2
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Message from the Dean
Once more, the
students, faculty, and
Cluster Chair have
proven their capability
and commitment to
produce a series of
student papers that
reflect their applied
learning in quantitative
and operations
management issues.
Congratulations once again
to the Operations Cluster for
this back-to-back Techne 3
and Techne 4 publication.
Once more, the students, faculty, and Cluster
Chair have proven their capability and
commitment to produce a series of student
papers that reflect their applied learning in
quantitative and operations management issues.
The variety of topics in Techne 3 and 4 has again
demonstrated the usefulness and applicability of
topics in the Operations Management (Opeman)
cluster courses to any industry or any small,
medium, or large company/institution.
The inclusion of some green technology-related
topics is a welcome development because they
are very relevant to the University’s thrust on
environment and development, AGSB’s research agenda, and our Mulat Diwa’s Cura
Kalikasan project.
May the Operations Cluster, with its talented and committed faculty and leaders,
continue to lead in the publication of student papers. Please continue to teach and
inspire the students so they can learn more, do more, publish more, and do better.
Alberto L. Buenviaje
Dean
ATENEO STUDEN T BU S I NES S REVI EW
3
Message from the
Operations Cluster Head
Congratulations to the AGSB Operations Cluster
for coming up with the back-to-back issues,
Techne 3 and Techne 4. Also, a warm welcome to
our readers and friends to the 3rd and 4th editions
of our magazine!
These two issues were the output of 45 MBA
student-authors whose contributions focused
on the “Green” theme, which is aligned with our
school’s emphasis on nation-building.
As always, I convey
my heartfelt gratitude
to my colleagues in
the Operations Cluster
for their efforts to
encourage innovation,
and to continuously
motivate and guide our
MBA students.
As in the first two issues, we compiled our MBA
students’ projects in Applied Management
Science and Operations Management. The
potentials of the Applied Management Science
and Operations Management tools in improving
our workplaces and daily lives are limitless.
So in this issue, side-by-side articles on the power crisis in Mindanao and the waste
management system in the Payatas dumpsite, are equally interesting write-ups on
tikoy, shipping costs of computers to public schools, and even laundry concerns.
As always, I convey my heartfelt gratitude to my colleagues in the Operations Cluster
for their efforts to encourage innovation, and to continuously motivate and guide our
MBA students.
Thank you to all and happy reading!
Ralph Ante
Professor and Operations Cluster Chair
Ateneo Graduate School of Business
4
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Message from Editor
Techne is a magazine about numbers, making it distinct from other management publications. Additionally,
you will find this particular issue unique. Let me count the ways – by way of numbers, of course:
2
Means this is a double issue. The front cover is Techne 3. Flip the page around and, surprise,
the front cover becomes Techne 4.
2
The Operations Cluster manages a number of AGSB technically-oriented courses. Organized by the Cluster, this magazine focuses on two courses: Management Science and Operations Management.
2
The number of types of numbers presented: constants and variables. Of course, the variables are identified with the “let x =” expression.
3
Articles are trilingual. Although mostly in English, you will find a smattering of Greek letters such as mu, lambda, rho, sigma in a few places, plus a dash of Chinese.
13
The number of articles in this publication, sufficiently large to cover a wide range of technical applications for large corporations, government, schools, small and medium enterprises (SMEs), entrepreneurs, and for corporate social responsibility (CSR) initiatives. Ideas are aplenty: how to best move people and things from point A to point B, how to justify green initiatives, how to reduce time, and how to optimize resources. My personal favorite is the remarkable application of technical tools in the life of Carmina. Hopefully you will find at least one article that will match your interest.
25
The number of applications of mathematical tools (models, processes, concepts, formulas, diagrams, Excel templates) the students had to learn for the articles. Specifically, these consist of
six applications of Monte Carlo Simulation, five of Linear Programming, four of Linear Regression, three each of Queuing Models and Project Management, and one each of Inventory Management, Integer Programming, Process Improvement, and Quality Management.
45 The number of AGSB students who collaborated to write the articles. Many are engineers, accountants, and IT graduates, but you will be surprised to know how many lawyers, doctors, and politicians were involved as well.
510 Nanometers, the wavelength of visible green light in the color spectrum, right below the blue light. Management of the interaction and impact of humans on the environment is signified by green, the theme of Techne 3.
0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, …
Fibonacci sequence is an integer sequence where each subsequent number is the sum of the previous two. We do not have this yet in the current issue but with the way things are moving, you may be able to read about its application, perhaps in the field of decision theory, in a future Techne article.
Ed Legaspi
Editor
Techne: Managing through Numbers
Ateneo Graduate School of Business
ATENEO STUDEN T BU S I NES S REVI EW
5
:
o
a
n
a
d
in
M
in
is
is
r
C
Power
A Quantitative
Analysis of
Options and
Impacts
SURIGAO
DEL NORTE
CAMIGUINA
Dr. Jhanssen Castillo
Ma Katrina Mae Garcia-Dalusong
Rafi Delica
ZAMBOANGA
DEL NORTE
Atty. Anita C. Mapalo
ZAMBOANGA
DEL SUR
Irwin Tieng
Mary Ann M. Viloria
P
LANAO
DEL NORTE
C
H
H
H
AGUSAN
DEL SUR
H
D D
H
H
BUKIDNON
H
TAWI-TAWI
6
AT EN EO S T U D E NT B U SI NE SS R E V IE W
H
DAVAO
DEL NORTE
LANAO
DEL SUR
P
G
P
MAGUINDANAO
SULU
SURIGAO
DEL SUR
MISAMIS
ORIENTAL
MISAMIS
OCCIDENTAL
NORTH
COTABATO G
BASILAN
GUSAN
DEL NORTE
SULTAN
KUDARAT
SOUTH
COTABATO
D
DAVAO
DEL SUR
DAVAO
ORIENTAL
Introduction
B
rownouts in Mindanao
occurred more frequently
and lasted longer by midFebruary 2012. Not long after,
the power outage turned into
a crisis. Crisis of this kind is not the first
one that Mindanao has experienced. In
2010, almost during the same period,
Mindanao suffered from a debilitating
shortage of electricity that even
threatened to derail the automation of
elections that year on
the island. Officials in
charge of the control
The base load of the
power supply were
constrained to resort
region is no longer
to load shedding to
sustainable, considering meet demand and fill
the required level of
the many variables that reserves to maintain
the stability of the
affect water supply—
electricity grid.
from rainfall, natural
calamities, and even
seasonal variations such
as the El Niño
phenomenon, to the
depredations of man.
In both years, the
cause of the crises
is the reduced
dependability of
Mindanao’s powergenerating plants, the
biggest of which are
hydroelectric. The base
load of the region is
no longer sustainable,
considering the many
variables that affect
water supply—from rainfall, natural
calamities, and even seasonal variations
such as the El Niño phenomenon, to the
depredations of man.
Mindanao power plants are still owned
by the government through the National
Power Corporation (Napocor). The latter
is up for sale under the Electric Power
Industry Reform Act (EPIRA); however,
thus far, no significant takers have
expressed interest due to the staggering
debts incurred. Several projects have
already been approved and are awaiting
investment: 2 X 13.75 MW Bunker-fired
Power Plant; 15 MW Diesel Power Plant;
15 MW HFO Peaking Plant; 2 X 4 MW
Cabulig Mini-Hydroelectric Power Plant;
and the Southern Mindanao Coal-fired
Power Plant.
This paper examines the various sources
of power in Mindanao, their impact on
consumers in terms of the associated
generation, environmental, and health
costs, and the risks related to investing
in such alternative energy sources. The
ultimate goal is to identify a solution to
the Mindanao power crisis.
Forecasting: Linear Regression
Forecasting electricity consumption is
applied using several theoretical methods
including growth curves, multiple linear
regression methods that use economic,
social, geographic, and demographic
factors, and autoregressive integrated
moving average. The objective is to
forecast demand from 2015 to 2020 using
simple linear regression.
Different types of energy forecasts
exist due to the shifts in consumption
patterns that occur over time. Electricity
consumption varies according to the
season and the time of day. Energy
consumption varies from season to
season—more electricity is used on
special holidays and summer months
than during the rainy season when the
temperatures are usually moderate.
Residential energy consumption varies
from day to day—more electricity is
used on weekdays than on weekends.
Electricity consumption also varies from
ATENEO STUDEN T BU S I NES S REVI EW
7
hour to hour, as more electricity is used
during the morning hours, and then
electricity consumption declines during
the late morning and afternoon hours,
and increases again during the evening
hours.
Table 1 presents the maximum use of
electricity consumption data for 2001
to 2011 from the Department of Energy
(DOE). Electricity demand from 2012 to
2020 can be estimated using simple linear
regression.
Table 1. Electricity Demand (MW)
Maximum Use of
Electricity (Y)
Formula
Where
8
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Period (X1)
Year
954
1
2001
995
2
2002
1,131
3
2003
1,177
4
2004
1,149
5
2005
1,228
6
2006
1,241
7
2007
1,204
8
2008
1,303
9
2009
1,288
10
2010
1,346
11
2011
1,390
12
2012
1,425
13
2013
1,459
14
2014
1,494
15
2015
1,528
16
2016
1,563
17
2017
1,597
18
2018
1,632
19
2019
1,666
20
2020
Y=a+b(x1)
a
976.3272727
b
34.49090909
Summary Output
Regression Statistics
Multiple R
0.93556575
R Square
0.87528327
Adjusted R Square
0.86142586
Standard Error
45.5163862
Observations
Model is good
11
ANOVA
df
SS
MS
F
Significance F
Regression
1
130858.5091
130858.5091
63.16353
2.33E-05
Residual
9
18645.67273
2071.741414
Total
10
149504.1818
Coefficients
Standard
Error
t Statistics
P-Value
Lower 95%
Upper 95%
976.327273
29.43407195
33.16996964
1.01E-10
909.7427762
1042.742776
X Variable 1 34.4909091
4.339817145
7.947548925
2.33E-05
24.67356067
44.30825751
Intercept
t Statistics are good
Optimization: Linear
Programming
Linear programming is used to
determine the areas where electricity
would be optimally sourced while
taking into account generation charges,
environmental costs, and health costs.
Generation charges are indicated in the
monthly electric bills of consumers. The
charges pertain to the cost for the supply
of electricity that was transmitted to their
homes. Table 2 illustrates the generation
charges in pesos per MW per hour. The
data were derived from the 2011 postEPIRA rates provided by the DOE.
Table 2. Generation Charges per Type of
Plant (Php/MW-hr)
Type of Plant
Generation
Charges [GC(i)]
Oil
9,940
Geothermal
2,886
Hydroelectric
529
Solar
2,886
Coal
5,164
Biomass
5,500
ATENEO STUDEN T BU S I NES S REVI EW
9
The combustion of fossil fuels to generate
electricity is a known source for carbon
dioxide (CO2) emissions. This gas poses
environmental concerns, and this aspect
was considered in this study [(1)(2)(3)].
Table 3 illustrates the amount of carbon
dioxide (in kilograms) released per type
of plant. The basis for deriving the peso
equivalent was the widely used cost
estimate of a ton of CO2, which amounts
to $100 and is equivalent to Php4.3 per
kilogram per MW/hour.
Table 3. Environmental Costs per Type of Plant (Php/MW-hr)
Type of Plant
Kg of CO2 equivalent/MW-hr
Environmental Costs [EC(i)]
Oil
893
3,840
Geothermal
58
250
Hydroelectric
15
65
Solar
30
130
Coal
941
4,046
Biomass
893
3,840
Table 4. Health Costs of Mercuryand Cadmium per Type of Plant (P/MW-hr)
Type of Plant
Cadmium
Mercury
Health Costs [HC(i)]
13,003
2,766
15,769
Geothermal
100
0
100
Hydroelectric
91
0
91
Solar
100
0
100
Coal
18,748
18,748
37,496
0
2,766
2,766
Oil
Biomass
Cadmium and mercury emissions
from each plant were also determined
to obtain the health costs, which are
illustrated in Table 4. The peso equivalent
was determined based on the costs (in
pesos) for each of these elements, that is,
3,023 per mg of mercury and 307 per mg
of cadmium.
10
AT EN EO S T U D E NT B U SI NE SS R E V IE W
This paper covers two linear
programming formulations—in one
formulation, all costs are involved, and in
the other, generation charges are solely
considered. Table 5 summarizes Tables 2
to 4.
Table 5. Generation Charges, Environmental Costs, and Health Costs (P/MW-hr)
Generation Charges
[GC(i)]
Environmental Costs
[EC(i)]
Health Costs [HC(i)]
Oil
9,940
3,840
15,769
Geothermal
2,886
250
100
529
65
91
Solar
2,886
130
100
Coal
5,164
4,046
37,496
Biomass
5,500
3,840
2,766
Type of Plant
Hydroelectric
The variables and constraints used in
the study are defined in Tables 6 and 7.
Table 6. Variables
Table 7. Number of Plants per
Type of Source
Type of Plant
Number of Plants (k)
X(i,n)
Power plant n of type/category i
[DECISION VARIABLE]
Oil
14
Geothermal
1
C(i,n)
Capacity of each plant under
Category i (MW-hr/month)
Hydroelectric
12
Solar
1
GC(i)
Generation Charges
(Peso per MW-hr)
Coal
2
Biomass
1
EC(i)
Environmental Costs
(Peso per MW-hr)
HC(i)
Health Costs (Peso per MW-hr)
6
Generation Cost=
k
ΣΣ
X(i,n) * GC (i)
i=1 n=1
Environmental Cost=
6
k
X(i,n) * EC(i)
ΣΣ
i=1 n=1
Health Cost=
6
The constraints in the formulation are
limited to demands and capacity only.
Table 8 presents the constraints used for
demands from 2015 to 2020. The figures
for demand are derived from the linear
regression output with an allowance of an
additional 20 percent to serve as reserve
electricity.
Table 8. Peak Demand per Year
Limits (MW)
k
ΣΣ
X(i,n) * HC(i)
i=1 n=1
Total Cost= Generation Cost+Environmental
Cost+Health Cost, where k represents
the number of plants per category as
summarized in Table 7.
2015 demand
1,792
2016 demand
1,834
2017 demand
1,875
2018 demand
1,917
2019 demand
1,958
2020 demand
1,999
ATENEO STUDEN T BU S I NES S REVI EW
11
The limits on capacity are summarized in
Table 9, in which the power taken from
each plant must not be greater than its
dependable capacity, generally less than
installed capacity. The italicized plant
names are the proposals that have been
granted permit as of 2012. The rest are
existing power plants.
Table 9. A Summary of the Dependable Capacity of Each Power Plant (MW)
Installed
Capacity
Dependable
Capacity
Installed
Capacity
Dependable
Capacity
Mindanao Energy System 1
18.9
18.0
Mt. Apo
1037.0
827.0
Mindanao Energy System 2
27.5
27.0
Agus 1
80.0
52.0
Cotabato Light
10.0
9.9
Agus 2
180.0
135.0
Bajada DPP
58.7
48.0
Agus 4
158.1
156.0
SPPC
59.0
50.0
Agus 5
55.0
55.0
PB 104
32.0
16.0
Agus 6
200.0
155.0
TMI 2
100.0
100.0
Agus 7
54.0
27.0
TMI 1
100.0
100.0
Pulangi 4
255.0
200.0
WMPC
113.0
100.0
Sibulan Hydro
42.6
36.0
Iligan Diesel 1
62.7
56.4
Agusan
1.6
1.6
Iligan Diesel 2
40.0
36.0
Bubunawan
7.0
4.9
2 X 13.75 MW Bunker-fired
Power Plant
27.5
24.7
Talomo Hydro
4.5
4.5
15 MW Diesel Power Plant
15.0
13.5
2 X 4 MW Cabulig Mini
Hydro Power Plant
8.0
7.2
15 MW HFO Peaking Plant
15.0
13.5
Mindanao Coal
232.0
210.0
Crystal Sugar
21.0
7.0
200.0
180.0
Solar PV
1.0
1.0
Southern Mindanao
Coal-fired Power
Power Plant
12
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Power Plant
Risk Analysis:
Monte Carlo Simulation
The actual daily and monthly demand
fluctuates throughout the year.
Historically, the variation is at a certain
percentage of the peak value for the
year. Using the monthly peak and
monthly demand from 2001 to 2011 as
shown in Appendix A, a probability list
was created (Table 10).
Table 10. Cumulative Probabilities for
the Monthly Demand
Cumulative
Frequency
Monthly Demand
as Percentage of
the Year’s Peak (%)
0.000
78
0.015
80
0.023
82
0.030
84
0.030
86
0.114
88
0.212
90
0.348
92
0.545
94
0.705
96
0.841
98
1.000
100
The average utilization,
generation costs, and
selling prices were
calculated based on the
demand scenario.
