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International Journal of Management (IJM)

Volume 6, Issue 8, Aug 2015, pp. 57-70, Article ID: IJM_06_08_007

Available online at

http://www.iaeme.com/IJM/issues.asp?JTypeIJM&VType=6&IType=8

ISSN Print: 0976-6502 and ISSN Online: 0976-6510

© IAEME Publication

___________________________________________________________________________

TOTAL COST MODELLING AND

STRATEGIC SOURCING STRATEGIES FOR

DATA CENTRES IN UPCOMING ERA

Dnyanesh Sarang

Sr. Manager – Sourcing Analytics, Global Indirect Purchase Organization

Sandvik Asia Pvt Ltd, Pune, India

Srikanth Pingali

Asst. Manager – Sourcing Analytics, Global Indirect Purchase Organization,


Giri Ganesh

Asst. Manager – Sourcing Analytics, Global Indirect Purchase Organization,


ABSTRACT

The developing demand for IT resources from organizations that are

constantly increasing and improving their businesses adds significant pressure

on data centres. Industry predictions show that data centre traffic will

increase at a CAGR of 23% till 2018, and their workload will increase by 14%. A certain growth in data centre investments will be witnessed along with

the improving economy and increasing demand. For many organizations, it

becomes essential to frame a robust sourcing strategy to control their data

centre requirements. Depending on the organization’s IT demand, the strategy

should help them figure out whether to build a data centre or choose

colocation services. In both cases, a number of cost elements add onto the

high costs of the facility. A total cost of ownership (TCO) model is a viable

tool to estimate the overall costs involved in a data center facility.

Additionally, all data centres should be mindful of maintaining a data

migration strategy and also plan out the lifecycle of the data centre which

could potentially reduce the operating and or remodeling costs of a data

centre. The lifecycle strategy for a data center should account for future

planning in terms of space, cooling, airflow, electricity planning and next

generation equipment. This could be achieved by incorporating key elemental

tools and systems for capacity utilization and energy management. A design

based strategy that could be helpful for smaller organizations would be

modular data centre design, which could adapt and grow along with the

growing demand. With a modular design in place, the facility could evolve

Dnyanesh Sarang, Srikanth Pingali and Giri Ganesh


into a hybrid data centre that includes cloud, colocation and merged services.

This could be developed into a revenue source for the organization with time.

Keywords: Data Centre, Total Cost of Ownership, Strategy, Modular Design

Cite this Article: Dnyanesh Sarang, Srikanth Pingali and Giri Ganesh. Total

Cost Modelling and Strategic Sourcing Strategies for Data Centres in

Upcoming ERA. International Journal of Management, 6(8), 2015, pp. 57-70.

http://www.iaeme.com/IJM/issues.asp?JTypeIJM&VType=6&IType=8

1. INTRODUCTION

Data centre has become an integrated part of IT department operations of every

organization. Increasing data creation and operations, with new product and

application development is creating a steady demand for data centres within these

organizations. In this dynamic scenario, smaller organizations rely on colocation

services to meet their data centre needs; however, this is expected to change resulting

in many companies trying to set up their own data centres

1.1. Market Growth

In 2013, Cisco Global Cloud Index predicted a 23% CAGR growth in global data

centre traffic between the period, 2013 to 2018, as shown in Graph 11.

Graph 1 Global data centre traffic growth predictions1

The report also predicts that by 2018, the usage of cloud based data centres will

have increase by 32% CAGR per year, reaching 6.5 zettabytes per year usage. A

global split of 76% usage towards cloud based and 24% usage towards traditional data

centres. Globally, IT services industry sector would be the largest consumer of data

centre services, accounting for 28% data centre tenancy share. As seen in Graph 2,

Telecom services and financial services are also significant contributors in data centre

tenancy2.

3.1

3.8

4.7

5.8

7.1

8.6

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

2013 2014 2015 2016 2017 2018

Zet

tab

yte

s p

er y

ear

Global Data Centre IP Traffic Growth

Total Cost Modelling and Strategic Sourcing Strategies For Data Centres In Upcoming ERA


Graph 2 Global data centre tenant diversification2

In terms of the operational space required for a data centre colocation services,

which are the most famous data centre service type currently at a global scale, we

notice in Graph 3, North America is the leader accounting for about 42% of market

share globally3. This trend is likely to change in the next 5 years owing to the

developing demand in Asia and Latin America. This growth will be fuelled by the

improving global economy that is likely to bring gradual investments for data centre

setup and operations.

