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242 Cards in this Set

  • Front
  • Back
associative model
Forecasting technique that uses explanatory variables to predict future demand.
bias
Persistent tendency for forecasts to be greater or less than the actual values of a time series.
centered moving average
A moving average positioned at the center of the data that were used to compute it.
control chart
A visual tool for monitoring forecast errors.
correlation
A measure of the strength and direction of relationship between two variables.
cycle
Wavelike variations lasting more than one year.
Delphi method
An iterative process in which managers and staff complete a series of questionnaires
error
Difference between the actual value and the value that was predicted for a given period.
exponential smoothing
A weighted averaging method based on previous forecast plus a percentage of the forecast error.
forecast
A statement about the future value of a variable of interest.
irregular variation
Caused by unusual circumstances
judgmental forecasts
Forecasts that use subjective inputs such as opinions from consumer surveys
least squares line
Minimizes the sum of the squared vertical deviations around the line.
linear trend equation
Ft = a + bt
mean absolute deviation (MAD)
The average absolute forecast error.
mean absolute percent error (MAPE)
The average absolute percent error.
mean squared error (MSE)
The average of squared forecast errors.
moving average
Technique that averages a number of recent actual values
naive forecast
A forecast for any period that equals the previous period's actual value.
predictor variables
Variables that can be used to predict values of the variable of interest.
random variations
Residual variations after all other behaviors are accounted for.
regression
Technique for fitting a line to a set of points.
seasonal relative
Percentage of average or trend.
seasonal variations
Regularly repeating movements in series values that can be tied to recurring events.
seasonality
Short-term regular variations related to the calendar or time of day.
standard error of estimate
A measure of the scatter of points around a regression line.
time series
A time-ordered sequence of observations taken at regular intervals.
time-series forecasts
Forecasts that project patterns identified in recent time-series observations.
tracking signal
The ratio of cumulative forecast error to the corresponding value of MAD
trend
A long-term upward or downward movement in data.
trend-adjusted exponential smoothing
Variation of exponential smoothing used when a time series exhibits a linear trend.
weighted average
More recent values in a series are given more weight in computing a forecast.
A-B-C approach
Classifying inventory according to some measure of importance
cycle counting
A physical count of items in inventory.
cycle stock
The amount of inventory needed to meet expected demand.
economic order quantity (EOQ)
The order size that minimizes total annual cost.
excess cost
Difference between purchase cost and salvage value of items left over at the end of a period.
fill rate
The percentage of demand filled by the stock on hand.
fixed-order-interval (FOI) model
Orders are placed at fixed time intervals.
holding (carrying) cost
Cost to carry an item in inventory for a length of time
inventory
A stock or store of goods.
inventory turnover
Ratio of average cost of goods sold to average inventory investment.
lead time
Time interval between ordering and receiving the order.
Little's Law
The average amount of inventory in a system is equal to the product of the average demand rate and the average time a unit is in the system.
ordering costs
Costs of ordering and receiving inventory.
periodic system
Physical count of items in inventory made at periodic intervals (weekly
perpetual inventory system
System that keeps track of removals from inventory continuously
point-of-sale (POS) system
Record items at time of sale.
purchase cost
The amount paid to buy the inventory.
quantity discounts
Price reductions for larger orders.
reorder point (ROP)
When the quantity on hand of an item drops to this amount
safety stock
Extra inventory carried to reduce the probability of a stockout due to demand and/ or lead time variability.
service level
Probability that demand will not exceed supply during lead time.
setup costs
The costs involved in preparing equipment for a job.
shortage costs
Costs resulting when demand exceeds the supply of inventory; often unrealized profit per unit.
single-period model
Model for ordering of perishables and other items with limited useful lives.
two-bin system
Two containers of inventory; reorder when the first is empty.
universal product code (UPC)
Bar code printed on a label that has information about the item to which it is attached.
backflushing
Exploding an end item's BOM to determine the quantities of the components that were used to make the item.
bill of materials (BOM)
One of the three primary inputs of MRP; a listing of all of the raw materials
capacity requirements planning
The process of determining short-range capacity requirements.
