# Project Selection - PowerPoint PPT Presentation

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Project Selection. I. Project Selection: Non-Numeric Models. Sacred Cow Operating Necessity Competitive Necessity Product Line Extension Comparative Benefit

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Project Selection

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### I. Project Selection: Non-Numeric Models

• Sacred Cow

• Operating Necessity

• Competitive Necessity

• Product Line Extension

• Comparative Benefit

(E.g. Q-SORT: Projects are Divided into Rated Groups. If a Group Has More than Eight Members, It is Divided into Two Groups. Then Projects within Groups are Ranked).

### II. Project Selection: Numeric Models

• Payback Period

Initial Fixed Investment / Annual Cash Inflow E.g. \$10,000 / \$2000 = 5 Years

• Mean Rate of Return

Annual Return / Initial Investment E.g. \$3,000 / \$10,000 = 0.30

### II. Project Selection: Numeric Models

• Present Value (Discounted Cash Flow)

1.In One Year:

(Net Present Value)(1+k) = (Future Value)

Where k is Interest Rate

E.g. (\$10,000 or NPV) (1.1) = \$11,000 = F

2.In t Years:

NPV (1+k)t = F E.g. (\$10,000) (1.1) (1.1) = \$12,100

### II. Project Selection: Numeric Models

• Present Value (Discounted Cash Flow)

3.Solving for NPV:

NPV = F / (1+k)t

E.g. NPV = \$12,100 / 1.21 = \$10,000

4.If You Have F’s in Different Years (or Periods)

NPV = -A0 + [F1/(1+k)1] + [F2/(1+k)2] + Etc. NPV = -\$7,000+(\$5,000/1.1)+(\$5,000/1.21) NPV = \$1,677.68

### II. Project Selection: Numeric Models

• Profitability Index (Cost-Benefit)

Index = NPV / Initial Investment (A0)

E.g. Index = \$1,677.68 / \$7000.00 = 0.24

### II. Project Selection: Numeric Models

• Scoring Methods

1.Unweighted 0-1 Factor

2.Unweighted Factor Scoring

Example – Project A

QualifyNo Qualify S Environmental Impact x 8

Need for Consultants x 3

Impact on Image x 7

Totals2 1 18

### II. Project Selection: Numeric Models

• Scoring Methods

3.Weighted Factor Scoring

For Each Project i: Si = Si1W1 + Si2W2 + Si3W3 + Etc. E.g. S1 = (10)(0.5) + (10)(0.3) + (5)(0.2) = 9

Select Projects with Highest Scores (Si’s)

### II. Project Selection: Numeric Models

• Scoring Methods

4.Linear (Integer) Programming

Maximize Z = S1X1 + S2X2 + S3X3 + Etc.Subject to: m1X1 + m2X2+ Etc.  M Xi = 0 or 1

E.g. Max. Z = 10 X1 + 10X2 + 5X3 s.t. 2X1 + 5X2+ 3X3 7 Workers X1,X2,X3 = 0 or 1

### II. Project Selection: Numeric Models

• Analysis of Projects Under Uncertainty

• Primary Source of Uncertainty: Time and Cost

• We Can Use Monte Carlo Simulation

• Computer Can Generate Typical (E.g. Normally Distributed) Activity Times and Costs. After 1000’s of Runs a Cost Probability Distribution Can be Generated for Each Proposed Project.

ProbabilityCost.3 \$1000 .42000

.33000

### Summary

Numeric Methods Can Assist in:

• Project Selection

• Bidding through Cost Estimation and ComputerSoftware Such as Quickest (Constructive Computing)