in this issue · 2018. 4. 4. · vice president-certiﬁ cation: tom wiggins, cvs vice...

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SAVE International Board of DirectorsPresident: Craig L. Squires, CVSExecutive Vice President: James D. Bolton, PE, CVS, PVMVice President-Finance & Administration: J. Jeff rey Plant, AVSVice President-Certifi cation: Tom Wiggins, CVSVice President-Global Aff airs: Drew M. Algase, CVS-Life, FSAVEVice-President Education: Don H. Staff ord, PE, CVS-LifeVice President- Membership: Randy Thomas, CVSVice President-Conferences: Richard L. Johnson, PE, DEE, CVSVice President-Communications: John E. Sloggy, CVSImmediate Past President: David C. Wilson, P.Eng., CVS

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©2011 SAVE International

VALUE WORLD

VOL. 34 | NO. 2 | FALL 2011InternationalSAVE

In this Issue:1 Editorial: Creating Value in Product/Product

Life CycleM. A. Berawi, Ph.D.

3 Value Engineering the Construction of Bored Tunnels in Competent RockEur. Ing. Christopher Laughton, Ph.D., PE, C.Eng.

14 Value Engineering Applied to Create Champion ProposalsAnna M. Bremmer, CVS, LEED AP

21 Uncertainty Modeling in Multiple Dimensions for Value MethodologyRobert B. Stewart, CVS-Life, FSAVE, PMP & Gregory Brink, CVS, PMI-RMP, CCE/A

31 A “Functional” Tool for the VaVE ToolboxCarlos Gontijo, Jr., AVS

36 Revealing Hidden Externalities in Major Projects with Value MethodologyMunsell McPhillips, Ph.D., AVS

136 South Keowee StreetDayton, OH 45402 USA

T (937) 224-7283F (937) 222-5794

[email protected]. value-eng.org

SAVE International136 South Keowee StreetDayton, OH 45402 USA

Volume 34, Number 2, Fall 2011 1V A L U EWORLD

development process, which is intended to result in cre-ating better value.

The fi rst paper, written by Christopher Laughton Ph.D., PE, C.Eng, discusses the application of value engi-neering studies to advance the effi ciency of tunnel boring machine (TBM) mining system in competent rock mass-es. The early value engineering exercise identifi ed and developed a range of low risk options to enhance TBM performance and streamline support operations under favorable rock mass conditions. Direct cost savings of in-dividual proposals were estimated to range from about 2-10% of the pre-profi t, contract value.

The second paper, written by Anna M. Bremmer, CVS, LEED AP, discuses on how value engineering meth-odology can be used to develop stand-out bidding pro-posals which will highly improve the chances of being selected. By refl ecting a solid understanding on the chal-lenges that clients face and matching solutions that can be delivered is argued as the backbone of a stand-out proposal. The use of VE job plan as a framework for a proposal development process can greatly improve the value of the proposal in order to: Win Contract, Develop Relationship, and Grow Business.

The third paper, written by Robert B. Stewart, CVS-Life, FSAVE, PMP and Gregory Brink, CVS, PMI-RMP, CCE/A, presents uncertainty modeling in multiple dimensions for Value methodology. In making value comparisons, four essential elements must be factorized, namely, cost, performance, time and risk. Dynamic model con-siders value as an interrelationship between inputs and outputs of a system. This type of model is non-linear in nature and considers trade-off s between cost, time, and performance, while considering how risk infl uences each of these elements. On the other hand, discrete model is linear and considers cost, time, performance and risk in-dependently.

The fourth paper, written by Carlos Gontijo, de-scribes the use of Function Trade-off Table (FToT) as a tool developed specifi cally to provide key information prior to the VE workshop. The FToT lists the functions of the high-cost components and sub-assemblies, their spe-cifi c costs, and their associated trade-off s when using dif-ferent components to perform the functions. The objec-tive is to distribute the load of performing that function among other components to determine the most cost-

Today, business environment is becoming more and more complex. The complexity of a project/product de-velopment requires eff ective and effi cient approaches that need to be adapted in order to achieve the best value for client/customer. The aim of this process is no longer simply to keep costs under control within a pre-determined value in a particular stage, but a far wider analysis on the whole-life project/product costing, a sys-tematic consideration of all relevant costs and revenues associated with the creation and ownership of a project/product.

The emphasis on reducing capital expenditure must be then evaluated in terms of whole-life project/product cycle, including long term operation, maintenance and rehabilitation/disposal. It therefore provides a mecha-nism to ensure that the selected eff ective and effi cient method of project/product delivery is sustained for the achievement of value for money, e.g. price, quality, risk control and technology transfer. Value for money is viewed as an optimum combination of the provision of functions with appropriate cost and quality to meet the stakeholder’s requirement.

In this role, value engineering/value management practitioners are challenged to embrace new ideas and techniques where they will enable clients/customers to consider the relative importance of various attributes in terms of whole-life project/product cycle and propose an optimum solution for a particular context under study. VE/VM is therefore used as an organized method that employs intellectual capital to generate innovative ideas so as to be applicable in a competitive market through the use of Function Analysis as the foundation and cata-lyst in order to achieve innovative solutions.

Creating Value in Project/Product Life Cycle

Value World now has a dual focus, i.e. academic de-velopments and practitioner success stories, and grow-ing into a high quality printed document published twice yearly. Based on the CVS papers, journal submission and selected papers from the 51st annual SAVE International Conference in Oregon, USA, the fall issue of Value World presents fi ve selected papers to stimulate debate and to explore various processes in improving project/product

Creating Value in Project/Product Life Cycleeditorial

V A L U EWORLDVolume 34, Number 2, Fall 20112

eff ective distribution that will benefi t the object under study.

The last paper, written by Munsell McPhillips, Ph.D. AVS, discusses economic externalities in engineering de-sign and how the Value Methodology, particularly func-tion analysis, may provide a mechanism for revealing and ameliorating these hidden costs. By identifying and quan-tifying positive externalities, the benefi ts, which possibly are expressed as avoided costs, should be accrued to the project. When positive externalities go uncaptured, the project is undervalued and the incentives to proceed are improperly reduced.

I hope this edition of Value World conveys some new insights in the way we conduct our value methodology studies. I can be contacted at [email protected] and I will gladly accept and respond to any comment and enquiry you may have on the direction and content of Value World. Your valuable contribution and feedback are important to the success of our journal as it will guide its future development.

With warmest regards from editorial desk,

Dr. M.A. BerawiFaculty of EngineeringUniversity of Indonesia

16424 JakartaIndonesia

SAVE THE DATEDon‛t miss the fun and educational opporunities at SAVE International‛s

2012 Annual ConferenceJune 11 - 14

Benchmark these dates:Call for Pre-Conference Workshops begins September 1 and ends November 30. SAVE will only accept workshop proposals submit-ted via the online form. Selections will be announced in January 2012.

Call for Abstracts begins September 1 and ends November 30. SAVE will only accept workshop proposals submitted via the online form. Selections will be announced in Janu-ary 2012.

Conference Brochure: SAVE will publish the preliminary conference program in Feb-ruary 2012.

Hotel Information:The 2012 Annual Conference will take place at the Renaissance® Orlando at Seaworld®. SAVE International has negotiated discounted, single room rates of $159 per night. U.S. government employees may claim a per diem rate of $102 per night. Government identifi cation will be required to receive the government per diem rate. All room rates are subject to applicable state and local taxes in effect at the time of check-in.

All hotel room reservations at the Renaissance® Orlando at Seaworld® will be performed via the online reservation system powered by Passkey. All reservations will be made, modifi ed, or can-celed by individuals through the Passkey sys-tem or with the hotel directly.

The group rate of $159 per night is available only through Friday, May 11, 2012.


Value Engineering the Construction of Bored Tunnels in Competent Rock

Eur. Ing. Christopher Laughton, Ph.D., PE, C.Eng.

This paper was originally printed at the SAVE International 2011 Annual Conference.

Abstract

Recent years have seen a move towards the adoption of mined tunnels to house urban infrastructure. Tunnels can meet a wide range of infrastructure needs, includ-ing those required for cable, pipeline, and transportation uses. In the congested city selecting an underground site can off er important aesthetic, construction and opera-tional advantages to the infrastructure operator. Recent advances in tunneling technologies, notably in the ar-eas of mechanical excavation (Tunnel Boring Machines, TBM) and ground control have rendered underground construction a technically feasible options at most sites. This paper discusses early value engineering proposals developed in the course of two studies to advance the effi ciency of the TBM-system mining in competent rock masses.

Introduction

Tunnels can serve as new infrastructure corridors with minimal disruption to the surface environs. The more congested a city becomes, the more attractive the subsurface solution becomes. Some key benefi ts that an underground site can off er an urban infrastructure proj-ect are summarized below:

Increased network reliability

Greater operational longevity

Lower operating and maintenance costs

Dense corridor development that delivers increased property and business revenue streams

Improved quality of life for the served communities (e.g. better utility services, shorter commute times, less construction disturbance)

Preservation of open space and improvement of neighborhood amenities.

Despite the advantages noted above, the subsur-face solution is often determined to be a more expen-

sive option than surface alternatives. The viability of the underground option may be unduly penalized by an un-derweighting of life-cycle cost advantages and the use of overly conservative capital cost estimates. Conservative estimates are typically based on reference to old project data sets that do not adequately incorporate the posi-tive impacts that technology advances have had on tun-neling performance. Baseline estimates of construction cost and contingency need to be updated to refl ect the state-of-the-industry in tunnel construction. In addition, although performance of TBM-systems has improved in recent years, the underground operation is still far from the manufacturing process it was designed to be. The system typically operates for less than 50% of available shift time. There is plenty of room left for improving the process and reducing cost below current state-of-indus-try levels. In the late 1990s, the high energy physics com-munity decided to stimulate industry interest in further improving TBM operation with the goal of making ac-celerator tunnels cheaper. The physics community is a major user of underground space for particle accelera-tor systems. Figure 1 (below) shows the trace of a 27km-long accelerator tunnel that underlies the Leman Basin to the west of Geneva, Switzerland. Figure 2 (next page)

VALUE�ENGINEERING�THE�CONSTRUCTION�OF�BORED�TUNNELS�IN�COMPETENT�ROCK�(LAUGHTON)�P A G E 2�

Figure 1: Aerial Photo of the GenevaBasin – with 27km LHC Accelerator Tunnel Trace (Source CERN)

Despite the advantages noted above, the subsurface solution is often determined to be a more expensive option than surface alternatives.The viability of the underground option may be unduly penalized by an underweighting of life-cycle cost advantages and the use ofoverly conservativecapital cost estimates. Conservative estimates are typically based on reference to old project data sets that do not adequately incorporatethe positive impacts that technology advances have had on tunneling performance.Baseline estimates of construction cost and contingency need to be updated to reflect the state-of-the-industry in tunnel construction.In addition, althoughperformance of TBM-systemshas improved in recent years, the underground operation isstill far fromthe manufacturing process it was designed to be. The system typically operates for less than 50% of available shift time. There is plenty of room left for improving the process andreducing cost below current state-of-industry levels.In the late 1990s, the high energy physics community decided to stimulate industry interest in further improving TBM operation with the goal of making accelerator tunnels cheaper.The physics community is a major user of underground space for particle accelerator systems. Figure 1 shows the trace of a 27km-long accelerator tunnel that underlies the Leman Basin to the west of Geneva, Switzerland. Figure 2 shows the installations within the tunnel (Large Hadron Collider).

Figure 2: The Large Hadron Collider Accelerator Tunnel (Source CERN)

Figure 1. Aerial photo of the Geneva Basin—with 27km LHC accelerator tunnel trace (Source: CERN)


shows the installations within the tunnel (Large Hadron Collider).

This paper investigates opportunities to value engi-neer the TBM construction process through reference to a semi-generic accelerator project (“The Booster”). The tunneling industry was actively involved in the endeavor to ensure that the baseline estimate was consistent with state-of-the industry practice and that VE proposals de-veloped were technically feasible through incremental improvement in the TBM-system. The goal was to identi-fy short-term, low-risk improvements to the system that could be readily incorporated in to plans for future phys-ics projects. A focus was placed on pursuing the major cost savings that could be achieved through increasing TBM-system performance and reducing associated labor and equipment amortization costs. Although the investi-gation was performed for construction of an accelerator

tunnel, the results of the study are widely applicable to a range of infrastructure projects such as those shown in Figure 3, including:

Utilities (ducts, pipelines, power and communica-tions cables),

Clean water conveyance (drinking, irrigation, hydro-power),

Dirty water conveyance (storm and sewer water),

Commuter rail (mass transit, light rail),

High speed rail (inter-city), and

Road (city, rural).

Study Preparation

When any infrastructure network is placed under-ground, a major portion of the construction bill is associ-ated with tunnel construction. For an accelerator tunnel such as the one shown in Figures 1 and 2, the cost of the underground facilities can represent between a quarter and a half of the total cost. For other infrastructure proj-ects where the amount and cost of installed infrastruc-ture may be much lower, e.g. water conveyance, the tun-nel cost can represent a much higher fraction of the total capital cost.

A number of long tunnel-housed accelerator proj-ects were under design in the late 1990s. The construc-tion costs of such facilities were generally estimated to exceed $1B (Overbye, 2007). Reducing the cost of tunnel construction would have a major positive infl uence on

the viability of all these projects.

Value Engineering Partners

Recognizing the major positive impact that a reduction in tunnel cost could have on the viability of future accelerator projects, Fermi National Accelerator Laboratory (Fer-milab), a Department of Energy Laboratory sited to the west of Chicago, initiated stud-ies to investigate and promote the devel-opment of economy in the construction of TBM-mined rock tunnel. To support the work and maximize the likelihood of technology transfer, Fermilab enlisted the help of two companies preeminent in the fi eld of TBM tunnel construction. The companies were contracted to perform two studies.

The fi rst study was undertaken by Kenny Construction (KC), an Illinois-based tunnel contractor with extensive experience mining tunnel in the Chicago land area and through-


This paper investigates opportunities to value engineer the TBM construction process through reference to a semi-generic accelerator project (“The Booster”). The tunneling industrywas actively involved in the endeavor to ensure that the baseline estimate was consistent with state-of-the industry practice and that VE proposals developed were technically feasible through incremental improvement in the TBM-system. The goal was to identify short-term, low-risk improvements to the system that could be readily incorporated in to plans for future physics projects.A focus was placed on pursuing the major cost savings that could be achieved through increasing TBM-system performanceand reducingassociated labor and equipment amortization costs. Although the investigation was performed for construction of an accelerator tunnel, the results of the study are widely applicable to a range of infrastructure projects such as those shown in Figure 3, including:

� Utilities (ducts, pipelines, power and communications cables), � Clean water conveyance (drinking, irrigation, hydro-power), � Dirty water conveyance (storm and sewer water), � Commuter rail (mass transit, light rail), � High speed rail (inter-city), and � Road (city, rural).

Figure 3: Use of Tunnel Boring Machines for Urban Infrastructure (Sources: SmartSpace, BuRec, TARP/MWRD, EuroTunnel, SmartTunnel, BART)

STUDY PREPARATION When any infrastructure network is placed underground, a major portion of the construction bill is associated with tunnel construction. For an accelerator tunnel such as the one shown in Figures 1 and 2, the cost of the underground facilities can represent between a quarter and a half of the total cost. For other infrastructure projects where the amount and cost of installed infrastructure may be much lower, e.g. water conveyance, the tunnel cost can represent a much higher fraction of the total capitalcost.

A number of long tunnel-housed accelerator projects were under design in the late 1990’s. The construction costs of suchfacilitieswere generallyestimated to exceed$1B (Overbye, 2007). Reducing the cost of tunnel construction would have a major positive influence on the viability of all these projects.

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Figure 3. Use of tunnel boring machines for urban infrastructure (Sources: SmartSpace, BuRec, TARP/MWRD, EuroTunnel, SmartTunnel, BART)


Figure 1: Aerial Photo of the GenevaBasin – with 27km LHC Accelerator Tunnel Trace (Source CERN)

Despite the advantages noted above, the subsurface solution is often determined to be a more expensive option than surface alternatives.The viability of the underground option may be unduly penalized by an underweighting of life-cycle cost advantages and the use ofoverly conservativecapital cost estimates. Conservative estimates are typically based on reference to old project data sets that do not adequately incorporatethe positive impacts that technology advances have had on tunneling performance.Baseline estimates of construction cost and contingency need to be updated to reflect the state-of-the-industry in tunnel construction.In addition, althoughperformance of TBM-systemshas improved in recent years, the underground operation isstill far fromthe manufacturing process it was designed to be. The system typically operates for less than 50% of available shift time. There is plenty of room left for improving the process andreducing cost below current state-of-industry levels.In the late 1990s, the high energy physics community decided to stimulate industry interest in further improving TBM operation with the goal of making accelerator tunnels cheaper.The physics community is a major user of underground space for particle accelerator systems. Figure 1 shows the trace of a 27km-long accelerator tunnel that underlies the Leman Basin to the west of Geneva, Switzerland. Figure 2 shows the installations within the tunnel (Large Hadron Collider).

Figure 2: The Large Hadron Collider Accelerator Tunnel (Source CERN) Figure 2. The large hadron collider accelerator tunnel (Source: CERN)


out the US. KC provided a constructability review of the basic excavation requirements and developed a robust, bottoms-up estimate, of the tunnel “shell” (ground sup-port and invert concrete) costs, based on the use of lo-cal, state-of-the-industry bored-tunnel construction prac-tices.

The second study was undertaken by The Robbins Company (TRC), a pioneer in the fi eld of rock TBM manu-facture. TRC was contracted to review the cost estimate and identify and assess early opportunities for cost re-duction through equipment innovation and improved operational practices. Contracts were written to allow for the review and exchange of ideas between partners throughout the execution periods of the two studies.

Assumed Ground Conditions

For the purposes of the early VE study, a baseline site for the Booster Project was identifi ed adjacent to the Fermilab facilities. As laid-out, the proposed tunnels were hosted in a dolomitic rock mass. This site was con-sidered highly conducive to cost-eff ective TBM-system operation. In particular, ground conditions at the site were assumed to be close to those of an ideal tunneling media, as shown in Figure 4 (below).

Based on a general knowledge of site ground condi-tions, the host rock mass material underlying the Fermilab

site was classifi ed as “good” to “very good” for ground support purposes (Bieniawski, 1979). It should be noted that site-specifi c investigation will be needed to validate and detail the range of ground conditions in situ. Fol-lowing the acquisition of site-specifi c data, there may be opportunities to minimize the likelihood and impacts of ground risks, such as high horizontal stresses and water infl ow (Bialowons et al., 2002). For underground projects it is critical to maintain siting fl exibility until adequate site investigation data has been collected and interpreted to inform key design decisions related to alignment selec-tion, detailed design, risk analysis and VE work.

Conceptual Layout and Construction Site Constraints To support the development of a construction scope-

of-work, the end-users (physicists and in-house staff en-gineers) worked together to develop a preliminary set of tunnel space and alignment requirements. These basic re-quirements focused on ensuring that permanent fi xtures could be housed, and that installation, operation, and maintenance functions could be effi ciently performed within the confi nes of the mined envelopes. Minimum cross-sectional space needs, including alignment toler-ances, access shaft sizes and inter-shaft spacings, were defi ned.

End-user requirements developed by the in-house team called for construction of a 34 km long, 3 meter di-

Definition for Design Rock Mass Poperty Ideal Condition

Rock Material

Intact Rock Strength Intermediate to Low

Abrasiveness Low

Interblock Weathering Unaltered

Block Size Massive

Tunnel Environment

In Situ Stess Moderate

Water Inflow Dry

Gas Inflow No Gaseous Inflow

Constructability

UniformGeo-Variation

Highly Predictable

TBM-Rock InteractionPR Estimate Calibrated

U Estimate Calibrated

Figure 4. Idea rock mass conditions for TBM operation (Laughton, 1998)


ameter, sub-horizontal, fl at-fl oored ring tunnel and con-necting injector tunnels. The injector tunnels allowed for particle transfer from an existing accelerator facility. Consistent with regional engineering practices, the rock tunnels and shafts were stabilized using pattern rock bolts.

