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Applied Information Economics: Kickoff for Risk Return Analysis

Applied Information Economics: Kickoff for Risk Return Analysis. Decision/Game Theory. Operations Research. Empirical Decision Theory. Statistics. Information Engineering. Information Theory. Software Metrics. What is AIE?.

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Applied Information Economics: Kickoff for Risk Return Analysis

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  1. Applied Information Economics: Kickoff for Risk Return Analysis

  2. Decision/Game Theory Operations Research Empirical Decision Theory Statistics Information Engineering Information Theory Software Metrics What is AIE? Applied Information Economics is the practical application of scientific and mathematical methods to quantify the value of IT-enabled business investments Economics Applied Information Economics Modern Portfolio Theory

  3. Real Solutions to… • …the economics of information • …the economics of IT infrastructure • …the economics of risk • …the economics of labor reduction when headcount is not reduced • Bottom Line: AIE assesses and prioritizes IT investments based on quantitative and economically rational methods

  4. What Do the Critics Say? • “Quantifying the risk and comparing its risk/return with other investments sets AIE apart from other methodologies. It can substantially assist in financially justifying a project -- especially projects that promise significant intangible benefits.” The Gartner Group • “AIE represents a rigorous, quantitative approach to improving IT investment decision making…..this investment will return multiples by enabling much better decision making. Giga recommends that IT executives learn more about AIE and begin to adopt its tools and methodologies, especially for large IT projects.” Giga Information Group • “AIE-like methods must become the standard way to make (IT) investment decisions.” Forrester Research, Inc.

  5. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions Basic Risk/Return Analysis Organization Procedure Tools AIE Deliverables AIE

  6. 1. Classify & Plan 2. Clarify Intangibles & CBA 3. Conduct Measurements 4. Conduct VIA 5. Conduct Risk & Return Analysis 6. Make Recommendations Describe, Classify & Plan • Purpose: Agree on the specific investment to be analyzed, Agree on the specific question to be answered, Plan the rest of the analysis

  7. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions Clarify The Decision Model • During Clarification we translate the “Intangibles” into measurable units • These are ultimately modeled in a spreadsheet

  8. Understanding Measurement(The Measurement.com approach) • Gilb’s Law “Anything can be measured in a way which is superior to not measuring it at all” • The perceived impossibility of measurement is an illusion caused by not understanding: • the Concept of measurement • the Object of measurement • the Methods of measurement • See my “Everything is Measurable” article in CIO Magazine (got to “articles” link on www.hubbardresearch.com

  9. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions Conduct Measurements • We use the variety of measurement methods previously discussed • We usually start with what we know now (i.e. calibrated estimates) • More elaborate measurements (large controlled experiments or surveys) are only taken if we can show they are economically justified

  10. Calibrated Estimates • Measuring your own uncertainty about a quantity is a general skill that can be taught with a measurable improvement • Studies show that most managers are statistically “overconfident” when assessing their own uncertainty • Training can “calibrate” people so that when they provide a 90% confidence interval, it still has a 90% chance of being right (even though it is subjective) When asked to provide a subjective 90% confidence interval, most managers provide a range that only has about a 40%-50% chance of being right Perceived 90% Confidence Interval Actual 90% Confidence Interval

  11. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions Calculate the Value of Information • The value of additional information can be calculated for each uncertain variable in the analysis • Measurement efforts will be more productive by focusing on variables that matter the most (results are often surprising) • This method is based on the probability of a change in a decision with additional information and the difference in the value of the decision $$$ $

  12. The Economic Value of Information The Decision Theory Formula: • What it means: • Information reduces uncertainty • Reduced uncertainty improves decisions • Improved decisions satisfy business objectives (by definition)

  13. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions ROI 0% 50% 100% Conduct Risk/Return Analysis Administrative Cost Reduction 5% 10% 15% % Improvement in Customer Retention 10% 20% 30% Total Project Cost $2 million $4 million $6 million

  14. 1. Describe & Classify 2. Clarify Decision Model 3. Make Measure- ments 4. Conduct VIA 5. Conduct Risk/Return Analysis 6. Make Recommenda- tions Make Recommendations • The recommendations include: • To accept or reject the investment • Possible modifications to the proposed investment • Various risk management tactics • Deliverables include • The written report • The spreadsheet • The presentation

  15. Measurements 5% 10% 15% 10% 20% 30% $6 mill $2 mill $4 mill Calculate Risk/Return Position "expected" ROI Probability of a negative ROI Probability of a positive ROI -50% 0% 50% 100% 150% 200% 250% Overview of RRA Analysis Classification Value of Info. $ Intangibles “Customer Satisfaction” “Strategic Alignment” “Technology Risk” “Information Quality” etc. $$$ $$ Measurables Errors in Decision X Change to Strategic Measure M Productivity in Activity Y Chance of cancellation, etc. Risk Organization's investment limit Acceptable region of investment Return

  16. Workshops • Much of the initial data gathering is from a series of workshops • We need to schedule 5-6 workshops for the following activities: • Define & Classify the investment • Clarify Decision Model • Measurement (initial) • Calibration • Estimation

  17. Defining the Investment • What is the objective of this investment? (A one-sentence description of why) • What costs are unique to this investment? • What benefits are unique to this investment? • What are the risks of the investment? • What “decision dimensions” are important besides just an accept/reject recommendation? • Is all of the investment optional? • The decision is analyzed on behalf of which investor?

  18. The Concept Of Measurement • Sometimes one believes that a thing is “immeasurable” only because they do not actually understand the concept of measurement • The “Measurement Theory” definition of measurement: “A measurement is an observation that results in information (reduction of uncertainty) about a quantity.” • Any “reduction of uncertainty” about a quantity can be of value ?

  19. Real-world Measurements vs. Ideal Values Ideal Values: Point Real-world Meas. Normal Distribution Uniform Distribution Lognormal Distribution Hybrid 15% 85% Threshold confidence

  20. The Object of Measurement • If a thing seems like and immeasurable “intangible” it may just be ill-defined • Often, if we can define what we mean by a certain “intangible” we find ways to measure it ?

  21. The Clarification Chain AIE assumes that if a benefit or cost is defined unambiguously, then it is measurable. • If it is “Better” it is different in some relevant way... • If it is relevantly different then it is observable... • If it is observable then it is observable in some amount... • If we can observe it in some amount then it is measurable.

  22. The “Thought Experiment” • Imagine that you are a scientist capable of making clones of entire companies and that you have a cloned pair of your company • Change one of the companies so that one has the stated “intangible” and the other does not • Ask what would you actually observe that would be different between the two companies

  23. Examples of Clarification • Tools like “The Clarification Chain” are used to identify unit-of-measure variables hidden beneath the “intangible” label • I offer a challenge that given any intangible, I can clarify it and identify a method of measurement within 15 minutes (I’ve never lost) The “Intangible” Possible Meanings After Clarification • Less management overhead • Certain decisions are more accurate and faster “Employee Empowerment” “Information Availability” • Time and cost of searching is reduced • Certain costly errors are less frequent “Customer Relationship” • Increased repeatbusiness

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