caba and the following caba members funded this...

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CABA and the following CABA members funded this project:

Ruby Sponsors

Emerald Sponsors

Diamond Sponsors

Life Cycle Costing of Intelligent Buildings

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Disclaimer

Frost & Sullivan takes no responsibility for incorrect information supplied by industry participants or users. Qualitative and quantitative market information is based primarily on interviews and secondary sources referenced at the research phase and; therefore, is subject to fluctuations. The scope of this research does not include quantitative market sizing or projections. Intelligent buildings, life cycle costing tools, cases, capabilities of products and technologies, and processes evaluated in the report are representative of the market, but not comprehensive, and inclusion in the study does not imply endorsement. All directional statements about the expected future state of the industry are based on consensus-based industry dialogue with key stakeholders, anticipated trends, and best-effort understanding of the future course of the industry. The views expressed in this report accurately reflect Frost & Sullivan’s views based on primary and secondary research with industry participants, industry experts, end-users, standards bodies, industry organizations, and other related sources. Information provided in all segments is based on availability and the willingness of participants in sharing these within the scope, budget, and allocated time frame of the project, and reflects the views of industry participants. Any reference to “Frost & Sullivan’s research findings, industry interactions, and discussions” in this report is made in the context of primary research findings obtained from this project titled “Life Cycle Costing of Intelligent Buildings,” unless otherwise stated. While the document is believed to contain correct information, Frost & Sullivan does not make any warranty, expressed or implied, or assume any legal responsibility for the accuracy, completeness, or usefulness of the information, product, technology, solution, company name, or process discussed in the report, or claims that its use would not infringe any privately owned rights. References made to products, technology, solutions, trade names, vendors, or otherwise, do not necessarily constitute or imply its endorsement or recommendation. No part of our analyst compensation was, is, or will be, directly or indirectly related to the specific recommendations or views expressed in this service. Frost & Sullivan consulting services are limited publications containing valuable market information provided to the Continental Automated Buildings Association (CABA) in response to an information request. Our customers acknowledge, when ordering, that Frost & Sullivan consulting services are for customers’ internal use and not for general publication or disclosure to third parties, unless prior permission is obtained from CABA. © 2013 Frost & Sullivan and CABA. All rights reserved. This document contains highly confidential information. With approval from the CABA Board of Directors, CABA Intelligent & Integrated Buildings Council (IIBC) and the CABA sponsors, this entire document may be circulated, quoted, copied, or otherwise reproduced. Written approval from CABA or Frost & Sullivan is not required, but appropriate recognition must be given to CABA and Frost & Sullivan.


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Study Background The Continental Automated Buildings Association (CABA) is an industry association dedicated to the advancement of connected home and intelligent building technologies. CABA is an international trade association, with over 350 major private and public technology organizations committed to research and development within the intelligent buildings and connected home sector. Association members are involved in the design, manufacture, installation, and retailing of products and services for home and building automation. CABA is a leader in initiating and developing cross-industry collaborative research, under the CABA Research Program. In 2013, CABA’s Intelligent & Integrated Buildings Council (IIBC) commissioned the “Life Cycle Costing of Intelligent Buildings” research study to assist in its ongoing endeavors in promoting the benefits of life cycle costing (LCC), uncovering pertinent issues around LCC adoption, and helping in the formulation of an actionable strategy to address the complexities associated with making LCC and similar cost justification tools a necessary component of the intelligent building industry. The broad purpose of the study was to identify and understand the imperfections and inconsistencies that exist in adopting project evaluation techniques and cost justification tools in intelligent buildings projects, as well as making investment decisions on intelligent technologies. To this end, the research assessed critical areas to enable project sponsors to identify ways of increasing adoption of LCC, unify stakeholder decision-making processes, identify opportunities/needs for training and coaching to remove obstacles from the process, and finally, determine the fundamental changes required to propagate the use of LCC. Organizations that participated in CABA’s “Life Cycle Costing of Intelligent Buildings” 2013 study included: buildingSMART Alliance, Cadillac Fairview Corporation Limited, Consolidated Edison Co. of New York, Inc., CSA Group, Hydro One Networks, Hydro-Québec, Honeywell, International Facility Management Association (IFMA), Ingersoll Rand/Trane, Johnson Controls, Microsoft Corporation, PCN Technology, Inc., Philips, Public Works and Government Services Canada, Siemens Industry, Inc., The Siemon Company, Southern California Edison and WattStopper/Legrand. CABA commissioned Frost & Sullivan (www.frost.com), an independent market research and consulting firm, to conduct this 2013 landmark research study after a competitive selection process.


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Table of Contents

Contents Page #

Chapter 1 – Executive Overview

1.1 Project Background 6

1.2 Overview and Focus Areas 6

1.3 Key Objectives 7

1.4 Methodology 8

1.5 Definitions 9

1.6 Summary of Key Findings 11

Chapter 2 – Intelligent Buildings and the Role of LCC

2.1 Overview of the LCC Adoption Process 13

2.2 LCC in Intelligent Buildings 14

2.3 LCC Method for Buildings 16

2.4 LCC Adoption Inducers for Intelligent Buildings 18

2.5 Key Challenges 21

2.5.1 The Intelligent Buildings Value Chain and Delivery Process 21

2.5.2 Usage of LCC and Alternative Methods 23

2.5.3 Challenges in LCC Incorporation 25

2.5.4 Prevalent Issues with LCC Models 27

2.6 LCC and the Role of Building Information Modeling 29

2.7 Building Intelligence Ratings and LCC 30

Chapter 3 – Opportunity Identification for LCC use in Intelligent Buildings

3.1 Identification of Market Demand Potential 31

3.2 Stakeholder Interaction Process in LCC Adoption 35

3.3 LCC Adoption Preferences by Vertical Segment 38

3.4 Incentivizing LCC Use 39

Chapter 4 – Evaluation of Market Approach for LCC

4.1 Optimization of the Technology Integration Model 40

4.2 Establishing a Market Approach for Inclusive Decision Making 43

4.3 Prospects for Collaborative Partnerships 45

Chapter 5 – Evaluation of Project Cases

5.1 Best Practices Review 47

5.2 Evaluation of Project Cases and Success Factors 71

5.3 Standardization Initiatives 72

Chapter 6 – Conclusions and Recommendations

6.1 Key Conclusions 74

6.2 Recommendations 75

Appendix – List of References 78


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List of Exhibits

Exhibit Page #

Exhibit 1.1: Primary Research Sample Categorization 8

Exhibit 1.2: Technology Transitions in Buildings 10

Exhibit 1.3: Typical Life Cycle of Buildings and Associated Costs 12

Exhibit 2.1: Characteristics of a Building and the Level of System Integration 15

Exhibit 2.2: Typical Life Cycle of Buildings and Associated Costs 16

Exhibit 2.3: LCC Approaches Adopted in Buildings 17

Exhibit 2.4: LCC Adoption Influencers 19

Exhibit 2.5: Intelligent Building Projects with LCC as a Key Decision Making Factor 20

Exhibit 2.6: Intelligent Buildings Value Chain and Delivery process 22

Exhibit 2.7: Adoption Level of LCC and Other Alternatives 23

Exhibit 2.8: LCC Usage Trend 24

Exhibit 2.9: LCC Adoption Challenges by Stakeholder Group 25

Exhibit 2.10: Core Issues with LCC Models 27

Exhibit 3.1: Industry Representation (target user survey) 31

Exhibit 3.2: Familiarity with Intelligent Building Solutions 31

Exhibit 3.3: Impact of Familiarity on Usage 32

Exhibit 3.4: Future Adoption Potential 32

Exhibit 3.5: Factors Driving Technology Selection 33

Exhibit 3.6: Proactive Request for ROI and LCC Analysis from Project Partners 33

Exhibit 3.7: Percentage of Respondent Using In-house LCC Methods 33

Exhibit 3.9: Factors Challenging LCC Adoption 34

Exhibit 3.10: Opportunities and Value Propositions for LCC Adoption 35

Exhibit 3.11: Potential for LCC Evaluations for Selecting Various Intelligent Building Solutions 37

Exhibit 4.1: Feasibility of Mandating LCC 40

Exhibit 4.2: Market Approach to LCC Implementation – Stakeholder Analysis 44

Exhibit 4.3: Activity Areas and Dynamic SWOT Analysis 46

Exhibit 5.1: List of Case Studies Evaluated 47

Exhibit 6.1: Recommendations and Identified Focus Areas 76


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1 Executive Overview 1.1 Project Background The Continental Automated Buildings Association (CABA) is a not-for-profit industry association dedicated to the advancement of connected home and intelligent building technologies. The organization is supported by an international membership of more than 350 organizations involved in the research, design, manufacture, installation, and retailing of products relating to home automation and building automation. Public organizations, including utilities and government organizations, are also members. The CABA Intelligent & Integrated Buildings Council (IIBC), a core working committee of the Continental Automated Buildings Association (CABA), commissioned this research project titled “Life Cycle Costing of Intelligent Buildings,” with the objective that it could assist in building the industry’s knowledge base and perspectives on life cycle cost (LCC) methods, and the issues and challenges associated with its adoption. Frost & Sullivan was commissioned by the project steering committee, instituted for the specific purpose of funding and overseeing this collaborative research, to undertake the project on behalf of CABA.

1.2 Overview and Focus Areas The heterogeneous and fragmented nature of the building technology industry and its associated service segments warrants that various stakeholders be involved in any given project delivery process. The ultimate decision on technology adoption is usually dependent on the influence of various service partners. Differences in operational methods of these partners leads to delay in implementation, and often results in the selection of low-cost options that do not offer benefits to the building owner. Stringent budgets and quicker payback frequently become the sole criteria for selecting a particular set of technology solutions. Incorporating intelligence is usually either postponed indefinitely or not considered at all. The present procurement processes followed in the industry further add to the issue because contractors, system integrators, and consultants exert varying degrees of influence on the building owner’s decision making process. The intelligent buildings industry is characterized by vendors and service providers from established technology, product, and solution segments, as well as those offering smart


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and energy-efficient alternatives. These players operate in the market with a variety of service providers involved from prototype development to delivery. Given this position, there are challenges that the industry participants have to face in communicating their value proposition to the building owner as well as his consultants and external project partners. Therefore, the key focus areas agreed upon by the project steering committee include the following:

Current status of adoption of intelligent technology and LCC methods

Optimal delivery process for success of adopting LCC

Level of awareness of various decision makers

Process changes to be adopted

Opportunities for industry participants

The content of this report encompasses the above focus areas.

1.3 Key Objectives of this Research The key objectives of the research study are as follows:

Investigate the use of LCC for incorporation of intelligent design and technology

solutions at the early stages of a project

Evaluate ways to address issues and common detrimental practices associated with

regard to LCC concept adoption and project evaluations

Understand the relevance of current tools and techniques in accurately evaluating

LCC specific to intelligent building design and technologies

Understand how evolved and adequate the training and education efforts are around

LCC incorporation

Determine the optimal ways for various industry stakeholders to collaborate in order

to make LCC a mainstream component in intelligent building projects

Understand the elements of an ideal roadmap for development and incorporation of

LCC with regard to technology changes anticipated within intelligent buildings

Understand the best way forward for industry participants to consolidate efforts,

goals, and objectives in the development and promotion of LCC

Determine next steps, awareness creation initiatives, and education efforts to be

taken to guide the end customers, value chain partners, and vendors appropriately


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1.4 Methodology1 Frost & Sullivan used a combination of primary and secondary research methodologies to compile the necessary information for this research. Information provided in all segments of this report is based on availability and the willingness of participants in sharing these within the scope, budget, and allocated time frame of the project. The trends identified in this report are based on discussions with industry participants and Frost & Sullivan’s ongoing research in building technologies, energy, and related markets. The conclusions drawn are based on our best judgment of exhibited trends, the expected direction the industry may follow, and consideration of a host of industry drivers, restraints, and challenges that represent the possibility for such trends to occur over a specific time frame. All supporting analyses and data, as feasible within the contractual time and budget, are provided to the best of our ability. Primary Research – Interviews2 Primary research formed the basis of this project. Interviews were conducted with technology providers, LCC tools and technique providers, consultants such as engineers, design build firms, architects, building owners, asset managers, system integrators, and contractors. To provide balance to these interviews, think tanks, not-for-profit bodies, and industry thought leaders who track the implementation of the outlined technologies were also interviewed to get their perspective on the issues of market acceptance and future direction of the industry. Any reference to “Frost & Sullivan’s research findings, industry interactions, and discussions” in this report is made in the context of primary research findings obtained from this project titled “Life Cycle Costing of Intelligent Buildings,” unless otherwise stated. However, the analysis and interpretation of such data in this report are those of Frost & Sullivan’s consulting team. Exhibit 1.1 shows the sample breakdown for primary research for this project. Exhibit 1.1: Primary Research Sample Categorization (n=85)

Targeted User Research In addition to the above primary research, Frost & Sullivan also undertook targeted user research3 through a controlled 150 sample survey. It was conducted among building owners and asset managers to evaluate their views on intelligent buildings, technology adoption, decision making factors, and perceptions towards LCC. Findings are provided in Chapter 3.

Source: Frost & Sullivan, 2013


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Secondary Research Secondary research comprised the balance of the research effort and included published sources such as those from government bodies, think tanks, industry associations, Internet sources, and Frost & Sullivan’s own repository of research publications and decision support databases. This information was used to enrich and externalize the primary data. A listing of all works cited can be located in the appendix. References are cited on the first instance of occurrence. Dates associated with such reference materials are provided where available.

1.5 Definitions The term4 “intelligent building” was coined through consensus-based deliberations as part of previous projects commissioned by CABA, such as the Convergence of Green and Intelligent Buildings, and the Intelligent Buildings Roadmap for 2011. As developed over the course of these two projects, an intelligent building was defined as a building that uses both technology and process to create an environment that is safe, healthy, and comfortable, and enables productivity and well-being for its occupants. An intelligent building provides timely and integrated system information for its owners so that they may make intelligent decisions regarding its operation and maintenance. An intelligent building has an implicit logic that effectively evolves with changing user requirements and technology, ensuring continued and improved intelligent operation, maintenance, and optimization. It exhibits key attributes of environmental sustainability to benefit present and future generations. What can we expect of such a building?

Improved interdependency between building systems and building users

A building that can detect the state it is in and make adjustments to itself

Provides a healthier and more comfortable environment

Improves economic performance

Reduces energy and resource usage

Leverages renewable energy technologies

Improves indoor air quality and occupant satisfaction

Is easier to maintain and built to last

Advanced/enhanced capabilities to deal with "churn" (occupant turnover/evolving

mission)

Intelligent buildings transcend integration to achieve interaction in which the previously independent systems work collectively to optimize the building’s performance and constantly create an environment that is most conducive to the occupants’ goals. Additionally, fully interoperable systems in intelligent buildings tend to perform better, cost less to maintain, and leave a smaller environmental imprint than individual utilities and communication systems. Each building is unique in its mission and operational objectives and therefore, must balance short and long-term needs accordingly.


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Intelligent buildings serve as a dynamic environment that responds to occupants’ changing needs and lifestyles. As technology advances and as information and communication expectations become more sophisticated, networking solutions both converge and automate the technologies to improve responsiveness, efficiency, and performance. To achieve this, an intelligent building combines data, voice, and video with security, heating, ventilation, air conditioning, and refrigeration (HVACR), lighting, building controls, and other electronic controls on a single IP network platform that facilitates user management, space utilization, energy conservation, comfort, and systems improvement. Exhibit 1.2 shows the technology transitions in intelligent buildings, as tracked by Frost & Sullivan over the last decade. Exhibit 1.2: Technology Transitions in Buildings

Definition of LCC5 Frost & Sullivan’s research for this project indicates that there are two distinct approaches6 adopted for building-related LCC evaluations, depending upon which stakeholder group is involved and what aspects of a building’s life cycle play a role in the process. Typically, end-to-end life cycle or whole building life cycle (WLC) appraisal is carried out for a much broader set of assessments of cost-benefit and performance of the facility/asset over its lifetime. WLC is more suited to new and greenfield projects. WLC amounts to LCC plus external costs and a wide range of other analyses, including environmental cost-benefit and social cost-benefit analyses. LCC, on the other hand, is used under a somewhat narrower context where an evaluation of costs is required to be carried out for incorporating/replacement/retrofitting products and technologies into an already existent facility/asset. However, it occurs that the two terms are often used interchangeably. For the purpose of this research, a consistent definition of LCC7 is adopted as follows: “LCC represents the sum of all recurring and one-time (non-recurring) costs over the full life span or a specified period of a project, service/process, or technology. It includes purchase price, installation cost, operating costs, maintenance and upgrade costs, disposal cost, and remaining (residual or salvage) value at the end of ownership or its useful life.”

Source: Frost & Sullivan

Until 2000 Early 2000 Mid 2000 Onwards


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1.6 Summary of Key Findings The key findings8 of this research are as follows:

Frost & Sullivan’s interactions with various industry participants, as part of the

primary research process for this project, reveal that initiatives adopted by

institutional bodies and technical organizations over the last two decades have

brought the concept of LCC to the forefront of pre-project evaluations in intelligent

buildings and construction.

Despite gaining early focus, LCC has remained largely confined to project

evaluations within the federal sector9, with very limited frequency of use witnessed in

other vertical segments. This is attributed to a variety of factors including

inconsistent methodologies, lack of valid data, irreconcilable values, and above all,

apathy of building owners, vendors, and service providers to voluntarily incorporate

LCC into the early phases of a project.

Nevertheless, because of the need to logically approve capital investments and to

validate return on investment and equity, cost assessment tools have become a

necessary part of the project flow even though a full-fledged LCC approach may not

be pursued.

LCC is often substituted by simple payback analysis and other capital cost

justification methods to meet the same objective. They offer the minimum required

incentive to bridge the gap between having to accommodate untendered costs, as

opposed to allowing parametrically justified investment.

Intelligent buildings essentially fall within two major categories—partially integrated

and fully integrated10. The true value of effective operation and maintenance (O&M),

progressive asset management, and cost savings via predictive energy

management are only achievable with a fully integrated approach. This, in turn, is

reliant on the building industry’s motivation to adopt open standards and integrated

systems, selected on the basis of their ability to offer lowest life cycle costs.

The intelligent buildings industry participants are showing gradual signs of moving

away from putting undue emphasis on initial costs and simple payback and towards

a more holistic approach where recurring costs, incentives, and life cycle

assessments are taken into consideration.

A major drawback in the presently used LCC methods is that these are

characterized by the absence of a consistent methodology for deriving LCC. But

perhaps more hindering than this issue is the fact that the majority of these tools and

calculation techniques cannot be easily comprehended by building owners and their

operations staff.

A fragmented delivery chain and transactional interactions among value chain

partners further act as restraining factors in LCC adoption.