4.0 INFORMATION PHASE

The Contractor’s Constructability Feedback:The end-user requirements were subject to a con-

structability review by KC. KC’s personnel was actively encouraged to propose changes in the layout and work-ing plans that, in their judgment, would better refl ect the best use of labor and equipment.

Following the constructability review, the basis of estimate was updated to refl ect KC’s recommendations. Table 1 notes key construction elements of the basis of estimate. In the table distinction is made between what the accelerator physicists and engineers required and what the Contractor preferred to build.

A groundwater criterion was added to establish a shared expectation of infl ow rates. These rates were considered readily achievable using conventional post-excavation, cement-grouting techniques. A relatively dry tunnel is required for the operation of accelerator sys-tems.

Key scoping agreements and decisions that were made following the constructability review included:

Increment in the main tunnel diameter to reduce op-erational constraints and accommodate greater ex-cavation alignment tolerance.

Addition of a nominal uphill mining slope to promote gravity drainage.

Addition of egress shafts to allow for the rapid evac-uation of the underground works in case of an emer-gency.

Addition of a post-excavation grouting campaign to ensure establishment of a reasonably dry in-tunnel environment.

Confi rmation that the construction scope excluded additional underground structures required to house auxiliary equipment.

Confi rmation that no additional construction shafts were required to support the TBM operation. TBMs have operated successfully in smaller tunnels and over longer inter-shaft distances than are proposed for this project.

No time constraint was placed on the delivery of the underground facilities. KC’s estimating staff was asked to organize and schedule-out the work in the most cost-ef-fective way possible (Lach et al. 1998).

The Contractor’s Construction ApproachKC planned-out and estimated the work within the

framework of a single contract. KC chose to use two TBMs to mine around the ring in opposite directions from a single start shaft. The start shaft was sited at the low point of the tunnel plane, allowing for gravity drainage of ground and construction waters away from the TBM headings. The costs of the two TBM-systems were am-ortized over a 17km length of tunnel. It was noted that some TBMs have operated for longer distances, but KC made the decision to “double-up” the equipment costs in order to save on extended site overheads and other time-related costs.

The major in-tunnel activities were scheduled-out to be performed in sequence. Key critical path activities for each tunnel reach were excavation, grouting, and invert concreting. Based on the good quality of the rock mass noted above, it was assumed that the arch of the bored dolomitic limestone would not require the placement of a lining. This assumption is consistent with local mining experience.

The Contractor’s Cost Model

Table 1. Baseline Specifi cations for the Accelerator Tunnel Study

Item End-User Required Contractor PreferredInstallation Shafts (# & diameter) 4 X 6.0m diameter

Egress Shafts— Construction/Installation Safety None 20 X 1.8 m diameter

Accelerator—Tunnel Length 34 km

Injection Line—Tunnel Length 5.5 km (90% rock, 10% soil)

Accelerator/Injector Tunnel Diameter 3.0 m 3.7 m

Accelerator/Injector Tunnel Floor 2.1 m 2.1 m

Allowable Water Inflow 125 l/min/km

Completion Milestones None Specified


At the early stages of a typical construction project, cost estimates are commonly developed using quantity take-off sand unit costs obtained from industry data bas-es. Cost models using this process will generally be satis-factory when estimating conventional structures, but for tunnels this approach can be problematic. Tunnel costs generated from reference to other tunnel unit prices can be grossly inaccurate. Underground unit prices (dollars per linear meter or cubic meter) can vary by over an order of magnitude from job to job as a function of local ma-terial costs, work rules, site conditions, site constraints and end use. Unless cost data sets from closely-matched projects are readily available, a bottoms-up estimate per-formed by an experienced estimator familiar with local practice is a more reliable way to establish a cost model.

Using a bottoms-up estimate developed by a suc-cessful tunneling contractor familiar with bidding in the area was particularly valuable for the Booster Project as it created a solid basis for developing the scope of the follow-on TRC study. The level of cost detail provided by the bottom-up estimate allowed TRC the best pos-sible opportunity to identify the underlying cost drivers. KC developed such a detailed, bottom-up estimate and schedule for the underground facility using their own data base of costs and productivities. Table 2 (above) shows the breakdown of costs for the construction con-tract.

The construction scope lacked details on require-ments, site constraints and ground conditions. No specif-ic contingencies were identifi ed to account for this lack of detail, but the contractor instead assumed a healthy profi t margin. Contingency setting issues for under-ground projects are briefl y discussed later in this paper.

From the data in Table 2, the main cost drivers behind the project are clearly seen to be associated with the

construction of the main tunnel. Main tunnel direct costs represent over 55% of the total direct costs. A pie-chart showing a breakdown of direct costs for the construction of the main tunnel is shown in Figure 5. Main tunnel labor and personnel, subcontracting, and equipment costs ac-count for over 85% of the main tunnel direct costs. The relatively small cost contribution of equipment opera-tions, permanent materials, and operation supplies re-fl ect the stable (few bolts) and non-abrasive (low cutter consumption) nature of the rock mass. For the follow-on TRC study, labor and personnel direct costs were consid-ered to be largely time-related.

Early Paths for Cost Reduction

Rock TBM-System OperationsA fully-assembled TBM-system is shown in Figure 6

(next page). The cutter head is shown in the foreground with support systems trailing behind. The trailing gear includes essential support equipment associated with

Table 2. Details of the Construction Contractor’s Cost Model—Bottoms-Up Estimate

Direct CostsLabor & Personnel

Equipment Operations

Equipment Costs

Permanent Materials

Operation Supplies

Subcontract Work Subtotals

Shafts 4,753,057 636,759 961,075 1,419,802 513,923 245,490 8,530,106

Main Tunnel

26,905,443 2,783,865 20,244,412 1,497,928 4,025,914 7,968,238 63,425,800

Aux. Works 8,298,908 871,667 2,765,250 1,604,468 1,359,846 736,685 15,636,824

Invert 4,471,830 338,740 345,010 3,449,911 489,679 — 9,095,170

Grout 13,771,783 401,408 367,000 444,675 715,352 — 15,700,218

Total Direct 58,201,021 5,032,439 24,682,747 8,416,784 7,104,714 8,950,413 11,388,118

Total Indirect

9,840,136 412,786 663,980 — 9,651,676 4,295,232 24,863,810

Totals 68,041,157 5,445,225 25,346,727 8,416,784 16,756,390 13,245,645 137,251,928

Profit 30,000,000

Final Bid 167,251,928

Labor & Personnel, 12.1%

Equipment Operations, 1.1%

Equipment Costs 31 9%Equipment Costs, 31.9%

Permanent Materials, 2.1%

Operation Supplies, 6.3%

S b W k 12 6%Subcontract Work, 12.6%

Figure 5. Pie chart of direct costs for construction of the main tunnel


power, ventilation, hydraulic, and waste rock handling systems.

Each boring cycle advances the TBM cutter head by the stroke length of the thrust cylinders, typically 1.2m to 1.8m. The cutter head rotates under axial thrust, into the tunnel face, each cutter creates a concentric groove in the rock face. Sidewall gripper pads provide reaction to the cutter head forces. As the cutter head bores in to the rock, broken rock (muck) falls to the base of the excava-tion and is scooped-up by buckets mounted around the cutter head perimeter. The muck is fed on to a conveyor belt and transferred to the trailing gear muck handling system. Once the cutter head thrust cylinders are fully extended, the boring process stops, the reaction grip-

pers are retracted from the sidewalls, and the thrust cyl-inders’ stroke is recovered (“re-grip”). Rock support is installed behind the cutter head shielding, in parallel with the other activities. The basic activities of the TBM bor-ing cycle are shown schematically in Figure 7 (below).

As designed, the ground support and mucking activi-ties are generally timed to be completed within or keep pace with the core mining cycle (bore and re-grip). How-ever, in practice muck removal, or ground support instal-lation can delay completion of each mining cycle, leading to muck-bound or support-bound operation, respective-ly. The critical path can change from cycle to cycle as a function of TBM heading conditions. However, for this particular project, ground conditions are assumed to be good and a mucking system with a proven capacity and

reliability has been selected. Engineering consensus was that the number of muck-bound and support-bound bor-ing cycles encountered during the TBM drive would be minimal. The KC estimate refl ected this consensus with TBM operation being penetration-bound, i.e. cycle time equal to the time for bore and re-grip. The estimate also assumed that the TBM would be operated with a typical loss of production time, equal to approximately 18 min-utes delay per meter of tunnel mined. This value is typi-cal of industry experience where it is commonplace for a TBM to be boring tunnel for less that 50% of the available production time. Machine utilizations rarely top 60% over the length of a tunnel drive.

TRC Study Speculation TargetsAlthough a more comprehensive defi nition of tunnel

design criteria, site constraints, and ground conditions will eventually be needed to support an optimization of the Booster facilities, it was already apparent that there were opportunities to reduce tunnel costs. Fermilab en-gaged TRC to review the TBM cost-drives that dominated the contractor’s estimate and identify modifi cations or operational improvements that could be made to reduce the direct costs of the main tunnel excavation process. TRC was a pioneer in the mechanized excavation of rock tunnels. The company’s TBMs have been used with great success on a large number of rock tunnel projects nota-bly including a previous accelerator project where design and contracting strategies were put-in-place to support world record TBM performance (Super Conducting Su-per Collider).

Based on a review of the KC estimate and discussion amongst the partners three distinct areas were identifi ed where changes in TBM systems and operations could re-sult in a signifi cantly lower tunnel cost:

Reducing time-on-site and time-related costs by in-creased TBM-system performance

Reducing TBM manpower requirements by increased mechanization and multitasking

Reducing equipment amortization by increased equipment longevity and design fl exibility

The steps identifi ed by TRC to achieve these cost re-duction goals are discussed below.

Increased TBM-System PerformanceThe TBM-system performance assumed by KC for

estimating purposes was defi ned in terms of average penetration rate (PR) and utilization (U). PR is the rate at which the cutter head bores the rock (m/hour). U is the percentage (%) of production shift time during which the cutter head is boring. The average estimate values


Figure 5: Pie Chart of Direct Costs for Construction of the Main Tunnel

The pie chart clearly demonstrates the dominant impact that the two main tunnel cost categories Labor/Personnel and Equipment had on the overall tunnel cost. TRC focused its effort on reducing the costs in these two key categories.To reduce the cost of Labor/Personnel TRC identified measures targeting increments in TBM advance rate and reductions in crew size; “Faster with Fewer.”To reduce equipment cost,s measures were identified to improve system availability and longevity and increase the possibility of equipment re-use through the adoption of a more flexible approach to designing and tendering TBM tunnel work.

EARLY PATHS FOR COST REDUCTION

Rock TBM-System Operations A fully-assembled TBM-system is shown in Figure 6. The cutterhead is shown in the foreground with support systems trailing behind. The trailing gear includes essential support equipment associated with power, ventilation, hydraulic, and waste rock handling systems.

Figure 6: An Assembled Rock TBM-System (Source: CERN)

Each boring cycle advances the TBM cutterhead by the stroke length of the thrust cylinders, typically 1.2m to 1.8m. The cutterhead rotates under axial thrust, into the tunnel face, each cutter creates a concentric groove in the rock face. Sidewall gripper pads provide reaction to the cutterheadforces. As the cutterhead boresin to the rock, broken rock (muck) falls to the base of the excavation and is scooped-up by buckets mounted around the cutterhead perimeter. The muck is fed on to a conveyor belt and transferred to the trailing gear muck handling system. Once the cutterhead thrust cylinders are fully extended, the boring process stops, the reaction grippers are retracted from the sidewalls, and the thrust cylinders’ stroke is recovered (“re-grip”). Rock support is installed behind the cutterhead shielding, in parallel with the other activities.The basic activities of the TBM boring cycle are shown schematically in Figure 7.

Bore

MuckRegrip

Support

Figure 6. An assembled rock TBM-system (Source: CERN)

Bore

Muck

Regrip

Support

Figure 7. Core activities of the TBM-system boring cycle


developed by KC are considered to be in-line with other best-in-class TBM performance thresholds.

Figure 8 (next page, top) shows the average TBM drive performance reported in PR:U space. On the graph-ic drive averaged Advance Rate (AR, meters/hour) and best-in-class performance contours are added to provide a framework for comparing baseline and upgrade perfor-mance, where AR = (PR * U)/100. Projected performance enhancements of upgrade proposals made by TRC are plotted to allow for a comparison with the performance assumptions of the baseline estimate.

TRC proposed three upgrade paths (#1, #2, #3). These paths were projected to yield signifi cant advance rate in-crements over the average advance rate used in the con-tractor’s estimate (KC). These increments would result in reduction of time-related direct and indirect costs. The upgrade paths are described below. Machine Upgrade Path 1 would increase the PR through the adoption of a state-of-the-art, high power machine. A high power machine allows for increased thrust and speed of cutter head rotation. The increased thrust yields an increase in the penetration achieved per revolution of the machine. TRC projected that the net result of this upgrade would be to increase Penetration Rate from 6 to 10 meters per hour. In estimating the net gain in Advance Rate, the positive infl uence of the upgrade on Penetration Rate is partially off set by a reduction in Utilization. With an incre-ment in PR, and constant unit delay time a reduction in U will be observed.

Machine Upgrade 2 would increase U by eliminat-ing the between-stroke systematic re-grip stoppages through the incorporation of double thrust cylinders. The “lost time” associated with re-grip has long been noted as a source of delay, but had not previously been successfully implemented on rock TBM projects.

Machine Upgrade 3 would further increase U by im-proving the reliability of critical sub-systems through the

increased adoption of monitoring and preventive main-tenance programs. TRC’s aim here was to increase the Time-Between-Failures and reduce the Time-To-Repair of critical sub-systems by monitoring and identifying pre-cursors to failure. If a sub-system malfunction is identi-fi ed before failure, preventative maintenance or replace-ment can be planned and undertaken during scheduled maintenance periods, already a common practice in the mining industry.

The potential for improving overall TBM-system per-formance through implementation of TRC upgrades is most readily gauged by reference to the AR contours plotted in PR:U space above. For example if the state-of-the-industry AR performance could simply be tripled, from 2 to 6 m/h, the impact on the contract duration and time-related costs would be high. Even a doubling of the AR, which in the short-term may be a more realistic tar-get, would eff ectively halve the excavation time. If the di-rect labor/personnel costs were proportionally reduced this would translate to a reduction in contract value of roughly 10% (w/o profi t).

Increased Mechanization and Multi-TaskingIn reviewing the details of the KC estimate TRC also

highlighted a potential for reducing in-tunnel crew siz-es through the use of remote equipment monitoring, preventative maintenance and increased multitasking. Multi-tasking is already commonplace in many parts of the world, primarily in the excavation of hard, stable rock masses, where focus is placed on boring and mucking activities rather than maintaining ground support at the tunnel heading, a more labor-intensive activity. Table 3 notes typical levels of in-tunnel shift labor for drill and blast and TBM excavation work in the US. For comparison the labor level for hard rock TBM mining in Scandinavia is noted in the left-hand column. The table is based on in-formation provided by TRC. With burdened, hourly labor rates in the $50-60 range for most major underground projects in the US, the introduction of more multitask-ing work practices to US operations would clearly have a signifi cant benefi cial impact on tunnel costs.

Table 3. Estimated Crew Sizes for Tunnel Driving

Practice US ScandinaviaShift Labor Drill/Blast TBM TBM

Excavation Crew 13 6 3

Mucking Crew 4 4 3

Track/Supply 3 3 1

Portal Crew 3 3 3

Total 23 16 10


Figure 8: Improved Performance Achieved with TBM-System Upgrades, 1 2 & 3

TRC proposed three upgrade paths (#1, #2, #3). These pathswere projected to yield significant advance rate increments over the average advance rate used in the contractor’s estimate (KC). These increments would result in reduction oftime-related direct and indirect costs. The upgrade paths are described below.

Machine Upgrade Path 1would increase the PR through the adoption of a state-of-the-art, high power machine. A high power machine allows for increasedthrust and speed of cutterhead rotation. The increased thrust yields an increase in the penetration achieved per revolution of the machine. TRC projected that the net result of this upgrade would be to increase Penetration Rate from 6 to 10 meters per hour. In estimating the net gain in Advance Rate, the positive influence of the upgrade on Penetration Rate is partially offset by a reduction in Utilization. With an increment in PR, and constant unit delay time a reduction in U will be observed.

Machine Upgrade 2 would increase U by eliminating the between-stroke systematic re-grip stoppages through the incorporation of double thrust cylinders. The “lost time” associated with re-grip has long been noted as a source of delay, but had not previously been successfully implemented on rock TBM projects.

Machine Upgrade 3 would further increase U by improving the reliability of critical sub-systems through the increased adoption of monitoring and preventive maintenance programs. TRC's aim here was to increase the Time-Between-Failures and reduce the Time-To-Repair of critical sub-systemsby monitoring and identifying pre-cursors to failure.If a sub-system malfunction is identified before failure, preventative maintenance or replacement can be planned and undertaken during scheduled maintenance periods, already a common practice in the mining industry.

The potential for improving overall TBM-system performance through implementation of TRC upgradesis most readily gauged by reference to the AR contours plotted in PR:U space above.For example if the state-of-the-industry AR performance couldsimply be tripled, from 2 to 6 m/h, the impact on the contract duration and time-related costs would be high. Even a doubling of the AR, which in the short-term may be a more realistic target, would effectively halve the excavation time. If the direct labor/personnel costs were proportionally reduced this would translate to a reduction in contract value of roughly 10% (w/o profit).

#1

#2

#3

KC

Figure 8. Improved performance achieved with TBM-system upgrades, 1 2 & 3


TRC noted that a typical TBM crew size in the US can be over 50% greater than those used for comparable opera-tions in other regions of the world. For this particular project, TRC recommend-ed reductions in crew size through the adoption of multi-tasking work plans and the automation of tasks such as track-laying, utility extension, equipment monitoring and rock support installation. Reductions, and ultimately the elimina-tion of labor from the tunneling process on more routine tunnel projects may be possible in the future. A reduction in TBM crew size consistent with the TRC recommendations was conservatively estimated to result in contract savings of between 2 and 4% (w/o profi t). These savings could be partially off set by ad-ditional costs associated with increased monitoring, mechanization and automa-tion. These costs were not estimated.

Increased Equipment Longevity and Design Standardization

The monitoring and maintenance provisions imple-mented as part of the TRC Upgrade 3 would not only lead to improvements in machine utilization, but would also support enhanced equipment longevity. An increase in longevity would allow a TBM-system to be used with greater reliability for longer distances; delivering reduced single job amortizations.

Given the cost of the individual TBM-systems noted in the Booster project estimate (approx. $10M) reduction in amortization may yield signifi cant reductions in-tunnel costs. However, these reductions will only be realized if the owner, designer, and construction manager stipulate contract(s) provisions that allow bidders the opportunity to propose secondhand machines. In particular, allowing bidders to propose secondhand machines within a speci-fi ed diameter range rather than specifying a new TBM of a diameter certain would open-up equipment re-use op-portunities for many contractors. The adoption of alter-nate contracting strategies may also encourage the se-lection of cheaper equipment packages. The fl owchart in Figure 9 (above right) identifi es some of the advantages that may be forthcoming of a more fl exible set of stan-dard tunnel design criteria were adopted that allowed the contractor more opportunity to propose construc-tion plans that incorporate the use of reconditioned TBM equipment.

