Green Supply Chain Management:
Final Paper
Professor: Dr. Roland Geyer
Authors: Christian Del Maestro, Adam Rohloff
Servicizing the Computer Supply Chain: Potential Economic and Environmental
Benefits of Cloud Computing
February 17, 2016
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Del Maestro, Rohloff
The IT industry has recently been included as a significant actor in global greenhouse gas (GHG)
emissions, at approximately 2-3% of emissions, roughly equivalent to the international airline
industry [IUSE, 2009]. An ever increasing innovation cycle with shorter product lifecycles,
exponentially increasing demand for data and processing power, and more energy intensive
processing have fueled this emissions increase. We suggest a strategy that can substantially
dematerialize the industry by increasing computing utilization rates through centralization of
computing power, and distribution of computing as a service. This concept, cloud computing, has
been emerging for the past decade, but only to a certain degree, and without any evidence of
dematerialization. As an academic demonstration, we seek to show the potential that cloud
computing has to fully servicize the computing industry, significantly reducing material and
energy consumption while enhancing performance and productivity.
1 Cloud Computing
The concept of cloud computing can be implemented to varying degrees. In its most simple and
existing form, it offers online data storage on a remote server that can be accessed via the
internet. The next level of the cloud is where not only data but applications are accessed via the
cloud, known as software as a service (SAAS) or platform as a service (PAAS) deployment
[Right Scale]. This eliminates the need to install and manage the hardware-software interface
internally and can ease the burden of providing sufficient computing power and IT management
for a firm. Companies such as Google, Amazon, and Microsoft have begun investing in this type
of infrastructure, and Google Docs is a simplified application of this concept. The ultimate level
of cloud computing, known as infrastructure as a service (IAAS) is where software , operating
systems, and server hardware and infrastructure are all managed as a service within the cloud.
Computing resources can be distributed amongst one or many remote servers and computers, and
delivered via the internet to the end user.
The potential energy, material, time and cost savings for this ultimate form of cloud computing
are vast. The utilization rates of a common desktop in a business environment are between 1020% [Zhou, 2009]. By centralizing the computing power in the cloud, the need for end-user
processor power is minimized, and utilization rates can be vastly increased to as high as 80-90%
[Zhou, 2009]. Not only is this far more energy efficient, but reduces the material needs for
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procuring local machines. Instead of high performance desktops, thin- client machines can be
used that are vastly simpler, lighter smaller, and less energy intensive. Programs like Windows
Remote Desktop and GoToMyPC.com are the closest thing to true cloud computing that exists
today, however these services our not intended to necessarily replace your desktop, but to
complement it. Coordination between machine makers, software designers, and internet
infrastructure and bandwidth providers will have to continue to develop, so that a seamless IASS
service can eliminate the need for desktops.
2 Goal and Scope
The goal of our analysis is to show that even on a small scale, implementing the principles and
infrastructure of cloud computing to the degree of IAAS can reduce both environmental and
economic costs of computing. Additionally, because the benefits of cloud computing come
primarily from dematerialization and productivity increase, environmental and economic costs
are highly correlated.
The economies of scale of a national scale cloud computing infrastructure are a complex system
to simulate. For the purposes of our analysis, we chose to compare the life cycle of a collection of
100 traditional desktops vs. a network of 100 thin-client machines (w/server allocation) to
simulate a micro-scale version of a cloud. This 100 client cloud system is comparable to the
computing needs of a small business. Small businesses often do not have the capital to invest in
internal computing infrastructure and IT, and cloud computing would perfectly suit their needs.
Companies such as Right Scale are targeting these kinds of customers for their cloud services.
Full cloud computing for larger firms is less realistic, as they have their own IT capabilities,
higher utilization rates, and security concerns that would discourage cloud use, at least in its
infancy stages before security and lock-in issues are resolved [Right Scale]. The scope of our
analysis is small, and it should be recognized that economies of scale in a true cloud
infrastructure would further enhance the potential economic and environmental savings.
