Ron Rammage Earlyestimation

7/31/2019 Ron Rammage Earlyestimation

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Sources of error in Software Estimation for MedicalDevice Development Projects



“That’s the wrong answer… ”



According to the 1994 CHAOS

report the average cost over-run for software projects is

189%



Builder estimated cost as part of scope definition



The Need for earlier estimatesy Projects are a function in 4 variables

y Scope

y Resources

y Schedule

y Quality

y If Scope, Resources, and Schedule expectations arenot realistic

y Quality becomes the inevitable loser!



Estimation is seen as part of

Schedule Development

Project TimeProject Scope ManagementManagement

•Define Activities

•Collect Requirements •Sequence Activities•

Define Scope•

Estimate Activity Resources•Create WBS •Estimate Activity Durations

•Develop Schedule



The Dilemma of Scope

Definitiony Outputs from Define Scope Process

y Product scope description

y Product acceptancecriteria y Projectdeliverablesy Project exclusionsy Project

constraintsy Project constraints usually includes scheduleand resources



The dilemmay Defining scope without estimating the impact

of restraints leads to failure

y But we don’t do estimation until after the scopeis defined



Mr Honcho,the VP says “We need a scope statement but don’t havemuch time to coordinate.

•Mr Earnest, you make a list of everything you can think of that you’d

like it to do.

•Mr Eager, you decide how long you want to wait for it. • We’ll paste

your inputs into the scope statement, approve it and send it to the

developers next week.



The Challenge !yWe need a data driven

estimation tool that can

be employed prior tomaking decisions of scope and constraints



Otherw ise we’ re stuc k w ithIndustry standard definition of

“Estimate” y [The common definition of

estimate is] "the most optimistic prediction that has anon-zero probability of coming true." … Accepting this

definition leads irrevocably toward a method called

what's-the-earliest- date-by-which-you-can't-prove-you-

won't-be-finished estimating

Tom DeMarco—



“How long will it take you to do this in six months?”



Why do w e fail to estim ate ?



The Cone of Uncertainty



Estimate

Targ et Schedu le



Estimate, Target or Plany Estimate -- “a prediction of how long a project

will take or how much it will cost.” *

yTarget - “i s a statement o f a desirable bu sinessobjective.”*

y *Steve McConnell, Software Estimation

y Plan -- an expedient methodology for accomplishinga required effort (possibly from an estimate) within theconstraints imposed by a target. Example - a schedule.



Definiti on of an “Estim ate”



The Solutiony Expert Estimation during Scope Definition

y “Expert judgment, guided by historical information, can

prov ide du ration es tima te in f orma tion or recommen dedmaximum activity durations from prior similar projects.”

y PMBOK Guide, 4th Edition, pp 149.

y Expert Estimation can be applied to earlier phases of the project



Method for Expert Estimationy Get as much definition of expected scope

and requirements on paper as possibleCWBS w ithh det ailibl yreate aas mucas

possey It helps to have a standard template with deliverables of

your development process already populatedy Distributeto Subject Matter Experts y Collect 3 point Estimates

for each tasky See PMBOK Guide 4, pp 150)



Method for Expert Estimationy Collect estimates and compile as appropriate

y Calculate Expected Values according to the PERT

f ormu lay Expected Value = (BestCase + 4*LikelyCase +

WorstCase)/6 y Calculate Estimated StandardDeviationy EstStdDev = (WorstCase - BestCase)/6

yPresent Estimates in terms of y Expected Effort

y Uncertainty bound

y(Expected + 1 StdDev) = 84% confidence



Example - Subway SandwichTask Best Likely Worst Expected Estimated

StdDev

Wait in Line 0 sec 45 sec 180 sec 60 sec 30 sec

Build Bread/Meat 20 sec 40 sec 120 sec 50 sec 17 secSubassembly

Add Cheese Accessory 5 sec 10 sec 20 sec 11 sec 3 sec

Compile Veggie 10 sec 25 sec 90 sec 33 sec 13 secOptions

P rocess mone t ary 20 sec 100 sec 200 sec 103 sec 30 secexchange

Complete Drink 30 sec 48 sec 90 sec 52 sec 10 secdelivery



Example - Monte Carlo Analysis

Certainty 1.2Time (sec) Certainty

1

220 0.02 0.8

0.6

264 016 04

0.2

309 0.5 0

0 100 200 300 400 500

354 0.84

84% confidence Project will

complete within 5 min 54 sec398 0.98



Example - Analysis conclusionsy The sum of Best Case estimates (85 sec) -

probability of completion on time would bey ~ 1i n

400,000y The sum of Likely Case estimates (268 sec) -

probability of completion on time would be

y ~ 1 in 6

y Best estimate is 354 seconds with 84% confidence



References and Recommended

Readingy Steve McConnell, Software Estimation: Demystifying

the Black Art. Redmond WA: Microsoft Press, 2006.

yRo n R ammage et. a l ,E xpert So f tware Dev elopmentEstimation with Uncertainty Correction, SEDM IEEE Proceedings, June 2010 (See additional slides section)

y Tom DeMarco, Controlling Software Projects: Management, Measurement & Estimation. EnglewoodCliffs NJ: Yourdon Press, 1982.



?



For notes and Q&A



E xpert Sof tware Dev elopmentEstimation with Uncertainty

CorrectionRon Rammage, Hairong Lei, Michael Claus, David Baer. SoftwareEngineering and Data Mining Conference, Chengdu China, June 23-25, 2010Proceedings published by IEEE, Conf #16902

Abstract- Creation of an effective metrics and estimation program is an importantbut daunting step for the maturing software development organization. This

paper outlines a roadmap for implementing a process that establishes a programthat will reap a large portion of the benefits early in the process with a minimumof implementation effort and cost. This process includes a mechanism to improvesoftware estimation accuracy as historical data becomes available for moresophisticated methods. Furthermore, we present a practical proposal for softwareestimation in industry based on software task size, complexity, and uncertainty.

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