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Growing your Internal Analytics Capabilities

This session will conclude the 2020 Power & Utilities webcast series. We will provide a brief review of the key learnings from prior sessions, then pivot to the managerial aspects of achieving buy-in and building an advanced analytics capability. Topics will include:
• Brief recap of prior five sessions
• The business case for stronger analytics
• Why @Risk and DecisionTools Suite are ideally suited for electric utilities
• Communicating results of simulation models
• Best practices for achieving adoption of advanced methods
Recorded Dec 17 2020 72 mins
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Presented by
Glen Justice, Experience On Demand
Presentation preview: Growing your Internal Analytics Capabilities
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  • Insights about Decision Analysis With Case Study Models And Applications Mar 10 2021 4:00 pm UTC 75 mins
    Manuel Carmona, Director Edy Training
    The DecisionTools Suite is an integrated set of programs for risk analysis and decision making under uncertainty. DecisionTools Suite software integrates seamlessly with Microsoft Excel, and includes:

    @RISK – Discover Monte Carlo simulation and scenario analysis for investment appraisal.
    PrecisionTree – Build a Decision Tree analysis for oil exploration.
    TopRank – Learn how to analyze variable sensitivity and explore in depth MsExcel spreadsheet models.
    StatTools – Overview the statistical analysis procedures available.
    Neural Tools- Implement a credit assessment Neural Network model in Excel.
    Evolver – Explore the power of Genetic Algorithms to solve complex optimization problems.

    The DecisionTools Suite enables endless applications, including; Cash Flow & Financial Analysis, Multi-stage Decision Modeling, Portfolio Optimization & Resource Allocation, Enterprise Risk Management and many others. During the webinar we will review some models and modeling techniques as well as many interesting product features for decision makers and modelers.
  • Advanced Valuation: Start-ups Valuations Feb 25 2021 4:00 pm UTC 75 mins
    Dr. Fernando Scarpati, Managing Partner, BVint
    Why You Should Attend What You Will Learn

    • The problems of traditional valuations and the DCF deterministic models
    • The problem of the CAPM (systematic and non-systematic risk)
    • Why advanced valuations?
    • Systematic and non-systematic risk using stochastic analysis
    • How to measure the risk-return trade-off using stochastic and Monte Carlo analysis
    • Traditional valuation vs Advanced Valuation for a start-up
  • Exploring Electric Utility Energy Cost Behavior using Advanced Features Feb 18 2021 4:00 pm UTC 75 mins
    Glen Justis, Experience On Demand
    The energy cost behavior of most electric utilities is complex and has significant non-linear features. With the advanced features of @RISK, you can improve energy risk measurement, communication, and mitigation. In this concise 30-minute webinar we will cover:
    • The drivers of electric utility energy cost behavior
    • Flexible energy portfolio modeling using @Risk
    • Advanced @RISK results analysis features
    • Practical applications
    • Q&A
  • Project Contingency Reserve Fair Share Determination Feb 11 2021 4:00 pm UTC 75 mins
    Dr. Steve Van Drew
    You’ve built a comprehensive project cost estimate that accounts for significant risks and uncertainties. The project baseline uses most likely values provided by those responsible for each control account/WBS element. A contingency reserve has been determined from cost risk/uncertainty analysis simulation results in conjunction with either the PM’s tolerance for risk or corporate policy. These funds have been earmarked for use by the PM as needed. NICE WORK!