Our analysis looks at the life cycle of a thin-client + server, desktop, from material procurement,
pre-component and component production, final product assembly, use, and disposal. Our
quantitative analysis focuses on manufacturing and use phase environmental and economic costs.
Quantitatively we only consider global warming potential (GWP) as an environmental indicator
while waste, water, and toxicity indicators are described qualitatively. Our economic scaling
factor could be used for a quantitative comparison for the remaining environmental indicators.
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This is defensible as the major difference between the two supply chains is the use of less
material, which reduces costs over almost every link of the supply chain.
We purposely omitted the impacts of keyboards, monitors, and mice in our analysis, as these
would be necessary in both cases. We also do not calculate office cooling savings from using thin
clients. Thin client machines use considerably less power, and therefore distribute less heat than
traditional desktops into the office environment. This was difficult to quantify and left out of our
scope.
Baseline numbers for the environmental impact of the computer components and processing
(packaging, transport, manufacturing, etc) were derived from Williams (2004), and scaling
factors were used to compare our thin-client machine. Scaling factors included the: economic
factor, based on cost difference and used when no other data was applicable; transport factor,
based on volume (since density of thin client was roughly equal to desktop, volume was assumed
to be the constraining factor for transport costs); and packaging factor, based on surface area
difference. Power consumption requirements, used for use-stage calculations were based on
manufacturer specifications.
3 Description of the Supply Chain
Rather than individual supply chains descriptions, a simultaneous supply chain comparison is
more useful in this case because the actual stages of the supply chain are nearly identical. The
critical differences along most stages are less material and energy inputs, and so in most cases a
simple scaling factor can be implemented. The only supply chain additionality is the cloud
distributor stage, interjected between computer hardware distributor and end-user. Figure 1
describes the traditional supply chain of the desktop and identifies changes and reductions in
inputs when comparing the thin client cloud system. In most cases environmental and economic
consideration are linked to dematerialization and lower energy requirements.
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Figure 1 -Supply Chain of the Desktop vs. Thin–Client (w/ server share)
Supply Chain
Stages
Components, processes, inputs
Desktop (100)
Pre-component
manufacturing
(raw materials,
production)
Component manufacturing
(production)
Assembly
Transport
semi conductors,
circuit boards, silicon
wafers, other
Main board (fans,
CPU)
Drivers (HDD,
optical drives, power
supply) Cards
(memory, graphic,
sound, modem),
Casings ( Fan, Wire,
tower, other)
Packaging (box,
cushion)
Primarily energy
requirements
Mass, Volume,
packaging
requirements,
Thin-Client Cloud
Provider
Not part of traditional
supply chain
End Use
Desktop power
requirements (~130
Whr per user), and
maintenance
Disposal
(recycling, reuse,
landfill)
Volume, Mass,
materials toxicity.
Product life cycle, ~
3 years
Total Economic
Cost
$500
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Environmental
Considerations
Economic
Considerations
Less material
input, less
environmental
impact
Fewer
components,
simpler
components, less
environmental
impact.
Less material and
energy input,
lower costs
Less energy
requirements
Smaller mass and
volume, less
cushioning
because no
fragile optical
drives
Server, IT
management,
(server and
infrastructure)
Less energy,
smaller GWP
Less fuel, smaller
GWP
Same as above
Server impacts
are allocated
amongst thin
clients.
Thin client power
requirements
(~12 Whr per
user). Simpler
machine, less
maintenance
Less material,
less disposal.
Product Life
Cycle, 3-5 years,
as performance is
at server, not at
thin-client.
$350
GWP directly
related to power
requirements
Added link to the
supply chain.
Distributed server
costs and labor
costs (IT)
Costs related to
power
requirements and
maintenance.
Thin Client (100
+ Server)
Less input
(economic
scaling factor)
No fans, smaller
CPU, no HDD,
smaller power
supply, simpler
graphics card,
less casings, less
packaging, less
cushioning b/c no
fragile optical
and HDD drives
5
Less material
input and longer
lifecycle, less
environmental
impact.