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It is encouraging to witness a growing breed of building owners and asset managers

that lay emphasis on superimposing cost-benefit analysis over an extended project

life span, whereby better visibility into recurring costs and incentives can be

obtained.

Among prevalent LCC tools, the National Institute of Standards and Technologies

building life cycle costing tool is by far the most widely accepted11 and forms the

basis of various customized LCC techniques.

There is a greater need for consultants, owners, vendors, and service providers to

collaborate and create a market approach to promote inclusive decision making so

that integrated design and delivery approaches are supported.

The immediate need for industry participants is to organize initiatives to work

together and create structural frameworks for joint collaboration in technology

deployment as well as propagating LCC adoption.

Exhibit 1.3 shows the typical life cycle of buildings and associated costs. Exhibit 1:3 Typical Life Cycle of Buildings and Associated Costs

Intelligent Integrated

Building

Resources Extraction

Manufacturing

Construction

Occupancy/

Maintenance

Demolition

Recycle/ Reuse/

Disposal Life Cycle

Full Integration Life Cycle Costs

First Costs

Training Costs

O&M Costs

Service Agreement Costs

Upgrade/Retrofit Costs

Disposal/ Deconstruction

Costs



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2 Intelligent Buildings and the Role of LCC 2.1 Overview of the LCC Adoption Process As a concept of providing computational support for the analysis of capital investments in buildings, life cycle costing has existed for a relatively long time. Concerted initiatives1 adopted by institutional bodies and technical organizations over the last two decades have brought this concept to the forefront of pre-project evaluations in many industries. LCC is intrinsically a subset of life cycle analysis (LCA), which comprises a much wider framework of tools and evaluation parameters to address environmental, ecological, energy, and other impacts comprehensively for any project or sector. LCC, on the other hand, is more specific to built environments and extends end-to-end through the life cycle of a building project. This includes all stages from pre-construction, construction, project management, and continued operation of the building or asset through its life cycle. As evident from Frost & Sullivan’s discussions with industry participants for this research, in North America LCC has received significant impetus due to early interest from organizations such as the National Institute of Standards and Technology (NIST), the Rocky Mountain Institute2 (RMI), Harvard University3, the Athena Institute4, and various state and province-led LCC initiatives5 in both the United States and Canada, starting from the early 1990s. Despite gaining early focus, LCC remained largely confined to project evaluations within the federal sector, with very limited frequency of use witnessed in other vertical segments. This is attributed to a variety of factors including inconsistent methodologies, lack of valid data, irreconcilable values, and above all, apathy of building owners, vendors, and service providers to voluntarily incorporate LCC into the early phases of a project. Nevertheless, to logically approve capital investments and to validate return on investment (ROI) and equity, cost-assessment tools have become a necessary part of the project flow, even though a full-fledged LCC approach may not be pursued. Frost & Sullivan’s primary discussions with participants of this study suggest that LCC is often substituted by simple payback analysis and other capital cost justification methods to meet the same objective. Such substitute approaches may not lead to a complete amalgamation of all necessary elements such as first costs, training costs, operation and maintenance (O&M) costs, service agreement costs, upgrade/retrofit costs, and disposal/deconstruction costs, and does not enable involved parties to understand the true ROI. However, they offer the minimum required incentive to bridge the gap


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between having to accommodate untendered costs as opposed to allowing parametrically justified investment.

2.2 LCC and Intelligent Buildings Intelligent buildings are characterized6 by the presence of devices, controls, and systems that interconnect and communicate with one another to enable an environment that is responsive and adaptive to occupants’ needs and comforts. The degree of “intelligence” varies by the sophistication underlying the software-aided applications and communication network that helps these devices and systems function in an interoperable manner and share operational data. This ultimately forms the backbone of this evolving concept. The evolution and transition in buildings has led industry experts to dwell upon various terminologies such as green, automated, intelligent, smart, and high performance to define these buildings. Examples of intelligent buildings in North America range widely, starting with structures where some degree of system automation and control strategies have been implemented to achieve significant reduction in energy and resource wastage, to a comprehensive enterprise-wide integrated platform that eliminates all silos. No matter how robust the vision of an intelligent building is today, there are some distinct functionalities and applications that have come to exist within its domain, and others that may be prominent as part of its future evolution. Yet, as Frost & Sullivan’s discussions with industry participants for this research indicate, the important outcome of this transition is that industry stakeholders, and the value chain catering to the intelligent buildings industry, agree on some of the fundamental principles that this concept revolves around. These include the following:

Definition of intelligence – the attributes that encompass and contribute to

intelligence

Technology, product, and service profile – the various means that help achieve and

continuously maintain intelligence

Tangible and intangible benefits of an intelligent building – both quantifiable and

non-quantifiable benefits that provide a distinguishing mark from other buildings

A building’s intrinsic relationships with energy – its ability to consume, generate, and

store energy

Environmental and social impacts of buildings – impacts that should be considered

to determine the optimal life cycle cost

These fundamental principles are crucial in conducting LCC analysis for buildings that primarily exist within three distinct profiles7 today: non-integrated, partially integrated, and fully integrated buildings. While the majority of buildings today conform to the first two profiles, it is the fully integrated profile that ultimately provides the building its intelligence quotient. Intelligence, in turn, is dependent upon the level of system integration, interoperability, inter-communication, and granular visibility into the


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operational dynamics that has been achieved in a building. Before diving deeper into the elements of LCC analysis for intelligent buildings, it is important to analyze the key characteristics of buildings based on these three profiles. Exhibit 2.1 depicts a building’s characteristics associated with its corresponding level of system integration and intelligence, as progressively tracked by Frost & Sullivan over the last decade.

Exhibit 2.1: Characteristics of a Building and the Level of System Integration

Building Profile

Spec Approach Reliance On System Integration Specialist

Integration Determinants

Limiting Factors

Non-integrated

Segregated

approach

divided across

divisions of

construction

specification

master formats

Performance specs

with minimal design

documentation

Overtly

dependent on

contractors

Availability

Low cost

Relationships

No open

standards

Difficult to

accomplish

system integration

Long-term

maintenance

contracts of

manufacturers

Engineering-by-

design not adopted

as a norm

Costly upgrade

contracts

Partially integrated

Combination of

segregated

and integrated

approach

Some design

documentation, but

generally

standalone

system/hardware

intensive

Extensive use of

Middleware/Web

services to enable

unified user

interfaces and peer-

to-peer

communication

between disparate

systems

Dependency on

contractors and

system

integrators

Advocacy of

open standards

to some degree

Cost still

overrides

decisions

Benefits of

integration not

fully exploited

Hardware intensive

with multiple

communication

interfaces/gateways

making the switch to

full integration

cumbersome

Proprietary

strongholds persist

Fully integrated

Technology

contracting or

integrated

consulting

approach with

a sole source

contractor

assigned

Design

documentation is a

mandatory norm

Sub-system

integration at the

control network

level reduces

multiple devices

and drivers

Collaborative

approach and

accountability

shared by

multiple

stakeholders

with the building

owner at the

center of

decision making

Specs dictated

by compatibility

and

interoperability

Demonstrates

lowest life cycle

cost

Variances in cost

estimation

Perception issues

with regards to cost

and time consumed

Lack of skilled

professionals

The single-user graphical interface for all systems and advocacy of a non-proprietary system are distinct advantages of the partially integrated approach. However, the true value of effective O&M, progressive asset management, and cost savings via predictive energy management are only achievable with a fully integrated approach. This, in turn, is reliant on the building industry’s motivation to adopt open standards and integrated systems, selected on the basis of their ability to offer lowest life cycle costs8. Depending upon the technology or service that is under consideration as part of the full integration process, the life cycle costs will incorporate other elements that are relevant to those considerations. This will also dictate the replacement period, replacement cost, duration of life cycle, and value of inflation over that life cycle.



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2.3 LCC Methods for Buildings To understand the determinants of life cycle costing for intelligent buildings, it is important to consider the elements that constitute the life cycle of building products9 as shown in Exhibit 2.2.

Exhibit 2.2: Typical Life Cycle of Buildings and Associated Costs

These impacts are important in evaluating which project alternatives would be optimal when comparing various solutions to execute building systems integration. Such comparative analysis is carried out to determine economic value of a project by evaluating one, or all of the following:

Determining net savings (NS)

Savings-to-investment ratio (SIR)

Internal rate of return (IRR)

Net present value (NPV)

Lowest life cycle cost

For instance, two project alternatives may deliver the same performance requirements, but differ with respect to initial costs and operating costs. In such cases, the alternative that is capable of significantly reducing O&M costs, and thereby, maximizing net savings would be preferred over the other. While most projects may be sanctioned with just the determination of net savings, or IRR, the lowest life cycle cost is by far the most comprehensive. The purpose of LCC is to select the design and/or technology that will ensure the facility will provide the lowest overall cost of ownership consistent with its quality and function. Needless to say, LCC analysis should be performed early in the design process while there is scope for refinement to the design or technology spec to achieve a low LCC. Frost & Sullivan’s discussions with primary research participants of this project, as well as review of secondary data10, indicate that there are two distinct approaches adopted for building-related LCC evaluations, depending upon which stakeholder group is

Intelligent Integrated

Building

Resources Extraction

Manufacturing

Construction

Occupancy/

Maintenance

Life Cycle

Full Integration Life Cycle Costs

First Costs

Training Costs

O&M Costs

Service Agreement Costs

Upgrade/Retrofit Costs

Disposal/ Deconstruction

Costs


Recycle / Reuse/

Disposal

Demolition


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involved, and what aspects of a building’s life cycle play a role in the process. Typically end-to-end life cycle or whole building life cycle (WLC) appraisal is carried out for a much broader set of assessments of cost benefits, and performance of the facility/asset over its lifetime. WLC is more suited to new and greenfield projects where WLC amounts to LCC plus external costs (including, but not limited to, environmental, social, and community costs that are included in LCA) associated with any project and a wide range of analysis. LCC, on the other hand, is used under a somewhat narrower context, where an evaluation of costs is required to be carried out for incorporating/replacement/retrofitting products and technologies into an already existent facility/asset. However, the fact that the two terms are interchangeably used cannot be ruled out. In fact, several accredited standards and LCC techniques11 are notorious for propagating this ambiguity and confusion. Interviews conducted among building owners and asset managers as part of this research reveal that external consultants (estimators, architects, and consulting engineers) often club LCA components into building LCC calculations. This research defines LCC as including both original costs, and cost incurred throughout the whole functional lifetime, including demolition. The stakeholder involvement, and the variation in components that may exist in either approach, are qualified for clarity. Sources of information for either approach can be obtained from similar agencies12 such as NIST, Building Owners and Managers Association (BOMA), National Institute of Building Sciences (NIBS), Federal Energy Management Programs of Department of Energy (DOE/FEMP), and RSMeans, to name a few. Exhibit 2.3 shows Frost & Sullivan’s interpretation of the LCC approaches adopted for buildings, as indicated by primary and secondary research undertaken for this project.


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Exhibit 2.3: LCC Approaches Adopted in Buildings

Approach Data Categories

(All or Part) Stakeholder Involvement Sources of Information Limitations

New project whole building life cycle appraisal (WLC)

Costs – acquisition,

capital, taxes,

inflation,

replacement, resale,

recurring and non-

recurring O&M, repair,

energy, insurance,

demolition/disposal

Impacts – social,

environmental,

economic

Analysis – LCC,

NPV, IRR, NS, SIR,

payback, sensitivity

and scenarios, risk

and uncertainty, other

computations

Other data –

occupancy, physical

performance, quality

of equipment

Environmental/site

planners

External development

cost estimators

Equipment vendors,

Building

owner/developer,

Architect/design build

firm

Performance contract

providers

Post-completion and

continued service

providers

External cost estimators

Data aggregators (e.g.,

RSMeans, NIST,

DOE/FEMP, BOMA,

NIBS)

External third-party data

and cost estimators

Equipment vendors and

service providers

Financial analysis – some

components do not take

inflation into account

If life span of project

alternatives vary, WLC does

not yield comparable results

Existing project life cycle costing (LCC)

Building

owner/developer

Contractor

Technology vendor

Project management

provider

External cost estimators

Data aggregators (e.g.,

RSMeans, NIST,

BOMA, DOE/FEMP,

NIBS)

Internal O&M and

performance data logs

External estimators

Service providers

Financial analysis – some

components do not take

inflation into account

Investment options can be

compared only where that

investment yields income

Some analysis only provides a

rough estimate of profitability,

not an exact number

Difficulty in comparing

alternatives where project life

span varies


For both new and existing projects, the key factors during the early design stage would be occupancy and physical data. Frost & Sullivan’s interactions with industry participants for this project reveal that inadequacies in these components can result in grossly misleading analysis that, in turn, could defeat the purpose of carrying out WLC or LCC analysis of project alternatives. Still, estimators can at least have control over these data sets and strive to reconcile information from relevant sources. But when it comes to performance and quality-related data, it can get rather subjective and values seem to fluctuate. Such data is often dictated by codes, policy, and standards that often do not have a clear way of defining these components. For instance, energy performance metrics used by various LCC tools rely on ambiguous calculation criteria13 (actual performance versus time-dependent value), and there is no fully justified way of including one measurement metric over another. Most commercial building owners talked about this issue when citing the key challenges they and their estimators face in deriving LCC analysis accurately. Consequently, this makes such performance data less reliable, as compared to cost data. Moreover, the ultimate accuracy of both LCC and WLC approaches is dependent on how detailed and evolved the design spec process is, and how the value chain influencers were brought into the project scheme. The overriding importance of either approach is, of course, dependent upon cost results. However, cost data, if not properly complemented with supplementary analysis (sensitivity, scenarios, “break-even”) is


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meaningless in full or part LCC evaluation and interpretation. Project alternatives that are selected on the basis of such comprehensive cost analysis are far more reliable and have evidently provided a more succinct business case to sanction project investments.

2.4 LCC Adoption Inducers for Intelligent Buildings A host of factors have influenced the adoption of LCC tools for intelligent building projects, as indicated by primary research among industry participants undertaken for this project, as well as past collaborative landmark research conducted by Frost & Sullivan and CABA14. A close review of successful projects suggests that both readily available free and paid LCC tools, as well as self-developed and custom tools, are used by building owners and project managers to justify investments in technology integration and new project initiation. The key factors that have influenced adoption, as indicated by this research, are shown in Exhibit 2.4. For instance, initial costs alone can never present the full picture. Energy conservation measures (ECM) can seldom be profitable unless recurring lifetime costs are considered. Additionally, the goals and objectives pertaining to greenhouse gas (GHG) reduction can be weighed effectively, and targets set more accurately, when the total cost of ownership (TCO) is evaluated via a comprehensive LCC approach as opposed to an assessment of initial costs. The ability to judge initial capital expenses (CAPEX) in conjunction with potential operating expenses (OPEX) over the lifetime of the project is essential when it comes to budgeting for contingencies, and to proceed with, or reverse original project designs in a more logical manner. Furthermore, recurring savings and incentives that could accrue beyond initial years have an impact on total cost of ownership, which can be better judged by a complete LCC analysis, as opposed to a simple payback analysis.


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Exhibit 2.4: LCC Adoption Influencers

As it emerges from this research, as well as past projects completed by Frost & Sullivan and CABA, it is encouraging to witness a progressive approach adopted by some end-users, such as asset management companies and institutional clients, whose decisions are clearly driven by energy reduction initiatives, efficiency gains, and endorsement of sustainable and high-performance buildings. The technology integration process adopted by such clients18 does indicate absolute reliance on LCC tools and project evaluation methods for justifying investments. Exhibit 2.5 provides a list of such projects, evaluated by Frost & Sullivan that demonstrates how LCC was used as a prominent decision-making factor19. These projects were evaluated as part of the Convergence of Green and Intelligent Buildings project (CABA and Frost & Sullivan, 2008), and the Intelligent Buildings Roadmap 2011 (CABA and Frost & Sullivan, 2010).


Initial cost can be

misleading

• Initial costs comprise only a fraction of actual capital

outlay a building owner/project manager has to

provision for.

• It is not possible, using these costs, to reflect

recurring and timeline-oriented costs that get

attached to a project’s life cycle.

• LCC provides visibility into TCO over a 20 or 30-year

life span.

LCC Adoption Influencers

Present costs do not equal

future

costs

Simple payback does not

reflect full

value

Harvard University’s Green Building Standards15

, developed for internal use in 2009, stipulates that for implementing all ECMs, a 20-year LCC appraisal is mandatory, with the prerogative of reducing GHG by 30% by 2012 from 2006 levels. LCC allowed foolproof selection of ECMs based on ability to meet GHG reduction targets, and helped reduce TCO by linking CAPEX and OPEX budgets over the 20-year span.

• Beyond initial costs, LCC takes into consideration

potential future costs that will ultimately be added to

the total ownership costs for the building

owner/project manager.

• LCC converts all future costs into present value by

discounting those in present value terms.

• This allows for apples-to-apples comparison of

costs over 20 or 30 years, irrespective of when they

may get added to the life cycle of the project.

TIAA-CREF headquarters in New York City adopted an LCC approach

17 to justify its investment in high

performance building solutions. This comprised of multiple HVAC chillers, thermal ice storage systems, and a cooling tower. The LCC approach allowed the project managers to evaluate recurring utility rebates owing to continued reduction in demand charges, realize over 20% in 10-year IRR, and project over $760,000 annual savings in OPEX over that life span.

• Simple payback only offers a cursory glance to

preliminary savings that could accrue in the early

years of a project.

• Initial costs and expected annual savings do not

reflect variances in expected equipment lifetime.

• Additionally, maintenance cost differences, periodic

rebates and incentives, as well as other operational

savings that could accrue beyond initial years has an

impact on TCO.

The Department of Defense (DoD) has adopted LCC for military facility construction purposes for several years

16. This has allowed the authorities to

shift focus from initial costs and gain better visibility into unintended consequences of adopting poor design. In one such case, LCC helped to reverse a decision to forgo an extra 5,000 sq.ft. of space in a new project because this would have resulted in O&M costs escalating by $200,000 for the next 10 years. Adding cost of labor and parts at future rates

would have further increased that figure.


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Exhibit 2.5: Intelligent Building Projects with LCC as a Key Decision-making Factor20-24

Project Description LCC Modeled Intelligent Building Solutions Showcased

Key Highlight

655,000 sq.ft. office tower, owned by Morgan Stanley and managed by Hines, 750 Seventh

Avenue Manhattan, New York, U.S.A.

