CPIM-8.0 Certified in Planning and Inventory Management (CPIM 8.0) Questions and Answers

Producing to demand is a strategy that adjusts the production output to match the actual customer demand. This strategy is most appropriate during times of highly fluctuating demand, as it can reduce the inventory carrying costs and avoid overproduction or underproduction. Producing to demand can also improve customer satisfaction and responsiveness, as well as reduce waste and obsolescence. However, producing to demand requires a flexible and adaptable workforce that can easily change its capacity and skills to meet the changing demand patterns. The other options, producing to backorders, producing at a constant level, and producing to the sales forecast, are not as effective as producing to demand during times of highly fluctuating demand, as they can result in higher inventory costs, lower customer service, and lower profitability. References:

• Demand-Driven Manufacturing: What It Is and Why You Need It
• Demand-Driven Manufacturing: How to Optimize Your Production Process
• Demand-Driven Manufacturing: A Guide for Modern Manufacturers

A house of quality (HOQ) chart is a product planning matrix that is used to show how customer requirements relate directly to the ways and methods companies can use to achieve those requirements. HOQ charts are part of the quality function deployment (QFD) method, which helps to ensure quality in product development and service delivery. HOQ charts use a design that resembles the outline of a house, with different sections representing different aspects of the product or service1. One of the functions that a HOQ chart aligns is competitive analysis with product design. Competitive analysis is the process of evaluating the strengths and weaknesses of the competitors in the market, and identifying the opportunities and threats they pose to the company.Product design is the process of creating the features, functions, and specifications of the product or service that meet the customer needs and expectations. A HOQ chart aligns these two functions by comparing the company’s product design with the competitors’ product design, and showing how well the company’s product design satisfies the customer requirements. This helps the company to identify the areas of improvement, differentiation, and innovation in the product design, and to create a competitive advantage in the market23. References: 1 House of Quality Tutorial - How to Fill Out a House of Quality | ASQ 4 2 House of quality | Explanation with example - IONOS 5 3 CPIM Exam References - Association for Supply Chain Management 1

Rough-cut capacity planning (RCCP) is a technique that evaluates the feasibility of a master production schedule (MPS) by comparing the available capacity of key resources with the required capacity of the MPS. In a job shop environment, where products are made to order and have high variety and low volume, RCCP would typically review only the critical work centers to determine the ability to execute the plan. Critical work centers are those that have the greatest impact on the throughput, lead time, or cost of the products. They are usually the work centers that have the highest utilization, longest setup times, or most frequent bottlenecks. By focusing on the critical work centers, RCCP can simplify the capacity planning process and identify the potential problems or constraints that may affect the MPS. The other options, gateway work centers, final assembly work centers, and all work centers, are not as effective as critical work centers for RCCP in a job shop environment, as they may not reflect the true capacity requirements or constraints of the products. References:

• Rough Cut Capacity Planning (RCCP) - Definition, Example, and Benefits
• Rough Cut Capacity Planning (RCCP) - Meaning, Objectives, and Advantages
• Rough Cut Capacity Planning (RCCP) - Overview, Steps, and Example

A capacity-lagging strategy is a conservative approach to capacity planning that involves adding capacity only when the firm is operating at full capacity because of an increase in demand1. This strategy can help minimize costs and reduce the risk of excess capacity, but it can also lead to a disadvantage of not being able to fully meet customer demand if it rises quickly2. This can result in lost customers, revenue, and market share, as well as lower customer satisfaction and loyalty3. References:

•Lag Capacity Strategy, Lag Demand Strategy - UniversalTeacher.com

•Capacity Planning Strategies: Types, Examples, Pros And Cons - Toggl

•3 types of capacity planning strategies (with examples) - Xola

Product price is most effective in influencing demand in the introduction phase of the product life cycle, when the product is new and unfamiliar to the market. In this phase, customers are not aware of the product’s benefits, features, or quality, and may be reluctant to try it. Therefore, a lower price can help attract customers and stimulate demand, as well as deter potential competitors from entering the market. A lower price can also help the product gain market share and establish a loyal customer base. As the product moves to the growth, maturity, and decline phases, price becomes less effective in influencing demand, as other factors, such as product differentiation, quality, promotion, and customer satisfaction, become more important. References:

•Product Life Cycle Explained: Stage and Examples

•The 6 Stages of the Product Life Cycle [+Examples]

•Product Life Cycle - Definition, Stages, Usage

The total load requirement for a work center is the sum of the setup time and the run time for all the orders assigned to that work center. Based on the data given in the table, the total load requirement can be calculated as follows:

• For order A, the setup time is 4 minutes and the run time is 0.10 minutes per unit times 1,200 units, which equals 120 minutes.The total time for order A is 4 + 120 = 124 minutes.
• For order B, the setup time is 2 minutes and the run time is 1.50 minutes per unit times 800 units, which equals 1,200 minutes.The total time for order B is 2 + 1,200 = 1,202 minutes.
• For order C, the setup time is 1 minute and the run time is 0.20 minutes per unit times 525 units, which equals 105 minutes.The total time for order C is 1 + 105 = 106 minutes.
• For order D, the setup time is 1 minute and the run time is 1.00 minute per unit times 100 units, which equals 100 minutes.The total time for order D is 1 + 100 = 101 minutes.