changes
Revisions of due dates or order quantities
cumulative lead time
The sum of the lead times that sequential phases of a process require
dependent demand
Demand for items that are subassemblies or component parts to be used in the production of finished goods.
distribution resource planning (DRP)
A method used for planning orders in a supply chain.
enterprise resource planning (ERP)
Integration of financial
exception reports
Data on any major discrepancies encountered.
gross requirements
Total expected demand for an item or raw material in a time period.
inventory records
One of the three primary inputs in MRP; includes information on the status of each item by time period.
load reports
Department or work center reports that compare known and expected future capacity requirements with projected capacity availability.
lot sizing
Choosing a lot size for ordering or production.
low-level coding
Restructuring the bill of materials so that multiple occurrences of a component all coincide with the lowest level at which the component occurs.
manufacturing resources planning (MRP II)
Expanded approach to production resource planning
master schedule
One of three primary inputs in MRP; states which end items are to be produced
material requirements planning (MRP)
A computer-based information system that translates master schedule requirements for end items into time-phased requirements for subassemblies
net-change system
Approach that updates MRP records continuously.
net requirements
The actual amount needed in each time period.
order releases
Authorization for the execution of planned orders.
pegging
The process of identifying the parent items that have generated a given set of material requirements for an item.
performance-control reports
Evaluation of system operation
planned-order receipts
Quantity expected to be received by the beginning of the period in which it is shown.
planned-order releases
Planned amount to order in each time period; planned-order receipts offset by lead time.
planned orders
Schedule indicating the amount and timing of future orders.
planning reports
Data useful for assessing future material requirements.
product structure tree
A visual depiction of the requirements in a bill of materials
projected on hand
Expected amount of inventory that will be on hand at the beginning of each time period.
regenerative system
Approach that updates MRP records periodically.
scheduled receipts
Open orders scheduled to arrive from vendors or elsewhere in the pipeline.
time fences
Series of time intervals during which order changes are allowed or restricted; the nearest fence is most restrictive to change
Activities
Project steps that consume resources and/or time.
Activity-on-arrow (AOA)
Network diagram convention in which arrows designate activities.
Activity-on-node (AON)
Network diagram convention in which nodes designate activities.
Beta distribution
Used to describe the inherent variability in activity time estimates.
CPM
Critical path method
Crash
Shortening activity durations.
Critical activities
Activities on the critical path.
Critical path
The longest path; determines expected project duration.
Deterministic
Time estimates that are fairly certain.
Events
The starting and finishing of activities
Independence
Assumption that path duration times are independent of each other; requiring that activity times be independent
Most likely time
The most probable length of time that will be required.
Network (precedence) diagram
Diagram of project activities that shows sequential relationships by use of arrows and nodes.
Optimistic time
The length of time required under optimal conditions.
Path
A sequence of activities that leads from the starting node to the finishing node.
PERT
Program evaluation and review technique
Pessimistic time
The length of time required under the worst conditions.
Probabilistic
Estimates of times that allow for variation.
Project champion
A person who promotes and supports a project.
Projects
Unique
Slack
Allowable slippage for a path; the difference between the length of a path and the length of the critical path.
Virtual project teams
Some or all of the team members are geographically separated.
Work breakdown structure (WBS)
A hierarchical listing of what must be done during a project.
Avoidance
Finding ways to minimize the number of items that are returned.
Bullwhip effect
Inventory oscillations become progressively larger looking backward through the supply chain.
Centralized purchasing
Purchasing is handled by one special department.
Closed-loop supply chain
A manufacturer controls both the forward and reverse shipment of product.
Cross-docking
A technique whereby goods arriving at a warehouse from a supplier are unloaded from the supplier’s truck and loaded onto outbound trucks
Decentralized purchasing
Individual departments or separate locations handle their own purchasing requirements.
Delayed differentiation
Production of standard components and subassemblies
Disintermediation
Reducing one or more steps in a supply chain by cutting out one or more intermediaries.
