We are pleased to offer the following series of webinars (all times PDT, UTC−07:00). Each webinar is 60 minutes long.
Introduction to Probability Management (Sam Savage): Friday, April 12, 10:00 AM
SIPmath Modeler Tools Basics (Brian Putt): Friday, April 26, 8:00 AM and Thursday, June 13, 4:00 PM
The Metalog Distributions (Tom Keelin): Monday, April 29, 9:00 AM
Beyond Risk Management: How Embracing Uncertainty Helps the Whole Enterprise (Matthew Raphaelson): Wednesday, May 15, 10:00 AM
Virtual SIPs (Sam Savage): Wednesday, June 5, 10:00 AM
Risk-Aware Planning for City Finances: How Much of a Rainy Day Fund is Enough? (Shayne Kavanagh & Dan Matusiewicz): Wednesday, June 26, 10:00 AM
Webinars are $50 each or $250 for all webinars. To register for all webinars, select "Multi-webinar package" for one webinar. Before registering for the other webinars, contact Mary Claire Meijer for the discount code to waive registration fees for the remaining webinars.
Friday, April 12, 10:00 AM PDT
Introduction to Probability Management
The discipline of probability management is a revolutionary approach for communicating uncertainty as data. It may be used with everyday software such as Excel, Matlab, and R. Unlike traditional techniques, it allows simulation models to be rolled up into consolidated risk statements. Topics include:
The Flaw of Averages: Learn why expressing uncertainties as a single “average” numbers causes projects to be behind schedule, beyond budget, and below projection. Learn how to make consistently better decisions by explicitly modeling uncertainty.
Communicating Uncertainty as Data: The discipline of probability management communicates uncertainty as arrays a data called SIPs (Stochastic Information Packets). SIPs may be communicated across platforms across the enterprise to generate consolidated risk statements.
SIPmath, The Arithmetic of Uncertainty: Performing calculations with SIPs is called SIPmath. In native Excel, for example, you may add, multiply or use any other Excel formula on uncertainties using the same keystrokes you would have used for numbers. The magic is the Excel Data Table, which can perform thousands of simulation trials per keystroke. The free SIPmath tools available at our website make it easy to create such simulations, but the resulting models run in native Excel with no macros or add ins.
Real World Examples: Examples of actual applications will be demonstrated including:
Portfolios of R&D Projects
Rolling up Operational Risk
Friday, April 26, 8:00 AM PDT
Thursday, June 13, 4:00 PM PDT
SIPmath Modeler Tools Basics
In this tutorial webinar, you will learn how to use the free 3.0 SIPmath Modeler Tools, available on our website. With these tools you can easily create dynamic simulation models that can run in Microsoft Excel without any macros or add-ins. Create new models or make your existing deterministic model robust to reflect uncertainty using the SIPmath Tools.
New Features in 3.0 Version:
Generates a wide array of probability distributions to include the Myerson and Metalog distributions.
Utilize and control separate random number seeds to ensure repeatability in the model.
Easily calculate Means and percentiles of random variables.
Generates histograms of the distribution and Cumulative Distribution Graphs that are automatically updated with model changes.
Supports Excel 2010 and newer in Windows, Excel 2016 and newer on Mac.
Monday, April 29, 9:00 AM PDT
The Metalog Distributions
The metalog distributions are an innovative new family of continuous probability distributions that better meet many of today’s needs than conventional distributions from centuries past. The metalogs can represent a much wider range of shapes than conventional distributions like the normal, lognormal, beta, or triangular. Being quantile-parameterized, metalogs automatically mold themselves to assessed or empirical data, eliminating any need for curve-fitting. They offer a choice among unbounded, semi-bounded, and bounded forms and have simple, closed-form, easy-to-program equations – making them ideal for decision analysis, simulation, and instant representation of most any assessed or empirical probabilistic data.
Wednesday, May 15, 10:00 AM
Beyond Risk Management: How Embracing Uncertainty Helps the Whole Enterprise
Models that embrace uncertainty have been gaining traction in risk management. Matthew Raphaelson, based on his executive management experience spanning dozens of lines of businesses, will demonstrate how simulation-based models can be applied to the rest of the enterprise - marketing, sales, operations, financial management...even human resources! In this webinar, Matthew will demonstrate how interactive models built using SIPMath tools can help managers in all disciplines ask better questions and make better decisions.
Wednesday, June 5, 10:00 AM PDT
The open SIPmath™ Standard represents uncertainties as arrays of outcomes and metadata called SIPs (Stochastic Information Packets). SIPs play a role in probabilistic calculations analogous to the role of Arabic numerals in deterministic calculations. This allows simulations running on diverse platforms to be networked into enterprise wide systems. The simplicity of the approach allows for implementation in native Excel.
Two recent breakthroughs, the HDR™ Random Number Framework and the Metalog™ System for analytically matching probability distributions to data, extend the SIPmath standard to virtual SIPs, which are generated in the client environment. This can reduce the storage requirements to a tiny fraction of standard SIPs.
As an analogy, just as you can add water to powdered milk or powdered Kool-Aid to get milk or Kool-Aid, you can add a stream of uniform random numbers to a Metalog to get virtually any continuous probability distribution. And what is the HDR Framework in this analogy? Powdered Water.
Wednesday, June 26, 10:00 AM PDT
Risk-Aware Planning for City Finances: How Much of a Rainy Day Fund is Enough?
How much money do cities need to have in reserve to be prepared to respond to extreme events? Too little could leave the community exposed to unexpected losses. Too much could meet with disapproval from the public. The right amount of reserves requires cities to know their risks. In this webinar, you will see a real-life probability management risk model used by multiple cities in the United States and Canada to help them think about the risks they are exposed to and how that has shaped their decision-making about their financial reserves.