Graph 3 Global colocation market share in terms of operational space3

By analysing the country level growth of data centres in Graph 4, it could be

understood that most data centre service providers such as Amazon, Digital Realty,

Equinix, etc. are strongly expanding in developing countries such as Brazil and China,

anticipating the growth in demand from these regions4. This also adds pressure on the

energy requirement for the operation of these data centre additions.

28%

27%

19%

6%

20%

Data Centre Tenant Diversification

IT Services

Telecom Network Providers

Financial Services

Internet Enterprise

Other Corporate Enterprise

42%

27%

26%

6%

Global Colocation Market

NA APAC

EMEA LATAM



Graph 4 Country level data center growth rates4

2. NEED FOR THE STUDY

As a step toward gaining a better understanding of the sourcing strategies of Data

Centers, this study is designed to analyze the optimal cost model for data centers. The

study also propose the sourcing strategies for data centers together with cost model

proposed. It explains the details of various vertices of sourcing strategy and their co-

relation proposed.

3. OBJECTIVES OF THE STUDY

Two questions were identified to guide the study:

To propose valid cost model for sourcing Data Centers

To propose sourcing strategy for sourcing Data Centres in upcoming years.

4. COST MODEL FOR DATA CENTRES

4.1. Value Chain of Data Centres

The value chain of a data centre, as seen in Fig.1, provides the high level

understanding of all its active participants. Based on the EBITDA margin analysis

during the period 2009 – 2013, it was observed that Data Centres enjoy 43% profit

margin, the second highest grossing service in Europe during that period5. With an

anticipated growth in demand, along with the high profit margins, data centres prove

to be a viable investing opportunity for most companies.

Figure 1 Data Centre Value Chain

3%

3%

6%

9%

9%

10%

11%

14%

0% 5% 10% 15%

Nethelands

Nordic

Germany

UK

China

Singapore

Brazil

Ireland

Country level Data Centre Growth



4.2. Total Cost of Ownership (TCO) of a Data Centre

There are several cost factors that strongly impact the setup and operation of a data

centre. Refer graph 5 bellow.

Graph 5 Data centre high level cost breakdown6

Property costs such as leasing, maintenance and property related operating expenses

are the key cost components that affect a data centre setup and operations. From Chart

5, we can see that Property costs account for 34% of the overall costs6. Depreciation

of asset value and other amortization costs contribute to a significant bearing on the

overall costs of a data centre, accounting for about 25%. These costs are not merely

associated with the core components of a data centre, but throughout the operation of

a data centre, most components such as backup generators, alternative cooling

systems are installed to prevent any incident during power outages. Such backup

equipment is subjected to regular maintenance and there are costs associated towards

any software and hardware requirement.

Other significant data centre cost drivers

Recurring cost of energy

Among the overall substantial utility costs incurred in the operation of a data centre,

the most significant would be the electricity costs associated. However, it is tricky to

understand the exact costs associated with energy, as they are generally combined

together with broader facilities management costs7.

Cost of Servers: Server capacity is predetermined by the amount of operational space

available in the data centre. In the future, upon increase in demand for the data centre,

the rack space required to hold the server capacity will directly correlate towards the

area space that needs to be expanded.

Existing Storage Costs

The storage capacity within the data centre is considered to be a combination of the

high-performance arrays for transactional applications.

Communications Network Costs

The networking within the data centre is accounting as the internal communications

which includes most common components such as LAN, cables, tools, switches and

their maintenance

34% 25% 18% 19% 4%

0% 20% 40% 60% 80% 100%

Cost Breakdown of a Data Centre

Property

Depreciation & Amortization

SGA

Operating Income

Others



Software Costs: System management software, operating system and other security

licenses, storage management and other operational tools comprise of the overall

software used inside the data centre.

4.3. Data Centre pricing

There are different pricing standards for a data centre, depending on the service type

chosen8; however the basic components of the pricing include

Initial costs – costs for the services used in a data center

Lease period – contract period between supplier and customer

Quality of service – depends on value added services provided

Resources – the age of the facility and resources will impact the price

Maintenance costs – any maintenance costs involved in the overall operation of the

data centre

Based on the above components the various available pricing mechanisms

prevalent across the data centre services industries are seen in Graph 6. Globally,

fixed term contracts are more prevalent when purchasing data centre services.