Same as above
Same as above
Similar to
environmental
costs
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Del Maestro, Rohloff
3.1 Additional Value Considerations of Cloud Computing
The cloud distributor supply link indicates potential for innovation and business growth for this
sector, stemming from added value for the consumer as the computer is servicized. Besides
reducing economic and environmental costs, cloud computing provides additional performance
benefits, inherent to the cloud. In fact it is these performance benefits that are most likely driving
the current growth of the cloud computing industry, and not necessarily the environmental, or
even economic benefits. Some of these noted benefits include:
Significantly greater computing power by tapping into powerful supercomputer [Business Week,
2007] capabilities;
1. Lower cooling costs because less heat loss; less security (theft) concerns because thin client
machines have no value without the cloud;
2. Reduced labor costs because less requirements of on site IT department;
3. Greater mobility because of enhanced remote desktop capabilities;
4. Lower switching costs as upgrading computing performance does not require purchasing a
new machine.
5. Reduced office noise pollution w/o fans
It is important to recognize the possibility that cloud computing will not replace but supplement
(rebound effects) desktops because of the added performance benefits of cloud computing.
Consumers may retain their desktops, and simply add cloud computing capabilities to it.
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6. Environmental Valuation
3.2 Methodology and Scaling Factors
Inventory values for modeling in this analysis were used from Eric Williams’ study titled ‘Energy
Intensity of Computer Manufacturing: Hybrid Assessment Combining Processes and Economic
Input-Output Methods’ published in the Environmental Science and Technology Journal (2004).
No data was available to assess the environmental impacts of the thin-client unit. A series of
scaling factors were calculated to adjust the desktop inventory values from Williams 2004 to
estimate the impact from the manufacturing of a thin-client.
3.3 Economic Scaling Factor
Because the energy inventory for manufacturing is only available for a desktop, an economic
scaling factor was used to project the environmental impact of thin-client manufacturing. The
thin-client has fewer printed circuit boards, no hard disk, no fan, slower processor speeds and less
overall components which result in an overall lower environmental impact from manufacturing.
The retail prices were used for the two machines to calculate the economic scaling factor. The
implied assumption is that if a good costs more, it will contain additional materials and embedded
energy. The prices and scaling factor are provided below:
Type
Desktop
Thin Client
Model
Dell Optiplex 745 [Optiplex]
HP T5145 [T5145]
Price ($)
482
200
Picture
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Equation 1 - Economic/Environmental Scaling Factor
Desktop price
ThinClient price

$482
 2.41
$200
i. Sample Calculation
Desktop computer assembly requires 35.5 MJ of direct fossil energy and 51.2kWh of electricity
[Williams 2004]. Using the economic scaling factor, the impact of the thin client’s assembly
process can be projected:
35.5 MJ
2.41
 14.7 MJ
51.2 kW h
 21.2 MJ
2.41
Full series of calculations found in Table 2.
3.4 Power Usage Calculation
The inventory values for the desktop are several years old (2004), so an adjustment was required
to account for the increased power efficiency of a newer machine. The electricity used in the use
phase was calculated with the specs for the machines in this analysis.
Type
Desktop
Thin Client
Server
Model
Dell Optiplex 745
HP T5145
2DLW Serv N20
Energy Demand – Active (watts)
123
11.4
865 (full utilization)
Energy Demand – Sleep (watts)
3
1
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Instantaneous Power Demand for Thin Clients
and Desktops
140
120
watts
100
80
60
Server
Allocation
40
20
0
Thin Client + Server Allocation
Desktop
Figure 2
(OfficeWorkday hours * Powerwatts  Idle / Night hours * Powerwatts ) *
kWh
 UsePhaseDemand kW h
1000
Equation 2-Thin Client Power (Use Phase- 1 Year)
(2080 *11.4  6680 *1) *
1
 111kW h
1000
Equation 3 - Desktop Power (Use Phase - 1 Year)
(2080 *123  6680 * 3) *
1
 276 kW h
1000
Because the server powers multiple thin-clients simultaneously, an allocation was used for an
accurate comparison (Figure 2).
