Custom Development

Applications tailored to your needs, right in your spreadsheet, using a range of powerful analytics including Monte Carlo simulation, decision trees, statistics, neural networks, and optimization. Read more at http://www.palisade.com/development/

@RISK Used to Prepare Hospitals for Hurricane Strike

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.

Risk and Decision “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.”

» Read the full case study
» Learn more about @RISK
» Palisade Custom Development

Amway Improves Capacity Planning with @RISK and Palisade Custom Services

amwayLogo.pngWith $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.”

» Read the full case study
» Learn more about @RISK

NeuralTools Assists Airline to Determine the Most Profitable Price Points

How much is too much when it comes to plane ticket prices?  This is a key question for commercial airlines, and one CommercialAirlinethat Palisade helped answer.

Fernando Hernandez, a Senior Risk Consultant and Trainer at Palisade, was tasked with developing a model for predicting demand and price elasticity for a domestic airline catering to the tourism industry in Costa Rica. This predicting model uses neural networks technology powered by Palisade’s NeuralTools application, a sophisticated data mining application that makes new predictions based on the patterns of known data. By imitating brain functions to “learn” the structure of data, NeuralTools can take new inputs and make intelligent predictions.

The objective of this trained network was to adequately predict how many passengers would purchase tickets on a particular flight and the optimum price point, based on a wide range of condition combinations. Once the data set was created, the neural network was set to be trained and tested. Upon training and testing, a sensitivity analysis on 21 variables was performed to predict the passenger demand for a particular flight. A sensitivity analysis showed which factors held the greatest weight in determining the number of passengers per flight. The most impactful factors included mean fare, distance and competitor strength.

A data entry table was created utilizing fare increments of $5.17, starting at $50, and all the way up to $200. The model predicted that occupancy would remain more or less steady—between 17 to 23 passengers— regardless of the fare, until the $175 threshold was reached. Once this mean fare was surpassed, passenger demand abruptly decreased driving down total expected revenue for the route. At a mean fare of above $185—a mere increase of $10 per ticket—occupancy dipped to less than five passengers.

While demand and price elasticity is not an exact science, NeuralTools helped the airline utilize data it already had to determine the most profitable price point and adjust it based on the numerous factors that impact air travel.

To see the full case study, click here.

Custom Solutions within the Insurance Sector: Catastrophe and Large Loss Simulation Model

Insurance companies are now encouraged by regulation to perform assessment of their own risk exposure. Monte Carlo simulation, and particularly @RISK are extremely useful in performing assessments that can be used not only to satisfy regulators, but also to improve financial risk management within the company.

Waszink Actuarial Advisory in collaboration with Palisade's Custom Development Team created this Catastrophe and Large Loss Simulation Model to provide an output that includes the aggregate loss gross and net of reinsurance, and the reinsured loss.

In this example, an application was created using @RISK to generate the aggregate loss resulting from multiple large or catastrophic losses occurring within a given period of time. Aggregate losses are determined gross and net of any Excess of Loss Reinsurance.

Parametric distributions for frequency and severity of loss gross of reinsurance must be specified by the user. Frequency and severity are assumed to be mutually independent.

In addition, the user can specify an Excess of Loss Reinsurance program. The following features of the reinsurance program must be specified:

  • Number of layers
  • Limit and retention by layer
  • Reinsurance premium by layer
  • Number of reinstatements by layer;
  • Reinstatement premium as percentage of reinsurance premium

The output includes the aggregate loss gross and net of reinsurance, and the reinsured loss.

More example of Custom Development:

Custom Solutions: Using @RISK for Oil Field Development Decisions

Oil companies need to assess new fields or prospects where very little hard data exists. Based on seismic data, analysts can estimate the probability distribution of the reserve size. With little actual data available, companies still must quantify and optimize the Net Present Value (NPV) of this asset. The number of wells to drill, the size of the processing facility, and the plateau rate of the field must all be optimized. The following example is a custom application written by Palisade Custom Development using @RISK’s XDK in Excel.

Oil Field Development Screenshots

This analysis can be simplified by representing the production profile by three phases:

  1. Build up: The period when wells are drilled to gain enough production to fill the facilities.
  2. Plateau: After reaching the desired production rate (plateau), the period when production is continued at that rate as long as the reservoir pressure is constant and until a certain fraction of the reserves is produced. In the early stages of development, this fraction can only be estimated, and production above a certain rate influences plateau duration.
  3. Decline: The period when production rates, P, decline by the same proportion in each time step, leading to an exponential function: P(t) = P(0) exp(-c*t), where t is the time since the plateau phase began and c is some constant.

With only estimates for the total Stock Tank Oil Initially In Place (STOIIP = reserve size) and percent recovery amounts, the objective is to select a production rate, a facility size, and well numbers to maximize some financial measure. In this example, the measure used is the P10 of the NPV distribution. In other words, the oil company wants to optimize an NPV value which they are 90% confident of achieving or exceeding.

As described, the problem is neither trivial nor overly complex. A high plateau rate doesn’t lose any reserves, but it does increase costs with extra wells and larger facilities. However, facility costs per unit decrease with a larger throughput, so choosing the largest allowed rate and selecting a facility and number of wells to match might be appropriate.

This is just one example of how Palisade can provide personalized risk solutions for your business needs. We offer custom software development services as well as software developer kits to create your own applications integrating @RISK, RISKOptimizer, and other Palisade technology. We can also help automate Palisade software using VBA in Microsoft Excel or Project.