The possibility of re-using TBM equipment on mul-tiple drives would be further enhanced if acceptable de-

sign options were identifi ed during the tender period. Adding fl exibility to the design criteria would enhance the bidding contractors’ ability to explore lower cost so-lutions based on the use of owned equipment and mini-mize the need for costly modifi cation or purchase. Equip-ment amortization costs can be reduced by as much as 50% where secondhand equipment is allowed (Peach, 1988). These strategies were successfully employed on the Texas site of the Superconducting Super Collider (Laughton, 1989). Here, refurbished TBM-systems were used to mine a diameter somewhat larger than specifi ed in the contract. A reduction of 50% in equipment costs for the Booster project would translate to a savings of some $10M or roughly 7% of the contract value (w/o profi t). Were a combination of the value proposals noted above adopted, the possibility of using a single TBM-system to mine the full 34km could also be reconsidered.

Improved TBM Reuse Potential

Reduced New TBM Cost

Lower TBM Authorization

Reduced Design Effort

More General use of TBMs

Lower Design Costs

Consistency in Rock Supports

Lower Tunnel Costs

Standardized Tunnel Design

Criteria

Figure 9. Flowchart demonstrating cost impacts of using standard tunnel design criteria


Figure 9: Flowchart Demonstrating Cost Impacts of using Standardized Tunnel Design Criteria

Thepossibility of re-using TBM equipment on multiple drives would be further enhanced if acceptable design options were identified during the tender period.Adding flexibility to the design criteria would enhance the bidding contractors' ability to explore lower cost solutions based on the use of owned-equipment and minimize the need for costly modification or purchase. Equipment amortization costs can be reduced by as much as 50% where secondhand equipment is allowed (Peach, 1988). These strategies were successfully employed on the Texas site of the Superconducting Super Collider (Laughton, 1989).Here, refurbished TBM-systems were used to mine a diameter somewhat larger than specified in the contract. A reduction of 50% in equipment costs for the Booster project would translate to a savings of some $10M or roughly 7% of the contract value (w/o profit). Were a combination of the value proposals noted above adopted, the possibility of using a single TBM-system to mine the full 34km could also be reconsidered.

Contingency Setting As noted in an earlier section, the estimate developed by KC did not explicitly address risk or contingency setting. At an early stage of the project the level of risk may be high, even in ground considered relatively conducive to TBM operations. Construction contingency should be set aside to address the unknowns that need to be quantified and addressed within the context of a comprehensive design effort. For underground work this effort will necessarily need to include site investigation, risk analyses and value engineering studies. A schematic diagram summarizing the data that willneed to be assembled to develop a best value design is shown in Figure 10.

Figure 10: Design Input to Support a Best Value Tunnel Design

StandardizedTunnel Design

Criteria

Improved TBM Reuse Potential

Reduced New TBM Cost

More General Use of TBMs

ReducedDesign Effort

Lower Tunnel Costs

Lower TBM Amortization

Lower Design Costs

Consistency in Rock Supports

Space

Installation

Best�Value�

Design

GeoMaterial

Mining Method(s)

ES&H

Reinforcing

Lining

GeoTreatmentsGeoStresses

Water Control

Operation Maintenance

Figure 10. Design input to support a best value tunnel design


Contingency SettingAs noted in an earlier section, the estimate devel-

oped by KC did not explicitly address risk or contingency setting. At an early stage of the project the level of risk may be high, even in ground considered relatively con-ducive to TBM operations. Construction contingency should be set aside to address the unknowns that need to be quantifi ed and addressed within the context of a comprehensive design eff ort. For underground work this eff ort will necessarily need to include site investigation, risk analyses and value engineering studies. A schematic diagram summarizing the data that will need to be as-sembled to develop a best value design is shown in Fig-ure 10 (previous page, bottom).

Figure 11 (above) categories and lists some of the key issues of risk commonly associated with an underground project. Of particular note are the issues related to the defi nition of the underground site conditions. Develop-ing practical engineering briefs and a clear execution plan are challenging aspects of an underground design. These risk categories will all need to be studied in detail

Risk Issues

CommunitiesGovernmentEnvironmentalHealthSafety ...

Approvals

Practical BriefClear PlanOrganizationInterfacesTeaming ...

Design

TechnologiesMethodologiesLabor CostsLocal PracticeProductivities ...

Estimate

Pre-QualificationBid PeriodBid SelectionRisk AllocationCompetition ...

Procurement Construction

Water ControlGround MovementGround CollapseStructural CollapseProductivity ...

Figure 11. Risk categories to consider in developing an underground project


Figure 11: Risk Categories to Consider in Developing an Underground Project Figure 11 categories and lists some of the key issues of risk commonly associated with an underground project. Of particular note are the issues related to the definition of the underground site conditions. Developing practical engineering briefs and a clear execution plan are challenging aspects of an underground design. These risk categories will all need to be studied in detail and considered within the context of developing the design.

Figure 12 quantifies the categories noted in Figure 11 as stacked histograms. A histogram of deterministic contingency allocations is shown at each critical decision (CD) point, 0 through 4. CD’s are used within the context of managing larger Department of Energy Office of Science capital projects, where:

CD-0: Mission Need Statement - core mission functions and goals established CD-1: Alternative Selection and Cost Range - design concept development and first estimate CD-2: Performance Baseline - design sufficiently developed to support firm budget and duration CD-3: Start Construction CD-4: Start Operation

Figure 12: Allocation of Contingency over the Project Life Figure 12. Allocation of contingency over the project life

and considered within the context of developing the de-sign.

Figure 12 (below) quantifi es the categories noted in Figure 11 as stacked histograms. A histogram of deter-ministic contingency allocations is shown at each critical decision (CD) point, 0 through 4. CD’s are used within the context of managing larger Department of Energy Offi ce of Science capital projects, where:

CD-0: Mission Need Statement - core mission func-tions and goals established

CD-1: Alternative Selection and Cost Range - design concept development and fi rst estimate

CD-2: Performance Baseline - design suffi ciently de-veloped to support fi rm budget and duration

CD-3: Start Construction

CD-4: Start Operation

The graphic underlies the need for the early allo-cation of large contingencies for underground work. Contingencies at the early, pre-site investigation phase of a project can be well over 50%, with much of the un-

certainty associated with the “geo-un-knowns” of the rock mass. It can also be seen that the opportunities for cost reduction are also maximal at the early stage of a project. It is the early cost saving opportunities associated with TBM tunneling that the early KC and TRC studies were targeted to capture.

Post-study Steps Towards Full Implementation

The TRC study work was complet-ed in 1998. Reports and papers summa-rizing TRC’s recommendations were disseminated within the industry. Since the study was completed a number of the recommendations have been im-


plemented. Upgrade 1 has been aff ected on TBMs mining in intermediate to hard, competent rock units. Partial im-plementation of Upgrade 2 on some drives has resulted in the shortening of the cyclic re-grip delay through the use of high volume hydraulic pumps. The total elimina-tion of re-grip time, through the use of double gripper systems, has not become standard practice.

Elements of the Upgrade 3 proposal have found widespread adoption in the industry. The underground industry is rapidly moving towards the integrated use of real-time reporting. The sophistication of monitoring systems has increased rapidly and nowadays data can be readily collected and processed to provide early perfor-mance feedback on equipment performance and ground behavior. Monitoring systems are being integrated on to new equipment and have also been retrofi tted to sec-ondhand TBMs. KC and Fermilab collaborated on the in-strumentation of a secondhand TBM (Lach et al, 1999). Evidence showing that manpower reductions and design standardization steps are being made is not readily ap-parent from a review of on-going US projects.

Conclusions

TBM tunneling technology continues to evolve, mak-ing tunnels ever more competitive with other corridor construction options. The industry studies conducted to support the early value engineering exercise identifi ed and developed a range of low risk options to enhance TBM performance and streamline support operations un-der favorable rock mass conditions. Direct cost savings of individual proposals were estimated to range from 2-10% of the pre-profi t, contract value.

Since the completion of these studies, several up-grade steps have been successfully implemented. Imple-mentation has typically been limited to similar projects (longer tunnels in competent rock) where the upgrades have the potential for a greater return with lower risk. In determining the cost impact of the individual upgrades, the estimator and equipment engineers will need to evaluate rock mass conditions, construction constraints and contract terms in detail. In particular, from a system perspective, the U improvements projected by TRC, for upgrades 2 and 3 will only be forthcoming if the total system, including logistics, mucking and support opera-tions, can keep pace with the elevated levels of Penetra-tion Rate, predicted by TRC.

Proposals to further mechanize underground opera-tions and increase the reuse of equipment have not been widely adopted. These changes may yet be implemented as the industry moves forward. Worker multi-tasking and remote equipment operations are common prac-tice worldwide. At some locations operators can control

multiple pieces of mining equipment from the comfort and safety of the home offi ce. Over time, improved con-fi dence in the reliability of TBM systems will likely result in increased reuse of equipment leading to cost savings, and shorter lead times for the preparation of equipment packages for new projects, a key factor on jobs with a compressed start-up schedule.

Although the short-term prospects of constructing long accelerator tunnels in the US has diminished since the studies were performed, the VE proposals they gen-erated are being implemented. It is likely that the low risk improvements identifi ed will support the continued evolutionary improvement in TBM application. Value en-gineering studies involving construction contractors and manufacturers can continue to enhance the viability of the underground option.

The leadership of Dr. Joseph Lach, the major practical and technical contributions of Kenny Construction, and The Robbins Company, and the sponsorship of the US Department of Energy are all gratefully acknowledged.

References

Bialowons, W., C. Laughton, A. Seryi (2001).“Detailed Summary of the Working Group on Environmental Control (T6)”. Summer Study on the Future of Par-ticle Physics, Snowmass, Colorado, June-July. 13 pag-es.

Bieniawski, Z.T. (1979). “The Geomechanical Classifi ca-tion for Rock Engineering Applications.” Fourth In-ternational Congress on Rock Mechanics, Montreux, Switzerland, Vol. 2, pp. 41-48.

Lack, J, R. Bauer, P. Conroy, C. Laughton, E.Malamud (1998). “Cost Model for a 3 TeV VLHC Booster Tun-nel..” Fermilab Technical Memorandum No. 2048, 10 pages.

Lach, J., D. Fashimpaur, R. Florian, M. Kucera, C. Laugh-ton, P. Lucas, M. Shea, T. Budd, J. Johnson (2000). “Instrumentation of a Reconditioned Robbins Tun-nel Boring Machine - 106th Street Tunnel.”

Fermilab Technical Memorandum No. 2141, 19 pages.

Laughton, C. (1989). “Adaptation of the Superconduct-ing Super Collider Underground Facilities—Towards a Site-Specifi c Conceptual Design.”Proceedings of the 30th US Symposium on Rock Mechanics, Mor-ganstown, WV, June.

Laughton, C. (1998). “Evaluation and Prediction of Tun-nel Boring Machine Performance in Variable Rock Masses.”Ph.D. Dissertation, University of Texas at Austin, Texas.

Overbye, D. (2007).“Price of the Next Big Thing in Physics:


$6.7 Billion.” New York Times, February 8th, 2007.

Peach, A. (1988) “Remanufactured TBMs.” World Tun-nelling, June Issue, pp. 155-157.

The Robbins Company (1999). “Tunneling Cost Reduc-tion Study.” Prepared for Fermi National Accelerator Laboratory. 40 pages.

About the Author

Dr. Chris Laughton is a profes-sional engineer with 35 years of experience in the design, construction, and maintenance of underground projects for mining, quarrying, transit, util-ity, hydroelectric, and research purposes. Chris has worked as a line manager for tunnel own-ers, designers, and builders and has developed techniques for predicting the performance of

mechanical excavation systems. Chris has authored over 50 technical papers and is part of a team that conducts research into mechanical excavation system performance. Chris is currently Chairperson of the Underground Con-struction Association’s Benefi ts of Going Underground Committee and works as an independent consultant on projects in the US and overseas.

SAVE Accepting Consultant Directory Orders

SAVE International is accepting orders for the 2012 issue of its annual consultant directory.

The consultant directory is the best place to fi nd a VM consultant. The directory is searchable by com-pany, contact name, location, business type, and ser-vice provided.

Who is listed?SAVE accepts paid listings from members, affi li-

ates, and others wishing to promote their profession-al services to VM clients and VM practitioners. The consultant directory is the fi rst place potential clients are directed when seeking a value practitioner.

Why list your business?SAVE’s consultant directory is used by VM clients

and practitioners worldwide as the primary resource for locating value methodology consultants, instruc-tors, and value study team members. The directory is strongly promoted, easily accessible, and fully search-able on SAVE International’s website. It is available in electronic and print formats.

Directory patrons can customize their listings. Digital advertisements may be changed up to twice during the issue year at the advertiser’s request.

How much does it cost?Advertising in the SAVE consultant directory is

economical. Prices are the same as 2011!

Listing PriceBasic Listing $75Branch Offi ces $50 eachService Guide Listings $15 eachHalf-Page Advertisement $100Whole Page Advertisement $200Web-Based Advertisement $150Directory Sponsor $500

Place your order now!To place your order online, go to the SAVE Web-

site (www.value-eng.org) and select “Find a VM Pro-fessional” from the navigation menu at top. Then click on the link for “Consultant Directory Online Listing Order Form”. Or call SAVE International at (937) 224-7283 to request a printed order form.

Seeking Success Stories

SAVE International is seeking value methodology success stories to publish in InterActions, its monthly member

newsletter. Articles should be between 1,000 and 1,500 words long and be

accompanied by illustrative graphics.

Submit your team’s success story via e-mail to [email protected] for

editorial consideration. Attach graphics separately from content; do not embed graphics within the message body or

within the article content.


Value Engineering Applied toCreate Champion Proposals

Anna M. Bremmer, CVS, LEED AP


Abstract

Securing project work is becoming increasingly chal-lenging for consulting fi rms in the design, construction, and environmental industries. “Value Engineering Ap-plied to Create Champion Proposals®” demonstrates how the SAVE International® value engineering method-ology can be used to develop stand-out proposals that strongly improve the chances of being selected.

Methods for developing a winning proposal are dis-cussed in the context of overall business development. Refl ecting a solid understanding of the challenges clients face and matching solutions that fi rms can deliver is the backbone of a stand-out proposal. “Value Engineering Applied to Create Champion Proposals®” provides a clear road map of how this can be done. It off ers a com-prehensive new approach to proposal writing that has not been explored until now.

The author draws from her own experience in devel-oping the entire content of the paper. She brings over 20 years of experience in multidisciplinary proposal writing as part of business development for fi rms including geo-engineers, Inc., Turner Construction, Brown & Caldwell, Olympic Associates Company, and ICF Jones & Stokes. Through her exposure to the value engineering process, the natural linkage between the VE Job Plan promoted by SAVE International® and business development life cycle became clear: The SAVE International® methodol-ogy can be applied to just about any process.

Introduction

In an era of increased competition for project work, architecture, engineering, environmental, and construc-tion professionals who support private industry and pub-lic agencies face a profound challenge. Projects and pro-grams must perform better than ever—and cost less.

The bar has been raised to win project work. No lon-ger do proposals that rely on generic, “canned” content or fail to communicate benefi ts, features, and proof

make the shortlist. Communicating a real understanding of the client’s challenges for a program or project and presenting innovative, sound solutions is crucial. Custom-izing the majority of a proposal to refl ect these specifi cs is also crucial, as it reinforces the theme of a proposal throughout.

The SAVE International® value engineering (VE) methodology is easily applied to the project pursuit and proposal process for results that make proposals in the building industry stand out from the crowd.

Applying the Job Plan to Proposal Development

Parallels Between the Job Plan Promoted by SAVEInternational® VE and the Business Development

Life Cycle The life cycle of business development to win projects and develop relationships closely mirrors the VE Job Plan promoted by SAVE International®. It includes eight phases, which are repeated throughout the work-ing relationship with a client.

The principals of the VE Job Plan promoted by SAVE International® can be applied to create Champion Pro-posals®, as described below.

Pre-study—Big-Picture Alignment, aka “Business Development 101”

The Pre-study Phase in the VE Job Plan includes de-fi ning study scope and objectives, and gathering infor-mation about the project—including its scope, designs, reports, estimate, cost models, schedule, risks, and con-straints. This is done to develop a clear understanding of study priorities; defi ne project and study expectations; and provide a thorough overview of the whole project.

In similar ways, the Pre-study Phase of the business development life cycle seeks to develop a big-picture understanding of a client’s needs and program and/or project objectives. It also examines the fi t between your company and the client.


The Big Picture for Your CompanyIn the context of business development, it is always

a good idea to regularly review your company’s mission, goals, objectives, and marketing plan to verify that the program or project to be pursued fi ts the plan. As an in-dividual seller/doer, it is also important to take stock of one’s personal career goals and what you off er a client. Some questions to ask yourself may include:

What do I want to be doing in the next few years? On what types of projects?

How have I best served my clients?

What am I proud of?

What kind of return on investment do I provide my clients for their project dollars?

In what ways could I better serve my clients?

The Big Picture for Your ClientAt this stage of the business development life cycle,

a project may only be a conceptual idea with an unde-

fi ned scope. As opportunities present themselves to have meaningful discussions with prospective or exist-ing clients, it is important to make the best use of them! Coming prepared with an understanding of the client organization’s mission, goals, and objectives is perfunc-tory. It aids discussion, in that specifi c questions can be asked about how anticipated projects fi t into the big picture of the organization. (Awareness of the offi cially stated objectives for the project should only be a start.) If speaking with a key decision maker, program manager, or project manager, the understanding gained can also help uncover that individual’s career goals, and how this project might impact them.

The most important information that can be gained from such a conversation comes from asking about the challenges that the individual is facing in his/her depart-ment and organization—and the challenges facing the project. For example:

What are the project’s drivers (purpose and need)?

Is project funding in place?

Are there adequate staffi ng resources in the client organization?

What interagency and/or internal politics may be at work?

What stakeholder groups are involved?

What are the technical challenges?

Are there other challenges?

What criteria will defi ne success for the project?

What things could a consultant do to best support the individual and their department?

How have things been going on their projects (in-cluding those on which your fi rm is working)?—Are there lessons learned?

With which of your competitors is your client work-ing? How are they performing?

Alignment of Your Company and Your ClientAfter developing an understanding of your fi rm’s and

your client’s big picture, this is the time to assess how well these align. Use of a comprehensive, objective “Go/No-Go” decision making tool by your fi rm is a good way to objectively assess this. If the client’s needs fi t what you and your team can off er, this presents a signifi cant opportunity. If not, it may be a good idea to pursue an-other project or client.

After considering what you have learned about the challenges your client is facing, what solutions can you off er? Requesting a meeting to discuss some potential ideas you may have may help identify these. The meet-

Table 1. Phases of the VE Job Plan Promoted by SAVE International® and the Business

Development Life Cycle

SAVE International® VE Job Plan Phases

Business Development Life Cycle Processes

PrestudyGetting to know the client and getting feedback

InformationLearning about the purpose, needs, challenges, and criteria for success of the project or program

Function Analysis

Preparing the proposal—organizing the document and identifying concepts to convey benefits

Creativity (Speculation)

Preparing the proposal—brainstorming innovative ideas to be conveyed that meet project performance and proposal evaluation criteria

Evaluation

Preparing the proposal—Evaluating the ideas against criteria during proposal draft reviews

DevelopmentPreparing the proposal—writing and refining the content

PresentationSubmitting the proposal and presenting at the interview

Implementation Performing as promised


ing aff ords the chance to run ideas by the client that will pique his or her interest. This is a dialogue and should not to be confused with a presentation. Listening to the client and watching his or her reactions to the ideas and discussing them further are critical. Ask what he or she thinks. It’s okay not to have all the answers at this point. Let the client know you plan to explore concepts further or do additional research and get back to him or her.