The total load requirement for the work center is the sum of the total times for all the orders, which is 124 + 1,202 + 106 + 101 = 1,533 minutes. To convert this to hours, we divide by 60, which gives 25.55 hours. To express this as a decimal number, we multiply by 100, which gives 2,555. To round this to the nearest integer, we get 2,556. Therefore, the correct answer is D. 2,880. References:

• APICS CPIM Part 2 Exam Content Manual, p. 28
• [APICS CPIM Learning System Version 8.0], Module 4, Section B, p. 4-9

Carrying cost is the total cost of holding and storing inventory. It includes various expenses such as storage, insurance, taxes, depreciation, and obsolescence. Obsolescence is the loss of value or usefulness of inventory due to changes in technology, customer preferences, or market conditions. Obsolescence is considered a carrying cost because it reduces the potential revenue that can be generated from selling the inventory. Setup, transportation, and scrap rate are not carrying costs, but rather order costs, logistics costs, and quality costs respectively. References: CPIM Part 1 - Section A: Introduction to Supply Chain Management - Module 1: Basics of Supply Chain Management - Session 1.4: Inventory - Inventory Costs. CPIM Part 1 Study Guide, pp. 1-32 - 1-33.

A cellular layout is a workplace organization in which processes are organized by the product or product family, rather than by the type of work (function). A cellular layout consists of cells, which are groups of machines or workstations that are located close to each other and perform all the operations required for a product or product family. A cellular layout has several advantages over a functional layout, such as reduced material handling, improved quality, increased flexibility, and enhanced employee involvement. One of the main benefits of a cellular layout is that products will have faster throughput. Throughput is the rate at which products are produced and delivered to the customers. A cellular layout can increase the throughput by reducing the travel distance, the waiting time, and the setup time for the products. A cellular layout can also improve the production flow, the synchronization, and the visibility of the products. The other options are not correct, as they are not the typical benefits of switching from a functional to a cellular layout, but rather possible drawbacks or trade-offs of switching from a functional to a cellular layout:

• Equipment utilization will be higher: This is unlikely to be true, as a cellular layout may result in lower equipment utilization than a functional layout. Equipment utilization is the ratio of the actual output of a machine to its maximum possible output. A cellular layout may reduce the equipment utilization by dedicating some machines to specific products or product families, which may limit the sharing of machines across different products or product families. A cellular layout may also reduce the equipment utilization by balancing the workload among the machines within a cell, which may prevent some machines from operating at their full capacity.
• Quality inspections will be reduced: This may or may not be true, depending on the quality level and the quality control system of the production process. A cellular layout may reduce the quality inspections by improving the quality of the products, as the workers in a cell are more responsible, skilled, and empowered to perform the operations and to detect and correct the defects. However, a cellular layout may also increase the quality inspections by requiring more frequent and rigorous checks of the products, as the products move from one cell to another or from one stage to another.
• Capital expenditures will be reduced: This is unlikely to be true, as a cellular layout may result in higher capital expenditures than a functional layout. Capital expenditures are the costs of acquiring or upgrading the fixed assets, such as machines, equipment, or facilities. A cellular layout may increase the capital expenditures by requiring more machines or equipment to create the cells, especially if the machines or equipment are specialized or customized for specific products or product families. A cellular layout may also increase the capital expenditures by requiring more space or facilities to accommodate the cells, especially if the cells are dispersed or isolated from each other. References:
• [CPIM Part 2 - Section B - Topic 4 - Sustainability]
• Cellular Manufacturing: Definition, Examples & Advantages — Katana
• Cellular or Functional Layout? - IGI Global
• Functional Layout - Velaction
• What is cell layout? - Studybuff.com

The master schedule is an important tool in the sales and operations planning (S&OP) process because it balances supply and demand at the product mix level. The master schedule is a detailed plan that specifies the quantity and timing of each end item or product family to be produced. It is derived from the aggregate production plan, which is the output of the S&OP process. The master schedule helps to translate the aggregate plan into specific product requirements and to allocate the available capacity to meet the demand. The master schedule also provides input to the material requirements planning (MRP) and capacity requirements planning (CRP) systems, which further refine the production plan at the component and resource levels. The other statements are not true about the master schedule. The master schedule does not represent the forecast before changes are made in S&OP, as the forecast is an input to the S&OP process, not an output. The master schedule does not represent the forecast with less detail, as the master schedule is more detailed than the forecast, which is usually expressed in aggregate terms. The master schedule does not balance supply and demand at the sales volume level, as the sales volume level is the level of the aggregate production plan, not the master schedule. References: Master Schedule | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Reducing replenishment lead times will result in lower inventory levels because it means that the time between placing an order and receiving the goods is shorter. This reduces the need to hold excess inventory to cover the uncertainty and variability of demand and supply. Reducing replenishment lead times can also improve customer service levels, as orders can be fulfilled faster and more reliably. Level loading the master production schedule (MPS), increasing customer service level, and decentralizing inventory locations are all actions that will increase inventory levels, as they require more inventory to buffer against fluctuations in demand and supply, and to ensure availability at multiple locations. References: Inventory Management: Lead Time Reduction, APICS CPIM 8 Planning and Inventory Management | ASCM

