or use a combination of suppliers to meet the demand4. Therefore, multiple sourcing can provide lower price and reduced risk as potential advantages in the supplier selection process.

References: 1: Multi-Sourcing: Everything You Need To Know - SupplierGATEWAY 3 2: Dual sourcing: Advantages and disadvantages - Hermes Supply Chain Blog 4 3: The Case for Making Multiple Suppliers Part of Your Supply Chain Strategy 5 4: Using Multi-Sourcing to Diversify the Supply Chain 6

Exponential smoothing is a forecasting technique that uses a weighted average of past and present data to predict future values. It is suitable for time series data that have a stable or slowly changing trend and no significant seasonal variations. Exponential smoothing assigns more weight to the most recent data, giving it a higher influence on the forecast. This makes it more responsive to changes in demand patterns than other techniques, such as moving average or time series decomposition, which use fixed weights or historical data. The Delphi method is a qualitative technique that involves a panel of experts who provide their opinions and feedback on a topic through multiple rounds of surveys. It is not based on historical data or mathematical formulas, but rather on human judgment and consensus. Therefore, it is not appropriate for developing a forecast. References: CPIM Part 2 Exam Content Manual, Version 7.0, Domain 3: Plan and Manage Demand, Section A: Demand Management, Subsection 2: Forecasting Techniques and Methods, p. 14-15.

A customer value proposition (CVP) is a statement that summarizes the benefits that a product or service offers to a target customer segment1. A CVP can help a company differentiate itself from its competitors by highlighting its unique value proposition (UVP), which is the main reason why customers should choose its product or service over others2. A CVP can also help a company communicate its value to its customers, increase customer satisfaction and loyalty, and improve its market position3.

One of the strategies that can improve the effectiveness of a CVP and enhance its differentiation in the market is to adopt best practices that improve product design. Product design is the process of creating a new product or service that solves a customer problem or fulfills a customer need4. By improving product design, a company can create products or services that are more desirable, feasible, and viable for its customers5. Some of the best practices that can improve product design are:

• Understanding the customer: conducting research and analysis to identify the customer segments, their jobs, pains, and gains, and their expectations and preferences. This can help create products or services that are tailored to the customer needs and wants, and deliver value that exceeds their expectations.
• Using the Value Proposition Canvas: a tool that helps design, test, create, and manage products and services that customers actually want. The Value Proposition Canvas consists of two parts: the Customer Profile, which describes the customer segment in terms of their jobs, pains, and gains; and the Value Map, which describes how the product or service creates value for the customer by addressing their jobs, relieving their pains, and creating their gains. The Value Proposition Canvas can help align the product or service with the customer needs and wants, and create a fit between them.
• Applying design thinking: a human-centered approach to innovation that integrates the needs of people, the possibilities of technology, and the requirements of business. Design thinking involves five phases: empathize, define, ideate, prototype, and test. Design thinking can help create products or services that are desirable for the customers, feasible for the technology, and viable for the business.
• Incorporating feedback loops: collecting and analyzing data from customers and stakeholders to measure the performance and impact of the product or service. Feedback loops can help validate the assumptions and hypotheses about the customer needs and wants, test the effectiveness of the value proposition, and identify areas for improvement or innovation.

Therefore, by adopting best practices that improve product design, a company can create products or services that deliver superior value to its customers, and differentiate itself from its competitors in the market.

References: 1: Customer Value Proposition Definition 3 2: Unique Value Proposition Definition 4 3: How to Write a Value Proposition (+ 6 Modern Examples) 5 4: Product Design Definition 5: What is Product Design? : Customer Discovery: The Ultimate Guide : Value Proposition Canvas – Download the Official Template 3 : What is Design Thinking? : Feedback Loop Definition

Producing to backorders means that the company only produces goods when there is a confirmed customer order. This strategy is most appropriate during times of highly fluctuating demand, as it allows the company to avoid holding excess inventory that may incur high carrying costs and become obsolete. Producing to backorders also enables the company to adjust its workforce according to the actual demand, which can be easily changed as the question states. This strategy can improve customer satisfaction, as the products are tailored to the specific needs and preferences of each customer. However, producing to backorders also has some drawbacks, such as longer lead times, higher production costs, and lower economies of scale.

The other strategies are less suitable for highly fluctuating demand. Producing at a constant level means that the company produces goods at a fixed rate regardless of the demand fluctuations. This strategy can result in either excess inventory or stockouts, depending on whether the demand is lower or higher than the production level. Producing to the sales forecast means that the company produces goods based on the projected demand for a certain period. This strategy can be effective if the forecast is accurate, but it can also lead to inventory imbalances if the forecast is inaccurate or if there are unexpected changes in demand. Producing to demand means that the company produces goods based on the current demand in the market. This strategy can be responsive and flexible, but it can also be challenging to implement, as it requires high visibility, coordination, and agility in the supply chain.

References : CPIM Part 2 Exam Content Manual, Domain 4: Plan and Manage Supply, Section B: Production Planning and Control, Subsection 1: Production Strategies and Techniques, Page 19.

