APICS Updated CPIM-Part-2 Exam Questions and Answers by ammar

The measurement that indicates there may be bias in the forecast model is the tracking signal. The tracking signal is a ratio of the cumulative forecast error to the mean absolute deviation (MAD). The cumulative forecast error is the sum of the differences between the forecasted and actual values over a period of time. The MAD is the average of the absolute values of the forecast errors. The tracking signal can help detect and measure the bias of a forecast model by comparing the magnitude and direction of the forecast errors. A positive tracking signal indicates that the forecast model is consistently over-forecasting, while a negative tracking signal indicates that the forecast model is consistently under-forecasting. A zero tracking signal indicates that there is no bias in the forecast model. A rule of thumb is that if the tracking signal exceeds a certain threshold, such as ±4, then there is a significant bias in the forecast model that needs to be corrected.

The other measurements do not indicate bias in the forecast model, but rather other aspects of the forecast accuracy or variability. The MAD is a measure of the average error or deviation of the forecast model from the actual values. The MAD does not indicate bias, as it does not consider thedirection or sign of the errors. A low MAD indicates a high accuracy of the forecast model, while a high MAD indicates a low accuracy of the forecast model.

The standard deviation is a measure of the dispersion or variation of the forecast errors around their mean. The standard deviation does not indicate bias, as it does not consider the direction or sign of the errors. A low standard deviation indicates a low variability or uncertainty of the forecast model, while a high standard deviation indicates a high variability or uncertainty of the forecast model.

The variance is a measure of the squared deviation or dispersion of the forecast errors around their mean. The variance does not indicate bias, as it does not consider the direction or sign of the errors. The variance is related to the standard deviation, as it is equal to the square of the standard deviation. A low variance indicates a low variability or uncertainty of the forecast model, while a high variance indicates a high variability or uncertainty of the forecast model.

References := Forecast KPI: RMSE, MAE, MAPE & Bias | Towards Data Science, A Critical Look at Measuring and Calculating Forecast Bias – Demand Planning, Forecast bias - Wikipedia

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

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.

In a make-to-order (MTO) environment, the production process is triggered by customer orders, which means there is no finished goods inventory or work-in-process inventory to consider in the sales and operations planning (S&OP) process. The available-to-promise (ATP) data is not an input to the S&OP process, but rather an output that indicates the quantity and date of products that can be promised to customers based on the current supply plan. The projected backlog of customer orders, on the other hand, is an important input to the S&OP process, as it reflects the current and future demand for the products and services offered by the organization. The projected backlog can help the organization plan its capacity, resources, materials, and delivery schedules to meet customer expectations and optimize profitability. References: CPIM Part 2 Exam Content Manual, Domain 3: Plan and Manage Demand, Section 3.1: Demand Management Concepts and Tools, p. 27-28.