mega projects - maximizing strategic value -info decision making

8112019 Mega Projects - Maximizing Strategic Value -Info Decision Making

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Maximizing strategic value from megaprojects The in1047298uence of information-feed on decision-making by the project manager

John Eweje a 1 Rodney Turner b 2 Ralf Muumlller c 3

a Shell Nigeria EampP Company 2122 Marina Lagos Nigeria b Univ Lille Nord de France LSMRC SKEMA Business School Avenue Willy Brandt F59777 Euralille France

c Dept of Leadership and Organization BI Norwegian Business School 0442 Oslo Norway

Received 24 August 2011 received in revised form 11 January 2012 accepted 12 January 2012

Abstract

Large projects are notorious for erosion of value during execution Decisions made by project managers have a signi1047297cant impact on the stra-tegic value of the asset delivered and those decisions depend on the information feed on which they are based This study uses theories of orga-nizational behavior decision-making and program management to investigate the impact of information feed used by project managers on thestrategic value delivered by mega projects in the oil and gas industry A global survey of 69 managers of mega-projects was conducted Resultsshowed that information feed to project managers signi1047297cantly in1047298uences the strategic value created by megaprojects Also some moderating ef-fects of contextual factors on this relationship were found The contextual factors that in1047298uenced project manager decision-making relate to what they perceived to be Senior Management drivers for their projects However the hypothesized moderating in1047298uence of project manager experienceon decision-making was not foundmdashan interesting observation It was found that the extent to which project managers feel in control should in-1047298uence the scope and quality of information-feed that should be sought Four risk areas were observed as signi1047297cant to long-term value creation

from megaprojects government relations host community relations contract management and procurement and the in1047298uence of multi-locationexecutioncopy 2012 Elsevier Ltd APM and IPMA All rights reserved

Keywords Megaprojects Program management Strategic value Decisions

1 Introduction

Megaprojects are programs that integrate strategically-aligned projects into one very large project (Miller and Lessard 2000

Jaafari 2004) and are used by the oil and gas industry to deliver key strategic assets In recent years most of the large oil and gascompanies have been re-investing much of their annual profits

(up to 90 in some cases) as capital expenditure (RoyalDutch Shell 2008 ExxonMobil 2007 BP 2007) Megaprojectstypically do not leave the socio-economic life of communities im-

pacted by their implementation The financial and social stakes

on megaprojects are so large they can endanger the survival of corporations and threaten the economic stability of the countriesinvolved (Miller and Lessard 2000)

The performance of megaprojects in the oil and gas industryhas seen little improvement over the last decade (Merrow1988 Merrow 2003 Fayek et al 2006) Underperformanceincludes substantial shortfalls in benefits such as financial per-formance of the delivered assets social acceptability regulato-ry compatibility and future business opportunities (Merrow1988 Merrow 2003 Miller and Lessard 2000 Fayek et al2006) The seeds of this underperformance are often sownearly in the execution phase yet not much can be found in

Corresponding author at Wildwood Manor Close East Horsley SurreyKT24 6SA UK Tel +44 1483 282 344

E-mail addresses jewejegooglemailcom (J Eweje)rodneyturnerskemaedu rodneyturnereuroprojexcouk (R Turner)ralfmuellerpm-conceptscom (R Muumlller)1 Tel +234 808 583 73642 Tel +33 3 2021 59723 Tel +47 464 10 000

0263-7863$3600 copy 2012 Elsevier Ltd APM and IPMA All rights reserveddoi101016jijproman201201004

Please cite this article as Eweje J et al Maximizing strategic value from megaprojects The in1047298uence of information-feed on decision-making by the project manager International Journal of Project Management (2012) doi101016jijproman201201004

Available online at wwwsciencedirectcom

International Journal of Project Management xx (2012) xxx ndash xxx

JPMA-01373 No of Pages 13

wwwelseviercomlocateijproman



literature on this phase of megaprojects (Miller and Lessard2000 Grun 2004)

Organizational behavior theory suggests that the ability of a person within an organization to influence its strategic directionis a function of the amount of resource allocation he or she con-trols (Brower and Gilbert 2007) and not necessarily his or her

seniority The managers of megaprojects can be responsible for the allocation of between $03 billion to $20 billion The abilityof these senior project managers to influence corporate strategicdirection should not be underestimated Failure of just one pro-

ject can potentially wipe out the entire annual profit of an oiland gas conglomerate The strategic performances of busi-nesses are underpinned by decisions and the cost of poor deci-sions can be high This study aims to draw attention to how thedecision-making of project managers during project executioncan impact on the long-term strategic goals of corporationsTwo research questions are addressed

which factors of information-feed supporting project man-agers decision impact the strategic value delivered bymegaprojects for the sponsoring organization the most

how can the decision framework of the managers of megaprojects be enhanced

Information is critical as an input into the decision process A positive correlation has been established between business per-formance and decision-making practice (Thomas et al 1993Mackie et al 2007) and since a program is a temporary organi-zation a correlation between program performance and decision

practices should be expected (Thiry 2004) Flyvbjerg (2007) has

observed that the main challenges of megaprojects is inadequateunreliable or misleading information and conflicts between deci-sion making policy and planning

The perspective of this research is from the view point of the project manager with focus on how decisions made by the project manager during execution impact on the strategic value deliv-ered by the megaproject to the sponsoring organization Fig 1illustrates the typical project delivery process followed by most oil and gas corporations The process is decision-based but

heavily biased towards the project front-end where the most value is created The execution phase activities and deliverablesenable the realization of value and is where projects managerstake the lead

In the next section we consider the nature of megaprojects andthen decision-making on megaprojects and we introduce the hy-

potheses We then describe the research methodology and resultsof the study We conclude by discussing the implications of thestudy