» Learn more about Palisade's Custom Development

You may also be interested in the following:

Free Webcast this Thursday: "Exploring Oil & Gas Applications of @RISK and the DecisionTools Suite" – See more at: https://blog.palisade.com/blog/risk-and-decision-analysis-news/free-webcast-this-thursday-exploring-oil-and-gas-applications-of-risk-and-the-decisiontools-suite#sthash.sev3ym2s.dpuf

Cost Risk Analysis Example Movie: Palisade's Custom Development Team uses @RISK's XDK for this custom application
 

 

Cost Risk Analysis Example Movie: Palisade’s Custom Development Team uses @RISK’s XDK for this custom application

Here is an example of a custom application written by Palisade Custom Development using @RISK's XDK in Excel. In this example, @RISK is used for cost risk analysis and estimation.  The application prompts the user for a three-point estimate for each cost item in the project as a way to recognize uncertainty in these cost elements.  A risk register is created using a simply colored grid interface.  Next, because in real life costs are seldom independent of each other, the user is able to set up correlations between related cost elements.  Finally, the user can define external risk events that will affect the total cost of the project. Automation takes the shape of an Excel add-in, which is shown to the user as a new Excel ribbon.

 

 

Custom Development in Excel

Palisade Custom Development has written applications for insurance, cost estimation, retirement planning, oil and gas prospecting, portfolio risk management, schedule-cost risk analysis and more – all utilizing @RISK technology in Excel. This means we can create risk analysis solutions for you using a range of powerful analytics, including Monte Carlo simulation, decision trees, statistics, neural networks, and optimization. In each case, the interface is customized to include only what the users need, hiding unused @RISK functionality and preventing user access to the underlying model logic. You can also automate processes like reporting, generating only the charts and data you want. The result is a tailored application ready to roll out to your workgroup. 
 

New XDK Functionality and Documentation in version 6.2

Excel Developer’s Kits (XDK) automatically come as part of the DecisionTools software which includes, @RISK, PrecisionTree, Evolver, StatTools, and NeuralTools. XDKs allow you to automate and customize the tool within Excel using Excel’s built-in VBA programming language. In @RISK 6.2, the XDK has been updated to include new functionality for the automation of @RISK graphs and simulation filters, as well as several additional improvements. For most  products, the XDK now includes a new “Automation Guide” to help you get started quickly. In addition, new videos and example files have been added to the XDKs to help you use this powerful feature.

» See XDK videos

 

See how a customized Retirement Saving template assesses the performance of a portfolio in future years

Here is an example of a custom application written by Palisade Custom Development using @RISK's XDK in Excel. In this example, @RISK is used to analyze the investment of funds for retirement planning.  The application prompts the user for profile characteristics of the client and portfolio parameters. 

Once the information is entered, the application runs an @RISK simulation to assess the performance of the portfolio in future years as well as the effects of various withdrawal rates after retirement.  Results are presented in tables and graphs.

This video demonstrates how easy it is to utilize this Custom Application:
  1. Define Profile Parameters
    The user inputs the profile characteristics of the individual whose profile is to be modeled. 
     
  2. Define Model Parameters
    The next step is to add the probability distributions for the return of each of the investments. 
     
  3. Simulate and View Results
    Observe multiple simulations and view the custom reports that are provided.
     
Automation takes the shape of an Excel add-in, which is shown to the user as a new Excel ribbon. 
 

Custom Development in Excel

Palisade Custom Development has written applications for cost estimation, retirement planning, oil and gas prospecting, portfolio risk management, and more – all utilizing @RISK technology in Excel. In each case, the interface is customized to include only what the users need, hiding unused @RISK functionality and preventing user access to the underlying model logic. You can also automate processes like reporting, generating only the charts and data you want. The result is a tailored application ready to roll out to your workgroup. Because the application is in Excel, the training required for users is minimal. XDKs come with the DecisionTools software PrecisionTree, StatTools, NeuralTools, RISKOptimizer, and Evolver as well as @RISK. This means we can create risk analysis solutions for you using a range of powerful analytics, including Monte Carlo simulation, decision trees, statistics, neural networks, and optimization. 

How to Create a Custom Application for Stock Portfolio Optimization, Right in Your Spreadsheet

This is an example of the use of @RISK automation applied to stock portfolio optimization. It is a custom application written by Palisade Custom Development using @RISK’s XDK in Excel. 

The steps outlined in the Stock Portfolio Optimization example movie:
  1. Obtain Price & Weight Data
    The user will first define a portolfio of stocks. 
     
  2. Run Analysis & Review
    The next step is to run the analysis for the returns of each security. 
     
  3. Fit Data & Simulate
    The third step is to obtain the distributions that fit the historical return of the portoflio. Distributions of 10 will be used as a base for prediting gains or losses using a simulation. 
     
  4. Optimize & Generate Efficient Frontier
    The last step is to run the optimization process and maximize the portfolio's mean return, given certain constraints. Another feature available is to get the Efficient Frontier of the portfolio.
Automation takes the shape of an Excel add-in, which is shown to the user as a new Excel ribbon. 
 

Custom Development in Excel

Palisade Custom Development has written applications for cost estimation, retirement planning, oil and gas prospecting, portfolio risk management, and more – all utilizing @RISK technology in Excel. In each case, the interface is customized to include only what the users need, hiding unused @RISK functionality and preventing user access to the underlying model logic. You can also automate processes like reporting, generating only the charts and data you want. The result is a tailored application ready to roll out to your workgroup. Because the application is in Excel, the training required for users is minimal. XDKs come with the DecisionTools software PrecisionTree, StatTools, NeuralTools, RISKOptimizer, and Evolver as well as @RISK. This means we can create risk analysis solutions for you using a range of powerful analytics, including Monte Carlo simulation, decision trees, statistics, neural networks, and optimization.