3.5 Transportation/Logistics Scaling Factor
There are considerable environmental gains that can be achieved with respect to transportation
logistics.
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Type
Desktop
Thin Client
Model
Dell Optiplex 745
HP T5145
Dimensions (inches)
4.5x15.7x13.9
7x7x2
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Volume
982
98
Packaging Surface Area
702.86
154
Mass (lbs)
23
3
The size of the thin-client is considerably smaller than the standard desktop used in this analysis.
In addition, the mass of a thin-client is only 3lbs compared to the desktop that weighs 23lbs.
More units can be packed into the same container volume and shipped from OEMs to distribution
outlets and consumers.
Equation 4 - Transportation Scaling Factor
VolumeDesktopBox
VolumeThin _ ClientBox
 TransportScalingFact or 
982 Inches3
98 Inches3
 10
For every desktop that is shipped, it is estimated that 10 thin-clients can fit in the same volume of
a container or package. To ensure that mass would not be an additional constraint while shipping,
the weights of each shipping box are compared:
Mass of 10 thin-clients
Mass of 1 Desktop
3lbs*10=30lbs
23lb
The mass is not significantly more for the grouped package, so the likely shipping constraint is
the volume of the container.
3.6 Packaging Scaling Factor
The smaller packages that return transportation gains also require less packaging for shipping. To
calculate the packaging scaling factor, the surface area of material that is required to package the
container was used.
Type
Desktop
Thin Client
Model
Dell Optiplex 745
HP T5145
Packaging Surface Area
703 inches
154 inches
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3.7
SurfaceArea DesktopBox
SurfaceAreaThin _ ClientBox
Del Maestro, Rohloff
 PackagingScalingFact or 
703 Inches3
154 Inches3
 4.5
3.8 For each box shipped, it is estimated that 4.5 times less packaging will be
required due to the considerable size differential.
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Impact and Energy Requirements
Table 1
Color
Data Source
Scaling Factor
Data from Williams 2004
n/a
Calculated from Economic Scaling Factor
2.41
Calculated from Transport Scaling Factor
10
Calculated from Packaging Scaling Factor
4.56
Calculated from Manufacturer Power Specs
n/a
Table 2
Production
Desktop
Thin Client
Direct Fossil
Direct Fossil
Use (MJ)
Use (MJ)
Desktop
Thin Client
Electricity
Electricity (kWh)
(kWh)
Production Analysis
Semi Conductors
Printed Circuit Boards
298.00
123.65
170.00
70.54
26.70
11.08
7.71
3.20
38.10
15.81
Bulk Materials: Control Unit
Silicon Wafers
Computer Assembly
35.30
14.65
51.20
21.24
381.00
158.09
18.50
7.68
Equipment
392.00
162.66
29.40
12.20
Passive Components
109.00
45.23
10.30
4.27
Disk Drives and Parts
365.00
0.00
23.00
0.00
Transport
338.00
33.80
3.50
0.35
Packaging
120.00
26.32
4.80
1.05
Other Processes
973.00
403.73
61.00
25.31
Total Production
3038.00
979.20
417.51
161.66
Use Phase
275.88
111.36
Total Production + Use Phase
693.39
273.01
IO Analysis
Electronic Chemicals
Semi Conductor Manufacturing
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The energy inventories from Table 2 are used to estimate the global warming potential (GWP) of
desktop and thin-client use and manufacturing.
Table 3 – Coefficients provided by PE International GaBi4.3
Type
Coefficient
Unit
Electricity Generation (US Average)
0.804
Kg/kWh
Fossil Fuel Use
0.223
Kg/MJ
Greenhouse Gas Equivalent for Production and Use
Phases for Computers
1800
kg CO2equivalent
1600
1400
Server Production
Allocation
1200
Use Electricity
1000
800
Production Electricity
600
Direct Fossil use
400
200
0
Desktop
Thin Client/Server
Figure 3 – Use phase is estimated to be three years.
Total Impact for Small Business with 100 Machines
180000
160000
kg CO2 Equiv.