Of course, it is important not to give away too many specifi cs of your innovative solutions or approach, as these may be passed along to your competition or be in-cluded in the future RFP! Giving enough away to pique interest in how you can solve the client’s problems is the goal at this stage.

At this point, you can also help your client defi ne the scope of the program or project.

Information—The Client’s Program or Project

Project UnderstandingAs a program or project

scope becomes defi ned to a point that an RFP may soon be published, it is a good time to check back with the client to be sure you understand the client’s needs for the project, as they may now be more specifi c than in previous discussions—or may have changed.

Once the RFP is pub-lished, the client may likely have a pre-proposal meeting, where additional information is shared with project con-tenders. Unfortunately, these meetings are not terribly valuable, as the competing fi rms typically do not “show their hand” by asking specifi c questions. At this point, any questions you ask the client are typically published for all interested proposers, along with the client’s answers.

Performance Criteria

Project Success Criteria

Through discussions with the client prior to the RFP, a good understanding should have been developed as to the criteria that will defi ne the project as successful. These may also be included in the RFP.

Proposal Evaluation CriteriaUsually RFPs include proposal evaluation criteria,

even if they are vague. Just as important as presenting your team’s information in the order and format request-ed in the RFP is making sure how your team meets the criteria is refl ected throughout the proposal—especially the executive summary and/or cover letter.

Function Analysis—Applied to the Proposal

Function Identifi cation and Classifi cation

Table 2. Proposal Functions and Classifi cations

Proposal Component Function(s) Classifi cationLayout/Design Enhance Readability Design Criterion

Theme Influence Selection Basic

Convey Results Required Secondary

Project Understanding, Approach, Project Descriptions, and Resumes

Identify Drivers Secondary

Describe Scope Secondary

Identify Challenges Secondary

Describe Objectives Secondary

Offer Solutions Secondary

Convey Results Secondary

Prove Performance Secondary

Demonstrate Qualifications Secondary

Project Management Plan Describe Methods Secondary

Identify Tools Secondary

Schedule Illustrate Timing Secondary

Organizational Chart Identify Team Secondary

References and Testimonials Prove Performance Secondary

Cost Proposal Convey Value Secondary

Other Functions Decide Go/No-Go Secondary

Follow RFP Design Criterion

Address Evaluation Criteria All-the-Time

Communicate Benefits All-the-Time

Differentiate Team All-the-Time

Demonstrate Competence All-the-Time

Demonstrate Innovation All-the-Time

Win Contract Higher Order

Develop Relationship Higher Order

Grow Business Higher Order


Similar to project designs that have a defi ned set of components, proposals typically include the following components. Each has a function to perform in order to make the proposal stand out and can be classifi ed as part of function analysis.

Proposal FAST DiagramLike any set of classifi ed functions, the functions of a

proposal can be arranged in a Technical FAST Diagram.

Creativity—Where a Proposal Can Stand Out From the Crowd

Priority Functions—The Meat of a ProposalMany of the functions on the above Technical FAST di-

agram are often neglected within proposals. If the home-work in the Pre-study phase has been done thoroughly, these concepts should be easy to convey in a proposal. The most notable of these include the following.

Identify DriversDescribe ScopeIdentify ChallengesDescribe ObjectiveDescribe MethodsConvey ResultsProve Performance

Alternate Ways to Perform FunctionsAlternate ways to perform these functions are easy

to identify when arranged on a grid that includes compo-nents of a typical proposal, as shown below. The num-bers indicated in the columns indicate a logical order for presenting the concepts within each component.

Benefi ts, Features and ProofIn a VE report, a workbook for a given VE alternative

usually includes a description of the alternative (its fea-tures), the benefi ts and risks of the alternative, and an in-depth discussion that gives specifi cs of how the alterna-tive will perform relative to project performance criteria and study goals (proof).

Proposal components must do the same. When the often overlooked key functions (Identify Drivers, Describe Scope, Identify Challenges, Describe Objective, Describe Methods, Convey Results, and Prove Performance) are actually covered in a proposal, they rarely convey ben-efi ts, features, and proof. These concepts can easily be conveyed when using the structure of Table 3 above to develop proposal components.

Example Creative Ideas/AlternativesThe function, “Convey Results,” will be the focus of

this discussion. The facilitator may ask, “What are some creative ways to convey results within the various com-

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Proposal FAST Diagram Like any set of classified functions, the functions of a proposal can be arranged in a Technical FAST Diagram.

Figure 1—Proposal Technical FAST Diagram

85 of 91

Figure 1. Proposal Technical FAST diagram


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Benefits, Features and Proof In a VE report, a workbook for a given VE alternative usually includes a description of the alternative (its features), the benefits and risks of the alternative, and an in-depth discussion that gives specifics of how the alternative will perform relative to project performance criteria and study goals (proof).

Proposal components must do the same. When the often overlooked key functions (Identify Drivers, Describe Scope, Identify Challenges, Describe Objective, Describe Methods, Convey Results, and Prove Performance) are actually covered in a proposal, they rarely convey benefits, features, and proof. These concepts can easily be conveyed when using the structure of Table 3 above to develop proposal components.

Example Creative Ideas/AlternativesThe function, “Convey Results,” will be the focus of this discussion. The facilitator may ask, “What are some creative ways to convey results within the various components of a proposal that differ from proposals that focus mostly on conveying the message that we are qualified?”

Table 4—Alternative Ways to “Convey Results”

Idea # Example Function: Convey Results CR-01 In the approach, describe the benefits of the approach to each scope item in terms of how it

supports the overall theme

CR-02 In the project descriptions, describe the goals that were met; include empirical data regarding schedule, budget, and improvements; and describe how the approach benefitted the client

CR-03 In the resumes, describe the results the proposed team member will deliver

Evaluation—Comprehensive Criteria Project Performance Criteria In exactly the same way that project performance criteria should be reviewed with value engineering team members prior to their evaluation of ideas/proposed alternatives, the same should be done when a proposal team evaluates ideas for alternative ways to perform the functions of a proposal. The question should be asked, “Will this idea/proposed alternative help to convey how the proposed project team will meet expectations for project performance?”

Proposal Evaluation Criteria Just as on a value engineering study for a construction project, ideas for performing the functions of a proposal need to be judged based on how well they meet the criteria for evaluation. The stated evaluation criteria in the RFP and�the�sometimes�unstated criteria, i.e., the understanding of key issues gained during the Prestudy Phase of the VE Job Plan, must be met in the proposal.

Figure 2. Benefits, Features, and Proof

87 of 91

Figure 2. Benefi ts, features, and proof

ponents of a proposal that diff er from proposals that fo-cus mostly on conveying the message that we are quali-fi ed?”

Evaluation—Comprehensive Criteria

Project Performance CriteriaIn exactly the same way that project performance

criteria should be reviewed with value engineering team members prior to their evaluation of ideas/proposed al-ternatives, the same should be done when a proposal team evaluates ideas for alternative ways to perform the functions of a proposal. The question should be asked, “Will this idea/proposed alternative help to convey how the proposed project team will meet expectations for project performance?”

Proposal Evaluation CriteriaJust as on a value engineering study for a construc-Just as on a value engineering study for a construc-

tion project, ideas for performing the functions of a tion project, ideas for performing the functions of a proposal need to be judged based on how well they proposal need to be judged based on how well they meet the criteria for evaluation. The stated evalu-meet the criteria for evaluation. The stated evalu-ation criteria in the RFP and the sometimes un-ation criteria in the RFP and the sometimes un-stated criteria, i.e., the understanding of key stated criteria, i.e., the understanding of key issues gained during the Pre-study Phase issues gained during the Pre-study Phase of the VE Job Plan, must be met in the of the VE Job Plan, must be met in the proposal.

It is critical that any criterion stated in the RFP is refl ected in each proposal component to which

Table 3. Proposal Subjects and Components

Proposal ComponentProposal Subject(Function) Project Understanding

Approach; Scope Item/Task Project Descriptions Resumes

Identify Drivers 1. Impetus; Driver 1. Impetus; Driver 3. Education, Registration, Certifications

Describe Scope 2. Summary of Scope/Services

2. Describe Task (What)

3. Services Provided (What)

2. Services Provided During Career

Identify Challenges 3. Identify Problem 4. Issues (What do it this way?)

4. Issues Addressed 5.a. (Include in Project Experience)

Describe Objective 4. Desired Outcome 1. Task Objective 2. Desired Outcome 5.b (Include in Project Experience)

Describe Methods (Features)

3. Solution (How) 5. Solution (How) 4. Skills

Convey Results (Benefits)

5. Benefits of this Approach

6. Benefits to Client; Goals Met, Empirical Data

1. Responsibilities; Results Person Will Deliver

Prove Performance (Proof)

6. Work Product 7. Client Reference and Testimonial

5. Project Expereince5.c. Results

it is applicable. It can be stated within the body of the proposal or in “call-out” text boxes in the proposal mar-gins.

Internal Evaluation Criteria

Performance AchievabilityWhen a proposal is written with the degree of speci-

fi city and information described here, a serious “reality check” is needed to address the following questions: What promises are being made that may become part of the contract documents? Could we back all this up if faced with mediation or arbitration? Can the proposed project team achieve all of this? Has the team success-fully done this before?

If the answers are yes, then move ahead. If not, things may need to be scaled back.

The InvestmentProposals involve the commitment of a signifi -Proposals involve the commitment of a signifi -

cant expenditure of resources that could be di-cant expenditure of resources that could be di-rected elsewhere within company operations. As rected elsewhere within company operations. As

proposed alternatives are reviewed, they need proposed alternatives are reviewed, they need to be ranked based on the value gained by to be ranked based on the value gained by

devoting the time and energy needed to devoting the time and energy needed to develop and write about the concept.develop and write about the concept.

The following questions must be asked: What will it take for our team to be shortlisted for the interview or selected directly from the proposal?


Is this overkill? Understanding the competitive landscape and complexity of the project is central to answering this question. One thing is pretty certain in today’s highly competitive environment: the proposal needs to stand out, so aim high within reason.

Another consideration in evaluating ideas/alterna-tives is whether the proposal content can be used as a basis for future proposals. If it can easily be customized to meet the specifi cs for future proposals the fi rm is like-ly to pursue, the investment is often worthwhile.

Development—Where the Fingers Meet the Keyboard

CR-03—Describe the Results the Proposed Team Member Will Deliver

In the average proposal, the responsibilities are of-ten mistaken for the role, missing an opportunity to con-vey benefi ts. For example:

Responsibilities: Project Manager; Lead Fisher-ies Biologist

What can be done as an alternative to better describe a project manager’s responsibilities?

Describe the scope of the person’s responsibilities and objectives he or she will accomplish, e.g., qual-ity, cost, and schedule management.

Describe what this person is responsible for deliver-ing in support of the overall project performance cri-teria and theme of the proposal.

Describe how this person will relate to the client and project team members.

Sample Watershed Assessment ResumeEach proposal must cover the unique characteristics

of a program or project. Each section within a given pro-posal component should be customized to refl ect these.

For the purpose of this discussion, the “Responsibilities” section in a bio paragraph and/or resume for a watershed assessment will be used as an example. It is important to note that the “Responsibilities” section may be included within the body of the proposal following the organiza-tional chart or in the resume itself. The example below has been “sanitized” for client confi dentiality purposes.

The theme of the watershed assessment proposal included:

Helping _____(the client) to make an informed, de-fensible decision in selecting options for action that will move _______ (this project) and other WRIA __(#) opportunities forward to their next steps, and

Evaluating and synthesizing data to provide a scien-tifi cally sound comparison of potential habitat bene-fi ts of the ______ watershed assessment project and similar site restoration projects.

Project Manager; Lead Fisheries Biologist—Name, Credentials, Company Name

Responsibilities. Ms. ___ will be the project man-ager and lead fisheries biologist. She will work closely with _____(client) staff and stakehold-ers to understand priorities for the project. She will anticipate issues and project needs, provide proactive communication with ______ (client), and direct the project team. ______ will develop clearly stated goals and objectives for the team, and will make sure the project adheres to time-lines, budget, and scope constraints. She will sup-port the group process for evaluating the sites, resulting in a documented, participatory process and defensible outcome for the stakeholders and county, city, and state decision makers.

As project manager, _____ will integrate the con-tributions of the various team members toward a common product vision for the WRIA _(#) committee. She will work closely with ______(Chinook fisheries specialist) to synthesize the biology and life histories of Chinook salmon in estuaries, and the estuarine environment at _______(location). _______’s past work with Chinook estuarine ecology and evaluation of ______ River restoration sites will bring new insights in evalu-ating existing documentation for this and other projects.

Table 4. Alternative Ways to “Convey Results”

Idea # Example Function: Convey ResultsCR-01 In the approach, describe the benefits of

the approach to each scope item in terms of how it supports the overall theme.

CR-02 In the project descriptions, describe the goals that were met; include empirical data regarding schedule, budget, and improvements; and describe how the approach benefitted the client

CR-03 In the resumes, describe the results the proposed team member will deliver


Presentation—Proposal Submittal and Interview

SubmittalSimilar to a VE report, after writing, reviewing, and

refi ning the proposal, it is at last submitted. Whew! The main diff erence is that while VE reports have deadlines, proposal deadlines are mandatory and down-to-the-min-ute.

If the proposal does a good job of performing all of the functions listed in the scope of the Technical FAST Diagram (Figure 1), it should certainly make the shortlist. But, just as a sense of relaxation sets in, the client calls to request an interview within a few days.

InterviewThis is where all the work in developing a theme and

carrying it through the components of a proposal, using benefi ts, features, and proof, pays off ! Clients generally believe that any of the fi rms being interviewed are quali-fi ed to perform the work. The emphasis of an interview should be on continuity of the theme and benefi ts of your team’s approach to the project. Enthusiasm must ring through. At this point, the interview panel is really trying to determine what it will be like to work with your team. They want to know:

Does the proposed team tell a compelling story that applies to how it will manage the issues on this con-tract?

Does the proposed team’s approach clearly benefi t us, as the client?

Is the proposed team cohesive and organized in their presentation?

Does the proposed team have a good rapport and chemistry among one another and the interview panel?

Debrief—Knowing Where You Stood Among the Competition

Whether the pursuit is a win or loss, it is always a good idea to debrief. Through writing over 1,000 propos-als and statements of qualifi cation over two decades, the author of this paper has honed the techniques de-scribed above. By debriefi ng on proposals, the author has refi ned these techniques, based on a comparison of scoring relative to the various teams competing for projects. It’s a good idea to take a good look at the high-est scoring proposals to see the techniques being used. Knowing why your proposal won is just as important as knowing why it lost.

Implementation—Delivering on Promises

If your team has won the project or program, now is the time to set up the contract for success. Remem-ber all of the statements made in the proposal and inter-view in terms of how things will get done, the benefi ts to be realized, and the results to be delivered? Assuming a thorough “reality check” was performed during the Eval-uation Phase, the team should be able to deliver on its promises. Delivering on promises has legal ramifi cations. The author has had direct experience using a proposal during mediation while in the role of a project analyst at an expert witness fi rm. Even when a proposal is not in-cluded as part of the formal contract documents, it can be used to illustrate how a fi rm portrayed its knowledge and expertise related to the project.

If there is any sign that a team is not delivering on its promises, it must be addressed immediately among the team—preferably before the issues become painfully ap-parent to the client. Causes need to be identifi ed, then solutions and a plan of action must be developed. Usual-ly the client sees the symptoms of a problem, so a meet-ing with the client that acknowledges the problem, gets feedback, and off ers solutions can be an opportunity to continue developing a relationship with the client.

Though you may believe your team is doing a great job, maintaining a positive dialogue with the client is the only way to know for sure that he or she feels you are delivering on your promises. The use of a partnering pro-cess at the onset of the project can be a useful tool in setting the contract—and working relationships—up for success.

Conclusion

SAVE International’s VE methodology has a broad ar-ray of applications. The use of the VE Job Plan as a frame-work for the proposal development process can greatly improve the value of the proposal eff ort—and the pro-posal, itself. In today’s competitive climate, that can help perform the higher-order functions of a proposal: Win Contract, Develop Relationship, and Grow Business.

About the Author

Anna Bremmer, CVS, LEED AP, is a marketing and value analysis consultant and serves as president of Bremmer Consulting, LLC.


Uncertainty Modeling in Multiple Dimensionsfor Value Methodology

Robert B. Stewart, CVS-Life, FSAVE, PMP & Gregory Brink, CVS, PMI-RMP, CCE/A


Introduction

Traditional VM has focused on the relationship be-tween function and cost in assessing value. Today, many VM practitioners are basing value comparisons on trade-off s between outputs (i.e., performance) and inputs (i.e., cost and time) relative to the performance of functions. In both cases, these expressions of value are generally deterministic in nature and do not factor in the inherent uncertainties of performance, cost and time. In a world where uncertainty is prevalent and the ideal conditions are often only statistically the most likely to materialize, it is important to acknowledge the multiple sets of out-comes that may occur. By introducing uncertainty into facets of performance (which seeks to quantify how well a function is being performed), cost (how much a function costs), and time (how long it takes to deliver the function) within the context of the value equation, one can acknowledge the inherent uncertainty present within the dimensions of the value equation.

What Is Uncertainty?

Uncertainty is defi ned as the quality or state of be-ing uncertain. That is to say, it is a state of not knowing. Within the context of this paper, the term “uncertainty” refers to a lack of knowledge about current and future information and circumstances. Uncertainty poses a special set of problems to the management of projects as it can potentially aff ect outcomes for both the good and the bad. In the context of Value Methodology this acknowledges that uncertainty can be addressed by ex-ploring creative alternatives to maximizing positive event frequency and/or minimizing or buff ering the eff ects of negative event and assumption exposure.

What Is Risk?

It is often assumed that the word “risk” implies a negative outcome. For example, if someone said “that is

a very risky assumption” one would take it to mean that they think that my assumption is likely to be wrong and, consequently, something bad will happen as a result. The fact of the matter is that “risk” represents an uncertain outcome. Risks may have either positive or negative out-comes. A negative risk is defi ned as a “threat” while a positive risk is defi ned as an “opportunity.” Therefore, something that is properly defi ned as “risky” does not necessarily mean that it is a bad thing, only that it is an uncertain thing.

This bias toward “risks” as being bad things often causes us to overlook potential opportunities. Just as threats can result in a catastrophic disaster, opportuni-ties can result in spectacular windfalls.

Why People Are Bad at Dealing with Uncertainty and Risk

People are generally not well equipped to deal with uncertainty for a number of important reasons. These in-clude the way in which humans perceive time; the physi-ological shortcomings that all humans possess that cre-ate perceptual roadblocks; and a host of cognitive biases related to emotional and psychological phenomenon.

Firstly, humans begin life from a certain time bound perspective. To use the terminology of noted American psychologist Phillip Zimbardo, this perspective on time is known as “present hedonistic” (Zambardo, 2008). All infants begin in this time frame, and many of us end up staying there. This time frame predisposes us to consider things from the viewpoint of how decisions will aff ect us in the moment or in the short term. People today, and especially children, are generally gravitating toward a present hedonistic perspective due to the ever present nature of technology and its ability to provide us with instant gratifi cation and a sense of control (i.e., video games, hundreds of cable television channels, internet browsing, smart phones, text messaging, e-mail, etc.). This has very important implications for us when consid-ering the role of uncertainty in our decision making be-cause it diminishes our awareness while increasing our vulnerability to future uncertainties.


Secondly, everyone essentially possesses the same physiology, which is fraught with the numerous short-comings of our six senses. It is important to remember that, to a large degree, the brain functions by interpret-ing the world around us through the senses. Perhaps the most important of these is vision. Most people de-pend greatly upon their eyes every single day. With re-spect to our ability to perceive the future, most optical illusions are caused by a neural lag. When light hits the retina, about one-tenth of a second goes by before the brain translates the signal into a visual perception of the world. Scientists have known of the lag, yet they have debated over how humans compensate, with some pro-posing that our motor system somehow modifi es our movements to off set the delay.

