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

An assignable cause of variation is a source of variation that is intermittent, not predictable, and identifiable. It is also called a special cause of variation. An assignable cause of variation affects the process performance in an unexpected and non-random way, and it can be eliminated or controlled by finding and correcting the specific cause1. An example of an assignable cause of variation in process performance is incorrect setup of a machine by the operator. This means that the operator did not follow the standard procedure or specification for setting up the machine, which may result in defective or nonconforming products or materials. This cause of variation can be identified and corrected by checking the setup instructions, training the operator, or implementing a setup verification system23. References: 1 Assignable Cause - isixsigma.com 4 2 Process Capability Analysis - an overview | ScienceDirect Topics 5 3 CPIM Exam References - Association for Supply Chain Management 1

The cost to deliver the order consists of two components: the shipping cost and the holding cost. The shipping cost is the amount paid to the transportation mode for moving the order from the origin to the destination. The holding cost is the amount incurred for storing the order until it is delivered to the customer. The holding cost depends on the delivery time, which is the number of days it takes for the order to reach the customer. The longer the delivery time, the higher the holding cost. The shipping cost and the holding cost for each transportation mode are calculated as follows:
Shipping via rail:
Shipping cost = $300
Delivery time = 14 days
Holding cost = $40 x 14 = $560
Total cost = $300 + $560 = $860
Shipping via truck:
Shipping cost = $600
Delivery time = 3 days
Holding cost = $40 x 3 = $120
Total cost = $600 + $120 = $720
Therefore, the cost to deliver the order via rail is $860, and the cost to deliver the order via truck is $720.
References: Transportation Costing | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Inventory days of supply (IDS) is a measure of how long it takes for a company to sell its entire inventory.
Reducing IDS means that the company is selling its inventory faster, which increases the inventory turnover ratio. Inventory turnover ratio is the number of times a company sells and replaces its inventory in a given period. A higher inventory turnover ratio indicates that the company is more efficient in managing its inventory and generating sales. Reducing IDS also means that the company is reducing the time between paying its suppliers and receiving payment from its customers, which reduces the cash-to-cash cycle time.
Cash-to-cash cycle time is the number of days a company's cash is tied up in its operations. A lower cash-to-cash cycle time indicates that the company is more efficient in converting its inventory into cash and improving its liquidity. Therefore, reducing distribution network inventory days of supply will have the impact of increasing turnovers and reducing cash-to-cash cycle time. References:
Gartner's Top Actions for Supply Chain Inventory Reduction
Inventory Days Of Supply | Supply Chain KPI Library | Profit.co
Maximizing Efficiency: Understanding Inventory Days of Supply in - oboloo

Proximity to suppliers would be classified as a cost factor in preparing for a facility location decision. Cost factors are the expenses associated with operating a facility in a specific location, such as labor, materials, utilities, taxes, and transportation. Proximity to suppliers can affect the cost of inbound transportation, inventory holding, and quality control. Choosing a location that is close to suppliers can reduce these costs and improve the efficiency and reliability of the supply chain. References:
Managing Supply Chain Operations, Chapter 2: Global Supply Chain Strategy, Section 2.3: Facility Location CPIM Exam Content Manual, Module 1: Supply Chains and Strategy, Section 1.4: Facility Location, Subsection 1.4.1: Facility Location Concepts