140000
120000
100000
Desktop
Thin-Client
80000
60000
40000
20000
0
Figure 4
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7. Economic Evaluation of Thin-Clients
The following scenario assumes that a business purchases the server for the internal computation
and storage power to run a small company.
Type
Desktop
Thin Client
Server
Model
Dell Optiplex 745
HP T5145
DLW Serv N20
Price ($)
482
200
4000
The server can handle the computational power of approximately 20 machines performing
common business tasks and applications (Linux Terminal Service Project 2009). The cost of the
server is allocated at a ratio of 1/20.
Equation 5
CostAllocation 
ServerCost $4000

 $150 per _ workstation
ThinClient s
20
Life Cycle Cost of Desktop and Thin Client/Server
Allocation
$700
$600
Cost ($)
$500
$400
Electricity Cost
Unit Cost
$300
$200
$100
$Thin Client + Server
Allocation
Desktop
Figure 5 - Cost for three years of operation
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A rate of 10% was used to discount the electrical cost cash flows on an annual basis. If a
company purchased the equipment internally (server + thin-clients) the cost savings would be
significant over the three years. For a typical small business with 100 machines, the savings
returned would be approximately $20,000 over three years.
Disposal
The economic costs of disposal were not quantitatively evaluated in this analysis. Because the
thin-clients are smaller and have less components, disposal costs will likely be lower, and could
be estimated using our economic scaling factor.
Computing as a Service:
If the computational power and data storage services were provided by an external agent even
greater efficiency gains would be obtained through increased optimization and economies of scale
for cooling. In addition, a small company would need less internal information technology staff
to run their systems if the servers were offsite.
The utilization rate for the server’s computational power would increase because the cloud
service company can take advantage of national economies of scale. The peak computational
demand required by businesses would be more evenly distributed because of the time zones in the
country. A three year time span was used for this analysis, but there are no technical constraints
limiting the thin-client to such a short-lifespan. It is feasible that the hardware could last much
longer (5+ years) because they are not as performance-dependent as a desktop machine. The
servers can be upgraded centrally rather than the individual desktop machines, but with the thinclient setup, users still receive the same unit of computing at their desks.
If the internet can reliably and quickly route business machine computational power, the market
for traditional desktop machines could be affected. Companies that provide desktop business
machines (Dell) would need to shift their business models. A greater reliance on highperformance centralized servers will likely drive the market for computing in coming years.
Innovation in computational service contracts will emerge and small companies will have less
risk investing in IT equipment. Cloud providers could provide the thin-clients for free or a
monthly rental rate similar to the approach currently utilized by cable companies. Because the
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thin-clients do not need to be upgraded as frequently because computation occurs offsite, cloud
providers could re-use thin-clients further decreasing the environmental burdens.
8. Economic and Environmental Evaluation
This case study represents the coveted win-win outcome of strategic supply chain management.
The switch from traditional desktops to thin-clients returns both environmental and economic
savings. The strong linear correlation between economic and environmental benefits from thinclient implementation verifies the pollution prevention benefits of dematerialization through
decreased resource use.
Economic and Environmental Evaluation of ThinClients Compared to Desktops
100%
80%
60%
60%
40%
31%
20%
0%
Economic Savings
Environmental Savings (GWP)
Figure 6
In an alternative study, the cost savings with 175 thin-clients returned an economic savings of
€660 or 28% (IUSE 2009). The IUSE study included disposal costs that were omitted from this
study.
Type
100 Client Cloud Simulation
IUSE Study(175 client)
Scope
3 years
5 years
GWP (kg) per machine
1679
1220
GWP (kg) per year
560
244
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There are many factors that were outside the scope of this analysis, but it is likely that in most
cases the un-quantified aspects will provide additional environmental and cost savings for the
thin-client option.
9. Constraints and Challenges
3.9 Reliability and Security
With any reliance on new technology, businesses may be hesitant to fully move to a cloud based
thin-client service. If all computational and data storage is provided live in the cloud, a business
is completely reliant on their internet connection. If for any reason the internet goes down, all the
workstations would be effectively useless and productivity would suffer.