 Vendor-managed inventory (VMI) is a type of supply chain collaboration where the supplier takes responsibility for managing the inventory levels and replenishment orders of the buyer. VMI provides a benefit to the buying company in several ways, such as improving service levels, reducing stockouts, increasing visibility, and enhancing trust. One of the specific benefits of VMI is that it reduces administrative expenses for the buying company. Administrative expenses are the costs associated with the general operations and management of the business, such as salaries, rent, utilities, office supplies, and communication. VMI reduces administrative expenses by eliminating or simplifying the tasks related to inventory management, such as forecasting, ordering, invoicing, and payment. VMI also reduces administrative expenses by streamlining the communication and coordination between the buyer and the supplier, and by reducing the errors and disputes that may arise from inventory discrepancies.

References: CPIM Exam Content Manual Version 7.0, Domain 7: Plan and Manage Distribution, Section 7.1: Develop Distribution Plans, Subsection 7.1.3: Describe how to develop supplier-customer relationships (page 66).

A reduction in purchased lot sizes will reduce inventory levels. Purchased lot sizes are the quantities of inventory that a stage of the supply chain either produces or purchases at a given time1. Inventory levels are the amount of stock available throughout the distribution network2. By reducing the purchased lot sizes, a company can lower the amount of inventory it holds, which can reduce the inventory costs, such as holding costs, shortage costs, and order costs3.

Holding costs are the costs associated with storing and maintaining inventory, such as rent, utilities, insurance, taxes, depreciation, and obsolescence4. Shortage costs are the costs incurred when demand exceeds supply, such as lost sales, customer dissatisfaction, and backorder costs4. Order costs are the costs involved in placing and receiving orders, such as transportation, inspection, setup, and administrative costs4.

Reducing the purchased lot sizes can lower the holding costs by decreasing the average inventory in the supply chain due to either production or purchases in lot sizes that are larger than those demanded by the customer1. This is also known as cycle inventory1. Reducing the purchased lot sizes can also lower the shortage costs by increasing the frequency of orders and decreasing the lead time between orders5. This can help avoid stockouts and meet customer demand more consistently. Reducing the purchased lot sizes can also lower the order costs by optimizing the order quantity based on the trade-off between holding costs and order costs. This is also known as economic order quantity (EOQ).

Therefore, a reduction in purchased lot sizes will reduce inventory levels and inventory costs.

References: 1: Chapter 11 Flashcards by Amy Horton 3 2: Optimal Inventory Levels: Calculate & Manage Your Stock Levels 2 3: Inventory Levels Explained: The Highs & Lows Of Optimal Stock 1 4: Economic Order Quantity Model in Inventory Management 4 5: Dual sourcing: Advantages and disadvantages : Economic Order Quantity: What Does It Mean and Who Is It For5

Customer relationship management (CRM) is a program that uses data and technology to manage the interactions and relationships with customers. CRM helps to understand the needs, preferences, and behaviors of customers, and to provide them with better products, services, and experiences. In a rapidly changing business environment, a primary advantage of an effective CRM program is earlier identification of shifts in customer preferences. This means that CRM can help to detect and anticipate the changes in customer demand, tastes, or expectations, and to respond accordingly. This can help to improve customer satisfaction, loyalty, and retention, as well as to gain a competitive edge in the market. CRM does not necessarily reduce forecast variability, which is the degree of difference between the actual demand and the forecasted demand. CRM does not necessarily reduce customer order changes, which are the modifications or cancellations of orders by customers. CRM does not necessarily reduce customer defections, which are the losses of customers to competitors or other alternatives. References: CPIM Exam Content Manual Version 7.0, Domain 3: Plan and Manage Demand, Section 3.1: Demand Management Concepts, p. 16; Customer relationship management; Customer Relationship Management (CRM) Definition.

Load variability is the fluctuation in electricity demand over time. It is influenced by factors such as weather conditions, time of day, day of the week, and various external events. The higher the load variability, the more challenging it becomes to accurately predict demand and plan capacity1.

A technique to manage load variability would be to plan additional safety capacity as a part of total available capacity to meet unplanned demand. Safety capacity is the act of consistently planning your production below capacity. The reason for this is so the company can become more flexible and responsive to the changing needs of the customer2. For example, if your company was operating at full capacity and your best customer needed extra product, you would be unable to meet their request. By allowing for safety capacity, your company can become more flexible and more responsive.

The other options are not techniques to manage load variability, because they are either irrelevant or ineffective. Applying capacity planning using overall factors (CPOF) to identify priority items at the work center is a simple approach to capacity planning that applies historical ratios. These ratios are based on the master production schedule along with established production standards3. However, this method does not account for load variability or unexpected changes in demand or supply. Designing the shop floor with machines that sit idle until additional demand requires their use is a wasteful and costly way of managing load variability. It does not optimize the utilization of resources or minimize the inventory costs4. Using capacity bills to provide a rough-cut method of planning total-time-per-unit value is a procedure based on the manufacturing production schedule (MPS). It indicates the total standard time required to produce one end product in each work center required in its manufacture5. However, this method does not address the fluctuations in demand or supply that may occur due to load variability.