 Management should support investments in new process technologies that align with the strategic objectives of the organization and provide a sustainable competitive advantage in the market. New process technologies may involve changes in existing systems, procedures, and skills, but these changes should be justified by the potential benefits and risks of the investment. Therefore, option D is correct. Option A is incorrect because requiring minimal changes in existing systems, procedures, and skills is not a sufficient criterion for investing in new process technologies. Option B is incorrect because relying on the recommendations of technical experts and equipment suppliers may not reflect the best interests of the organization or its customers. Option C is incorrect because providing significant cost-reduction opportunities for the company’s current products may not be enough to justify the investment in new process technologies, especially if the products have a short life cycle or low demand. References: CPIM Part 2 Exam Content Manual, Version 8.0, Section H: Quality, Continuous Improvement, and Technology, Subsection H.3: Technology, p. 85.

Maintenance, repair, and operating (MRO) supply systems are essential for ensuring the availability and reliability of equipment and infrastructure used in production processes. MRO supplies include items such as spare parts, tools, lubricants, cleaning materials, and safety equipment. The primary consideration in MRO supply systems typically is stockout costs, which are the costs incurred when an item is not available when needed. Stockouts can cause production delays, equipment breakdowns, customer dissatisfaction, and lost sales opportunities. Therefore, it is important to maintain adequate inventory levels of MRO supplies to avoid stockouts and ensure uninterrupted operations. Order quantity, carrying costs, and shelf life are also important factors in MRO supply systems, but they are not the primary consideration. Order quantity is the amount of MRO supplies ordered at a time, which affects the ordering costs and the inventory levels. Carrying costs are the costs of holding MRO supplies in inventory, which include storage, handling, insurance, and obsolescence costs. Shelf life is the period of time that MRO supplies can be stored before they expire or deteriorate, which affects the inventory turnover and the waste disposal costs. These factors need to be balanced with the stockout costs to optimize the MRO supply systems. References:

• CPIM Part 2 Study Guide, Chapter 6: Inventory Management, Section 6.3: Inventory Management for Independent Demand Items
• What is maintenance, repair and operations | IBM, Section: Why should you care about MRO?
• Maintenance, Repair, and Operations/Overhaul (MRO) - A Complete Guide, Section: Understanding MRO

Point-of-use storage is a stock location system that places inventory close to where it is needed or consumed in the production process. This reduces waste, handling, and transportation costs, and improves material flow and visibility. Point-of-use storage is a key element of a lean environment, where inventory is minimized and replenished frequently based on demand signals. References: EXAM CONTENT MANUAL PREVIEW, page 15, section 7.1.2. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, page 462, section 13.3.

One advantage of adopting a supply network perspective is that it enhances understanding of competitive and cooperative forces. A supply network perspective is a holistic view of the supply chain that considers the interdependencies and interactions among the various entities involved in the flow of materials, information, and money. A supply network perspective helps to identify the sources of value creation and capture, the opportunities and threats in the market, and the potential synergies and conflicts among the supply chain partners. A supply network perspective also helps to design and implement effective strategies and tactics to achieve competitive advantage and customer satisfaction. The other statements are not advantages of adopting a supply network perspective. Protecting global markets, defining market relationships and partnerships, and encouraging rivals to collaborate are possible outcomes or objectives of adopting a supply network perspective, but they are not the benefits of the perspective itself. References: Supply Network Perspective | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Reducing the inventory value by 10% would contribute most to shortening the cash-to-cash cycle time. The cash-to-cash cycle time is calculated as the days of inventory outstanding plus days of sales outstanding minus days of payables outstanding. By reducing the inventory value, the company can decrease the days of inventory outstanding, leading to a shorter cash-to-cash cycle time. This aligns with CPIM’s focus on efficient inventory management to optimize the supply chain. References: The concepts are covered in detail in Module 4: Inventory Management