    But … in the back of your mind is a nagging concern that some of those involved may be trying to game the process. If only there was a way to judge when an area of risk or uncertainty was diving too deep into the pool of contingency funds. This webinar will demonstrate a technique for determining proportionate “fair share” amounts, a procedure called WBS allocation in some cost estimating circles, that can be used to help manage these funds. The technique incorporates @RISK simulation results including tornado graphs and statistic functions.
  • Trucos Productivos con el Nuevo @RISK 8.1 Jan 29 2021 4:00 pm UTC 75 mins
    Gustavo Vinueza, Custom Development Manager, Palisade
    a. Este es un webinar para personas de todos los niveles y explorará trucos que harán más productiva su experiencia con el @RISK 8.1. Desde el uso simple de un RiskSimTable y un análisis de stress, cambiar colores a los nuevos tornados de sensibilidad, hasta ejecutar modelos con y sin matrices de correlación, comparar grupos de productos, y cosas avanzadas como generar probabilidades conjuntas. Esta es una presentación a la que todo usuario de @RISK debería asistir, para potenciar su experiencia en el uso del software.
  • Influencing Decisions With Effective Reporting Recorded: Jan 28 2021 68 mins
    Rishi Prabhakar, Senior Consultant, Palisade
    Analyses are only useful if you can convey the most relevant information effectively and efficiently to convince decision-makers. In this webinar, we will explore the reporting options in @RISK, focusing on the practical relevance of the results, or how they relate to specific business problems and decisions. The mechanics of how @RISK creates its reports will get us started, followed by a deeper dive into specific results such as the probability density of an output (and why you will use the relative frequency instead!), tornado charts, and other sensitivities, as well as decision comparisons.
  • Utilizing @RISK to Optimize Safety Stock Planning Recorded: Jan 22 2021 48 mins
    Francisco Erize, Supply Chain Strategy Senior Manager at Dell
    The long supply chains of modern technologic companies combined with the need to fast delivery to customers have made it pretty difficult to optimize finished goods planning. Dell has adopted a hybrid replenishment mode that alternates between ocean and air fulfillment modes to protect service levels while reducing logistics costs. This hybrid replenishment mode does not currently have a closed solution in the operation research field to identify optimal safety stock targets while minimizing total fulfillment costs. While we are working with a research team to achieve that closed solution we have created empirical solution curves based on Monte Carlo simulation models built using @RISK.
  • The Enigma Machine: Creative Problem Solving with the DecisionTools Suite Recorded: Jan 20 2021 75 mins
    Brendan McGrath, CFA, CPA Senior Vice President, Chief Risk Officer
    How do you solve a problem with 150 million million million potential combinations on only one right solution? @RISK and the DecisionTools Suite are powerful tools to find the best solution to a problem, but what happens when a problem seems impossible to solve through straightforward means? Can you simplify the problem before trying to solve it? How do you reduce uncertainty in order to make better informed decisions? This presentation is intended to be a fun overview of the history and inner workings of the Enigma machine and the techniques used to make what was (at the time) an unsolvable problem solvable. These techniques then can then be combined with @RISK and the DecisionTools Suite to tackle complex problems in the real world.
  • Exploring Little-Known @RISK Functions - Part 2 Recorded: Jan 7 2021 68 mins
    Manuel Carmona, Director Edy Training
    As a continuation of the previous seminar, we will explore @RISK features that are not usually covered in other modeling seminars. The following features will be explored:
    • @RISK Swap - Learn how to remove and restore @RISK functions for sharing models with non-@RISK users
    • @RISK GoalSeek function - Learn how to find an input value that achieves a target simulation result you that specify.
    • Stress Analysis - An alternate way to explore scenarios to control the range that is sampled from a distribution function, enabling you to see how different scenarios affect your bottom line without changing your model.
  • Growing your Internal Analytics Capabilities Recorded: Dec 17 2020 72 mins
    Glen Justice, Experience On Demand
    This session will conclude the 2020 Power & Utilities webcast series. We will provide a brief review of the key learnings from prior sessions, then pivot to the managerial aspects of achieving buy-in and building an advanced analytics capability. Topics will include:
    • Brief recap of prior five sessions
    • The business case for stronger analytics
    • Why @Risk and DecisionTools Suite are ideally suited for electric utilities
    • Communicating results of simulation models
    • Best practices for achieving adoption of advanced methods
  • Exploring Little-Known @RISK Functions Recorded: Dec 11 2020 61 mins
    Manuel Carmona, Director Edy Training
    Did you know that @RISK includes a set of hundreds of functions? Some of these functions such as RiskTriang or RiskOutput are popular and well known, but there are the Riskpercentile, RiskTheo, or RiskAlt that are also useful but less known. This session would be an interactive random walk around the @RISK function set with modeling examples that will show how to use the less known @RISK functions in a modeling context. We will also visit the @RISK settings menu to show you the essential features and how to customize your simulations, sampling methods supported, and much more.
  • Modeling Unit Learning Curves from Lot Data with @RISK Recorded: Dec 10 2020 67 mins
    Dr. Steve Van Drew
    Estimating the cost of a project or manufacturing operation where the effect of learning is anticipated can pose a calculational challenge, especially when extrapolating from lot data. After a brief introduction covering the basics of unit learning/experience curves, this webinar will: demonstrate how to make the appropriate transformations for modeling a power curve from lot data; use Excel’s Goal Seek to solve for the unknown learning curve “slope;” and with the resulting regression equation’s error term as the input variable run an @RISK simulation for the cost of a succeeding lot.