The monthly demand for 2015 to 2020
was simulated using a uniform random
number generator in MS Excel and
the probabilities in Table 10. Based on
the linear programming results on the
prioritization of power plant to use, the
power demand in excess of the existing
capacity is distributed to the new
power plants. Applying the Monte Carlo
simulation, a total of 10,000 trials were
conducted for each year. The average
utilization, generation costs, and selling
prices were calculated based on the
demand scenario. The generation costs
used are the same as those discussed in
Table 2, whereas the selling prices are
shown in Table 11. A screenshot of the
Monte Carlo worksheet is presented
in Appendix B. The expected payback
period for the investment is also
calculated based on generation costs
and selling prices.
ATENEO STUDEN T BU S I NES S REVI EW
13
Table 11. Costs and Prices of Each Proposed Plant
Cost (P/MW-hr)
Selling Price
(P/MW-hr)
Investments
(in million pesos)
8 MW Cabulig Hydro
528
2,000
814
15 MW HFO Peaking
9,940
12,000
379
15 MW Diesel
9,940
12,000
550
13.75 MW Bunker
9,940
12,000
500
13.75 MW Bunker
9,940
12,000
500
Coal Plant
5,164
6,000
18,000
Proposed Plant
Results and Discussion
From the forecast results in Table 12,
demand will reach 1,666 MW in 2020
from 1,390 MW in 2012, indicating a
17% increase. Hence, the gap between
demand and capacity (1,280MW) is
expected to widen further.
Table 12. Electricity Demand (MW)
Max Use of
Electricity
Period
Year
1,390
12
2012
1,425
13
2013
1,459
14
2014
1,494
15
2015
1,528
16
2016
1,563
17
2017
1,597
18
2018
1,632
19
2019
1,666
20
2020
2005
2010
Period in Different Years
1,800
1,600
1,400
1,200
1,000
800
600
2000
Predicted
14
AT EN EO S T U D E NT B U SI NE SS R E V IE W
2015
Actual
2020
Separate linear programming
optimization outputs were derived for
each year, from 2012 to 2020. However,
only the outputs of 2015 and 2020 are
presented in Table 13.
Only five of 14 oil plants and no coal plant
are utilized; all other power plants are fully
utilized. Notably, the choice among the
diesel-powered plants is solely decided
by the computer. The demands from oilfueled plants can be transferred to other
Table 13. Power Plant Optimal Mix (MW)
Power Plant/Generation Company
Mindanao Energy System 1
Mindanao Energy System 2
Cotabato Light
Bajada DPP
SPPC
PB 104
TMI 2
TMI 1
WMPC
Iligan Diesel 1
Iligan Diesel 2
2 X 13.75 MW Bunker Fired Power Plant
15 MW Diesel Power Plant
15 MW HFO Peaking Plant
Mt. Apo
Agus 1
Agus 2
Agus 4
Agus 5
Agus 6
Agus 7
Pulangi 4
Sibulan Help
Agusan
Bubunawan
Talomo HEP
2 X 4 MW Cabulig Mini Hydro Power Plant
Solar PV
Mindanao Coal
Southern Mindanao Coal Fired Power
Crystal Sugar
For 2015, the total costs would amount
to Php7.0 million broken down into the
following: generation charges, Php4.1
million; environmental costs, Php0.8
million; and health costs, Php2.1 million.
Minimize
Generation
Cost Only
2015
2020
827
827
52
52
135
135
156
156
55
55
155
155
27
27
200
200
36
36
2
2
5
5
5
5
7
7
1
1
130
210
127
-
Minimize Overall Cost
(including health and
environment)
2015
2020
86
100
35
56
36
36
25
25
14
14
14
14
827
827
52
52
135
135
156
156
55
55
155
155
27
27
200
200
36
36
2
2
5
5
5
5
7
7
1
1
7
7
generators of the same type. Looking at
the case where we ignore the health and
environmental factors, the coal-powered
plants will be used instead of the oilpowered generators.
ATENEO STUDEN T BU S I NES S REVI EW
15
For 2020, the total costs would amount
to Php13.1 million broken down into the
following: generation charges, Php6.1
million; environmental costs, Php1.6
million; and health costs, Php5.4 million.
Only five of 14 oil plants and no coal plant
are utilized; all other power plants are
fully utilized. Similar to the case in 2015,
the coal-powered plants are utilized
instead of the oil-powered generators
when health and environment are not
considered.
Effect Generation cost (Php / Kw -hr)
Although coal may be the fourth most
affordable option for generation charges,
it yields the highest health cost. The
electricity source that would yield the
lowest cost to the consumer and the
3.5
3
2.5
2
1.5
1
2014
2015
2016
2017
Do Not consider H&E
Figure 1. Yearly Generation Cost (P/Kw-Hr)
16
AT EN EO S T U D E NT B U SI NE SS R E V IE W
environment would be hydroelectric,
followed by solar, geothermal, oil, and
coal. For the succeeding years (2015 to
2020), the effective generation costs
given the two options are calculated and
presented in Figure 1. The gap increases
with time because an increasing number
of oil-powered plants are used instead of
the cheaper coal. Hydro and geothermal
plants are always running at full capacity.
To the common Juan with a monthly
electrical energy consumption of 450 kwhr, demonstrating responsibility toward
the environment and fellow Filipinos
would amount to Php0.33/kw-hr in 2015
(or approximately Php150/month) and
increase to Php0.79/kw-hr in 2020.
2018
2019
Consider H&E
2020
2021
The yearly demand, revenue, and
gross margin were calculated based on
the Monte Carlo simulation of 1,000
trials (months). Table 14 illustrates an
example for 2015. For 2011, the cheapest
hydroelectric plant is only 65% utilized
for the year; the other plants have a
much lower utilization.
resulting utilization is summarized in
Figure 2. The coal-powered plant is no
longer included due to its high cost to
health and environment. Although the
utilization in 2015 is below 65% for hydro
and roughly 25% for oil-powered plants,
the scenario changes by 2020. In this
scenario, all the plants will run at their
full dependable capacity and with 100%
utilization.
The same calculations were implemented
for each year from 2015 to 2020. The
Table 14. Year 2015 Power Demand and Costs
Monthly Average
8MW Cabulig
Hydro
15MW HFO
Peaking
15MW Diesel
13.75 Bunker
13.75 Bunker
1378.6
Number of Times Demand Exceeds Existing Capacity
65%
65%
46%
46%
30%
30%
Average Monthly Power Taken from New Players (MW)
34.6
4.7
7.0
6.3
4.8
3.7
Energy for 1 year (MW-hr)
Cost per MW-hr
26812
39673
35621
27228
21021
PHP 528
PHP 9,940
PHP 9,940
PHP 9,940
PHP 9,940
Generation Cost (in Million)
PHP 14.2
PHP 20.9
PHP 18.8
PHP 14.4
PHP 11.1
Selling Price per MW-hr
PHP 2,000
PHP 12,000
PHP 12,000
PHP 12,000
PHP 12,000
Revenue (in Million)
PHP 53.62
PHP 476.08
PHP 427.45
PHP 326.73
PHP 252.15
Gross Margin (in Million)
PHP 39
PHP 455
PHP 409
PHP 312
PHP 241
Investment (in Million)
PHP 814
PHP 379
PHP 550
120%
100%
80%
60%
40%
20%
0%
2015
2016
2017
2018
8MW Cabulig Hydro
15MW HFO PeakingHydro
13.75 Bunker
13.75 Bunker
2019
2020
15MW Diesel
Figure 2. Utilization per Plant per Year
ATENEO STUDEN T BU S I NES S REVI EW
17
Having different utilization and different
capacities implies different revenues per
year. The gross margin per plant (gross
margin = selling price – generation cost)
is shown in Figure 3, along with the
investment for each plant. Although
the cost for hydroelectric power plant
is low, the low margin and capacity
of the hydro-plant cannot sell the
adequate required power to recover the
investment, which is the second highest
among the alternatives. The expected
payback period is a minimum of 12
years without even taking into account
the operating costs into the equation.
Conversely, the investment for oilpowered plants will be recovered quickly
due to the costly selling price despite the
high generation cost. In fact, the margin
per MW-hr of the oil-powered plant is
twice that of the hydroelectric power
plant. Recovery on investment will be
realized within a few months (operating
cost is excluded from the calculation).
Annual Gross Margin
5000
4000
3000
INVESTMENT
2000
2020
2019
1000
2018
2017
0
2016
-1000
2015
-2000
8MW
Cabulig
Hydro
15 MW HF0
Peaking
15MW
Diesel
Figure 3. Utilization per Plant per Year
18
AT EN EO S T U D E NT B U SI NE SS R E V IE W
13.75
Bunker
13.75
Bunker
Conclusion and
Recommendations
The peak power demand in Mindanao
is expected to increase to 1,666 MW
by 2020. This demand is to be met by
creating new power plants. The cheapest
overall cost would initially involve the use
of hydro and oil-powered plants before
using coal-fired plants. The direct impact
on the bill of the consumer of using this
human and environment-friendly power
mix is an increase in
generation cost by
P0.33/kw-hr in 2015. This
Given the overall
situation is the cost of
responsible citizenship
cost to consumers
in this aspect of power
and financial risk
distribution.
to investors, the
recommendation
is to fund the
Heavy Fuel Oil
(HFO) peaking
plant in Davao.
Based on the results of
risk analysis, an investor
seeking to earn profit
will need to invest in
oil-powered plants.
The government,
however, might still
support the funding for
the small hydroelectric
power plants as
its participation in
producing low-cost
clean energy. The results
imply that hydropower has the least
overall cost to consumers, but with a
payback period of 12.8 years to investors.
The coal-fired power plant is the most
expensive option, both to investors and
consumers, with a very long payback
period because it will be seldom utilized;
meanwhile, the oil-powered plant is in the
middle for both consumers and investors.
Given the overall cost to consumers
and financial risk to investors, the
recommendation is to fund the Heavy
Fuel Oil (HFO) peaking plant in Davao. In
consideration of environmental effects,
part of the profit can be used for ensuring
top-of-the-line solutions to minimize
harmful emissions and/or capture CO2.
The ethical framework affecting the
decision has likewise been considered.
Thus, the assessment provides social
benefits, minimizes social injuries, and
is consistent with the rights of those
affected. The action sought to be
advanced also exhibits concern for the
well-being of others.
The recommended action reflects
social responsibility to alleviate the
poor conditions of fellow Filipinos in
Mindanao. The avoidance of brownouts
and the lower cost of electricity are the
positive effects of the recommendation.
Moreover, environmental issues have
been considered and addressed.
References
1.
Climate Risks and Carbon Prices: Revising
the Social Cost of Carbon. Economics for
Equity and the Environment. [Online]
http://www.e3network.org/social_cost_
carbon.html.
2.
Environmental Impact of Electricity
Generation. [Online] http://en.wikipedia.
org/wiki/Environmental_impact_of_
electricity_generation.
3.
Full cost accounting for the life cycle of
coal. Epstein, Paul et al. 1, s.l. : Ann. N.Y.
Acad. Sci, 2011, Vol. 1219.
4.
http://www.manilatimes.net/index.php/
opinion/110-editorials/20581-napocorngcp-should-honestly-accept-blame.
[Online]
ATENEO STUDEN T BU S I NES S REVI EW
19
Appendix A. Monthly Demand Variation from 2001 to 2011 (Source: Department of Energy)
20
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Jan
887
911
946
1058
1082
1062
1108
1158
1143
1240
1250
Feb
900
913
918
1044
1082
1077
1141
1146
1163
1180
1231
Mar
903
900
978
1027
1082
1088
1177
1162
1158
1026
1219
Apr
887
927
985
1051
1087
1090
1167
1190
1186
1009
1253
May
901
920
1001
1099
1055
1118
1109
1159
1194
1211
1253
Jun
897
931
1021
1035
1072
1100
1145
1188
1220
1238
1264
Jul
894
924
976
1025
1045
1093
1141
1163
1198
1214
1298
Aug
926
941
980
1086
1061
1119
1141
1147
1208
1221
1290
Sep
947
927
995
11092
1078
1090
1203
1163
1217
1235
1288
Oct
954
950
1019
1134
1122
1130
1193
1156
1292
1263
1290
Nov
938
965
1051
1155
1149
1147
1158
1204
1303
1286
1326
Dec
933
995
1131
1177
1105
1228
1241
1175
1282
1288
1346
PEAK
954
995
1131
1177
1149
1228
1241
1204
1303
1288
1346
AT EN EO S T U D E NT B U SI NE SS R E V IE W
ATENEO STUDEN T BU S I NES S REVI EW
21
0.8976739
0.1572756
0.0647713
0.2725825
3
4
5
6
7
0.96
0.7264478
0.3504758
0.1196598
0.6373825
0.4956829
9
10
11
12
13
0.92
0.94
0.88
0.92
0.9
0.9
0.86
0.88
0.98
0.78
0.92
0.94
Percentage
of Peak
0.2530747
8
0.4353813
0.0043664
2
0.603397
RN Month
Demand
Power
Requirement
during
Reserve
Amount
Taken from
New Plants
1374.2
1404.1
1314.4
1374.2
1433.9
1344.3
1344.3
1284.6
1314.4
1463.8
1165.1
1374.2
1404.1
1672.9
1702.8
1613.2
1672.9
1732.7
1643.1
1643.1
1583.3
1613.2
1762.6
1463.8
1672.9
1702.8
10.9
40.8
0.0
10.9
70.7
0.0
0.0
0.0
0.0
100.6
0.0
10.9
40.8
7.20
7.20
0.00
7.20
7.20
0.00
0.00
0.00
0.00
7.20
0.00
7.20
7.20
8MW
Cabulig
Hydro
3.73
13.50
0.00
3.73
13.50
0.00
0.00
0.00
0.00
13.50
0.00
3.73
13.50
15MW HFO
Peaking
13.5
7.2
1
TRIALS
PHP 379
PHP 814
Investment
PHP 449
PHP 469.66
PHP 39
PHP 53.36
Revenue (in PHP M)
PHP 12,000
PHP 20.7
PHP 9,940
39138
6.9
6.9
46%
15MW HFO
Peaking
Gross Margin
PHP 14.1
PHP 2,000
Generation Cost (in PHP M)
Selling Price per MWk-hr
PHP 528
4.7
Cost per MW-hr
33.9
Average Monthly Power Taken from New Players (MW-hr)
4.7
26681
65%
Number of Times Demand Exceeds Existing Capacity
65%
8MW
Cabulig
Hydro
Energy for 1 Year (MW-hr)
1378.0
Monthly Average
Appendix B. Monte Carlo Worksheet
12.375
PHP 306
PHP 320.57
PHP 12,000
PHP 14.1
PHP 9,940
26715
4.7
4.7
29%
12.375
PHP 236
PHP 247.07
PHP 12,000
PHP 10.9
PHP 9,940
20589
3.6
3.6
29%
0.00
13.50
0.00
0.00
13.50
0.00
0.00
0.00
0.00
13.50
0.00
0.00
13.50
0.00
6.61
0.00
0.00
12.38
0.00
0.00
0.00
0.00
12.38
0.00
0.00
6.61
0.00
0.00
0.00
0.00
12.38
0.00
0.00
0.00
0.00
12.38
0.00
0.00
0.00
15MW Diesel 13.75 Bunker 13.75 Bunker
13.5
PHP 550
PHP 401
PHP 419.70
PHP 12,000
PHP 18.5
PHP 9,940
34975
6.1
6.1
46%
15MW Diesel 13.75 Bunker 13.75 Bunker
Payatas:
Maximizing the
Profits of Dump Site
Waste Pickers
Rosalie B. Formento
Gladys Olano
Zosimo Richard Carlos III
Margaret Samson
Jhie Camacho
Collection
of NonMarketable
Post
Consumer
Waste
Plastics
and Used
Cooking Oil
Shredding/
Grinding of
Styropor,
Plastic Bags
and
metalized
plastics/
Aluminum
foil packs
Densification/
Melting (up
to 200C) and
molding of
melted plastic
by casting
into the
metal moulds
Weighing,
Loading
and
Pre-heating
of cooking
oil, Feeding
of shredded
plastics
into the
Densifier
Finished
Sample
Products
22
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Introduction
T
he strategies for solving the
problem on solid waste in
Metro Manila and other urban
centers in the country have
been the subject of extensive
research and debate. However, the
problem persists and worsens every day.
Based on the studies conducted by the
National Solid Waste Management
Commission Secretariat of the
Environmental Management Bureau
(EMB), an average of 0.56 kg of waste
is produced per person living in the
metropolis per day. This finding implies
that with a population of 12 million,
total waste generated in Metro Manila
alone could run up to 6,720 metric tons
per day or 201,600 metric tons per
month. According to waste analysis and
characterization study conducted by the
DOST-ITDI, approximately 56% of this
waste is biodegradable and 44% is nonbiodegradable and mostly, recyclable.