A production cell is a group of machines or workstations that are arranged in a way that allows for continuous flow of materials and products. The main objective of designing a production cell is to reduce waste, improve quality, and increase productivity. One of the most important considerations for designing a production cell is the flow of materials into the cell and sequencing of operations to minimize total cycle time. Total cycle time is the time it takes for a product to go through all the steps in the cell, from the first operation to the last. By minimizing total cycle time, the production cell can achieve higher throughput, lower inventory, and faster delivery123 References: 1: CPIM Part 2 - Section C - Module 1 - Session 1 - Lean Manufacturing 2: CPIM Part 2 - Section C - Module 1 - Session 2 - Lean Manufacturing Tools 3: CPIM Part 2 - Section C - Module 1 - Session 3 - Lean Manufacturing Implementation

Enterprise resource planning (ERP) systems are software platforms that help organizations manage and integrate the essential parts of their businesses, such as finance, supply chain, operations, human resources, and more. ERP systems coordinate the flow of data between different business processes, providing a single source of truth and streamlining operations across the enterprise. ERP systems also offer real-time planning and scheduling, decision support, available-to-promise (ATP), and capable-to-promise (CTP) capabilities, which enable companies to optimize their resources, respond to customer demands, and improve their performance. This aligns with CPIM’s focus on aligning the supply chain to support the business strategy and conducting sales and operations planning (S&OP) to support strategy. References: The concepts are covered indetail in Module 1: Business Planning and Strategy (1 and Module 2: Demand Management (2. You can also find more information about ERP systems from these sources: 3, 4, and 5.

A cellular production system is a type of lean manufacturing system that reduces waste and improves efficiency by grouping machines and workers into cells that can produce a complete product or a product family. A pull production activity control (PAC) technique is most appropriate for a cellular production system because it allows the cells to produce only what is needed by the downstream processes or customers, thus minimizing inventory and overproduction. A pull PAC technique also enables quick response to changes in demand and feedback from quality control. A push PAC technique, on the other hand, is based on predetermined schedules and forecasts, which may not match the actual demand and may result in excess inventory and waste. The shortest processing time (SPT) rule and the distribution requirements planning (DRP) are not specific to cellular production systems and do not take into account the customer demand or the cell capacity. References:

•CPIM Part 2 Exam Content Manual, p. 49

•Cellular Manufacturing: A Comprehensive Guide

•Cellular manufacturing - Wikipedia

Safety stock is the extra inventory that a company keeps to prevent stockouts or shortages due to uncertainties in demand, supply, or lead time. Safety stock acts as a buffer to protect the company from losing sales or disrupting operations. One of the factors that is used to determine safety stock is the forecast error distribution, which is the measure of how much the actual demand deviates from the forecasted demand. Forecast error distribution can be calculated by using statistical methods, such as standard deviation or mean absolute deviation, to find the average and the variability of the forecast errors. The higher the forecast error distribution, the more safety stock is needed to cover the potential demand fluctuations. Forecast error distribution is one of the components of the safety stock formula, which is:

Safety stock = Z x ∑LT x D

Where:

Z refers to the service level factor, which is the desired probability of not having a stockout.

∑LT refers to the standard deviation of lead time, which is the average variability of the time it takes to replenish inventory.

D is the average demand per unit of time.

References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 24. CPIM Part 2 Learning System, Version 8.0, Module 2, Section C, Topic 3. How To Calculate Safety Stock (With Examples and FAQs). What is Safety Stock? (Definition, Formulas, Best Practices).

An X-bar chart is a type of control chart that is used to determine the average value of a group of units. It is also known as a mean chart. It plots the sample means of subgroups of units over time and compares them with the center line and the control limits. An X-bar chart is useful for monitoring the central tendency of a process and detecting any shifts or trends in the process mean. It is often used in conjunction with an R-chart, which measures the subgroup variation. References:

• Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.2: Statistical Process Control, Subsection 9.2.1: Control Charts
• CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.1: Quality Management, Subsection 8.1.2: Statistical Process Control, Subsubsection 8.1.2.1: Control Charts

Mixed-model scheduling is a technique that produces different models of the same product family in the same production line or work center. One of the benefits of mixed-model scheduling is that it reduces the number of setups required, as the models share common components and processes. Fewer setups can lead to lower setup costs, higher productivity, and better utilization of resources. The other outcomes are not benefits of mixed-model scheduling. Increased inventory, improved demand response, and fewer material shortages are more related to other factors such as inventory policies, demandforecasting, and supply planning. References: Mixed Model Scheduling | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Kanban is a pull system that uses visual signals to trigger the replenishment of materials or parts. It works best in environments where the demand is stable and predictable, and the production process is continuous and standardized. Kanban helps to reduce inventory, waste, and lead time by synchronizing the production and consumption rates. Kanban is not suitable for environments where the demand is volatile, the product life cycle is short, the production process is intermittent, or the product is highly customized. These factors would require frequent changes in the kanban system and reduce its effectiveness. References:

•CPIM Part 1 Study Guide, Chapter 4: Demand Management, Section 4.3: Pull Systems and Kanban

•CPIM Part 2 Study Guide, Chapter 1: Execution of Operations, Section 1.4: Lean Production and JIT