Graph 6 Primary pricing mechanisms for data centers8

TCO = Cost (IT capital) + Cost (site infrastructure) + Cost (energy) + Cost

(operation)

5. SOURCING STRATEGY FOR DATA CENTRES

A clear data centre sourcing strategy helps to identify the ideal data centre type that

can fit into the organizational requirement. These strategies are developed to address

growth of data operations, see Figure 2, which is likely to increase above the current

capacity and energy utilization, along with the probable increase in risk, or the need

for lowering the cost of operation. There are many data centre service options

available for organizations to choose from in the market. A strong sourcing strategy is

necessary to identify the data centre types that fit into their requirement9.

36%

28%

20%

6%

5% 5%

Primary Pricing Mechanisms for Data Centres

Fixed

Performance based

Cost plus

Time & Materials

Index-based

Rebate



Figure 2 Key factors to target while framing a data centre strategy9

5.1 Use of Data Centre

It is very critical to identify the role performed by a data centre within the

organization, before building/leasing it. The data centre evolution should be

understood, which can help invest in a data centre service that can be useful even for

the future business needs of the organization10

.

Figure 3 Data Centre selection matrix10

The basic criteria in selecting the right data centre involve in the assessment of the

selection matrix; see Fig 2.

Innovation – the data center should be able to keep up with the application and

process innovation that happens in the business environment of the organization

Availability – higher storage space available to keep up with the increased data that

is being generated, and the data that would be generated with the increasing demand

Intelligence – intelligent data centers would be capable of not only storing and

processing the data in the organization, but would also assist in product development

Risk – data centers built to manage risks related to data security and other forms of

data attacks

5.2. Financial Evaluation of Data Centre options

The investment required for a data center is subject to change depending on the type

and requirement of the data center. This investment can be evaluated by the available

options of data centers10

, as shown in Table 1. It should also be noted that while

considering the financial evaluation of a data center, the overall tax associated with

the operation and setup of data center should also be considered.



Table 1 Financial evaluation for data centre options10

Type Capital Cost Lifecycle Value Expenditure

Traditional

Modular

Lease

Managed Services

5.3. Data Centre Type Selecting Strategy

The following flowchart considers all the parameters that aid into making a decision

for selecting a suitable data center design, while accounting for the buyer’s

requirements.

Figure 4 Data center type selection flowchart



5.4. Strategies to manage TCO of Data Centre

Data centre costs are largely proportional to the economies of scale principles. A

better advantage could be leveraged from the overall spend, and benefit from the non-

linear growth of costs in line with earning potential could be observed8.

5.4.1. Capacity Utilizations

Improving vertical utilization would improve the efficiency of managing the physical

capacity in a data center, by spreading the fixed costs

Server consolidation can improve the effective CPU and server utilization, by which

the purchase of additional hardware can be delayed. Server consolidation reduces

capital expenditure, and also decrease storage complexity, which causes lower

administrative and labor costs

5.4.2. Energy Management

Incorporating the early usage of data monitoring systems such as energy intelligence

systems or energy management systems with regular energy audits

Setting up the data centers in areas with low energy costs would be the ideal way to

start the low energy consumption from the inception of the data center

5.4.3. Collaboration

In a buyer specific aspect, collaboration with other buyers with similar data center

needs could prove to be an effective way of reducing costs

Participants could pool their resources and demand, and share the procurement

burden

5.4.4. Operational Improvements

Process reforming by the implementation of CRM solutions that could aid the

improvement of marketing & sales process and modular data center solutions

Further advantages of having a CRM solution is that the planning for capacity

expansions can be planned more effectively, that could ease the pressure on

operational expenditure

Improvements in hardware & software technology directly improve the process

automation and create operational visibility throughout the data center. These

increase operational efficiency and bring down operational costs

5.5. Pricing Strategy

Most data center suppliers tend to take advantage of their buyers who do not

understand the various loopholes in a pricing strategy8. It is essential that buyers

analyses the basic supplier tactics and gain knowledge on the pricing mechanisms

depending on the type of data center pricing they opt for,

Limited Cost Visibility: Transparency in costs is limited when engaging with

suppliers for bundled pricing contracts.

Power Reselling: Suppliers without proper power tracking systems tend to resell

power to buyers at a profit

Power metering: As mentioned above, suppliers tend to neglect metering power

usage per rack used by buyers. This leads to buyers paying more on their price per

power consumption pricing structures. This can be eliminated by ensuring a metered

tracking of power at every rack.



Incentives: Most colocation data center service providers offer incentives and other

gain sharing schemes for their buyers. These are dependent on the performance the

data center. Buyers could identify such providers in the markets to take advantage of

such offers.