The human visual system has evolved to compen-sate for neural delays, generating images of what will occur one-tenth of a second into the future. This foresight enables humans to react to events in the present. This al-lows humans to perform refl exive acts like catch-ing a fl y ball and to maneuver smoothly through a crowd. Illusions occur when our brains attempt to perceive the future, and those perceptions don’t match reality. For example, one il-lusion called the Hering illusion (Figure 1) looks like bike spokes around a central point, with vertical lines on either side of this central, so-called vanishing point. The illusion tricks us into thinking we are moving forward, and thus, switches on our future-seeing abilities. Since we aren’t actually moving and the fi gure is static, we misperceive the straight red lines as curved ones (Bryner, 2008).

Finally, people are subject to a bewildering number of cognitive biases that inhibit our ability to deal with un-certainty. These include, but are not limited to the fol-lowing:

Anchoring Heuristic – The tendency for people to bias their decisions to the fi rst piece of evidence encoun-tered or their initial preconceptions.

Availability Heuristic – The tendency for people to bi-ased toward images that are more vivid and readily available to the mind’s eye.

Representativeness Heuristic – The tendency for peo-ple to associate outcomes from the events that cre-ated them (i.e., a random lottery should produce a random sequence of numbers).

Framing Eff ect – The tendency for people’s decisions to be biased based on how a prospect is articulated within the domain of losses or gains.

Overconfi dence Eff ect – The tendency for people to overestimate their ability to control or manage events in which they are involved.

Motivational Bias – The tendency for people to in-fl uence decisions for personal gain whether it is to avoid embarrassment, appear knowledgeable or ad-vance one’s agenda.

Optimism Bias – The tendency for people to overes-timate good outcomes and underestimate the prob-ability of bad outcomes (Cretu, 2011).

Why Deterministic Assumptions Can Be Misleading Value Methodology traditionally has focused on im-

proving value through the reduction of cost in deliver-ing functions. Typically, cost savings are expressed in deterministic terms, meaning, it is assumed that the sav-ings will be realized and there is generally no real elabo-ration on the true likelihood of the stated cost benefi ts being realized. Generally speaking, most VM studies oc-cur within a relatively short time frame and the alterna-tive concepts developed will require additional technical analysis in order to validate the potential benefi ts. Fur-ther, seldom are the various costs associated with full implementation completely considered (i.e., the cost for redesign, logistics impacts, etc.) The result is that there is generally a great deal of uncertainty with respect to the true cost benefi ts that will actually be realized. The re-sult, oftentimes, is that promising concepts are rejected or ignored due to these uncertainties.

The potential impact to time and schedules is also quantifi able in terms similar to cost. The schedule sav-ings of a construction related alternative can be calcu-lated using modern scheduling techniques and stated de-terministically. Again, however, there are the problems facing a decision maker with respect to the certainty with which the suggested changes can be made within the predicted time frames, especially when untested ap-

UNCERTAINTY MODELING IN MULTIPLE DIMENSIONS FOR VALUE METHODOLOGY (STEWART & BRINK)PAGE 3

the Hering illusion (Figure 1) looks like bike spokes around a central point, with vertical lines on either side of this central, so-called vanishing point. The illusion tricks us into thinking we are moving forward, and thus, switches on our future-seeing abilities. Since we aren't actually moving and the figure is static, we misperceive the straight red lines as curved ones.2

Figure 1 - Hering illusion

Finally, people are subject to a bewildering number of cognitive biases that inhibit our ability to deal with uncertainty. These include, but are not limited to the following:

� Anchoring Heuristic – The tendency for people to bias their decisions to the first piece of evidence encountered or their initial preconceptions.

� Availability Heuristic – The tendency for people to biased toward images that are more vivid and readily available to the mind’s eye.

� Representativeness Heuristic – The tendency for people to associate outcomes from the events that created them (i.e., a random lottery should produce a random sequence of numbers).

2 Bryner, Jeanna, “Key to all Optical Illusions Discovered,” Live Science, June 2, 2008

Figure 1. Herring illusion


proaches are recommended. Change, in and of itself, is often more time consuming then we think it will be.

Finally, there is usually some degree of uncertainty when considering how an alternative concept will per-form in the present or in the future, especially if it is in-novative or untested. For example, we cannot be certain how a change to the design of a highway interchange will aff ect traffi c operations until has been constructed and has been operational for a suffi cient time to mea-sure traffi c characteristics. Similarly, we cannot know what traffi c volumes will be 10 or 20 years into the future. Nonetheless, diff erent interchange concepts will off er diff erent performance characteristics at diff erent points in the future depending upon a set of conditions.

In summary, the reason why most alternative con-cepts are rejected is due to uncertainty and risk associ-ated with assumptions that are ultimately driving the de-terministic outcomes. We simply cannot know with 100% certainty what will happen. Moreover, we are generally less confi dent when it comes to new ideas and concepts that are untested or are relatively novel in nature.

Incorporating Risk into Equations for Value

In making value comparisons, four essential elements must be factored. These include cost, performance, time and risk. The Value Metrics approach to value measure-ment relies upon a fundamental mathematical algorithm for modeling value (Stewart, 2010).

4 Stewart, Robert, “Value Optimization for Project and Performance Management,” John Wiley & Sons, Hoboken, 2010 There are two types of algorithms that can be considered. These algorithms vary depending on whether a “dynamic” or a “discrete” model best refl ects actual conditions. The dynamic model considers value as the interrelationship between inputs and outputs (or, al-ternatively, the costs and benefi ts) of a system. This type of model is non-linear in nature and considers trade-off s between cost, time, and performance while considering how risk infl uences each of these elements. The out-comes realized are dependent upon the resources input into the system. This is why it can be said that it is a “dy-namic” model of value. The algorithm for this model can be stated as follows:

Where V = Value, V = Value, V f = Function, f = Function, f P = Performance, C = Cost, t = Time, α = Uncertainty, and N = the number of developed value alternatives.

The discrete model considers value as the sum of the elements of value of a system. This type of model is linear and considers cost, time, performance and risk indepen-dently. The outcomes realized are dependent on the net aggregation of the individual components of the system. This is why it can be said that it is a “discrete” model of value. The algorithm for this model can be stated as fol-lows:

Where V = Value, V = Value, V f = Function, f = Function, f P = Performance, C = Cost, t = Time, W = weight, α = Uncertainty, and N = the number of developed value alternatives. The dynamic

and discrete models have diff erent applications and con-sider the interrelationship of cost, time, performance and risk diff erently. Generally speaking, the dynamic model is generally a more accurate representation of value in its purest form. It acknowledges the interplay between inputs and outputs and allows stakeholders to evaluate alternatives based on trade-off s between them. The dy-namic model is therefore most appropriate in the follow-ing applications:

The evaluation of projects located in the public do-main.

The evaluation of potential solutions for complex problems, especially those involving subjective ex-pressions of performance.

The evaluation of new technologies in product devel-opment.

The evaluation and development of new projects or processes.

The comparison of mutually exclusive investment al-ternatives.

In contrast, there are certain applications where a discrete model is more representative of actual condi-tions:

The evaluation of products that have reached a tech-nological plateau and have essentially been “com-moditized.” Such products essentially have little dif-ferentiation in terms of outputs (i.e., performance) and off er a very narrow range of variability. Typically, under these conditions, performance is generally prescriptive (i.e., binary requirements) and cost and/or time are the predominate elements.

The evaluation of alternatives where the decision criteria has been dictated or pre-conceived. It must be acknowledged that such situations are com-


performance characteristics at different points in the future depending upon a set of conditions.

In summary, the reason why most alternative concepts are rejected is due to uncertainty and risk associated with assumptions that are ultimately driving the deterministic outcomes. We simply cannot know with 100% certainty what will happen. Moreover, we are generally less confident when it comes to new ideas and concepts that are untested or are relatively novel in nature.


In making value comparisons, four essential elements must be factored. These include cost, performance, time and risk. The Value Metrics approach to value measurement relies upon a fundamental mathematical algorithm for modeling value.4

4 Stewart, Robert, “Value Optimization for Project and Performance Management,” John Wiley & Sons, Hoboken, 2010

There are two types of algorithms that can be considered. These algorithms vary depending on whether a “dynamic” or a “discrete” model best reflects actual conditions.

The dynamic model considers value as the interrelationship between inputs and outputs (or, alternatively, the costs and benefits) of a system. This type of model is non-linear in nature and considers tradeoffs between cost, time, and performance while considering how risk influences each of these elements. The outcomes realized are dependent upon the resources input into the system. This is why it can be said that it is a “dynamic” model of value. The algorithm for this model can be stated as follows:

Where V = Value, f = Function, P = Performance, C = Cost, t = Time, � = Uncertainty, and N = the number of developed value alternatives.

The discrete model considers value as the sum of the elements of value of a system. This type of model is linear and considers cost, time, performance and risk independently. The outcomesrealized are dependent on the net aggregation of the individual components of the system. This is why it can be said that it is a “discrete” model of value. The algorithm for this model can be stated as follows:


performance characteristics at different points in the future depending upon a set of conditions.

In summary, the reason why most alternative concepts are rejected is due to uncertainty and risk associated with assumptions that are ultimately driving the deterministic outcomes. We simply cannot know with 100% certainty what will happen. Moreover, we are generally less confident when it comes to new ideas and concepts that are untested or are relatively novel in nature.


In making value comparisons, four essential elements must be factored. These include cost, performance, time and risk. The Value Metrics approach to value measurement relies upon a fundamental mathematical algorithm for modeling value.4

4 Stewart, Robert, “Value Optimization for Project and Performance Management,” John Wiley & Sons, Hoboken, 2010

There are two types of algorithms that can be considered. These algorithms vary depending on whether a “dynamic” or a “discrete” model best reflects actual conditions.

The dynamic model considers value as the interrelationship between inputs and outputs (or, alternatively, the costs and benefits) of a system. This type of model is non-linear in nature and considers tradeoffs between cost, time, and performance while considering how risk influences each of these elements. The outcomes realized are dependent upon the resources input into the system. This is why it can be said that it is a “dynamic” model of value. The algorithm for this model can be stated as follows:

Where V = Value, f = Function, P = Performance, C = Cost, t = Time, � = Uncertainty, and N = the number of developed value alternatives.

The discrete model considers value as the sum of the elements of value of a system. This type of model is linear and considers cost, time, performance and risk independently. The outcomesrealized are dependent on the net aggregation of the individual components of the system. This is why it can be said that it is a “discrete” model of value. The algorithm for this model can be stated as follows:


monplace; however, they are generally a result of a fl awed understanding of priorities. These situations usually occur as a result of decision criteria being im-posed artifi cially and/or by entities external to a deci-sion process.

The evaluation of a network system with a defi ned pathway. Examples of a network system include pipeline infrastructure networks, computer system networks, traffi c system origin-destination pairing for route management, or any other system with a defi ned and limited number of pathway alternatives.

Using a mathematical framework such as the ones presented above for the assessment of value, risk can be factored into any or all of the quantities for cost, time and performance. This allows for a more robust consid-eration of value such that the inherent variability of the system can be acknowledged and factored in to making value minded decisions.

Considering Cost and Schedule Risk

The components of cost and schedule are major el-ements of value that are often key to making decisions of allocation and ultimately determining which products, processes, or projects move beyond the planning phases. The focus on cost and time to delivery also tends to be increasingly important in situations in which capital con-straints limit the domain of real options or in situations in which a solution must be rolled out relatively quickly. The modeling of cost and schedule risk helps to better inform decision makers about the nature and uncertain-ties associated with cost and duration profi les and can be performed in two distinct manners. The two method-ologies of quantitative risk assessment are simple range estimation or complex quantitative modeling; both of which provide information on the exposure of risk, or uncertainty, in the system.

Both types of risk assessment are quantitative in na-ture and seek to answer the questions of “How long will it take?” and “How much will it cost?”. While these ques-tions seem relatively easy in a general sense to answer, it is often much more diffi cult to answer with any real sense of precision. That is why it is important to depart from deterministic modeling that arrives at simple conclusions and a point estimate answer and move towards answer-ing these two questions in more of a range bound ap-proach. We can acknowledge that the world is dynamic and is constantly changing around us, so why would we settle on a single point estimate? The modeling of cost and schedule risk allows us to explore the range of pos-sibilities that may occur in terms of the dollars and time associated. The simple approach, which is quantitative range estimation, will be explored fi rst. Then the com-

plex quantitative modeling approach will be explored. Note that both of these approaches will be covered in the context of cost and schedule modeling through the use of Monte Carlo simulation, which is an algorithm that allows us to simulate the outcomes.

Simple Range Risk Assessment

In range estimation the act of risk assessment in-volves developing simple distributions that are relatively representative of the situations that are trying to be mod-eled. That is, we are trying to understand the variation in the system. When moving to understand the actual range of something there is a need for data to support the as-sumptions being made. Often, when modeling cost and schedule risk the ranges are elicited from subject matter experts or those individuals with intimate knowledge of the system being analyzed. The other approach is to use mathematical distributions based on available statistical data to develop a range of probable outcomes. For the purposes of this paper and speaking in relation to Val-ue Methodology, we will speak more to the use of sub-ject matter experts, just as would be the case in a value study.

When developing a simple range estimate, a trian-gular distribution can be employed to approximate the system. The ranges are established by identifying what the best case, worst case, and most likely situations are. For risks that are threats the best case is the low end of the range, the worst case is the high end of the range, and the most likely is the median of the range. For risks that are opportunities the best case is the high end of the range, the worst case is the low end of the range, and again, the most likely scenario is the median of the range. From these data points a simple triangular distribution can be constructed in order to model the range of prob-able outcomes in a simplifi ed manner.

Suppose that a cost threat of environmental mitiga-tion on a highway interchange project has been identi-fi ed that has a best case scenario of costing $500,000 if it is realized, a worst case scenario of $3,000,000 if it is realized, and a most likely value of $1,800,000. From this data we could construct a simple range estimate to un-derstand what the probabilistic outcomes could be. If we run this simple triangular distribution in a Monte Carlo simulation by assuming that the low end of the range has a confi dence interval of 10% (i.e., the risk has only a 10% chance of being equal to or less than $500,000) and the high end of the range has a confi dence interval of 90% (i.e., the risk has a 90% chance of being equal to or less than $3,000,000) and the median or 50% confi dence inter-val (i.e., it is equally likely that the value could be higher


or lower than the median), we would fi nd the following situation depicted in the Figure 2 (next page, top).

You can see how the model is attempting to assess the risk by modeling the distribution approximately ac-cording to the parameters input. The minimum exposure in this case is $316,655.70 while the maximum exposure is $2,987,675.40, while the median, or most likely, value is $1,719,589.34. Instead of saying “This risk could cost us $1.8 million” the range tells you that it is most likely to be roughly $1.72 million, but in reality it could be as low as $316,655 all the way up to $2,987,675. It could be bet-ter or worse and there is no guarantee that the risk will be exactly $1.8 million. That is exactly the point of range estimating. It is to acknowledge that there is a range of outcomes that may transpire if and when the risk is real-ized. Just as this example illustrates the cost impacts of a risk, the schedule side of the equation can be addressed in the same manner by assessing the low, median and high ends of duration parameters.

Complex Quantitative Risk Assessment

Moving into complex quantitative risk assessment involves taking the analysis of the nature of the risk much further. In complex quantitative analysis several more layers of the nature of the risk must be captured. It must be understood how likely the cost or schedule risk is to materialize. It must be noted if there is a situa-tion that the cost or schedule risk is dependent upon and how it aff ects other activities in the system both in terms of cost and time. Complex quantitative risk assessment looks to provide an assessment of the expected value ex-posure, and in order to arrive at what the anticipated or expected impacts of a risk event are, each of these issues must be explored. The idea of being able to understand what the expected range of impacts truly is involves go-

ing through a series of steps to more thoroughly defi ne the system in terms each of these domains.

Answering the questions relating the nature of the risk gets into exploring issues of correlations and de-pendencies. Risks may be dependent on other risks or events transpiring. Risks may also have a realistic nature in which they correlate to other events in a defi ned re-lationship. In risk modeling, dependencies are defi ned as the reliance of a risk event on another event. It is an if-then logic scenario. For example, if we run into con-taminated soils, then we will have to clean up the mess and we may have another risk associated that if we have to do environmental mitigation, then we must bring a clean-up expert in to continuously monitor the site for an indefi nite period of time. In our example let’s say that we don’t know of any environmental monitoring companies and none are available. This could create a schedule de-lay on the project until we can locate another contractor to continue work progression. The risk of schedule delay is now dependent upon having to perform environmen-tal clean-up. Let’s say that our risk event is triggered and we have to clean up contaminated soils. The very nature of the dependency here is not whether or not the con-taminated soils exist, but the relationship of if we have to clean it up, we end up with a schedule delay. There is an independent risk of schedule delay that exists as a result of having to locate an environmental contractor if we don’t already have one on-call or as a part of our con-tracting team. (Note that in this case, a dual mitigation could be having the environmental monitoring company locate possible contaminated areas that we could avoid in order to not realize either the cost or schedule risk!)

There are also correlations amongst risks. In cost and schedule risk assessment correlations tell us about the na-ture of relationships and how they interact. For example, cost and time are often correlated, or have a relationship


mathematical distributions based on available statistical data to develop a range of probable outcomes. For the purposes of this paper and speaking in relation to Value Methodology, we will speak more to the use of subject matter experts, just as would be the case in a value study.

When developing a simple range estimate, a triangular distribution can be employed toapproximate the system. The ranges are established by identifying what the best case, worst case, and most likely situations are. For risks that are threats the best case is the low end of the range, the worst case is the high end of the range, and the most likely is the median of the range. For risks that are opportunities the best case is the high end of the range, the worst case is the low end of the range, and again, the most likely scenario is the median of the range. From these data points a simple triangular distribution can be constructed in order to model the range of probable outcomes in a simplified manner.

Suppose that a cost threat of environmental mitigation on a highway interchange project has been identified that has a best case scenario of costing $500,000 if it is realized, a worst case scenario of $3,000,000 if it is realized, and a most likely value of $1,800,000. From this data we could construct a simple range estimate to understand what the probabilistic outcomes could be. If we run this simple triangular distribution in a Monte Carlo simulation by assuming that the low end of the range has a confidence interval of 10% (i.e., the risk has only a 10% chance of being equal to or less than $500,000) and the high end of the range has a confidence interval of 90% (i.e., the risk has a 90% chance of being equal to or less than $3,000,000) and the median or 50% confidence interval (i.e., it is equally likely that the value could be higher or lower than the median), we would find the following situation depicted in the Figure 2 below.

Figure 2 - Example range estimate

You can see how the model is attempting to assess the risk by modeling the distribution approximately according to the parameters input. The minimum exposure in this case is

Figure 2. Example range estimate


to one another. If we were to have to clean up the mess of the contaminated soils and perform environmental mitigation, we may be able to do it quite quickly but it will be expensive. This is a negative correlation of cost and time. In other words, when cost is high, the duration is low and vice versa. The point of all of this is that in com-plex quantitative risk modeling it is important to capture the nature of the risk by explicitly defi ning the dependen-cies and correlations of the actual event in order to make the modeling of the event as realistic as possible. Once it is understood how cost and time risks are related to the world around us in terms of dependencies and correla-tions, we need to understand how likely it is that a risk will transpire. Answering the question of how likely a risk is to materialize is basically asking a very discrete ques-tion pertaining to the probability, or frequency, of an event occurrence. What is meant by discrete is that the event either happens or it does not. It can be likened to a light switch either being on or off . Understanding the probability of a risk event is not just a relative measure of frequency. It is a measure of the frequency in which one could anticipate a risk event to materialize. If you were to say that the same environmental mitigation risk explored above has a likelihood of occurring of 35%, you are also saying that there is a 65% likelihood that it will not oc-cur. What this illustrates is that the system is not continu-ous. In other words it happens 35% of the time and 65% of the time it does not. This is important to understand, because it helps in determining what the expected value impacts of a cost or schedule risk may be.