    It may be helpful for those who’ve never worked with power models or regression error terms to first watch the “Modeling Regression Errors with @RISK” webinar. It can be found at https://go.palisade.com/Modeling-Regression-Errors-with-RISK.html .
  • Production Curve Uncertainty: Analysis and Simulation of Type Wells with DTS Recorded: Dec 2 2020 72 mins
    Rafael Hartke, CEO of Imagine Risks and Analytics
    This webinar will present a hands-on example of how to analyze historical production data and forecast future production of a portfolio, including the effect of uncertainty and noise in the data and in the model.
    We will use the tools provided by the DecisionTools Suite to:
    (i) Propose a type well model for the historical production data
    (ii) Estimate the model parameters using optimization
    (iii) Analyze the model results and residuals
    (iv) Build a forecast model for a production portfolio based on the type well model
    (v) Simulate the portfolio production curve using Monte Carlo simulation
    (vi) Analyze the simulation results and discuss how to best present them regarding the risks (threats and opportunities) of the portfolio
  • Asset Allocation Modeling with Black Swans Using Monte Carlo Simulation Recorded: Nov 19 2020 59 mins
    Joe DiNunno, Chartered Alternative Investment Analyst
    The traditional approach to asset allocation has been to use efficient frontier models that seek to find the optimal portfolio mix that has the lowest possible level of risk (standard deviation) for its level of return (mean). In these models all asset class returns are assumed to follow the normal distribution. The financial crisis of 2008 convinced us that it was time to look closer at the use of the normal distribution for modeling the probability of investment returns, in particular for equities. While the normal distribution assigns about 1 chance in 1000 for the stock market to experience a 3-standard-deviation decline, such as the market experienced in 2008, the reality is that a move of this magnitude occurs more frequently than that. Looking back at historical data, a move up or down of 3 standard deviations or more, over 6 months to a year, happens more like 2 out of every 100 time periods. The problem then is: How do you add 'Fat Tails' (outlier events that occur more frequently in reality than would be predicted by the normal distribution) to the model distribution in an effort to give the ‘theoretical’ stock market a more realistic chance of experiencing one of these unexpected 'Black Swan' events?
    In this webinar we'll demonstrate how @RISK can be used to create financial models that give investors a more realistic view of the risks in their portfolios by incorporating simulated distributions that more closely resemble reality and provide more realistic 'Fat Tails'. Another revelation of the financial debacle in 2008 was the fact that correlations between most asset classes were, at least temporarily, much higher than expected. On the other hand, some asset classes that historically had a low or negative correlation with equities had positive returns that year, a result that makes sense. In this case we'll talk about how we were able to incorporate a second correlation table in to our model to account for stress in financial markets.
  • Rates, Pricing and Cash Reserves Recorded: Nov 12 2020 68 mins
    Glen Justis, Senior Partner, Experience On Demand
    Palisade is excited to offer this five-part webcast series providing an overview of advanced economic analysis using Microsoft Excel and Palisade DecisionTools Suite. Webcast content and examples will be specifically tailored to electric utilities and other power sector participants.

    Overview
    The webcast series progresses from basic to advanced technical concepts in the 1st four sessions, concluding with a final session covering management approaches for building internal analytic capabilities. Example models will be demonstrated to show how the theory is put into practice.

    Participants will gain a great understanding of the following:
    • What is Monte Carlo analysis and how is it particularly beneficial for electric utilities?
    • What types of economic analyses are worth the added complexity of Monte Carlo analysis?
    • What are best practices for building models that can make full usage of @Risk capabilities?
    • How do you explain the results and promote adoption of advanced techniques?
    • What are best practices for introducing and promoting the adoption of advanced methods such as Monte Carlo analysis?
    • Behavior of fixed and variable utility costs
    • Impact of non-linearity and price/load correlation
    • Incorporating fixed cost uncertainty
    • Estimating reserve requirements
    • Improving rate design using Monte Carlo simulation
  • Production Modeling with @RISK 8 XDK (Excel Developer Kit) Recorded: Nov 5 2020 75 mins
    J. Raúl Castro Actuary, MBA, PhD, Senior Consultant and Trainer
    This webinar will show the way a production modeling process can be simplified to avoid the use of multiple cells by linking an Excel VBA Macro into the simulation. Additionally, all details related to model planning and implementation will also be discussed, including which probability distributions seem to be more adequate for this type of problems across different industries.
    A preliminary file with all assumptions will be given to participants so they can follow up with the instructor at any time during his presentation.
  • Modeling Regression Errors with @RISK Recorded: Nov 4 2020 68 mins
    Dr. Steve Van Drew, Consultant & Trainer
    If your spreadsheet model includes a regression equation and you are not explicitly modeling the associated error, for a linear model you are implicitly assuming that there is no error. On average that’s a safe assumption; it’s individual occurrences however that can make this risky. After a brief review of regression fundamentals (yeah, calculus), this webinar will use applications from multiple industries to show how @RISK can be used to model a regression equation’s error term for both linear and nonlinear (intrinsically linear) models. Along the way you will improve your skill working with the normal distribution and add the lognormal distribution to your repertoire.
  • 使用@ RISK8进行蒙特卡罗模拟 Recorded: Nov 3 2020 76 mins
    张宏亮博士
    尽管未来存在很大不确定性,然而无论是短期还是长期政府和企业都必须努力做出明智的决策。我们应该投资一个新的项目吗?此项目的应急方案是什么?我们可以从项目核心产品中获得多大收入?我们应该关注哪些关键价值驱动因素?哪种产品组合可以最大化项目收入?
    蒙特卡罗模拟(Monte Carlo Simulation)提供了这样一种技术,可以通过在电子表格Excel模型中考虑不确定性来帮助决策者解决上述那些问题以及许多其他问题。 @RISK 8直接在电子表格Excel模型中执行蒙特卡罗模拟,为您最重要的决策问题提供科学和理性的统计分析答案,例如,项目失败的概率是多少?明年利润的期望值是多少?项目总成本的P90值是多少?

