1. Project Selection

2. 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).

3. 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

4. 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

5. 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

6. II. Project Selection: Numeric Models
Profitability Index (Cost-Benefit)
Index = NPV / Initial Investment (A0)
E.g. Index = $1, / $ = 0.24

7. II. Project Selection: Numeric Models
Scoring Methods
1. Unweighted 0-1 Factor
2. Unweighted Factor Scoring
Example – Project A
Qualify No Qualify S Environmental Impact x
Need for Consultants x
Impact on Image x
Totals

8. 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)

9. 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 + 5X s.t X1 + 5X2+ 3X3  7 Workers X1,X2,X3 = 0 or 1

10. 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.
Probability Cost $

11. Summary Numeric Methods Can Assist in: Project Selection
Bidding through Cost Estimation and Computer Software Such as Quickest (Constructive Computing)