Advanced lighting controls, systems integration, automated demand response (DR)

Rated as an Energy Star building and a candidate for LEED EBOM certifications

Based on an Energy Star score of 79, the building is 30% more energy efficient and saves $1.28 in energy costs per sq.ft. per year

38 ECMs have been pursued at an estimated cost of $1.1 million, resulting in savings of 2.9 million kWh, equivalent to about $600,000 in utility cost reductions

Van Andel Institute of Research Cancer Center;

240,000 sq. ft. spread over an eight-story building, Grand Rapids, Michigan, U.S.A.

Digital lighting management systems, automated DR

Performance and ROI based on initial assessment

of technology implementation

Annual operational savings - $100,000

Annual energy savings - $130,000

Net decrease in energy expenses of 10% over

conventional building performance will generate

savings of $130,000 annually.

Bell Trinity Square; 1,073,600 sq. ft. of gross floor area, Toronto, Canada

Intelligent building management, optimized control strategies, energy-efficient HVAC, automated DR, and ‘smart grid readiness’

Optimization of energy consumption

Seamless integration of all mechanical systems and devices

Smart grid ready with fully automated OpenADR; Reduction of power demand by 400-800 kwH achieved during DR events

Reduction in peak electrical demand of 522 kW and 1,394,500 kWh per year

Annual energy savings of $170,000 per year

Continuous commissioning for optimal performance

Certified by LEED for Commercial Interiors

King Abdul Aziz Endowment ;1.4 million sq. mt. built area supporting

75,000 tenants and a podium for commercial space, Saudi Arabia

IP-based telecom and security infrastructure deployment

IP Telephony, IP Pay Phones, IP FAX, IP DATA, IPTV, IP ATM, IP Point-of-Sale terminals (POS), IP Access Control, IP Video Surveillance, IP Door Locks, IP Audio

Digital signage - advertising screens throughout the buildings, including elevators

Estimated 33% reduction in cost due to avoiding redundant cabling and containment space (and labor, scheduling, commissioning, etc.)

Rogers Centre, One Blue Jays

Way, Toronto, is a world-class sports and entertainment complex; 1.4 million sq. ft.

Major lighting control retrofit comprising the deployment of personal lighting control capabilities, occupancy sensing, and addressable dimming across the facility

Reduced overall lighting energy consumption by 50% and delivered a simple payback from energy savings in less than five years

76% savings in energy expenses from lighting

Cost savings; reached $325,000 annually after phase 2

With energy reductions of 3,731,000 kWh annually, the project will have reduced its dependency on the energy grid equal to the energy required to power over 400 homes in Toronto.

Source: Frost & Sullivan and project owners cited here


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2.5 Key Challenges Despite the obvious benefits and adoption influencers, there are some fundamental issues that make LCC incorporation less compelling for most projects. For the vast majority of intelligent building projects, this potentially means that capital cost considerations and first costs override decision making in technology integration or project expansion. However, a growing number of industry participants are evidently relying on some form of financial justification alternative25. While this may indicate that even though only individual financial metrics such as NPV and net savings are evaluated from a project approval perspective, they are presently offering project participants a viable substitute to not considering any option at all. A major drawback of presently used LCC methods is that they are characterized by the absence of a consistent methodology for deriving LCC, as indicated by the feedback obtained from primary research interviews for this project. Perhaps more hindering than this issue is the fact that a majority of these tools and calculation techniques cannot be easily comprehended by building owners and their operations staff. The challenge of implementing the concept of LCC is to identify the key decision makers involved in fund allocations in the design, construction, and operations process, and also to encourage manufacturers and consultants to provide life cycle information about products. To accomplish this, it is necessary for the intelligent buildings industry participants to understand and address the needs and reservations towards LCC, and explore a practical and unified approach for its frequent implementation in projects. 2.5.1 The Intelligent Buildings Value Chain and Delivery Process Before diving further into the challenges, it is important to first examine the prevalent intelligent buildings value chain and delivery process, where the adoption of LCC, or any alternative to it, fits in. Encompassing all critical supply points within the delivery process, the value chain26 of an intelligent building assumes a fairly robust sequential flow with value-added components moving from suppliers on the left end to the user on the right. Original equipment manufacturers (OEM) and technology vendors work directly with the building owner, or through any of their supply chain partners. These partners generally include their own line of agent representatives, distributors, and system integrators. Unless working directly with building owners, often times these partners either interface with a contractor, architect, or a project management agency that takes on the responsibility of acting as the “fulfillment partner” in project execution and installation. Frost & Sullivan’s research within the intelligent buildings industry value chain over the last decade indicates that the contractor typically assumes all procurement responsibility, although decisions on what to procure are often incumbent upon what the project fulfillment partners decide in conjunction with the building owner. These fulfillment partners could either be comprised of energy service companies (ESCOs), a design build firm, a consulting engineer (CE), or the project management firm involved in the design, specification, and conceptual planning process of the project.


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There is a further fragmentation of the value chain below the general contractor level, where the specific tradespeople get involved. The category that sits right below the general contractor is the technology contractor, and is a relatively new entrant of this value chain. The sophistication and innovation in technology and building systems has created the need for project fulfillment partners to understand technology in order to incorporate them into the project. This calls for the inclusion of other nontraditional or “new entrants” into the traditional value chain. For the longest time, the value chain and delivery process operated with a fairly static structure, with little or no consensus as to how and where these new entrants/technology contractors should be included. However, this is gradually changing with the value chain moving to a more dynamic framework of functioning. As most successful intelligent building projects show, the technology contractor’s role has come to occupy its own position in the value chain, and works closely with the general contractor and fulfillment partners in delivering technology integration in intelligent buildings. The categories below the general contractor comprise of electrical, mechanical, and other sub-contractors that interface with the general contractor to provision specific products, technology, and services, as dictated by the project vision. Together, they take the responsibility of organizing and managing the various suppliers and integrators of the myriad of items required to complete the project. It may also be the case that only one type of contractor (general/electrical/mechanical) is used in a project. Finally, the industry has come to realize the importance of an overall neutral advisor or quality surveyor for successfully fulfilling projects that are undertaken via competitive bids. Although this position is not a frequent inclusion, there is some evidence of such neutral project advisors getting involved in various integrated design delivery projects. This responsibility is mostly shouldered by someone from the building owner/developer camp. Exhibit 2.6 depicts the value chain of the intelligent buildings industry. This is interpreted based on Frost & Sullivan’s ongoing research in the intelligent buildings industry. Exhibit 2.6: Intelligent Buildings Value Chain and Delivery process

Source: Frost & Sullivan


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Disciplined and straightforward as it may appear, the reality of conducting business within this value chain presents some critical challenges for all parties involved. Managing costs, expectations, project objectives, and ensuring that all parties understand and deliver to those objectives poses a major hurdle in each step of the process. The structure itself has remained static for most parts, with little recognition of the fact that technology and operational requirements of buildings have undergone considerable changes. Clearly the processes have not kept pace with these changes, resulting in situations where transactional practices have taken over what should have been an orchestrated and seamless delivery process, with all the right parties involved. Consequently, such imperfections lead to divergence of emphasis from vital methods such as LCC, or its alternatives in justifying project value. 2.5.2 Usage of LCC and Alternative Methods

A qualitative review of actual adoption levels for LCC and other similar techniques clearly indicate that, at present, the intelligent buildings industry and its various channel influencers are well below the desired mark when it comes to frequent and prescriptive use of these methods, as per research conducted for this project. Exhibit 2.7 depicts the adoption levels achieved so far in relative comparison to where the actual market appetite for adoption of such techniques appears to be from this research. The components of this exhibit are explained below:

None or limited usage – This represents the present usage rate for LCC and

alternative approaches by all stakeholders such as technology vendors, building

owners/developers, project managers, and consultants.

Market appetite – This represents the receptiveness of user groups such as building

owners/developers and project managers to incorporate some form of value

justification technique into their pre-project process.

Progressive usage – This represents where the ideal level of adoption for LCC and

alternative techniques ought to be, as dictated by market appetite.

Disruption point – This represents the point where this progressive usage level can

be attained if the right measures are adopted.

Exhibit 2.7: Adoption Level of LCC and Other Alternatives


Ranking* of Components None or Limited Usage - 4 Progressive Usage – 7 Market Appetite - 6 *Scale of 1-10; 1 being Lowest; 10 being Highest


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Frost & Sullivan’s interactions with various stakeholder groups during the course of this project suggests that the potential rate of adoption for LCC, as well as any alternative financial value justification techniques, could be ideally higher than where it appears to be at present. This is supported by a review of the key influencers identified during this research, as listed below:

There is a growing emphasis on proving the business case prior to sanctioning any

project. Budget curtailments that followed the recessionary conditions post 2007 in

North America, and its cascading effect that was felt globally, indirectly exerted a

significant push on the adoption levels of these techniques.

Besides funding approvals from private investors and institutional funding bodies, as

well as obtaining the internal chief financial officer’s (CFO) buy-in, increasingly

requires a solid pre-project evaluation.

Most interestingly, there is a thrust among building owners and asset managers to

superimpose cost-benefit analysis over an extended project life span, whereby

better visibility into recurring costs and incentives can be obtained.

These factors put the market appetite at a ranking of six (on a scale of 1 to 10, with 1 being the lowest, and 10 being the highest), with definite room to increase over the next 10 years. However, a majority of such initiatives are limited to analyses and crunching of individual financial metrics such as simple payback, NPV, and adjusted IRR. As such, a qualitative ranking for actual usage stands at a low 4. Beyond technical challenges that require due attention, Frost & Sullivan’s research with the majority of the industry stakeholders for this project did not elucidate any significant perception-based reservation to using a comprehensive LCC technique, which would also incorporate some of the above individual financial metrics that are presently being used. Because most technical challenges are surmountable over time with the right initiatives in place, the progressive usage anticipated is high, and this component has been ranked at 7 between now and the next five years. Progressive usage can outpace the present scenario of limited usage significantly within the next 10 years, provided the issues with non-adoption are addressed on priority. The steps needed towards achieving this are discussed later in the report. Exhibit 2.8 shows the current LCC usage trend observed in the intelligent buildings industry from this research. Exhibit 2.8: LCC Usage Trend

Industry Stakeholder Usage Statistic (Approximate %)* Trend Building Owners/Developers/Project Managers

38% Sporadic Users

Neutral-to-increasing

Consultants 68% Heavy Users Increasing

Contractors and Integrators 12% Negligent Users

Neutral

OEMs 40% Moderate Users

Increasing * Percentage of total interviewed Source: Frost & Sullivan, 2013


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2.5.3 Challenges in LCC Incorporation The challenges of incorporating LCC by various industry stakeholders and value chain partners are unique, as well as common to some degree for each group, as revealed by primary research for this project. Exhibit 2.9 provides an overview of the challenges in adoption associated with each stakeholder group, and recourse to LCC alternatives adopted by each.

Exhibit 2.9: LCC Adoption Challenges by Stakeholder Group

Industry Stakeholder

LCC Incorporation Challenges Usage Characteristics

Building owner/developer

Reliance on fulfillment partners and consultants provides early acquaintance with LCC; however, do not proactively adopt it

More concerned with justifying immediate capital cost as opposed to value

Internal stakeholders such as CFO or fund approvers emphasize more on project review and individual financial metrics

Understanding LCC techniques is a hurdle; explaining that to internal staff including CFO poses additional challenge

Perceived extra costs of undertaking LCC analysis by involving third parties acts as a restraining factor to adoption

More reliant on case-by-case project evaluation with simple payback analysis

Limited use of LCC

Have interest in evaluating cost benefit via LCC to ensure they make sound investments in their assets

Customized tools preferred such as those brought forward by consultants and OEMs to demonstrate value

More familiar with NIST-Building Life Cycle Costing (BLCC) tool than other LCC tools

Consultants and fulfillment partners (consulting engineer, design build, architect, ESCO)

More attuned to using LCC and similar cost-benefit tools as part of their daily business

Relatively little clarity on intelligent buildings technology characteristics – controls/integration/converged systems

Meeting minimum project requirements is the bottom line; therefore, do not consider it worthwhile to provide detailed LCC analysis for intelligent building solutions

More likely to use LCC where maximum risk with performance guarantees are associated in projects, particularly performance contracts via public private partnerships (PPP)

Finds public sector clients more receptive towards LCC; usually a hard sell to private clients

Tendency to use more in-house developed tools that enable LCC calculations

Most consultants use their own version of LCC, developed either via building upon free or paid public LCC versions

Have mandatorily used LCC when involved in project via a sole source technology contracting and integrated design delivery method

Independent LCC analysis, as well as other types of cost-benefit analysis, is typically provided for a fee, unless it is part of a large project contract

Contractors

Little inclination towards offering any form of project or technology evaluation because this is not directly their prerogative

No incentive to keep up with the influx of intelligent technology; therefore, unfamiliar with the financial benefits or ROI

Do not consider it worth their time, primarily due to cost constraints and the lack of support from suppliers

Present methods of procurement for intelligent building solutions do not give them the opportunity to participate from the start (only provide follow through)

Education and training, including incentives, are needed to ensure contractors can adopt such techniques, and provide solutions that meet the project’s original intent

Some interest in low-cost certification process, provided these offer universal applicability

Earlier project involvement is needed to be able to participate through the design phase

Some familiarity with LCC and similar techniques where they participated through integrated design delivery approach

System integrators (SIs)

Cost driven and mostly brand agnostic; therefore, do not have any reason to promote intelligent building solutions via demonstrated lowest LCC

Mostly work to deliver to spec, so meeting minimum requirement is the sole criteria

Gradually taking a progressive stand on promoting technology integration, but challenges of working with tradespeople, both above and below the value chain, makes it hard for them to pursue this objective

Not fully open to spending on education, training, or certification processes voluntarily

Industry-led initiatives are necessary to bring them under compliance

OEM-led incentives to drive adoption, including training, are necessary


27

Industry Stakeholder

LCC Incorporation Challenges Usage Characteristics

OEMs

Gradual move toward open technology and full integration has prompted the use and advocacy of LCC in recent years.

Slow to address integration challenges; therefore, LCC or similar techniques not always adopted

Overtly focused on building owners and contractors, generally hampers involvement in early project design phases

Inadequate efforts to help consultants understand the value of technology integration and intelligence keeps them from participating jointly in project value demonstrations

Tendency to use more in-house developed tools that enable LCC calculations

Have mandatorily used LCC when involved in project via a sole source technology contracting and integrated design delivery method

Realize the need for partner education, training, and collaborating on an ongoing basis with consultants to keep technology visible

Keen on standardizing initiatives


Review of the challenge and usage characteristics of the various stakeholders provides an understanding of the distinct roles and responsibilities that each group delivers within the project execution process, and in the systematic incorporation of LCC or other similar techniques. To accurately judge the gravity of the challenge of non-adoption, it is important to understand the sequential flow that characterizes a project from start to finish. Frost & Sullivan’s ongoing research in the intelligent buildings industry over the last decade indicates that technology vendors and OEMs have traditionally interfaced more with building owners directly to propose their products and solutions. However, building owners have mainly relied on consulting specification engineers and design build organizations to make the right technology selection. Given this situation, a clear mismatch often arises between the originally intended project vision and the final outcome. Industry participants have continued to work within their defined domains to create optimal value propositions for the building owner, using LCC and similar value demonstration techniques, where possible. Nevertheless, this creates a major hindrance for the parties to proactively pursue any one approach. As evident from primary research undertaken for this project, often there is a multiplicity of LCC approaches, with OEMs and consultants each offering their customized versions, leaving the building owner/project manager unsure about which to choose. When this inconsistency is combined with the already existing challenge of building owners not having clear knowledge of using LCC tools and techniques, it further aggravates the situation. Selling the proposition to funding sources under these circumstances, as well as to the internal CFO, becomes even more cumbersome. And because most funding sources, institutional or otherwise, including the internal CFO who manages the budget, are more comfortable understanding project value with simple payback analysis, LCC often takes a backseat. Besides, LCC is not a budget- allocation tool. Therefore, fund managers do not treat it as a critical determinant of project cost-benefit evaluation. Furthermore, fragmentations in the value chain and delivery processes prevalent in the intelligent buildings industry often does not allow for distinction between the real “buyer” and the “installer/facilitator”, with the contractor fulfilling both roles. Instead of acting as the traditional project overseer, the contractor is often responsible for critical buying decisions. Because various project partners do not typically work together, it becomes


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easier for everyone to minimize accountability by overtly depending on the contractor to carry out the buying process. This imprints a flaw on the delivery process, as well as any efforts to integrate LCC as the basis of decision making. Past relationships, cost, and ease of installation guides the process instead. Hence, even though a sound project plan with the lowest LCC may have been specified, a flawed buying process leads to a sub-optimally delivered project. 2.5.4 Prevalent Issues with LCC Models Upon closer review27 of all major LCC models presently in use in the intelligent buildings industry, it is clear that no single model is capable of addressing all issues related to cost justifications for intelligent building projects. Exhibit 2.10 depicts the core issues with LCC models used at present, as revealed by this research project.

Exhibit 2.10: Core Issues with LCC Models

Key Issue Industry Perspective

Limitation on robustness

Currently, prevalent LCC models are less comprehensive. Components and variables are not well defined or directly relevant to intelligent building technologies.

Variations in definition and estimation of values

The concept of residual value used in all LCC models is often met with conflicting opinions, with different stakeholders varying in their estimation of this component.

Macro framework and lack of specificity

Prevalent LCC methods are direct derivatives of LCA, which makes it difficult to apply them fully to buildings. LCA is used to estimate a wide range of environmental impacts or costs of a project over its entire life, from cradle to grave. This can, at times, render the LCC frameworks far too broad for relevance.

Usage complexities Perception of time consumed in these analyses deters their frequent adoption. Complexities in the software further add to this issue.

Difficulty in reconciling values using different approaches

Despite addressing the same problem, there are subtle variations in the tools that are not clearly demarcated upfront. Variation in base information in two different alternatives can result in incomparable analysis.

Low awareness Educational initiatives are lacking, and little has been done by major industry stakeholder groups to consolidate the stray efforts made in this direction.