Businesses may also be wary of outsourcing their sensitive data to external third party companies
that provide a cloud service. Privacy issues could hinder deployment of full cloud computing as
the importance of data security can trump potential economic and environmental gains.
3.10 Switching Costs
If computation and data storage is provided as a service, there could be considerable business
costs required to switch service providers. Businesses would essentially be locked into their
service provider and even if another company could offer cheaper rates, a considerable
transaction cost would have to be considered.
3.11 Scope of Analysis
The only indicator used in this analysis is global warming potential. There are other
environmental impacts in computer manufacturing such as human and aquatic toxicity that are
important to consider. As much as 70% of the human toxicity impact occurs during the disposal
stage of the extended supply chain [Byung-Chul et. al 2004]. However, because the switch to
thin-clients (and the cloud) is essentially a dematerialization strategy for pollution prevention, all
of these other environmental impacts associated with component manufacturing will be reduced.
When data storage and computation is provided as a service that is routed through the internet,
additional network components and electricity will be required. This study omits the impacts
associated with an increasing demand requirement for internet infrastructure.
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3.12 Uncertainty
The raw values for energy requirements for PC manufacturing published by Williams 2004
already have embedded uncertainty and then they are scaled again in this study to account for
thin-client manufacturing impacts. There is a considerable error margin with our projected GWP
reduction of %60.
10. Conclusions
The dematerialization strategy for altering the IT supply chain with thin-clients and computing
resources in the cloud can return both environmental and economic savings. The suggestion in
literature [Williams 2004, Byung-Chul et. al 2006] that increased PC reuse rates and
upgradability potential will lead to environmental savings is correct, however no trends in this
area are emerging. The usage of thin-clients and cloud computing may turn out to be the
preferable route to reduce the environmental impacts of computing. The issue of computer
obsolescence may become less of an issue because the thin-client’s performance can increase
with additional computational resources from remote servers. This effectively extends the life of
the equipment used in office computing as computational services in the cloud can always be
upgraded. Computing as a service is an exciting proposition and will potentially grow as internet
bandwidth becomes cheaper, faster, and more reliable. The switch to the cloud also has the
ability to promote innovation and entrepreneurship because small businesses and start-ups will
face much lower capital costs for IT and computing. A large focus with computing revolves
around the energy-efficiency of chips, however the cloud provides a path for dematerialization
that does not rely on re-use and upgradability.
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11. Sources
Choi, Byung-Chul, Hang-Sik Shin, Su-Yol Lee, and Tak Hur. "Life Cycle Assessment of a
Personal Computer and its Effective Recycling Rate." Int. J LCA 11 (2006): 122-28.
Computing Heads for the Clouds 16 Nov. 2007. Business Week. 5 June 2009
<http://www.businessweek.com/technology/content/nov2007/tc20071116_379585.htm>.
Linux Terminal Server Project. 2009. LTSP.org
GaBi 4.3 Software. PE International. 2009.
Environmental Comparison of the Relevance of PC and Thin Client Desktop Equipment
for the Climate, 2008. Fraunhofer Institute for Environmental, Safety and Energy
Technology, UMSICHT.
Williams, Eric. "Energy Intensity of Computer Manufacturing: Hybrid Assessment Combining
Process and Economic Input-Output Methods." Environ. Sci. Technol. (2004): 6166-174.
Why Right Scale: Cloud Portability, Right Scale. Accessed June 5th, 2009
<http://www.rightscale.com/products/advantages/cloud-portability.php>
Zhou, Ben. "Cloud Computing." Personal interview. USCB. 03 June 2009.
HP Compaq t5145 Thin Client. Brochure. 5 June 2009
<http://h20195.www2.hp.com/v2/GetPDF.aspx/c01555466.pdf>.
Dell Optiplex 745 Tech Specs. Brochure. 5 June 2009
<http://www.dell.com/downloads/global/products/optix/en/opti_745techspecs.pdf>.
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