Free APICS CPIM-8.0 Practice Exam with Questions & Answers | Set: 3

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

Moving average forecasting methods are best when demand shows high random variation, as they help to smooth out the noise and capture the underlying level of demand. Moving average methods use the average of the most recent observations as the forecast for the next period. They assign equal weights to all observations in the average, and drop the oldest observation when a new one becomes available. Moving average methods are not suitable for demand patterns that show a clear trend, consistent seasonality, or a cyclical pattern, as they cannot capture these components of demand. For these patterns, more sophisticated methods such as exponential smoothing or regression are needed. References: Forecasting with moving averages, APICS CPIM 8 Planning and Inventory Management | ASCM

 The shortest processing time rule is a prioritization rule that assigns the highest priority to the job that requires the least amount of processing time. This rule minimizes the average flow time of jobs and reduces the number of jobs in queue. The critical ratio rule assigns priority based on the ratio of time remaining until the due date to the remaining processing time. The fewest operations remaining rule assigns priority based on the number of remaining operations for each job. The first come, first served rule assigns priority based on the arrival time of the jobs. References: Managing Supply Chain Operations, Chapter 9: Scheduling and Sequencing, page 237. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, Chapter 13: Scheduling and Execution, page 419.

Substitute products are components of an organization’s immediate industry and competitive environment. They are products or services that can satisfy the same customer needs or wants as the organization’s offerings, but are provided by different industries or markets. Substitute products can affect the demand, price, and profitability of the organization’s products, and require the organization to monitor and respond to the changes in customer preferences and competitive pressures. Political factors, interest rates, and sociocultural forces are examples of macroenvironmental factors, which are broader and more general forces that affect the organization and its industry, but are not directly related to its competitors or customers. References :=

• CPIM Exam Content Manual, Module 1: Supply Chains and Strategy, Section 1.1: Business Strategy, p. 4
• Strategic Supply Chain Management: The Five Core Disciplines for Top Performance, Chapter 2: Align Your Supply Chain with Business Strategy, Section 2.2: Assessing the External Environment, pp. 25-26

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

Safety factor is a multiplier that is applied to the standard deviation of demand to determine the safety stock level. Safety factor remains constant while maintaining the same customer service level, as it reflects the desired probability of not stocking out. The higher the safety factor, the higher the customer service level, and vice versa. The other factors do not remain constant while maintaining the same customer service level. Reorder point (ROP) is the inventory level that triggers a replenishment order. ROP increases with increasing forecast error, as more safety stock is needed to cover the demand uncertainty. Safety stock is the inventory that is carried to protect against forecast errors and demand fluctuations. Safety stock increases with increasing forecast error, as more buffer is needed to avoid stockouts. Inventory investment is the total value of the inventory that is held in the system. Inventory investment increases with increasing forecast error, as more inventory is required to maintain the same customer service level. References: Safety Factor | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

 Backflushing is a method of inventory accounting that deducts the materials used in production from the inventory record after the completion of a product or batch. This introduces a temporary variance between the actual inventory balance and the inventory record, which should be reconciled periodically. Inventory write-off, cycle count, and kanban do not cause such a variance. References: [CPIM Part 1 Study Guide], Chapter 5: Inventory Management, Section 5.3: Inventory Record Accuracy, p. 5-15.

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

A pull system in distribution management is a method of inventory replenishment that is driven by the actual demand of the customers, rather than by forecasts or schedules. In a pull system, each warehouse makes its own replenishment decisions based on the inventory level and the customer orders. A pull system reduces the risk of overstocking or understocking inventory, as it responds to the real-time demand fluctuations. A pull system also improves the efficiency and flexibility of the distribution network, as it eliminates the need for centralized planning and coordination. A pull system is suitable for products that have high demand uncertainty, low holding costs, or short lead times12. References: Push vs. Pull Inventory Management Systems 2023 | Business.org, Push vs. pull: Inventory management for distribution businesses

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.