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Improve Project Plans, Budgets & Schedules Mike Tulkoff [email protected]
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Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff [email protected] Overruns the norm: 40 to 200%1 ... C. R.

Sep 29, 2018

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Page 1: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Improve Project Plans, Budgets & Schedules Mike Tulkoff

[email protected]

Page 2: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

◦ Overruns the norm: 40 to 200%1

◦ E&Y 2009 Survey 3

96% of managers want to improve risk mgmt.

46% think spending more $ on risk mgmt leads to competitive advantage

0

10

20

30

40

50

60

70

Projects in

Budget

Projects on

Time

Projects met

Deliverables

Project

Failures

KPMG 2012 Survey2

1. Morris, P., & Hough, G. (1987). The anatomy of major projects: A study of the reality of project management. Chichester: Wiley. 2. https://www.kpmg.com/NZ/en/IssuesAndInsights/ArticlesPublications/Documents/KPMG-Project-Management-Survey-2013.pdf 3. https://www.yumpu.com/en/document/view/27686141/the-future-of-risk-protecting-and-enabling-performance-directors-

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Project Success Factors

Brief history of project management

Basic Risk Management

Review of Project Management Methods

Simulation and Monte Carlo

Example Project with Simulation

Conclusions

Speaker Bio

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Adoption &

consistent use of

project management

methodology

Dedicated project

manager

Aligning project

goals with business

& customer needs

Scope management Effective RISK

MANAGEMENT

Effective use of

multi-point

estimation

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4. Meredith, J., & Mantel, S. (1995). Project management: A managerial approach (3rd ed.). New York: Wiley.

5. Wilson, J. M. (2003). Gantt charts: A centenary appreciation. European Journal of Operational Research, 149(2), 430-437.

6. Moder, J. J., & Phillips, C. R. (1970). Project Management with CPM and PERT (2nd ed.).

Project schedule is

most important

tool.4

Gantt invented Gantt

chart early 20th

century

•Earliest network graph

•Adapted for project mgmt

1920s.5

1957 DuPont

invented Critical Path

Management (CPM)

•Optimal tradeoff between

time and cost

1958 – U.S. Navy and

Booz, Allen, and

Hamilton invented

Program Evaluation

Review Technique

(PERT) for Polaris

Missile Project.

•Decreased costs 66% and

durations 33%.6

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Identify Risks, perform risk analysis & plan risk responses (PMI PMBOK 5).

Use Identification Tools

•Documentation, project WBS, SWOT analysis, cross-functional reviews (e.g. legal, financial)

Use Risk Register

•Matrix of identified risks, categories, likelihood, mitigation, owner.

Risk Management is an iterative approach – feedback into the project plan

Simulation & prototype have highest correlations to successful risk

mitigation.7

7, Raz, T., & Michael, E. (2001). Use and benefits of tools for project risk management. International Journal of Project Management, 19(1)

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Risk Register helps characterize known risks and potential “black swans”.

Probability and project impact

Mitigation plans

Page 8: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Critical Path ◦ Longest chain of dependent steps in a project

◦ Determines the time it takes to finish overall project

◦ Any delay along critical path delays whole project

Page 9: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Single point estimates are error prone & not conducive to risk management

PERT durations/costs use 3-point estimates ◦ a = best case (5% chance or better) ◦ m = most likely (90%) ◦ b = worst case (5%)

PERT uses a Beta Distribution8 ◦ Mean = (a+4m+b) / 6

“Modern” formula is .63 * m + .185*(a+b) corrects for lack of true min and max

◦ Variance = (b-a/6)2 “Modern” formula is (b-a/3.25)2

◦ Standard Deviation = b-a/6 “Modern” is b-a/3.25

8. Source of PERT information: Anderson, M.A and Anderson E.G. (2015) lecture materials from the course

Technology Enterprise Design and Implementation at the University of Texas at Austin.

Page 10: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

You still need to use a risk register & simulation!

PERT

Cont’d

Can now calculate

overall project

probabilities

Expected project cost

= 𝞢 activity costs

Project cost variance =

𝞢 activity variances

Project duration/cost is normally distributed

Estimate the 90% or 95% likely completion time and cost (within a range).

Limitations Garbage in, garbage out

Does not account for true uncertainty

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Why Simulation?

Project plans have

variance risk due

to imprecise or

overly optimistic

estimates

Risk also comes

from predictable &

unpredictable

events

•Have a disproportionate

effect on the project

duration & cost

Management of

uncertainty is key

Page 12: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Used finance, business, physics, engineering, biology, project management, etc.