5.6. Key metrics for Data center, pricing structure and supplier selection

There are certain metrics that buyers should refer to before deciding on the data centre

and its respective supplier.

5.6.1. Metrics for data centers

Power Utilization Effectiveness (PUE): The ratio of incoming energy in a data

center, to the energy that is used by the IT equipment11. This is termed as “useful

energy” inside a data center, and the energy used by auxiliary equipment such as

cooling systems is considered to be wasted. A PUE value of 1 would mean that all of

the energy coming inside the data center is useful. Any data center with its PUE value

close to 1 is considered to be performing well, and could bring down on the energy

costs.

Carbon Usage Effectiveness (CUE): The ratio of total CO2 emissions caused by the

total incoming energy of a data center, to the total energy used by IT equipment in a

data center12. It is measured in kgCO2eq per kWh. The ideal value of CUE is zero,

and data centers with CUE value close to zero are considered to be sustainably

designed to release minimum carbon emissions. These data centers enjoy the benefits

from CO2 emission taxes.

Vertical Space Utilization (VSU): The effective space utilization of a data center can

be measured by the effective space utilized by the IT equipment, to the total space

available for the IT equipment13

. In ideal cases, the VSU percentage unit should be

close to 100%, i.e. all available space is used for IT equipment. In practical cases

however, this is never achieved, as space is consumed by auxiliary equipment that is

not available for the IT equipment. A data center with a VSU closest to 100% can be

termed to be using its available space very effectively.

Water Usage Effectiveness (WUE): The ratio of annual water usage at the data

center, to the total energy used by the IT equipment in the data center is termed as

WUE14

. This metric is measured in L per kWh. An effective data center design would

have a WUE value of zero, which infers that the total water consumed in the cooling

activities inside the data center is minimal.

5.6.2. Metrics for Pricing Structure

The buyer’s strategy should consider all the clauses that are present in a supplier’s

pricing mechanism for any type of data centre. Specific clauses could mention a



revision of the pricing charges, if the supplier faced with a substantial change in his

operational expenses.

5.6.3. Metric for Supplier selection

A buyer should evaluate the available suppliers of data centers on the following

metrics8,

Flexibility & Scalability – supplier’s capability to expand the data center facility

based on the capacity requirement, with minimal disturbance to the buyer’s

operations

Security & Risk assessment – supplier should conduct regular risk assessment

analysis and take the necessary security measure to protect the buyer’s data

Local & compliance – Buyer’s should ensure the data center location protects it’s the

facility from power disturbances due to the absence of continuous energy and water

supply. Also, the supplier should be complying with the local environmental

regulations.

Energy Consumption – The data center’s design and technology should be

consuming the least electricity while providing a quality service.

Availability – All data center utilities and storage space should be available at 100%

capacity for the buyer’s operations

Administration – An effective administration that regularly monitors the data center

for any unpredictable incidents, and provide instant management solutions

TABLE 2 Qualitative Supplier Selection Metrics9

Parameter Metric 1 Metric 2 Metric 3 Metric 4

Energy Rates Sustainability Reliability Free Cooling

Communication Diversity Relative Costs Latency

Labour Availability Relative Costs

Facilities Control/ Leasing

Accessibility Transportation Door-to-door time

Support Services Proximity to

vendor

Environmental

Risk Seismic Volcanic Hurricane/Tidal Severe Weather

Incentives Enterprise Zones Sales Tax Energy rebate

5.6.4. Data center service selection by Analytical Hierarchy Process (AHP)

To tackle a complex decision making process, any method employed should be able

to break the key issues into smaller elements that could be arranged in a hierarchy

format15

. Analytical Hierarchy Process applies prioritization information on the

problem elements in the hierarchy. Thus AHP derives the final decision without

relying on the biased criteria, but by using a pairwise comparison of the available

alternatives16

. Using AHP, the decision making process is segregated into four steps17

,

Step 1: Mapping the problems hindering the decision

Step 2: Identifying the technique for measurement

Step 3: Collecting the data



Step 4: Determine the normalized weightage of elements, and synthesize the ideal

solution

Application of AHP in selecting Data Centre service type18

Level 1: Setting the goal – Selection of the Data Centre service type

Level 2: Identifying the strategic problems associated with the selection process – eg.