At the rate we are producing waste,
finding ourselves in the midst of a large
number of man-made mountains of
garbage is highly probable. The tragedy
that has befallen the residents of the
Payatas dump site in Quezon City – in
Based on the studies conducted
by the National Solid Waste
Management Commission
Secretariat of the Environmental
Management Bureau (EMB), an
average of 0.56 kg of waste is
produced per person living in the
metropolis per day.
which it’s a mountain of garbage slid
down, in the process burying several
garbage pickers – should strengthen
our resolve to practice solid waste
management.
In reality, recycling and composting
account for only 720 tons per day, or
roughly 11% of solid waste generated in
Metro Manila due to non-segregation,
unavailable recycling technologies, and
lack of markets for recyclables.
Hence, the DOST has developed
technologies for solid waste
management, which are simple,
affordable, environmentally friendly, and
capable of generating livelihood. One of
these technologies is the DOST plastic
densifier, a plastic recycling technology
that converts waste styropor/plastics,
especially foamed Polystyrene and plastic
sando bags and laminates, into useful
products, such as tables, chairs, cat walk
tiles, plastic planters, pails, boards, bricks,
and synthetic timber plank. One unit of
the plastic densifier and other accessories
were donated by LGU Quezon City as
grant to provide a livelihood opportunity
for the the residents of Payatas, where
more than 2,000 scavengers work as
waste pickers of recyclable materials from
the dump site as an income-generating
activity.
Based on the Waste Analysis and
Characterization Study (WACS)
conducted by the DOST in 2009, an
average of 411 trips using 10-wheeler, sixwheeler, and mini-dump trucks are being
received by the Payatas controlled dump
site per day. The average total volume of
solid waste is approximately 5,800 m3 a
day or 1,200 tons a day. The classification
of wastes is presented in Table 1.
ATENEO STUDEN T BU S I NES S REVI EW
23
Table 1. Classification of Solid Waste
Classification
Particulars
Biodegradable
Fruit and vegetable peelings/scraps, bones, leftovers, grass, wood,
parts of plants and trees, tissue, dead animals, animal waste, manure,
and other biodegradable materials
Recyclable
Plastics
PET bottles, PVC pipes, shampoo bottles, PP white, PE white, PE black,
cups, blowing, and other recyclable plastics
Glass/Glass Bottles
Glass bottles, broken glasses, and other recyclable glass
Paper
White paper, newspaper, cartons, folders, cardboard, yellow paper, and
other recyclable paper
Metals
Aluminum, aluminum cans, tin cans, GI sheet/yero, brass, and other
recyclable metals
Residual
Styrofoam
Styrofoam
Sando Bags
Sando bags
Laminates
Candy wrappers, foil packs, sachets, pouches
Others
Rags, cloth, rubber slippers, foam, tires, shoes made of leather, leather
bags, and other residuals
Inert
Ceramics, unrecyclable glass, bricks, stones, pebbles, ash, dirt, broken
plates/bowls, and other inert
Special Wastes
Injections, tissue and cloth with blood, diapers, napkins, battery, paint,
fluorescent lamps, and other special wastes
Monte Carlo Simulation
From the given WACS data of actual
trips for nine days, the probability of
occurrence of trips was calculated based
on the frequency of occurrence in the
nine-day trip period. Each number of trips
for each source is assigned a probability
% of occurrence, and this factor was used
as reference on randomly picked number.
An average per day trip was derived
from the average of 100 randomly picked
numbers. The resulting average daily
trip is multiplied by 30 to arrive at the
monthly equivalent.
The WACS data yielded the daily average
ton of waste per trip. The total trip of
24
AT EN EO S T U D E NT B U SI NE SS R E V IE W
30 days was multiplied by the ton per
trip to generate the total tons for the
30-day period, which is then broken
down into how much of the waste was
biodegradable, plastic, glass, paper,
metal, inert, special waste, and residual.
The breakdown was also part of the
WACS data. Each source has a different
breakdown of waste; the data calculated
were based on per-source breakdown to
achieve more accuracy.
Tables 2 to 5 describe the process of using
the WACS trip data, converting these to
probability distribution, determining the
tons of waste at source using simulation,
and breaking these down by type of
waste.
Table 2. Actual Source Data from WACS
Number of Trips
Commercial
Hospital
Residential
Institution
Market
Day 1
27
2
364
10
23
Day 2
37
6
395
5
11
Day 3
33
1
381
2
14
Day 4
33
3
377
2
18
Day 5
33
4
384
5
13
Day 6
35
5
371
7
13
Day 7
25
3
167
-
11
Day 8
27
2
348
7
20
Day 9
36
6
377
3
9
Table 3. Probability Distribution from the Frequency of Occurrence
Commercial
No. of Trips
Occurence
Commercial
Lower Limit
Upper Limit
No. of Trips
Probability
11%
-
10%
25
25
1
11%
22%
11%
32%
27
27
2
22%
33%
33%
66%
33
33
3
33%
11%
67%
77%
35
35
1
11%
11%
78%
88%
36
36
1
11%
11%
89
99%
37
37
1
11%
Total
9
100%
No. of Trips
Occurence
Hospital
Hospital
Lower Limit
Upper Limit
No. of Trips
Probability
11%
-
10%
1
1
1
11%
22%
11%
32%
2
2
2
22%
22%
33%
55%
3
3
2
22%
11%
56%
66%
4
4
1
11%
11%
67%
77%
5
22%
78%
99%
6
Residential
Lower Limit
Upper Limit
No. of Trips
5
1
11%
6
2
22%
Total
9
100%
Residential
No. of Trips
Occurence
Probability
11%
-
0.10
167
167
1
11%
11%
0.11
0.21
348
348
1
11%
11%
0.22
0.32
364
364
1
11%
11%
0.33
0.43
371
371
1
11%
22%
0.44
0.66
377
377
2
22%
11%
0.67
0.77
381
381
1
11%
11%
0.78
0.88
384
384
1
11%
11%
0.89
0.99
395
395
1
11%
Total
9
100%
ATENEO STUDEN T BU S I NES S REVI EW
25
Institution
No. of Trips
Occurence
Institution
Lower Limit
Upper Limit
No. of Trips
Probability
11%
-
0.10
-
-
1
11%
22%
0.11
0.32
2
2
2
22%
11%
0.33
0.43
3
5
3
1
11%
22%
0.44
0.66
5
2
22%
22%
0.67
0.88
7
7
2
22%
11%
0.89
0.99
10
No. of Trips
10
1
11%
Total
9
100%
Market
Lower Limit
Upper Limit
No. of Trips
Occurence
Probability
11%
-
0.10
9
9
1
11%
22%
0.11
0.32
11
11
2
22%
22%
0.33
0.55
13
13
2
22%
11%
0.56
0.66
14
14
1
11%
11%
0.67
0.77
18
18
1
11%
11%
0.78
0.88
20
20
1
11%
11%
0.89
0.99
23
23
1
11%
Total
9
100%
Market
Table 4. Simulation for 100 Days
Commercial
Hospital
DAY
RNs
No. of Trips
DAY
RNs
No. of Trips
1
0.90
37
1
0.84
6
100
0.93
100
0.47
Average per Day
37
31
30 Days
944
4
30 Days
113
Residential
RNs
No. of Trips
DAY
RNs
No. of Trips
1
0.72
381
1
0.90
10
100
0.64
100
0.71
377
345
30 Days
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Institution
DAY
Average per Day
26
3
Average per Day
10,346
7
Average per Day
5
30 Days
143
Market
No. of Trips
DAY
RNs
No. of Trips
(Simulated Daily
Ave. x 30 days)
1
0.64
14
Commercial
100
0.79
20
Hospital
Average per Day
15
Residential
30 Days
441
Insitution
Market
Tons per Trip
(WACS)
Total Tons
944
3.24
3,053
113
2.80
317
10,346
2.83
29,288
143
2.880
399
441
2.70
1,189
Table 5. Breakdown of Types of Waste
Types of Waste
Commercial
Hospital
Residential
Institution
Market
Biodegradable
44%
52%
49%
52%
56%
Plastics
5%
4%
6%
4%
5%
Glass/Glass Bottles
2%
3%
2%
3%
1%
Paper
20%
14%
6%
14%
10%
Metal
1%
0%
1%
0%
1%
Inert
2%
1%
1%
1%
5%
Special Wastes
4%
3%
12%
3%
4%
Residual-Styrofoam
1%
2%
1%
2%
1%
Residual-Sando Bags
12%
14%
15%
14%
12%
Residual-Foil Packs
2%
1%
1%
1%
1%
Residual-Others
8%
6%
7%
6%
4%
In Tons
Commercial
Hospital
Residential
Institution
Market
Biodegradable
1,332
164
14,289
206
666
Plastics
147
14
1,721
18
62
Glass/Glass Bottles
59
9
686
11
13
Paper
607
43
1,753
54
114
Metal
27
1
282
2
10
Inert
68
4
148
4
61
Special Wastes
112
11
3,611
13
49
Residual-Styrofoam
25
6
183
8
9
Residual-Sando Bags
382
43
4,250
54
148
Residual-Foil Packs
46
4
392
5
8
Residual-Others
248
19
1,971
24
49
TOTAL
3,053
317
29,288
399
1,189
In Kg
Commercial
Hospital
Residential
Institution
Market
Biodegradable
1,332,364
163,625
14,289,346
205,614
665,805
Plastics
146,932
13,953
1,721,118
17,534
61,547
Glass/GlassBottles
58,954
8,636
686,121
10,852
12,813
Paper
607,379
43,181
1,753,098
54,261
113,599
Metal
27,210
1,322
282,007
1,661
10,296
Inert
67,722
3,534
148,272
4,441
61,318
Special Wastes
112,164
10,634
3,610,858
13,363
48,849
Residual-Styrofoam
25,093
6,208
183,159
7,801
9,152
Residual-Sando Bags
381,539
42,965
4,250,463
53,991
148,376
Residual-Foil Packs
45,954
4,210
392,485
5,291
8,466
Residual-Others
247,608
18,932
1,971,145
23,790
48,505
The composition of waste from different sources (in terms of weight) derived from the
Monte Carlo simulation and WACS data is presented in Table 6.
ATENEO STUDEN T BU S I NES S REVI EW
27
Table 6. Total Quantity for One Month
Total kg
% Composition
Residential
Market
Commercial
Institution
Total per Month
14,289,346
665,805
1,332,364
369,239
16,656,755
49%
Plastics
1,721,118
61,547
146,932
31,487
1,961,083
6%
Glass/Glass Bottles
686,121
12,813
58,954
19,488
777,377
2%
Paper
1,753,098
113,599
607,379
97,442
2,571,513
8%
Metal
282,007
10,296
27,210
2,982
322,495
1%
Biodegradable
Inert
148,272
61,318
67,722
7,976
285,287
1%
3,610,858
48,849
112,164
23,996
3,795,867
11%
Styrofoam
183,159
9,152
25,093
14,009
231,414
1%
Sando Bags
4,250,463
148,376
381,539
96,956
4,877,335
14%
392,485
8,466
45,954
9,501
456,406
1%
Special Wastes
Residuals:
Foil Packs
Others
TOTAL
1,971,145
48,505
247,608
42,722
2,309,980
7%
29,288,072
1,188,725
3,052,920
715,799
34,345,516
100%
Small junk shops in the Payatas area buy
recyclable materials [i.e., plastic bottles
(PET), glass/glass bottles, papers, and
metals] from waste pickers, which they in
turn sell to recycling facilities. However,
the recycling facilities do not accept
residual wastes (styropor, sando bags, and
laminates) that are wet and contaminated
with dirt and oil. These materials are
processed through the plastic densifier
that converts them into useful products.
Through this project, the residual wastes
are bought from scavengers for Php1 per
kg, thus augmenting the latter’s income.
Linear Programming
This study aims to determine how the
Payatas Controlled Disposal Facility can
maximize its profit using the styropor/
plastic densifier. As part of the agreement
with the DOST, the LGU Quezon City
has allocated a space with shelter for
the operation of the densifier. The DOST
trained at least three operators to run
28
AT EN EO S T U D E NT B U SI NE SS R E V IE W
the densifier. Other machineries, such as
grinder, molder, and other auxilliaries,
which are required by the densifier were
also donated by the DOST.
Through linear programming (LP), the
study aims to determine the optimum
output of the densifier to maximize
profits, and how much of each product
should be produced by the densifier.
The optimum outputs will help draw
recommendations to maximize the
benefit of the plastic densifier not only
to the LGU, but also to the residents of
Payatas.
Based on the results of the Monte Carlo
simulation through which the amount
of residual wastes brought to Payatas
dump site per month was simulated, the
assumption is that 60% of these residual
wastes can be processed in the plastic
densifier (Table 7). Another assumption
is that fuel/electricity, which comes from
the biogas generated from the disposal
facility, will remain free at Payatas.
Table 7. Potential Input to the Plastic Densifier
Total (in kg)
Residual Wastes for the Densifier
Total per Month
60% of Weight
Styrofoam
231,414
138,849
Sando Bags
4,877,335
2,926,401
Foil packs
456,406
273,843
The decision variables used for the
optimization model are as follows:
Ts = number of small tables to make per month
Tb = number of large tables to make per month
C = number of chairs to make per month
P = number of planters to make per month
Cw = number of catwalk tiles to make per month
The identified constraints are as follows:
Table 8. Resource Data
Material
Cost per Kg
Kg Available per Month
Waste styropor
1.00
138,849
Waste plastics/sando bags
1.00
2,926,401
Waste laminates
1.00
273,843
Used oil
18.00
2,400
Numerous establishments in Quezon
City, such as fast food chains and
restaurants, generate large volumes
of used cooking oil. However, other
backyard businesses buy this quantity
from these establishments. The backyard
businesses recycle and filter used cooking
oil, and then sell the filtered cooking oil
to street vendors or carinderias that use
the filtered oil for further cooking. Given
this competition, the Payatas group could
only source out 2,400 kg of used cooking
oil per month.
ATENEO STUDEN T BU S I NES S REVI EW
29
Table 9. Product Data
Product Data
Small Tables
Large Tables
Chairs
Planters
Catwalk Tiles
Monthly Minimum
32
16
40
76
200
Monthly Maximum
480
240
600
1140
3000
The monthly minimums are based on the
current quantities that the Payatas group
is making and are bought by the LGU for
its own use or for giveaways. The monthly
maximums are based on the maximum
capacity of the densifier using three
batches as determined through the PERT
analysis (Pls refer to the next case).
The material requirements and all
relevant costs for each potential
product that can be made from the
densifier are presented in Table 10.
Table 10. Material Requirements and Costs
Ratio
P/kg
Unit Weight (kg)
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Table
(Small)
Table
(Large)
Chairs
Planters
Catwalk
Tiles
6.0
12.0
4.5
2.5
1.0
Waste Styropor
0.5
1
3.0
6.0
2.25
1.25
0.5
Waste Laminates
0.13
1
0.75
1.5
0.56
0.31
0.13
Waste Plastic/
Sando Bags
0.13
1
0.75
1.5
0.56
0.31
0.13
Used Oil
0.25
18
1.5
3.0
1.13
0.63
0.25
6.0
12.0
4.5
2.5
1.0
Raw Material Cost,
Php/unit
31.50
63.00
23.60
13.10
5.30
Labor Cost, Php/unit
43.80
87.50
35.00
18.40
7.00
Other Material Cost,
Php/unit
100.00
150.00
120.00
Total Production Cost,
Php/unit
175.30
300.50
178.60
31.50
12.30
Selling Price, Php/unit
300.00
600.00
250.00
45.00
15.00
Profit, Php/unit
124.70
299.50
71.40
13.50
2.70
Total
30
Type of Product
Putting together all of the above, one
possible LP model is as follows:
Objective:
Maximize Profit = Selling price – total
production cost
Maximum Profit = 124.8Ts + 299.5Tb
+ 71.4C + 13.5P + 2.8Cw
Constraints:
a. Material Limitations (in kg)
3Ts + 6Tb + 2.25C + 1.25P + 0.50Cw <= 138,849 (waste styropor)
0.75Ts + 1.50Tb + 0.56C + 0.31P + 0.13Cw <= 2,926,401
(waste laminates)
0.75Ts + 1.50Tb + 0.56C + 0.31P + 0.13Cw <= 273,843 (waste plastic sando bags)
1.50Ts + 3.00Tb + 1.13C + 0.63P + 0.25Cw <= 2,400 (used cooking oil)
b. Minimum and Maximum Number of
Products to Make per month
32 <= Ts <= 480 (Small tables)
16 <= Tb <= 240 (Large tables)
40 <= C <= 600 (Chairs)
76 <= P <= 1,140 (Planters)
200 <= Cw <= 3,000 (Catwalk Tiles)
c. Non-negativity factors
This result implies that to maximize
profits in operating the plastic densifier,
the production of small tables, large
tables, and chairs should be maximized.
The production of catwalk tiles and
planters should be kept at the minimum
of 200 units and 368 units per month,
respectively.
The quantity of used cooking oil available
is binding, that is, the Payatas group
should source more used cooking oil from
other sources. An increase or decrease
of 1 kg of cooking oil would indicate an
increase or decrease in profit by Php21.40.
