Explore @RISK for Excel‘s tornado graphs and spider charts to learn how they can be used as a tool to help make more informed decisions. You will learn what the five different types of tornado graphs are, some of their additional features, and how they can be used to figure out which, and how much, the individual input variables impact the output variables that you are most interested in.
Registrants also receive a link with example models and a slidedeck to accompany the presentation.
Due in part to the significant impact of hurricane season on the Gulf Coast of the U.S., Louisiana is considered a “wet lab” for emergency preparedness. As part of its annual preparations, the State creates and maintains plans that involve the full coastal evacuation of entire hospitals and nursing homes in Southeastern Louisiana, mostly via aircraft. Palisade’s @RISK software plays a critical part in both estimating needs, and justifying resources.
“Palisade built a sophisticated model for us that allows us to take the configuration data and construct a model, quickly and easily,” said Henry Yennie of the Louisiana Department of Health (LDH). “@RISK is a really valuable tool that lets us perform up to 10 different scenarios based on patient numbers and other data, plus it has an interface that makes it ‘idiot proof’ for us.” For each scenario, modelers can change evacuation parameters such as airport and plane availability, or patient bed availability.
LDH worked with Palisade’s Custom Development team to create the model. A custom interface allows for easy configuration of model parameters, reducing errors. The LDH can plan ahead of time, and change parameters on the fly during a hurricane to plan during an actual hurricane. According to Yennie, “@RISK gives us benchmarks we can measure against actual patient movements, then lets us know the probabilities of success. By providing us with this estimate of success throughout the process, we’re able to figure out what we can do to fix it right away.”
“I’ve used other simulation software over the years and none has come close to the usability of @RISK,” reports Yennie. “It makes it really easy for a person who doesn’t have a PhD in statistics to build an accurate model of a real-world situation that has an impact.”
Real option valuations are used by existing or prospective owners of power plants to support acquisition, divestiture, development, or retirement decisions. Owners of power plants also use real option valuations to support capital decisions, such as the installation of environmental controls, the expansion of plant capacity, or equipment to improve efficiency.
L.E. Peabody & Associates, Inc., an economic consulting firm, specializes in supporting economic decisions around electric power generating facilities or “power plants.” The company uses Palisade’s @RISK software to measure a power plant’s real option value and define a power plant’s risk profile. Monte Carlo simulation is applied to simulate a power plant’s economic dispatch into uncertain power and fuel prices, thus helping the firm show current and prospective plant owners the full range of possibilities around strategic decisions.
“@RISK allows our firm to easily and comprehensively develop real options analysis for our projects that involve market uncertainty,” says Brian Despard, Vice President with L. E. Peabody & Associates. “As an Excel add-in, it integrates seamlessly into our various spreadsheet models. @RISK’s selection of distributions and functionality provide us with more than enough flexibility to develop our quantitative analyses.”
With $10 Billion in annual sales, 450 different products, 18 different plants and selling in more than 100 different countries, Amway‘s operations are vast and complex. Faced with a planned expansion that eventually added five new manufacturing sites, the Industrial Engineering team wanted to find a solution that required less time for data collection, thereby providing more time for critical analysis. So they partnered with Palisade and its Custom Development team to design a new interface and customize Amway’s Excel-based models, using @RISK in the background to power analyses. The result is a custom application Amway calls the Long Range Capacity Planning (LRCP) tool.
Users across the company were trained on how to use the LRCP tool. Plant managers and capacity experts can enter changes to variables such as demand, output rates, new products and run sizes in real time for a selected plant, and then run up to 20 different “what-if” scenarios individually or in combination and see results almost instantly. Results can be studied on their own or displayed alongside existing baseline scenarios for comparison.
Amway’s new tool has already proven its worth across the company, from both the Plastics and Liquids departments, where it was used to determine the feasibility of shift reductions, to the Nutritional Products plant, where it showed the need for new capacity for a series of new products.
Amway Senior Principal Engineer Phil Miclea expects the demand for the LRCP tool to increase, saying, “When you can satisfy a customer’s curiosity in a single meeting, you’ve gained a fan, a believer and a person who is going to ask you to come to the decision-making table more often.”