Life cycle cost comparisons for building components or equipment can be accomplished rather easily if there are no significant financing costs or differences in procurement costs among the various alternatives considered. However, this is rarely the case. Such variances are commonly encountered in gathering information on any of the following:

Initial cost of each system

Expected life of each system in years

Expected average yearly maintenance, operation, and repair costs of each system

Maintenance and repair costs that occur only every several years, averaged over the

time between occurrences

Operation, including fuel, electricity, and water use costs, as well as ongoing costs

such as operator wages, regular cleaning, and restocking

Any salvage or other residual value that can be derived out of the system at the end

of its intended application


29

Assembling this information can be a challenge, sources are often inadequate, and most importantly, the reliability of information, even from original sources such as manufacturers, is questionable. As a result, LCC estimators heavily rely on experience of the O&M staff, as well as their own past knowledge to come up with a reasonably sound analysis. As indicated earlier, presently available tools comprise of both free as well as paid options. Frost & Sullivan’s research for this project indicates that the intelligent buildings industry participants have maximum familiarity and/or experience with the following tools:

Building LCC (BLCC) by NIST

DOE-Lawrence Berkeley National Laboratory jointly developed tool28

eQUEST by Energy Design Resources29

ATHENA Eco Calculator and Impact Estimator30

Others/Partially Used31

Federal Energy Management Program’s energy cost calculators

State Developed Models for LCC Analysis – such as for the state of California and

Georgia

Among those mentioned above, primary research conducted among various industry participants for this project confirms that NIST’s Building LCC (BLCC) appears to have a significantly wide acceptance among various users, and is considered the most flexible, with scope for maximum detail orientation. Moreover, it is considered a standard for most public sector projects. It calculates LCC, NS, SIR, adjusted IRR, and payback for any alternative relative to a base case. Reports provide good detail on payback time, energy consumption (in dollars, kilowatt hours, therms, and British thermal units), and emissions. Reports are relatively straightforward and easy to set up, compared to other tools. There are some limitations. Computation can be obtained for a 25-year life cycle only. The financing information must be entered in a format that is not intuitive to people who are not normally involved in financial calculations. Nonetheless, BLCC is a far more recognized tool, and has been used as a base for customizing LCC by various stakeholders in the industry at present, particularly in projects with the government sector, as indicated by primary and secondary research undertaken for this project.


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2.6 LCC and the Role of Building Information Modeling (BIM) Evaluating individual stages of a building’s life cycle, post-construction, are equally important to judge its LCC and impacts accurately. Design, construction, and technology integration are only partial elements of a building’s life cycle. Operational phases including maintenance, repairs, and refurbishments are equally critical in helping drive down LCC. The concept of building information modeling has come to play an important role in this regard, and, is in many ways, considered a precursor to comprehensive LCC analysis. Frost & Sullivan’s ongoing research in the intelligent buildings industry suggests that even though BIM was initially more confined to supporting design and construction, it is increasingly being utilized to support facility operation and management functions in intelligent buildings. Given that more than 80 percent of the total life cycle costs associated with a facility occur post construction, building owners and operators stand to benefit by adopting BIM32. Facility information in BIM specs empowers owners and operators to take advantage of a growing breadth of available software tools, with applications supporting a host of elements such as energy efficiency, asset location, security, health and safety, and predictive HVAC management without data updates. However, for best results, users need to ensure that data is routinely captured and made available for gaining insight into a facility’s performance to improve future returns on their investment. The benefits range from helping asset managers to streamlining preventative maintenance through integration of data management processes, projecting repairs and renovations accurately, reducing cost of renovation and retrofit projects, and enhancing energy use information through proper analytics and diagnostics. But, most importantly, BIM helps to improve communication and collaboration between consultants, vendors, owners, and asset managers through the various stages of the building’s life cycle. This concept of life cycle BIM provides an opportunity to share building information during initial design and construction, building operations, and renovation or retrofit projects. There are several products33 that have found acceptance within the intelligent buildings industry, from suppliers such as Autodesk and FM Systems, IMAGINiT Technologies to enterprise resource planning solution providers such as SAP (SAP for EC&OTM). According to a study conducted by NIST, losses resulting from poor interoperability between different computer-aided design, engineering, and software systems accounts for more than $15.8 billion per year34. Integrated life cycle BIM strategies help reduce these losses by enabling access to valuable information compiled from multiple systems. For instance, based on the primary research findings of this project, the University of Southern California uses an integrated life cycle BIM in combination with other systems including Honeywell’s Enterprise Buildings Integrator™ to manage all sensors and energy meters across the campus to achieve significant operational efficiencies. Among the major drawbacks with present BIM models, issues with manual and/or duplicate entries, interoperability specifications of the models, largely disparate information collation structure, and lack of education and training stand out as the main


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deterrents. The usage statistics for BIM are considered relatively progressive, with expectations of growing usage over the next few years. As with LCC tools, Frost & Sullivan’s ongoing research in the intelligent buildings industry indicates that consultants appear to lead the user category. However, BIM has found considerable acceptance among asset managers and building owners as well. This trend could potentially help the intelligent buildings industry participants to further the receptiveness and adoption rates in LCC itself, considering the fact that the push towards advocating a life cycle BIM is gaining steady momentum.

2.7 Building Intelligence Ratings and LCC The ability to rate a building’s intelligence helps to provide essential information regarding choices of systems and sub-systems, and the level of integration adopted to achieve certain objectives and goals. These tools help to support the integrated design and delivery process, in addition to LCC. The intelligent buildings industry has witnessed the introduction of several tools that work towards evaluating a building’s intelligence quotient; thereby, providing valuable insights into integration aspects, retrofits requirements, and cost planning. Jones Lang LaSalle’s Building Intelligence Quotient35 (BiQ) tool is a notable development in this area. As a Web-based tool, BiQ provides a means to evaluate and measure the value of intelligent building performance and offers input towards design for integration of building intelligence in new and retrofit projects. Using BiQ and comparing BiQ values across corporate portfolios provides new ways to learn about actual building performance and improve decision making for the automation systems of future buildings. Owners and developers with multiple properties can also use the BiQ tool to assess and compare the building intelligence systems in their portfolio. The modular assessment generates a report that provides benchmark rankings and recommendations for improvements in the following categories: building automation, communication systems, annunciation, security and control systems, facility management applications, and building structure. For LCC modeling, such data on existing degree of intelligence works as a valuable initial information base. The adoption rate for such tools is gradually increasing among building owners as it helps to position their assets distinctively against less intelligent ones. Such intelligence ratings can offer necessary impetus to more comprehensive evaluations such as LCC. The intelligence evaluations will help building owners better define efficiency and integration targets for their assets, and evaluate present and future cost of improvements and upkeep to achieve a desired standard of intelligence.


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3 Opportunity Identification for LCC use in Intelligent Buildings 3.1 Identification of Market Demand In this section, the potential for implementing LCC techniques based on a review of exhibited demand in the intelligent buildings industry is analyzed. As part of this research, Frost & Sullivan interacted with various intelligent building owners and asset managers to gain their perceptions on intelligent building solutions, their adoption rate, likelihood of revamping technologies in the new future, perceptions regarding LCC use, issues and challenges. The analysis provided here is based on the feedback obtained from these groups. A parallel demand-side research1 was carried out amongst a pre-screened limited sample, comprising of 150 target respondents in the United States and Canada. A set of 12 intelligent building technologies were included in the sample. While the level of importance accorded to asset value and ROI is commonly cited by several respondents, their interpretation and means adopted to evaluate varies. Before proceeding to the discussion on the specifics of LCC adoption, it is important to understand their view of intelligent buildings and technology adoption criteria. The findings of this research are summarized below. Exhibit 3.1 shows the types of intelligent buildings that were covered as part of this research2. Exhibit 3.2 shows the expressed familiarity with intelligent building solutions3.

Exhibit 3.1: Industry Representation Exhibit 3.2: Familiarity with Intelligent Building Solutions



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While familiarity and current usage rates are relatively directional, in that those technologies that have higher levels of familiarity also have higher levels of current uptake rates, there are significant gaps between current usage and familiarity. On average, there is a gap of 52 percentage points across all 12 technologies. Despite that decision makers know about these building technologies, although they may not be frequently using them. Of the facility decision makers who are currently not using these technologies, the majority is likely to adopt within the next two years. Exhibit 3.3 shows the impact of familiarity on usage witnessed among users4. Exhibit 3.4 shows the future adoption potential5. Exhibit 3.3: Impact of Familiarity on Usage

Exhibit 3.4: Future Adoption Potential




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Exhibit 3.5 shows the factors driving technology selection6. Although the majority of the respondents cited reliability as a key decision making factor, it is interesting to note that reduced operating cost, ROI, and integration benefits are clearly accorded importance in the buying process. However, cost perceptions, primarily related to initial purchase and installations, are given due importance. Nonetheless, qualitative feedback indicates that increasingly realizing better asset value with the right technology is gaining importance among users. The methods engaged to that end are perhaps not adequate, and definitely inconsistent. For instance, only a small percentage of the respondents were proactively requesting ROI demonstrations, including LCC analysis, when consulting with project partners. In-house methods and processes to achieve the same were instituted in some cases, but majority did not have any standard procedure to achieve that. Exhibit 3.5: Factors Driving Technology Selection

Exhibit 3.6 shows the distribution of respondents proactively requesting ROI and LCC analysis from project partners7. Exhibit 3.7 shows the percentage of respondents using some form of in-house methods to achieve the same8.


Exhibit 3.6: Proactive Request for ROI and LCC Analysis from Project Partners

Exhibit 3.7: Percentage of Respondent Using In-house LCC Methods


Integrated Design Approach – 75%, Other – 25%


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Most in-house methods for deriving LCC and other cost justification analysis are primarily done via use of basic financial modeling tools. Comprehensive LCC evaluation was done by a small 15 percent of the respondents. Of this group, only a few had familiarity with specific industry-developed LCC tools cited in the previous chapter. Some of these users developed their models based on previously received LCC analysis from external project partners; therefore, the level of customization to conform to their actual project requirement is somewhat questionable. Convenience, and the availability of a template solution, is what prompted this attempt in the majority of such cases. Of the 25 percent of respondents who proactively requested LCC analysis from their project partners (mostly consultants and OEMs), a significant 75 percent pursued an integrated design delivery approach to their projects, while the balance 25 percent comprised of other ad hoc/non-integrated approaches. This represents a strong correlation between the project approach adopted and the corresponding receptiveness towards LCC. These projects were pursued with strong evaluation of the design and delivery process, with the lowest life cycle cost alternative being proposed as the best fit. There is a significant non-user category that represents potential for conversion to users, provided some the challenges they cited are mitigated through collaborative industry efforts. The three major issues expressed by industry participants pertain to cost, technical barriers, and communication challenges. Exhibit 3.9 shows the various challenge factors that were rated on a scale of 1-10, with 1 being of lowest importance, and 10 being of highest importance9. Technical barriers pertain to lack of knowledge of operating LCC tools, confusion about what data to feed into the base model, lack of software and data modeling skills. Exhibit 3.9: Factors Challenging LCC Adoption

Product familiarity is considerably low for most non-users, making the issue of supplier support a less critical challenge. Although the cost of the LCC tool itself is not a critical consideration, it is the perception of time cost which makes most respondents in this



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category somewhat averse to consider LCC adoption. Engaging in-house staff to comprehend and carry out these evaluations is not a priority. Given the option, they would rather consider service providers to add that to their list of deliverables. However, their own technical challenges and inability to fully comprehend the software aspects, calculation criteria, and, most importantly, lack of understanding of the value of customizing any such tool to their specific need further keeps them from engaging with project partners to include LCC analysis as a prescriptive item to their list of tasks. Finally, communication issues that stem as a corollary to the issue of technical barrier make LCC incorporation for these respondents a daunting task. The lack of knowledge of the tools, and their perception of value to overall project success, makes it harder for these respondents to communicate with external partners as well as internal financial staff.

3.2 Stakeholder Interaction Process in LCC Adoption Based on the demand potential anticipated from the user analysis and a review of the challenge factors that continue to propagate non-adoption, it is clear that the interaction process in the intelligent buildings industry needs to undergo some changes to achieve LCC adoption. Given the preliminary state of endorsement witnessed by LCC tools and similar cost-justification techniques, as revealed by this research, it is premature to conclude these challenges are major restraints and roadblocks. In fact, they represent opportunity areas for industry participants to capitalize on. These opportunities, combined with the value propositions they present each stakeholder group with, can be optimized to promote LCC adoption to their advantage. Exhibit 3.10 provides a broad list of opportunities, developed based on the findings of this research, that applies to the key stakeholder categories and the factors that will ensure these are realized successfully through changes in the interaction process with other value chain partners. Exhibit 3.10: Opportunities and Value Propositions for LCC Adoption

Stakeholder Opportunity Value Proposition Success Factors

OEMs, technology vendors, SIs

Extending their engagement cycle with clients by voluntarily offering LCC computations and continued support as part of the bundle

Ability to up sell and offer consolidated products and services

Recognizing the role of the contractor as a key buying influencer; therefore, engaging more with this category to help demonstrate product value to clients

Creating parallel revenue streams and additional partner ecosystems

Expanding engagement terms with existing clients

Engage more with value chain partners and their associations, particularly those that do not presently advocate LCC and similar techniques

Consider incentivizing tradespeople to propagate technology solutions

Consultants and external project partners (ESCOs, CEs, architects, etc.)

Revenue prospects from better project value justification and longer engagement cycle with clients

Credibility and specialty in the new domain of intelligent buildings

Collaborate with client staff to support knowledge- building initiatives around LCC


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Stakeholder Opportunity Value Proposition Success Factors

Expanding their reach and presence and offering adjunct services

Building experience and specialty in the growing intelligent buildings segment

Enhancing project presence and visibility among clients

High margin prospects

Collaborate with technology vendors to exchange knowledge base

Understand the role of technology in achieving and maintaining a high value building

Building owners, operators, investors

Capitalize on buyer’s market advantage – benefit from bundled solutions from project partners with LCC incorporated in it

Take advantage of a well-coordinated integrated design approach with cost advantages, instead of dependency on contractors

Achieve high performance buildings, with operational efficiencies and savings

Realize returns from investment in smart technologies and better buildings

Enhance asset life

Qualify for certifications

Command higher lease and capital values

Consider costs and incentives in building financial justifications for projects

Gain control of projects – encourage collaboration between vendors and consultants

Assume accountability of projects – ensure right technology is procured

Make technology overhaul decisions on time to avoid surmounting inefficiencies

For OEMs and technology vendors, the key success factors lie in their ability to engage with value chain partners and offer product and technology knowledge. They would also need to directly engage with industry associations representing consultants to enhance technology awareness and acquaint with construction guidelines. Additionally, providing documentation of LCC, performance metrics and savings from their technologies, and incentives to tradespeople could increase the selection of their technologies through a better justified process than upfront capital cost considerations. Given the opportunity that consultants and project partners have to expand their capabilities and value proposition into the growing intelligent buildings domain, it is critical for this segment of participants to understand the various aspects of an intelligent building, the technology components that go into it, and the LCC analysis of such technologies. The partners would need to collaborate with the technology suppliers, not only to increase their knowledge base, but also to educate vendors on construction practices and guidelines, so that both parties can mutually benefit from collaborating in projects. Nevertheless, the groups of stakeholders that can distinctively enjoy the advantages of fundamental changes to the interaction processes are the building owners, asset managers, and investors. They can benefit from choosing the best technology from a host of competitive offerings. They need to acknowledge the benefits of owning assets that are not only enriched by such technology, but considerably enhanced in value derived from the market. The critical success factors for this category would encompass the need to use lowest LCC as a key determinant of project success. Additionally, taking direct responsibility for projects and procurements, and calling for an integrated project delivery approach, rather than entirely relying on third parties to make these decisions is important. Delayed replacement plans only add to an inefficient asset and result in higher operational expenses of running that asset. Therefore, infrastructure



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renewal decisions would need to happen faster in order for this category of participants to maximize their opportunity of benefiting from owning intelligent buildings. Exhibit 3.11 shows the demand potential for LCC adoption in the procurement of various intelligent building solutions, as revealed by primary and secondary research undertaken for this project. This overall potential assessment is provided based on feedback obtained from industry stakeholders during the course of this project. The potential for these technologies and services has been categorized based on the likelihood of building owners and consultants to evaluate these through LCC techniques and other cost justification/ROI modeling. Exhibit 3.11: Potential for LCC Evaluations for Selecting Various Intelligent Building Solutions

High Potential Category Technologies that fall within the building owner’s ambit of critical infrastructure are covered in this category. This includes HVACR, lighting, building infrastructure and structural elements, energy service performance contracts and retrofits, fire and life safety, and IT and communication components. Technology upgrades are considered essential to optimize operational efficiency and to reduce energy costs. Thus, the likelihood of lowest LCC being used as the project determinant is relatively high. Moderate Potential Category This category is further sub-divided into moderate-certain and moderate-uncertain. The moderate-certain group includes technologies such as building automation systems and controls, physical security components, and many application software solutions, wireless technologies, and integration platforms that are being offered through various technology contractors and SIs. Technology sophistication in these areas makes them more likely to be commissioned via an integrated technology contracting approach with vendors and consultants brought together to collaborate on their implementation. Therefore, the incidence of lowest LCC being a determinant of project commissioning is more certain.



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The moderate-uncertain group includes existing contractual services such as outsourced facility management, energy information monitoring, and analytics. Services such as facility management are usually procured through contracts10. However, long-term public-private partnership projects are an exception to this rule. Given the fact that the contract period for such projects could span up to 30 years, and would also include technology upgrades and retrofits at the service provider’s risk, LCC evaluations are almost mandatory in such cases11. New outsourced services such as energy information modeling and monitoring are still mostly experimental and currently in the pilot phase. These services will continue to be procured via direct negotiations between building owners and vendors, with little emphasis given to lowest LCC. Low Potential Category Components such as commissioning and audits, remote monitoring, predictive optimization, and diagnostics fall in this category12. These components are expected to hold limited potential for being procured via detailed LCC analysis as they fall within the purview of “intangible/pure services”. They tend to be engaged on a need-based manner, and are either offered to building owners as free pilots, or clubbed by project management firms within their portfolio of services offered, thus eliminating the need for any separate cost-benefit analysis.

3.3 LCC Adoption Preferences by Vertical Segment The usage rate for LCC is relatively higher in new build projects as opposed to renovation and retrofit. Given the slow growth of the new building market, demand for intelligent building projects will continue to grow moderately. Primary and secondary research undertaken for this project indicates that relationships with project management and design build firms are leveraged to procure technology and services on an ad hoc basis by most building owners. The responsibility of providing LCC analysis rests with these consultants. For renovation/retrofit projects, there appears to be a higher incidence of using LCC analysis. This is partly due to the fact that replacement budgets are taking longer for approval with budget curtailments. Therefore, the ability to demonstrate ROI and lowest LCC provide speedy sanctions for pending replacements and renovations. As commercial buildings are generally tenanted facilities, occupancy and faster leasing prospects drives the need for technologies and services procured by the building owners and operators13. Short-term gains play a key role in decision making. Energy savings and green labels have gained relative importance among building owners in this category because both help in differentiating properties. Yet, longer payback from investment in smart technology is not attractive. Technology procurement is also partly constrained by budget issues. There is sporadic use of LCC analysis for renovation and replacement projects. Frost & Sullivan’s interaction with industry participants for this project indicates that for major retrofits and high-cost solutions such IT and technology integration, LCC finds incorporation via the integrated design delivery process adopted. For new build projects, LCC adoption is more frequent, with consultants voluntarily incorporating LCC into pre-project evaluations.


