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2012 Australian Cost Conference Keynote Cost Estimation: A Key Component of Affordable Program Success Dan Galorath [email protected] Copyright 2012 Galorath Incorporated Key Points Cost is a key project performance parameter Cost Estimation with repeatable process is best practice Viable affordability decisions yield project achievements 2 © 2012 Copyright Galorath Incorporated 2 Using Best Practices Are A Best Practice Themselves • “Method or technique that has consistently shown results superior to those achieved with other means, and that is used as a benchmark” • “Best" practice can evolve to become better as improvements are discovered Processes Tools People © 2012 Copyright Galorath Incorporated 3 Delusions of Success: How Optimism Undermines Executives' Decisions Richard Hartley, HBR) (Source: • Problem: Humans seem hardwired to be optimists • Optimism from cognitive biases & organizational pressures • Exaggerate talents & degree of control • Attribute negative consequences to external factors • Anchoring (relying too heavily on one piece of information) magnifies optimism Best practice: Temper with “outside view” • Most pronounced for new initiatives Supplement traditional forecasting w/ statistical parametrics Don’t remove optimism, but balance optimism & realism © 2012 Copyright Galorath Incorporated 4 While Optimism Needs Tempering, So Does Short Sightedness (Source Northrop) © 2012 Copyright Galorath Incorporated 5 Key Points Cost is a key project performance parameter © 2012 Copyright Galorath Incorporated 6 Cost Overruns Are Everywhere • “GAO: Staggering cost overruns dwarf modest improvements in Defense acquisition” • R&D costs of weapons programs increased 42% over original estimates • Average delay 22 months in delivering initial capabilities • Evolving technical requirements • Shortage of qualified government staff to manage • "Every dollar of cost growth on a DoD weapon system represents a lost opportunity to pay for another national priority" • “The Collins Class submarine program: Murphy was an optimist” http://epress.anu.edu.au/apps/bookworm/view/Agenda,+Volume+19,+Number+1,+2012/9601/Ergas.htm • “BG Group shares hit by $5.4B cost overruns on Australian Liquified Natural Gas project” © 2012 Copyright Galorath Incorporated 7 Software Is A Key Risk Item In Weapons Systems • Navy Mobile User Objective Satellite Communication System delays to the Joint Tactical Radio System, a set of software-defined radios causes advanced MUOS capabilities to be drastically underused… GAO • GAO identified 42 programs at risk for cost & schedule 1. military requirements changes 2. software development challenges 3. workforce issues • National Institute of Standards and Technology (NIST) • Software defects cost nearly $60 Billion Annually • 80% of development costs involve identifying and correcting defects Software, not Hardware or technology readiness levels were called out © 2012 Copyright Galorath Incorporated 8 Example: Project Cost Alone Is not The Cost of IT Failure (Source: HBR) • Case Study: Levi Strauss • $5M ERP deployment contracted • Risks seemed small • Difficulty interfacing with customer’s systems • Had to shut down production • Unable to fill orders for 3 weeks • $192.5M charge against earnings on a $5M IT project failure “IT projects touch so many aspects of organization they pose a new singular risk” http://hbr.org/2011/09/why-your-it-project-may-be-riskier-than-you-think/ar/1 © 2012 Copyright Galorath Incorporated 9 An ROI Analysis of A New System: Should We Fund This? • • • Can we do better? Will stakeholders tolerate a loss for 3 years? What is the risk? © 2012 Copyright Galorath Incorporated 10 Software & IT Systems Are About Business Value Total Ownership Cost Value • “Software economics should provide methods for analyzing the choices software projects must make.” Leon Levy • Business economics should provide methods for analyzing choices in which projects to fund © 2012 Copyright Galorath Incorporated 11 Potentially 80% of Projects Don’t Return Adequate Value Most projects cost more than they return, Mercer Consulting: • “When the true costs are added up, as many as 80% of technology projects actually cost more than they return. It is not done intentionally but the costs are always underestimated and the benefits are always overestimated.” Dosani, 2001 © 2012 Copyright