Decision Making on selection
of alternate energy resources
in a Software Company
Presented By
Hamid Amir
EM/MSC/048
Company Introduction
Numetrics Private Limited, Islamabad Pakistan
 Fully-owned subsidiary of Numetrics Management Systems
 Based in Silicon Valley in USA
 A world leader in providing predictive analytics project
management software for:
◦ IC
◦ Semi-conductor
◦ Embedded systems organizations
 The core engineering center for the worldwide organization
 Has setup an offshore office in Islamabad comprising 30
colleagues.

Six Steps in Decision Making
Step 1
Step 2
Step 3
• Clearly define problem at hand.
• List possible alternatives
• Identify possible Outcomes
• List pay offs or profits for each combination of
alternatives and outcomes
Step 4
• List one of the mathematical i.e Quantitative decision
theory models.
Step 5
Step 6
Apply the model and make your decision
Decision Making on selection of
alternate energy resources in a
Software Company
Possible Alternatives

Do nothing i e WAPDA electricity and working with
4 hour load shedding

Solar plus WAPDA

UPS plus WAPDA

Generator plus WAPDA
◦
. Electricity Load Calculation - Numetrics Software
Equipment
Quantity
Wattage
Total
Wattage
CPUs
50
110
5500
LCD Monitors 18"
50
45
2250
Laptops
40
150
6000
Server Machines
6
260
1560
Refrigerator
2
1000
2000
Split A.C 2 Ton
11
2200
24200
Tube lights
80
40
3200
Energy Savers
70
25
1750
Fans
20
80
1600
Total
Total
KW
(Watts/100
0)
48060
48.06
1 Electricity Cost - WAPDA
1.1 Electricity Cost - WAPDA @ Total Load Calculation with 4 hrs daily load-shedding
1 Unit Price for 1 KWH (Rs.)
Peak (Rs.)
Off Peak (Rs.)
13.20
8.01
Assuming Average (Rs.)
(Peak+Off Peak)/2
10.61
Total Load (KW)
Electricity Cost Rs. Per Hr
(Unit Price * Total KW)
Additional Surcharges @
50% (Fuel Adjustment +
GST + Duty )
WAPDA Electricity Cost Rs
Per Month = 22 days
(Unit Price * Total KW
*8*22)
Per Year (for 8 hrs, without
load shedding)
Per Year (for 4 hrs daily
operation)
Total Electricity Cost
WAPDA - 5 years
(for 4 hrs daily operation)
Total Electricity Cost
WAPDA - 10 years
(for 4 hrs daily operation)
48.06
509.68
764.51
134,555
1,614,655
807,327
4,036,636
8,073,273
Electricity Cost - WAPDA
Electricity Cost - WAPDA Partial Load Calculation only for AC & Refrigerator Load (28 KW) )
For further consideration with UPS and Solar options which don't support AC/Ref loads)
1 Unit Price for 1 KWH (Rs.)
Peak (Rs.)
Off Peak (Rs.)
Assuming Average (Rs.) (Peak+Off Peak)/2
WAPDA Electricity Cost Rs.
(Partial for AC/Ref. only)
Per Month = 22 days
(Unit Price * Total KW *8 hrs*22 days)
Per Year (without load shedding)
(month * 12 )
Per Year (for 4 hrs daily operation)
Total Electricity Cost WAPDA - 5 years
(for 4 hrs daily operation)
Total Electricity Cost WAPDA - 10 years
(for 4 hrs daily operation)
13.20
8.01
10.61
78,392
940,706
470,353
2,351,765
4,703,530
B. Revenue Loss due to 4 hrs daily load-shedding
No of Employees
Total Salaries per month (22 days)
30
3,000,000
Total Salaries per hr
17,045
Total Salaries loss per day (4 hrs-load shedding)
68,182
Total Revenue loss per day (4 hrs-loadshedding) Assuming 25% of
salaries
17,045
Total Revenue Loss per month (22 days)
(4 hrs-load shedding)
375,000
Total Revenue Loss per year (12 months)
(4 hrs-loadshedding)
4,500,000
Total Revenue Loss for 5 years
(4 hrs-loadshedding)
22,500,000
Total Revenue Loss for 10 years
(4 hrs-loadshedding)
45,000,000
2 Electricity Cost - SOLAR + WAPDA (Partial)
Solar System
Capacity
Electriciy Load (KW)