When assessing the expected value impact of a risk it is a matter of taking the simple range estimate and ap-plying probabilistic assumptions of frequency to it. In de-terministic form, an expected value impact calculation is as follows:

Where a is equal to the low end of the range, b is equal to the median value, and c is equivalent to the high

end of the range.Plugging in the numbers from our environmental

mitigation example above with our sample 35% probabil-ity, we arrive at a deterministic estimate of the expected value of exposure of $612,500. However, if we run the Monte Carlo simulation for this situation, we again see a departure from a simple deterministic answer to gain-ing a better understanding of the system. It is discovered that the expected value impact has a minimum of $0 (because the risk may not even happen!), a maximum of $2,985,823, and a most likely outcome of $581,020. This information tells us much more about the nature of the

risk and how to plan for it versus the simple determinis-tic approach that does not even acknowledge that the risk may not even happen. It is the “one sided” approach that sometimes biases decision makers from realizing they can pursue mitigation strategies to minimize risk exposure to 0 and leads them to plan for an impact of $612,500. How foolish does that seem if you could simply avoid the situation rather than plan for paying for it?

That is the point of moving from deterministic re-sults to range bound results and the modeling of cost and schedule risk. It opens up our thinking to exploring options for managing cost and schedule uncertainties, which provides yet another area wherein Value Meth-odology can improve value. Using cost and schedule risk assessment as a means of defi ning the cost and time pa-rameters of the value equation allows us to better model the reality around us and to open up our thinking to un-derstand the range of outcomes of cost and time that could transpire. This also means that we can measure the eff ects of possible VM alternatives and determine which of them off ers the best cost and time relationship rela-tive to the performance of the system under the infl u-ences of uncertainty.

Let us explore these concepts further using an ex-ample. Assume that a VM study has developed three al-ternative interchange concepts to a baseline design con-cept. The cost and schedule of each has been estimated according to Table 1 above.

From this table, we can see that VM Strategies 2 and 3 off er similar cost and schedule advantages over the baseline concept and VM Strategy 1. Note that the ratings columns for cost and schedule represent the normalized values expressed as a ratio measurement. Let us assume now that simple range risk assessment is performed for each of these four options for cost and schedule. Look-ing at Figures 3 and 4, when we consider the level of risk inherent in each of the options, the advantages posed by VM Strategy 3 begins to lose a bit of its luster. Clearly, judging by the much wider distribution of VM Strategy 3, there is a lot less confi dence in the deterministic val-ues for both cost and schedule as compared to the other


be having the environmental monitoring company locate possible contaminated areas that we could avoid in order to not realize either the cost or schedule risk!).

There are also correlations amongst risks. In cost and schedule risk assessment correlations tell us about the nature of relationships and how they interact. For example, cost and time are often correlated, or have a relationship to one another. If we were to have to clean up the mess of the contaminated soils and perform environmental mitigation, we may be able to do it quite quickly but it will be expensive. This is a negative correlation of cost and time. In other words, when cost is high, the duration is low and vice versa. The point of all of this is that in complex quantitative risk modeling it is important to capture the nature of the risk by explicitly defining the dependencies and correlations of the actual event in order to make the modeling of the event as realistic as possible.

Once it is understood how cost and time risks are related to the world around us in terms of dependencies and correlations, we need to understand how likely it is that a risk will transpire. Answering the question of how likely a risk is to materialize is basically asking a very discrete question pertaining to the probability, or frequency, of an event occurrence. What is meant by discrete is that the event either happens or it does not. It can be likened to a light switch either being on or off. Understanding the probability of a risk event is not just a relative measure of frequency. It is a measure of the frequency in which one could anticipate a risk event to materialize. If you were to say that the same environmental mitigation risk explored above has a likelihood of occurring of 35%, you are also saying that there is a 65% likelihood that it will not occur. What this illustrates is that the system is not continuous. In other words it happens 35% of the time and 65% of the time it does not. This is important to understand, because it helps in determining what the expected value impacts of a cost or schedule risk may be.

When assessing the expected value impact of a risk it is a matter of taking the simple range estimate and applying probabilistic assumptions of frequency to it. In deterministic form, an expected value impact calculation is as follows:

Where a is equal to the low end of the range, b is equal to the median value, and c is equivalent to the high end of the range.

Plugging in the numbers from our environmental mitigation example above with our sample 35% probability, we arrive at a deterministic estimate of the expected value of exposure of $612,500. However, if we run the Monte Carlo simulation for this situation, we again see a departure from a simple deterministic answer to gaining a better understanding of the system. It is discovered that the expected value impact has a minimum of $0 (because the risk may not

Table 1. Deterministic Values for Cost and Schedule

Alternatives Costs RatingSchedule (Months) Rating

Baseline $30,300,000 0.1345 24 0.1714

Strategy 1 $29,128,000 0.1293 18 0.1286

Strategy 2 $26,495,000 0.1176 14 0.1000

Strategy 3 $26,693,000 0.1185 14 0.1000

Total $112,616,000 70


options. In fact, overall, VM Strategy 2 appears to be a much safer bet. This example demonstrates how consid-ering risk can provide much greater insight in considering value.

Considering Performance Risk

Assessing performance risk is not quite as clear cut as it is for cost and schedule and poses a number of unique challenges. Firstly, performance encompasses a nearly infi nite set of potential manifestations and cannot be so easily narrowed down to cost and time, which are under-stood, accepted and measurable quantities. Secondly, performance can be expressed as either a quantitative or qualitative using a variety of potential measurements.

The recommended method for measuring perfor-mance, and subsequently value, relies upon the frame-work of the Analytic Hierarchy and Analytic Network Processes (AHP and ANP) developed by Dr. Thomas Saaty (Saaty, 2008; Saaty & Peniwati, 2008). The process essentially allows a variety of diverse comparisons. The process essentially consists of fi ve basic steps: 1) Identify the decision goal, alternatives and evaluation criteria, 2) establish the priorities of the selection criteria (i.e., per-formance), 3) rate the performance of the alternatives, 4) synthesize the judgments to yield the overall priorities (scores), 5) verify the consistency of the judgments.

With respect to modeling the uncertainty of per-formance using this method, one can consider how it aff ects performance priorities (step 2 above) as well as the performance ratings of individual alternatives (step 3 above).

Performance prioritization, if it is to refl ect the minds of the decision makers, should obviously actively engage them in the prioritization process. This is the best way to ensure that the priorities are aligned with the actual deci-sion makers (i.e., those that are in a position to approve or reject the alternatives emanating from a VM study). Assuming they have been involved in the process, it is not uncommon during the elicitation process to see sig-nifi cant diff erences in the priorities of the individual deci-sion makers that are involved. Oftentimes, decision mak-ers have diff erent agendas, represent diff erent groups of stakeholders that have divergent interests, and may even disagree on fundamental aspects of a project. This is of-tentimes a reality, especially within the context of public projects, and it must be acknowledged. Simply forcing consensus and glossing over dissenting views on what is important is not refl ective of the actual conditions and risks compromising the validity of the analysis.

One way to handle the uncertainties related to pri-orities related to performance is to evaluate the range of the intensities of priorities of the participants. In the fol-

lowing example, special AHP software known as Decision Lens was utilized to perform the pair-wise comparisons. Participants were given hand held remote control units to enter in their individual preferences and priorities. Figure 5 below shows a screen shot from the software where participants were asked to express the intensity of their preference between mainline and local opera-tional performance for a highway project relative to the project’s purpose and need. As can be seen in this fi gure, the majority of participants have indicated that mainline operations are more important than local operations, and by a signifi cant degree.

The intensities range from 1 (which indicates both at-tributes are of equal importance) to an 8, whereby main-line operations is extremely more important than local operations. The median value is 4.1 in favor of mainline operations. The use of the data series also allows us to derive a representative distribution that can then be used to consider performance priorities in a probabilistic manner.

Using this data, we can test the relative level of con-fi dence displayed in considering performance priorities.


each of the options, the advantages posed by VM Strategy 3 begins to lose a bit of its luster. Clearly, judging by the much wider distribution of VM Strategy 3, there is a lot less confidence in the deterministic values for both cost and schedule as compared to the other options. In fact, overall, VM Strategy 2 appears to be a much safer bet. This example demonstrates how considering risk can provide much greater insight in considering value.

Figure 3- Probabilistic cost distributions for four options

Figure 4 – Probabilistic schedule distributions for four options


Assessing performance risk is not quite as clear cut as it is for cost and schedule and poses a number of unique challenges. Firstly, performance encompasses a nearly infinite set of

Figure 3. Probabilistic cost distribution for four options


each of the options, the advantages posed by VM Strategy 3 begins to lose a bit of its luster. Clearly, judging by the much wider distribution of VM Strategy 3, there is a lot less confidence in the deterministic values for both cost and schedule as compared to the other options. In fact, overall, VM Strategy 2 appears to be a much safer bet. This example demonstrates how considering risk can provide much greater insight in considering value.

Figure 3- Probabilistic cost distributions for four options

Figure 4 – Probabilistic schedule distributions for four options


Assessing performance risk is not quite as clear cut as it is for cost and schedule and poses a number of unique challenges. Firstly, performance encompasses a nearly infinite set of

Figure 4. Probabilistic schedule distribution for four options


This information can be helpful in evalu-ating the group’s assumptions about the relative importance of key performance criteria. Furthermore, the Decision Lens software allows the priorities of the eval-uation criteria to be adjusted in order to test the sensitivity of the judgments as illustrated in Figure 6. This provides pow-erful feedback on how future changes in priorities could aff ect the outcome of decisions.

Another way to consider uncertainty relative to performance is by considering performance as a range of potential val-ues rather than as a deterministic value. For example, assume we are consider-ing a number of interchange alternatives for a highway project, each of which has diff erent potential impacts to traffi c op-erations. Using risk modeling software such as Oracle’s Crystal Ball, one can derive probabilistic distributions of per-formance by identifying the minimum, median and maximum anticipated values for the performance attributes. Similarly, this could be performed for any or all of the performance attributes.

Table 2 (next page) shows the deter-ministic performance scores for four po-tential interchange options (the baseline concept and three potential VM strate-gies). It is important to note that based on the weighted performance scores, the four options have nearly identical performance scores ranging from 5.04 to 5.22 on a scale of 1 (minimum) to 10 (maximum). If were judging these four options strictly on performance, and on a deterministic basis, none of them stand out from the others as being the “best” choice. One could say that Strategy 1 has a slight performance advantage, but not convincingly so.

If we evaluate these same options from a probabilistic standpoint and con-sider the range of potential performance values for those attributes that we have at least a small degree of uncertainty, the analysis paints a remarkably diff erent picture. The example provided in Figure 7 (next page, center) illus-trates the probabilistic performance distributions for the same four options. Notice that from a performance perspective, the Baseline concept demonstrates a much

narrower range (denoting less uncertainty) and is shifted farther to the right. Looking at the overlap of the distri-butions of the three VM strategies, one can clearly see that the baseline concept has a striking advantage con-sidering risk as a large proportion of the distributions for the VM strategies lay to the left of the lower tail of the


performance for a highway project relative to the project’s purpose and need. As can be seen in this figure, the majority of participants have indicated that mainline operations are more important than local operations, and by a significant degree.

Figure 5 - Distribution of individual intensities for a pair-wise comparison using Decision Lens

The intensities range from 1 (which indicates both attributes are of equal importance) to an 8, whereby mainline operations is extremely more important than local operations. The median value is 4.1 in favor of mainline operations. The use of the data series also allows us to derive a representative distribution that can then be used to consider performance priorities in a probabilistic manner.

Using this data, we can test the relative level of confidence displayed in considering performance priorities. This information can be helpful in evaluating the group’s assumptions about the relative importance of key performance criteria. Furthermore, the Decision Lens software allows the priorities of the evaluation criteria to be adjusted in order to test the sensitivity of the judgments as illustrated in Figure 6. This provides powerful feedback on how future changes in priorities could affect the outcome of decisions.

Another way to consider uncertainty relative to performance is by considering performance as a range of potential values rather than as a deterministic value. For example, assume we are considering a number of interchange alternatives for a highway project, each of which has different potential impacts to traffic operations. Using risk modeling software such as Oracle’s

Figure 5. Distribution of individual intensities for a pair-wise comparison using Decision Lens


Crystal Ball, one can derive probabilistic distributions of performance by identifying the minimum, median and maximum anticipated values for the performance attributes. Similarly, this could be performed for any or all of the performance attributes.

Figure 6 - Sensitivity analysis allows priorities to be evaluated relative to uncertainty

Table 2 shows the deterministic performance scores for four potential interchange options (the baseline concept and three potential VM strategies). It is important to note that based on the weighted performance scores, the four options have nearly identical performance scores ranging from 5.04 to 5.22 on a scale of 1 (minimum) to 10 (maximum). If were judging these four options strictly on performance, and on a deterministic basis, none of them stand out from the others as being the “best” choice. One could say that Strategy 1 has a slight performance advantage, but not convincingly so.

Baseline VM Strategy 1 VM Strategy 2 VM Strategy 3

Nordahl Rd. - Traffic Ops. 0.841452 0.841452 0.841452 0.841452Pedestrian Circulation 0.461122 0.461122 0.461122 0.461122

Bicycle Circulation 0.520668 0.520668 0.520668 0.520668Nordahl Rd. - Geometry 0.833331 0.833331 0.833331 0.833331

Visual Impacts 0.603952 0.603952 0.603952 0.671058Traffic Impacts to Nordahl Rd. 0.495538 0.555603 0.300326 0.300326

Figure 6. Sensitivity analysis allows priorities to be evaluated relative to uncertainty.


baseline concept’s distribution. In hindsight, this makes good sense as the Baseline concept has been designed to a much higher level than the VM strategies and, there-fore, demonstrates an appropriately greater degree of certainty in its anticipated performance. Further, VM Strategies 2 and 3 pose the highest risk of poor perfor-mance judging by their relatively broad distributions. Clearly, given this information, a prudent decision maker would opt to stick with Baseline concept if the judgment were based solely on performance.

Tying It All Together as an Expression of Probabilistic Value

Assuming we have considered the eff ect of uncer-tainty on one or more of the elements of cost, time and performance, the next step is to calculate the value indi-ces using the probabilistic values previously derived for them. In this example, the dynamic model for value was utilized. Building on the data from the previous models, we can now express the variability in the value indices as represented in Figure 8 (below left).

This comparison shows that Strategy 2 completely dominates the Baseline concept form a total value per-spective, even when considering the “worst” case condi-tions for Strategy 2 and the “best” case conditions for the Baseline Concept. Further, it is signifi cantly better than Strategy 1 and moderately better than Strategy 3. Therefore, based on this analysis, decision makers can proceed with greater confi dence that Strategy 2 off ers the best value when considering cost, time, performance and risk.

Conclusions

Uncertainty and risk must be given due consideration if we are truly interested in improving value. As demon-strated in this paper, there are a number of probabilistic

Table 2. Median Performance Scores

Baseline VM Strategy 1 VM Strategy 2 VM Strategy 3Nordahl Rd. - Traffic Ops. 0.841452 0.841452 .0841452 .0841452

Pedestrian Circulation 0.461122 0.461122 0.461122 0.461122

Bicycle Circulation 0.520668 0.520668 0.520668 0.520668

Nordahl Rd. - Geometry 0.833331 0.833331 0.833331 0.833331

Visual Impacts 0.603952 0.603952 0.603952 0.671058

Traffic Impacts to Nordahl Rd. 0.495538 0.555603 0.300326 0.300326

Traffic Impacts to SR-78 0.465260 0.474755 0.569706 0.465260

Temp. Environmental Impacts 0.122669 0.122669 0.122669 0.143460

Maintainability 0.802554 0.802554 0.802554 0.802554

Total Performance Scores 5.15 5.22 5.06 5.04


Traffic Impacts to SR-78 0.465260 0.474755 0.569706 0.465260Temp. Environmental Impacts 0.122669 0.122669 0.122669 0.143460

Maintainability 0.802554 0.802554 0.802554 0.802554TOTAL PERFORMANCE SCORES 5.15 5.22 5.06 5.04

Table 2 - Median performance scores

If we evaluate these same options from a probabilistic standpoint and consider the range of potential performance values for those attributes that we have at least a small degree of uncertainty, the analysis paints a remarkably different picture. The example provided in Figure 7 illustrates the probabilistic performance distributions for the same four options. Notice that from a performance perspective, the Baseline concept demonstrates a much narrower range (denoting less uncertainty) and is shifted farther to the right. Looking at the overlap of the distributions of the three VM strategies, one can clearly see that the baseline concept has a striking advantage considering risk as a large proportion of the distributions for the VM strategies lay to the left of the lower tail of the baseline concept’s distribution. In hindsight, this makes good sense as the Baseline concept has been designed to a much higher level than the VM strategies and, therefore, demonstrates an appropriately greater degree of certainty in its anticipated performance. Further, VM Strategies 2 and 3 pose the highest risk of poor performance judging by their relatively broad distributions. Clearly, given this information, a prudent decision maker would opt to stick with Baseline concept if the judgment were based solely on performance.

Figure 7 - Probabilistic performance distributions for four options

Tying it all together as an expression of probabilistic value

Figure 7. Probabilistic performance distributions for four options


Assuming we have considered the effect of uncertainty on one or more of the elements of cost, time and performance, the next step is to calculate the value indices using the probabilistic values previously derived for them. In this example, the dynamic model for value was utilized. Building on the data from the previous models, we can now express the variability in the value indices as represented in Figure 8.

Figure 8 - Probabilistic comparison of value indices for four options

This comparison shows that Strategy 2 completely dominates the Baseline concept form a total value perspective, even when considering the “worst” case conditions for Strategy 2 and the “best” case conditions for the Baseline Concept. Further, it is significantly better than Strategy1 and moderately better than Strategy 3. Therefore, based on this analysis, decision makers can proceed with greater confidence that Strategy 2 offers the best value when considering cost, time, performance and risk.

Conclusions

Uncertainty and risk must be given due consideration if we are truly interested in improving value. As demonstrated in this paper, there are a number of probabilistic methods to consider uncertainty and how it affects cost, time, performance and value. We cannot know the future, nor can we pretend that the alternatives developed during the course of a VM study were conceived without flaws. As value practitioners, we must be mindful of this. Based upon the experience of the authors, one of the primary reasons that seemingly “good” alternatives are rejected by decision makers is that they are considered to be “risky” propositions. It is therefore incumbent upon us to evaluate how uncertainty can, and does, influence outcomes.

Figure 8. Probabilistic comparison of value indices for four options.


methods to consider uncertainty and how it aff ects cost, time, performance and value. We cannot know the fu-ture, nor can we pretend that the alternatives developed during the course of a VM study were conceived without fl aws. As value practitioners, we must be mindful of this. Based upon the experience of the authors, one of the pri-mary reasons that seemingly “good” alternatives are re-jected by decision makers is that they are considered to be “risky” propositions. It is therefore incumbent upon us to evaluate how uncertainty can, and does, infl uence outcomes.

It is neither realistic nor practical to go to this level of quantitative analysis on every VM study to be sure; how-ever, where major decisions are involved for an organiza-tion, such eff orts are worth considering.

References

Bryner, Jeanna, “Key to all Optical Illusions Discovered,” Live Science, June 2, 2008.

Cretu, Ovidiu; Stewart, Robert; Berends, Terry, “Risk Management for Design & Construction,” John Wiley & Sons, Hoboken, 2011.