E-business
The use of electronic technology to facilitate business transactions.
Event management
The ability to detect and respond to unplanned events.
Fill rate
The percentage of demand filled from stock on hand.
Gatekeeping
Screening returned goods to prevent incorrect acceptance of goods.
Information velocity
The speed at which information is communicated in a supply chain.
Inventory velocity
The speed at which goods move through a supply chain.
Logistics
The movement of materials
Order fulfillment
The processes involved in responding to customer orders.
Purchasing cycle
Series of steps that begin with a request for purchase and end with notification of shipment received in satisfactory condition.
Reverse logistics
The process of transporting returned items.
Radio frequency identification (RFID)
A technology that uses radio waves to identify objects
Strategic partnering
Two or more business organizations that have complementary products or services join so that each may realize a strategic benefit.
Strategic sourcing
Analyzing the procurement process to lower costs by reducing waste and nonvalue-added activities
Supply chain
A sequence of organizations—their facilities
Supply chain management
The strategic coordination of the supply chain for the purpose of integrating supply and demand management.
Supply chain visibility
A major trading partner can connect to its supply chain to access data in real time.
Third-party logistics (3-PL)
The outsourcing of logistics management.
Traffic management
Overseeing the shipment of incoming and outgoing goods.
Vendor analysis
Evaluating the sources of supply in terms of price
Vendor-managed inventory (VMI)
Vendors monitor goods and replenish retail inventories when supplies are low.
What is a Forecast?
A statement about the future value of a variable of interest such as demand
What happens when under forecast?
lose customers
What happens when over forecast?
too much inventory
What are three characteristics of forecasts?
1. Rarely perfect because of randomness
2. More accurate for groups vs. individuals
3. Less accurate as time horizon increases
Good forecasts are:
5 characteristics
timely
reliable
accurate
meaningful
easy to use
True or False: Forecasts needs to be continuously monitored for accuracy
true
What happens when results are under forecast?
Shortages and excesses throughout the supply chain. Shortages of materials, parts, and services can lead to missed deliveries, work disruption, and poor customer service. Ultimately, could lose customers.
What happens when results are over forecast?
Excesses of materials and or capacity, which increase costs.
How do we reduce the occurrences of inaccurate forecasts?
Develop the best possible forecast, collaborative planning and forecasting with major supply chain partners, information sharing among partners and perhaps increasing supply chain visibility by allowing supply chain partners to have real-time access to sales and inventory information, rapid communication about poor forecasts as well as unplanned events that disrupt operations, and changes in plans.
Why are forecasts rarely perfect?
The presence of randomness precludes a perfect forecast. Allowances should be made for forecast errors.
Are forecasts more accurate for groups of items or individual items?
More accurate for groups of items because forecasting errors among items in a group usually have a cancelling effect.
Good forecasts are:
timely, reliable, accurate, meaningful, and easy to use
What are the six elements of a good forecast?
(1) Forecast horizon must cover the time necessary to implement possible changes.
(2) accurate and the degree of accuracy stated.
(3) reliable and work consistently.
(4) expressed in meaningful units.
(5) in writing so that they can be evaluated once data is in.
(6) techniques used should be simple to understand and use.
How do you improve the accuracy of forecasts?
Continuously monitor them, work aggregately across functions to develop them
What are the two most important factors affecting a forecast?
Cost and Accuracy. Consider how much money is budgeted for generating the forecast, what are possible costs of errors, and what are the benefits that might accrue from an accurate forecast. The higher the cost, the higher the accuracy.
Aside from cost and accuracy, what are some other factors that affect forecasts?
historical data
availability of computer software
the time needed to gather and analyze the data
the forecast horizon
Which type of forecasts use a short horizon? Why?
Moving Average and Exponential Smoothing since they produce forecasts for the next period.
Which type of forecasts use a long horizon?
Trend Equations
What is helpful in determining what forecasting method to use?
Plotting the data
List the three types of forecasts:
Judgmental
Time Series
Associative Models
Which type of forecast uses subjective inputs?
Judgmental
Which type of forecast uses historical data?