48.06
Electriciy Load (KVA)
(1 KVA = 0.8 * KW)
38.448
Solar Panels +
Solar System Initial Cost Inverters + Charge
Controller + Install Cost
Batteries Cost
Solar System Total Initial + Running Cost (5 years)
WAPDA Partial Load Cost for AC + Refrigerator (5 years)
Total Solar (Initial + Running ) + WAPDA Partial Load Cost ( 5 years)
Solar Batteries Upgrade after 5 years
Solar System Total Initial + Running Cost (10 years)
(5 years cost + batteries replacement after 5 years)
WAPDA Partial Load Cost for AC + Refrigerator (10 years)
Total Solar (Initial + Running ) + WAPDA Partial Load Cost ( 10 years)
Cost (Rs.)
4,108,000
5,131,000
9,239,000
2,351,765
11,590,765
5131000
14,370,000
4,703,530
19,073,530
3 Electricity Cost - UPS + WAPDA
Dedicated UPS
Electriciy Load (KW)
Electriciy Load (KVA)
(1 KVA = 0.8 * KW)
UPS Capacity (KVA)
No. of Units Required
Installed capacity (KVA)
UPS Cost per unit
UPS Cost per unit + Maintenance @30% during 5 years
Total UPS Install Cost for 5 years (Rs.) Assuming 5 year
life
WAPDA Supply Cost for 5 years (4 hrs daily)
48.06
38.45
10
8
80
345,000
448,500
3,588,000
4,036,636
UPS Charging cost on WAPDA supply
for 5 years (after 4 hrs discharge daily)
WAPDA Supply * 1.5
6,054,954
Total Cost for 5 years (UPS Install + UPS Operation +
WAPDA Supply for 4 hrs) (Rs.)
10,091,591
Total Cost for 10 years (UPS Install + UPS Operation +
WAPDA Supply for 4 hrs) (Rs.)
20,183,181
4Electricity Cost - Generator + WAPDA
Generator
Capacity (KVA)
Capacity (kW)
Initial Cost (assuming 10 years life)
Running cost per hr (Diesel, Parts, Maintenance)
Running cost per 4-hr (daily load-shedding)
Running cost per month 22 days (4-hr daily loadshedding)
Generator Running cost per year (during 4-hr daily
load-shedding)
Generator Running cost for 5 years (during 4-hr daily
load-shedding)
Total Generator Cost for 5 years (Running cost + initial
cost) for 4 hr daily operation
WAPDA Supply cost for 5 years (4 hrs daily)
Total Generator + WAPDA Cost for 5 years (4 hrs
WAPDA + 4 hrs Generator)
Generator Running cost for 10 years (4-hr daily
operation)
Total Generator Cost for 10 years (Running cost + initial
cost) for 4 hr daily operation
WAPDA Supply cost for 10 years (4 hrs daily)
Total Generator + WAPDA Cost for 10 years (4 hrs
WAPDA + 4 hrs Generator)
60
75
2,200,000
650
2,600
57,200
686,400
3,432,000
5,632,000
4,036,636
9,668,636
6,864,000
9,064,000
8,073,273
17,137,273
Decision making models used
Sensitivity
analysis
Decision Making Models Applied
Decision theory is an analytic and systematic
approach to the study of decision making models.

Good decision; logical, considering all available
data, alternatives and application of quantitative
decision model.
Decision Making Environments

Certainty: alternatives and outcomes known with

certainty -e g interest on income.


Risk: alternatives and Probability of occurrence of each
outcome known-e g fliping of coin .
Uncertainty: Probability of occurrence of each outcome
not known-e g election results after 10 years.

Decision Making under Risk
◦ Probabilistic decision situation
◦ EMV is the weighted sum of possible payoffs
for each alternative.
◦ EOL requires an opportunity loss table; it is the
amount lost by not picking the best
alternative/solution.
◦ Maximum EMV and Minimum EOL will always
give same result.
◦ Sensitivity Analysis investigates how our
decision might change with different input data
/probability scenario.
◦ Decision Trees used for large sequential
decision problems.