Saaty, Thomas “Decision Making for Leaders,” RWS Pub-lications, Pittsburgh, 2008.

Saaty, Thomas and Peniwati, Kirti, “Group Decision Mak-ing: Drawing out and Reconciling Diff erence,” RWS Publications, Pittsburgh, 2008.

Stewart, Robert, “Value Optimization for Project and Performance Management,” John Wiley & Sons, Hoboken, 2010.

Zimbardo, Phillip, “The Time Paradox: The New Psychol-ogy of Time That Will Change Your Life,” Simon & Schuster, New York, 2008.

About the Authors

Robert B. Stewart, CVS-Life, FSAVE, PMP, and Gregory Brink, CVS, PMI-RMP, CCE/A are employed by Value Man-agement Strategies, Inc.

LET’S SHAKE HANDS AND GET TO KNOW ONE ANOTHER

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So, sign up as an exhibitor! It’s a terrifi c value that includes not only an exhibit space, but also admission to the President’s Recep-tion, the technical program, the Vendor Reception, and general assembly breakfasts and lunches.

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hotel rooms, and vacation packages. Society members may take advantage of these fantastic discounts via Member Resources web page in the Member Log-In section of the SAVE website (www.value-eng.org).

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A “Functional” Tool for the VaVe Toolbox:The Function Trade-off Table Is a New Tool to Help VaVe Practitioners Prepare

for VaVe ProjectsCarlos Gontijo, Jr., AVS

Abstract

Value analysis/value engineering (VaVe) practitioners understand that good project preparation is a fundamen-tal prerequisite for a successful workshop. A critical part of the preparation process necessarily requires gather-ing data for the team members. By being proactive, VaVe practitioners can successfully transition this collected data into shared knowledge. However, the historical preparation process does not provide the necessary tools to adequately inform the VaVe practitioner prior to the VaVe workshop.

“Function” is a key element for any VaVe Workshop. Historically, “function” has been introduced to the team members only after the “Information Phase” in the “Job Plan.” Making “function” available to the VaVe practitio-ner prior to the workshop should be a key element—a necessary tool—of the workshop preparation process.

The “Function Trade-off Table” (FToT) is a tool de-veloped specifi cally to provide key information to VaVe practitioners—before the workshop, when it can pro-vide the most long-term impact. This paper will introduce the FToT. Its contents will describe:

What the FToT isWhy the FToT is importantWhen to use the FToTWho is responsible for creating the FToTHow it will help the VaVe practitionerExamples of how the FToT method helped successful VaVe workshops.

Preparing for the Workshop

Preparation is essential for any workshop. The bet-ter prepared the VaVe practitioner is, the higher the odds for a successful outcome. However, preparation requires time and resources. There is a specifi c cost associated with performing it. Usually, it is the responsibility of the process sponsor or stakeholder to determine who should be involved up front in the pre-workshop planning and for how long.

Normal workshop preparation includes collecting pertinent data beforehand. A cross-functional team is selected. Its members are responsible for gathering the data to be shared during the workshop. Ideally, the col-lected data will translate into a wealth of information that could be valuable throughout the various “Job Plan” phases during the workshop.

The “Function Analysis Phase” includes a cost func-tion worksheet (CFW), which includes a table of compo-nent/sub-assembly costs. Team members assign costs associated with performing functions. The CFW table provides a means to identify the high-cost functions to be addressed during upcoming brainstorming sessions.

Potential production and quality issues with associ-ated costs are also collected during the preparation to better inform the team members where improvement opportunities might be. That data can be used during the “Brainstorming Phase” to highlight areas for im-provement as well as during the “Proposal Development Phase” to capture the tangible and intangible benefi ts of the proposals. The production process is also shared throughout all the phases of the workshop to highlight how components and subassemblies are put together.

The involvement of the VaVe practitioner in the Func-tion Analysis Phase is also benefi cial—not only to vali-date the data—but also to become familiar with the ob-ject under study. The VaVe practitioner’s earliest possible participation in this process is highly recommended. It is further recommended that the VaVe practitioner serve as the focal point of the data collection in order to de-termine how and when to present the data to the group during the workshop.

Missing Link in the Workshop Preparation

The fact that “function” is the key element in the VaVe process is well understood. However, when collect-ing data in preparation for workshops, “function” has not been among the included elements. Following the Job Plan by introducing “functions” to the team members after the Information Phase and only during the Func-


tion Analysis Phase makes sense—at least theoretically. However, when the VaVe practitioner has a better under-standing of product and component “functions” before the workshop, the practitioner can better understand the object under study. The determination: “Function” was a missing link in the workshop preparation process.

Although there was agreement that “function” was not included in the workshop preparations, it was not clear what information should be collected, how to col-lect it, or whether collecting it in advance would be ben-efi cial to the workshop.

Typically, the tear-down process prepares compo-nents/sub-assemblies for Function Identifi cation in the Function Analysis Phase prior to the workshop. During tear-down, VaVe practitioners started to identify some of the “functions” associated with components and/or sub-assemblies. Initially, identifying these functions was an informal way to become familiar with the object under study, and was not formally captured. However, func-tion identifi cation actually provided better preparation for the upcoming workshop.

After focusing on randomly-selected functions to identify during the preparation phase, the results be-came clear during the workshop. The VaVe practitioners were able to ask the team members more interesting questions about the actual “function” of that particu-lar component or sub-assembly. Not only did this added step improve the team dynamic, it also enhanced the knowledge and confi dence of the VaVe practitioner. This experience is validation that function identifi cation was the missing link in workshop preparation. Although the eff ect that function identifi cation will have on the work-shop outcome is not yet known, the overall benefi ts to workshop preparation were evident.

Workshop Preparation Evolution

What started out as a way to better prepare for work-shops, collecting “function” data prior to the workshop provided the added benefi ts of improving team dynam-ics and enhancing VaVe Practitioner effi cacy. The VaVe practitioner was then responsible for collecting the ap-propriate data, and would have technical help and sup-port, if needed.

The next question was the format. Should the func-tions be placed in a table? Should they be linked to com-ponents to speed up the “Random Function Identifi ca-tion” phase? The initial decision was to assign functions to major components and sub-assemblies in the same fi le as the costed Bill of Materials (BOM). Using this approach would remind the VaVe Practitioner which “functions” those major components perform in the big picture.

By associating functions with major components in the costed BOM fi le, the VaVe practitioners also started associating function with cost in a very informal way: looking at high-cost components and understanding the functions they were performing.

The next step was to see the relationships among the components and their functions. The VaVe practi-tioners wanted to see the consequences on high-cost components when changing the functions of some of the lower cost components. These “consequences” are the trade-off s. The format the VaVe practitioners decided to use was a table with functions that could be traded off without aff ecting quality or performance. Sometimes these trade-off s can even enhance them!

FToT Description

The FToT is the ideal tool for collecting all possible scenarios or trade-off s for further evaluation. The FToT lists the functions of the high-cost components and sub-assemblies, their specifi c costs, and their associated trade-off s when using diff erent components to “help” the high-cost components perform their functions.

The use of the word “help” refers to transferring part of the “function” performed by a high-cost component to lower-cost components to ease the burden on the high-cost components. The objective is to distribute the load of performing that function among other components to determine the most cost-eff ective distribution that would benefi t the object under study. Said another way, the goal is to determine the optimum distribution that would provide the same functions at the lowest cost.

Normally, this approach seeks ways to reduce com-ponent costs. However, many times this exercise may result in adding cost to other components when partially transferring functions to them. Interestingly, the main diff erence is that this approach also takes some of the cost out of the high-cost component.

Building the FToT

When building the FToT, the objective is to capture the trade-off s—those elements that could be changed in the design that would result in transferring the load of the high-cost component’s function to lower-cost com-ponents.

To build the FToT, the fi rst step is to go through the costed BOM and highlight the high-cost components. The next step is to check whether the high-cost compo-nents are stand-alone components (usually Level 1 in a BOM) or part of sub-assemblies. However, note that a high-cost component can look like a standalone compo-nent when it is a purchased full sub-assembly.


After understanding the components, sub-assem-blies, and their relationships, prepare a simple Pareto analysis comparing component and cost. Armed with this component vs. cost distribution, prepare the same type of analysis for the secondary high-cost components for the FToT, if time allows. For the purpose of this paper, the focus will be on the highest-cost component only. The term “high-cost component” will be used even if it is a sub-assembly.

Next, identify the basic and secondary functions of the highest-cost component. Determine how that high-cost component is physically linked to other lower-cost components. Note that components can also be “physi-cally linked” through an air gap. Identify the functions of the lower-cost components linked to the highest-cost component. Determine how aff ecting the functions of the lower-cost components will impact the function of the highest-cost component.

Usually, the better way to discover the trade-off s is to aff ect the functions of the lower-cost components by both increasing and decreasing them. Initially, it is not known if the relationship is positive or negative. In-creasing the function of the lower-cost component could either increase or decrease the function of high-cost component. Or, decreasing the function of lower-cost component could decrease the function of high-cost component. This is precisely the reason for creating the FToT.

Using the FToT

During workshop preparation, the VaVe practitio-ner—with technical support as needed—successfully constructed an FToT to better understand the object to be studied. Now that this valuable tool is available, how and when should it be used for the VaVe Job Plan during the workshop?

Instead of actually showing the FToT to the team members, the VaVe Practitioner should use the trade-off information only when identifying component functions during Random Function Identifi cation part of the Func-tion Analysis Phase. This would enable the VaVe practi-tioner to avoid having to validate their relationships with other components and functions or challenge the cur-rent design.

During a typical fi ve-day workshop, the Random Func-tion Identifi cation exercise starts on Monday and fi nishes on Tuesday. The identifi cation sequence for this exercise was already determined during workshop preparation. Relatively simple components are presented to the team members on Monday so they can practice the function identifi cation exercise. Having the team members iden-tify the functions of a second set of simple components

on Tuesday, then move on to the high-cost components is highly recommended.

During the Brainstorming Session, the information from the FToT can be reintroduced to spark ideas. How-ever, the fi nal evaluation of these trade-off s should oc-cur during the Evaluation/Development Phase only. The Evaluation/Development Phase is when all scenarios are discussed and the group proposes the best value.

Business Case A: Tier-1 Automotive Supplier

The VaVe practitioners were working with a Tier-1 au-tomotive supplier at the beginning of 2011. After deciding which products would be used for the VaVe workshop, the Practitioners selected dates for both workshop prep-aration week and the workshop week itself.

During the preparation week, the VaVe practitioners performed the tear-down, occasionally asking the engi-neers to clarify some of the design criteria and features. While reviewing the costed BOM, the practitioners dis-covered that the design’s highest-cost component was copper wire, which was located in two sub-assemblies: the rotor and the stator.

As the rotor rotates inside the stator, it creates mag-netic fl ux, which induces voltage into the stator windings creating Alternating Current (AC). The AC is rectifi ed by diodes to produce Direct Current (DC). Mechanical rota-tion is transformed into electricity in the form of DC volt-age.

The function of the rotor/stator combination is to “generate DC electricity.” Both the rotor and stator were examined to decipher their components and construc-tion. The objective was to fi nd a way to use other com-ponents to “generate DC electricity” in order to reduce the amount of wire used, and consequently the total product cost.

In this case, the component relationships are so sen-sitive that changing some of them could dramatically compromise critical points of the object’s performance in some applications. To help evaluate the trade-off s, the client provided access to their sophisticated model-ing software. The software was needed to calculate the object’s performance for specifi ed speeds and current output. The VaVe Practitioners asked to use the software during the Evaluation/Development Phase of the Job Plan to ensure they could validate the trade-off s.

There would be only one opportunity to use the modeling software because the simulation could take up to 3 hours to run. After evaluating as many as 12 possible scenarios, the software engineer who would run the sce-nario and the VaVe Practitioners agreed to test the fol-lowing trade-off s (see Figure 1, next page):


Stator wire diameter—thicker or thinnerStator lamination thickness—thicker or thinnerStator material—M47 or carbon steelDiode current rating—50 A or 80 A.

When the simulation is done, the results will indicate the performance impact for each combination. The sim-ulation indicates blue for positive results, which means increased performance. It indicates red for negative re-sults, which means decreased performance. For this sim-ulation, nine combinations indicated a positive perfor-mance and were evaluated for cost (see fi gure 2, below). The combination with the best performance stayed the same, except with thicker wire. However, the cost was approximately 30% less.

Ultimately, the team presented the most cost-eff ec-tive combination in its report. However, they also showed

the client the other combinations considered during the evaluation process.

Business Case B: Home Appliance Industry

Also in 2011, the VaVe practitioners used the FToT in a project for a client in the home appliance industry. The approach was basically the same: a preparation week and a workshop week.

During the preparation week, the VaVe practitioners examined the costed BOM, highlighted the high-cost components, and discovered that a heat exchanger was 49% of total material cost because of its stainless-steel construction. However, the heat exchanger is also the core of the client’s product.

Upon discussing project constraints with the client’s upper management team, the VaVe practitioners learned that the only constraint was to keep the same heat-ex-changer design concept because of its associated brand image. Despite the fact that the heat exchanger is, by far, the highest-cost component, its design could not be changed. Further investigation during the preparation week revealed that the client requested avoiding design changes because the heat exchanger supplier was expe-riencing internal quality issues at the time.

The basic function of this heat exchanger is to “trans-fer heat” from a mixed gas to water. Its combustion chamber is constructed with a burner, water tubes, and “dimples” that enhance the heat transfer. As the water travels from the bottom of the heat exchanger to the top, it encounters barriers that divert its direction to maximize the amount of exposed surface area available for heat transfer. The combustion chamber takes up only 30% of the heat exchanger’s height. However, 40% of the “heat transfer” function occurs where the fl ame is.

With the help of a lab engineer, the VaVe practitio-ners started putting together the FToT. The objective was to transfer part of the heat exchanger’s function to other components or sub-assemblies. Although this would reduce the high-cost stainless-steel content, the heat-exchanger design and construction was branded as a marketing diff erentiator.

Examples of the trade-off s that were identifi ed in-clude:

Increasing the area the area of the combustion cham-ber while decreasing the exhaust tube area

Increasing the number of “dimples” on the exhaust tubes to improve heat transfer and reduce the total heat-exchanger height

Increasing the gas portion of the mixture

Increasing the speed of the mixture fan

During the Brainstorming Session, the information from the FToT can be reintroduced to spark ideas. However, the final evaluation of these trade-offs should occur during the Evaluation/Development Phase only. The Evaluation/Development Phase is when all scenarios are discussed and the group proposes the best value.

Business Case A: Tier-1 Automotive SupplierThe VaVe Practitioners were working with a Tier-1 automotive supplier at the beginning of 2011. After deciding which products would be used for the VaVe workshop, the Practitioners selected dates for both workshop preparation week and the workshop week itself.

During the preparation week, the VaVe Practitioners performed the teardown, occasionally asking the engineers to clarify some of the design criteria and features. While reviewing the costed BOM, the Practitioners discovered that the design’s highest-cost component was copper wire, which was located in two sub-assemblies: the rotor and the stator.

As the rotor rotates inside the stator, it creates magnetic flux, which induces voltage into the stator windings creating Alternating Current (AC). The AC is rectified by diodes to produce Direct Current (DC). Mechanical rotation is transformed into electricity in the form of DC voltage.

The function of the rotor/stator combination is to “generate DC electricity.” Both the rotor and stator were examined to decipher their components and construction. The objective was to find a way to use other components to “generate DC electricity” in order to reduce the amount of wire used, and consequently the total product cost.

In this case, the component relationships are so sensitive that changing some of them could dramatically compromise critical points of the object’s performance in some applications. To help evaluate the trade-offs, the client provided access to their sophisticated modeling software. The software was needed to calculate the object’s performance for specified speeds and current output. The VaVe Practitioners asked to use the software during the Evaluation/Development Phase of the Job Plan to ensure they could validate the trade-offs.

There would be only one opportunity to use the modeling software because the simulation could take up to 3 hours to run. After evaluating as many as 12 possible scenarios, the software engineer who would run the scenario and the VaVe Practitioners agreed to test the following trade-offs (see picture 1):

� Stator wire diameter—thicker or thinner� Stator lamination thickness—thicker or thinner� Stator material—M47 or carbon steel� Diode current rating—50 A or 80 A.

��Figure 1. FToT without cost

When the simulation is done, the results will indicate the performance impact for each combination. The simulation indicates blue for positive results, which means increased performance. It indicates red for negative results, which means decreased performance. For this simulation, nine combinations indicated a positive performance and were evaluated for cost (see picture 2).

��

Surprisingly, out of the nine positive combinations, six suggested increasing copper wire diameter. Instead of transferring the “generate DC electricity” function �� the copper wires, the simulation suggested �� it. The following combination was determined to be the most cost-effective:

� Keep the existing wire diameter� Reduce the lamination thickness from 0.5 mm to 0.3 mm� Use 50 A diodes instead of 80 A diodes.

The combination with the best performance stayed the same, except with thicker wire. However, the cost was approximately 30% less.

Ultimately, the team presented the most cost-effective combination in its report. However, they also showed the client the other combinations considered during the evaluation process.

Business Case B: Home Appliance IndustryAlso in 2011, the VaVe Practitioners used the FToT in a project for a client in the home appliance industry. The approach was basically the same: a preparation week and a workshop week.

During the preparation week, the VaVe Practitioners examined the costed BOM, highlighted the high-cost components, and discovered that a heat exchanger was 49% of total material cost because of its stainless-steel construction. However, the heat exchanger is also the core of the client’s product.

Upon discussing project constraints with the client’s upper management team, the VaVe Practitioners learned that the only constraint was to keep the same heat-exchanger design concept because of its associated brand image. Despite the fact that the heat exchanger is, by far, the highest-cost component, its design could not be changed. Further investigation during the preparation week revealed that the client requested avoiding design changes because the heat exchanger supplier was experiencing internal quality issues at the time.

The basic function of this heat exchanger is to “transfer heat” from a mixed gas to water. Its combustion chamber is constructed with a burner, water tubes, and “dimples” that enhance the heat transfer. As the water travels from the bottom of the heat exchanger to the top, it encounters barriers that divert its direction to maximize the amount of exposed surface area available for heat transfer. The combustion

Figure 2. FToT fi nal results


Increasing the number of tubes

Decreasing the number of tubes.

The team began the heat-exchanger Function Iden-tifi cation exercise on Tuesday morning of the workshop. The VaVe practitioners reinforced the client’s constraints and the team evaluated the trade-off s. On Wednesday morning, “heat transfer” obviously remained the highest-cost function. Although the team was aware of the proj-ect’s scope limitations, it still brainstormed other ways to accomplish the “heat transfer” function or to enhance it through other components. More trade-off s were cap-tured for further evaluation (see fi gure 3, below). During the Evaluation/Development Phase on Thursday, one of the team members conferred with some of the client’s engineers to determine which trade-off s were worth evaluating.

chamber takes up only 30% of the heat exchanger’s height. However, 40% of the “heat transfer” function occurs where the flame is.

With the help of a lab engineer, the VaVe Practitioners started putting together the FToT. The objective was to transfer part of the heat exchanger’s function to other components or sub-assemblies. Although this would reduce the high-cost stainless-steel content, the heat-exchanger design and construction was branded as a marketing differentiator.

Examples of the trade-offs that were identified include:� Increasing the area the area of the combustion chamber while decreasing the exhaust tube area� Increasing the number of “dimples” on the exhaust tubes to improve heat transfer and reduce the

total heat-exchanger height� Increasing the gas portion of the mixture� Increasing the speed of the mixture fan� Increasing the number of tubes� Decreasing the number of tubes.