Time Series
Which type of forecast uses explanatory variables to predict the future?
Associative Models
List the subjective inputs used in a Judgmental forecast.
Executive opinions
sales force opinions
consumer surveys
outside opinions
Delphi method
opinions of managers and staff
What does a judgmental forecast achieve?
it achieves a consensus forecast.
What are the components of a time series forecast?
Trend
Seasonality
Cycle
Irregular Variations
Random Variations
What causes random variations?
Chance
What are the 5 Time Series Models of Forecasting?
Naïve
Moving Average (MA)
Weighted Moving Average (WMA)
Exponential Smoothing (ES)
Simple Linear Regression
If the time series data contains random variation, but does not contain a trend, seasonality, or cycles, which Time Series Model should be used?
Moving Average (MA)
Weighted Moving Average (WMA)
Exponential Smoothing models
If the time series data contains random variation and a trend which Time Series Model should be used?
Simple Linear Regression
If a time series data contains random variation, trend, and seasonality which Time Series Model should be used?
Simple Linear Regression and Seasonal Factors
What is the formula for a moving average?
It is the unweighted mean of the previous "n" datum points. Determine the frequency of the average (i.e. 3 month, 5 month, etc.). Sum the data points for the specified frequency then divide by the frequency.
What is the formula for a weighted moving average?
The same as a moving average, except each data point is weighted. Typically the most recent data point has the most weight.
What is the error term in Exponential Smoothing?
(A-F)
What is the smoothing constant in Exponential Smoothing?
Sigma: a
What is the premise behind Exponential Smoothing?
The most recent observations might have the highest predictive value. Therefore we should give more weight to the more recent time periods when forecasting.
What is the formula for Exponential Smoothing?
Ft = Ft-1 + α(At-1 - Ft-1)
F is the forecast
A is the actual
t is the time period.
What is the goal of Simple Linear Regression?
to find a Trend Line to best fit the Time Series.
What is a forecast error?
It is the difference between the actual value and the predicted value.
What are the three most commonly used measures for summarizing historical errors? What is the difference between these measures?
Mean Absolute Deviation (MAD)
Mean Squared Error (MSE)
Mean Absolute Percent Error (MAPE)
The difference between these measures is that MAD weights all errors evenly, MSE weights errors according to their squared values, and MAPE weights according to relative error.
What is Mean Absolute Deviation (MAD)?
It is the average absolute forecast error.
What is Mean Squared Error (MSE)?
It is the average of the squared error.
What is Mean Absolute Percent Error (MAPE)?
It is the average absolute percent error.
What is the purpose of MAD, MSE and MAPE?
To compare the accuracy of alternative forecasting methods, to track error performance over time,
When should MAD, MSE, and MAPE should be used?
MAD is the easiest to compute, but weights errors linearly. MSE squares the errors, thereby giving more weight to larger errors, which typically cause more problems. MAPE should be used when there is a need to put errors into perspective.
What does a control chart detect?
It detects non-randomness in errors.
Which is better: MAPE or a Control Chart?
Control Chart
When using a Control Chart, how is it determined that the errors are in control?
All errors are within the control limits, and no patterns such as trends or cycles are present.
What are four features common to all forecasts?
(1) Forecasts generally assume that the same underlying causal system that existed in the past will continue to exist in the future.
(2) Forecasts are not perfect; actual results usually differ from predicted values.
(3) Forecasts for groups of items tend to be more accurate than forecasts for individual items
(4) Forecast accuracy decreases as the time period covered by the forecast--the time horizon--increases. Generally speaking, short-range forecasts must contend with fewer uncertainties than longer-range forecasts, so they tend to be more accurate.
What are the six basic steps in the forecasting process?
(1) Determine the purpose of the forecast.
(2) Establish a time horizon.
(3) Obtain, clean, and analyze appropriate data.
(4) Select a forecasting technique.
(5) Make the forecast.
(6) Monitor the forecast.
What is the caveat to forecasting?