Decision making under Uncertainty
◦ Probability data not available
◦ Maximax is an optimitic approach/decision
criterion as it maximizes the maximum
outcome for every alternative
◦ Maximin is a pessimistic approach/decision
criterion as it maximizes the minimum outcome
for every alternative
◦ Equally Likely (Laplace Criterion) computes
the highest average outcome
◦ Criteria of Realism (Hurwicz Criterion)
uses the weighted average approach( personal
choice of alpha 0-1;alpha close to 1 ;optimistic
decision maker )
◦ Minimax Regret is based on opportunity
loss;it finds the alternative that minimizes the
maximum opportunity loss with in each
alternative
Decision Making Models Applied
Decision making models under uncertainty





Maximin
Maximin
Minimax Regret
Laplace
Hurwicz
Decision making models under Risk
EMV( Expected monetary value)
 EOL( Expected opportunity loss)
 Decision Tree
 Sensitivity Analysis
 Prospect Theory

Decision Model
OPTIONS
(Do Nothing)
WAPDA Supply for 4
1 hrs daily
SOLAR + WAPDA
2 (Partial)
3
4
UPS + WAPDA
Generator + WAPDA
Net Savings -5 yrs
(Revenue Gain - Elect. Cost
–
Revenue Losses)
Net Savings- 10 yrs
(Revenue Gain Elect. Cost –
Revenue Losses)
-26,536,636
-53,073,273
10,909,235
25,926,470
12,408,409
24,816,819
12,831,364
27,862,727
Decison making model under
uncertainity
Options
Regret Table
Minimax
Regret
Do Nothing 39,368,000 80,936,000 80,936,000
Solar +
WAPDA
1,922,129
1,936,57
1,922,129
UPS +
WAPDA
422,955
3,045,908
3,045,908
Generator
+ WAPDA
0
0
0
Decision making under uncertainty
Maximax
Maximin
Laplace
Max in a row`
Min in a row
Row Average
(Equally Likely)
hurwicz
Criterion of
Realism
Alpha
|
Minimax
Regret
0.4
Alpha(max) +
(1-alpha)(min)
- 26,536,636
25,926,470
24,816,819
27,862,727
-53,073,273
[(-26,536,636
-53,073,273)]/2
=- 39,804,954.5
10,909,235
[ (10,909,235+
25,926,470)]/2
= 18,417,852.5
12,408,409
12,831,364
[( 12,408,409+
24,816,819)]/2
=18,612,614
[(12,831,364+
27,862,727)]/2
= 20,347,045.5
- 42,458,618.2
39,368,000
80,936,000
16,916,19
1,922,129
1,936,57
17,371,773
422,955
3,045,908
18,843,909.2
0
0
Decision making model under Risk
EOL
5 Years
prob=0.5
EOL
10 Years
prob=0.5
EOL Value
39,368,000
80,936,000
19,684,004.47
1,922,129
1,936,57
1,057,893
422,955
0
3,045,908
0
1,734,431.5
0
EMV
- 39,804,618.2
18,417,852.5
18,612,614
18,843,909.2
Prospect Theory
OPTIONS
Net Savings -5 yrs
P1
X2
P2
V(F)=v(x1)w(
(Revenue Gain - Elect.
(Probabili (Outcome as (Probabili p1)+v(x2)w(p
Cost –
ty
loss-failure)
ty
2)
Revenue Losses)
weightage
weightage
X1 (Outcome as gainof X1)
of X2)
success)
SOLAR +
WAPDA
(Partial)
10,909,235
0.2
-22,500,000
0.8
3,780,641.369
UPS +
WAPDA
12,408,409
0.3
-22,500,000
0.7
3,174,388.785
Generato
r+
WAPDA
12,831,364
0.90
-22,500,000
0.1
-116,256.7974
Decision Tree
5 yrs
- 39,804,954.5
- 26,536,636
Do Nothing
10 Yrs
- 53,073,273
18,417,852.5
5 Yrs
Solar+WAPDA
10 Yrs
18,612,614
5 Yrs
10,909,235
,
25,926,470
12,408,409
UPS+WAPDA
10 Yrs
20,347,045.5
5 Yrs
Generator+ WAPDA
10 Yrs
24,816,819
,
12,831,364
27,862,727
Decision Making under
Uncertainty
Criterion
Choice
Alternative
Maximax
Generator plus WAPDA
Maximin
Generator plus WAPDA
Laplace
Generator plus WAPDA
(Equally Likely)
Hurwicz
Generator plus WAPDA
(Criteria of Realism)
Minimax(Regret)
Generator plus WAPDA
Decision Making under Risk
Criterion
Choice
Alternative
EMV
Generator plus WAPDA
EOL
Generator plus WAPDA
Sensitivity Analysis
Generator plus WAPDA
Decision Tree
Generator plus WAPDA
Prospect Theory
Generator plus WAPDA
Conclusion
Decision planning
 Making a decision without planning is fairly
common but does not often end well.
 Planning allows for decisions to be made
comfortably and in a smart way.
 Planning makes decision making a lot more
simple than it is.
 Decision will get four benefits out of planning:
1. It gives chance to the establishment of
independent goals. It is a conscious and directed
series of choices.
2. Provides a standard of measurement. It is a
measurement of whether you are going towards
or further away from your goal.
3. It converts values to action.
4. Allows for limited resources to be committed
in an orderly way. Always govern the use of what
is limited to you. (e.g. money, time, etc.)
Decision making
In the real world, most of our decisions are made
unconsciously in our mind.
 Decision-making models offer analytical tools
which can be combined to provide useful
insights.
 No perfect model as decision environments vary.
Therefore risk preference/profile and decision
environment may dictate choice of appropriate
model.

