WEEK 3 FORECAST & PRODUCT DESIGN

Question 1

Seven Steps in Forecasting

Answer 1

Determine the use of the forecast
Select the items to be forecasted
Determine the time horizon of the forecast
Select the forecasting model(s)
Gather the data
Make the forecast
Validate and implement results

Question 2

The Realities!

Answer 2

Forecasts are seldom perfect
Most techniques assume an underlying stability in the system
Product family and aggregated forecasts are more accurate than individual product forecasts

Question 3

Introduction

Answer 3

Best period to increase market share

R&D engineering is critical

Question 4

Growth

Answer 4

Practical to change price or quality image

Strengthen niche

Question 5

Maturity

Answer 5

Poor time to change image, price, or quality

Competitive costs become critical
Defend market position

Question 6

Decline

Answer 6

Cost control critical

Question 7

Qualitative Methods

Answer 7

Used when situation is vague and little data exist
New products
New technology
Involves intuition, experience

Question 8

Quantitative Methods

Answer 8

Used when situation is ‘stable’ and historical data exist
Existing products
Current technology
Involves mathematical techniques

Question 9

Overview of Qualitative Methods

Answer 9

Jury of executive opinion

Delphi method

Sales force composite

Consumer Market Survey

Question 10

Overview of Quantitative Approaches

Answer 10

Time-Series Models
Naive approach
Moving averages
Exponential smoothing
Seasonal indices

Associative Model
Linear regression

Question 11

Components

Answer 11

Trend component
Seasonal component
Cyclical Component
Random component

Question 12

Naive Approach (Quantitative)

Answer 12

Assumes demand in next period is the same as demand in most recent period.
Mathematically: Ft = At – 1

Question 13

Moving Average Method (Quantitative)

Answer 13

∑ demand in previous n periods/n

Question 14

Potential Problems With Moving Average & Partial solution

Answer 14

Do not forecast trends
Require extensive historical data
Increasing n smoothes the forecast, but makes it less sensitive to changes
Partial solution: weighted moving average

Question 15

Exponential Smoothing (Quantitative)

Answer 15

Ft = Ft – 1 + a(At – 1 - Ft – 1)

If a = 0 or 1 then this is equal to: naive approach / world’s most stable forecast*

Question 16

Common Measures of Error

Answer 16

Mean Absolute Deviation (MAD)
Mean Squared Error (MSE)
Mean Absolute Percent Error (MAPE)

Question 17

Seasonal Variations (Quantitative)

Answer 17

average of this month’s demand over the years/

average of all months of all years

Question 18

Tracking signal

Answer 18

RSFE/MAD = ∑(Ai - Fi)/ (∑| Ai - Fi |/n)

Question 19

Associative Forecasting

Answer 19

Used when changes in one or more independent variables can be used to predict the changes in the dependent variable.
Most common technique is linear regression analysis.

Question 20

Focus Forecasting

Answer 20

based on two principles:
Sophisticated forecasting models are not always better than simple ones
There is no single technique that should be used for all products or services

Question 21

You should distinguish your product by

Answer 21

Differentiation
Rapid response
Low cost

Question 22

Classical products

Answer 22

Entry: Early
Exit: Late

Question 23

Innovators

Answer 23

Entry: Early
Exit: Early

Question 24

Followers

Answer 24

Entry: Late
Exit: Late

Question 25

Introduction

Answer 25

Product design and development critical
Frequent product and process design changes
Short production runs
High production costs
Limited models
Attention to quality

Question 26

Growth

Answer 26

Forecasting critical
Product and process reliability
Competitive product improvements and options
Increase capacity
Shift toward product focus
Enhance distribution

Question 27

Maturity

Answer 27

Standardization
Less rapid product changes – more minor changes
Optimum capacity
Increasing stability of process
Long production runs
Product improvement and cost cutting

Question 28

Decline

Answer 28

Little product differentiation
Cost minimization
Overcapacity in the industry
Prune line to eliminate items not returning good margin
Reduce capacity

Question 29

Product Development System

Answer 29

Ideas => Ability => Customer Requirements => Functional Specifications => Product Specifications => Design Review => Test Market => Introduction => Evaluation

Question 30

Quality Function Deployment

Answer 30

Determining what will satisfy the customer and translating those customer desires into the target design.

Question 31

Product Design aspects

Answer 31

Robust design
Modular design
Computer-aided design (CAD)

Question 32

Robust design

Answer 32

Product is designed so that small variations in production or assembly do not adversely affect the product
Typically results in lower cost and higher quality

Question 33

Modular design

Answer 33

Products designed in easily segmented components
Adds flexibility to both production and marketing
Improved ability to satisfy customer requirements

Question 34

Computer-aided design (CAD)

Answer 34

Using computers to design products and prepare engineering docs
Shorter development cycles, improved accuracy, lower cost
Information and designs can be deployed worldwide

Question 35

Product Design aspects

Answer 35

Computer-aided manufacturing (CAM)
Virtual reality technology
Value analysis
Environmentally friendly design

Question 36

Defining The Product

Answer 36

First definition is in terms of functions

Rigorous
specifications are developed during the design phase

Manufactured products will have an engineering drawing

Bill of material (BOM) lists the components of a product