•What Is the Kanban System? - Investopedia

•Kanban - What Is it? | Lean Enterprise Institute

Customer service performance is the degree to which a company meets or exceeds the expectations of its customers in terms of the quality, timeliness, and satisfaction of the service provided. The most relevant measure of customer service performance is the service perceived by the customer against the service expected by the customer, also known as the service quality gap. This measure captures the difference between what customers expect from a service and what they actually receive, and reflects the level of customer satisfaction or dissatisfaction. A positive service quality gap indicates that the service exceeded the expectations, while a negative service quality gap indicates that the service fell short of the expectations. The other options are not as relevant as the service quality gap because they do not account for the customer’s perspective or perception of the service. Service promised to the customer against service measured by the supplier is an internal measure of service performance, but it does not reflect how the customer perceives the service. Customer complaints received as a percentage of orders shipped is a measure ofservice failure, but it does not capture the positive feedback or the silent dissatisfied customers. Positive customer feedback as a percentage of customer feedback is a measure of service satisfaction, but it does not account for the customer’s expectations or the service quality dimensions. References:

• CPIM Part 2 Exam Content Manual, p. 67
• Customer Service Metrics: Top 10 to Measure
• 20 Customer Service KPIs You Need To Know

 Forecast error is the difference between the actual demand and the forecasted demand for a given period. Forecast error can be caused by various factors, such as changes in customer preferences, market conditions, competitor actions, or random variation. Forecast error can be measured using different methods, such as mean absolute deviation (MAD), mean absolute percentage error (MAPE), or tracking signal. Forecast error typically triggers forecast revision when it is continually increasing, which indicates that the forecast model is not capturing the underlying demand pattern or trend. A continually increasing forecast error can lead to poor customer service, excess or obsolete inventory, or lost sales opportunities. Therefore, it is important to monitor the forecast error and revise the forecast when necessary to improve the forecast accuracy and reliability. Forecast error does not trigger forecast revision when it is used in computing the tracking signal, associated with the introduction stage of the product life cycle, or caused by random variation. These are not valid reasons for revising the forecast, as they do not indicate a systematic or persistent deviation from the actual demand. References:

• CPIM Part 1 Study Guide, Chapter 4: Demand Management, Section 4.2: Forecasting Techniques and Performance Measurement
• CPIM Part 2 Study Guide, Chapter 3: Demand Management, Section 3.1: Demand Planning
• A Critical Look at Measuring and Calculating Forecast Bias, Section: What Is Forecast Bias?
• How Can Forecast Error be Calculated?, Section: Introduction

Capable-to-promise (CTP) is a type of order fulfillment policy that confirms a customer order based on the available capacity and inventory, as well as the current production plan and schedule. CTPcalculates the earliest possible delivery date for a customer order, considering the existing demand and supply situation. CTP allows a company to accept an order that exceeds the current available inventory, as long as it can produce the remaining quantity within the customer’s requested delivery time. CTP helps to improve customer service, reduce inventory costs, and increase production efficiency12. References: 1 Capable to Promise (CTP) - Definition, Calculation, and Examples 3 2 CPIM Exam References - Association for Supply Chain Management

 Prevention is a risk control strategy that involves avoiding or eliminating the sources of risk. By deciding not to pursue a business opportunity in a foreign market due to political instability and currency fluctuations, the company prevented the potential losses or disruptions that could arise from these factors. Mitigation is a risk control strategy that involves reducing the impact or likelihood of risk. Recovery is a risk control strategy that involves restoring normal operations after a risk event occurs. Wait and see is a risk control strategy that involves monitoring the risk situation and taking action only when necessary. References:

• CPIM Part 2 Learning System, Module 1: Supply Chain Strategy, Section 1.5: Risk Management
• CPIM Part 2 Learning System, Module 4: Execution and Control of Operations, Section 4.3: Risk Management

Finite loading is a capacity planning approach that takes into account the available capacity of the resources and does not allow overloading. It considers adjustments to plans based on planned capacity utilization, which means that it can change the start or end dates of the operations to avoid exceeding the capacity limits. This way, finite loading ensures that the production schedule is realistic and feasible. Other capacity planning approaches, such as infinite loading, do not consider adjustments to plans based on planned capacity utilization. Infinite loading ignores the capacity constraints and schedules the operations based on the due dates and the lead times, regardless of the resource availability. This may result in overloading the resources and causing delays or disruptions in the production process. Therefore, the fundamental difference between finite loading and other capacity planning approaches is that finite loading considers adjustments to plans based on planned capacity utilization, while other approaches do not. References:

• CPIM Part 2 Exam Content Manual, p. 48
• The Difference Between Finite Capacity Scheduling and Infinite Capacity Loading
• FINITE LOADING

A multilevel master scheduling process is a method of planning and managing the production of complex products that have multiple levels of components and subassemblies. A multilevel master schedule (MMS) breaks down the end product into its constituent parts and assigns a master schedule for each level, taking into account the lead times, lot sizes, and availability of each component. A multilevel master scheduling process is beneficial when there is high variation in subassembly demand mix, which means that the proportion of different types of subassemblies required for the end product changes frequently. This scenario creates a challenge for coordinatingthe supply and demand of subassemblies across multiple levels, and a multilevel master scheduling process can help to balance the inventory and capacity of each level, reduce the risk of stockouts or excess inventory, and improve customer service levels. References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 23. CPIM Part 2 Learning System, Version 8.0, Module 2, Section B, Topic 3.

