Data

1
Data Business Decision

• (Lesson - 01)
• Role of Data in modern Organization

2
Management by Fact

• As a manager you observed a decline in
  Stockholder satisfaction. (the Business
  Situation)
• You believe that the Stockholder satisfaction is
  a function of Revenues, Profits Before Taxes,
  Return on Assets and Earnings per Share. (the
  Model, and the variables)
• You analyze the data on these variables and
  decide on increasing Earnings per Share. (the
  Decision)
• You are managing by Fact

3
Management by Fact

• Managing based on models that explain the
  relationship between
• the Business Situation and
• Decision
• is called
• Management by Fact.

4
Management by Fact Tools

• Data Analysis
• Decision Modeling
• One of the most important tool for data
  analysis is Statistics.

5
Role of Data Analysis in Business

• is to extract larger meaning from data
• in order to support
• Evaluation and
• Decision-making.

6
Types of Business Data

• Customer Satisfaction Data.
• Financial Data
• Market Performance Data
• Human Resources Data
• Supplier and Partner Performance Data
• Organizational Effectiveness Data.

End-User Satisfaction, etc.
EPS, ROI, etc.
Market share, Sales, etc
Employee satisfaction etc
Defects, etc.
Response Time, etc.
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Statistics

• - Definition
• Role
• Types

• is science of
• Collecting,
• Organizing,
• Interpreting, and
• Presenting
• data.

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Statistics

• - Definition
• Role
• Types

• to Draw Inferences
• (Increases in Sales are not stable)
• to Monitor the Effectiveness of
• business processes.
• (Customer Satisfaction Customer Satisfaction
  Index)

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Statistics

• - Definition
• Role
• Types

• Descriptive Statistics
• (Gender distribution of customers)
• Statistical Inference
• (Impact of age on color preference)
• Predictive Statistics.
• (Number of expected visitors next year)

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Decision Model

• - Definition
• Role
• Types

• is
• Logical or
• Mathematical
• representation of a business situation (or
  problem)
• Room_Sales f(Room_Price, Advertisement,
  Service_Quality, etc.).

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Decision Model

• - Definition
• Role
• Types

• is to establish a relationship between
• Actions and
• Results.
• ( 5 ? Room_Rates ? 3 ? Room_Sales )

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Decision Model

• - Definition
• Role
• Types

• Regression Models
• Forecasting Models
• Selection Models
• Simulation Models
• Optimization Models.

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Data Scales

• Data scales can be defined two ways
• In terms of quality of data scale, such as Ratio,
  Interval, Ordinal, Nominal
• In terms of time of data scale, such as time
  series , cross-sectional

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Scales of Measurement

• Ratio ( natural zero, fixed unite of measure,
  Sales)
• Interval (no natural zero, fixed unite of
  measure, C)

• Ordinal (no fixed unite of measurement, ranking,
  Priorities)
• Categorical / Nominal (no ranking, Religion)
• No meaningful comparison of ranges, averages, and
  other statistics.

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Scales of Measurement

• Ratio
• natural zero, constant scale, ranked
• e.g., number of rooms sales, length of stay, age
  of guests,
• Interval
• no natural zero but constant scale, ranked,
• differences make sense, but ratios do not
• (e.g., 30-2020-10, but 20/10 is not twice
  as hot!
• e.g., temperature (C,F), longitudes, dates
• Ordinal
• No constant scale, ranked but differences between
  values are not important
• e.g., hotel ratings
• Surway data although ordinal could be treated
  like interval
• e.g., degree of guest satisfaction Likert
  scales, rank on a scale of 1..7
• Categorical / Nominal
• classification data, e.g. m/f,
• no ranking, e.g. it makes no sense to state that
  M gt F
• arbitrary labels, e.g., m/f, 0/1, etc
• also called count data since only numerical
  aspect is the number of observations

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Time Scale of Data

• Time Series
• Different dates different observation.
• Room sales of one hotel over many months
• Ctross Sectional
• On one date there are many observation
• Room sales of many hotels for a particular month.

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Time Series Data

• Time Series Data means that each observation is
  link to one unique time period different from the
  rest.
• One date - one observation
• The sequence of the data cannot be changed.

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Cross-sectional Data

• Cross Sectional Data means that there is one time
  period at which many observations are recorder.
• One date - many observations
• The sequence of the data can be changed.

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Data Scales in SPSS

• Scale Data
• (both Ratio or Interval data are grouped under
  this name)
• Ordinal Data
• Categorical Data

• Numeric Data (Scale Ordinal data)
• String Data (Categorical data)

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ExampleTypes of Data Scales

• Trees are surveyed and their species and height
  are measured. The levels of measurement for the
  two variables (species and height) are
• Nominal (Categorical) and Interval
• Ratio and Interval
• Categorical (Nominal) and Ratio
• Ordinal and Full

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ExampleTypes of Data Scales (cont.)

• Which of the following variables is measured at
  the Ordinal level?
• Mean annual rainfall (e.g. millimeters)
• Town Post-codes (e.g. 2840)
• Accommodation ratings (e.g. 5 star, 4 star)
• Temperature (e.g. degrees Celsius)

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ExampleTypes of Data Scales (cont.)

• Which of the following is NOT measured at the
  Nominal level of measurement?
• Eye Color
• Income Tax Bracket
• Country of birth
• Post-code

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How Data are used in Evaluating and Solving
Business Problems
Role of Statistics in Business Is to draw
inferences and to monitor the effectiveness of
business processes. Statistics is science of
Collecting, Organizing, Interpreting, and
Presenting data.
Role of Decision Modeling in Business Is to
establish a relationship between actions and
results. Decision Model is logical or
mathematical relation of a business situation (or
problem).
Role of Data Analysis in Business Is to extract
larger meaning from data to support evaluation
and decision making. One of the most important
tool for data analysis is statistics.
Regression Models Forecasting Models
Selection Models Simulation Models
Optimization Models
Descriptive Statistics Statistical
Inference Predictive Statistics
Customer Satisfaction Data Market
Performance Data Human Resources Data
Supplier Performance Data Effectiveness Data
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Next Lesson

• (Lesson - 02)
• Displaying Summarizing Data