Quantitative forecasting methods in management

1
Quantitative forecasting methods in management

• Prof. Dr. Algirdas Budrevicius
• Vilnius University, Faculty of Communication

Course website http//www.kf.vu.lt/albud/progn/P
ortugal
2

• Famous forecasting quates
• --William Shakespeare
• "If you can look into the seeds of time, and say
  which grain will grow and which will not, speak
  then unto me. "

3

• "It is far better to foresee even without
  certainty than not to foresee at all. "
• --Henri Poincare in The Foundations of Science,
  page 129.

4
Course materials

• Course description Website http//www.kf.vu.lt/a
  lbud/progn/Portugal
• Demonstrations PowerPoint presentations
• Time-series data, forecasting examples (Excel
  workbooks), assignments

5
Course plan

• Look http//www.kf.vu.lt/albud/progn/PortugalLe
  ctures

6
Part 1. Forecasting methods in general
7
History development of the forecasting technique

• Non scientiffic forecasting e.g. Astrology, Book
  of Changes.
• 19-20 century. Demographic forecasts
• Development of the quantitative methods
  middle-to-second part of the 20th century.
• New developments Neural network based methods

8
Current situation in forecasting

• Forecasting is widely used in management now
• There exist a well defined set of quantitative
  forecasting methods
• There exists computer software that may be quite
  simply applied in forecasting
• Excel program allows to solve simple forecasting
  tasks

9
Forecasting in management
Forecasting is used in various domains of
management

• Personnel management
• Resource management
• Finance management
• Organizational management

10
Taxonomy of forecasting methods

• Methods quantitative and qualitative
• Qualitative judgmental (based on expert
  opinions) and technological (used for long term
  forecasting)
• Quantitative time series methods and reasoning
• Note only time series methods will be considered
  in this course.

11
Naive forecasting techniques

• Naive forecasts a folk forecasting technique
• In every day life situations we forecast using
  very simple technique
• This technique is close to linear trend model

12
Naive forecasts NF1 and NF2

• NF1. (The value tomorow will be the same as
  today). Example Number of visitors today was
  120. Forecast NF1 for tomorow 120.
• NF2. (The value tomorow will be less (greater)
  by 10 ). Example Average temperature this
  month is 20 degrees. Forecast NF2 for the next
  month Temperature will be 25 degrees (increase
  of 25).

13
Quantitative time-series based forecasting a
rationale
14
Time-series methods of forecasting

• Time-series analysis relies on historical data
  and attempts to project historical patterns into
  the future
• Note only time series methods will further be
  considered

15
Example of time-series data

• Number of visitors (in th.)

16
Example of time-series data

• EVOLUÇÃO DA CAPACIDADE DOS ESTABELECIMENTOS
  HOTELEIROS EM PORTUGAL (a)
• (Camas)
• Anos Total Geral Hotéis Pousadas e Estalagens
  Pensões Hotéis Apartamentos Motéis
• 1992 151063 76427 4035 44845 24344 1412
• 1993 155356 77199 4452 46372 26079 1254
• 1994 161729 82353 4767 43327 30025 1257
• 1995 162954 83372 4873 43306 30166 1237
• 1996 166030 86598 5081 42732 30383 1236
• 1997 164066 88601 5716 41979 26308 1462
• 1998 168396 93357 6186 40310 27013 1530
• 1999 170863 94217 6446 40537 28076 1587
• 2000 177328 98434 6826 40721 29764 1583
• 2001 183919 101684 7112 41588 31757 1778
• 2002 187265 104727 7460 40594 32725 1759
• 2003 192480 109528 7442 41930 31755 1825
• Fonte INE
• (a) Não inclui Aldeamentos nem Apartamentos
  Turísticos

17
Definition of a forecasting situation

• Data (time series, or historical data)
• Forecasting method (e.g. Moving average, Trend
  analysis)
• Forecast
• Error of forecast

18
Basic steps of a forecasting task

• Defining the problem
• Choosing time-series data
• Analysing visually data paterns
• Choosing a model
• Calculating a forecast
• Evaluating the forecasting accuracy, caculating
  errors

19
Recomended form to present data and forecasts an
example
20
Example of data
21
Patterns of the time-series data
A forecasting method should comply with the data
pattern.
22
Example of forecasting
23
Forecast accuracy

• Forecast accuracy can be determined only when
  actual (future) data are available.
• Error of a forecast is measured as a difference
  between the actual and forecasted values

24
End