Tools used in this presentation include ◦ @RISK (Palisades Corp)

◦ Project & Excel (Microsoft Corp)

Monte Carlo Process

Model

uncertain

inputs as

distributions

Generate

pseudo

random

numbers

each iteration

Deterministic

computation

Aggregate

output -

probability

density

Page 13: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

A Trivial Example ◦ Roll two 6-sided die

◦ Output is sum of dice

◦ After 1000 iterations, results show probabilities

Die 1

=RiskDiscrete({1,2,3,4,5,6},{0.166666667,0.166666667,0.166666667,0.166666667,0.166666667,0.166666667},RiskStatic(1))

Die 2

=RiskDiscrete({1,2,3,4,5,6},{0.166666667,0.166666667,0.166666667,0.166666667,0.166666667,0.166666667},RiskStatic(1))

Sum =RiskOutput("Sum")+SUM(B2:B3)

Page 14: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Sample Project Simulation

Background schematic image courtesy of InvenSense

Proj Plan courtesy of Kibbe, Pfau, Reber, Shields, Tulkoff (2015)

Page 15: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Step 1 : Create Project Plan

Create a Work Breakdown Structure (WBS)

Enter tasks into PM tool (e.g. MS Project)

Assign resources & dependencies

Use most likely or optimistic durations for now

•Will deal with durations again later

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Page 17: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

1. Cannot control vendor performance

2. Not accounting for Engineering re-work is a major reason projects fail.9

3. Task duration variance (use PERT)

4. External risks have great effect ◦ In this simulation, they delay the project start date.

Event Probability Delay

No Delay .45 0 days

Problem with funding

.20 30 days

Hiring problems .15 15 days

Freedom to operate issue

.10 90 days

Technology prototype issues

.10 45 days

9. Reichelt, K., & Lyneis, J. (1999). The Dynamics of Project Performance: Benchmarking the Drivers of Cost and Schedule Overrun.European Management Journal, 17(2), 135.

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Click project on @RISK ribbon and import MPP file. Note that it draws a Gantt chart. Inputs and Outputs are tied to Excel cells.

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Create appropriate input distributions. ◦ There is no “right” answer.

◦ Do what makes sense.

The uncertain inputs that we found can be modeled as a discrete probability distribution with initial duration tied to probability:

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Vendor risk (Mold creation task in this example) can be modeled as a Uniform distribution between two bounds.

All values are equal probability.

Note this is to illustrate the distribution ◦ would use something more discrete here.

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Engineering re-work can be modeled as a normal distribution with some right skew.

Task can be accounted for & simulated as it is uncertain how extensive this will be going into the project.

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Task variance can be modeled using PERT (or with Triangle or Trigen distributions)

PERT is a natural fit for project tasks.

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Step 5: Add Outputs, Run simulation

•Outputs are tied to cells with data that varies

based on varying inputs

•Flexibility to also tie values to additional Excel

data, formulas, conditionals

•May run simulation using multiple scenarios &

perform sensitivity analysis

•Should run at least 1000 iterations

•10k is better

•Directly integrated with Project – uses Project’s

scheduling engine each iteration

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Total Task Duration

Critical Path Duration

Page 25: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

End Date

Cost

Page 26: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Total duration Tornado

Page 27: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Total Cost Tornado

Page 28: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Projects have inherent task variation risk as well as risk from

uncertainty

Projects can be more successful by using a consistent

methodology, using multi-point estimates, accounting for re-

work, and analyzing/managing risk

Simulation including Monte Carlo is a powerful tool to deal

with uncertainty

Risk management is an iterative process

Page 29: Improve Project Plans, Budgets & Schedules Mike Tulkoff ... · Improve Project Plans, Budgets & Schedules Mike Tulkoff mtulkoff@gmail.com Overruns the norm: 40 to 200%1 ... C. R.

Mike Tulkoff is a Software Engineer with over twenty years of delivering Enterprise Computing solutions. He has spent his career building great products that satisfy market needs and has had technical and managerial roles at both large, global companies and small start-ups. Mike has 12 U.S. patents and holds an MS in Technology Commercialization from the University of Texas at Austin McCombs School of Business and a BS in Computer Science from Georgia Institute of Technology.

Please feel free to contact Mike at [email protected] with additional questions, discussion, or consulting inquiries.