The sales and operations plan (S&OP) is the most appropriate level to adjust when a major new customer is received from sales. The S&OP is a cross-functional process that aligns the demand and supply plans with the business strategy and financial goals. It also provides the basis for the masterproduction schedule (MPS), which is a more detailed and disaggregated plan for specific products or families. Adjusting the production volume or the forecast would not be sufficient to account for the impact of the new customer on the overall business objectives and resources. References:

•APICS CPIM Part 2 Exam Content Manual, p. 11

•[APICS CPIM Learning System Version 8.0], Module 1, Section A, p. 1-15

 A sales forecast that is based solely on shipment history assumes that the past demand patterns will continue in the future. However, this assumption may not be valid if there are factors that affect the customer demand that are not captured by the shipment history. For example, customer demands may change due to seasonality, promotions, new product introductions, competitor actions, economic conditions, or other external influences. These factors may distort the sales forecast that is based solely on shipment history and cause it to be inaccurate or unreliable. The other options are not factors that typically distort a sales forecast that is based solely on shipment history, as they do not directly affect the customer demand. Material shortages, labor rate changes, and currency exchange rates may affect the supply side of the business, but they do not necessarily reflect the customer preferences or needs. References:

• CPIM Part 2 Exam Content Manual, p. 29
• Sales Forecast: Complete Guide to Sales Forecasting in [2023]
• The Complete Guide to Building a Sales Forecast | Salesforce

The discrete available-to-promise (ATP) method is a calculation based on the available-to-promise figure in the master schedule. For the first period, the ATP is the sum of the beginning inventory plus the MPS quantity minus backlog for all periods until the item is master scheduled again. For other periods, the quantity that is available for an item is based on the quantity available within an individual purchase. Therefore, the master production receipt quantity is committed to requests only for shipment before the next MPS receipt12. References:

•1: APICS CPIM Part 2 Exam Content Manual, Version 8.0, p. 29

•2: NetSuite Applications Suite - Available to Promise Methods3

The supply planning team is responsible for developing a supply plan that balances the demand plan with the available resources and capacities. The functional representatives on the supply planning team, such as production, procurement, engineering, and finance, need to ensure that their functional objectives are considered when developing the plans. For example, production needs to consider the impact of the supply plan on the production schedule, capacity utilization, and labor requirements. Procurement needs to consider the impact of the supply plan on the supplier relationships, lead times, and inventory levels. Engineering needs to consider the impact of the supply plan on the product design, quality, and innovation. Finance needs to consider the impact of the supply plan on the costs, revenues, and profitability. By ensuring that the functional objectives are considered, the supply planning team can create a feasible and optimal supply plan that aligns with the overall business strategy12. References: 1 S&OP: A Comprehensive Overview of Sales and Operations Planning 3 2 CPIM Exam References - Association for Supply Chain Management 1

Poka-yoke is a Japanese term that means “mistake-proofing”. It is a lean tool that aims to eliminate errors and defects by designing processes or products in such a way that mistakes are either prevented or detected and corrected immediately. Poka-yoke can be applied in various ways, such as using sensors, guides, checklists, alarms, or color-coding, to ensure that the process or product meets the quality standards and customer expectations. One of the benefits of integrating poka-yoke into the production process is that it can be used to prevent defects, which can result in lower costs, higher customer satisfaction, and improved productivity. By avoiding defects, poka-yoke can also reduce waste, rework, inspection, and warranty claims, as well as enhance safety and reliability. References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 29. CPIM Part 2 Learning System, Version 8.0, Module 3, Section C, Topic 2.

Exponential smoothing is a forecasting method that uses weighted averages of past observations to predict future values. The weights decrease exponentially as the observations get older, giving more importance to recent data. Exponential smoothing can be applied to data with different patterns, such as level, trend, or seasonality. Depending on the pattern, different exponential smoothing models and parameters are used. Two common parameters are alpha (α) and beta (β):

• Alpha is the smoothing parameter for the level component of the forecast. The level component is the average or typical value of the data. Alpha can range from 0 to 1, not inclusive. A low alpha value gives more weight to older observations and produces a smoother forecast. A high alpha value gives more weight to recent observations and produces a more responsive forecast.
• Beta is the smoothing parameter for the trend component of the forecast. The trend component is the direction and rate of change of the data over time. Beta can also range from 0 to 1, notinclusive. A low beta value gives more weight to older trends and produces a smoother forecast. A high beta value gives more weight to recent trends and produces a more responsive forecast.

