APICS CPIM-8.0 - Certified in Planning and Inventory Management (CPIM 8.0)

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

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 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

A control chart is a tool that shows process changes and random variation over time. It is a type of statistical process control (SPC) that monitors the performance of a process and detects whether it is in or out of control. A control chart consists of a center line, an upper control limit, and a lower control limit. The center line represents the average or target value of the process. The control limits represent the acceptable range of variation within the process. If the data points fall within the control limits, the process is considered stable and in control. If the data points fall outside the control limits, or show a non-random pattern, the process is considered unstable and out of control, indicating the presence of special causes of variation that need to be investigated and eliminated. References:

Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.2: Statistical Process Control

CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.1: Quality Management, Subsection 8.1.2: Statistical Process Control