The quantities for large tables, small
tables, and chairs are also binding.
A decrease or increase in the unit of
large tables would imply a decrease or
increase in profit of Php235.21. Similarly,
a decrease or increase in the unit of
small tables would indicate a decrease or
increase of Php92.65 in profit. An increase
or decrease in the unit of chairs would also
imply an increase or decrease in profit by
Php47.18.
Moreover, an increase or decrease in
the unit of catwalk tiles would indicate a
decrease or increase in profit by Php2.56.
This premise suggests that the Payatas
group can opt not to produce catwalk tiles
at all due to the small profit that can be
generated from it.
Ts, Tb, C, P, Cw >= 0
Running Excel’s Solver, the optimal
production for the five products are as
follows: Small Tables = 480 units/month,
Large Tables = 240 units/month, Chairs
= 600 units/month, Planters = 368 units/
month, and Catwalk Chairs = 200 units/
month. The resulting optimal profit is
Php180,155/month.
The quantity of used cooking
oil available is binding, that
is, the Payatas group should
source more used cooking oil
from other sources.
ATENEO STUDEN T BU S I NES S REVI EW
31
PERT
Currently, the Payatas group operates
only one batch per day, with a daily
capacity of 50 kg. The group takes four
hours to complete the processing of one
batch. Given the lunch break, the Payatas
group opted not to process a second
batch due to time constraints. The group
performed a PERT analysis to determine
the optimum number of batches that can
be produced in one day.
Task Name
The current production schedule for a
day’s operation is shown in Figure 1. The
critical path (in red) takes a four-hour
operation. At least three people are
involved in the processing of the residual
wastes; thus, maximizing the capacity
of the plastic densifier may be achieved
by introducing a second and a third
production batch, as illustrated in Figure 2.
Duration
Start
Finish
Predecessors
1
Start
0 mins
8:00 AM
8:00 AM
2
Shredding
30 mins
8:00 AM
8:30 AM
1
3
Weighing
15 mins
8:30 AM
8:45 AM
2
4
Melting
90 mins
8:45 AM
10:15 AM
3,5
5
Pre-heating of oil
30 mins
8:00 AM
8:30 AM
1
6
Filling
30 mins
10:15 AM
10:45 AM
4
7
Curing
60 mins
10:45 AM
11:45 AM
6
8
Removing from Molders
15 mins
11:45 AM
12:00 PM
7
Finish
Finish
u
Start
u
Shredding
30
u
Removing
from molders
Weighing
15
15
u
u
u
Pre-heating
of oil
30
u
Melting
90
u
Filing
30
u
Curing
60
Figure 1. Network Diagram for the Operation of One Batch per Day
32
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Task Name
Duration
Start
Finish
8:00 AM
Predecessors
1
Start
0 mins
8:00 AM
2
Shredding 1
30 mins
8:00 AM
8:30 AM
1
3
Weighing 1
15 mins
8:30 AM
8:45 AM
2
4
Melting 1
90 mins
8:45 AM
10:15 AM
3,5
5
Pre-heating of oil 1
30 mins
8:00 AM
8:30 AM
1
6
Filling 1
30 mins
10:15 AM
10:45 AM
4
7
Curing 1
60 mins
10:45 AM
11:45 AM
6
8
Removing from Molders 1
15 mins
11:45 AM
12:00 PM
7
9
Shredding 2
30 mins
8:30 AM
9:00 AM
2
10
Weighing 2
15 mins
9:00 AM
9:15 AM
3,9
11
Pre-heating of oil 2
20 mins
10:45 AM
11:05 AM
6
12
Melting 2
90 mins
11:05 AM
12:35 PM
11,10
13
Filling 2
30 mins
12:35 PM
1:05 PM
12
14
Curing 2
60 mins
1:05 PM
2:05 PM
13
15
Removing from Molders 2
15 mins
2:05 PM
2:20 PM
14
16
Shredding 3
30 mins
9:00 AM
9:30 AM
9
17
Weighing 3
15 mins
9:30 AM
9:45 AM
10, 16
18
Pre-heating of oil 3
20 mins
1:05 PM
1:25 PM
13
19
Melting 3
90 mins
1:25 PM
2:55 PM
17, 18
20
Filling 3
30 mins
2:55 PM
3:25 PM
19
21
Curing 3
60 mins
3:25 PM
4:25 PM
20
22
Removing from molders 3
15 mins
4:25 PM
4:40 PM
21
Finish
u
W1
W2
15 u 15
M2 u F2
90
30
u
u
u
St
S1
art u 30
u
u
W3
15
u
M3
90
u
F3
30
u
C3
60
u
u
u
M1
F1
90 u 30
C1
u 60
u
R1
15
u
O1
30
S3
30
O3
20
u
u
u
u
S2
30
C2 u R2 u Fin2
60
15
u Fin1
R3
15
u
u
O2
20
Fin3
1 = 1st batch
2 = 2nd batch
3 = 3rd batch
S = Shredding
O = Oil preheating
W = Weighing
M = Melting
F = Filling
C = Curing
R = Removal from Molds
Fin = Finish
Figure 2. Network Diagram for the Operation of Three Batches per Day
ATENEO STUDEN T BU S I NES S REVI EW
33
As depicted in the foregoing figure,
several processes can be conducted
simultaneously, and preheating for the
second and third batches of oil can be
crashed to 20 min from the original 30
min because the densifier is already hot
on the second and third batches. If the
production starts at exactly 8:00 am, all
three batches can be finished at 4:40 pm.
This process can be crashed further by 15
min on the next day if the shredding and
weighing of the first batch were done on
the previous day. Therefore, if production
starts at 8:00 am, all three batches can be
completed by 4:25 pm the next day.
Conclusion/Recommendations
The quantity of tables and chairs
produced are binding due to the low
capacity of the plastic densifier. The
Payatas group can opt to add more units
of plastic densifier to accommodate
the allowable increase in the volume of
tables and chairs, thereby increasing
profits. However, more used cooking
oil should be available as well. The
sourcing of used cooking oil by the
Payatas group is one of the problems
encountered due to competition with
other businesses; hence, the LGU Quezon
City in collaboration with the Department
of Health should create an ordinance
that prohibits business establishments
that generate used cooking oil from
The LGU may create
an ordinance requiring
government offices to
patronize recycled products to
promote environment-friendly
or so-called “green” products.
34
AT EN EO S T U D E NT B U SI NE SS R E V IE W
selling their used cooking oil to people
who recycle it for further cooking as this
procedure would cause health risks to
consumers.
The Payatas group should operate
for three batches a day to maximize
the usage of the plastic densifier. This
approach will also optimize profits for the
Payatas group.
The LGU Quezon City could help in the
marketing of the products by encouraging
green consumerism in the city. The
LGU may create an ordinance requiring
government offices to patronize recycled
products to promote environmentfriendly or so-called “green” products.
Product development could also be
done in which these products could be
laminated or covered (as in office cubicle
tables) to enhance product value.
Assuming that market demand for the
product is twice the maximum volume
that can be produced by one densifier and
the availability of used cooking oil is not
limited, then an additional unit of plastic
densifier would produce an optimal profit
of Php180,155.
The investment of Php150,000 for an
additional unit of densifier could be
recovered in a month. However, an
additional densifier would also need
additional auxiliary equipment such as
molders. Each set of molders would cost
Php50,000 to Php80,000 depending on
the type of product. Large tables would
require four sets of molders, whereas
small tables would require eight sets.
Assuming that a bigger quantity of the
large tables are to be produced, four
sets of molders would cost Php240,000.
Considering that the shredder is
undercapacity and can still accommodate
twice the quantity of raw materials
required, acquiring an additional shredder
is unnecessary. The total additional
investment for a densifier and the molders
would be Php390,000. The payback period
is 2.16 months (Php390,000/Php180,155),
assuming that the densifier is used solely
for the large tables, which would produce
additional 240 units per month.
Another LP formulation can be done to
calculate optimal profit if data will be
amended (e.g., increase in the quantity of
used cooking oil available).
References
Casabar, C., et al., 2009. “Waste Analysis
Characterization Study in Payatas Controlled
Dump Site.” A Project of the Department of
Science and Technology in collaboration with
the Payatas Operations Group.
ATENEO STUDEN T BU S I NES S REVI EW
35
Ateneo CCE:
Establishing a
Green & Sustainability
Course Program
Atty. Anton Carlo E. Espino
Edwin J. Falcotelo
Evangeline P. Y. Ho
Deanna Marie A. Lansagan
Arleen M. Pacheco
Mayelle C. Wycoco
DISCLAIMER:
and number of course runs of some of the financial management trianing programme presented in this paper do not represent the actual course runs of the center.
36 Dates
Green
finance
yet offered by the center.
AT EN EO
S T U D training
E NT B U SIcourse
NE SS RisE not
V IE W
Introduction
T
he Center for Continuing
Education (CCE) is Ateneo’s
dynamic link to the world of
business, finance, and technology.
It also addresses issue-specific
industry concerns that require immediate,
purposeful, and focused responses.
Ateneo CCE continuously serves the
development needs of people and
organizations from the private and
public sectors, dutifully reflects the
breadth and depth of the Ateneo
Graduate School of Business vision and
mission, and consistently champions the
Ateneo de Manila University’s ideals of
Excellence, Service, and Ethics.
Ateneo CCE is a training provider with the
following core characteristics:
1.
Workplace-based courses with
immediate take-away value
Ateneo CCE courses are immersed
in the workplace. Participants are
equipped with competencies and values based on the current realities of their respective organizations.
2. Interplay of workplace and
classroom dynamics
Ateneo CCE classrooms are
microcosms of the workplace; the workplace is a classroom of
practical learning. The interplay of workplace and classroom dynamics provides immense opportunities for learning, collaboration, and
innovation.
3. Industry specialists as resource persons
Programs and courses are designed, developed, and delivered by
industry practitioners who are
renowned experts in their respective fields.
4. Practical, experiential, and highly
interactive
Methodologies are based on
business simulations, practical exercises, case analyses, practical applications, and focused discussions.
5. Integration of ethics, information management, and research
Business decision process
considers ethics; Information
Management is applied on content
and delivery; and Research renders courses relevant to specific
industries.
6. Synergy with the academe and
industry
The unique pool of expertise and experience from the academe and from the roster of seasoned
industry professionals enriches the
courses. Successful participants
earn units toward a graduate
degree. Their competencies are
certified by Ateneo CCE and
distinguished industry partners.
As part of the Ateneo, CCE maintains the university’s tradition of excellence that is exemplified in the following dimensions:
Programs and courses are designed, developed, and delivered
by industry practitioners who are renowned experts in their
respective fields.
ATENEO STUDEN T BU S I NES S REVI EW
37
1. Emphasis on the basics
Basic skills that endure time, as well
as fundamental competencies that
form the foundation of sound
management education enable
leaders to cope with rapid changes
in the environment.
2. Premium on critical thinking
The hallmark of Jesuit education, which Ateneo CCE embodies, is a mindset that constantly questions
rather than simply accepts, and analyzes causes and effects before formulating strategies, thereby
making the practice of management
a dynamic exercise.
3. Drive for excellence
The Jesuit “Magis” is the driving
force behind an individual’s efforts to give his best, always do better
each time, and avoid complacency and mediocrity with fierce
determination.
4. Commitment to serve
Education is not merely for an
individual’s sole benefit, but also
for the service of others. This
powerful paradigm inspires Ateneo
CCE to get things done the Ateneo
way and to do so for the greater
glory of God, Ad majorem Dei
gloriam.
Ateneo CCE’s program classifications
are diploma, certification, and business
excellence. Ateneo CCE further
customizes training programs based on
distinct client needs.
CERTIFICATION
The Ateneo CCE, the country’s premier institution for professional training,
maintains and strengthens its market position through internationally recognized
certification programs.
DIPLOMA
The Ateneo CCE’s unique and competitive advantage is the expertise in
customizing courses to effectively address the needs of specific disciplines and
industries.
Business Excellence
The Ateneo CCE systematically enhances the quality and productivity of
professionals through continuously evolving, workplace-based, and performancedriven education programs, namely:
• Marketing and Sales Management
• Human Resources Management
• Financial Management
• Entrepreneurship
• Technology, Quality, and Operations Management
• Leadership and Management
• Lifelong Learning
38
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Certification
Diploma
Marketing and sales
Management
Human Resource Management
Financial Management
Entrepreneurship
Technology, Quality and
Operations Management
Leadership and Management
Lifelong Learning
Linear Programming
in demand) courses under the Financial
Management classification. The process
presented here is repeatable across all the
other courses of the CCE.
The data show the courses and the
number of participants per run. The
course fees, despite inflation, remained
unchanged. The gross revenue was
obtained from the number of participants.
The Center offers an Early Eagle Rate,
which is 10% off the published or regular
rate.
The application of LP to Ateneo CCE
starts with the decision variables. The
six Financial Management courses are
represented by the following variables:
X1 = ANA I, X2 = ANA II, X3 = AMDM, X4 =
TFA, X5 = CA, and X6 = Finance 101. The
variables represent the number of times
each course will be offered in a year.
The objective is to maximize profits for
the six financial management courses.
An example of the template used for
the computation of profit for each of
the financial management courses is
presented in Table 1. The assumption is
that total number of students per class is
25, with the Early Eagle Rate applied to 15
of them.
Linear programming (LP) could be a useful
tool for planning the courses Ateneo CCE
would offer. To illustrate this premise, the
LP application is focused on the Financial
Management courses currently offered
but classified under Business Excellence
category, specifically, Accounting for
Non-Accountants I (ANA I), Accounting for
Non-Accountants II (ANA II), Accounting
for Management Decision Making
(AMDM), Techniques of Financial Analysis
(TFA), Credit Analysis (CA), and Finance
101. The six courses were chosen as these
are the Center’s top-selling (i.e., most
ATENEO STUDEN T BU S I NES S REVI EW
39
Table 1. Example of a Course Profit
Template
Course Title
Number of Days
ANA I
3
Number of Students
25
Course Fee
PhP
Early Eagle Rate (60%)
14,580
15
218,700
Regular Rate (40%)
16,200
10
162,000
25
380,700
Total Revenue
RP Fee
24,000
Marketing
Room
10,000
30,000
Equipment
400
9,600
Food Service
600
45,000
Training Kits
800
20,000
Overhead
196,600
40,000
Total Expenses
316,600
Profit
64,100
ANA I
3.0 days
ANA II
2.0 days
AMDM
3.0 days
TFA
3.5 days
CA
3.5 days
Finance 101
3.5 days
2. Maximum Demand
Based on the historical data, the
demand at 25 students for each course run for Financial Manage-
ment courses is shown in Table 3.
Therefore, ×1<= 12, ×2<= 8, ×3<=
7, ×4<= 9, ×5<= 5, ×6<= 3
Table 3. Maximum Demand for Each
Course
The objective function can be stated as
follows:
Course
Runs/Year
ANA I
12 times
Maximize Profit = 64,100×1 + 29,400×2
+ 64,100×3 + 224,800×4 + 224,800×5 +
224,800×6
ANA II
8 times
AMDM
7 times
TFA
9 times
The aforementioned objective is
influenced by the following constraints:
CA
5 times
Finance 101
3 times
Therefore, 3×1+ 2×2 + 3×3 + 3.5×4 +
3.5×5 + 3.5×6 <= 90 days
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Duration
120,000
1. Days Allocated
Each of the six financial management courses lasts for the duration
listed in Table 2. Moreover, the
Center’s Management allocated 90
days for Financial Management
courses in a year’s time.
40
Course
72,000
20,000
Total Direct Expenses
Table 2. Duration per Course
3. Minimum Demand
The Financial Management courses
are part of the Center’s core
training programs. Thus, running the
said courses at least once a year
constitutes the Center’s policy.
Therefore, ×1 >= 1, ×2 >= 1, ×3 >=
1, ×4 >= 1, ×5 >= 1, ×6 >= 1
The optimal solution generated by Solver
(LP’s optimizer in Excel) is presented in
Table 4. To maximize profit, Ateneo CCE
should offer nine runs of ANA I, one run
of ANA II, one run of AMDM, nine runs
of TFA, five runs of CA, and three runs of
Finance 101 in one year. Implementing
the optimal solution will enable Ateneo
CCE to generate profits totaling
PhP4,455,350 every year on only these six
courses. Furthermore, Solver indicates
that each increase in runs for TFA, CA, or
Finance 101 will further improve profits by
PhP150,000. Conversely, each reduction
in runs of any of these three courses
will correspondingly reduce profits by
PhP150,000.
of the LP model should generate new
optimal course mixes that can guide the
decision process.
Green Finance Course
As part of its business commitment
to promote Green and Sustainability
awareness, Ateneo de Manila University
hosted a management and research
conference in 2012 titled, “The Nature
of Business: Green Innovations and
Competitive Advantage,” to shed light
on several complex issues on green
innovations facing business.
