Managing Disruptive Projects Using Business Analytics & Big Data

Workshop Overview

Performance enhancement has always been all organizations’ main goal. To gain competitive edges, decisions are made concerning problems solution in ways initially related to the art of management. Tech support helped the organization of these efforts at first but the competitive edge has always been in analysis based on which decisions are optimized. This course is about the disruptive introduction of Business Analytics as the ultimate strategic weapon of mass success and it is permeating all fields of Management, recently Project Management.

Learning Objectives

  1. Understand the importance of decision analysis in projects.
  2. Identify the various elements of analytics and their interaction.
  3. Organize analytics into project strategic structures.
  4. Resolve example cases of analytics across the Project Management practice.
  5. Optimize analytical tool selection.

Course Outline

  • Introduction to Analytics
    • Problem solving and decision making strategies
    • Analytics categories: Descriptive, Predictive and Prescriptive
    • Big Data descriptors
    • Business analytics practice
  • Exploring data
    • Data modification
    • Data visualization
  • Sampling inference
    • Selecting samples
    • Point estimation
    • Interval estimation
  • Hypothesis testing
    • Testing means
    • Testing dispersion
  • Regression analysis
    • Least square curve fitting
    • Linear and nonlinear data
    • Goodness of fit
  • Time series and forecasting
    • Types of randomness
    • Stationary data
    • Trend data
    • Seasonal data
  • Decision making with certainty
    • Deterministic models of decision
    • Spreadsheet modeling
  • Decision making under uncertainty
    • Contingency tables
    • Attitude of stakeholders
  • Decision making under risk
    • Structural elements of decisions
    • Influence diagrams
    • Decision trees
    • Value of information
  • Introduction to optimization models
    • Linear programming
    • Models and applications
    • Computerized solution
    • Sensitivity analysis
  • Introduction to simulation models
    • The concept of simulation
    • Simulation structure and properties
    • Models for simulation

 Course Duration

21 Hours

Workshop Format

Hands-on approach with short instruction and mini-cases.

Intended Audience

Decision makers, public administrators, decision owners, Monitoring stakeholders, Sponsors, Business leaders, General managers, Project managers, Operations managers, Strategic consultants, Functional managers, Claim evaluators, Risk profilers.

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