A true next-generation comprehensive ERM process should include, at a minimum, the qualitative methods and steps previously outlined plus quantitative IRM methodologies. Instead of continuing the chapter by outlining additional items and bullet lists of methods and steps, we illustrate the quantitative ERM methods through the use of the PEAT (Project Economics Analysis Tool) software’s ERM Module, which is showcased in the next chapter.

The Project Economics Analysis Tool (PEAT) software was developed to perform a comprehensive Integrated Risk Management analysis on capital investments, discounted cash flow, cost and schedule risk project management, oil and gas applications, healthcare analytics, and Enterprise Risk Management. This tool will help you to set up a series of projects or capital investment options, model their cash flows, simulate their risks, run advanced risk simulations, perform business intelligence analytics, run forecasting and prediction modeling, optimize your investment portfolio subject to budgetary and other resource and qualitative constraints, and generate automated reports and charts, all within a single easy-to-use integrated software suite. The following modules are available in PEAT, and Chapter 2 focuses on the ERM module in particular.

  • Enterprise Risk Management (ERM)
  • Corporate Investments (Dynamic Discounted Cash Flow)
  • Corporate Investments (Lease versus Buy)
  • Goals Analytics (Sales Force Automation)
  • Healthcare Economics (HEAT and REJ)
  • Oil and Gas (Oil Field Reserves, Oil Recovery Analysis, Well-Type Curves)
  • Project Management (Cost and Schedule Risk)
  • Public Sector Analysis (Knowledge Value Added)
  • ROV Compiled Models
  • Customized company-specific modules and applications

ROV’s PEAT incorporates all of the advanced risk and decision analytical methodologies covered in this book into a simple-to-use and step-by-step integrated software application suite. It simplifies the risk-based decision analysis process and empowers the decision maker with insights from powerful analytics. If you already perform discounted cash flow modeling or Enterprise Risk Management in Excel, why do you still need PEAT? Because PEAT’s integrated advanced analytical techniques extend the analysis you have already performed and do so in a simple-to-use, simple-to-understand, and automated format, thus generating valuable insights that would be impossible without such advanced methods. PEAT allows you to scale and replicate your analysis, archive and encrypt your models and data, create automated reports, and customize your own PEAT modules.

  • Enterprise Risk Management (ERM): Perform traditional qualitative ERM with Risk Registers but also enhance the analysis with more quantitative analysis. This ERM module comes with an online Web version as well as a module within PEAT, where you can enter and save multiple Risk Registers to generate Key Risk Indicators (KRI) by Risk Divisions and Risk Taxonomy (Geographic, Operations, Products, Activity or Process, and Department); assign risk items to different Risk Managers by performing Risk Mapping of Risk Categories to different Risk Divisions; create Risk Dashboards of the results; enter Risk Elements within multiple customizable Risk Engagements; draw Risk Diagrams; perform and run Risk Controls on KRIs to see if certain risks are within control or out of control; perform Risk Forecasts; check if certain Risk Mitigation projects do, indeed, work or are statistically ineffective; perform Risk Sensitivity on KRIs; perform Risk Scenarios on quantitative risk metrics; run Risk Simulations on risk metrics; generate Risk Reports; and encrypt your data and files for the purposes of Risk Security. (See Chapter 4’s case study on Eletrobrás in Brazil on how the PEAT ERM was employed at this multinational company.)
  • Corporate Investments (Dynamic Discounted Cash Flow): With a few simple assumptions, you can auto-generate cashflow statements of multiple projects; obtain key performance indicators and financial metrics (NPV, IRR, MIRR, PP, DPP, ROI); run risk simulations on uncertainty inputs; generate static tornado sensitivity analysis; run dynamic sensitivities; simultaneously compare multiple projects within a portfolio; perform forecasts of future revenues and cash flow; draw multiple strategic investment pathways and options, and model and value these strategic paths; compute and optimize the best projects within a portfolio subject to multiple constraints and restrictions; view results in management dashboards; encrypt your model and data; and auto-generate analysis reports.
  • Corporate Investments (Lease versus Buy): Run a lease versus buy analysis; compare capital and operating leases with interest payments and tax advantages; value the lease contract from the point of view of the lessee and lessor; and generate the complete cashflow analysis to obtain the net advantage to leasing.
  • Goals Analytics (Sales Force Automation): Develop and maintain corporate sales goals. A Web-based SaaS and desktop-based PEAT module, it focuses on the creation and use of goals that help make goal-setting more accurate and sustainable by any company seeking to improve its sales performance (sales goal forecasting, probability of hitting corporate revenues, sales pipeline analysis, and other sales-based metrics analysis).
  • Healthcare Economics (HEAT and REJ): Run the economics of various options available under the U.S. Affordable Care Act (Obamacare) for corporations providing employer-sponsored healthcare by loading employee-census data (healthcare economics analysis tool, HEAT), or perform rapid economic justification (REJ) of each option by simulating its high-level inputs.
  • Oil and Gas (Oil Field Reserves, Oil Recovery, and Well-Type Curves): Perform oil and gas industry models on analyzing the economics of oil field reserves and available oil recovery based on uncertainty and risks, as well as generate oil-well–specific type curves and economics.
  • Project Management (Cost and Schedule Risk): Draw your own project pathways (simple linear project tasks versus complex parallel and recombining projects), then click a button to auto-generate the model. Enter the cost and schedule estimates as well as their spreads, then run a risk simulation on the model to determine the probability of cost-schedule overruns, cost-schedule buffers at various probabilities of completion, critical path identification, and sensitivity analysis.
  • Public Sector Analysis (Knowledge Value Added): Model government and nonprofit organizations’ value, value to society, or intangible value via Knowledge Value Added utilizing market comparables to identify and monetize such projects and assets.
  • ROV Compiled Models: With the compiler software, users can compile their existing Excel models into license-controlled executable EXE files. ROV’s patented methods can be used to encrypt and lock up the intellectual property and mathematical algorithms of the model, and issue hardware-controlled and timed licenses to the purchaser’s own users or customers.


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