Table 4. Solver’s Optimal Solution
ANA I
ANA II
AMDM
TFA
CA
FINANCE 101
9
1
1
9
5
3
64,100.00
24,800.00
64,100.00
224,800.00
224,800.0
224,800.00
4,455,350.00
Days Alloted
3
2
3
3.5
3.5
3.5
90
<=
90
Demand ANA I
1
9
<=
12
1
<=
8
Objective Function (Max P)
Constraints
Demand ANA II
1
Demand AMDM
1
Demand TFA
1
Demand CA
1
Demand FINANCE 101
Min ANA I
1
1
Min ANA II
1
Min AMDM
1
Min TFA
1
Min CA
1
Min FINANCE 101
Ateneo CCE must regularly offer the
Financial Management courses as the
demand increases. Despite the small
class size in some courses, Ateneo CCE
should perhaps consider the participants
who register for the class and build on the
value of the client, not solely on profit. In
such instances, revising the parameters
1
1
<=
7
9
<=
9
5
<=
5
3
<=
3
9
>=
1
1
>=
1
1
>=
1
9
>=
1
5
>=
1
3
>=
1
Establishing the first Green and
Sustainability course program at Ateneo
CCE is an appropriate – and timely –
response to the rising demand for green
initiatives. This program is designed
to cater to employees in businesses
adopting sustainable practices, as well
as government agencies and NGOs.
ATENEO STUDEN T BU S I NES S REVI EW
41
In addition, the program is a strategic
means of contributing to nation building
while earning profit for the CCE.
The possible green and sustainability
courses that can be offered to the public
are as follows:
1. Green Finance
2. Green Building/Systems/Materials
3. Green Certifications and Standards
4. Green Cleaning Practices and
Food Service
5. Green Supply Chain Management
6. Renewable Energy
7. Social Responsibility
8. Sustainability Planning
9. Transportation Program/Green
Fleet Management
10. Waste Management
11. Water Resource Conservation
and Management
Following the results of the LP
sample case on Finance previously
discussed, Ateneo CCE should develop
Green Finance as its first Green and
Sustainability course offering.
Green Finance (or Environmental Finance)
is a course designed to educate people
about Environmental Management
System (EMS). It is focused on the
elements of environmental accounting,
the associated eco-efficiency metrics, and
the financial elements of sustainability
planning.
With Green Finance, opportunities
can be identified and action taken by
implementing environmental/ carbon
accounting as part of a sustainability
plan. Plans should prioritize actions
based on the return on investment, as
well as meet energy, water, and wastereduction targets. An organization’s plan
to cut emissions may include making
infrastructure improvements, reducing
42
AT EN EO S T U D E NT B U SI NE SS R E V IE W
fossil fuel use, and implementing better
maintenance practices. This plan can
also be incorporated into procurement
programs to help improve the supply
chain of products used. Renewable
energy systems and energy conservation
programs are other initiatives that are
included in environmental/carbon Finance
plans.
With a budget of PhP130,000, Ateneo
CCE will roll out the Green Finance course
program by August 5-6, 2013. However,
CCE intends to advance the roll-out to July
15-16, which is 15 working days sooner.
The CCE goal is to meet the new roll-out
date with the least possible cost increase.
This goal may be achieved using the
program evaluation and review technique
(PERT).
PERT
PERT was used to determine the
estimated duration time of each activity
and the likelihood (probability) that the
project could be finished on or ahead of
time. The project tasks and dependencies
are listed in Table 5. The expected time
per task is shown in Table 6. The PERT
diagram is illustrated in Figure 1. The
Critical Path is identified in Table 7 as path
ABDEGHIJKMN.
Tables 8 and 9 demonstrate that the
expected completion time of the project
is 62 working days, and less than 1.8%
chance that the project can be finished
within 49 days is noted. The variance (σ2)
is dominated by activities K and L, having
values of 25 and 30.25, respectively.
This variance reduces the probability
of completing the project more quickly
because variance is the divisor to compute
for the level z. To increase the chances
of completing the project more quickly,
the gap in both activities K and L must be
narrowed by streamlining the process,
thereby increasing efficiency. The other
approach to reduce project time is by
allocating manpower and resources,
which will result to crashing.
Table 10 shows the crashing information,
and Table 11 details the crashing process.
Crashing the project by 15 days will incur
an additional cost of PhP16,300, and will
exceed the original budget of PhP130,000
by PhP34,450.
Table 5. Work Breakdown and Sequence of Activities
Task Name
Activity
Predecessor
Assess the Needs
A
-
Source the Subject Matter Expert (SME)
B
A
Select the Training Method
C
B
Design the Course
D
B
Develop the Course Content
E
D
Source the Resource Person (Instructor)
F
C
Prepare the Training Materials
G
E, F
Conduct a Pilot Test: Info Session
H
G
Evaluate, Revise, and Finalize the Course
I
H
Set the Training Date (and Conduct Product Orientation)
J
I
Promote the Program Course
K
J
Activate the Sales Operation
L
J
Handle Last-minute Details (Go or No Go?/Room and Food Reservation)
M
K, L
Conduct the Training
N
M
Table 6. Using Historical Data to Compute Expected Time and Variance (In Days)
Activity
Optimistic
Most Likely
Pessimistic
Expected Time (t)
Variance (σ2 )
A
B
0.5
1.5
1.0
2.0
2.0
1.42
0.06
3.0
2.00
0.11
C
0.5
1.0
2.0
1.08
0.06
D
1.0
2.0
5.0
2.33
0.44
E
8.0
15.0
22.0
15.00
5.44
F
1.5
3.0
4.0
2.92
0.17
G
1.0
2.0
6.0
2.50
0.69
H
1.0
1.0
1.0
1.00
0.00
I
2.0
3.0
5.0
3.17
0.25
J
0.5
1.0
2.0
1.08
0.06
K
15.0
30.0
45.0
30.00
25.00
L
12.0
27.0
45.0
27.50
30.25
M
0.5
1.5
2.0
1.42
0.06
N
2.0
2.0
2.0
2.00
0.00
ATENEO STUDEN T BU S I NES S REVI EW
43
g F
C
g
H g
G g
g E
g
g
g
J
g
g
D
I
g
g A g B
g
Start
K
M
L
g N g Finish
g
Figure 1. Network Diagram
Table 7. Critical Path
Path
Duration (Working Days)
ABCFGHIJKMN
48.58
ABCFGHIJLMN
46.08
ABDEGHIJKMN
61.92
ABDEGHIJLMN
59.42
Table 8. Expected Time of the Critical Path (In Days)
Critical Path
Expected Time (t)
Sum of Variance (σ2)
Standard Deviation (σ)
ABDEGHIJKMN
61.92
32.13
5.67
Table 9. Probability that the Project will be Finished in X Days
X days
z
F (z)
% Probability, z < F(z)
60
-0.34
0.6331
36.69
55
-1.22
0.8888
11.12
50
-2.10
0.9821
1.79
45
-2.98
0.9986
0.14
Table 10. Duration and Costs of Project Task
Task Name
44
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Task
Duration
(Days)
Normal Cost
(PhP)
Crashed
Time (Days)
Crashing Cost
(PhP/Day)
Assess the Needs
A
1.5
750
0.5
400
Source the SME
B
2.0
1,000
0.5
400
Select the Training Method
C
1.0
500
0.5
400
Design the Course
D
2.5
5,000
1.0
1,000
Develop the Course Content*
E
15.0
36,000
6.0
1,500
Source the Resource Person (Instructor)
F
3.0
1,500
2.0
500
Prepare the Training Materials
G
2.5
2,250
1.0
800
Conduct a Pilot Test
H
1.0
8,000
0.0
0
Evaluate, Revise, and Finalize the Course
I
3.5
7,000
1.0
1,000
Set the Training Date (and Product Orientation)
J
1.0
2,000
0.0
0
Promote the Program Course
K
30.0
20,000
5.0
1,400
Activate the Sales Operation
L
27.5
10,000
5.0
800
Handle Last-minute Details (Go or No Go?/
Room and Food Reservation)
M
1.5
750
1.0
600
Conduct the Training
N
2.0
53,400
0.0
0
Table 11. Crashing Process
Normal
Completion
Paths
Crash A Crash B Crash M
1
1.5
.5
Crash
G 1.5
Crash D
1.5
Crash I
2.5
Crash K Crash E
2.5
4
ABCFGHIJKMN
49.0
48.0
46.5
46.0
44.5
44.5
42.0
39.5
39.5
ABCFGHIJLMN
46.5
45.5
44.0
43.5
42.0
42.0
39.5
39.5
39.5
ABDEGHIJKMN
62.5
61.5
60.0
59.5
58.0
56.5
54.0
51.5
47.5
ABDEGHIJLMN
60.0
59.0
57.5
57.0
55.5
54.0
51.5
51.5
47.5
Completion Cost
148,150
148,150
148,550
149,150
Additional Cost
0
400
600
600
148,150
148,550
149,150
149,750
Total
Monte Carlo Simulation
In the present case, determining the
risks associated with the development
of a new training program (i.e., Green
Finance) for Ateneo CCE is essential.
The best means to attain this aim is
through simulation, particularly, the
Monte Carlo simulation. Considering
that Green Finance is a new training
program, historical data that can be used
for simulation are unavailable. Thus,
the next best approach is to look into
the historical data of another training
program similar to Green Finance. In
this particular case, the historical data
of Techniques in Financial Analysis
(TFA) were chosen to simulate the risks
involved in developing the Green Finance
training program.
149,750 150,950 152,450 154,950 158,450
1,200
1,500
2,500
3,500
6,000
150,950 152,450 154,950 158,450 164,450
worthwhile is critically important. The key
questions that need to be answered are
as follows:
1. Will Ateneo CCE be able to recoup
its investment in creating the Green
Finance training program? If so,
how long will it take Ateneo CCE to
recoup the investment?
2. What is the probability that CCE will
not generate any profit?
The cost of creating this program is
PhP148,150; the cost could possibly
increase to PhP164,450 if the same
program were to be crashed. Hence,
determining whether the time, resources,
and efforts to be invested in the
creation of this training program will be
ATENEO STUDEN T BU S I NES S REVI EW
45
Table 12. TFA Three-year Data
Data
Point
Year
Date
No.
of
Pax
Early
Eagle
Pax
Regular
Rate
Early Eagle
Rate
Revenue
Regular
Rate
Revenue
Total Revenue
Revenue/
Student
Total Profit
Profit/
Student
Techniques of Financial Analysis
1
2012
January 9-12
22
15
7
246,500.00
165,000.00
511,500.00
23,250.00
158,500.00
7,204.55
Regular Rate: Php 25,000.00
2
February 6-9
10
7
3
157,500.00
75,000.00
232,500.00
23,250.00
(86,700.00)
(8,670.00)
Early Eagle Rate: Php 22,500.00
3
April 9-12
28
8
20
180,000.00
500,000.00
680,00.00
24,285.71
308,600.00
11,021.43
3.5 days
4
May 7-10
22
20
2
450,000.00
50,000.00
500,000.00
22,727.27
146,000.00
6,636.36
5
June 4-7
17
10
7
225,000.00
175,000.00
400,000.00
23,529.41
60,500.00
3,558.82
6
July 9-12
14
7
7
157,500.00
175,000.00
332,500.00
23,750.00
138,900.00
9,921.43
7
September 3-6
16
8
8
180,000.00
200,000.00
380,000.00
23,750.00
43,400.00
2,712.50
8
October 8-11
19
9
10
202,500.00
250,000.00
452,500.00
23,815.79
107,200.00
5,642.11
9
November 5-8
28
8
20
180,000.00
500,000.00
680,000.00
24,285.71
308,600.00
11,021.43
December 11-15
25
21
4
472,500.00
100,00.00
572,500.00
22,900.00
209,800.00
8,392.00
11
April 11-14
26
16
10
360,000.00
250,000.00
610,000.00
23,461.54
244,400.00
9,400.00
12
June 13-16
29
8
21
180,000.00
525,000.00
705,000.00
24,310.34
330,700.00
11,403.45
Courses
10
13
August 8-11
33
13
20
292,500.00
500,000.00
792,500.00
24,015.15
406,600.00
12,321.21
14
October 10-13
10
6
4
135,000.00
100,000.00
235,000.00
23,500.00
(84,200.00)
(8,420.00)
15
November 7-10
24
14
10
315,000.00
250,000.00
565,000.00
23,541.67
205,200.00
8,550.00
February 15-18
26
18
8
409,500.00
195,000.00
604,500.00
23,250.00
239,400.00
9,207.69
17
April 12-15
8
6
2
126,000.00
60,000.00
186,000.00
23,250.00
(128,400.00)
(16,050.00)
18
June 14-17
25
10
15
225,000.00
375,000.00
600,000.00
24,000.00
237,300.00
9,492.00
19
August 16-19
18
13
5
283,500.00
135,000.00
418,500.00
23,250.00
75,100.00
4,172.22
20
November 15-18
27
19
8
425,250.00
202,500.00
627,750.00
23,250.00
259,000.00
9,592,59
427
299
128
5,303,250.00
4,782,500.00
10,085,750.00
16
Total
2011
2010
Based on Table 12, it appears that to
compute revenue; however, the number
of enrollees for the training module is
uncertain. Moreover, taking into account
the number of enrollees who pay the
Early Eagle Rate vis-à-vis those who pay
the Regular Rate is important. These
factors determine the total revenue of
Ateneo CCE for this particular training
program.
46
AT EN EO S T U D E NT B U SI NE SS R E V IE W
3,179,900.00
With regard to expenses, a fixed cost
of PhP150,200 represents the RP fee,
marketing, and room and equipment
rental. The variable costs, which change
depending on the number of enrollees
at a given period, cover food service and
training kits.
Table 13. Techniques for the Financial Analysis of Income Statement
Course Title
Techniques of Financial Analysis
Faculty
Number of Days
3.5
Income
Number of Pax
25
Course Fee
Students
Eagle
Min
Max
Probability
Min
Max
Probability
0
4
0.00
0
9
0
5
9
0.05
10
19
0
10
14
0.15
20
29
0.15
15
19
0.20
30
39
0.05
20
24
0.15
40
49
0.1
Early Eagle Rate
22,500.00
337,500.00
60%
25
29
0.40
50
59
0.2
Regular Rate
25,000.00
250,000.00
40%
30
34
0.05
60
69
0.2
35
39
0.00
70
79
0.2
1.00
80
89
0.05
90
99
0.05
587,500.00
Direct Expense
RP Fee
24,000.00
Marketing
84,000.00
20,000.00
10,000.00
35,000.00
Equipment
Room
400.00
11,200.00
Food Service
600.00
52,500.00
Training Kits
800.00
20,000.00
40,000.00
20,000.00
Overhead
TOTAL EXPENSES
362,700.00
PROFIT
224,800.00
A simple income statement was
developed for the course (Table 13). The
income statement presupposes that 25
students are enrolled in the TFA training
module. It also presupposes that 60% of
the enrollees paid the Early Eagle Rate,
whereas 40% paid the Regular Rate. In
this scenario, Ateneo CCE is expected to
earn profits amounting to PhP224,800.
The foregoing illustration is only one
of the numerous scenarios should
Ateneo CCE decide to pursue and offer
the new training module called Green
Finance. Thus, conducting simulations is
imperative to more accurately determine
the possible financial outcome of this
undertaking.
A number of software products that
facilitate the Monte Carlo simulation
are currently available. One of these
products is the Oracle Crystal Ball,
considered as the leading spreadsheetbased application for predictive
modeling, forecasting, simulation, and
optimization. The Oracle Crystal Ball
provides unparalleled insights into the
critical factors affecting risk. The Crystal
Ball enables tactical decision making,
thereby achieving objectives and gaining
a competitive edge under even the most
uncertain market conditions.
ATENEO STUDEN T BU S I NES S REVI EW
47
1. Will Ateneo CCE be able to recoup
its investment in creating the Green
Finance training program? If so,
how long will it take Ateneo CCE to
recoup the investment?
2. What is the probability that Ateneo
CCE will not generate any profit?
The results of the simulation (i.e.,
100,000 attempts using the Oracle
Crystal Ball) of the offering of the Green
Finance training program are shown in
Chart 1. The simulation yielded a mean
profit of PhP149,086. This result implies
that every offering of this training
program is likely to generate such a profit
for Ateneo CCE.
Despite the projection of a high
probability for earning profit from the
Green Finance training module, the
Oracle Crystal Ball warns against the
possibility of earning no profit or even
losing money (Chart 2). Accordingly,
an 18.65% chance that Ateneo CCE will
have no profit or even lose money once it
offers the training module is established.
Chart 3 shows that Ateneo CCE has a
41.15% chance of earning a profit of
PhP224,800—the same profit indicated
in the income statement presented in
Table 13. Finally, Chart 4 highlights a 50%
chance that Ateneo CCE will earn a profit
ranging from PhP35,400 to PhP267,500
per run of Green Finance.