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The duration of projects in the industrial segment tends to be longer than in others, and contractors operate as the most important touchpoint throughout the procurement process. This gives the contractor influence over design changes during the execution phase of the project. The use of LCC to justify project design cannot be overruled at the initial phases when consultants are engaged. However, there is a high likelihood of such lowest LCC-backed design and technology specs being value-engineered out later on in the process, irrespective of the project being in the new build or renovation category. Institutional and government buildings appear to be the only category where budgets and pricing do not exert an overwhelming influence on technology procurement or vendor selection, according to the primary research findings of this project. Because this segment has access to performance contracting and has set some stringent energy efficiency goals for their facilities, their appetite and adoption rate of intelligent building solutions, justified via lowest LCC calculations, is relatively better than the other two vertical segments. This segment also operates on direct OEM and vendor relationships, and sole source contracts, eliminating the risk of low-priced, contractor-led solutions taking away from the objective and vision of the project.

3.4 Incentivizing LCC Use While incentivizing LCC use is a consideration for the intelligent buildings industry, it is important to point out that there is a significant opportunity for projects utilizing LCC criteria to address issues related to green buildings, as well as benefit from already available green incentives. Data analyzed in an LCC model, with regards to incorporation of technologies pertaining to day-lighting, energy efficiency, and sustainable materials can directly help building owners and asset managers to avail of credits in green rating tools and certifications. The majority of projects that have used some LCC technique or ROI modeling were also involved in obtaining green accreditations14 from various agencies15 such as U.S. Green Building Council (LEED), the Building Owners and Managers Association (BOMA), and the Green Building Institute (GreenGlobes). Furthermore, there are other programs such as Architecture 2030 and the Living Building Challenge that are already compelling industry participants to go beyond the criteria described in green credit tools. Both LCC and BIM are extensively used in such projects as they help to build the investment case. For example, periodic review of reports conducted via LCC analysis or BIM modeling are being used to track green credits. Frost & Sullivan is of the opinion that rather than incentivizing the use of LCC itself, the industry participants need to consider ways of mitigating the more fundamental barriers pertaining to LCC adoption, which may not be resolved by introduction of a specific LCC-oriented credit alone. The present set of credits available through various rating tools in the intelligent buildings industry is incentive enough for pursuing well-justified projects. The fact that intelligence in technology further adds to greening initiatives is already well proven, as the case studies in this report will suggest. Training and educational efforts and collaboration in project delivery are more critical than LCC credits to increase adoption levels.


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4 Evaluation of Market Approach for LCC 4.1 Optimization of the Technology Integration Model The practices currently followed in pursuing intelligent building projects and technology purchases are well entrenched among all value chain partners, and have so far provided a structured way of undertaking projects. However, there are some fundamental issues in each of these methods that lead to either project failure or completing projects below their set expectations. The incorporation of LCC or similar investment justification criteria could potentially help avoid such issues. Frost & Sullivan’s interaction with various stakeholders as part of this project led to a qualitative assessment of optimization possibilities that could help mitigate some of the flaws inherently present in project evaluation methods followed in the industry. The findings of this research indicate that the possibility of making LCC a mandatory prerequisite is not considered to be effective or attainable in the short term. This is because use of LCC analysis tools does not form part of an institutionalized practice at present. To achieve such a mandate would require distinct focus on the following elements shown in Exhibit 4.1. Exhibit 4.1: Feasibility of Mandating LCC

Elements for Achieving a Mandate for LCC

Feasibility Time Frame* and Steps Needed

Codification of LCC analysis as a norm by standard bodies (e.g., ANSI, ASHRAE, others)

Medium-High Make provisions in building and product specification codes; long term

Mandating LCC as a prerequisite to obtain institutional project funding

Medium Lobby with financial bodies to advocate the importance of LCC over other financial metrics; mid term

Changing building owners’ perceptions

Medium-High Extensively use education, training, and other interactive processes; short term

Redefining utility-led incentives and rebates

Medium High Lobby with utility commissions and regulators to improvise incentives and rebates supporting LCC; mid-to-long term

Certification processes including LCC modules for tradespeople

Low-Medium Promote sponsorships from technology vendors for such certification/training processes; short term


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* Short term: 2–3 years, mid term: 5–7 years, long term: 10 years or more


Although the feasibility aspect is considered more favorable for elements such as codification into standards and mandating as a prerequisite for obtaining finances, these are not considered attainable within the immediate period. Codes and standards take a considerably long time in the intelligent buildings industry to get fully approved and sanctioned for application. Getting financial bodies to consider LCC as a prerequisite is not impossible, though, it is less likely that it would be considered as the only way of approving financing when other financial metrics do not in any way render a project less risky to their evaluation. Including LCC modules within industry certification processes is a valid option. Nonetheless, proper provisions need to be made with regard to offsetting any increased cost to the tradespeople seeking such certifications. Because most LCC tools and techniques are either developed by not-for-profit organizations or nascent software providers, it may not be feasible to expect them to contribute towards any such incremental costs. OEMs and other established technology vendors would need to come forward to sponsor such costs. Most utility rebates and incentives presently available in North America are geared towards supporting short-term energy savings, initial payback, and immediate building performance achievements, with practically no emphasis on continued process monitoring or long-term cost modeling. For instance, the Ontario Power Authority has set aside $1.4 billion1 with respect to funding for energy conservation and demand management programs run by local utilities and distribution companies in Ontario, Canada over the 2011-2014 period. However, other than the incentives available for new building design that partially take some LCC components into consideration, the money paid out for conservation measures out of this total funding are generally for short-term savings achieved by customers. Similarly, conservation programs and incentives instituted by the California Public Utilities Commission2 for its participating investor-owned, public, and municipal utilities also favor short-term gains only. Although the “savings-by-design” concept applied to new building projects does attach due importance to continued monitoring and ongoing performance to determine progressive incentive payout, it falls short of linking incentives with stringent LCC modeling. This is despite the fact that provisions and directives under California Title 24, which advocates long-term LCC modeling, are used as the basis for energy and performance evaluation in determining such incentives. Because utility incentives are a key driver3 for building owners and asset managers to advocate energy-efficient designs and major retrofits, there is a possibility of propagating LCC adoption by linking such incentives to projects that support LCC use. This will require lobbying with utility commissions and regulators to the revamp incentive criteria prior to upcoming budget cycles, and could potentially be achieved over the medium-to-long-term period.


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Education and training efforts among building owners and asset managers could, in the meanwhile, be used as a more feasible option to not only familiarize them with the concept and value of LCC, but also to achieve better adoption rates without incurring major investments by any particular stakeholder group. Some voluntary efforts from OEMs and consultants are required in this area. In terms of making the technology contracting model more optimized, the following aspects need to be incorporated into the present practices to obtain better outcomes. These are interpreted based on the primary and secondary research findings of this project, and include: Supply chain collaboration – Delivering intelligent buildings requires close collaboration among building owners, architects, engineers, financiers, managers and operators, contractors, and suppliers. Collaboration is needed throughout the design, construction, and commissioning process to make holistic evaluations and tradeoffs that can lead to optimal solutions. Leveraging BIM can help achieve this to a large degree. Additionally, building technology organizations and their industry associations should find ways to work with the construction industry associations, contactor associations, and architect associations to make this a reality. Integrated design and delivery approach – There is a need for an integrated design delivery approach to replace the prevalent disjointed and transactional approach followed in project implementation in intelligent buildings. This includes integration of design and spec teams with mechanical and physical system suppliers, IT and communication infrastructure providers, and contractors at the conceptual stage of the project. Where a consortium of partners is involved and jointly accountable for project success, project profitability is considerably enhanced. Sharing LCC data and analysis can be far better achieved under such circumstances. This will prompt suppliers and service providers to collaborate and offer the most optimal solution, while at the same time capitalize on collective bargaining capabilities to influence selection. Opt for objective evaluation criteria – It is undoubtedly possible that competitive bids for project execution and technology selection will continue to thrive in a parallel manner in the intelligent buildings industry, regardless of how rapid a move the industry makes towards an integrated design and delivery process. One of the key issues with competitive bid processes is that the point criteria adopted for evaluation of competitive bids is highly subjective in nature. As such, there is no way of assigning the right importance to technology, value-add, or specialized bundled services in evaluating competitive bids. An objective evaluation criterion is required to ensure that product and technology selection is based on some quantification of actual benefits to the project/building, particularly its ROI. Avoid cost thresholds – Although cost thresholds are adopted to keep the project within budget estimation, these thresholds are neither realistic nor achievable in actual projects. Their invariable adoption often prevents accepting solutions that could have otherwise qualified on the basis of expertise and value. Some building owners and operators agree that there should be no compelling reason for such cost thresholds to


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be adopted. Others continue to resort to it, following it more as a traditional practice, as opposed to using it as a key determinant of project success. Removing this component could potentially help to optimize the process and allow for the inclusion of more vendors and suppliers into the selection process. This will ensure that the right project alternative is adopted, which is backed by lowest total cost of ownership. Role of quality surveyor/advisor – Given the disconnect among various delivery partners in the intelligent buildings delivery chain5, there is a critical need for autonomous supervision to ensure that processes are followed transparently and the correct choices are made in selection of products, technology, and services. The role of a quality surveyor or advisor is important in meeting this requirement. The intent is to introduce a neutral partner into the process that can function with autonomy and maintain the checks and balances in the process. This role can be fulfilled either by an appointed executive from the building owner’s organization or from the consortium of partners. Mandate a periodic feedback loop – The linear value chain does not require ongoing performance monitoring and continuous improvement, which is fundamental to a successfully delivered project. The high degree of industry fragmentation complicates the process of project implementation. This significantly limits the prospect for technology incorporation as well. Installers, architects, and even building operators often do not offer any vital feedback on the solutions they solicit, install, and operate, unless there is a problem. Including this as a prescriptive requirement into the contractual process can offer valuable insights into technology performance, cost benefit, and establish their importance in intelligent buildings projects. While some of these aspects are being incorporated on a project-to-project basis by suppliers and building owners, as indicated by primary research discussions among industry participants during the course of this project, a more concerted effort is required at the industry level to make these integral to the intelligent buildings industry.

4.2 Establishing a Market Approach for Inclusive Decision Making In the intelligent buildings industry, it is evident that the advent of new technology and service needs, and the emerging relationships between OEMs and service providers, is likely to result in convergence of domain expertise of various vendors to cater to these new requirements. Beyond this convergence of technology players, the integration of the design-build approach calls for collaboration among consultants and participants in other parts of the delivery process. The optimization requirements pointed out earlier will ensure that processes, participants, and engagement characteristics are brought together to make the market approach for all players more unified. The interaction process within the value chain can be made far more dynamic, which will help sustain the recommended changes. To evaluate how this can be achieved, a stakeholder analysis is presented below in Exhibit 4.2. The analysis is based on Frost & Sullivan’s interpretation of the primary and secondary research findings from this


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project. The first step is to identify the stakeholders who can exert the right influence towards achieving the right market approach for LCC adoption. Also, steps need to be taken to address those stakeholders that can either hinder the change implementation process or develop options and strategies to collaborate with them. Each group is plotted on the matrix provided as part of Exhibit 4.2. Exhibit 4.2: Market Approach to LCC Implementation – Stakeholder Analysis

Where options for influencing a particular stakeholder category prove redundant, a redefining of the service or involvement criteria is necessary to make the processes more acceptable. These options are discussed as follows: Coalition Building – The major stakeholders that this option should target are OEMs, utility commissions/regulators, and consultants. As indicated in previous sections, clearly these categories need to work more closely to help building owners and asset managers see value in an optimized design, no matter what upfront costs it may entail. For LCC adoption to reach desirable levels among consultants, OEMs, technology vendors, and building owners, the coalition among these two categories is an absolute requirement. And considering the vested interested they would have in promoting their technologies and services for the right price, they are in the best position to influence the same. In addition, working with regulators and utility commissions prior to upcoming budget cycles is necessary to ensure that funding allocated for incentives and rebates emphasizes the use of LCC evaluations in projects that apply for such incentives. Win Over – The building owners and asset managers fall within this target category. Strategy options that can be adopted to win over this category would include value demonstrations with use of best practice examples, offering bundled value propositions that can induce them to undertake more integrated design projects, working closely with them to reduce the technical barriers they face in adopting LCC and similar methods, and, most importantly, increasing the level of periodic interaction to keep them appraised of technology and design benefits.



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Leave Alone – At this time there is very limited need to involve any LCC tools and technique developers in the market approach development process. This category has developed a multitude of options that are yet to be fully tested for veracity and full applicability in the intelligent buildings industry. The few that have found adoption and acceptance to a certain degree are capable of providing the functional base for LCC incorporation. Further, the majority of them are either the output of not-for-profit organizations or very nascent developers, which makes it questionable whether they can, in any way, help in incentivizing adoption, other than offering training and educational support through mutually beneficial barter arrangements with other industry stakeholders. Collaborate/Incentivize – The least likely to promote LCC adoption are the contractors and integrators. Besides training and certification initiatives for them, a distinct need exists for suppliers and consultants to engage with this category of stakeholders to ensure they are at least able to communicate further the benefits of technology integration and an integrated design process for returns. The possibility of changing attitudes and increasing loyalty towards any particular brand or service provider is perhaps unachievable. However, suppliers and consultants would need to consider some financial incentives to ensure that they comply with the original project vision and do not change things midway in favor of low cost.

4.3 Prospects for Collaborative Partnerships

The market approach, and the ability to attain the collaborative partnerships discussed therein, will depend upon how well the stakeholders are able to address four critical areas of activity as shown in Exhibit 4.3. These activities have been identified based on Frost & Sullivan’s findings from the primary and secondary research undertaken for this project. A consolidated dynamic SWOT analysis is provided for the four areas as a whole. The elements of the activity areas are discussed as follows: Build/support – This includes activities such as pursuing lobbying efforts and working with partners and consultants closely to promote joint initiatives to support LCC adoption. Additionally, documenting past successes for collaboration partners to help better understand and evaluate business cases would prove beneficial. Lead/influence – Activities under this would include concerted efforts to move away from key barriers to technology adoption, doing away with proprietary solutions, seeking out partnerships among industry stakeholder groups, and promoting training and sponsorship efforts to help achieve LCC adoption. Develop – This includes efforts to help articulate individual value propositions, setting requirements for data inputs that can be procured and maintained easily and periodically, as well as building efforts to communicate technology and service value propositions and performance improvements effectively. Avoid –Under this activity area, stakeholders must try to incorporate initiatives that will help them avoid project solutions that are purely driven on the basis of cost, which


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ultimately leads to proposing a reactive solution, rather than one that provides long-term benefits. Avoiding transactional and disjointed interaction with other industry participants is absolutely necessary. Efforts should be made to be more entrenched in each other’s industry activities and work together. Exhibit 4.3: Activity Areas and Dynamic SWOT Analysis

There are distinct strengths, weaknesses, opportunities, and threats in pursuing these activity areas by all stakeholders. While industry presence, established influence, and brand positions could work as strengths, fragmentations in the value chain and limited established collaborative methods could weaken the initiatives. However, the opportunities lie in the ability for stakeholders to enhance revenue streams and engage longer with business prospects. Towards achieving this, all stakeholders must work towards dismantling internal divides, keeping pace with industry changes and working towards promoting more accountable project practices.



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5 Evaluation of Project Cases 5.1 Best Practices Review As part of this research, Frost & Sullivan evaluated a cross section of projects that lend themselves as illustrations of best practices. These projects offer valuable insights into how plausible changes are effectively endorsed by building owners and operators, with the help of technology suppliers and fulfillment partners, to implement projects more successfully. While these projects do fall within the purview of typical intelligent building projects, there are clear deviations made in the manner of execution and process flow, which ultimately ensured project success. The list of projects, highlighted as case studies in this section, include the following: Exhibit 5.1: List of Case Studies Evaluated

1-4

Project/Arranger Details

Western Kentucky University, Kentucky Arranged by Johnson Controls, Inc. and Western Kentucky University

Showcase of Energy Information System: Panoptix®

platform that

includes applications for utility tracking and reporting; fault detection and diagnostics; equipment performance analytics; measurement and verification; and a public-facing energy information kiosk.

Adobe Systems Incorporated, West Tower 12 Smart Floor, California Arranged by WattStopper and IBS, Inc.

Showcase of digital lighting management solution by WattStopper and IBIS-centralized software interface responsible for integrated sequences of operation, optimizing control strategies, and reducing energy consumption.

Virginia Tech Campus, Blacksburg, Virginia Arranged by Siemens Industry, Inc.

Showcase of the development of an operations control center, centralizing the coordination and management of the campus HVAC infrastructure, improvement in operations efficiency and responsiveness, and effective management of BAS data to improve decision making.

Microsoft Corporation Headquarters, Redmond, Washington

Arranged by Microsoft Corporation

Showcase of intelligent building system overlay, automating RCx program, optimizing campus portfolio (35,000 assets), improving labor efficiencies, and automating building performance reporting.



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Panoptix® Building Efficiency Management System

Johnson Controls, Inc.

Cloud-Based Building Automation and Analytics

Source: Johnson Controls, Inc., Western Kentucky University

Project Address: 1906 College Heights Blvd., Bowling Green, KY 42101-3576

Key Highlights:

Showcases Johnson Controls’ Energy Information

System: Panoptix®

platform that includes applications

for utility tracking, equipment performance analytics,

and measurement and verification, to name a few

Features:

Continuous diagnostics advisor detects abnormal

energy consumption and identifies equipment faults

Energy performance monitor creates energy baseline

models and tracks savings from energy efficiency

projects

Carbon and energy reporter tracks energy usage and

carbon emissions across and enterprise

Custom analyzer provides flexible trend analysis to

compare facilities, diagnose problems, and report

performance.

Technology Specialists: Johnson Controls, Inc., Panoptix

®

Client: Western Kentucky University (WKU)


50

This case study has been provided in arrangements with Johnson Controls, Inc., and Western Kentucky University (WKU). Project Overview WKU is a multi-site educational institution founded over a century ago. For the last three decades, the administration has actively pursued efficiency measures, and has emerged as a pioneer in greenhouse gas emissions reduction and energy usage control. WKU has had installed Johnson Controls’ Metasys® building management software in 56 campus buildings on three sites since 2007, but has not been able to transform that data into actionable intelligence until now. With the installation of Johnson Controls’ Panoptix® building efficiency solution, the aggregate data collected by Metasys® can be uploaded into the cloud where it can be analyzed through a range of applications to deliver better control over energy use, equipment operation, and occupant comfort. In addition to Panoptix®, two other similar offerings were evaluated by WKU. Although all three were comparable in cost/investment, WKU considered Panoptix®, from a capability point of view, technically far superior. Facility Details The facility is an institution of higher education, including classrooms, dormitories, sports and fitness facilities, libraries, meeting areas, laboratories, and offices. Over 300 monthly utility bills were integrated into the Panoptix® platform.

