CPIM-Part-2 Dumps With Exact Questions and Answers

 In a make-to-stock (MTS) environment, improving estimates of customer demand would improve the trade-off between the cost of inventory and the level of customer service. MTS is a production strategy that manufactures products in anticipation of customer demand, based on forecasts. The main challenge of MTS is to balance the inventory costs and the customer service levels. Inventory costs include holding costs, ordering costs, and obsolescence costs. Customer service levels measure the ability to meet customer demand without delay or stockout. A trade-off exists between these two objectives, as higher inventory levels can increase customer service levels but also increase inventory costs, and vice versa.

Improving estimates of customer demand can help reduce the trade-off between inventory costs and customer service levels, as it can lead to more accurate production planning and inventory management. By forecasting demand more accurately, a company can avoid overproduction or underproduction, which can result in excess inventory or stockouts, respectively. By producing the right amount of products at the right time, a company can lower its inventory costs and increase its customer service levels.

Eliminating raw material stockouts would not improve the trade-off between inventory costs and customer service levels in a MTS environment, as it would not affect the finished goods inventory or the customer demand. Raw material stockouts are a supply issue that can disrupt the production process and cause delays or shortages in the finished goods. However, they do not directly impact the inventory costs or the customer service levels of the finished goods, which are determined by the demand forecasts and the production plans.

Decreasing the frozen time zone would not improve the trade-off between inventory costs and customer service levels in a MTS environment, as it would increase the variability and uncertainty in the production process. The frozen time zone is the period of time in which no changes can be made to the production schedule, as it is considered fixed and final. Decreasing the frozen time zone would allow more flexibility and responsiveness to changes in demand or supply, but it would also increase the risk of errors, disruptions, or inefficiencies in the production process. This could resultin higher production costs, lower quality, or longer lead times, which could negatively affect the inventory costs and the customer service levels.

Reducing manufacturing overtime would not improve the trade-off between inventory costs and customer service levels in a MTS environment, as it would reduce the production capacity and output. Manufacturing overtime is a way of increasing the production capacity and output by extending the working hours of the production resources, such as labor or equipment. Reducing manufacturing overtime would lower the production costs, but it would also lower the production output. This could result in insufficient inventory to meet customer demand, which could lower the customer service levels. References := Make-to-Stock (MTS) Definition, Make-to-Stock (MTS) vs Make-to-Order (MTO) | TradeGecko, Value Creation: Assessing the Cost-Service Trade-off

 Time-to-market (TTM) is the length of time it takes to develop a product from conception until it is released to the market and is available for sale1. Reducing TTM can provide a competitive advantage, as it can help a company to capture customer demand, respond to market changes, and increase profitability1.

One strategy to decrease TTM for a new product family is to increase collaboration between the buyer and the supplier of new components. Collaboration can involve sharing information, resources, risks, and rewards among supply chain partners to achieve mutual benefits2. By collaborating with the supplier of new components, the buyer can improve the quality, reliability, and innovation of the components, as well as reduce the costs, lead times, and uncertainties associated with them2. This can speed up the product development process and reduce the time and resources required to bring the new product family to the market.

The other options are not effective strategies to decrease TTM for a new product family. Decreasing the number of suppliers for components of the new product may reduce the complexity and variability of the supply chain, but it may also increase the dependency and vulnerability on a single or few suppliers, which may affect the availability and performance of the components3. Decreasing the purchasing lot size for the new product’s components may reduce the inventory carrying costs and risks, but it may also increase the ordering costs and frequency, which may affect the efficiency and responsiveness of the supply chain4. Increasing the safety stocks for the new product’s components may reduce the risk of stockouts and delays, but it may also increase the inventory carrying costs and risks, as well as tie up cash flow and working capital.

References : Time to market: Definition and strategies to speed up TTM; Time To Market (TTM) Defined & Why It’s Important | TCGen; Market Timing Tips Every Investor Should Know; Supply Chain Collaboration: Definition & Benefits; [Supplier Consolidation: Definition & Benefits]; [Economic Order Quantity (EOQ) Model: Definition & Formula]; [Safety Stock: The Ultimate Guide].

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