After performing the simulations,
reverting to the original questions raised
by CCE is imperative:
48
AT EN EO S T U D E NT B U SI NE SS R E V IE W
The answer to the first question is
yes—Ateneo CCE will be able to recoup
its investment. The surprising aspect,
however, is the time it will take the
Center to recoup the investment. The
simulation reveals that Ateneo CCE
would only need to offer the Green
Finance training module once, and its
investment amounting to PhP148,150
will already be covered. The reason is that
the simulation, after 100,000 attempts,
revealed a mean profit of PhP149,086.
Moreover, even if the Center is
forced to crash the time to create the
Green Finance training module, the
corresponding additional amount will be
so negligible that Ateneo CCE’s decision
will not be affected. The difference in
the crashed amount and the mean profit
Ateneo CCE will make is only PhP15,364.
Given the justification for the high
probability of earning a profit, Ateneo
CCE could already risk the 18.65% chance
of not making any money. Despite the
possibility, the opportunity is extremely
significant to ignore.
Overall, based on the simulation, creating
the Green Finance training program will
not only enable the Center for Continuing
Education to adapt to changing times,
but will also substantially contribute to its
profits.
Chart 1. Crystal Ball Simulation Results for the Green Finance Training Program
100.000 Trials
Frequency View
100.000 Displayed
PROFIT
4,400
0.04
4,000
3,600
3,200
2,800
2,400
0.02
2,000
Frequency
Probability
0.03
1,600
1,200
0.01
800
400
0.00
(200,000.00)
0
(100,000.00)
0.00
-Infinity
100,000.00
200,000.00
300,000.00
400,000.00
Certainty: 100%
Infinity
Chart 2. Crystal Ball Indication of the Likelihood of Incurring a Loss
100.000 Trials
Frequency View
100.000 Displayed
PROFIT
4,400
0.04
4,000
3,600
3,200
2,800
2,400
0.02
2,000
Frequency
Probability
0.03
1,600
1,200
0.01
800
Mean = 149,086.44
400
0.00
(200,000.00)
-Infinity
0
(100,000.00)
0.00
100,000.00
200,000.00
Certainty: 18.646%
300,000.00
400,000.00
0
Overall, based on the simulation, creating the Green Finance
training program will not only enable the Center for Continuing
Education to adapt to changing times, but will also substantially
contribute to its profits.
ATENEO STUDEN T BU S I NES S REVI EW
49
Chart 3. Crystal Ball Indication of the Likelihood of Realizing Significant Profits
100.000 Trials
Frequency View
100.000 Displayed
PROFIT
4,400
0.04
4,000
3,600
3,200
2,800
2,400
0.02
2,000
Frequency
Probability
0.03
1,600
1,200
0.01
800
Mean = 149,086.44
400
0
0.00
(200,000.00)
(100,000.00)
0.00
224,800.00
100,000.00
200,000.00
300,000.00
400,000.00
Certainty: 41.646%
Infinity
Chart 4. Crystal Ball Indication of the Likelihood of Realizing Profits
Around the Mean
100.000 Trials
Frequency View
100.000 Displayed
PROFIT
4,400
0.04
4,000
3,600
3,200
2,800
2,400
0.02
2,000
Frequency
Probability
0.03
1,600
1,200
0.01
800
Mean = 149,086.44
400
0
0.00
(200,000.00)
224,800.00
(100,000.00)
0.00
100,000.00
200,000.00
Certainty: 50%
300,000.00
400,000.00
267,500.00
. . . the key challenge is to nurture a culture that has the discipline,
patience, and courage to look beyond short-term solutions and opt
for business practices that can offer the greatest positive impact
and longevity.
50
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Conclusion
Quantitative analysis provided value
to this paper. The concept or the
process of changing the corporate
mindset and culture to embrace green
and sustainable undertakings can be
daunting. Nevertheless, introducing
Green Finance course is an initiative that
is a step closer toward creating a greener
and more sustainable planet and a
responsible citizenry, as well as achieving
sound profits. Yes, profits are attainable;
this paper ascertained the possibility of
making money out of green innovations.
•
•
LP was applied to maximize the
profit of existing Finance courses.
PERT was employed to identify the
variance of activities in the development of new courses before
applying crashing to maximize cost
savings.
•
The Monte Carlo simulation was
performed to assess the risk of
offering Green Finance course.
A number of alternatives to promote
green and sustainability efforts are
available, including the application of
quantitative analysis. However, the key
challenge is to nurture a culture that has
the discipline, patience, and courage to
look beyond short-term solutions and opt
for business practices that can offer the
greatest positive impact and longevity.
This challenge can be resolved through
the Center for Continuing Education in a
tried and tested fashion: the Ateneo way.
References
1 http://www.oracle.com/us/products/applications/crystalball/crystal-ball-product/overview/
index.html
2The list of possible green and sustainability
courses and the Abstract for Green Finance are
quoted from ecochamber.com.
ATENEO STUDEN T BU S I NES S REVI EW
51
Ensuring Continuous
Improvement through
ISO 9001 Certification
Ivy Joy Alagar
Daniel Leon S. Berroya
Atty. James S. Biron
Dong Haiyan
Eliza T. Guades
Irene Palad
52
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Introduction
N
owadays, most manufacturing
companies aim to improve
their operational efficiency
and effectiveness. Obtaining
a certification to ISO
Management System Standards helps
companies to attain their desired outcome.
To ensure operational safety, large
companies often invest in ISO certification.
In some industries, ISO certification is
a regulatory requirement. Aside from
ensuring the manufacture of high-quality
products, the benefits of ISO certification
include cost savings in optimized
processes, improved customer satisfaction,
opportunities for catering to new markets,
increased market share, guaranteed food
safety, and even minimized negative
impacts on the environment.
Aligning company operations with ISO
9001 Quality Management System and
achieving certification can help solve
problems in customer dissatisfaction
with linkage to outsourced processes and
streamlining of established workflows.
ISO 9001 Quality Management System
certification can address current problems
in delivery, storage, and customer
complaints. Such certification is a means
to manage product and service challenges.
Moreover, processes are established and
put in place. Controls are also identified
and prevent the recurrence of nonconformance.
ISO 9001 Quality
Management System
certification can address
current problems in delivery,
storage, and customer
complaints.
Current & Target Situation
C
U
R
R
E
N
T
High customer
delivery
complaint
High rating
vendor
performance
No structured
3PL processes
Structured 3PL
processes
Non-ISO
certified
ISO
certified
T
A
R
G
E
T
Solution
VOC
• Customer Complaints on product
quality upon delivery, mishandling,
equipment not calibrated
Goals
• Target of Company to be known in the
global market as an exporter like that
of KLT and Profood which can aid in
increasing market share domestically
IPO
• Operational Efficiency
• Customer Intimacy
ISO 9001 Quality Management
System Certification
A company may have in place a process
for receiving incoming raw materials.
However, the criteria for selecting,
evaluating, and continuously monitoring
suppliers must be established. Existing
purchasing policy must also be reviewed
to include a provision for outsourced
services. ISO 9001 elements 7.4.1 to 7.4.3
will help companies to ensure that the
ATENEO STUDEN T BU S I NES S REVI EW
53
purchased product or service conforms
to the specified purchase requirements.
The standard will lay down the guidelines
that help the organization to evaluate
and select suppliers based on their ability
to supply products in accordance with
the organization’s requirements. The
criteria for selection, evaluation, and reevaluation shall be established to include
site inspection and audit of supplier
premises to verify the purchased product
or service.
A manufacturing process or system
must be in place as this is the heart of
service realization. A company may also
conform to Good Manufacturing Practice
(GMP) and gear toward Hazards Analysis
and Critical Control Point (HACCP) to
efficiently structure its food processing
system and safeguard food against
unsafe elements and practices. Critical
control points (CCPs), simultaneously
with HACCP alignment, may also be
established alongside verification and
validation processes that complement
product research and development (R&D).
ISO 9001 Quality Management System
certification will likewise facilitate the
review and improvement of all the
processes of each department aimed
toward customer satisfaction.
The following diagram illustrates a sample
flow of operations from batching to
storage and delivery of finished products.
When purchase orders are received from
clients, the outsourced delivery company
transports the products from the cold
storage provider (also outsourced) to
the clients’ premises. As presented in the
diagram, the process demonstrates a lack
of control over its frozen products; it only
covers receiving to cooling. The challenge
now lies in the cold storage and delivery of
frozen products.
Processing
Batching
Critical Control Point
Cook
Critical Control Point
Sterilization
Check Parameters
Pack & Seal
Critical Control Point
AT EN EO S T U D E NT B U SI NE SS R E V IE W
1-4 HR
Kettle is by 50kg capacity
1-4 HR
Machine Retort is by 50kg capacity
15 MIN
LAB checking if within standards
30 MIN
Industrial Packaging (primary)
Cool
1 HR
Industrial Packaging (secondary)
Store (-18 to -23)
5-7 Days (freezing)
3rd Party Cold Storage (nearby)
Delivery
54
Prepare by 50kg
Prepare chemicals and other
materials needed
will depend on the client
3rd party Reefer Van
Production processes had been aligned
with GMP and HACCP. Other processes,
such as those of HR, Sales, delivery, and
control and monitoring of its outsourced
processes and production, need to
be aligned with ISO 9001 elements to
achieve customer satisfaction in all
aspects of the organization. Customer
satisfaction is focused both on external
clients and internal clients (i.e.,
employees). Streamlining processes to
efficiently deliver services to internal
and external clients is vital. The same
approach must be applied to all stages,
from receiving to delivery. Although
storage and delivery are outsourced, the
standard specifies that the organization
should have control over its outsourced
processes as these could affect the
quality of the product and service being
rendered.
Following are some ISO elements that
a company may use to align production
process with the Quality Management
System (QMS):
ISO Procedure 7.3.1. Design and
Development Planning. The organization
shall plan and design the product
development according to customer
requirements. This step ensures that
the work flow to be established is in
accordance with the output agreed with
the customer. The step also enables the
organization to control product or service
quality at any stage of the production
process. Review and verification shall
be established at each stage to ensure
conformity to requirements.
ISO Procedure 7.3.2, 7.3.3. Design and
Development Planning Input and Output.
The organization should identify the
process inputs that affect product design
and development. Inputs can be in the
form of customer input, international
standards, industry practices,
technological experiences, records,
data, market research, and feedback
information from past experiences. These
inputs will help identify the processes
that are critical to product or service
quality. The output should include
information that can be verified and
validated to determine if the design and
development efficiently meet product
or service requirements. This aspect is
evident in the above workflow – checking
of parameters, cooling temperature,
cooking temperature, sterilization, and
packing and seal specifications.
ISO Procedure 7.3.4. Design and
Development Review. Design such as
R&D and workflow must be continuously
and regularly reviewed to determine if
the current process still meets customer
requirements. Through this step, the
company can ascertain if its practices are
at par with industry practices and trends.
This factor will enable the company to
identify any problems in the process and
recommend the necessary solutions.
ISO Procedure 7.3.5, 7.3.6. Design and
Development Verification and Validation.
Verification should be performed to
check if the design and development
outputs have met the design and
input requirements. Validation should
be performed to determine if the
resulting product is capable of meeting
the specified requirements. This step
should be undertaken prior to product
delivery or, in this case, prior to delivery
to third-party logistics. The company
may perform laboratory results and
product quality monitoring as a form of
verification and validation at a specific
stage in the production process and prior
to delivery to its cold storage provider.
ATENEO STUDEN T BU S I NES S REVI EW
55
Customer delivery complaints may be
anchored in products that do not meet
the agreed temperature. An investigation
of the company’s supply chain and the
amount of control/monitoring it has
applied to ensure product or service
quality indicated that the company
lacked established processes and control
at each stage of the delivery and storage
processes. Hence, a proposed flow is
shown below:
Delivery and Storage to
Third Party Supplier
Critical Control Point
Finishes Goods from Production Plant
Inspection of items
Checklist
Warehouse GMP
FIFO Policy
Proper Stacking
Warehouse Temperature
Observation of the 7 day
Incubation
Critical Control
Point
Storing of product in Cooling Warehouse
(Company Owned)
Checklist
Product Temperature
Product Integrity Packaging
Truck GMP
Vehicle Temperature
Proper Stacking
Holding Time
Logging items in the stock card
Delivery Schedule
Checklist
Truck GMP
Truck Temperature
Packaging Integrity
Product Temperature
Distribution Staff’s
Personal Hygiene
COA
(Certificate of Analysis)
Holding Time
Proper Stacking/No
Mixture of other
goods
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
Observation of the FIFO Policy
Critical Control
Point
Reefer Van/Truck
Checklist
Trip Ticket
Delivery Slip
Critical Control
Point
Delivery at Third Party Cold
Storage/Unloading
Product Temperature
Product Integrity Packaging
Truck GMP
Vehicle Temperature
Proper Stacking
Distribution Staff’s Personal
Hygiene
The CCPs are strategically placed in areas
where the quality and safety of goods
may be altered due to factors such as
environment, man, and equipment.
This step ensures that stringent controls
are maintained at these critical stages.
Finished goods need to be inspected
before leaving the manufacturing plant.
Checklists are used as a guide for ensuring
the items are in good condition prior to
release, transit, and unloading. These
include product temperature, packaging,
proper stacking of goods in the truck,
and cleanliness. The goods must be
transported to the cooling warehouse
(company-owned) to prepare the goods
for a frozen state. Inside the cooling
warehouse, temperature and FIFO (FirstIn-First-Out) policy must be observed to
ensure proper stock rotation and product
quality.
Transferring goods from the cooling
warehouse to reefer vans is critical as it
may negatively affect product quality.
Delivery (in transit) to the third-party cold
storage supplier is also crucial. Delivery
and transfer from cold storage to reefer
vans can break the cold chain that makes
these stages critical. If the cold chain
is not sustained at all stages, harmful
microorganisms can proliferate due to
an increase in temperature. Therefore,
temperature in cold storage must be
well monitored to ensure that goods are
kept within -18°C to -23°C. The company
can check the log books or monitoring
sheets of the supplier during internal audit
activities as objective evidence to ensure
that the equipment is performing on
standard. The data could also be used as
preventive maintenance inputs.
Delivery to Customer
Finished Goods from Third Party Cold Storage
Checklist
Critical Control Point
Checklist
Loading Bay GMP
Truck/Storage GMP
Temperature
Distribution Staff’s
Personal Hygiene
Holding Time
Critical Control Point
Reefer Van/ Truck (IN TRANSIT)
Trip Ticket
Delivery Slip
Loading bay @ Cold Storage
Warehouse staff to checktrip ticket
Storage
Truck GMP
Temperature
Distribution Staff’s Personal
Hygiene
Items to be delivered
Critical Control Point
Checklist
Storage Temperature
Stacking Height
Warehouse GMP
Checklist
Truck GMP
Truck Temperature
Packaging Integrity
Product Temperature
Distribution Staff’s
Personal Hygiene
Items to be delivered
COA
Reefer Van/Truck (Delivery to cold client)
Critical Control Point
Checklist
Trip Ticket
Delivery Slip
Delivery to Client
Product Temperature
Product Integrity Packaging
Truck GMP
Vehicle Temperature
Proper Stacking
Distribution Staff’s Personal
Hygiene
ATENEO STUDEN T BU S I NES S REVI EW
57
Once the orders from clients are made,
goods are transferred to reefer vans for
delivery. The CCPs reflect the areas to
be monitored that could affect product
quality. Proper laboratory reports must
be presented upon delivery to the client
as proof that goods and services have
met acceptable criteria. The proposed
flow results in the hiring of additional
quality assurance (QA) staff members to
perform inspections and audit of CCPs for
proper monitoring.
The company should perform an internal
audit on the suppliers to monitor
the decline and improvements in
performance against its performance
standards. This measure will also help
the company to ensure that product
or service quality is similar to what had
been agreed with its customers. Internal
quality audit (IQA) should identify
process gaps that provide opportunities
for refining workflows.
ISO Procedure 7.5.5. Preservation of
Product. The organization shall preserve
the product during internal processing
and delivery to the intended destination
to maintain conformity to requirements.
Although the company uses a thirdparty supplier for cold storage and
delivery, established processes and
controls must be put in place. The owner
is responsible for ensuring that the
goods meet the agreed specifications
as they reach the client’s premises. As
applicable, preservation shall include
several activities, such as identification
(labelling), handling, packaging, storage
(at the proper temperature), and
protection.
Following are the ISO elements that
should be aligned in all stages of the
supply chain:
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
ISO Procedure 8.2.4. Monitoring and
Measurement of Product/Service.
The organization should be able to
monitor and measure product or service
characteristics to verify that product or
service requirements have been met. This
verification can be in the form of logging
sheets or receiving checklist to verify if
the product has met the agreed criteria
when it reached the client’s premises.
ISO Procedure 8.3. Control of NonConforming Product. The organization
should establish ways to identify the
products that do not conform to product
requirements. Such products should be
identified and prevented from being
delivered or used inadvertently. This
guideline is related to the next one.
ISO Procedures 8.5.2 and 8.5.3.