Galorath Incorporated 12 IT Has Similar Failures • Cutter Consortium Software Project Survey: • 62% overran original schedule by more than 50% • 64% more than 50% over budget • 70% had critical product quality defects after release • Standish Group CHAOS Report • 46% challenged • 19% failed • 35% successful •“ Fully one in six of the projects we studied was a black swan, with a cost overrun of 200% on average, and a schedule overrun of almost 70%” ~$875 billion spent on IT ~$300 billion spent on IT projects ~$57 billion wasted annually © 2012 Copyright Galorath Incorporated 13 Using Gates and Refining Estimates is a Best Practice (Adapted from K. Aguanno) Gate 1 Great Idea Concept - Describe idea & Possible benefits Gate 2 Opportunity Analysis Gate 3 Preliminary Business Case Marketing Feasibility Study Analysis -Determine customer acceptance -Interview focus groups, etc. - Design solution - Estimate cost / schedule - Analyze risk - Determine feasibility / ROI Gate 4 Committed Business Case Pilot or Proof of Concept Achieve Business Case Full Execution or Deployment - Validate & commit to design & approach -Build solution -Revised estimates & schedule -Achieve -business case -Risk reduction -Baselined plan - Deploy -Capture lessons learned -Including estimating Causes of Project Failure Source: POST Report on UK Government IT Projects 1. Lack of a clear link between the project and the organisation’s key strategic priorities, including agreed measures of success. 2. Lack of clear senior management and ministerial ownership and leadership 3. Lack of effective engagement with Stakeholders 4. Lack of skills and proven approach to project management and risk management 5. Lack of understanding of and contact with the supply industry at senior levels within the organisation 6. Evaluation of proposals driven by initial price rather than long-term value for money (especially securing the delivery of business benefits) 7. Too little attention to breaking development and implementation into manageable steps 8. Inadequate resources and skill to deliver the total delivery portfolio Source: POST Report on UK Government IT Projects © 2012 Copyright Galorath Incorporated 15 US Better Buying Power Initiatives • • • June 28, 2010 Mandate September 14, 2010 Guidance November 3, 2010 Implementation • Five Specific Areas of Concern: • Target Affordability and Control Cost Growth • Reduce Non-Productive Processes and Bureaucracy • Incentivize Productivity and Innovation in Industry • Promote Real Competition • Improve Tradecraft in Services Acquisition © 2012 Copyright Galorath Incorporated 16 Affordability Initiatives With “Should Cost” and “Will Cost” Will Cost Performance © 2012 Copyright Galorath Incorporated - Cost Initiatives (Applied practices & improvements) = Should Cost Performance 17 Characteristics of a Successful Should Cost Review (Source: AT Kearney) © 2012 Copyright Galorath Incorporated 18 Key Points Cost Estimation with repeatable Process is best practice © 2012 Copyright Galorath Incorporated 19 An Estimate Defined • An estimate is the most knowledgeable statement you can make at a particular point in time regarding: • Effort / Cost • Schedule • Staffing • Risk • Reliability • • Estimates more precise with progress A WELL FORMED ESTIMATE IS A DISTRIBUTION 20 © 2012 Copyright Galorath Incorporated 20 Viable Estimation Is Critical • Estimating is critical for all kinds of systems • Yet many treat is as a second rate process • Everyone estimates…. Just most get it wrong and don’t have a process • Having a repeatable estimation process is critical to both estimating AND to successful projects • Estimation and measurement go hand in hand © 2012 Copyright Galorath Incorporated 21 Estimation Methods 1 of 2 Model Category Description Advantages Limitations Guessing Off the cuff estimates Quick Can obtain any answer desired No Basis or substantiation No Process Usually Wrong Analogy Compare project with past similar projects. Estimates are based on actual experience. Truly similar projects must exist Expert Judgment Consult with one or more experts. Little or no historical data is needed; good for new or unique projects. Experts tend to be biased; knowledge level is sometimes questionable; may not be consistent. Top Down Estimation A hierarchical decomposition of the system into progressively smaller components is used to estimate the size of a software