Modeling Time Series Forecasts with @RISK

Overview

Making decisions for the future is becoming harder and harder because of the ever increasing sources and rate of uncertainty that can impact the final outcome of a project or investment. Several tools have proven instrumental in assisting managers and decision makers tackle this: Time Series Forecasting, Judgmental Forecasting and Simulation.

This free live webcast is going to present these approaches and how they can be combined to improve both tactical and strategic decision making. We will also cover the role of analytics in the organization and how it has evolved over time to give participants strategies to mobilize analytics talent within the firm.

We will discuss these topics as well as present practical models and applications using @RISK.

Discussion Topics:

Analytics and the organization

• The history of time series analysis methods (from the Census Method to Today)
• Different organizational models for developing and delivering time series analytics to organizational decision makers.

Time Series Basics

• Overview of conventional Time series Methods.
• Linear Regression
• Random Walks
• Trend Charts

Integrating expert judgment/opinion into your time-series predictions

• Working with ranges to understand the forecaster’s bias.
• Modeling Expert Opinion using a Power Curve Envelop Method
• Model Splicing
• Time-Phased Decision Trees

Overview of empirical/data driven time series methods

• Auto-regressive models
• Moving Averages
• Wilkie Models
• Markov chains