Total area 56 buildings distributed over three campuses

Year of construction 1906

Student population 21,000

Technical Requirements of the Project:

Create powerful data analytics platform to aggregate raw data collected by Johnson Controls’ Metasys® building automation system

Arrange data into actionable intelligence supporting energy-usage-based decision-making practices

Develop easy-to-use interface for 24-7 monitoring of energy usage and building status is real time

Provide solutions for building efficiency measures, retrofits, preemptive maintenance, and system adjustments, translating into operational cost savings

Panoptix®, Johnson Controls Inc., WKU

WKU’s objective was to implement real-time monitoring of a multi-building, higher education facility and to identify opportunities for operational savings including reduced energy usage.

Project Partners Western Kentucky University (WKU) Johnson Controls, Inc.

Source: Johnson Controls, Inc., WKU, 2013


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Panoptix® Solution from Johnson Controls, Inc.

Bringing data to life in a relevant, meaningful, and actionable way

Panoptix® is a building efficiency platform that takes complex building system data and turns it into actionable insight. Panoptix® collects data from a single building or a global enterprise and transmits it to the cloud where it can be used with a range of applications to deliver better control of excessive energy use, equipment operation, and occupant comfort. It tracks trends, charts energy use, and continuously monitors equipment for faults that could affect energy consumption. The Panoptix® solution is an open platform, which means new applications can be added at any time, both by Johnson Controls and by third-party developer partners. Users are encouraged to share and explore best practices through the online Panoptix® community. A dedicated team of professionals is assigned to each customer to help with installations, personalized tech support, training, and coaching.

Panoptix® Design Features

Continuous Diagnostics Advisor

Energy Performance Monitor

Carbon and Energy Reporter

Custom Analyzer

Continuously monitors data from existing building systems

Automates measurement and verification of energy savings

Monitors comprehensive data from measurement instruments

Allows user to investigate and report equipment performance from multiple sources

Automatically detects problems that waste energy, create discomfort, or lead to equipment failure

Compares actual measured energy usage to industry baseline

Allows management of cost, consumption, greenhouse gas emissions, environmental metrics, and facility equipment

Correlate data with weather, utility bill, and equipment data

Controls meters, VAV boxes, and AHUs with multiple views to identify, diagnose, and correct system faults

Uses industry standard measurements IPMVP Option C

Determine performance improvement opportunities

Source: Johnson Controls, Inc., 2013


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Key Measurement at a Glance for the WKU Project

Pay-as-you-go SaaS Pricing Model

Proven Building Efficiencies Simple Payback

Keep costs low by paying only for

what is used

Corrected multiple system faults Six months, with energy savings going

forward

Custom-designed service package

with tech support

Improper sequencing, valve and

damper positions, ventilation, and

missed opportunities to reduce peak

demand

The Need for Building Efficiency Systems

Improperly controlled or degrading equipment can account for 10

to 30 percent of energy used in commercial buildings. Monitoring

equipment in real time and employing efficiency diagnostics can

help identify and address problems before they become critical.

Through proper equipment tuning and preventative maintenance,

costly and uncomfortable critical failures can be completely

avoided, as well as increasing efficiencies across the board.

Equipment life spans are increased as issues can be identified

and corrected before they become serious. The incredibly short

ROI period enjoyed by WKU will allow them to invest that new

liquidity back into their facilities and enjoy continued savings going

forward.

Technology Procurement Process

WKU identified an under-utilization of data collected through

Johnson Controls’ Metasys® building automation system. They

contracted with Johnson Controls to analyze and package that

data into actionable intelligence that could translate into

operational cost savings.

The project process is shown in the following section.


Monitoring takes the guesswork out of equipment maintenance and efficiency tuning. Building systems’ life span is increased as preventative maintenance can be scheduled when needed. In most cases, at least 10 percent energy savings can be immediately realized by facilities

managers.


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Project Stages Flowchart

Data Collection

• Since 2007, WKU has used Johnson Controls’ Metasys® to monitor and collect data on 52 structures in 3 locations. No data analytic framework was in place and conventional analysis was prohibitively cumbersome.

Need for Analytics • Johnson Controls contracted to provide a framework for

data collected through existing building automation system into actionable format.

Data Organization

• Johnson Controls’ Panoptix® suite of analytic software designed to organize data for energy- and environmental-based decision making. Panoptix® is open source and constantly upgraded, extended, and improved.

Implementation • WKU facilities data was uploaded to the Panoptix® cloud

platform, accessible via mobile app platform for real-time monitoring and control.

Monitor

• Multiple inefficiencies were immediately identified and corrected to provide improved operational cost. Preventative maintenance can be scheduled before issues affect the bottom line.

ROI • WKU recovered its investment within six months of

deploying the Panoptix® suite of solutions.



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The Energy Performance Monitor Process

The energy performance monitor, which is part of Panoptix® helped in

the following areas:

M

Key Achievements and Cost Avoidance

Since their investments in Panoptix®,

WKU realized a target energy

savings in six months amounting to $192,463. Additionally, WKU extensively uses engineering algorithms to view

and run equipment. Based on these algorithms, they are now able to

see, via Panoptix®, subtle performance changes against the

standards, and are able to make near real-time adjustments, further

helping to drive down costs. For instance, using Panoptix

®, WKU was able to identify some very

large air handling units that were simultaneously heating and cooling,

resulted in air flow volumes running 10 to 15 percent above set

points. Accordingly, adjustments and changes could be made to

correct the situation. From a capital budgeting perspective, the success of Panoptix

® has

had a very specific impact on a $50 million renovation project. The

Panoptix® Continuous Diagnostics Advisor application will be used to

commission this project. By using this application, WKU estimates it

will save 50 percent or more on commissioning time and labor. By having better visibility over millions of square feet of buildings,

WKU is much better equipped to proactively take care of issues

before they get to a point of having to conduct a very large retro-

commissioning project, which typically can run close to $500,000. WKU expects to achieve extended equipment life with the installation

of Panoptix®

. For instance, the buildings’ Bellimo valve actuators

were detected cycling several times a minute. If left unchecked,

WKU would have had to replace these valves in a matter of months.

By correcting the cycling issue, they now expect these values to last

several more years.

Created an energy performance plan

Specified a utility rate with consumption (kWh)

Created a whole-building baseline model

Configured the system for calculating and reporting savings

Calculated savings during project’s installation period

Calculated savings during the project’s reporting period

Outdated building systems can cost an extra 10 to 30 percent in energy and suffer from shorter life spans through lack of preventative maintenance.

Panoptix®

identifies and

communicates energy fluctuations and anomalies in real time to support efficiency-based decision making. Flexible pay-as-you-use features allow the solution to be tailored to need.



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It has been much easier for WKU staff to prioritize maintenance;

address issues faster; and increase the quality of their work,

productivity, and customer satisfaction.

In the case of WKU, Johnson Controls’ Panoptix® suite of

solutions allowed the university to realize immediate operational

cost savings through more efficient use of existing building

automation systems. The open-source, cloud-based mobile

application transforms raw, aggregate data into actionable

intelligence to deliver an attractive ROI period with additional

savings going forward. The open-source platform used by the

Panoptix® application developers ensures continued improvement

in data analytics software and the possibility for even greater

cost-saving mechanisms in the future.


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Digital Lighting Management (DLM) in Intelligent

Buildings

WattStopper DLM - Defining the future of lighting load control for intelligent buildings

Source: Adobe Systems Inc.

Project Address: Adobe Systems Incorporated West Tower 12 Smart Floor 345 Park Ave. San Jose, CA 95110

Key Highlights:

Intelligent Building Information System (IBIS)

operating HVAC, lighting, and plug loads on

BACnet, Modbus, and SNMP protocols

IBIS-centralized software interface responsible

for integrated sequences of operation,

optimizing control strategies, and reducing

energy consumption

WattStopper DLM providing occupancy

measurements and lighting controls through

BACnet

Software-based continuous commissioning

identifying for fault detection and diagnostics,

work order generation, etc. to sustain energy

efficiency

Technology Specialists:

Integrated Building Solutions (IBS), Inc.

WattStopper

Client: Adobe Systems Inc.

Operator: Cushman & Wakefield


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This case study has been provided in arrangements with Adobe Systems Inc., Cushman & Wakefield, Integrated Building Solutions (IBS), and WattStopper. Project Overview Adobe’s headquarters consist of three high-rise office towers located in downtown San Jose, California. With approximately 2,100 employees locally, Adobe is the largest corporate presence in downtown San Jose. The San Jose headquarters complex is comprised of a million square feet of office space and parking facilities spread over three towers. The project showcased here automated energy conservation by creating an integrated occupancy-driven HVAC and lighting solution for the 12th floor of the West Tower. For this project, Adobe took a holistic, end-to-end view of the space they were using, the associated metrics of energy efficiency, and how their workspace was designed and operated at each floor level. The purpose of the ‘floor remodel’ approach was to create a modern and highly efficient, collaborative work environment with a contemporary and energy-efficient design as the guiding principle. Facility Details The facility is designated for general office use. It has three occupied towers, comprised of Almaden and the East and West towers, with a total of 51 occupied floors. The floor space details are as below: Total Floor Space 1,000,000 sq.ft.

Number of Towers, Year of Construction and Occupied Floors

Total towers – 3 Almaden (2003) – 17 floors East Tower (1998) – 16 floors West Tower (1996) – 18 floors

Total Space in the West Tower

755,000 sq.ft.

Remodeled Floor 12th Floor of West Tower

Project Area of 12th

Floor 25,000 sq.ft. Source: WattStopper and IBS, Inc., 2013

Technical Requirements:

Design and implementation of a highly efficient open floor plan that would lower operating costs

Increase floor capacity while improving employee comfort

New floor level energy management solution that was consistent with Adobe’s current portfolio-level energy management automation and reporting

New feature-rich lighting controls that support an integrated approach to energy conservation

Leverage and enhance existing Johnson Controls HVAC solution at the variable air volume (VAV) level

WattStopper DLM Solution at the West Tower, Adobe Inc. Headquarters, California

Adobe’s objective was to create a highly efficient and collaborative work environment with a highly automated and energy-efficient design as the guiding principle.

Project Partners Adobe Systems Inc. Building Owner Cushman & Wakefield Facility Operator Integrated Building Solutions (IBS) IBIS SmartFloor Software and Master System Integration (referred to as IBIS in the case study) WattStopper Digital Lighting Management System DevCon General Contractor ACCO Mechanical Contractor Avidex A/V Contractor Valerio Dewal Train Architect PG&E Utility Provider The Cadmus Group LEED Commissioning Agent


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WattStopper’s DLM Solution

Transforming Lighting Energy Management

The digital lighting management (DLM) technology platform provides a digital control infrastructure at every switch, outlet, lighting load, and control point for optimal energy performance. DLM delivers a robust customer experience. For the Adobe project, master integrator IBS selected WattStopper to provide DLM based on proven track record of excellence.

Simplicity Flexibility Scalability

Fewer essential components for easy specification in any type of space

Building block architecture for design and installation freedom

Single point of connection per room for centralized maintenance and reduced cost of ownership

Plug-together devices to avoid wrong wiring

Push ‘n’ learn personalization for simple to complex sequences of operation – without premium pricing

Intelligent monitoring capabilities to verify performance

Out-of-the-box code compliance with the plug ‘n’ go configuration

Easy integration with other systems including A/V, motorized shades, and HVAC

Integrates with building automation systems using open standards

Intuitive user interfaces and convenient remote management options

Capable of smart grid integration with enterprise-grade IT security

WattStopper’s digital lighting and sensor systems serve to optimize energy use in commercial and residential spaces.

The average workspace consumes over 1,500 kW of energy every year, costing $175 and accounting for 15 to 20 percent of commercial and residential plug-loads. Wattstopper power strip contains an occupancy sensor to curb phantom loads.

WattStopper daylight sensors and dimmers can reduce lighting costs by

over 80 percent.

Source: WattStopper, 2013


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IBIS Centralized Building Management Interface

Dynamic and optimized control of building functions

The Intelligent Building Information System (IBIS) was developed by Integrated Building Solutions, Inc. for the provision of fully integrated, real-time monitoring of the built environment. Measurement, verification, management, analysis, and reporting are supported by IBIS’s Web-enabled capabilities. IBIS is hardware and protocol independent and seeks to provide actionable data on control utility, power, mechanical, renewable, controls, and equipment in an intuitive, easily-accessed graphical interface. SmartFloor is a module within the IBIS suite of solutions and provides comprehensive monitoring and control of a tightly coupled occupancy to HVAC, lighting, and plug loads. Smart Floor automatically optimizes light dimming, plug loads, and the setback of VAVs to maximize cost and environmental savings. SmartFloor can be deployed over a single floor, a larger area, or an entire building.

IBS selected WattStopper to provide DLM for its rich feature portfolio and demonstrated performance and reliability.

Fu

lly D

evelo

ped B

AC

net S

upport

Esta

blis

hed R

eputa

tio

n

Relia

ble

Pro

duct T

echnic

al S

upport

Occupancy S

ensorin

g Inte

gra

tio

n S

upport

Real-

tim

e E

nerg

y M

easure

me

nts

Daylig

ht H

arv

estin

g

Inte

gra

ted C

om

ma

ndabili

ty O

ptio

ns

Dim

min

g S

upport

Balla

st-

level O

ccupancy S

ensin

g

Cost

WattStopper DLM X X X X X X X X X

Lighting System #2 X X X X X X

Lighting System #3 X X X X X X X

Intelligent Building Interface System (IBIS) is a comprehensive suite of control software designed to provide real-time energy monitoring solutions in an easy to understand graphical format. The IBIS solution was implemented in the Adobe project to provide comparison between upgraded, 12

th Smart

Floor, and standard 10th

floor. Identified 55% reduction in energy consumption on the 12

th floor

Total electrical savings were 241,000 kWh Total gas savings were 3,100 therms Utility rebates totaled $20,448 5 LEED measurement and verification points 1 LEED innovation and design point

Source: IBS, Inc., 2013


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Design Build Approach

Adobe Management partnered with IBS as the master systems integrator to avoid the issues common to third-party integrators who might not understand the objectives, vision, or technologies involved in the project. They chose WattStopper’s intelligent distributed control technology platform for integration of energy management technologies. This integrated approach was first deployed at Adobe’s headquarters in San Jose, covering over 1 million square feet in office and data center space, utilizing the full suite of IBIS modules and providing the professional services to support LEED measurement and verification, energy optimization, benchmarking, and actionable information-based decision making on a scalable level that could be expanded across the enterprise if desired. To enable implementation and subsequent scalability, including the ability to monitor energy consumption at the occupant level, the following steps were followed:

Benchmarked the 12th floor against the West Tower 10th floor to prove a 60 percent savings associated with the design and technologies selected for the project.

IBS created an energy model of the building/floors to better understand the expected energy performance of the new design and to act as an input to the IBIS software which was used for the LEED measurement and verification process.

WattStopper, IBS, and Sunbelt Controls collaborated to design the lighting and HVAC zones, respectively, which made up the neighborhoods of the SmartFloor, supporting the planned control strategies.

The staff of all participating consultants jointly collaborated to fine-tune the integrated sequence of operations and the lighting system occupancy sensor sensitivity.

IBIS SmartFloor was implemented and energy and LEED points were trended, baselined, and stored in a database for real-time analysis, alerting, and historical reporting analysis.

IBS’s experience and reputation earned them the position of master systems integrator, helping in the organization of gathered data into an intuitive graphical interface that supported all major open protocols.

Similar considerations were instrumental in selecting WattStopper as their lighting solution, which was considered the best fit from a reliability, feature, and integration standpoint.

Analysis of the floors’ baseline energy consumption, modeled energy performance, and actual results produced by IBS and verified by the utility provider and LEED commissioning agent showed that the SmartFloor was using 55 percent less energy than the standard Adobe office floor.

W12 served as a pilot project for a new workplace standard that has since been ubiquitously installed and is being rolled out across Adobe’s office spaces around the globe.

Project Cost

$93,086

Energy Reduction

1,147.22 MMBTU/yr

Simple Payback

2.56 years

• Total rebates

worth $20,448

• 1,183 kW per person • Annual energy

savings worth $33,285

• Two years with

rebates

Source: WattStopper and IBS, Inc.


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Process Improvements

Automated energy alerts trigger work orders for facility

engineers through IBIS integration to the CMMS

Automated energy reports including floor- and neighborhood-level benchmarking and analysis

Supports decision making based on energy information

Interoperability between HVAC and lighting and plug load control systems supports automated energy conservation

Lighting is turned off by default and requires occupants to physically turn on lights in addition to occupancy-driven lighting strategies

Floor-level granularity added to the current portfolio-level energy monitoring solution used at Adobe

Best value by integrating existing HVAC infrastructure

Cost Aversions

Increased occupant density of the floor with improved tenant comfort and productivity

Energy conservation is now automated and sustained through occupancy-driven HVAC, lighting and plug-load strategies, and sub metering utilizing a common measurement and reporting platform; thus, saving on manual intervention, analysis, and spreadsheets

Continuous commissioning module provides the end-user with an easy way to identify whether the floor is performing efficiently and supports sustainability by alerting team members when anomalies or deficiencies in energy consumption are observed. This has helped decrease the frequency at which the floors need to be commissioned and extended the life of the systems

Fifty-five percent reduction in energy consumption compared to standard Adobe office floors Annual energy savings of 241,000 kWh/yr Annual gas savings of 3,100 therms/yr Total energy savings of over $33,285 Utility company rebates of $16,500


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Virginia Tech Operations Control Center Siemens Industry, Inc.

Leveraging Life Cycle Strategies to Improve Campus Control

Source: Virginia Tech

Project Address: Virginia Tech Blacksburg, VA 24061

Key Highlights: Development of an operations control center:

Centralize the coordination and

management of the campus HVAC

infrastructure

Improve operations efficiency and

responsiveness

Effectively manage BAS data to improve

decision making


Siemens Industry, Inc.

Trane

Toshiba

WonderWare

Client: Virginia Tech


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This case study has been provided in arrangements with Siemens Industry, Inc. and Virginia Tech. Project Overview Virginia Tech is a comprehensive university and leading research institution with eight colleges and a graduate school. The campus buildings date back to the university’s founding in 1872. Integrating the campus’ HVAC systems under one centralized control center was necessary for operational cost and environmental concerns. Implementing the operations control center (OCC) allowed Virginia Tech to leverage its previous investments in building automation system technology to integrate a multitude of physical data points into a centralized command and control facility. As a result of campus-wide technology standards that had been implemented over several decades, the infrastructure already existed to create the OCC with minimal capital investment, validating the life cycle value of campus infrastructure and integration standards. Facility Details Located on 2,600 acres in Blacksburg, Virginia with 125 buildings on its main campus, Virginia Tech takes a hands-on, engaging approach to education, preparing scholars to be leaders in their fields and communities. As the commonwealth’s most comprehensive university and its leading research institution, Virginia Tech offers 215 undergraduate and graduate degree programs to more than 30,000 students and manages a research portfolio of more than $450 million. The university fulfills its land-grant mission of transforming knowledge to practice through technological leadership and by fueling economic growth and job creation locally, regionally, and across Virginia. Through a combination of its three missions of learning, discovery, and engagement, Virginia Tech continually strives to accomplish the charge of its motto Ut Prosim (That I May Serve).

