Lets Experience CL

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Lets Experience CL

• An Active Learning Simulation

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Forecasting
Art
Luck
Science
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Forecasting Approaches

• Qualitative
• Ex executive opinion, Delphi method, consumer
  survey.
• Quantitative
• Time-series Model
• Naive approach
• Moving averages
• Exponential smoothing
• Associative Model
• Trend Projection
• Linear Regression

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Time-series Models

• Naïve Approach
• - simplest
• - if AMay 65, FJune ?
• Moving Averages
• Simple Moving Average
• Ft S At-i/n (i 1,,n)
• If actual demand for May, June, July 18, 16,
  14 respectively,
• FAugust

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Time-series Models

• Weighted Moving Average
• Ft S ci (At-i) / S ci (i 1,.,n)
• where ci weight given to ith actual value
• If n 3, and weighted applied for last month,
  two months ago and three months ago is 3, 2 and 1
  respectively.
• Actual demand for May, Jun, July is 18, 16, 14,
  resp.
• FAugust

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Time-series Models

• Exponential Smoothing
• Ft Ft-1 ? (At-1 Ft-1)
• where ? smoothing constant (0 ? ? ? 1)
• In January, a car dealer predicted February
  demand for 142 cars. Actual February demand was
  153. Using ? 0.20, what is the forecast demand
  for March?
• FMarch

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Measuring Forecast Error

• During the past 4 quarters, the Port Tanjung
  Pelepas has unloaded large quantities of rice
  from ships. The ports operations manager wants
  to test the use of exponential smoothing to see
  how well the technique works in predicting
  tonnage unloaded. He guesses that forecast of
  rice unloaded in the first quarter was 175 tons.
  Two values of ? are examined ? 0.1 and ?
  0.5. The actual demand for quarter 1, 2, 3 and 4
  come out to be 180, 168, 159 and 175 tons. Which
  ? value is preferred?

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Lets Think

• 1. n ??
• 2. ? ??
• 3. Which approach is the best ?
• 4. Monitoring and controlling ?

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Reflection on the CL Session
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Differences with Lectures
Reading acquiring technical content
Interpersonal skills
Thinking skills
Active Participation OBE

• Team-working

Communication