Decision planning must be done.
Cognitive Biases must be taken care off.
Objectives must first be established.
Objectives must be classified and placed
in order of importance.
 Alternative actions must be developed.










Alternative must be evaluated against all the
objectives.
Alternative that is able to achieve all the
objectives is the tentative decision.
Tentative decision be evaluated for more
possible consequences.
Decisive actions be taken and additional actions
must be
taken to prevent any adverse
consequences from becoming problems and
starting both systems (problem analysis and
decision making) all over again.
Selected Decision model steps be followed to
determine an optimal plan.
In a situation featuring conflict, role-playing is
helpful for predicting decisions to be made by
involved parties.

Cognitive and personal
decision making

Biases can creep into our decision making
processes.
Confirmation bias in psychology- (Scott Plous,
1993) – People tend to be willing to gather facts
that support certain conclusions but disregard
other facts that support different conclusions.
Premature
termination
of
search
for
evidence – People tend to accept the first
alternative that looks like it might work.
Cognitive inertia – Unwillingness to change
existing thought patterns in the face of new
circumstances.



biases
in
Selective perception – We actively screen-out
information that we do not think is important. (e g
prejudice.)
 Wishful Thinking – a tendency to want to see
things in a positive light, which can distort
perception and thinking.
 Choice Supportive Bias- occurs when people
distort their memories of chosen and rejected
options to make the chosen options seem more
attractive.
 Recency – People tend to place more attention on
more recent information and either ignore or
forget more distant information.
 Repetition bias – A willingness to believe what
one has been told most often and by the greatest
number of different sources.


Anchoring and adjustment – Decisions are
unduly influenced by initial information that
shapes our view of subsequent information

Group think – peer pressure to conform to the
opinions held by the group.

Source credibility bias – A tendency to reject a
person's statement on the basis of a bias against
the person, organization, or group to which the
person belongs. People preferentially accept
statement by others that they like .

Incremental decision making and escalating
commitment – We look at a decision as a small
step in a process and this tends to perpetuate a
series of similar decisions; can be contrasted
with zero-based decision makin.

Attribution asymmetry – People tend to
attribute their own success to internal factors,
including abilities and talents, but explain their
failures in terms of external factors such as bad
luck.

Role fulfillment – A tendency to conform to
others' decision-making expectations.

Illusion
of
control–People
tend
to
underestimate future uncertainty because of a
tendency to believe they have more control over
events than they really do.
Thank You