Virginia Tech Operations Control Center - Project Arranged by Siemens Industry, Inc.

Virginia Tech’s objective was to unify the campus-wide HVAC systems under one centralized control center.

Project Partners

Siemens Industry, Inc APOGEE Building Automation, Campus Network, Integration Drivers Trane Chiller Plant and Trane Tracer Controllers Toshiba Boiler Plant PLC Controllers WonderWare SCADA Software

With a special thanks to Mark Helms, Director Facilities Operations, Virginia Tech

Source: Virginia Tech


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Facility Details

Total area 125 buildings distributed over 2,600 acres

Year of construction 1872, with buildings dating back to that time period

Student population 30,000

Technical Improvements:

Dedicated Siemens APOGEE Insight BAS network

Standard communication protocol across hardwired trunks, dedicated Ethernet, and wireless networks

Over 350 DDC field panels and several thousand application-specific controllers

BACnet integration through the Trane Tracer network to the Chiller Plant

Modbus integration through the Toshiba PLC network to coal-fired steam power plant

Modbus integration through the WonderWare software to the power distribution SCADA system

Demand response utility consumption reduction program

Steam-driven 3 MW power generating turbine and 100kW solar array

Systems Integration Overview

Source: Virginia Tech, Siemens Industry, Inc., 2013

Siemens APOGEE system allows for the integration of thousands of data collection points to be unified onto one, normalized platform.

Efficiencies are gained through the utilization of existing infrastructure systems, reducing overall cost.

Source: Siemens Industry, Inc., 2013


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Systems Integration Overview A fundamental aspect that characterizes this project is the development of campus-wide standards with a view of their impact on the facility infrastructure. Simple, yet far-reaching steps that Virginia Tech followed to begin developing a LCC approach to their facility include the following:

Implementing standards

Selecting strategic partners

Balancing first cost with life cycle cost

Using technology to work smarter

Using integration to improve decision making

Following a competitive selection process, Virginia Tech ultimately opted to work with Siemens to implement their integration strategy. Having Siemens’ systems already deployed on the campus, and past experience working with Siemens made it an easy decision.

Project Life Cycle Management Strategy

Develop Standards

Select Partners

Balance First Cost and Life

Cycle

Integrate and Share

Data

Leverage Technology

Source: Siemens Industry, Inc., 2013


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Campus Standards are Key Principle to LCC Model A fundamental principle that underlies this project is the development of campus-wide standards that have been put in place for all projects that have an impact on the facility infrastructure. These standards, implemented through the specifications for new construction and remodeling projects, are then maintained throughout the life cycle of the facility through operations and maintenance. These standards form the foundation for the LCC approach to providing an end-to-end life cycle impact from building design and construction on through the operations and maintenance requirements of servicing the building and its integrated systems. “So life cycle costs have become a huge issue here and it’s got to be a partnership between facilities, maintenance, and the capital folks. Historically we’ve been pretty good compared to any other university. We’re actually reviewing our design standards now and that fosters a good working relationship.”

Mark Helms, Director Facilities Operations, Virginia Tech Working Smarter, But Not As Hard A less technical example provides some insight into the standardization approach on the Virginia Tech campus. Virginia Tech was founded as a land-grant college, and appropriately, its distinctive buildings have been constructed from the product of Southwest Virginia geology. Originally called “our native stone,” the rock has become known more familiarly, and more affectionately, as Hokie Stone. Since the mid-1950s, the university has operated its own quarry on the fringes of Blacksburg, and the popular limestone appears on most of the university’s buildings. The standardization of this construction material has brought warmth and continuity to the campus, embodied in the wide range of buildings built over the past century. It has also brought the opportunity to better manage the overall process within the quarry. “The quarry is the best example I’ve got of what we have been able to accomplish with technology. There were 50 tons of stone per week produced for our buildings. There were 42 people and a lot of equipment down there working very hard. Today there are 11 people producing about 55–60 tons per week, and they aren’t working nearly as hard. They’re working much smarter, but not as hard. So it’s time to bring that old rock technology up here.”

Mark Helms, Director Facilities Operations, Virginia Tech Selecting Strategic Partners In the process of balancing first costs versus life cycle costs decisions, large campuses require reliable and proven technology, full-featured functionality, flexibility, scalability, and the support to back it up. Implementing a vendor standard in the installation specification ensures that the long-term interests of the campus are protected years beyond when the equipment warranty expires. “I think where we evolved has really been as much service-driven as it’s been product-driven. The service drives it, to me, more than a piece of equipment does. Lots of people make equipment, but if it breaks, who’s going to show up and help me fix it?”

Mark Helms, Director Facilities Operations, Virginia Tech


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Integration and Decision Making With the massive amounts of data generated daily by the multitude of physical points across the 2,600 acre campus, the integration model that was designed by the campus and their vendors was a critical factor in being able to implement the OCC model, providing a single seat for monitoring and control. The campus realized the challenge in managing complex facilities, capturing all of the data in a structured method that allowed operations and maintenance to turn the data into meaningful information that can help them make decisions. “We’ve got all these hundreds of thousands of points across campus. How many are we using? How many of them really mean something? So we got all of the data into one spot so we can control it and we can really talk about what kind of energy I saved in the North Plant because we operated it one way last year and now we’re doing it this way? So those are the kinds of discussions we started having.”

Mark Helms, Director Facilities Operations, Virginia Tech Balancing First Cost with Life Cycle Cost

ASHRAE studies have shown that over the life of a building, the greatest percentage of costs is realized in the category of operational costs. Historically, Virginia Tech has made decisions by balancing first cost versus life cycle cost. With buildings that date back to the late 1800s, the university recognizes the importance of making smart decisions today that will have a positive impact in the future. “But that’s the objective here. Maybe they don’t see today what we’re doing, but if we’ve done the right things with master planning and chilled water and those sorts of things – nothing would be better than 25 years from now somebody would say, “Wow, those guys were really thinking.””

Mark Helms, Director Facilities Operations, Virginia Tech

The Need for Building Efficiency Systems

Improperly controlled or degrading equipment can account for a

significant percentage of energy used in commercial buildings.

Centralized control and real-time monitoring, such as the one

Siemens installed, with appropriate efficiency diagnostics will help

Virginia Tech identify and address problems before they become

critical. Through proper equipment tuning and preventative

maintenance, costly and uncomfortable critical failures can be

completely avoided, as well as increasing efficiencies across the

board. All of this is expected to be achieved through Siemens’

solution. The use of equipment is also expected to be extended as

issues can be identified and corrected before they become

serious.

As a fraction of total life cycle costs, operational cost is the majority. The lower energy usage fulfills greening initiatives.


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Microsoft Corporation’s 15 Million Square Foot Campus

Redmond, Washington

Source: Microsoft Corporation

Project Address: Virginia Tech Blacksburg, VA, 24061

Key Highlights:

Intelligent building system overlay

Automate RCx program

Optimize campus portfolio (35,000 assets)

Improve labor efficiencies

Automated building performance reporting


Iconics

CB Richard Ellis

Smart Buildings, LLC

DB Engineering

Client: Microsoft Corporation

Microsoft Energy-Smart Buildings One Microsoft Way Redmond, WA 98052

https://www.refcoe.com/programs/wpa/resources/photobank/PhotoBank/Building 99/B99_Exterior_Entry2.jpg


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Brief Description of the Property Microsoft’s headquarter campus in Redmond, Washington was constructed over a period of 30 years. The facility is comprised of 125 buildings and 35,000 maintained assets. There are several LEED Silver- and Gold-certified buildings across the portfolio. The campus is fed from seven different substations, has a 100 megawatt peak load, and has a $55 million annual energy spend. The campus has 42 full-service cafes and a robust transportation system. Property Type Mixed use office and lab buildings Size Details Existing Buildings

14,900,000 sq.ft.

125 buildings

145 structures

Description of Project Showcase

Across all the building assets, Microsoft collects 500,000,000 data transactions every 24 hours and lacked the ability to leverage this “Big Data.” In 2011, after a 12-month pilot across 2.6 million square feet, a vendor was selected to deploy the solution across the entire campus.

Exact Technical Requirements:

Install software overlay across multiple disparate building

systems

Create dashboard and metrics for real-time energy

management and to visualize the consumption based on

key load drivers (base, plug, and lab)

Create a library of fault rules that can be eliminated across the campus through the software overlay

Complement the existing building systems Convert different protocols to BACnet/IP

Project Partners Iconics CB Richard Ellis Smart Buildings, LLC DB Engineering

The project showcases the ability to use existing data streaming from the building’s systems to reduce energy consumption, optimize the building assets, and improve labor efficiency at scale. This project did not require any hardware investments throughout the buildings, and is providing capabilities that had not existed before at this scale.


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Smart Campus Approach

The problem statement was that Microsoft had a “Big Data” problem to solve within their campus. The guiding principles were anchored on reducing energy consumption (thus reducing costs and carbon emissions), optimizing more than 35,000 building assets, and improving labor efficiencies. After extensive research with technology partners, universities, and national labs, Microsoft created the initial requirements that were the anchor of the project. The key steps were as follows:

Microsoft’s initial 195 requirements consisted of capabilities they wanted from the solution and provided test cases to validate that the solution met these requirements.

Working along with Smart Buildings, LLC, a gap analysis of the building systems and network architecture was completed. This verified that no investments were required (e.g., hardware) to meet their objective and make the campus “Smart Building” ready.

The next step was creating the request for information (RFI), followed by a request for proposal (RFP), to have a comprehensive understanding of what solutions were on the market and what capabilities existed.

As the RFP concluded, the idea was to pilot not just one vendor’s solution, but three vendors in parallel. This provided insight into the capabilities of each vendor.

Microsoft followed the software development life cycle (SDLC) as the solutions were tested and deployed. Due to security requirements, each solution was required to go through an extensive application security review (ACE).

Once the vendors completed the various security testing processes, the three solutions were deployed across the campus for approximately one year, where each vendor’s capabilities were tested against the requirements.

Some of the observations during the pilot included the following: o Identified that demand peaks were occurring in buildings due to the building and lab

start-ups occurring too closely o Identified that the standard commissioning process was not going deep enough prior

to handover o Proved the value of fault detection diagnosis and the impact it can have to “cast a

net” across the entire campus to identify assets that were either not working as designed or find where set-points had been made that were not within Microsoft’s standard setting. In each case, there was visible energy waste.

o Identified when a building was not economizing when it should be o Had visibility into how the building was running as a “system.” For example, when the

terminal units stuck dampers, which, in turn, was degrading the AHU strategy. o Identified when building schedules were operating outside of the normal hours due to

an error or issue with the building system

Microsoft has witnessed tremendous benefits with each vendor. Once the pilot concluded, scorecards were completed for each. There were four scorecards, comprising IT, user, performance, and business aspects, which rated different areas of the project.


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Project Outcome and Benefits

The results of this project are highlighted below: Reduced the cycle of the RCx program from once every five

years for every building to an automated and continuous RCx program

Efficiency Gains and Optimization

Contributed to 18,375 MWh of energy savings($1.5 million in FY13)

Obtained rebates from the local utility for the software and deployment

Unlike a retrofit, the software overlay is seamless to the building occupants and amounts to a fraction of the cost.

Focused the maintenance team on areas that matter the most (uptime for business critical space and areas of the highest energy reduction)

The software is a core element of the handover process Automated core-business reporting Achieved extended life of the assets No hardware was required to be installed within the building. Identified additional energy conservation measures due to

the analytics capability that did not exist before

18-month ROI Reduce addressable energy by 15 to 20 percent Contributed to 18,375 MWh of energy savings ($1.5 million in FY13)


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5.2 Evaluation of Project Cases and Success Factors The project case studies highlighted here clearly point toward changes to conventionally adopted processes that have been responsible for keeping them close to the original vision and project goal. Not only have they met the required stipulations of the building owner/operator, but have significantly exceeded project performance by ensuring the process flow adopted was best suited to deliver these requirements. Some of the key highlights and lessons learned from these projects can be found below: Integrated approach and communication flow: In all four projects, perhaps the most important factor leading to their success was following an integrated approach from the beginning. Despite using the traditional approach of working under competitive situations, efforts were made at the very start to integrate project partners by the building owners and asset managers. The project vision is consulted and deliberated upon by the owner, consultant, the technology vendor, and contractors to ensure all parties agree and understand the approach to delivery. This factor is instrumental in building trust and supporting partnerships amongst various participants, making them work towards a common goal, as opposed to merely delivering a task in the overall scheme. Establishing performance specifications via appropriate pre-project modeling: This was an underlying aspect of each of the projects highlighted. Not only were product or technology specifications required to be met, but also a set performance criteria supported by proper pre-project modeling. The significance of this factor is twofold. First, it provides clear understanding to the consultants as to what should be specified and the exact details to be included. Second, it establishes that the building owner is willing to assume utmost control and authority over what is procured to meet those exact requirements. It also provides purpose as to what the building owner is trying to achieve and ensures that the original project scope does not deviate further down the road. Not settling for less: Despite the overwhelming claim on first costs being the frequent damper, it is clear that building owners do not always cite this drawback, particularly when vendors and procurement partners have worked well to justify value. Performance and quantifiable savings are clear drivers for most building owners. However, the challenge lies in the inability to comprehend the real value in investing in the right service or solution. In these projects, consultants and vendors worked relentlessly to demonstrate value as per the exact needs. In addition, adequate access to vendors and continued service support were important in helping building owners to set aside first cost issues and opt for the right solutions. These projects illustrate that some building owners do wish to take proactive steps in creating and maintaining their buildings as intelligent entities. It is important for them to ensure that their money is well spent in enhancing asset value over time. They have a desire to work closely with partners and vendors in executing their project vision. However, it is contingent on partners to customize their approach and delivery to suit that purpose.


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5.3 Standardization Initiatives As part of this research, various standardization initiatives were evaluated with industry participants that could be adopted for streamlining project engagement processes. Frost & Sullivan’s discussions with various participants in the industry as part of this project indicate that these initiatives should be undertaken at the building owner level, as well as on an industry-wide level. The need for these discussions has also been corroborated by the project cases evaluated as part of industry best practices. Some of these initiatives are discussed below: Performance and ROI Modeling: A Standard Prerequisite The effort to institute energy and performance modeling as a prerequisite is heavily reliant on building owners adopting it as an integral part of their projects. There are various tools5 presently available to the industry, endorsed by prominent organizations such as the Department of Energy, ASHRAE, and the National Institute of Building Sciences, that offer simple assessment of building energy performance and optimization potential. These tools offer valuable clues to the building owner and their consultants in deciding what technologies to adopt and how to ensure that they are duly implemented in their buildings. With visibility into the various energy-saving and operational cost-saving scenarios, building owners can justify their investment and keep them more involved and in charge of their projects. Primary and secondary research findings from this project indicate that standardization efforts in this area will require reconciliation of methodologies in various modeling tools and an assurance that they all incorporate the right strategies to reflect savings potential consistently and holistically. Trade Certifications As highlighted previously in this report, there is a lack of trade certifications that support the role and service profile of various value chain partners in the intelligent buildings industry. This initiative needs to be undertaken at an industry level, with various organizations determining the need for certification and ultimately creating a framework for certification courses. The objective is for various trade professionals to be officially recognized for the services they can offer to the industry. This will also present the scope for incorporating LCC modules into such certification programs. For example, there is no recognized course or certification for SIs or technology integrators in the industry. To standardize industry certifications and make them effective, this would require OEMs to take a stand on open and interoperable technologies and to ensure that they move away from proprietary locked-in solutions.


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Streamlining Credits and Incentives Given that rating tools in the industry are heavily focused on operational performance of buildings, it is necessary to highlight the inherently strong competencies of such tools and enhance their framework to support the adoption of intelligent solutions. It would be in the interest of intelligent building projects if credit systems adequately endorse the contribution of intelligent technologies. Furthermore, the initiatives that can help in earning a credit or an incentive are merely encouraged, not prescribed. Some amount of prescriptive characteristics is necessary for better evaluations. While incentivizing LCC use is a consideration for the intelligent buildings industry, there already exists a significant opportunity for projects utilizing LCC criteria to address issues related to green buildings, as well as benefit from already available green incentives. As pointed out earlier, data analyzed in an LCC model with regards to incorporation of green and intelligent technologies can directly help building owners and asset managers to avail of credits in green rating tools and certifications. So while incentivizing the use of LCC itself may not be required, it may benefit the industry to consider restructuring of credits for adequate representation of intelligence in all rating tools. Merely designing to meet a green standard cannot ensure that savings or intelligence is maintained over time. The critical question for the intelligent buildings industry participants to consider is whether or not building owners are putting in the right technologies in the first place that are justified by LCC. Frost & Sullivan’s research from this project indicates that, other than in a handful of cases, such as those shown in the case studies included in this report, the majority are not. As long as industry participants continue to design with short-term gains in mind, incentivizing LCC in rating tools may serve no purpose at all. However, as a solution, credits in these tools could be revamped to take technology integration into their evaluation criteria adequately, so that long-term benefits of such technology is accorded due importance. This could indirectly help support LCC adoption.


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6 Conclusions and Recommendations 6.1 Key Conclusions - Identification of Market Potential for LCC The key conclusions are based on the research conducted by Frost & Sullivan for this project. The recommendations were developed based on how these conclusions are expected to influence the intelligent building industry with respect to LCC adoption. The key conclusions1 of the project are:

Initiatives adopted by institutional bodies and technical organizations over the last

two decades have brought the concept of LCC to the forefront of pre-project

evaluations in many industries, including intelligent buildings and construction.

Despite gaining early focus, research from this project indicates that LCC has

remained largely confined to project evaluations within the federal sector, with very

limited frequency of use witnessed in other vertical segments. This is attributed to a

variety of factors, including inconsistent methodologies, lack of valid data,

irreconcilable values, and above all, apathy of building owners, vendors, and service

providers to voluntarily incorporate LCC into the early phases of a project.

Nevertheless, in the need to logically approve capital investments and to validate

ROI and equity, cost-assessment tools have become a necessary part of the project

flow even though a full-fledged LCC approach may not be pursued.