    在这个介绍性网络研讨会中,我们将探讨@RISK 8如何与Excel集成,使用历史数据来构建概率分布,或者也可以使用主观估计方法,通过建立概率分布,时间序列和相关性来对不确定性进行建模分析。@RISK 8具有许多报告功能,可以使用标准报告和可自定义报告以及用户定义的模板来描述和交流您的分析结果。

    我们将使用@RISK内置的案例来讲解和展示这些功能,以便您以后可以轻松地进行后续软件实操并可以重新演练模型或重现模拟分析结果。
  • Data Science con el DecisionTools Suite (3 de 3): Modelos de Redes Neuronales Recorded: Oct 30 2020 71 mins
    Celia de la Cruz, Ricardo Patiño - Palisade
    En este último capítulo de la serie, se revisará cómo implementar un modelo con NeuralTools, la herramienta del DecisionTools Suite que sirve para implementar Redes Neuronales. Se construirá un modelo completo, revisando las posibles transformaciones de los datos, así como su implementación en el software. Se explicarán los distintos tipos de redes, su proceso de entrenamiento y predicción, así como los resultados que se obtienen, las matrices de clasificación y otras medidas adicionales que pueden ser tomadas en cuenta. Esta es una sesión para principiantes y la idea es que luego de verla, quien asista se sienta más seguro de los pasos a seguir para construir su modelo de predicción con redes neuronales.
  • 몬테카를로 시뮬레이션 개념 및 @RISK 8.0주요 기능 알아보기 Recorded: Oct 27 2020 73 mins
    이레테크 데이터랩스 민경현 부장
    Palisade사는 지난 50여년간 몬테카를로 시뮬레이션을 지원하는 분석 툴인 @RISK를 전 세계에 보급하고 교육 및 컨설팅 서비스를 제공하고 있습니다. 몬테카를로 시뮬레이션은 많은 산업 및 응용 분야에서 미래의 불확실성에 대한 리스크를 평가하기 위해 활용되는 확률론적 방법입니다. @RISK는 엑셀에 에드인(Add-in) 되어 제공되는 분석 툴로써 기존에 엑셀 기반으로 정량적 분석을 했던 기존의 수리적 모델에 @RISK를 활용하면 쉽고 편리하게 몬테카를로 시뮬레이션을 수행할 수가 있습니다. @RISK로 실행된 분석 결과들은 리스크에 대한 확률론적 정보를 제공함으로써 기존의 결정론적(점추정) 방법에서 제공되는 하나의 값으로 판단해야 하는 정보의 한계를 넘어 리스크 발생 가능성인 확률을 고려하는 의사결정에 대한 통찰력을 제시할 것입니다.
    Palisade는 몬테카를로 시뮬레이션을 활용하고자 하거나 이미 활용하고 있는 사용자들이 보다 쉽고 편리하게 분석을 수행할 수 있도록 지속적인 노력을 해 오고 있으며 이에 2020년 3월에 새로운 버전인 @RISK 8.0버전이 출시하게 되었습니다.
    이에 본 웨비나에서는 몬테카를 시뮬레이션에 대한 이해도를 높이기 위해 기본적인 개념들과 새롭게 출시한 @RISK 8.0버전에서 개선된 주요 기능에 대해서 이야기를 하고자 합니다.
    많은 분들의 관심과 참여 부탁 드립니다.

    아젠다
    순서 내용 발표자
    1 몬테카를로 시뮬레이션 이해 ㈜이레테크 데이터랩스
    민경현 부장
    2 @RISK 8.0 주요 기능 소개
    3 예제를 활용한 데모 시연
    4 Q&A
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Palisade Company is the world’s leading provider of risk and decision analysis software solutions for science and industry.

Our array of software products and custom services enhance the management experience by combining the latest in cutting-edge technology with over 35 years of analytics experience. Palisade’s
unified software platform helps clients increase margins, improve performance, expand market share, and maximize operational efficiencies.

We have a very simple mission: to minimize risk while
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  • Title: Growing your Internal Analytics Capabilities
  • Live at: Dec 17 2020 4:00 pm
  • Presented by: Glen Justice, Experience On Demand
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