True or false
Cost of forecast at the strategic level reflects emphasis on causal or regression techniques.
true
True or false
Level of executive involvement, forecast aggregation, frequency, and horizon vary in accordance with the requirements of strategic and business planning, S&OP, and master production scheduling
true
True or false
The master production scheduling horizon can be days for some products but usually are several weeks in length
true
True or false
Executive involvement in sales and operations planning reconciles the functional plans of finance, sales, manufacturing, hr, engineering, and so on
True
True or False:
Executive involvement can minimize the business risk of not getting the forecasts right, especially at the strategic planning level
True
True or False:
As MPC moves from strategic planning to master production scheduling, forecasts need to be more detailed, require less executive management direction and are better served by some forecasting techniques than others.
True
For Strategic and business planning, Quantitative techniques include things like
regression analysis
For strategic and business planning, Qualitative techniques are:
market research, expert opinion, and management estimation
T or F
Forecasting for strategic and business planning is short term range, consistent with lead time needed to implement the kinds of things in strategic and business plans
False
Forecasting for strategic and business planning is long range....
For S&OP, quantitative techniques include
time series forecasts, including decomposition, and causal techniques such as regression analysis
For S&OP, quantitative techniques are
expert opinion, pyramid, focus group, and Delphi
What is pyramid forecasting?
A Technique that combines quantitative and qualitative elements, used in S&OP, and includes the following forecasts:
a. Sales and marekting
b. Product family
c. Business level forecast at the corporate level
d. Assures consistency among strategic direction, marketing and sales, and use of manufacturing resources.
To calculate a force down forecast, what ratio do you use?
management forecast over the rollup forecast sales dollars.
You use this ratio and multiply each element by the ratio.
What three factors are the key to successful forecasting?
1. people
2. Data
3. Software
Explain the principles for ownership of the forecast
Whoever develops the forecast needs to be the one responsible for executing it and by extension the one who owns it. The demand planner.
How long is the forecast horizon for S&OP?
Varied depending on order fulfillment lead time for the product lines. Could be several months to a year or more.
Forecasts accommodate incremental capacity, workforce adjustments, engineering lead time
How long is the forecast horizon for strategic and business planning?
Can be 3 years or longer
Forecasts include data at a high level and highly qualitative, and a major objective is to determine long term resource and capacity needs that require long lead time.
What is the forecast horizon for master scheduling?
Forecast is derived from the sales and operations plan by dividing the months up through the planning time fence and slightly beyond, into weeks by 4, 4.3, and 5
What is the forecast horizon for the annual budget and financial planning?
3 months before the start of the budget year so it needs to span 15 months.
it must roll 12 months
What is forecast interval?
D) the duration of the time period used in the forecast
What are the advantages and disadvantages to using a quarterly forecast interval?
appropriate in industries with long production lead times, as in Engineered to order environments. May hide seasonal demand patterns but are good for mutliyear forecasts.
What are the advantages and disadvantages to using a monthly forecast interval?
Its not too detailed and gives an adequate level of precision. Allows detection of seasonal patterns that are hidden in quarterly intervals
what are the advantages and disadvantages of using a weekly interval?
weekly is necessary for master scheduling and can be achieved by dividing the monthly product family forecasts into weekly buckets.
it can give a false sense of precision
What does the term forecasting model pertain to?
judgmental and quantitative methods used in forecasting, and especially to statistical and mathematical ones.
What forecasting model would you use for high volume and high variance?
Aggregate forecast and then assemble to order
What forecasting model would you use for low volume, low variance?
Aggregate forecast and inventory then Make to order
How do you calculate the coefficient of variation (CV)?
Standard deviation of period demand over average period demand.
What forecasting model would you use for high volume and high variance?
High risk of obsolete inventory, check profitability, and move to Make to order only
What forecasting model would you use for high volume and low variance?
use statistical forecasting techniques and Make to stock
Describe the eight steps of the forecasting process
1. Data gathering and preparation
2. Forecast generation
3. Volume and mix reconciliation #1
4. Applying judgement
5. Volume and mix reconciliation #2
6. Decision making and authorization
7. Volume and mix reconciliation #3
8. Documenting assumptions.
What do qualitative techniques consist of?
subjective or judgmental techniques
What are two quantitative methods for forecasting?
1. Time Series (intrinsic)
2. Causal (extrinsic)
What are the two main categories of forecasting techniques
Quantitative and Qualitative
What are internal forecasting factors?