LCC is often substituted by simple payback analysis and other capital cost

justification methods to meet the same objective. They offer the minimum required

incentive to bridge the gap between having to accommodate untendered costs as

opposed to allowing parametrically justified investment.

Intelligent buildings essentially fall within two major categories—partially integrated

and fully integrated2. The true value of effective O&M, progressive asset

management, and cost savings via predictive energy management are only

achievable with a fully integrated approach. This, in turn, is reliant on the building

industry’s motivation to adopt open standards and integrated systems, selected on

the basis of their ability to offer lowest life cycle costs.

Primary research conducted among industry stakeholders for this project shows that

the intelligent buildings industry participants are showing gradual signs of moving


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away from putting undue emphasis on initial costs and simple payback and slowly

moving towards a more holistic approach where recurring costs, incentives, and life

cycle assessments are taken into consideration.

A major drawback in presently used LCC methods is that these are characterized by

the absence of a consistent methodology for deriving LCC3. More hindering than this

issue is that a majority of these tools and calculation techniques cannot be easily

comprehended by building owners and their operations staff.

A fragmented delivery chain4 and transactional interactions among value chain

partners further act as restraining factors in LCC adoption.

It is encouraging to witness a growing breed of building owners and asset managers

that emphasize superimposing cost-benefit analysis over an extended project life

span, whereby better visibility into recurring costs and incentives can be obtained.

Among prevalent LCC tools, the NIST-BLCC tool is by far the most widely accepted

and forms the basis of various customized LCC techniques.

Frost & Sullivan’s consulting team is of the opinion that there is a greater need for

consultants, owners, vendors, and service providers to collaborate and create a

market approach to promote inclusive decision making so that integrated design and

delivery approaches are supported.

The immediate need for industry participants is to organize initiatives to work

together and create structural frameworks for joint collaboration in technology

deployment as well as propagating LCC adoption.

6.2 Recommendations The following recommendations were developed based on Frost & Sullivan’s evaluation of the key conclusions of this project. Among all major issues analyzed, those outlined here are critical in determining the success of industry participants in promoting LCC adoption in the intelligent buildings industry. Collaborative Partnerships To respond to opportunities promptly, it is inevitable that most participants will have to form alliances to promote the need for LCC use, as well as to bundle solutions and position themselves competitively. Building owners’ need evaluations are expected to be significant in determining the acceptability of various intelligent solutions offered and the need to undertake projects via lowest LCC analysis. In addition to the above, lobbying efforts to bring disjointed industry segments together and, most importantly, to have some collaboration at the level of industry associations is important for the intelligent buildings industry to witness desired levels of LCC adoption.


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Education and Training In order of priority, this recommendation closely follows the previous recommendation on partnerships. Clearly, the lack of knowledge of LCC is a significant technical restraint that needs to be overcome through industry-led efforts in education and training. These efforts should be targeted at making LCC easier to follow, bringing about consistency in analysis tools and making sure that LCC is as frequently used by stakeholders as other financial metrics in justifying project investments. Driving the incorporation of LCC modules into standard industry training and certification programs will help promote knowledge of LCC techniques among value chain partners. Exhibit 6.1 outlines the key focus areas for industry participants, identified from the research conducted during the course of this project by Frost & Sullivan. Exhibit 6.1: Recommendations and Identified Focus Areas

Incentives There is a distinct need for industry participants to engage with certain stakeholders, such as contractors and integrators, to ensure they are at least able to further communicate the benefits of technology integration and an integrated design process for returns. Suppliers and consultants would need to consider some financial incentives to ensure that they comply with the original project vision and not change things midway in favor of low cost. Such incentives could be comprised of barter arrangements or financial payouts, as well as others directly available through credit systems.

Incentives Others

• Promote collaborative design approaches

• Cultivate value chain partnerships

• Work towards collaborative technology developement

• Develop best practices

• Consolidate lobbying efforts

• Standardize requirements for data and technology parameters in LCC

• Drive the incorporation of LCC modules into certification courses

• Work towards creating training workshops to involve all stakeholders and acquaint them with LCC processes

• Coordinate with value chain partners to make barter arrangements

• Consider financial incentives

• Work with standard/protocol creation bodies and credit rating tools

• Facilitate bundled options for competitive advantages

• Demonstrate energy use reductions and other environmental metrics

• Bridge internal communication disconnects

• Promote open solutions

Collaborative Partnerships Education and Training



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Other Areas of Focus Other areas of focus for industry participants include creating better communication flow within their own organizations to make value propositions more consistent, moving away from proprietary strongholds and promoting open solutions, demonstrating performance analysis, and exploring collaborations for bundled options among fellow stakeholders.


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Appendix - List of References

Chapter 1 1. Detailed in the proposal to the IIBC-CABA, dated May 2, 2013

2. Primary research sample for the project titled Life Cycle Costing of Intelligent Buildings;

Sample size N=85. Sample constituents – building technology vendors; LCC tool

developers; public bodies and think tanks; engineering consultants; design building firms;

architects; system integrators; contractors; building owners and asset managers. Partial list

of participants included in Frost & Sullivan’s proposal dated May 2, 2013.

3. Customer Research Survey – NCD3-19; Insights from North American Facility Decision

Makers, Frost & Sullivan, 2013; www.frost.com

4. Definition of Intelligent Buildings – Convergence of Green and Intelligent Buildings-CABA

Landmark Research 2008; Intelligent Buildings Roadmap 2011-CABA Landmark Research

2010; www.caba.org

5. National Institute of Standards and Technology (NIST);NISTIR 85-3273-27; BLCC

Handbook and Addendum; www.nist.gov/blcc; IEEE – www.ieee.org;

http://www1.eere.energy.gov/femp/information/download_blcc.html

6. Life cycle costing calculation models for buildings, Lulea University of Technology, Lulea,

Sweden; http://www.inpro-project.eu/media/lcc

7. NIST- www.nist.gov/blcc

8. Summarized findings from the primary and secondary research undertaken for project Life

Cycle Costing of Intelligent Buildings, presented across Chapters 2-6; CABA Landmark

Research 2013 by Frost & Sullivan

9. Primary interviews with various utilities in United States and Canada, public bodies such as

NIST, IEEE, and private organizations within the building technology vendor community

10. CABA Landmark Research 2010 – Intelligent Buildings Roadmap 2011 by Frost & Sullivan;

Life Cycle Costing of Automation Controls for Intelligent and Integrated Facilities, IIBC Task

Force White Paper, 2004; www.caba.org/research library

11. Primary research interview findings, Life Cycle Costing of Intelligent Buildings, CABA

Landmark Research 2013

Chapter 2 1. Summarized findings from the primary and secondary research undertaken for project Life



2. Rocky Mountain Institute – www.rmi.org/modellingtools

3. Harvard University Office of Sustainability, Green Building Resources;

http://www.green.harvard.edu/theresource/new-construction/life-cycle-costing

4. Athena Institute - http://www.athenasmi.org/resources/about-lca/

5. Various state and province-led LCC initiatives, the U.S. and Canada – U.S. Dept. of

Transportation http://www.fhwa.dot.gov/asset; California Title 24 –

www.energy.ca.gov/title24; BC Climate Action Toolkit - http://www.toolkit.bc.ca/resource/life-

cycle-cost-analysis; Whole Life Cycle Cost Analysis developed by Northwestern University

2008, State of Illinois, http://iti.northwestern.edu/publications/utc/tea-21; Ontario Ministry of

http://www.frost.com/

http://www.caba.org/

http://www.nist.gov/blcc

http://www.ieee.org/

http://www1.eere.energy.gov/femp/information/download_blcc.html

http://www.inpro-project.eu/media/lcc


http://www.caba.org/research%20library

http://www.rmi.org/modellingtools


http://www.athenasmi.org/resources/about-lca/

http://www.fhwa.dot.gov/asset

http://www.energy.ca.gov/title24

http://www.toolkit.bc.ca/resource/life-cycle-cost-analysis

http://www.toolkit.bc.ca/resource/life-cycle-cost-analysis

http://iti.northwestern.edu/publications/utc/tea-21


80

Infrastructure Life Cycle Costing Methods

http://www.moi.gov.on.ca/en/infrastructure/building


www.caba.org/research library




8. CABA Landmark Research 2008–Convergence of Green and Intelligent Buildings by Frost &

Sullivan; Life Cycle Costing of Automation Controls for Intelligent and Integrated Facilities,

IIBC Task Force White Paper, 2004; www.caba.org/research library

9. Interpreted in the exhibit and accompanied write-up by Frost & Sullivan based on theoretical

data referenced from NIST-www.nist.gov/blcc


http://www.green.harvard.edu/theresource/new-construction/life-cycle-costing; Life cycle

costing calculation models for buildings, Lulea University of Technology, Lulea, Sweden;


11. Indigenously developed by estimators, architects, project consultants upon building owners’

directive. Mostly customized from established tools such as NIST-BLCC

12. NIST-www.nist.gov/blcc, BOMA historical building data and O&M benchmarking data-

www.boma.org; National Institute of Building Sciences Whole Building Design Guide -

http://www.wbdg.org/resources/lcca; Federal Energy Management Programs of Department

of Energy (DOE/FEMP) - https://www1.eere.energy.gov/femp; RSMeans Life Cycle Costing

for Facilities – www.rsmeans.reedconstructiondata.com

13. Life cycle cost analysis – calculation of energy performance metrics, California Title 24 –

www.energy.ca.gov/title24

14. Frost & Sullivan and CABA Collaborative Research Reports - Convergence of Green and

Intelligent Buildings-CABA Landmark Research, 2008; Intelligent Buildings Roadmap 2011-

CABA Landmark Research, 2010; www.caba.org/researchlibrary



16. Primary interview with DoD spokespersons as part of the project Life Cycle Costing of

Intelligent Buildings, Frost & Sullivan, 2013.

17. Primary interview with technology partners for TIAA-CREF as part of the project Life Cycle

Costing of Intelligent Buildings, Frost & Sullivan, 2013; www.tiaa-cref.org

18. Case studies included in Frost & Sullivan and CABA Collaborative Research Reports -

Convergence of Green and Intelligent Buildings-CABA Landmark Research, 2008;

Intelligent Buildings Roadmap 2011-CABA Landmark Research, 2010;

www.caba.org/researchlibrary

19. See reference note 18 listed under references for Chapter 2

20. 655,000-sq.ft. Office tower, 750 Seventh Avenue Manhattan, New York, U.S.A. – data

obtained through discussions with Consolidated Edison Co of New York, Inc.;

21. Van Andel Institute of Research Cancer Center, 240,000 square feet spread over an eight-

story building – data obtained through discussions with WattStopper;

http://www.moi.gov.on.ca/en/infrastructure/building








http://www.boma.org/

http://www.wbdg.org/resources/lcca

https://www1.eere.energy.gov/femp

http://www.rsmeans.reedconstructiondata.com/

http://www.energy.ca.gov/title24

http://www.caba.org/researchlibrary


http://www.tiaa-cref.org/



81

22. Bell Trinity Square, 1,073,600 sq. ft. of gross floor area, Toronto, Canada – data obtained

through discussions with Northam Realty Trust;

23. King Abdul Aziz Endowment, Saudi Arabia – data obtained through discussions with BT

Applied Technology (BTAT) and CommScope IBIS;

24. Rogers Centre, One Blue Jays Way, Toronto – data obtained through discussions with

Encelium Technologies, Inc.

25. Primary interviews with industry participants and case study arrangers as part of the project

Life Cycle Costing of Intelligent Buildings, Frost & Sullivan, 2013.

26. Frost & Sullivan and CABA Collaborative Research Reports – Intelligent Buildings and the

Bid Spec Process, 2012; www.caba.org/researchlibrary

27. Review of major LCC tools currently in use for the project Life Cycle Costing of Intelligent

Buildings, Frost & Sullivan, 2013, such as NIST-BLCC – www.nist.gov; RMI -

www.rmi.org/modellingtools; Harvard University -

http://www.green.harvard.edu/theresource/new-construction/life-cycle-costing; Athena

Institute - http://www.athenasmi.org/resources/about-lca/

28. DOE-LBNL LCC tool development, 2008-9– www.doe-2.org; www.lbl.gov/facilitieslab

29. eQUEST by Energy Design Resources funded by California Public Utilities Commission,

http://energydesignresources.com/resources/software-tools/equest.aspx

30. Athena Eco Calculator – www.athenasmi.org

31. See reference note 5 listed under references for Chapter 2

32. Reed Construction Data – www.reedconstructiondata/smartBIM

33. Autodesk and FM Systems – www.autodesk.com/building-information-modeling;

www.kalblue.com; www.imaginit.com; www.sap.com/ec&o

34. Primary research interviews with NIST spokespersons as part of the project Life Cycle

Costing of Intelligent Buildings, Frost & Sullivan, 2013, additional secondary research –

www.nist.gov/el/CIB-BIM-Adoption

35. http://www.caba.org/online-forums/biq

Chapter 3 1. Customer Research Survey – NCD3-19; Insights from North American Facility Decision

Makers, Frost & Sullivan, 2013; www.frost.com; Sample size – N=150


Makers, Frost & Sullivan, 2013; www.frost.com; Q. What type of facility do you manage?


Makers, Frost & Sullivan, 2013; www.frost.com; Q. Familiarity with intelligent building

solutions – very familiar; familiar; unfamiliar


Makers, Frost & Sullivan, 2013; www.frost.com; Analysis – Impact of Familiarity on Usage


Makers, Frost & Sullivan, 2013; www.frost.com; Q. Future Adoption Potential – Adopt within

the next 2 years; Adopt within the next 3-5 years; Non-adopters


Makers, Frost & Sullivan, 2013; www.frost.com; Q. What factors drive technology selection?


http://www.nist.gov/




http://www.doe-2.org/

http://www.lbl.gov/facilitieslab

http://energydesignresources.com/resources/software-tools/equest.aspx

http://www.athenasmi.org/

http://www.reedconstructiondata/smartBIM

http://www.autodesk.com/building-information-modeling

http://www.kalblue.com/

http://www.imaginit.com/

http://www.sap.com/ec&o

http://www.nist.gov/el/CIB-BIM-Adoption

http://www.caba.org/online-forums/biq








82


Makers, Frost & Sullivan, 2013; www.frost.com; Q. Have you requested ROI/LCC analysis

from project partners – requested, not requested, neutral


Makers, Frost & Sullivan, 2013; www.frost.com; Q. Have you used any in-house developed

LCC model – used, not used, neutral


Makers, Frost & Sullivan, 2013; www.frost.com; Q. What are the factors challenging LCC

adoption and their rating?

10. Primary interviews conducted as part of the project Life Cycle Costing of Intelligent

Buildings, Frost & Sullivan, 2013; Additional secondary research - Analysis of North

American Integrated Facilities Management Market, ND11-19, Frost & Sullivan, 2013,

www.frost.com


Buildings, Frost & Sullivan, 2013; Additional secondary research - Analysis of Energy

Management Services and Performance Contracting Market, North America, 2011 and

2012, N9F3-19, Frost & Sullivan, www.frost.com


Buildings, Frost & Sullivan, 2013; Additional secondary research – Analysis of HEMS and

BEMS markets in North America and Europe, 2012, M84D-19, Frost & Sullivan,

www.frost.com





14. Case studies reviewed as part of the following projects: Life Cycle Costing of Intelligent

Buildings, CABA and Frost & Sullivan, 2013; Intelligent Buildings Roadmap 2011, CABA and

Frost & Sullivan, 2010; Convergence of Green and Intelligent Buildings, 2008, CABA and

Frost & Sullivan, 2008; www.caba/org/researchlibrary

15. U.S. Green Building Council LEED building rating tool – www.usgbc.org/leed; BOMA Go

green and GoGreen Plus – www.boma.org; Green Building Institute – GreenGlobes rating

tool – www.gbi.org/greenglobes; Architecture 2030 – www.architecture2030.org; Living

Building Challenge - https://ilbi.org/lbc

Chapter 4 1. Ontario Energy Conservation Programs - Studies in Ontario Electricity Policy Series Paper

No. 4 - http://sei.info.yorku.ca/files/2013/03/electricity-conservation-policy-ontario

2. CPUC programs and incentives - http://eega.cpuc.ca.gov/












http://www.caba/org/researchlibrary

http://www.usgbc.org/leed

http://www.boma.org/

http://www.gbi.org/greenglobes

http://www.architecture2030.org/

https://ilbi.org/lbc

http://sei.info.yorku.ca/files/2013/03/electricity-conservation-policy-ontario

http://eega.cpuc.ca.gov/



83


Buildings, Frost & Sullivan, 2013; CABA and Frost & Sullivan collaborative research –

Intelligent Buildings and the Bid Spec Process, 2012, www.caba/org/researchlibrary

Chapter 5 1. Western Kentucky University, Kentucky - Arranged in collaboration with Johnson Controls,

Inc., and Western Kentucky University

2. Adobe Systems Incorporated, West Tower 12 Smart Floor, California - Arranged in

collaboration with WattStopper and IBIS, Inc.

3. Virginia Tech Campus, Blacksburg, Virginia, - Arranged in collaboration with Siemens

Industry, Inc. and Virginia Tech

4. Microsoft Corporation Headquarters, Redmond, Washington, - Arranged in collaboration

with Microsoft Corporation

5. Department of Energy-

http://apps1.eere.energy.gov/buildings/tools_directory/subjects_sub.cfm; ASHRAE -

https://www.ashrae.org/resources--publications/free-resources/free-software; National

Institute of Building Sciences, Whole Building Design Guide-

http://www.wbdg.org/resources/netzeroenergybuildings.php

Chapter 6 1. Summarized findings from the primary and secondary research undertaken for project Life






3. Review of advantages and drawbacks in major LCC tools currently in use for the project Life

Cycle Costing of Intelligent Buildings, Frost & Sullivan, 2013, such as NIST-BLCC –

www.nist.gov; RMI - www.rmi.org/modellingtools; Harvard University -

http://www.green.harvard.edu/theresource/new-construction/life-cycle-costing; Athena

Institute - http://www.athenasmi.org/resources/about-lca/


Buildings, Frost & Sullivan, 2013; CABA and Frost & Sullivan collaborative research –

Intelligent Buildings and the Bid Spec Process, 2012, www.caba/org/researchlibrary

For a complete electronic version of the Life Cycle Costing of Intelligent Buildings and a PowerPoint deck go to: www.caba.org/lccib. For additional CABA landmark research contact: [email protected] or 613.686.1814 x228.


http://apps1.eere.energy.gov/buildings/tools_directory/subjects_sub.cfm

https://www.ashrae.org/resources--publications/free-resources/free-software

http://www.wbdg.org/resources/netzeroenergybuildings.php


http://www.nist.gov/





http://www.caba.org/lccib

mailto:[email protected]

caba and the following caba members funded this...

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