component. Provides an estimate linked to requirements and allows common libraries to size lower level components. Need valid requirements. Difficult to track architecture; engineering bias may lead to underestimation. © 2012 Copyright Galorath Incorporated 22 Estimation Methods 2 of 2 Model Category Description Bottoms Up Estimation Divide the problem into the lowest items. Estimate each item… sum the parts. Complete WBS can be verified. Design To Cost Uses expert judgment to determine how much functionality can be provided for given budget. Easy to get under stakeholder number. Little or no engineering basis. Simple CER’s Equation with one or more unknowns that provides cost / schedule estimate. Some basis in data. Simple relationships may not tell the whole story. Historical data may not tell the whole story. Comprehensive Parametric Models Perform overall estimate using design parameters and mathematical algorithms. Models are usually fast and easy to use, and useful early in a program; they are also objective and repeatable. Models can be inaccurate if not properly calibrated and validated; historical data may not be relevant to new programs; optimism in parameters may lead to underestimation. © 2012 Copyright Galorath Incorporated Advantages Limitations The whole is generally bigger than the sum of the parts. Costs occur in items that are not considered in the WBS. 23 23 “Best Value” Data Needs (adapted from Boeing Value Front) Customer Need Priorities (Decision Analysis) Customer Desirability Attribute Value Models & Methods TOC Cost-Risk Uncertainty Simulation Attribute Value Distribution © 2012 Copyright Galorath Incorporated DevProd O/S 24 Functional Focus Example: Ladies Purse • • • Function ………………………………………... Hold stuff Cost…………………………………………… $400 at Nordstrom What else will perform the function? • Paper bag - Cost = $0.05 • Go to plastic bag for more durability • Cost = $0.10 • • Add color………………………………………..Cost = $0.15 Add strap.……………………………………….Cost = $0.25 Misses one component of customer satisfaction © 2012 Copyright Galorath Incorporated 25 “Far Out” Higher TRL Level Estimation Goal: Better Cost For Highly Advanced Space Missions (15-20 Years in the Future) Proposed Hyperspectral Imaging Satellite predicted fielding: 2016 This capability would be of interest to: • Military space asset planners • Government agencies • Commercial satellite producers • Advanced concept designers Critical items at less than TRL 4… Like asking Edison in 1876 “How much longer for the light bulb?” •“Hard to say” In 1879, once he had found a workable carbon filament, “How much will a production version of the light bulb cost to develop and produce Tom?” •Then a TRL 4 question TRL 9 TRL 8 TRL 7 TRL 6 TRL 5 TRL 4 TRL 3 TRL 2 TRL 1 TRL9: Actual system “flight proven” thorough successful mission operations TRL8: Actual system completed and “flight qualified” through test and demonstration Desired capability Impact At TRL TRL7: System prototype demonstration in a space environment TRL6: System/subsystem model or prototype demonstration in a relevant environment Impact At TRL TRL5: Component and/or breadboard validation in relevant environment TRL4: Component and/or breadboard validation in laboratory environment TRL3: Analytical and experimental critical function and/or characteristic proof-of-concept TRL2: Technology concept and/or application formulated Early impacts have a much greater impact on the final system 7 C 3 B Impact At TRL 1 A Limits of potential impacts TRL1: Basic principles observed and reported TRL 1 © 2012 Copyright Galorath Incorporated 2 3 4 5 6 7 8 9 26 Black Swans (Unknowns) Overrun % The match is unlikely to ever be perfect because some projects are affected by “unknown unknowns,” also called Black Swans, that is, events that are essentially unpredictable (e.g., a severe worldwide credit squeeze) Score Overrun % • Score Score © 2012 Copyright Galorath Incorporated 27 Dealing With the “Problem of Assumptions” • • Assumptions are essential but… • Use an assumption verification process Incorrect assumptions can drive an estimate to uselessness 1. Identify assumptions 2. Rank order assumptions based on estimate impact 3. Identify high ranking assumptions that are risky 4. Clarify high ranking, high risk assumptions & quantify what happens if those assumptions change 5. Adjust range of SEER inputs to describe the uncertainty in assumptions