1 - Introduction

Question 1

What types of analytics are there?

Answer 1

Prescriptive
-> plan under uncertainty, using robust optimization, heuristics

Predictive
-> evaluate scenarios and strategies, using forecasts, classification, regression, inductive statistics, simulation

Descriptive
-> exploratory and descriptive data analysis, using data warehouse, OLAP, clustering, statistics, data visualization

Question 2

Descriptive analysis

Answer 2

• prepares and analyzes historical data

- identifies patterns from samples for reporting of trends

Question 3

Descriptive analysis

Methods

Answer 3

• Descriptive statistics, e.g. moments
• Data mining, e.g. clustering
• Visualization

Question 4

Descriptive Analysis

Example

Answer 4

• Compare mean distributions and variation to observe systematic differences between forecasts and sales

Question 5

Predictive Analysis

Answer 5

• Predicts future probabilities and trends

- Finds relationships in data that may not be readily apparent with descriptive analysis

Question 6

Predictive Analysis

Methods

Answer 6

• Inductive statistics, e.g. exponential smoothing and regression
• Data mining for predictions, e.g. on customer responses

Question 7

Prescriptive Analysis

Answer 7

• Evaluates and determines new ways to operate

- Targets business objectives given a set of contraints

Question 8

Prescriptive Analysis

Methods

Answer 8

• Evaluates and determines new ways to - Mathematical modeling
• Analytical optimization
• Heuristics and meta-heuristics

Question 9

Prescriptive Analysis

Example

Answer 9

Multi-criteria optimization to allocate the assignment of “Blindbookings” to specific flights

Question 10

Data Analysis in Advanced Analytics

Answer 10

Descriptive:

• statistics to describe the data
• visualizations

Model driven

• also: inductive
• pick the “best” model for your data, parametrize it, evaluate the results

Data driven

• also: exploratory, data mining
• consider patterns in the data using computational algorithms

-> for maximum impact, combine model driven and data driven approaches

Question 11

Simulation in Advanced Analytics

Components

Answer 11

Status Quo
Basic Scenario
What-if Scenario

Question 12

Simulation in Advanced Analytics

Answer 12

In the real world there’s a status quo: the system as it currently functions in the real world.

Based on this you calibrate a basic scenario for a simulation model. In the basic scenario models describe the structure and data analysis fills parameters. Models need validation, though.

The what-if Scenario is derived from the basic scenario through relative changes in parameters or structural changes in algorithms. The what-if scenario can be interpreted in its relationship to the real future.

Question 13

Optimization in Advanced Analytics

What kinds of optimization are there?

Answer 13

deterministic

robust

Question 14

Optimization in Advanced Analytics

Deterministic optimization

Answer 14

Deterministic (not robust) optimization determines the best solution for a single parameter set
-> this is great when you know exactly what the parameters are going to be

Question 15

Optimization in Advanced Analytics

Robust optimization

Answer 15

Robust optimization considers a number of possible parameter sets (scenarios) and determines the solution that is the best “compromise” for all

• > this is great, when you have an idea of possible scenarios
• > even better if you can estimate the probability per scenario

Question 16

Teams for analytics

Success factors of Teams

Answer 16

• Small groups
• Complementary abilities
• Everyone has a clear view of the joint objective and is motivated to achieve it
• Everyone puts in the same amount of work using similar tools
• Everyone is bound to hold themselves and the others to accountable