04_Demand Forecasting

Question 1

Purpose of contents of operational planning level

-

Answer 1

• smoothing of seasonal variations of capacity requirements and available capacity
• determine master production schedule (which products in which quantities)
  - procurement planning: which quantities of input materials are needed for master scheduling

Question 2

Chase Demand vs Level Production strategy

pros and cons

Answer 2

Chase demand:
- low inventories, but high capacities
- updating plan every month based on incoming aggregated sales data
Level Production:
- high inventories, low capacities

Question 3

Demand forecasting

Definion and Types of time series

Answer 3

• prediction of future values of a time series (demand patterns) under uncertainty (based on historical values)
  Types of time series:
  1. Level Demand
  2. Linear Trend
  3. Seasonal Variation

Question 4

Analysis of the characteristics of a time series

Answer 4

• long term
• mid-term cyclical variations (eg economic cycles, product lifecycle)
• seasonal fluctuations (eg. annual seasons)
• random variations

Question 5

Procedure of time series based forecasting

5 Steps

Answer 5

1. Analysis of characteristics of time series
2. selecting appropriate forecast model
3. estimate coefficients of forecast model
4. apply forecast model
5. monitor and analyse forecast accuracy over time (tracing errors)

Question 6

Ex ante forecast values
vs
Ex post forecast values

Answer 6

• ex ante: forecast for following period
• ex post: previous forecast

Question 7

Forecasting Models

Answer 7

• Simple exponential smoothing (level demand time series)
• Exponential smoothing with trend adjustment (linear trend time series)

Question 8

Simple Exponential Smoothing

forecasting model for level demand time series

Answer 8

• random variations around a constant demand level
• initialization Po has to be determined (often yo is chosen)
• smoothing paramter alpha: determines the strenght of the smoothing effect
• the higher alpha the closer you get to observed demand (naive forecast)

Question 9

Formula Simple Exponential Smoothing

Answer 9

Pt+1 = alpha x yt + (1-alpha) x Pt

(weighting of previously observed demand and previous forecast adjusted for errors)

yt = observed demand in period t ; Pt = forecast period t

Question 10

Exponential Smoothing with trend adjustment

forecasting model for trend line time series

Answer 10

• assumed demand process: random variations around linear trend
• simple exponential smoothing causes systematic error
• introdruce trend adjustment (correction factor) to adjust for systematic lag
• Initialization: before first forecast determination adequate initial values a0 and b0 have to be determined, e.g. through linear regressen

Question 11

Exponential Smoothing with trend adjustment

Step by Step

Answer 11

1. update of level demand at end of period t (at)
2. update of trend at end of period t (bt)
3. Forecast determination

Question 12

Which measured can be taken to match production and demand

Answer 12

• build up inventories
• backlog demand
• lost sales
• additional workforce
• rent machinery

Question 13

Level Demand

Type of Time Series

Answer 13

• levels are established with random fluctuations around them
• simple exponential smoothing

Question 14

Linear Trend

Type of time series

Answer 14

• average going up with fluctuations around it
• exponential smoothing with trend adjustment

Question 15

Seasonal Variation

3 types of time series

Answer 15

• seasonal peaks
• e.g. construction industry

Question 16

Exponential smoothing with trend adjustment

the smaller alpha

e.g. 0.2

Answer 16

• the larger deviations from ideal trend line

Question 17

Trend Adjustment

Exponential smoothing with trend adjustment

Answer 17

• correction factor

[(1 - alpha) / alph] * b

Question 18

Initialization Formula
Level Demand

Exponential smoothing with trend adjustment

Answer 18

a(0) = y(0) - [(1-alpha/alpha) x b(0)]

b(0) = trend increase per period

Question 19

Forecast Determination P(t+τ)
Formula

Exponential smoothing with trend adjustment

Answer 19

P(t+τ) = a(t) + b(t) x [(1-alpha) / alpha] + τ x b(t)

Question 20

Update of trend
Formula

Exponential Smoothing with trend line adjustment

Answer 20

b(t) = alpha x (a(t) - a(t-1)) + (1-alpha) x b(t-1)

Question 21

Update Level Demand
Formula

Exponential smoothing with trend adjustment

Answer 21

a(t) = alpha x y(t) + [(1-alpha) x a(t-1)]

Question 22

Simple Exponential Smoothing

The company wants to calculate in period t=5 a demand forecat for period t=7. What is the value for the forecast?

Answer 22

P(7) = P(6)
- as demand y(5) is used

Question 23

What is the de-trended initial value?

Answer 23

• a(0) of exponential smoothing with trend line
• initialization

Question 24

Difference when forecasting for t(6) and t(7) from t(5) on but demand is not nown for t(6) nor (t7)

Simple exponential smoothing
vs.
Exponential smoothing with trend line adjustment

Answer 24

Simple exponential Smoothing

P(t+1) = α x yt + (1-α) x Pt
- y(t) = P(t)
- Smoothing will return same result as for P(5)

Exponential Smoothing with trend line adjustment

P(t+𝜏) = a(t) + b(t) x (1-α)/α + 𝜏 x b(t)

• Take coefficients from t = 5 -> a(5) and b(5) and add 1 year for P(6) and 2 years for P(7)

=> the results will vary significantly between both models