Estimates must have assumptions defined, but… Bad assumptions should not be justification for bad estimates © 2012 Copyright Galorath Incorporated 28 System Description (Parametrics Can Estimate More, Earlier) Adapted from CEBOK “If you can’t tell me what it is, I can’t tell you what it costs.” -Mike Jeffers “If you can tell me the range of what it might be, I can tell you the range of cost, schedule & probability.” -Dan Galorath © 2012 Copyright Galorath Incorporated 29 Uncertainty in the Cost Depends On Uncertainty of the Project Itself SEER includes uncertainty in its estimates Within 10% Even though the entire project may be highly uncertain, tasks to the next gate should be estimatible within 10%. © 2012 Copyright Galorath Incorporated 30 Statistician Drowns in River with Average Depth of 3 Feet! 31 © 2012 Copyright Galorath Incorporated 31 Range vs. Point Estimates (Source US Army) Point estimate is most likely within range estimate with higher potential for cost increase Target Cost Actual -3% to +10% Engineering -5% to +15% Parametric -10% to +20% Analogy -15% to +30% Range estimate provides a degree of risk and uncertainty ROM -30% to +75% Range of Risk & Uncertainty +75% Technical and Program Maturity Estimating Accuracy Trumpet -30% A Materiel Solution Analysis B Technology Development Pre-Systems Acquisition © 2012 Copyright Galorath Incorporated C Engineering and Manufacturing Development Systems Acquisition Production & Deployment Operations & Support Sustainment 32 Firm Fixed Price? Feel lucky? What is likely to happen Understand the risk before you commit! 33 © 2012 Copyright Galorath Incorporated 33 Dealing With Early Estimates • Give a range: but they will hear the bottom of the range • Give a high probability number: • Will still be low in some cases and may be high in many cases but consider it a probably “not to exceed” • Sticker shock may be a problem • Give a category rather than an number: e.g over $10m Cat 1; over $5m Cat 2; over $1m Cat 3, etc. Stakeholders always remember the first number even when told it is preliminary. Developers will be optimistic by nature unless the process is tempered. © 2012 Copyright Galorath Incorporated 34 Potential Accuracy at Various Gates (Adapted From Canada Treasury) Concept / Approach •+- 10% to next gate •+_50 with Analogies & kbases Business Case •+_ 40% •Analogies, Kbases & some specifics Project Charter & Plan •+_25% Detailed Plan & functional specs Construction / Deployment •+_ 15% •+- 0% •SEER +_10% if good inputs PostDeployment •+-0% •NOTE Should understand if full functionality was delivered or if schedule/cost relief based on deferred functionality •While Galorath states SEER is Within 10%, many organizations report much closer Estimate Accuracy Is a Function of Input Information Quality. Estimates Can Be Much Closer than Shown IF Data Is Available. http://www.tbs-sct.gc.ca/itp-pti/pog-spg/irh-mei/irh-mei03-eng.asp © 2012 Copyright Galorath Incorporated 35 Converting Uncertainty to Risk Is A Best Practice • Many treat as synonymous but… • In risk situations, probabilities assigned based on data • In uncertainty situations, we may assign probabilities • But there is no data to back them up • If probability of rain tomorrow is 50%, that’s a risk • We have historical data & scientific analyses about rain which make it reasonable to estimate the probability • If we say Probability of success in harnessing nuclear fusion for routine energy production within the next ten years is 50%, that’s just a guess about uncertainty—evidence for the assignment is lacking or very weak If you toss this thumbtack, what is the probability it will land this way instead of on its back? © 2012 Copyright Galorath Incorporated 36 GAO Publication: Characteristics of credible cost estimates and a reliable process for creating them • • This chapter discusses a 1972 GAO report on cost estimating • We reported that cost estimates were understated and causing unexpected cost growth • Many of the factors causing this problem are still relevant today We also discuss a 12 step process for producing high quality cost estimates © 2012 Copyright Galorath Incorporated 37 Generalized 10 Step System Estimation Process 2011 1. 2. Establish Estimate Scope 10. Establish Technical Baseline, Ground Rules, Assumptions 9. 8. 4. Refine Technical Baseline Into Estimable Components 4. 6. Collect data / estimation inputs 6. 