This introduction to probabilistic risk analysis will show you how simple it is to add Monte Carlo simulation and other techniques into your models. If you currently build cost estimate models or risk registers in Excel, Palisade solutions can almost certainly help you to make more informed decisions, right from your desktop.
We start with an introductory overview of probabilistic analysis. Then, we show how @RISK risk analysis software can be applied to a simple cost estimation model to quantify the uncertainty. Next, we explore how a risk register can be developed and added, to obtain a fully integrated model which calculates confidence levels and contingency.
For 30 years Palisade software and solutions have been used to make better decisions. Cost estimation, NPV analysis, operational risk registers, portfolio analysis, insurance loss modelling, reserves estimation, schedule risk analysis, budgeting, sales forecasting, and demand forecasting are just some of the ways in which the tools are applied. This webinar will demonstrate how easy – and necessary – it is to implement quantitative risk analysis into a cost estimate.
John R. Schuyler delivers a wholly rewritten and expanded successor to the best-selling prior editions of his book.
Decision analysis provides assistance in making logical, consistent decisions under uncertainty. This book instructs readers in applying decision analysis to a wide range of project decisions. An essential concepts and how-to guide intended for serious Project Management students and practitioners, the scope of the book is quantitative analysis, from project inception to post-project review. The entire asset life cycle is covered, from an initial feasibility analysis, to the project plan, to the post-project review, and on to a look-back analysis of the capital investment decision.
This webinar is designed to provide an entry-level introduction into probabilistic analysis and will show how Monte Carlo simulation and other techniques can be applied to your everyday business analyses. If you build models in Excel then Palisade solutions can almost certainly help you to make more informed decisions, right from your desktop.
The webinar will explore some of the ways in which organisations are applying Palisade tools. From oil and gas, insurance and finance through to healthcare, defence and construction, @RISK and the other tools in the DecisionTools Suite enhance the decision making capabilities of some of the world’s most successful companies.
For more than 30 years, Palisade software and solutions have been used to make better decisions. Cost estimation, NPV analysis, operational risk registers, portfolio analysis, insurance loss modeling, reserves estimation, schedule risk analysis, budgeting, sales forecasting, and demand forecasting are just some of the ways in which the tools are applied. The webinar will demonstrate how easy – and necessary – it is to implement quantitative risk analysis in any business.
Join us for a full day of hands-on software training at Palisade’s Training Workshops in New Delhi, April 19th and Mumbai, April 20th! Learn about @RISK and The DecisionTools Suite software, and how quantitative risk analysis using Monte Carlo simulation can be applied to your problems, directly in Excel.
The program includes a hands-on training workshop run by expert Palisade trainer and consultant Rishi Prabhakar, and case study presentations from industry leaders.
Registration is only GBP/65 per participant, and includes software sessions, lunch, a networking reception, and a full 3-month license of The DecisionTools Suite Industrial version.
Intellectual property (IP) is one of the most valuable assets early stage companies own, and one of the many challenges faced by these companies with no assets other than untested technology is how to determine a fair market value for their IP should they face a civil lawsuit. IP makes a huge contribution to local, national and global economies. Businesses rely on the enforcement of their IP, e.g. patents, trademarks and copyrights, while consumers use IP to ensure they are purchasing safe, guaranteed products. This is why it is important for organizations to protect and understand the value of intellectual property.
Pellegrino & Associates, a boutique valuation company with a specialty in software and IP, uses Palisade’s @RISK software to run Monte Carlo simulations for their risk analysis and to calculate fair IP values, based on discounted future incomes. The method is detailed in the book BVR’s Guide to Intellectual Property Valuation, by Michael Pellegrino, a leading expert in IP valuation.
“We’ve used it on more than 300 client engagements in every major sector of the economy, from software and semiconductors to chemical coatings and consumer electronics,” said Pellegrino. “We apply it to a range of damages models including the assessed value of a product, reasonable royalty payments, total cost of product reproduction, as well as the potential for lost profits – and in all the cases that went to court where we used Monte Carlo simulation, our results were accepted every time.”