Accuracy and control of forecast is a vital aspect of forecasting so forecasters want to minimize forecast errors. However, the complex nature of most real-world variables makes it almost impossible to correctly predict future values of those variables on a regular basis.
What is the Delphi method useful for?
It is useful for technological forecasting, that is for assessing changes in technology and their impact on an organization. Often the goal is to predict when a certain event will occur.
When can the Naïve forecast approach be used?
It can be used with a stable series (variations around an average), with seasonal variations, or with a trend. The forecast is the last data point for each series. Example: the forecast for this season is equal to the value of the series last season.
What are the advantages and disadvantages of the Naïve forecast method?
Advantage: virtually no cost, it is quick and easy to prepare because data analysis is nonexistent, and is easily understandable.

Disadvantage: inability to provide highly accurate forecasts.
Which forecast technique can be used to serve as a standard of comparison against which to judge the cost and accuracy of other techniques?
The Naïve Forecasting Technique
What is the purpose of Averaging Techniques?
It smooth's fluctuations in a time series because the individual highs and lows in the data offset each other when they are combined into an average. It provides a forecast based on an average thus tends to exhibit less variability than the original data.
What is an ideal method of analyzing data? Why is this not practical?
Completely remove randomness from the data and leave only "real" variations such as changes in demand. However it is usually impossible to distinguish between these two kinds of variations, so it is best to hope that the small variations are random and the large variations are "real".
Why are average techniques useful?
Many of the movements on a trend line merely reflect random variability rather than a true change in the series.
What type of forecasts does averaging techniques present?
Generates forecasts that reflect recent values of a time series.
When do Averaging techniques work best?
When a series tends to vary around an average, although they can also handle step changes or gradual changes in the level of the series.
What happens in a moving average forecast as each new actual value becomes available?
The forecast is updated by adding the newest value and dropping the oldest and then recomputing the average. Consequently, the forecast "moves" by reflecting only the most recent values.
What does the number of data points in the average determine?
The sensitivity to each new data point: The fewer the data points in an average, the more sensitive (responsive) the average tends to be.
What should be used if a responsive forecast is important? Why?
A moving average forecast with relatively few data points. This will permit quick adjustments to a step change in the data, and also will cause the forecast to be somewhat responsive to random variations.
If smoothing of data is more important than forecast responsiveness what is important to consider?
You must weigh the costs of responding more slowly to changes in the data against the cost of responding to what might simply be random variation.
What are the advantages and disadvantages of the Moving Average Forecast?
Advantage: easy to compute, easy to understand.

Disadvantage: all values in the average are weighted equally, slow to react to changes in the series.
What is the advantages and disadvantages of the Weighted Moving Average Forecast?
Advantage: the weighted average is more reflective of the most recent occurrences.

Disadvantage: the choice of weights is arbitrary.
What is the quickness of forecast adjustment to error determined by?
the smoothing constant, a. The closer it's value to zero, the slower the forecast will be to adjust to forecast errors (i.e. the greater the smoothing). The closer the value of a is to 1.00, the greater the responsiveness and the less the smoothing.
What is the goal in selecting a smoothing constant?
To balance the benefits of smoothing random variations with the benefits of responding to real changes if and when they occur.
When are low and high variables of a used in Exponential Smoothing?
Low values are used when the underlying average tends to be stable; higher values are used when the underlying average is susceptible to change.
When should exponential smoothing forecasts begin?
They should begin several time periods back to enable the forecasts to adjust to the data.
What is analysis of trend?
Developing an equation that will suitable describe the trend (assuming that trend is present in the data). The trend component may or may not be linear.
What are the two techniques used to develop forecasts when trend is present?
Trend Equation, and an Extension of Exponential Smoothing
What is the formula for a trend equation?
Ft = a + bt.
F = forecast for period t
a = value of Ft at t = 0
b = slope of the line
t = specified number of time periods from t = 0
What does the slope mean or say in a trend equation?
The value of Ft will change by b units for each time period.
What is the simplest and most widely used form of regression?
Simple Linear Regression, which involves a linear relationship between two variables.
What is the objective in Simple Linear Regression?