5. © 2012 Copyright Galorath Incorporated Track Project Throughout Development Document Estimates and Lessons Learned Generate a Project Plan Validate Business Case Costs & Benefits (go / no go) Quantify Risks and Risk Analysis Estimate Baseline Cost, Schedule, Affordability Value 38 Contractors At Least Level 3 Would Be Acceptable Level 0 Informal or no estimating Manual effort estimating without a process Level 1 Direct Task Estimation Spreadsheets Level 2 Formal Sizing (e.g. function points) Direct Task Estimation Ad Hoc Process Simple model (Size * Productivity) or informal SEER Use Some measureme nt & analysis Informal Process Level 3 Formal Sizing Level 4 Formal sizing Repeatable process Robust parametric estimating (SEER) Rigorous measurement & analysis Parametric estimation with tracking & control Risk Management Process improvement via lessons learned Level 5 Formal sizing Repeatable process Robust parametric estimating (SEER) Rigorous measurement & analysis Parametric estimation with tracking & control Risk Management Continuous process improvement Robust Parametric estimation (SEER) Estimate vs. actual capture Formalized Multiple Estimate Process Rigorous measurement & analysis Parametric planning & Control Risk Management Repeatable process Why should we care? Maturity is related to estimate viability… Better estimation process more likely to be successful in execution © 2012 Copyright Galorath Incorporated 39 Key Points Viable Affordability decisions yield project achievements 40 © 2012 Copyright Galorath Incorporated 40 Affordability Process Step 1. Procure Key Performance Parameters that are inviolate Step 8. Perform Probabilistic Risk Analysis Step 9. Assess Alternatives & Select Optimal Alternative Step 2. Identify Affordability Goals & Figures of Merit (development, life cycle, payback, ROI, NPV, kill ratio, Budget constraints, etc.) Step 7. Assess Benefits Based on Figures of Merit Step 10. Document Analysis and Lessons Learned Step 3. Gather Requirements, Features, Performance Step 6. Perform Cost Schedule Analysis of Each Alternative Step 4. Define Baseline Alternatives Step 5. Perform Technical Design Analysis for Each Alternative © 2012 Copyright Galorath Incorporated 41 Should Cost: Trade Study Flow Requirements And Features Analysis Preliminary Design Process Alternative 1 Alternative 2 Alternative 3 Alternative 4 Other Factors •Human Factors •Security •Reliability •Availability •Survivability •Supportability •Testability •Producibility •Reuse •Transportability Selection Process 4 3 2 SEER Assessment •Performance •Schedule •Risk Assessment •Life Cycle Cost Iterate 5 1 No OK? Optimized? Yes Cost Performance Schedule Risk Bottoms Up Estimation as Required © 2012 Copyright Galorath Incorporated 42 Manual Estimates: Human Reasons For Error (Metrics Can Help) • Manual Task estimates yield SIGNIFICANT error without ranges • Desire for “credibility” motivates overestimate behavior (80% probability?) • So must spend all the time to be “reliable” • Best practice approach force 50% probability & have “buffer” for overruns • Technical pride sometimes causes underestimates © 2012 Copyright Galorath 43 Incorporated 43 Balancing Resources & Schedule Is A Best Practice For a given Size, Complexity and Technology Work Expands To Fill Time (Effort Increases Minimum Time To Complete (Effort Increases to Reduce Schedule) Effort Months Minimum Time due to lack of pressure ) Effort Increase due to Longer Schedule Optimal Effort (Lower Effort for Longer Schedule) Calendar Time © 2012 Copyright Galorath Incorporated 44 Understand Project Risks Include Them In Planning Decisions (Example SEER-SEM Outputs) Probability 99% 90% 80% 70% 60% 50% 40% 30% 20% 10% 1% 0 Schedule Probability Example Application 1 4 8 12 16 20 Probability 99% 90% 80% 70% 60% 50% 40% 30% 20% 10% 1% 0 Effort Probability Example Application 1 1800 Time (calendar months) 3600 5400 7200 9000 Effort (person-hours) Probability 99% 90% 80% 70% 60% 50% 40% 30% 20% 10% 1% 0 Defects Probability Example Application 1 12 24 36 48 60 Defects (count) • © 2012 Copyright Galorath Incorporated 45 Understanding & Tracking Defects, Growth And Other Metrics Health and Status Indicator shows status and trends from the previous snapshot Track defect discovery and removal rates against expected rates •Including Size Growth and Defect Discovery/Removal Rate •User defined control limits to control the