WEEK 3 FORECAST & PRODUCT DESIGN Flashcards
Seven Steps in Forecasting
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
The Realities!
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
Introduction
Best period to increase market share
R&D engineering is critical
Growth
Practical to change price or quality image
Strengthen niche
Maturity
Poor time to change image, price, or quality
Competitive costs become critical
Defend market position
Decline
Cost control critical
Qualitative Methods
Used when situation is vague and little data exist
New products
New technology
Involves intuition, experience
Quantitative Methods
Used when situation is ‘stable’ and historical data exist
Existing products
Current technology
Involves mathematical techniques
Overview of Qualitative Methods
Jury of executive opinion
Delphi method
Sales force composite
Consumer Market Survey
Overview of Quantitative Approaches
Time-Series Models Naive approach Moving averages Exponential smoothing Seasonal indices
Associative Model
Linear regression
Components
Trend component
Seasonal component
Cyclical Component
Random component
Naive Approach (Quantitative)
Assumes demand in next period is the same as demand in most recent period.
Mathematically: Ft = At – 1
Moving Average Method (Quantitative)
∑ demand in previous n periods/n
Potential Problems With Moving Average & Partial solution
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
Exponential Smoothing (Quantitative)
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*
Common Measures of Error
Mean Absolute Deviation (MAD)
Mean Squared Error (MSE)
Mean Absolute Percent Error (MAPE)
Seasonal Variations (Quantitative)
average of this month’s demand over the years/
average of all months of all years
Tracking signal
RSFE/MAD = ∑(Ai - Fi)/ (∑| Ai - Fi |/n)
Associative Forecasting
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.
Focus Forecasting
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
You should distinguish your product by
Differentiation
Rapid response
Low cost
Classical products
Entry: Early
Exit: Late
Innovators
Entry: Early
Exit: Early
Followers
Entry: Late
Exit: Late
Introduction
Product design and development critical Frequent product and process design changes Short production runs High production costs Limited models Attention to quality
Growth
Forecasting critical Product and process reliability Competitive product improvements and options Increase capacity Shift toward product focus Enhance distribution
Maturity
Standardization Less rapid product changes – more minor changes Optimum capacity Increasing stability of process Long production runs Product improvement and cost cutting
Decline
Little product differentiation Cost minimization Overcapacity in the industry Prune line to eliminate items not returning good margin Reduce capacity
Product Development System
Ideas => Ability => Customer Requirements => Functional Specifications => Product Specifications => Design Review => Test Market => Introduction => Evaluation
Quality Function Deployment
Determining what will satisfy the customer and translating those customer desires into the target design.
Product Design aspects
Robust design
Modular design
Computer-aided design (CAD)
Robust design
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
Modular design
Products designed in easily segmented components
Adds flexibility to both production and marketing
Improved ability to satisfy customer requirements
Computer-aided design (CAD)
Using computers to design products and prepare engineering docs
Shorter development cycles, improved accuracy, lower cost
Information and designs can be deployed worldwide
Product Design aspects
Computer-aided manufacturing (CAM)
Virtual reality technology
Value analysis
Environmentally friendly design
Defining The Product
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