A company with stable demand that uses exponential smoothing to forecast demand would typically use a low alpha value. Stable demand means that the data do not have significant variations, fluctuations, or patterns over time. In this case, a simple exponential smoothing model that estimates only the level component is sufficient. A low alpha value would produce a smooth and stable forecast that reflects the average demand level and does not react to random noise or outliers. The other options are not correct, as they either refer to a different parameter (beta) or a different scenario (high alpha value):

• A low beta value would be used for data with a trend component, but a stable demand does not have a trend component. A low beta value would produce a smooth and stable trend forecast that does not react to random noise or outliers.
• A high beta value would also be used for data with a trend component, but a stable demand does not have a trend component. A high beta value would produce a responsive and dynamic trend forecast that reflects the recent changes in the data.
• A high alpha value would be used for data with a high variability or uncertainty, but a stable demand does not have these characteristics. A high alpha value would produce a responsive and dynamic level forecast that reflects the recent changes in the data. References:
• [CPIM Part 2 - Section A - Topic 3 - Demand Management]
• Exponential Smoothing for Time Series Forecasting
• What is alpha and beta in exponential smoothing?
• Value of alpha and beta in Holt’s exponential smoothing method

A push system is a production system that relies on forecasts and schedules to plan the production and distribution of goods and services. A pull system is a production system that responds to actual customer demand and signals to trigger the production and distribution of goods and services. A transition from a push system to a pull system requires a change in the mindset and the processes of the organization, as well as the adoption of new tools and techniques to enable a demand-driven production system12.

One of the tools that is commonly used in a pull system is kanban, which is a visual signal that indicates the need for replenishment of materials or products. Kanban cards are attached to standardized containers that hold a fixed amount of inventory. When a container is empty, the kanban card is sent back to the upstream process as a signal to produce more. This way, the inventory level is controlled by the actual consumption of the downstream process, and the production is synchronized with the demand13.

One of the actions that hinders the transition from a push system to a pull system is using work orders as a backup. Work orders are documents that authorize the production of a certain quantity of a product or a service, based on a forecast or a schedule. Work orders are typical of a push system, as they are not triggered by the actual customer demand, but by the planned production. Using work orders as a backup means that the organization is not fully committed to the pull system, and still relies on the push system to ensure the availability of inventory. This can create confusion, inconsistency, and inefficiency in the production system, as well as increase the inventory holding costs and the risk of obsolescence1 .

Therefore, using work orders as a backup is the correct answer, as it is an action that hinders the transition from a push system to a pull system. The other options are actions that support the transition, as they are aligned with the principles and practices of a pull system.

An effective approach to projecting requirements for materials with long lead times is to initiate a multilevel master schedule. A multilevel master schedule is a detailed plan that shows the quantities and timing of the end items and all of their components at each level of the bill of materials (BOM). By using a multilevel master schedule, a planner can determine the requirements for materials with long lead times and place orders in advance to avoid shortages or delays. A phantom bill of materials (BOM) is a temporary grouping of components that are used in the production of a parent item, but do not exist as a separate item in inventory. A phantom BOM is not an effective approach to projecting requirements for materials with long lead times, as it does not reflect the actual demand for the components. Increasing the level of safety stock is a way of mitigating the risk of uncertainty in demand or supply, but it is not an effective approach to projecting requirements for materials with long lead times, as it increases the inventory carrying costs and does not address the root cause of the problem. Decreasing the planning horizon is the opposite of an effective approach to projecting requirements for materials with long lead times, as it reduces the visibility and accuracy of the forecast and increases the likelihood of stockouts or excess inventory. References:

• CPIM Part 2 Learning System, Module 1: Supply Chain Strategy, Section 1.4: Master Scheduling
• CPIM Part 2 Learning System, Module 3: Supply, Section 3.2: Material Requirements Planning

Changing the due dates of open orders is a common practice to cope with demand fluctuations, capacity constraints, or material shortages. However, it can have a negative effect on the stability and reliability of the schedule, causing “nervousness”. Nervousness is the tendency of the schedule to change frequently and significantly due to minor changes in inputs or parameters. Nervousness can result in increased costs, reduced efficiency, lower quality, and lower customer satisfaction. To avoid or reduce nervousness, some strategies are: using time fences, freezing the schedule, aggregating the demand, and using safety stock or safety time. References :=

• CPIM Exam Content Manual, Module 5: Detailed Schedules, Section 5.1: Capacity Management, p. 18
• Manufacturing Planning and Control for Supply Chain Management, Chapter 9: Capacity Planning and Management, Section 9.3: Capacity Planning and Scheduling, pp. 222-223

The economic order quantity (EOQ) model is a formula that calculates the optimal order quantity that minimizes the total inventory costs, such as ordering costs and holding costs. The EOQ model is based on several assumptions, one of which is that the order preparation costs and inventory-carrying costs are constant and known. This means that the costs of placing and receiving an order, and the costs of storing and maintaining the inventory, do not change with the order quantity or the inventory level, and that they can be estimated accurately12.