transition between red-yellow-green Increased defect reporting rate shows a worsening trend Track software size growth © 2012 Copyright Galorath Incorporated 46 Goal Question Metric Approach Best Practice Goal Organizational Goal Question Development Contractors Organizations Metric • Combine goal-orientation bottoms up, decision-support & other operational management techniques • www.weather.com to decide to bring an umbrella is decision support © 2012 Copyright Galorath Incorporated 47 Reasons Many Don’t Want To Provide Data • They could be proven wrong • It could be used against them • Data often doesn’t exist • Even if processes dictate data requirements • If it exists, it may not be clean • It may give away corporate productivity & bid strategy © 2012 Copyright Galorath Incorporated 48 Data Must Be Used With Caution • Run sanity checks on data • A million lines of code can’t be developed in 3 months • Ongoing issue between our statisticians and engineers • Some Statisticians claim.. “That is what the data says, so it must be right” • Sometimes even if it is obviously wrong © 2012 Copyright Galorath Incorporated 49 Data Doesn’t Have To Be Perfect To Be Useful: But Is Has To Be Viable • • • 80 Calories per serving 2.5 Servings per can 4 Ounces, Condensed, 8 Ounces With Water © 2012 Copyright Galorath Incorporated 50 You Have An Estimate … Now What? © 2012 Copyright Galorath Incorporated 51 The Error of Causal Analysis Creating a False Association • Correlation does not imply causation • Just because two data points may sit side by side doesn’t mean they are the same or will have the same outcome • Casual analysis is a recognized error in medicine Tumor Can Cause Headache Perhaps ??? Headache doesn’t mean a tumor © 2012 Copyright Galorath Incorporated 52 Use Historical Measurement to Evaluate Your Estimate! It’s easy to dig deeper and deeper to justify an estimate! © 2012 Copyright Galorath Incorporated 53 Estimation Best Practices • • Decide Why You Want An Estimate • • Have A Documented, Repeatable Estimation Process • Be Proactive: The Process Is Important, The Tools Go Along With The Process • • Get Buy-in From Program Managers • Tie The Estimate To The Plan Map Estimation Goals To Estimate Process Maturity & Develop Plan To Achieve The Maturity Make The Estimating Process As Simple As Possible; But No Simpler Hold People Accountable: Center Of Excellence Can Prepare Estimate But Program Managers Must Own Them © 2012 Copyright Galorath Incorporated 54 Estimation Best Practices 2 • • • • Evaluate Total Ownership Cost; Not Just Development • • • Keep A History: Start An Enterprise Database NOW… Estimate A Range And Pick A Point For The Plan Re-estimate The Program When It Changes Avoid Death Marches: Programs With Unachievable Schedules Are Likely To Fail And Drain Morale Business Case: Evaluate ROI In Addition To Costs Convert Expert Spreadsheets Into A Common Language © 2012 Copyright Galorath Incorporated 55 Estimation Best Practices 3 • • Track Progress Vs. Estimate Throughout The Life Cycle • • Tie The Business Case Into The Estimating Process Estimate Schedule As Well As Effort (Cost) For Complete Picture Attack Non-productive Rework As Part Of The Process © 2012 Copyright Galorath Incorporated 56 Estimation Best Practices 4 • Have clear definitions: What does “complete” mean? What activities are included and excluded (E.g. development only or total ownership; help desk included or excluded, etc.) Which labor categories are included and excluded in the estimate (e.g. are managers included? Help desk? Etc.) • • • • Measure what you care about Estimating & tracking rework can help control costs Don’t ignore IT infrastructure and IT services costs Tracking defect sources can go along with the process © 2012 Copyright Galorath Incorporated 57 Conclusions • Cost estimation and analysis are VITAL core processes • Best practices ferret out what the cost is REALLY anticipated to be • • Risk and uncertainty must be taken into account • Applying affordability analysis to the business case yields the best value Best practice project management understands the difference and acts to reduce uncertainty, or convert it to risk © 2012 Copyright Galorath Incorporated 58 Additional Information • • • • www.galorath.com Dan on estimating BLOG: www.galorath.com/wp Email: [email protected] Phone: +1 310 414-3222 x614 © 2012 Copyright Galorath Incorporated 59