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Avengers - Demand Forecasting

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on 4 May 2014

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Transcript of Avengers - Demand Forecasting

1. External environmental evaluation
Achievable and realistic targets
Key to profitability, higher revenues
What is Demand Forecast?
$400M Loss
2000: new demand forecasting system
9 months later: massive inventory write-off
Result: $90M order of wrong shoes & $80M shortfall on popular shoes
Christmas 1999: millions of $ on advertising
Unable to fulfill 10% of the orders placed
Poor customer service
Late delivery on orders

Lucy and the Chocolate Factory
Quantitative (Objective)
Qualitative (Subjective)
Intuitive information received from various surveys by carrying out expert point of view analysis
Delphi Method
Collective Opinion Survey
Criteria for Selection
Degree of accuracy
What are our key takeaways?
How to do it?
"I will never buy online again"
Why should it be done?
What is Demand?
6. Set performance/ error measures for the forecast
3. Formulation of forecast objective
7. Perform forecast
8. Verification
2. Separation of market demand according to segments
4. Collection of data
5. Determination of appropriate forecasting method
(Adams, 1986)
(Shim, Siegel & Liew, 1994)
(Bails & Peppers, 1993)
"A firm's best estimate of what demand will be in the future, given a set of assumptions."
(Moon, 2013, p. 32 )
(Chendroyaperumal, 2008, p. 1)
"Assigning a value to the quantity of product 'x' that will be demanded at a future point of time."
The Need
to Buy
Survey of Customer Opinion
Analyze mainly historical data by taking into account trends, seasonality and
other influences on demand
Time - Series
Identifying recurring patterns of demand driven by time
Predicting demand based on measurable factors other than time that affect demand
Uncomplicated data accessibility
Evaluation of economic
interrelationship and fluctuation
Unsuitable for demand forecast of new products
High costs due to requirement of constant market analysis
Quantitative Methods
Possible threat of "black-box forecasting" and
misinterpretation of results
Suitable for demand forecast in new markets
Development of opinion diversity
Subjective experts' opinion
No assessment of economic data interrelationship and fluctuation
Qualitative Methods
Forecast reliability increases due to experts' anonymity
Inappropriate for development of short-term forecast
Simple/ Linear
Dependent Variable: Demand (y)
Independent Variable: Factors that influence demand
One independent variable
Linear relationship
Is there a relationship between demand and the independent variable?

What if I as a manager plan to spend $200,000 into promotion, can you tell me the forecast for the demand?
are integral for demand forecasting
Population (Germany 2011)
Chain-Ratio Method
x % Aged 16+
x % Consuming alcoholic beverages
x % Consuming beer
x % Consuming light beer
Potential Market Size
Trend, Seasonality, Cyclical, Random
Moving Average
Smoothes out short-term fluctuations and highlights long-term trends or cycles while taking a fixed number of periods
Exponential Smoothing
Exponentially assigning pattern of weightages: weightage for the most recent period and for each successive older period decreases exponentially
Weighted Moving Average
Varying weightages for demands in previous periods, whereby weights must sum up to 1
Forecast Errors
Difference between the actual demand and the predicted demand
Mean Absolute Deviation (MAD)
What will we learn today?
What is demand forecasting?
Why do we do it?
How do we do it?
Where does it all lead to?
Make friends
and have fun :)
Consistent pattern of over- or underestimating
Average of the forecast errors neglecting the direction of the errors
Welcome on board trainees!
Thank you team! See you tomorrow :)
In case of high accuracy forecast:
MAD = O; Bias = 0

Lower percentage of error and higher accuracy
(Adapted from: Zukunftsinstitut, 2014)
Now it's your turn!
Can you quantify that relationship?
Case Study:

Increased competition
Changing customer preferences
Improved planning of supply chain
Recognition of rapid market changes
Improved customer service level
Where does it all lead to?
Type and amount of initial information
Time span of forecast
Costs involved
Demand = what consumers will buy if they could
Forecasting is our best guess of future demand
It needs to be taken seriously
Selection of appropriate forecast method
Both quantitative and qualitative are necessary
Avoid black-box forecasting
Good demand forecasting leads to higher ROI!
Inventory investment
Inventory carrying cost
Raw material cost
(Adapted from: Mentzer, 1999)
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