Things you can control like
new products
product life cycle
pricing and promotions
bids
historical data
management judgement
intra-company demand
What are external forecasting factors?
Things you cannot control
customers
competition
economic outlook and demographics
disruptive events
market life cycle
emerging technology
What are Qualitative techniques?
Expert opinion
management estimation
pyramid forecasting
focus groups
survey
panel consensus
delphi technique
sales force composite
product life cycle analysis
What are Causal (extrinsic) forecasting techniques?
Regression
Multiple regression
What are Time Series (intrinsic) forecasting techniques?
Simple average
moving average
Exponential smoothing
Time series decomposition
In the decline stage, what are sales doing?
lower and/or declining sales and product line simplification
In the mature stage, what do sales typically look like?
more competition, continuous demand that is gradually rising, level or gradually falling
In the introduction and growth states what do wales look like for a first mover?
high initial sales growth
What are the 5 categories of qualitative forecasting techniques?
1. independent judgement of experts
2. judgments of executives and managers
3. market research relating to specific customer groups in specific markets
4. sales estimates made by the sales force
5. historical analogy
What are the disadvantages of qualitative techniques?
1. Bias and overconfidence
2. Incomplete supporting documentation
3. not practical when organizations have thousands of stockkeeping units
4. Adverse effect of peer pressure in group decision making.
What are the advantages of qualitative techniques?
Qualititative techniques are useful when:
1. Initial quantifiable data are lacking
2. demand patterns and relationships are highly unstable
3. Strong need exists for executive and expert insight
4. long term forecasting needs behavioral insights from market research
5. sales forecasts need to be assembled quickly
Explain the inter-dependency between qualititative and quantitative forecasts.
What is Simple average?
SAF - Simple average forecast
The forecast for a period is the average of actual demand for the last two periods.
What is weighted moving average forecast?
Forecasters will weight actual demand values int he time series to determine a forecast that approximates the demand pattern
What is simple and moving average forecasts?
MAF techniques:
Objective is the smooth or average past demand to forecast future demand.
Sum of the past X periods /X = forecast for next period
When are time series techniques used?
When historical demand patterns can be assumed to continue into the future
What is exponential smoothing forecasting?
ESF - enables forecasters to assign weights to historical and current demand data and to calculate forecasts that take into account trend and seasonality.
If you have a medium to high smoothing constant, alpha, what demand pattern do you have?
Demand shows trend with low variability
If you have a low - medium smoothing constant, alpha, what demand pattern do you have?
Demand shows trend with volatility.
If you have a low smoothing constant, alpha, what is the demand pattern?
Demand is random with low variability
Time series decomposition can be divided into 4 components
1. trend
2. seasonal
3. cyclical
4. random (no pattern)
How do you calculate trend adjusted seasonal forecasts?
The trend adjusted seasonal factors based on averaging same quarter ratios
How do you calculate the trend ratio?
Actual divided by trend
What do quantitative forecasting techniques that consist of causal techniques apply in forecasting?
1. Analyze and predict based on relationships between event or occurrences, such as housing starts or sales of central ac
2. attempt to explain and quantify the relationships in order to predict demand in the future.
What do quantitative intrinsic techniques focus on?
1. Analyzing time series data
2. decomposition of demand patterns into trend, seasonal, cyclical, and random demand patterns.
3. determining the mathematical relationships within the data and demand patterns and extending them into the future.
Causal Techniques attempt to quantify the relationship between two types of events. What are they?
1. The predictor or independent variable. This is the cause of or influence on the 2nd event.
2. The Predicted or Dependent variable. You could call this the effect or the associated effect.
What are some advantages of causal analysis?
1. Relate internal and external factors to forecasts
a. Effects of promotions on sales
b. Market acceptance rates for new products
c. Use of leading indicators
2. Provide key insights into time series data
3. Are effective in long term forecasting
4. Are excellent at predicting aggregate demand
5. Are available in many software packages.
What are disadvantages of causal analysis?
1. Are sensitive to changes in relationships between variables.
2. Require high levels of external data collection
3. Require diverse numerical and behavioral data.
4. Have high data management, modeling, and storage costs.
5. Are seldom used in short term forecasts
6. Require extensive training in statistics.
What is Multiple regression analysis?
Forecasts based on relationships between more than one independent and one dependent variable
Models past relationships between more than one independent variable and a dependent variable.
a. has much higher computational requirements than single regression
b. Simultaneously measures the relationship between several variables and the dependent value, leading to a more robust forecast.