To obtain an equation of a straight line that minimizes the sum squared vertical deviations of data points from the line (i.e., the least squares criterion).
What are indicators of how accurate a prediction might be for a linear regression line?
The amount of scatter of the data points around the line. If the data points tend to be relatively close to the line, predictions using the linear equation will tend to be more accurate than if the data points are widely scattered.
What is an application of regression?
the use of indicators, which are uncontrollable variables that tend to lead or precede changes in a variable of interest.
What conditions are required for an indicator to be valid?
(1) the relationship between movements of an indicator and movements of the variable should have a logical explanation.
(2) Movements of the indicator must precede movements of the dependent variable by enough time so that the forecast isn't outdated before it can be acted upon.
(3) A fairly high correlation should exist between the two variables.
What does the square of the correlation coefficient provide?
It provides a measure of the percentage of variability in the values of Y that is "explained" by the independent variable. The closer the r^2 is to 1.00, the greater the percentage of explained variation.
What are three assumptions that must be satisfied in the use of simple regression?
(1) variations around the line are random. If they are random, no patterns such as cycles or trends should be apparent when the line and data are plotted.
(2) Deviations around the average value (i.e., the line) should be normally distributed. A concentration of values close to the line with a small proportion of larger deviations supports the assumption of normality.
(3) Predictions are being made only within the range of observed values.
To obtain the best results in Linear Regression Analysis:
(1) Plot the data to verify that a linear relationship is appropriate.
(2) Data may be time-dependent.
(3) A small correlation may imply that the other variables are important.
What are some weakness of Linear Regression analysis?
(1) it applies to only linear relationships with one independent variable.
(2) A considerable amount of data is needed to establish the relationship (20 or more observations)
(3) All observations are weighted equally.
How are errors plotted on a control chart?
In the order in which they occur
How is a control chart constructed?
First compute the MSE then compute the UCL and the LCL. Plot the errors in the order of occurrence on the chart.
Which is superior, Control Chart or a Tracking Signal? Why?
Control Chart. A tracking signal uses cumulative errors. Individual errors can be obscured so that large positive and negative values cancel each other. In Control Charts, each error is judged individually.
What are the advantages of better short-term forecasts?
enhance profits through lower inventory levels
fewer shortages
improved customer service
enhance forecast credibility
Are lean systems more dependent on short-term forecasts than traditional systems?
No, a lean system is demand driven; goods are produced to fulfill orders rather than to hold in inventory until demand arises.
What forecasting techniques are generally used by sales?
Subjective techniques such as focus groups and surveys.
What forecasting techniques are generally used by operations?
Objective techniques such as using data, historical information
What forecasting techniques are generally used by finance?
Generally the same tools as operations
What forecasting techniques are generally used by marketing?
Judgmental forecasts
How does accounting use forecasts?
cost estimates for new products or process, profit projections, and cash management
How does finance use forecasts?
evaluate equipment and equipment replacement needs, timing and amount of funding and/or borrowing needs.
How does human resources use forecasting?
Hiring activities such as recruitment, interviewing and training; layoff planning; outplacement counseling.
How does marketing use forecasts?
Pricing and promotion; e-business strategies; global competition strategies
How does MIS use forecasts?
New and/or revised information systems; internet services
How does product/service design use forecasts?
revision of current features; design of new products and/or services
What are executive opinions used for in forecasting?
Long range planning and new product development. It brings together the knowledge and talents of various managers. Disadvantage: groupthink
What are sales force opinions used for in forecasting?
Sales force may be aware of customers future plans. Disadvantages: unable to distinguish what a customer wants and actually does, may be overly influenced by recent experiences, estimates may be low if used to establish sales quotas.
What are consumer surveys used for in forecasting?
They can tap into data that may not be available elsewhere. They can be expensive and time consuming and require skills to administer and interpret results. They must contend with consumer irrational behavior methods.
What is focus forecasting?
Involves the use of several forecasting methods all being applied to the last few months of historical data after any irregular variations have been removed. The method with the highest accuracy is used to make the forecast for the next month.