1 / 17

Valuing R&D: Investment and Risk Modeling Methods and Tools at Boeing

Valuing R&D: Investment and Risk Modeling Methods and Tools at Boeing. Scott Mathews, Technical Lead Mathematical Modeling Analyst Computational Finance and Statistical Modeling Analytic Modeling & Simulation, PW 253-773-2695. Investment Questions Answered by Boeing Methods .

brenna
Download Presentation

Valuing R&D: Investment and Risk Modeling Methods and Tools at Boeing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Valuing R&D:Investment and Risk ModelingMethods and Tools at Boeing Scott Mathews, Technical Lead Mathematical Modeling Analyst Computational Finance and Statistical Modeling Analytic Modeling & Simulation, PW 253-773-2695

  2. Investment QuestionsAnswered by Boeing Methods • What should I be investing in today, how much and why? • Are these investments either increasing my return opportunities or decreasing risk? How? • What are the risks and how am I hedged for their eventuality? • How does this investment optimize my long term strategy-portfolio holdings/risk/return?

  3. Issues with Traditional Financial Models used for in Technical R&D Programs • Risk is never modeled as a quantitative value • Financial models don’t capture technical decisions or flexibility to change direction • High discount rate for long-term uncertain payoff or high risk programs result in negative NPV • Sparse market data and projections • Inability to collaborate technical and financial models, especially large programs

  4. Some Boeing Investment and Risk Methods • Quantitative Technical Risk Modeling • Investment vs. Risk Modeling • Real Options • Demand (Price & Quantity) Modeling • Structured (Object-Oriented) Spreadsheet Modeling • Portfolio Analysis

  5. 70% probability $100 $115 The most likely value does not represent the average value. Average Value = 70% x $100 + 30% x $150 = $115 30% probability $150 • Statistical models capture the range of possible outcomes $115 150 100 Why Model Uncertainty • Estimates compress reality into a single value: theMost LikelyValue

  6. Profit/Loss Profile Diagrams for Unfolding Future A Decision Treewithuncertainty generates a statistical probability

  7. Quantitative Technical Risk ModelingBuilding Uncertainty into Models ExcelspreadsheetwithCrystal Balladd-in

  8. Risk Eliminatedby Investment Risk Management through Targeted Investments • Today’s projection of future asset (Red distribution) • Without investment today, production will commence with great cost uncertainties. Project discount rate is high. • Investment today in Technology Development increases the predictability of program costs. This reduces program cost risks. (Blue distribution). Project discount rate lowers.

  9. Investment vs. Risk Modeling • Quantitatively rank investment decisions to risk reduction • Estimate reduction from current risk levels to target production-ready risk levels Mathews Ratio* Calculates Investment Effectiveness: Change in Risk Investment *“Mathews Ratio, Copyright (c) 2001, The Boeing Company, All Rights Reserved."

  10. The Value of Project Management Flexibility Concept of Real Options Profit/Loss Profile Greater Profits Most likely Value (NPV Value)    Worse Losses Time

  11. Simplified Real Options The Datar-Mathews Method* • Intuitive and transparent • Easily integrated into spreadsheets with simulation methods • Facilitates strategic planning • Extensible to many option types • A Boeing strategic advantage *“Datar-Mathews Method for Quantitative Real Option Valuation, Copyright (c) 2001, The Boeing Company, All Rights Reserved."

  12. Quickly Deriving Market DemandThe Boeing Demand Curve* Method • Key to quantifying primary project risk: Price and Quantity • Uses sparse data inputs • Easily integrated into spreadsheets with simulation methods • Two methods have been developed • Non-differentiated markets (such as commodities, prices are public) • Differentiated markets (such as durable goods sold by contract) • Calculates optimum price and quantity to maximize profits • An adjunct to project real option valuation *“The Boeing Demand Curve, Copyright (c) 2001, The Boeing Company, All Rights Reserved."

  13. Demand ModelingThe Boeing Demand Curve* Method $8B $140M Demand (Market Price) $120M $6B Cost Gross Profits $100M $4B $2B $80M Price Profits $0B $60M -$2B $40M Units Sold 0 200 400 600 800 1000

  14. Some Demand Model ResultsMaximizing Project Profits • Clear visualization of interplay of variables • Optimum Price is a narrowly defined price range • Easily integrated into real options simulation model

  15. Structured (Object-Oriented) Spreadsheet Modeling for Large-Scale Business Cases CPML UML Structured (OO) Model • Provides ability to exchange or add components efficiently • Allows objects created by different parts of a corporation to be tied together • Makes it easy to incorporate new ideas and methods given specific inputs and outputs • Key Capabilities: • Facilitates Knowledge Management • Monitors Data Flow • Extensibility

  16. $     Risk,  Portfolio Analysis • Combining independent models into portfolio • Use Sharpe Ratio, ($/) to determine investment exposure and returns Platform Risk, NPV, Cash Flow, Economic Profit, Option Value, Risk Adj. Profit, Sensitivity Asset 2 Asset 1 Low-Level Dependencies Asset 4 Asset 3

  17. End of Presentation

More Related