Corrective and Preventive Action. Once
a deviation from product requirements
has been identified, the organization
must eliminate the cause of nonconformity and prevent its recurrence.
The organization should also eliminate
the potential causes of non-conformities.
Corrective action is an immediate
solution to the challenge at hand.
Meanwhile, preventive action includes
root cause analysis to eliminate the real
cause of the problem and prevent any
recurrence.
ISO Procedure 4.2.4. Control of
Records. Records shall be established
and maintained to provide evidence of
conformity to requirements. Records
are objective evidence during internal
audits and certification audits. ISO
Procedure 4.2.3 Control of Documents
complements this procedure. Control of
documents ensures the use of documents
by authorized individuals, establishes
document retention, and identifies
the appropriate authority required for
the document. This step ensures that
despite the absence or unavailability
of the approver, an alternate signs off
on the document, thereby preventing
unauthorized use.
ISO Procedure 6.2.2.2. Awareness and
Training. The organization shall provide
the appropriate education and training
to employees/suppliers to emphasize
the importance of meeting the needs
and expectations of customers and
other interested parties. Such education
and training should include increasing
the awareness of the consequences of
failing to meet customer expectations.
Employees should be continuously
informed about the trends and best
practices in the industry and those in
their fields of expertise to provide better
service to the company’s internal and
external clients.
ISO 9001 Quality Management System
is aimed at customer satisfaction and
continuous improvement; thus, the
process flow of soliciting customer
feedback and internal audit must be
developed. Incorporating customer
feedback with the corrective and
preventive action procedures effectively
measures organizational performance
in terms of meeting and exceeding
customer requirements. Management
should be involved in this process as
their commitment is vital in ensuring
that complaints and process gaps are
resolved. Informing customers about the
corrective and preventive action that the
company has undertaken is also vital. This
approach enables clients to feel that they
are important. Moreover, the approach is
an affirmation that the company intends
to improve.
to the International Standard and to the
QMS requirements established by the
organization.
Process owners of the area being audited
must ensure that the necessary corrective
and preventive actions are undertaken.
Results of internal audits must be
discussed during management review.
The management review will function as
an avenue for evaluating the efficiency
and effectiveness of the system. The
review, headed by the leadership, will
open the discussion and evaluation of
inputs and the exchange of new ideas, as
well as infuse performance improvement
in product and service quality that
extends to the entire organization.
Workflow for rejected product delivery
is also reviewed to incorporate changes
originating from inputs of customer
feedback. Temperature is added as one
of the reasons for product rejection.
Appropriate steps are likewise added
to control the unintended use of the
rejected product.
ISO 9001 certification acts as guideline
for resolving and improving operation
management challenges; at the same
time, it is also a holistic approach to
achieving customer satisfaction and
continual improvement in all aspects
of the business. Moreover, ISO 9001
certification provides linkages between
departmental processes, and ensures that
all functions are value adding, efficient,
and effective.
Impact of ISO 9001 Quality Management
ISO 9001 certification provides numerous
benefits, including the following:
Internal audit must be conducted to
determine whether the QMS conforms
ATENEO STUDEN T BU S I NES S REVI EW
59
•
•
Reduces the cost of rejected
products or lost sales; eliminates
wastage and spoilage due to
excess production and rejection (see
the sample of Cost–Benefit Analysis)
Avoids errors and bad orders
Increases revenue; boosts the
availability of products for sale as
product rejection decreases
Promotes efficiency in production
and service; eliminates idle time and
rework resulting from unsure
processes and workflow; increases
revenue as more products are
available for sale and more
customers are satisfied
Enhances brand image due to
increased loyalty and the prioritization of product or service quality
and customer satisfaction
Increases employee morale due to
regular training; enhances the
brand image
•
•
•
•
•
•
•
•
Develops and reinforces mutual
supplier relationships (i.e., suppliers
are also the partners of the
organization)
Increases customer loyalty and
confidence due to product and
service improvement
Maintains product and service
consistency as standardized
processes are strictly implemented
to ensure the delivery of safe, high
quality products
Promotes a factual approach to
decision making as it entails the
analysis of customer feedback and
records; the company has a basis
for its decisions and need not simply
rely on gut feel that can lead to
losses; impacts can be identified
and controlled
Cost–Benefit Analysis
(Annual estimates, in pesos)
Year 1
Year 2
Year 3
TOTAL
6,000,000
4,800,000
2,880,000
13,680,000
Benefit
Rejection cost
80%
60%
30%
Adjusted rejection cost
% of Rejection
4,800,000
2,880,000
864,000
8,544,000
Cost Avoidance
1,200,000
1,920,000
2,016,000
5,136,000
200,000
75,000
75,000
350,000
200,000
200,000
400,000
200,000
200,000
200,000
600,000
356,400
356,400
356,400
1,069,200
600,000
600,000
600,000
1,800,000
Cost
ISO Certification Costs
Training costs
One-time QA and process owners
300,000
Yearly training
300,000
Machines
Metal detector (goods receiving and inspection)
Manpower
3 FTEs for extra audit inspections
Method
ISO-certified facility rental
Delivery
60
AT EN EO S T U D E NT B U SI NE SS R E V IE W
100,000
100,000
100,000
300,000
Total Cost
1,756,400
1,531,400
1,531,400
4,819,200
Total Savings
-556,400
388,600
484,600
316,800
The estimated annual loss due to nonsales of rejected items is Php6 million.
The implementation of ISO 9001 is
expected to decrease by 20% annually. The
aforementioned ISO certification costs
are three-year estimates and are valid for
only one site. In three years, the estimated
benefit for this project is Php5.136 million.
Additional costs that will be incurred
include ISO certification, training and
manpower, machine/device acquisition,
and other operation costs involving
storage and delivery. ISO certification for
three years in one site costs Php350,000.
The bulk of the cost is usually incurred
during the first year. Training costs involve
one-time training for process owners and
QA employees. Refresher training will also
be conducted annually for the employees.
Such training will help employees to
become familiar with the new procedures,
thereby ensuring product quality and
safety.
A metal detector that usually costs Php1
million will be required for receiving and
inspection of goods; its estimated useful
life is five years. Additional depreciation
cost using a straight-line method will
be Php200,000. ISO 9001 would require
a new QA team that will handle extra
audit inspections. The team will involve
three additional staff members with an
estimated annual cost of Php356,400.
Seeking a new, ISO-certified storage
facility for keeping products at the
required temperature is also encouraged.
Moreover, extra cost to improve the
delivery processes is expected. The
improvement of these processes is
estimated to cost Php700,000 annually.
The net benefit of this three-year project
is Php316,800. Although the net benefit
may not be considerable, the impact
on corporate reputation and customer
satisfaction will be significant. Given that
company procedures will be audited
and improved, lesser costs on spoilage
and wastage will be expected. Keeping
these procedures in place will facilitate
the company’s application for other
certifications on food safety and quality,
which are often required in the global
markets.
Recommendations
ISO 9001 certification is an achievable
step toward continuous improvement.
This organization should ensure the
control of its rejected products to help
minimize costs on wastage and lost sales.
It needs to discuss the results of audit
during management reviews so that
management is informed and engaged in
resolving gaps and challenges resulting
from an inefficient system. The company
achieves continuous improvement only
through these reviews.
The company’s purchasing policy should
be reviewed and modified to cover
outsourced services such as storage and
delivery. It should establish policies on the
control of rejected products, purchasing,
and supplier policies. Performing a secondparty audit on suppliers to conduct a
check and balance on the processes of
its suppliers is also advisable to ensure
that they are aligned with the company’s
storage and delivery requirements.
Compliance with and certification to ISO
22000 Food Safety Management System
– a combination of ISO 9001 (QMS),
HACCP and GMP – is highly encouraged
to meet the quality, food safety, and
marketing goals of the company. Finally,
the company must perform benchmarking
on ISO-certified clients, suppliers, and
competitors to enable it to imbibe best
practices.
ATENEO STUDEN T BU S I NES S REVI EW
61
Streamlining the
Government
ID Processing System
Ana Teodisio
Arthur Villones
Gladys Estandian
Ricky Lascano
Application Forms
Contains
here common
information
asked by
government
agencies
Finger Printing
Database Server where both
biometrics and logical data
are stored.
62
AT EN EO S T U D E NT B U SI NE SS R E V IE W
Face Capturing
Workstation
Background
W
four government agencies, namely, Social
Security System (SSS), Bureau of Internal
Revenue (BIR), Pag-IBIG, and PhilHealth.
hen applying for an
identification (ID)
number or a change
status request
SSS ID Application
from government
agencies, employees, especially new
The Applicant fills in SSS Form E-1
entrants to the workforce, have to
(Personal Record) and submits it to an
go to the offices of these agencies
SSS branch together with the following
and suffer from long queues to fill in
documents: Birth Certificate, Baptismal
forms requiring the same information
Certificate, Driver’s License, Passport,
to prove one’s identity. Examples
and Professional Regulation Commission
of such information are Name,
(PRC) Card, or Seaman’s Book. If the
Address, Telephone Number, Gender,
Applicant does not have any of these
Citizenship, Date
documents, any two
of Birth, Place of
supplementary ID
Birth, Civil Status,
cards, such as school
This paper proposes
Beneficiaries,
ID and ATM card, are
to integrate and
Employment
acceptable.
simplify the process
Classification, and
Signature. These
for obtaining the IDs
agencies typically
BIR ID Application
from four government
employ one to
two windows to
The Applicant fills in BIR
agencies, namely,
accommodate
Form 1902 (Application
Social Security
applicants who
for Registration for
would have to
Individuals Earning
System (SSS), Bureau
wait a half day or
Purely Compensation
of Internal Revenue
even an entire day
Income, Non-Resident
simply to obtain
(BIR), Pag-IBIG, and
Citizens, and Resident
an ID.
Alien Employee).
PhilHealth.
The documentary
The amount of
requirements are
effort to fill in
Birth Certificate of the Applicant,
the forms and the amount of space
Birth Certificate(s) of the declared
required to archive the collected
dependent(s), waiver of the husband on
information in databases of the
his right to claim additional exemptions
different agencies can be a good
if his wife claims exemption; and
reference for study, thereby providing
Marriage Contract if married. The
an improvement opportunity through
employer accomplishes the applicable
data integration and possibly service
sections of the application form. The
delivery consolidation. This paper
Applicant submits all the documentary
proposes to integrate and simplify
requirements to the BIR Revenue District
the process for obtaining the IDs from
Office that has jurisdiction over the
ATENEO STUDEN T BU S I NES S REVI EW
63
An investigative type of research design was applied through
actual visits to the different government branches under study
within the vicinity of Makati City, as well as interviews with
guards-on-duty, clerks, employees, and officers-in-charge.
location of the employer’s office where
the Applicant is expected to report for
work.
Pag-IBIG ID Application
The Applicant goes to the nearest PagIBIG branch. For branches provided with
an Online Membership Registration
System, the Applicant encodes the
required information. Otherwise, the
Applicant fills in and submits the PagIBIG form (i.e., Member’s Data Form).
PhilHealth ID Application
The Applicant fills in the PhilHealth
Membership Registration Form and
submits it with all the supporting
documents to the HR Department. The
practice whereby employers handle their
employees’ application with PhilHealth is
commonplace.
Research Design
An investigative type of research design
was applied through actual visits to the
different government branches under
study within the vicinity of Makati City, as
well as interviews with guards-on-duty,
clerks, employees, and officers-in-charge.
This kind of research design is best suited
for this study, enabling the researchers
to collect data for the Queuing Theory
through direct interaction with the staff
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
who have first-hand information. The
data collected are validated by observing
and extracting the arrival and service
times’ information of each agency
through a discrete time and motion
study, and even participating in actual
queues.
To determine the number of new
employees joining the workforce, the
regression data were extracted from the
SSS statistical information. The simple
linear regression forecasting method
was used to determine the number of
new entrants to the workforce consisting
of new college graduates seeking
employment, including college undergraduates, working students, and outof-school youth within and over the legal
age of 18.
Population and Sampling
Procedure
Given the sheer size of the scope of study,
the sample frames used for the research
are the government branches in Makati
(i.e., the SSS branches in Gil Puyat, Ayala,
and J.P. Rizal, the BIR branches in Atrium
and Gil Puyat, and the Pag-IBIG branch
in Gil Puyat. PhilHealth was excluded
because employers register their new
employees in batches, a process that
avoids employees queuing up at the
PhilHealth branch.
The aim of sampling within the Makati
area is to provide benchmark information
benefit-cost analysis. Consequently,
the researchers provided qualitative
evaluation based on perceived benefits
obtained from interviews with colleagues,
and classmates, as well as random
discussion with personal contacts and
among the researchers themselves.
Linear Regression Model
on the primary attributes of the queuing
model, such as arrival times and service
times, and the overall throughput time,
which may be extrapolated to any
location across the country if, in the
future, a similar study is to be made on
these government agencies.
Limitations and Assumptions
Given the short duration of the study, the
averages resulting from the primary data
are assumed to apply to the entire day. In
actuality, the visits did not take a whole
day, and the averages were based on the
information provided by the researchers’
contacts inside these agencies.
The selected sample is assumed to
represent the actual population (i.e., the
agencies outside Makati will have similar
outcomes regardless of geographical
locations). Moreover, the application data
obtained from SSS are extrapolated and
assumed to be similar for the other three
government agencies.
The researchers were unable to obtain
information on costs, such as ID
processing cost and forms cost, required
to effectively perform a quantitative
The linear regression model was used
to forecast the annual increase in SSS
membership for the Employee category.
Thus, the number of individuals who
will benefit should an Integrated ID
Processing System be adopted by the
government can be established.
The linear regression data show the total
number of registered members from
1999 to 2008 (Table 1). The data include
workers classified into three categories,
namely, Employees, Self-Employed,
and Voluntary Members. Results of the
regression analysis are presented in
Figures 1 and 2.
Table 1. Linear Regression Data
Year
Period (X)
Number of
Workers (Y)
1999
1
21,325,966
2000
2
22,630,832
2001
3
23,532,666
2002
4
24,308,033
2003
5
25,051,234
2004
6
25,666,386
2005
7
26,227,636
2006
8
26,739,282
2007
9
27,241,220
2008
10
27,759,568
ATENEO STUDEN T BU S I NES S REVI EW
65
Regression Statistics
Multiple R
0.9881225
R Square
0.97638607
Adjusted R Square
0.97343432
Standard Error
340754.076
Observations
10
ANOVA
df
SS
MS
F
Significance F
Regression
1
3.84E+13
3.84E+13
330.783
8.58E-08
Residual
8
9.29E+11
1.16E+11
Total
9
3.93E+13
Coefficients
Standard
Error
t Statistics
P-Value
Lower 95%
Intercept
21295543.1
232779.3
91.48382
2.27E-13
20758752.99
X Variable 1
682316.212
37515.79
18.18744
8.58E-08
595804.6475
Figure 1. Summary Output of Regression Analysis
X Variable 1 Line Fit Plot
30,000,000
25,000,000
20,000,000
y = 682316x + 2E+07
R2 = 1
15,000,000
10,000,000
Y
5,000,000
0
Predicted Y
Linear [Predicted Y]
0
5
10
15
X Variable 1
Figure 2. Linear Model
From the Summary Output generated
from the regression analysis solver of
Excel, the R2 nears 1, which implies that
the data model is a good fit. Further
analysis suggests that the model results
66
AT EN EO S T U D E NT B U SI NE SS R E V IE W
also passed the significance F and t-Stat
requirements, thus providing a high level
of confidence that the values generated
from the linear equation are acceptable.
Given these results, the number of
The total number of individuals who
will benefit should the Integrated ID
Processing System be adopted by the
government is 682,316 per year. Of this
number, 69% or 470,798 are Employees;
20% or 136,463 are Self-Employed; and
11% or 75,055 are Voluntary Members.
memberships can be forecast for 2009
to 2011, annually increasing by 682,316
(Table 2).
Table 2. Forecast Data
Year
Period (X)
Number of
Workers (Y)
2009
11
28,801,021
2010
12
29,483,338
2011
13
30,165,654
Queuing Analysis
The queuing technique was used to
quantify the benefit in terms of time
savings for each individual should the
proposed Integrated ID Processing
System be adopted. For this purpose, the
Makati area and the category Employees
were used as sample population.
The researchers went to the different
government agencies in Makati to
observe and conduct interviews. The data
collected are shown in Table 4, and the
queuing results are presented in Table 5.
However, the forecast annual increase
includes the other two categories (SelfEmployed and Voluntary Members). To
obtain the portion applicable only to the
number of Employees, the researchers
used the data provided by the SSS Head
Office, which show the Total Registration
as of June 2011 per category (Table 3).