Cost, Quality

Level 3: Breaking down the strategic problems into criteria. eg. Cost could be broken

down to Operational and Capital

Level 4: The criteria from level 3 are further broken down into elementary sub criteria

that in turn affect the overall strategic problem. eg. Operational cost could be broken

down further into cost of utilities, cost of maintenance, cost of depreciation and

amortization, etc.

Level 5: Consider the alternatives for each segment i.e. what are the data centre

service options available in the market eg. Cloud based Colocation, Hybrid,

Traditional, etc.

At each level, a pairwise comparison of the elements is done, followed by

assigning weightages based on prioritization. This would yield local weightage for all

elements in the hierarchy matrix. A global weightage score is then calculated from the

overall matrix scores. This score would vary for the different type of available service

types, as the prioritization of their elements would be different. Comparing the overall

global weightage of the service types would provide the solution as to which service

type would be ideal.

5.6.5. Modular Data Centre Design

Based on the TCO models created over the years, many strategies to control the

overall costs of TCO have been identified. These include basic strategies such as

improving the overall efficiency, rightsizing the data center, improved planning, etc.

Based on many observations, the savings on TCO for several scenarios were

noticed19

.

TABLE 3 Scenario based percentage TCO saved19

Scenario % of TCO saved

Power equipment with higher electrical efficiency 2%

Reducing electric rate 3.5%

Effective cooling performance 5.3%

Real Estate available for free 10.2%

Owning capital equipment (reducing standard equipment by 50%) 11.3%

Modular design 56.1%

A modular design for a data centre could be defined as a building block design

solution that could be expanded depending on the requirement, with the addition of

standard sections20

. This design style would reduce the space and power requirement,

along with the operational costs. However, such a design would not be feasible at the

current demand scenario. Nonetheless, it is most important that data centre designs are

made to achieve practical scalability with modularity, in order to gain better savings.



The design of several data centre components such as the power systems, air

conditioning can be deployed to achieve practical scalability. It must be understood

that many cost components in a data centre are not scalable with time such as the

space, engineering costs etc.

Modular data centre designs could lead to the development of hybrid data centres

that would house both cloud based, colocation and merged services under a single

roof.

6. STRATEGIC ROAD MAP FOR DATA CENTERS

A complete strategic roadmap for a data centre can be defined by considering the

current state of the data centre and the future state of the data centre. The roadmap

will prioritize the actions that need to be taken in order to achieve the future state of

the data centre. The future state of the data centre should consider all aspects of

growth in demand, growth in capacity requirement, change in environmental policies,

energy and water availability, and their pricing.

Figure 5 Strategic map to accommodate all forms of data centre types21

7. CONCLUSION

Data centers are complex business facilities that have become an essential part of

many organizations. A strong growth in the demand for data center services is

predicted in the upcoming years due to the increase in data creation and the need for

robust data center architecture that can facilitate innovation in growing organizations.

For outsourcing or designing a data center, developing a sourcing strategy becomes

inevitable. This strategy is formulated by understanding the basic objective a data

center would serve in an organization and the right type of data center is identified. A

total cost of ownership analysis would reveal the underlying cost drivers, using which

a strategy to tackle these expenses could be developed. While seeking data center

suppliers, there are many metrics corresponding to the contracts and pricing structure

that could be studied and implemented in the sourcing strategy. In essence, a sourcing

strategy provides a roadmap for organizations to reach their data center goals in a

specific period of time. Finally, an analytical hierarchy process could be used to

decide upon the right data center provider.

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published by Cisco Public.

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[3] 451 Research’s Data Centre Knowledge Base Q1 2015, 2015, published by 451

Research

[4] Gary Cook, “Clicking Clean: How companies are creating green internet”, 2014,

Greenpeace Inc.

[5] Iqbal Singh Bedi, “Data centres are one of the most profitable infrastructure

investments”, 2014, Analysys Mason Research Insight

[6] QTS Realty Trust, Annual Report 2015

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and Operation of a Data Centre”, 2005, HP Development Company, L.P.

[8] Emirali Mustafa, “Category Report on Data Centers”, 2015, Procurement Leaders

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Net Consulting

[10] Rakesh Kumar, “Examine these three questions before investing $100 million in

a new data center”, 2015, Gartner

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“Carbon Usage Effectiveness (CUE): A Green Grid Data Centre Sustainability

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[16] Thomas L Saaty, “How to mark a decision: the analytic hierarchy process”, 1990,

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[20] American Power Conversion, “Determining Total Cost of Ownership for Data

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[21] Jeffrey Hewitt, April Adams, “Market Guide for Modular Data Center

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