What is simple regression analysis?
Forecasts based on relationships between an independent and dependent variable.
Models past relationships between an independent and dependent variable.
a. identifies the relationship between the variables
b. Measures the error in using the relationship to predict values of the dependent variable.
c. Measures the degree of association between the two variables.
d. Calculates the degree of forecast error.
Summarize the value proposition of collaborative planning, forecasting, and replenishment (CPFR)
The objective was to
1. use one set of numbers in planning and forecasting by manufacturers and retailers.
2. Adopt standards for electronic communication and sharing of data.
What are the two aspects to CPFR?
1. Business process model in which parties electronically exchange written comments and data on demand trends, schedules, promotions, and forecasts.
2. Set of standards for electronic communication of data among the participating supply chain partners , which is beyond the scope of this course.
True or false:
The voluntary interindustry commerce standards association has the standards of CPFR model.
True
The CPFR model sets guidelines for collaboration at four levels of the partnering enterprises.
1. Strategy and planning
2. Demand and supply management
3. Execution
4. Analysis
In CPFR, Strategy and planning guidelines for collaboration are:
1. Collaboration arrangement (planning) - setting of business goals, scope of collaboration, and roles and responsibilities of the partners
2. Joint business plan - identifying significant events such as promotions, inventory policy changes, store openings, and product introductions.
In CPFR, demand and supply management guidelines for collaboration are:
1. Sales forecasting - analysis of market data by the manufacturer and point of sale data by the retailer
2. order planning and forecasting - demand planning by the manufacturer and replenishment planning by the retailer.
In CPFR, execution management guidelines for collaboration are:
1. Order generation - production and supply planning by the manufacturer; buying activities by the retailer
2. Order fulfillment - logistics and distribution management, both by the manufacturer and retailer
In CPFR, Analysis guidelines for collaboration are:
1. Exception management - execution monitoring by the manufacturer; store execution by the retailer
2. performance assessment - keeping of scorecards.
A collaboration process whereby supply chain trading partners can jointly plan key supply chain activities from production and delivery of raw materials to production and delivery of final products to end customers.
CPFR
A moving average where the oldest data point is dropped and the newest data point is included in the calculation
Simple moving average
A type of weighted moving average forecasting technique in which past observations are geometrically discounted according to their age.
Exponential smoothing forecast
An approach to forecasting where historical demand data is used to project future demand
Quantitative forecasting techniques
An averaging technique in which the data to be averaged are not uniformly weighted but are given values according to their importance
weighted moving average
A number used to adjust data to seasonal demand
seasonal index
Analysis of any variable classified by time in which the values of the variable are functions of the time periods
time series analysis
A method of forecasting where time series data are separated into up to three components: trend, seasonal, and cyclical; where trend includes the general horizontal upward or downward movement over time;seasonal includes a recurring demand pattern such as day of the week, weekly, monthly, or quarterly; and cyclical includes any repeating, nonseasonal pattern
Decomposition
A type of forecasting that uses cause and effect associations to predict and explain relationships between the independent and dependent variables
Causal forecast
A statistical technique for determining the best mathematical expression describing the functional relationship between one response and one or more independent variables
Regression analysis
Forecasts for products that are subject to promotional demand are most useful if they are based on
C) both quantitative and qualitative factors
Statistical forecasting provides the best solution in which of the following situations in an MTS environment?
D) Sales volume is high and forecast variance is low.
Which of the following is most directly affected by forecast inaccuracy?
C) Planned finished goods inventory level in an MTS environment
Which of the following qualitative methods of forecasting should a company consider for a product that is replacing another?
D) Historical analogy
Seasonality is demand that shows which of the following patterns?
B) Repetitive pattern over some time interval
Which of the following techniques is best suited to forecasting demand when the demand pattern shows seasonal and trend components?
D) Decomposition
Which of the following responses is the company most likely to consider when establishing the forecast for a new item being added to an MTS product line?
A) Evaluate the sales promotion effect of the new item on sales of existing products
In which of the following processes are qualitative techniques appropriately used?
D) Pyramid forecating
Which of the following quantitative techniques responds the most quickly to trends?
B. high alpha factor exponential smoothing
Given the following information, calculate the new forecast for Product A using exponential smoothing.
Alpha factor - 0.7
Actual Demand 600
Old forecast 562
Seasonal index 2.1