Table 3. Registration of New SSS Members
Cluster
Employee
Self-Employed
Voluntary
Total
North Luzon
724,314
590,296
137,834
1,452,444
Central Luzon
1,179,164
914,433
185,392
2,278,989
NCR
11,059,427
1,043,845
1,996,920
14,100,192
South Luzon
1,232,429
494,825
169,636
1,896,890
Bicol Region
283,100
321,886
78,106
683,092
Western Visayas
1,485,555
559,381
170,458
2,215,394
Central Visayas
1,494,646
344,088
172,500
2,011,234
Northern Mindanao
910,982
619,748
101,067
1,631,797
Western Mindanao
353,071
282,234
46,848
682,153
Southern Mindanao
1,287,202
610,262
183,297
2,080,761
20,009,890
5,780,998
3,242,058
29,032,946
69
20
11
100
Total
Percentage
Source: http://sssintranet/MIS/html/factmemjdec10.htm
ATENEO STUDEN T BU S I NES S REVI EW
67
Table 4. Queue Parameters
Data Gathered
Monthly
Daily
Mean Service Time
[in minutes (µS)]
Mean Arrival Time
[in minutes (µA)]
Gil Puyat
798
38
4.5
10.26
Ayala
600
29
4.5
13.44
J.P. Rizal
1,251
60
4.5
6.50
Atrium
1,473
70
5
5.57
Gil Puyat
1,152
55
5
7.09
2,340
111
6
3.51
Number of Applicants (for
the month of August)
SSS
BIR
HDMF
Table 5. Queuing Results for the Current Setup (in minutes)
System Load
Factor (r)
WTM
[r/(1-r)]
µW
µL
Throughput
(µS+µW)
SSS
9.8019
Gil Puyat
0.4386
0.7813
3.515
0.34
8.0159
Ayala
0.3348
0.5033
2.264
0.16
6.7649
J.P. Rizal
0.6923
2.2500
10.12
1.55
14.6250
BIR
32.9185
Atrium
0.8977
8.7752
43.87
7.87
48.8760
Gil Puyat
0.7052
2.3922
11.96
1.68
16.9610
1.7094
2.4097
14.45
4.11
20.4582
HDMF
Total Time Spent in ID Processing for the Three Agencies
Based on the foregoing computation, an
individual spends an average of almost
an hour in applying for ID numbers with
the three Government Agencies. This
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
Average
20.4582
63.1786
does not include yet their travelling time,
time spent in traffic, and waiting for
transportation.
Queuing for the Proposed
Integrated ID Processing
System
Using the data from SSS as shown in
Table 6 (with the assumption that new
employees applying for SSS ID number
will also obtain BIR and HDMF numbers),
the recommended queue system is
presented in Table 7.
Table 6. SSS Applicants
Monthly
Daily
Gil Puyat
798
38
Ayala
600
29
J.P. Rizal
1,251
60
Total
2,649
127
From the resulting computation, the
following premises are established:
individuals applying for governmentissued ID numbers will spend 24 minutes
if the setup will have a single server; 14.5
minutes if at least two servers are used;
and 7 minutes if three servers are used.
Each setup will give applicants time
savings of between 39 minutes and 56
minutes.
Findings and Recommendations
The annual increase in new applicants
is 682,316 nationwide, and the average
throughput time experienced by an
applicant is 63 minutes. The longest
stay-put time is determined at the BIR
at 33 minutes, followed by Pag-IBIG
at 20 minutes, and SSS at 10 minutes.
The current situation demonstrates
that each of the four agencies serves
its constituents individually. Using an
integrated ID processing mechanism
can dramatically reduce the overall
throughput time to 7 minutes using three
servers.
Table 7. Queue System Recommendation (in minutes)
Mean
Service
Time
Mean
Arrival
Time
System
Load
Factor
WTM
µW
µL
Throughput
Integrated
(1 processor/server)
6
4
1.5000
3.0000
18.0000
4.5000
24.0000
Integrated
(2 processor/server)
6
4
0.7500
1.4147
8.4900
2.1200
14.4900
Integrated
(3 processor/server)
6
4
0.5000
0.1579
0.9500
0.2400
6.9500
ATENEO STUDEN T BU S I NES S REVI EW
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The integration of the ID processing
of the four government agencies
under study can provide beneficial
effects to both government and its
people, specifically the entrants to
the labor market. This study can be
the beginning of something new in
improving government structures – an
innovation that is scalable as the need for
government services increases. Looking
into alternative forms of providing better
services while lowering costs is a viable
notion for the government.
This study recommends the adoption of
a shared service model for ID processing
in these four agencies. Shared services
primarily aim to reduce duplication of
effort, lower incidental times at queues,
enable government staff to focus on the
most valuable work in the agency, and
provide more services given the limited
resources. The costs on the following
qualitative factors can be minimized:
processing of registration forms into a
singular information sheet, integration
of staff services, savings on office space,
and fraud deterrence.
Shared services can provide the means
for these agencies to put more emphasis
on their core functions – social services
for SSS, tax collection for BIR, housing
requirements for Pag-IBIG, and adequate
provision of health services to Filipino
workers for PhilHealth. Shared services
can de-couple non-core activities that
are viewed as “support” and secondary to
their core processes.
Although not explicitly quantified, the
business case of a shared service center
can demonstrate that the intended
benefits would accrue to the new
employees, the service provider, and
the government as a whole. However,
a shared service approach requires
collaboration among the four agencies,
with the possibility of establishing a
separate office for the purpose.
References
BIR Website: Application for Taxpayer
Identification Number (TIN)
http://www.bir.gov.ph/reginfo/regtin.htm
SSS Website: How to Register
https://www.sss.gov.ph/sss/index2.
jsp?secid=109&cat=2&pg=null
SSS New Members Registration
http://sssintranet/MIS/html/factmemjdec10.
htm
PhilHealth Website: PhilHealth Members
http://www.philhealth.gov.ph/members/index.
htm
Pag-IBIG Fund Website: Members Services
http://www.pagibigfund.gov.ph/memserv/
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
Contributors
Everyone in the list is taking up or has completed his/her Master’s Degree in Business
Administration at the Ateneo Graduate School of Business.
Ivy Joy Alagar graduated from the University of the Philippines-Los Baños in 2008. She
works at The Hong Kong and Shanghai Banking Corporation Manila (HSBC) as Accounts
Payable Assistant II. She has been with the Back Office–Operations team for more than four
years.
Daniel Leon S. Berroya graduated with a BS degree in Marketing and Corporate
Communication at San Beda College in 2006. He worked at Globe Telecommunication, Inc.
in Sales and Customer Service. In 2009, he moved to Food Customs, a food manufacturing
business for processed fruits and vegetables. He is currently the Sales Manager engaged in
local and export transactions.
Atty. James S. Biron graduated cum laude from the University of the Philippines-Diliman
with a degree in B.A. Political Science in 2004. He then took up Law at the Ateneo de Manila
School of Law and graduated in 2008. He successfully passed the Bar Exams given in the
same year. He is currently a Legal Manager in a New York-based firm that has an office in
Makati City.
Jejie Junio Camacho graduated from the Technological University of the Philippines with a
degree in BS Engineering. He works with Analog Devices Phils, where he is responsible for
process improvements in test manufacturing such as error proofing, standardization, yield
improvement, process simplification, and process qualifications.
Zosimo Richard S. Carlos III obtained his B.S. in Computer Science major in Software
Technology degree from De La Salle University. He has a Project Management Professional®
certification from the Project Management Institute. He worked at ABS-CBN Interactive–
Multi-media, HanbitSoft, and IP e-Games Ventures. He is currently a Project Manager at IBM
Solutions Delivery.
Dr. Jhanssen Castillo is an Ophthalmology Consultant at Tagaytay Hospital and Medical
Center, Sta. Rosa Hospital and Medical Center, Westlake Medical Center, and iHealth
Multispecialist Clinic. He completed an observership at Jules Stein Eye Institute UCLA, Retina
Division, under the tutelage of Dr. Anurag Gupta, and at Stanford University Medical Center,
Cornea and External Disease Division, under Dr. Christopher Ta. Dr. Castillo obtained his
certificate in aesthetic medicine in Singapore under the American Academy of Aesthetic
Medicine. He completed his residency training in Ophthalmology at Manila Doctors Hospital
where he graduated as the “Most Outstanding Resident”. He earned his medical degree,
bene meritus, at the University of Santo Tomas and Bachelor of Science in Biology, cum
laude, at De La Salle University-Dasmariñas.
ATENEO STUDEN T BU S I NES S REVI EW
71
Ma. Katrina Mae Garcia-Dalusong is the Director of Sales for the Inquirer Group of
Companies-Freezine and Commercial Magazine Business Unit. Prior to this position,
she headed the publishing and business development, and marketing and distribution
departments. She graduated with honors from Assumption College, San Lorenzo, with
a degree in Bachelor of Communications, Major in Advertising and Public Relations. She
received exemplary recognition for Best Thesis.
Rafi Delica is a Senior R&D Engineer at Excelitas Technologies. He graduated with a degree
of BS in Applied Physics from UP Diliman, and obtained his MS and PhD in Physics from the
same university after a research stint at Osaka University.
Atty. Anton Carlo E. Espino is a Senior Partner of the Delloro Espino & Saulog Law Offices.
He holds a degree in A.B. Economics from the University of Santo Tomas and a Bachelor
of Laws from San Beda College. He has a diploma in Real Estate Management from the
Consortium of De La Salle and Chamber of Real Estate & Builders’ Association, Inc. He
is a Licensed Real Estate Broker and Real Estate Appraiser (sixth placer) both under the
Professional Regulation Commission. He has been a consultant to the Legal Department of
the Quezon City Government for more than six years. Anton specializes in Criminal and Civil
Litigation as well as Labor and Real Estate Laws.
Gladys Estandian took up BS Accountancy at St. Louis University in Baguio. She is an
intercompany accountant in Chevron Holdings Inc., focusing on accounting and billing.
Edwin J. Falcotelo is a network specialist with 12 years of experience in the
telecommunication industry. He now works for Verizon as Lead Engineer under the
Enterprise Solution Organization. He is a certified Project Management Professional.
Moreover, Edwin has completed two graduate diploma courses from the Ateneo Graduate
School of Business-Center for Continuing Education, Leadership and Management
Development Program (Mini-MBA) and Applied Project Management.
Engr. Rosalie Battung-Formento earned her degree in Bachelor of Science in Chemical
Engineering from the University of the Philippines-Los Baños in 1999. She recently obtained
her Master of Energy degree at the University of Auckland, New Zealand, with First Class
Honors. She completed her academic units on her MS in Materials Science and Engineering
at UP Diliman. She joined DOST in 2002; in the past three years, she was the Assistant
Regional Director for Technology Operations of DOST-NCR. Rosalie manages various
energy- and environment-related projects and the programs of the Metropolitan Manila
Industry and Energy Research and Development Consortium–Energy sector, and leads the
technology transfer of various DOST-generated waste management technologies.
Eliza T. Guades is an Accounting Officer III at the Central Accounting Office of Ateneo
de Manila University. She obtained her Bachelor of Science in Accountancy degree from
Polytechnic University of the Philippines and passed the CPA Licensure Exam.
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AT EN EO S T U D E NT B U SI NE SS R E V IE W
Dong “Kimberley” Haiyan graduated from Henan University of Science and Technology in
China. She majored in International Economics and Trade and received her Bachelor degree
in Economics in 2007. She worked at Yinlu Bicol Mining Corp. from 2007 to 2011 as Executive
Secretary to the President.
Evangeline P.Y. Ho graduated with a degree in B.S. in Information Systems from Deakin
University Melbourne, Australia. A Manila-based Singaporean citizen, Evangeline has eight
years of experience in Sales & Marketing and Event Management. She worked for four
years at Koelnmesse Singapore, which is one of the world’s largest trade fair companies,
organizing annually more than 100 trade fairs, conferences, and events worldwide. She was
the Regional Sales Manager in charge of sales and developments with project management
responsibilities in Asia. She previously worked at Moevenpick Hotels & Resorts in Dubai
in the areas of Training and Quality. She is fluent in English and Mandarin, conversant in
Bahasa, Hokkien, and Teochew, and has a fair understanding of German and French.
Deanna Marie A. Lansangan is the Head of the Training Services Group of the Ateneo
Graduate School of Business-Center for Continuing Education. A Registered NutritionistDietician (RND), Deanna graduated with a BS degree in Nutrition and Dietetics from the
University of Santo Tomas. She has units in MA in Public Administration from UP Diliman.
She worked as a Training Manager at the Advocate of Philippine Fair Trade, Inc., a nongovernment organization funded by the European Union, the UK Government, and
CORDAID of the Netherlands that seeks to enhance the entrepreneurship of the food and
handicraft producers in the country.
Ricky Lascano has a BS Accounting degree from Guagua National Colleges and is currently
working as a fixed assets analyst at Chevron Holdings Inc.
Atty. Anita C. Mapalo graduated cum laude from UP Diliman, with a degree in B.A.
Philosophy. She proceeded to take up Law in San Beda College and completed the course
at the Ateneo de Cagayan-Xavier University. She has considerable experience in both
litigation and contract management, having served the Department of Justice through the
Public Attorney’s Office for seven years and the Procurement Unit of San Miguel Pure Foods
Company (SMPFC). She currently handles the procurement of local and domestic freight and
logistics services, and manages the Import Services Group of SMPFC.
Gladys Maliwat-Olano completed Accountancy at the Pamantasan ng Lungsod ng Maynila.
She had 12 years of experience in Finance with Dao Heng Bank, Cosmos Bottling, CocaCola Bottling, and JG Summit Holdings. She is a Senior Manager for Finance at ACS of the
Philippines, a Xerox Company.
Arleen M. Pacheco heads the Trade Marketing and Sales Administration Group of Fly Ace
Corporation, makers of category-leading food brands, such as Jolly Canola Oil, Claro Palm
Oil, Goodlife Noodles, Dona Elena Olive Oil, and Jolly Cow Fresh Milk. She has held various
Sales and Brand Management positions in her past companies, Splash Corporation and Big E
Food Corporation (makers of Lemon Square brand).
ATENEO STUDEN T BU S I NES S REVI EW
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Irene Palad graduated from the University of the Philippines-Diliman in 2005. Irene is a
Business Development Executive at SGS (Société Générale de Surveillance) Philippines, Inc.
She is tasked to expand SGS services for the Philippines and Guam through the identification
of client needs, and packaging SGS services that would best fulfill customer requirements,
objectives, and program. She is concurrently a trainor and second-party auditor on food safety.
Margaret P. Samson graduated from Sta. Isabel College, Manila, with a degree in Bachelor
of Science in Accountancy. She has 12 years’ work experience with Andersen Consulting, EVA
Airways Corporation, Deutsche Bank Knowledge Services, and currently with Accenture, Inc.
Analyn Teodosio is a Certified Public Accountant. She graduated with a degree in BS in
Accountancy, magna cum laude, from Colegio de San Agustin, Bacolod City, and was named
The Most Outstanding Accounting Graduate by PICPA and Pricewaterhouse. Ana works at
Century Pacific Group of Companies–Meat Business, manufacturer of the Argentina corned
meat brands.
Cong. Irwin Tieng is on his second term as a Representative of Buhay Party-List. His
legislations focus on the promotion of life and the welfare of persons with disabilities.
Among his famous legislations is the Anti-Photo and Video Voyeurism Act, otherwise
known as the Cyber-Boso Law. He has been awarded as the most consistent outstanding
congressman for 2010. In addition to his sterling record is his commissionship as reserve
officer of the Philippine Marines, Navy, and AFP with a rank of Lieutenant Colonel. Aside
from his dedication to government service, Irwin is also engaged in running various familyowned companies. He completed his Bachelor Degree in Business Administration at De La
Salle-College of Saint Benilde.
Arthur Roy Villones has more than 17 years of diverse industry experience in engineering,
information technology, banking services, and the academe. He has worked with a number
of multinational organizations, such as Intel, IBM, J.P. Morgan Chase & Co., and Citibank, as
well as local institutions, such as J.G. Summit Holdings and the University of San Carlos. His
latest position was VP for Solution and Support at Citibank, N.A. (Philippines). A certified
Project Management Professional, Art teaches Project Management. He has a degree
in Mechanical Engineering from the University of San Carlos, Cebu City, and a graduate
certificate for MS in Mechanical Engineering from the University of the Philippines-Diliman.
Mary Ann M. Viloria is the Country Marketing Manager of EMC Philippines. With more than
10 years of marketing experience, Ann has an extensive product marketing background from
Microsoft Philippines where she led the marketing business of Microsoft Dynamics ERP and
CRM while encompassing product management, channels, PR, and events management.
Prior to joining Microsoft, Ann established her own events company, V and M Creativemedia
Marketing. She earned her Bachelor of Science in Business Administration, Major in
Marketing from the Pamantasan ng Lungsod ng Maynila.
Mayelle C. Wycoco is an entrepreneur. She is the owner of Sona Spa, a wellness center
located in Tanauan, Batangas. She likewise works as Area Sales Manager for Alveo Land,
a subsidiary company of Ayala Land. She has a degree in B.S. Food Technology from the
University of Santo Tomas.
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ATENEO STUDEN T BU S I NES S REVI EW
75