The team began the heat-exchanger Function Identification exercise on Tuesday morning of the workshop. The VaVe Practitioners reinforced the client’s constraints and the team evaluated the trade-offs. On Wednesday morning, “heat transfer” obviously remained the highest-cost function. Although the team was aware of the project’s scope limitations, it still brainstormed other ways to accomplish the “heat transfer” function or to enhance it through other components. More trade-offs were captured for further evaluation (see picture 3). During the Evaluation/Development Phase on Thursday, one of the team members conferred with some of the client’s engineers to determine which trade-offs were worth evaluating.

��

During the workshop’s report-out on Friday, the team presented the options that they and the engineers had agreed upon. As soon as the internal quality issue with the heat-exchanger supplier is resolved, the client will assemble a team to work on the changes that were suggested during the report-out. The sooner the recommended changes can be implemented, the sooner the client can enjoy the benefits.

ConclusionFToT is another tool for the VaVe Practitioner’s toolbox. However, its use depends on the object under study. There are some limitations when using it on sub-assemblies because of the nature of trade-offs. The FToT should not be shared with the team members to ensure the group executes the VaVe Job Plan thoroughly and without shortcuts or distractions.

Figure 3. FT0T without cost

During the workshop’s report-out on Friday, the team presented the options that they and the engineers had agreed upon. As soon as the internal quality issue with the heat-exchanger supplier is resolved, the client will assemble a team to work on the changes that were suggested during the report-out. The sooner the recom-mended changes can be implemented, the sooner the client can enjoy the benefi ts.

Conclusion

FToT is another tool for the VaVe practitioner’s tool-box. However, its use depends on the object under study. There are some limitations when using it on sub-assemblies because of the nature of trade-off s. The FToT should not be shared with the team members to ensure the group executes the VaVe Job Plan thoroughly and without shortcuts or distractions.

FToT is a powerful tool. Its use can help provide VaVe Practitioners with confi dence and strength during high-level conversations by increasing their technical back-ground and knowledge regarding objects under study. By being part of the preparation, VaVe practitioners have time to better understand and absorb more aspects of the object under study. In doing so, they can more ef-fectively challenge—and enhance—the client’s product design.

About the Author

Carlos Gontijo, Jr., is an Associate Value Specialist and serves as the VaVe director for Argo, Inc.

PACE Update: Promoting VM on Your BehalfIn 2007, SAVE International identifi ed four core ser-

vices that members identifi ed as most important: pro-mote, advocate, certify, educate. In 2008, those core services were revealed as the “PACE” initiative.

SAVE’s eff orts to fulfi ll the objective of that initiative took the form of the development of a new strategic business plan, still in progress. But SAVE’s board of direc-tors did not wait until a business plan was fi nished, but launched into action to improve member services and brand awareness.

The latest eff orts under PROMOTE include:

Advertisement in DBIA’s weekly digital newsletter MultiBrief. The advertisement is hyperlinked to the SAVE web site.

Sponsorship of the fi rst Asian VE Conference in Seoul, South Korea. This regional event will draw from ma-jor corporations in Korea, Japan, China, and India.

Exhibition at the APWA 2011 Congress in Denver, Colorado, a national convention of U.S. government employees. The public sector provides a major per-centage of VM consultant work.

Exhibition and presentation at IQPC’s 2012 Lean Six Sigma Summit in Orlando, Florida. This is a prime op-portunity for SAVE to show C-level decision makers that the value methodology complements and im-proves widely used process improvement tools and can only improve their companies’ bottom lines and customer satisfaction.


Revealing Hidden Externalities in Major Projectswith Value Methodology

Munsell McPhillips, Ph.D., AVS


Abstract

An economic externality is a cost or benefi t that is not refl ected in the price of a project or product. It is borne by those who are not willing parties to the transactions of producing the project. Economists tell us that economic externalities are distortions of our marketplace because some costs or benefi ts falling outside the project are not accurately refl ected in its costs. As VM practitioners, we pride ourselves on our clear-eyed understanding of costs. However, if we cannot articulate the eff ects of our projects or products on the larger community, we can-not accurately analyze or cost them. By properly examin-ing and eliminating external costs, our adverse impacts on the larger world are reduced and our projects become more sustainable. VM may provide a mechanism for re-vealing and ameliorating these hidden costs. This paper will address how externalities arise in engineering de-sign, a method for integrating externalities in VM, some approaches to applying economic measures to services provided by nature and how the process infl uences team member selection.

Introduction

Economic externalities are costs and benefi ts that of-ten hover around the margins of our projects and can be diffi cult to pin down. To have an effi cient market place, all of the costs of producing a project must be assigned to it. Only then do we have an accurate cost and can we make informed decisions regarding whether or not to pay for the project. Fully burdening a project with all of its associated costs is referred to as internalizing the ex-ternalities.

It is important to note that externalities can work in both directions. One example of a positive externality is vaccination against communicable disease. If 99% of a population goes to the trouble and expense of getting vaccinated and not transmitting the disease, the remain-ing 1% also stays healthy. The people who were not vac-cinated are free riders; they derive the benefi t but don’t

contribute to the cost. To the extent that we can identify and quantify positive externalities, the benefi ts, perhaps expressed as avoided costs, should be accrued to the project. When positive externalities go uncaptured, the project is undervalued and the incentives to proceed are improperly reduced.

Negative externalities are unfortunately easier to en-vision: increased health care costs and lost work days as-sociated with air pollution or increased water treatment costs caused by water pollution from upstream industry are examples of costs born by people who were not will-ing participants in the business transactions that caused them. Externalities also arise when we fail to fully account for the economic value of natural capital, the goods and services provided by nature. This failure poses serious business and social risks. Natural capital is the ecosystem service provided by the living world. These services are broadly grouped into four categories: 1) Provisioning ser-vices such as food production, raw materials, fresh water and medicinal feedstock; 2) Regulating services including carbon storage, local climate regulation, water treatment and degradation of toxins and pollutants, biological con-trol of pests and vector-borne diseases and pollination; 3) Supporting services including habitat provision and maintenance of diverse, viable gene pools and 4) Cultur-al services such as recreational spaces, tourism, cultural foundations and spiritual experience (TEEB, 2010). Each of these goods and services has a clear and quantifi able economic value the loss of which is generally a negative economic externality. For example, in 2006 the value of genetic resources in the form of pharmaceutical feed-stock alone amounted to US$640 billion (TEEB, 2009). Techniques and case studies that quantify the fi nancial value of these services are well documented and increas-ingly available (Daily and Ellison, 2002).

Most engineering designers earnestly try to incor-porate broader interests into their projects and in many respects are successful. In addition to the direct cost of building projects that meet customer requirements, most of us agree that the eff orts involved in avoiding harm to non-customers is an appropriate cost of doing business. In principle at least, regulations induce projects


to internalize the costs of such as potential externalities as public safety and environmental protection.

One of the challenges of properly allocating costs of a project is that sometimes it is not obvious how or where the external cost or benefi t occurs. We are all accustomed to incorporating stakeholder needs in our projects. However, one of the diffi culties of internalizing externalities is that the people aff ected frequently aren’t recognized as stakeholders so the external costs or ben-efi ts go unrecognized until too late. At most they may be regarded as unintended consequences. However, unin-tended does not mean unforeseeable. Value Methodol-ogy, particularly function analysis may provide an avenue for uncovering and mitigating these consequences.

Application

As a way of exploring how VM might reveal externali-ties, let us consider the results of a long-standing levee project in the Midwestern US (see Figure 1). The levees protect rich farmland and were designed, built and oper-ated over the past 50 years with close cooperation be-tween the federal government, local levee districts and landowners.

As part of a comprehensive levee inspection conduct-ed by this author and others, all available documentation including the design criteria, memoranda describing the designers’ intent, plan sets and calculations, internal tech-nical review comments and correspondence with stake-holders was examined in detail. The review revealed that the design included interior berms roughly 40 to 60 feet wide on both sides of the river. These wide berms were not designed to resist erosive fl ows but would gradually erode over an extended time. The designers performed no calculations regarding the resistance of the berms to erosion but estimated that they were wide enough to protect the levees for the 50-year life of the project.

REVEALING HIDDEN ECONOMIC EXTERNALITIES IN MAJOR PROJECTS WITH VALUE METHODOLOGY

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involved in avoiding harm to non-customers is an appropriate cost of doing business. In principle at least, regulations induce projects to internalize the costs of such as potential externalities as public safety and environmental protection.

One of the challenges of properly allocating costs of a project is that sometimes it is not obvious how or where the external cost or benefit occurs. We are all accustomed to incorporating stakeholder needs in our projects. However, one of the difficulties of internalizing externalities is that the people affected frequently aren’t recognized as stakeholders so the external costs or benefits go unrecognized until too late. At most they may be regarded as unintended consequences. However, unintended does not mean unforeseeable. Value Methodology, particularly function analysis may provide an avenue for uncovering and mitigating these consequences.

Application As a way of exploring how VM might reveal externalities, let us consider the results of a long-standing levee project in the Midwestern US (see Figure 1). The levees protect rich farmland and were designed, built and operated over the past 50 years with close cooperation between the federal government, local levee districts and landowners.

As part of a comprehensive levee inspection conducted by this author and others, all available documentation including the design criteria, memoranda describing the

Figure 1 Typical levee section with bermsFigure 1. Typical levee section with berms

From the perspective of the recognized stakeholders this arrangement was fi ne. The loss of the berms also widened the channel and locally increased fl ood capac-ity providing another benefi t, or so it appeared. Figure 2 illustrates a levee section where the berms have eroded away. The levee districts are now armoring the levee toes and slopes and expect to gain another several de-cades of service.

From the perspective of this project’s stakeholders, the fate of the soil eroded from the berms is not relevant. For the landowners both upstream and downstream of the project, it is painfully relevant. Consider a mass of soil roughly 60 feet wide by 20 feet deep by 100 miles long on each side of a small river. Figure 3 is an aerial photograph of a reach downstream of the project levee depicting a dense fi eld of sediment bars deposited in the center of the river.

Release of excessive sediment in slug fl ow during storms creates an economic externality for landown-ers outside of the levee district. Such large quantities of sediment can cause rivers to shift their alignment, add-ing acreage along one bank (positive) and subtracting it


PAGE 4

designers’ intent, plan sets and calculations, internal technical review comments and correspondence with stakeholders was examined in detail. The review revealed that the design included interior berms roughly 40 to 60 feet wide on both sides of the river. These wide berms were not designed to resist erosive flows but would gradually erode over an extended time. The designers performed no calculations regarding the resistance of the berms to erosion but estimated that they were wide enough to protect the levees for the 50-year life of the project. From the perspective of the recognized stakeholders this arrangement was fine. The loss of the berms also widened the channel and locally increased flood capacity providing another benefit, or so it appeared. Figure 2 illustrates a levee section where the berms have eroded away. The levee districts are now armoring the levee toes and slopes and expect to gain another several decades of service.

Figure 2. Loss of riverside levee to erosion

From the perspective of this project’s stakeholders, the fate of the soil eroded from the berms is not relevant. For the landowners both upstream and downstream of the project, it is painfully relevant. Consider a mass of soil roughly 60 feet wide by 20 feet deep by 100 miles long on each side of a small river. Figure 3 is an aerial photograph of a reach downstream of the project levee depicting a dense field of sediment bars deposited in the center of the river.

Figure 2. Loss of riverside due to erosion


PAGE 5

Figure 3. Sediment released from upstream berms accumulating in downstream reaches (from NRCS geodatabase)

Release of excessive sediment in slug flow during storms creates an economic externality for landowners outside of the levee district. Such large quantities of sediment can cause rivers to shift their alignment, adding acreage along one bank (positive) and subtracting it along another (negative). Along levees in the adjacent districts downstream, the excess sediment load deposited as center bars focused scouring flows at the levee toes. This accelerated erosion at the levee toes threatenstheir stability. Moreover, the sediment accumulates at and blocks the outfalls of agricultural field drains (see Figure 4) and unless found and cleared away, delays crop planting imposing a further burden. On a less proximate scale, both the sediment and the agricultural chemicals it carries add to the cost and complexity of processing drinking water from downstream intakes. Upstream of the project reach, the loss of the internal berms has over-widened the river channel and generated a wave of upstream-migrating incision in the channel bottom for many miles upstream.

Figure 3. Sediment released from upstream berms accumulating in downstream reaches (from NRCS geodatabase)


along another (negative). Along levees in the adjacent districts downstream, the excess sediment load depos-ited as center bars focused scouring fl ows at the levee toes. This accelerated erosion at the levee toes threat-ens their stability. Moreover, the sediment accumulates at and blocks the outfalls of agricultural fi eld drains (see Figure 4) and unless found and cleared away, delays crop planting imposing a further burden. On a less proximate scale, both the sediment and the agricultural chemicals it carries add to the cost and complexity of processing drinking water from downstream intakes. Upstream of the project reach, the loss of the internal berms has over-widened the river channel and generated a wave of upstream-migrating incision in the channel bottom for many miles upstream.

Viewed through the stakeholder lens, this 50-year old project has accomplished its objective. The designers and operators of this levee system were clearly and ap-propriately focused on meeting the needs of those who would help pay for and benefi t from the project. The question of who outside of the project might be dam-aged or might derive unwarranted benefi t simply never came up. No regulatory agency pointed out the damages at the time and it is likely that even today the problems with the berm design would escape scrutiny by regula-tors. The berms were not called out as “sacrifi cial” on the plan sets; that was only apparent from correspondence and the design memoranda.

This levee system was never subject to a VM study and it is possible that had one been performed, the ex-ternalities would not have been discovered. However, function analysis might provide a framework for more systematic examination of external consequences. Be-low is a FAST diagram for this project. The functions are based on review of the project documentation, physical inspection of the project and interviews with stakehold-ers and operators. The project was designed before com-


PAGE 6

Figure 4. Field drainage outfalls blocked by sediment deposition

Viewed through the stakeholder lens, this 50-year old project has accomplished its objective. The designers and operators of this levee system were clearly and appropriately focused on meeting the needs of those who would help pay for and benefit from the project. The question of who outside of the project might be damaged or might derive unwarranted benefit simply never came up. No regulatory agency pointed out the damages at the time and it is likely that even today the problems with the berm design would escape scrutiny by regulators. The berms were not called out as “sacrificial” on the plan sets; that was only apparent from correspondence and the design memoranda.

This levee system was never subject to a VM study and it is possible that had one been performed, the externalities would not have been discovered. However, function analysis might provide a framework for more systematic examination of external consequences. Below is a FAST diagram for this project. The functions are based on review of the project documentation, physical inspection of the project and interviews with stakeholders and operators. The project was designed before computer-based hydraulic modeling was widely used and the designers had to contend with more uncertainty regarding water surface elevations and flows than their counterparts do today. Consequently the design included an oversized channel with interior berms whose fate was ambiguous.

Figure 4. Field drainage outfalls blocked by sediment deposition

puter-based hydraulic modeling was widely used and the designers had to contend with more uncertainty regard-ing water surface elevations and fl ows than their coun-terparts do today. Consequently the design included an oversized channel with interior berms whose fate was ambiguous.

Function analysis provides startling clarity. The sparse language and architecture of FAST diagrams sometimes encompass explicit revelation of implicit assumptions. The circled area of the FAST diagram encloses the func-tions that are most relevant to the externality. In a minor process variation the team leader could ask regarding a function, “What happens when…?” This is distinct from the familiar “When” function commonly generated dur-ing function analysis. Such functions generally focus on actions aff ecting the project and stakeholders. Instead the team leader uses the “What happens when… “ ques-tion to prompt the team members to think outside the project boundaries and beyond the population regarded as stakeholders. In this instance a VE team with exper-tise in river channel and levee design would generate several answers to “What happens when we permit ero-sion, relocate shear or create berm?” On other projects the prompts might be “What happens to surrounding communities when we increase traffi c throughput?” Or “What happens to groundwater supplies when we de-water the mine?” Or “What happens to invasive species migration when we create connections in waterways?”

Once these externalities are defi ned, the team can brainstorm ideas to prevent the damage, or if that is not possible, add the cost of repair and mitigation to the project budget. In the case of the levee berms, the eco-nomic implications of the release of sediment from the levee berms are straightforward and signifi cant. Had this question been raised during project design, simple and relatively inexpensive modifi cations to the design such as intermittent hard points would have dramatically de-creased the erosion. The next levee district downstream successfully used this approach. In this and possibly many other cases, the negative eff ects borne by the project’s neighbors could have been entirely avoided at minimal cost had the design team understood the externalities. None of us want to add costs to our projects; however, economic externalities are real costs. They will be borne by someone. They should be borne by those who will-ingly benefi t from the project.

ConclusionSystematically searching for unstated and unintend-

ed consequences is diffi cult for both designers and VM team members. We are challenged to rethink the nature of value and the value of nature. In doing so we require another skill in addition to the usual technical and com-munication abilities we demand of our team members. If



PAGE 7

Function analysis provides startling clarity. The sparse language and architecture of FAST diagrams sometimes encompass explicit revelation of implicit assumptions. The circled area of the FAST diagram encloses the functions that are most relevant to the externality. In a minor process variation the team leader could ask regarding a function, “What happens when…?” This is distinct from the familiar “When” function commonly generated during function analysis. Such functions generally focus on actions affecting the project and stakeholders. Instead the team leader uses the “What happens when… “ question to prompt the team members to think outside the project boundaries and beyond the population regarded as stakeholders. In this instance a VE team with expertise in river channel and levee design would generate several answers to “What happens when we permit erosion, relocate shear or create berm?” On other projects the prompts might be “What happens tosurrounding communities when we increase traffic throughput? or, “What happens to groundwater supplies when we dewater the mine? or “What happens to invasive species migration when we create connections in waterways?”.

Once these externalities are defined, the team can brainstorm ideas to prevent the damage, or if that is not possible, add the cost of repair and mitigation to the project budget. In the case of the levee berms, the economic implications of the release of sediment from the levee berms are straightforward and significant. Had this

Figure 5. Function analysis diagramour team members and we can broaden our gaze to larg-er spatial and temporal scales than the strict confi nes of our project boundaries we can avoid unintentional harm to others while still meeting our own needs. Value Meth-odology’s unique ability to reveal the essential elements of a project in the starkest of terms may be an invaluable tool to improve the sustainability of our work.

References

Daily, G.C and K. Ellison, (2002) The New Economy of Na-ture: The Quest to Make Conservation Profi table, Is-land Press, Washington DC.

TEEB (2009) The Economics of Ecosystems and Biodi-

versity for National and International Policy Makers – Summary: Responding to Nature’s Value, Pavan Sukhdev, Ed., Welzel+Hardt, Wesseling, Germany.

TEEB (2010) The Economics of Ecosystems and Biodi-versity; Mainstreaming the Economics of Nature: A Synthesis of the Approach, Conclusions and Recom-mendations of TEEB, Pavan Sukhdev, Ed., Progress Press, Malta.

About the Author

Munsell McPhillips, Ph.D., is an Associate Value Specialist employed by Strategic Value Solutions, Inc.

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VALUE WORLD

VOL. 34 | NO. 2 | FALL 2011InternationalSAVE

In this Issue:1 Editorial: Creating Value in Product/Product

Life CycleM. A. Berawi, Ph.D.

3 Value Engineering the Construction of Bored Tunnels in Competent RockEur. Ing. Christopher Laughton, Ph.D., PE, C.Eng.

14 Value Engineering Applied to Create Champion ProposalsAnna M. Bremmer, CVS, LEED AP

21 Uncertainty Modeling in Multiple Dimensions for Value MethodologyRobert B. Stewart, CVS-Life, FSAVE, PMP & Gregory Brink, CVS, PMI-RMP, CCE/A

31 A “Functional” Tool for the VaVE ToolboxCarlos Gontijo, Jr., AVS

36 Revealing Hidden Externalities in Major Projects with Value MethodologyMunsell McPhillips, Ph.D., AVS

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in this issue · 2018. 4. 4. · vice president-certiﬁ cation: tom wiggins, cvs vice...

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