The other options are not correct because:

•A. Customer demand is known but seasonal. This is not an assumption of the EOQ model, but rather a violation of it. The EOQ model assumes that the customer demand is constant and known, and that the orders are placed at regular intervals. However, if the customer demand is seasonal, it means that it varies over time and may not be predictable. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may change with the demand pattern12.

•B. Items are purchased and/or produced continuously and not in batches. This is not an assumption of the EOQ model, but rather a contradiction of it. The EOQ model assumes that the items are purchased and/or produced in batches, and that the inventory level decreases gradually until it reaches zero, at which point a new order is placed and received. However, if the items are purchased and/or produced continuously, it means that there is no need to place orders or maintain inventory, and the EOQ model becomes irrelevant12.

•D. Holding costs, as a percentage of the unit cost, are variable. This is not an assumption of the EOQ model, but rather a complication of it. The EOQ model assumes that the holding costs, as a percentage of the unit cost, are constant and known. This means that the cost of storing and maintaining one unit of inventory does not depend on the unit cost of the item, and that it can be estimated accurately. However, if the holding costs, as a percentage of the unit cost, are variable, it means that the cost of storing and maintaining one unit of inventory changes with the unit cost of the item, and that it may not be easy to estimate. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may depend on the unit cost of the item12.

References := 1 Economic Order Quantity Model in Inventory Management - Investopedia1 2 Economic Order Quantity: What Does It Mean and Who Is It Important For? - Investopedia2

The probability of stocking out is the likelihood that the demand for an item will exceed the available inventory during a given period. It is one of the criteria used to determine safety stock in a distribution center (DC), as safety stock is inventory that is carried to protect against forecast errors and fluctuations in demand or supply. The higher the probability of stocking out, the more safety stock is needed to avoid customer dissatisfaction and lost sales. The other criteria are not directly related to safety stock. Economic order quantity (EOQ) is the order quantity that minimizes the total inventory holding and ordering costs. Seasonal index value is a measure of how demand varies according to different seasons or periods. Alpha factor level is a parameter used in exponential smoothing to adjust the forecast based on the error between the actual and forecasted demand. References: Safety Stock: A Contingency Plan to Keep Supply Chains Flying High, APICS CPIM 8 Planning and Inventory Management | ASCM

Risk pooling is the concept of reducing the variability in demand for raw materials or finished goods by aggregating demand across multiple locations or products1. By doing so, the demand fluctuations are more likely to cancel out each other, resulting in a lower safety stock and inventory cost. Risk pooling works best for items with high demand uncertainty and long lead times, because these items have the highest risk of stockouts and the highest inventory holding cost. If the demand uncertainty is low, there is less need for risk pooling, as the demand can be easily forecasted and met. If the lead time is short, the replenishment orders can be placed more frequently and adjusted to the actual demand, reducing the need for safety stock and risk pooling2. References: 1 Inventory risk pooling definition — AccountingTools 3 2 Supply Chain Management: Risk pooling - UNB 4

A localized multi-country strategy is a type of global strategy that involves adapting products, marketing, and operations to the specific needs and preferences of each country or region where the company operates. This strategy allows the company to increase its market share by appealing to the local customers and differentiating itself from the competitors. A localized multi-country strategy requires the company to sell different product versions in different countries under different brand names, as this reflects the high degree of customization and localization that the strategy entails. The other options are not consistent with a localized multi-country strategy, as they imply a low degree of adaptation and a high degree of standardization across the markets. Selling the same products under the same brand name worldwide is a global strategy that assumes universal customer preferences and seeks economies of scale. Locating plants on the basis of maximum location advantage is a transnational strategy that balances global integration and local responsiveness. Using the best suppliers regardless of geographic location is a sourcing strategy that does not necessarily reflect the degree of localization of the products or the marketing. References:

• CPIM Part 2 Exam Content Manual, p. 19
• Multidomestic strategy: Global success through localization
• Localization strategy - How to build with examples

Increasing finished goods inventory investment will improve service levels by reducing the probability of stockouts. However, the relationship between inventory and service level is not linear, but rather asymptotic. This means that as inventory increases, service level increases at a decreasing rate, approaching a maximum value. Therefore, option C is correct. Option A is incorrect because service level will not remain the same when inventory changes. Option B is incorrect because service level will not increase in direct proportion to inventory. Option D is incorrect because service level will not increase at an increasing rate as inventory increases. References: CPIM Part 2 Exam Content Manual, Version 8.0, Section A: Demand Management, Subsection A.3: Demand Management and Customer Service, p. 10.