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IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004
Model-Driven Business Model-Driven Business Intelligence Systems: Intelligence Systems: Part IIPart II
Week 9Dr. Jocelyn San PedroSchool of Information
Management & SystemsMonash University
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004 2
Lecture OutlineLecture Outline Trend Analysis Seasonality Analysis Multiplicative Decomposition of a Time
Series Causal Forecasting Models Decision Trees Influence Diagrams
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Learning ObjectivesLearning ObjectivesAt the end of this lecture, the students will Have understanding of some models used in
model-driven business intelligence systems Specifically, have understanding of trend
analysis, and seasonality analysis; decision trees and influence diagrams for decision modelling
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Trend AnalysisTrend Analysis Fits a trend equation (or curve) to a series of
historical data points Projects this curve into the future for medium-
and long-term forecasts Trend equations – linear, quadratic, exponential,
…
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Linear RegressionLinear Regression Least Squares Procedure
Fits a line that minimises the sum of the squares of vertical differences from the line to each of the actual observations – i.e. minimises the sum of squared errors
Least squares line: Y = a + bX a is the y-axis intercept b is the slope of the regression line
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Trend Analysis
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1 2 3 4 5 6 7
Time
Val
ue Actual values
Trend line
Vertical difference betw een trend line and actual observation
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Linear Trend Analysis- Linear Trend Analysis- ExcelModulesExcelModules
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Seasonality AnalysisSeasonality Analysis Recurring variations at certain periods (i.e.,
months) of the year make a seasonal adjustment in the time series necessary
E.g., demand for coal and oil fuel usually peaks in cold winter months; demand for sunscreen may be highest in summer
Seasonal Index – ratio of the average value of the item in season to the overall annual average value
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Example - ExcelModulesExample - ExcelModules
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Seasonality AnalysisSeasonality Analysis Seasonal Index <1 indicates demand is below
average that month Seasonal index >1 indicated demand is above
average that month Use the seasonal indices to adjust the monthly
demand for any future month Example: If 3rd year’s average demand is 100
units, forecast for January’s monthly demand is 100 x 0.957
= 96 units, (which is below average) Forecast for May’s monthly demand is 100 x 1.309=
131 units, (which is above average)
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Multiplicative Decomposition of a Multiplicative Decomposition of a Time SeriesTime Series
Breaks down a time series into two components Seasonal component A combination of the trend and cycle
component (simply called trend) Forecast is calculated a product of composite
trend and seasonality components
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Multiplicative Decomposition in ExcelModules
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Causal Forecasting ModelsCausal Forecasting Models Purpose is to develop a mathematical relationship
between one or more factors affecting a variable Example: sales of swimwear are likely to depend
on average daily temperature, price, advertising budget
Sales – dependent variable average daily temperature, price, advertising
budget – independent variables Most common methods
Linear regression – Y = a + bX Multiple regression – Y = a+b1X1+b2X2 +…bpXp
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Influence diagramsInfluence diagrams An influence diagram is a simple visual
representation of a decision problem Influence diagrams offer an intuitive way to
identify and display the essential elements, including decisions, uncertainties, and objectives, and how they influence each other.
http://www.lumina.com/software/influencediagrams.html
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Influence DiagramsInfluence Diagrams
http://www.lumina.com/software/influencediagrams.html
IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1 , 2004 16http://www.lumina.com/software/influencediagrams.html
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ExampleExample
Influence diagram for R&D and commercialization of a new product
http://www.lumina.com/software/influencediagrams.html
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Example - GenieExample - Genie
http://www2.sis.pitt.edu/~genie/
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Example - GenieExample - Genie
http://www2.sis.pitt.edu/~genie/
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Decision TreesDecision Trees
http://www.lumina.com/software/influencediagrams.html
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Example – TreePlan Example – TreePlan
Render, B., Stair, R. and Balakrishnan, N. (2003) Managerial Decision Modeling, Prentice Hall.
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ReferencesReferencesLangley, R. (1970) Practical Statistics Simple
Explained, Dover Publications, NY. Render, B., Stair, R. and Balakrishnan, N. (2003)
Managerial Decision Modeling, Prentice Hall.Render, B., and Stair, R. (1999) Quantitative
Analysis for Management (or any edition)Rowntree, D. (1981) Statistics Without Tears: A
Primer for Non-mathematicians, Penguin Books.Useful online resources: Analytica
www.lumina.com/software/influencediagrams.html
Genie - www2.sis.pitt.edu/~genie/
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Questions?
[email protected] of Information Management and
Systems, Monash UniversityT1.28, T Block, Caulfield Campus
9903 2735