11 Theoretical framework and hypotheses

111 Megaprojects and the program management paradigm

A megaprojects is a special case of a program and as such is aset of multiple but relatedprojects directed towards commonstra-tegic and business objectives which generates benefits beyondthose that would have been generated had the projects beendone individually (Office of Government Commerce 2007Project Management Institute 2006 2008) This is the nature of oil and gas megaprojects which are essentially programs that in-tegrate strategically aligned commercially viable and logisticallycombinable projects under a single management umbrella Theyusually cost over $1 billion involve high uncertainty compriseintangible benefits and promise attractive long-term outcomes

(Miller and Lessard 2000 Flyvbjerg et al 2003) Compared totraditional projects they have long project and product life-cycles are significantly less predictable in terms of time and

Fig 1 Opportunity and project realization process in the oil and gas industry

2




scope (Cooke-Davies 2002) demand substantial irreversiblecommitments have high probabilities of failure and a skewed re-ward structure (Miller and Lessard 2000)

The managers of megaprojects often adopt traditional modesof project delivery because that is their basic training and experi-ence In this mode the managers energy is devoted to low level

management of contracts focusing on time and cost (ie project efficiency as defined by Shenhar and Dvir 2007) without ade-quate attention to how to attain the best overall results (Halmanand Braks 1999 Asrilhant et al 2007 Turner et al 2009Turner et al 2010) thereby negating the longer-term strategicviews that inform the initiation of the projects As program man-agers their focus should be on strategic objectives and business

benefits requiring more of a leadership role than a management one (Murray-Webster and Thiry 2000 Shao 2010 Shao et al2011) From inception to the start of revenue generation mega-

projects can take 5 to 12 years (Reinhards 1989) while operation-al life-can be between 7 and 30 years This long-term nature

makes megaprojects vulnerable to uncertainty and ambiguity em- phasizing a need for a strategic decision making in their manage-ment (Office of Government Commerce 2007) rather than thetactical short-term efficiency management of traditional project execution (Project Management Institute 2008)

Applying a program management paradigm to megaprojectshelps address this being about benefit management stakeholder management and ensuring effective governance (Project Management Institute 2006 Office of Government Commerce2007) It provides a framework that easily identifies changesmakes causes and effects clear and enables good demarcation be-tween risks and opportunities (Murray-Webster and Thiry 2000)Recognizing megaproject managers as essentially program man-

agers they are therefore responsible for navigating the megaproj-ect through the ambiguities of strategy and its emergence

providing leadership including managing cultural and political is-sues involving other parts of the organization (Thiry 2004 Shao2010) and external stakeholders To be effective as program man-agers it is necessary to obtain and process the right information toreduce ambiguity (Thiry 2004)

112 Challenges of megaproject execution

Megaproject stakeholders are numerous as is the diversity of their objectives (Shao 2010) Significant stakeholders in the oiland gas industry include National Oil Companies and Govern-

ments local communities NGOs with interest in socio-culturaland environmental sustainability employees (including the pro-

ject team) and shareholders With such a constellation of stake-holders it is inevitable that megaprojects will attract high socio-economic and political interest and high industrial and publicattention It is therefore key that the strategic goals of their spon-sors and stakeholders and how they are linked to the project itself are clear (Turner et al 2009) Usually megaprojects are placedunder high time and cost pressure (Merrow 1988 2003 Miller and Lessard 2000) Of the project managers surveyed in this re-search 85 indicated they were under moderate to very highcost and time pressure These pressures generate systemic influ-ences within projects For example it has been shown that time

pressure can impair decision quality (Chu and Spires 2001)

113 Strategic value in the oil and gas industry

Strategy realization the basis for megaprojects is principallyabout decision-making (Sull 2007) and the managers of mega-

projects are responsible for big and often high-consequence deci-sions (Klein 1989) Their decisions are a double-edged sword astheir interpretation of strategic issues affecting their projects di-

rectly influences how the team responds (downward influence)and how senior management perceives challenges (upward influ-ence)However studies show project managers havebeenineffec-tive at responding to emergent strategy and the integration of strategic intents with the results generated by these large long-duration projects (Thiry 2004 Morris and Jamieson 2004)Major players in the oil and gas industry have adopted a sustain-able development approach for determining the value of their longer-term strategies for growth and profitability (BP 2008Royal Dutch Shell 2008 ExxonMobil 2007) reflecting a re-sponse to the evolving reaction of society to the energy industryand its historical socio-economic and political impact All the

major players investigated expressed sustainable development astheir core business value for projects that will be executed in pur-suit of strategy Sustainable development objectives of these com-

panies are largely similar The commonly expressed strategicobjectives were

making significant socio-economic contribution to the society health safety security and environmental responsibility

(HSSE) economic profitability of the business earning the admiration of key stakeholders

The extent to which these strategic objectives are achieved

is taken as indicative of the worth (value) of any strategic re-sults obtained These sustainable development measures arealigned with the balanced score card for organizational perfor-mance evaluation (Kaplan and Norton 1996) and the DiamondApproach (Shenhar and Dvir 2007) suggested for projects Thediamond approach presents five main success dimensions for

projects

project efficiency impact on customers and users impact on project team business and direct organizational success

preparing for the future

Achievement levels of these sustainable development objec-tives were adopted in this study as the basis for indicating strate-gic value obtained from projects within the oil and gas industry

114 Decision theory in megaprojects

In a general sense a decision is a position opinion or judgment reached after consideration (Miller 2009) It is a cognitive phe-nomenon and the outcome of a complex process of deliberationwhich includes an assessment of potential consequences and un-certainties (Muumlller et al 2009) Skinner (1999) defined a decisionas a conscious irrevocable allocation of resources with the pur-

pose of achieving a desired objective indicating that it involves

3




thinking judgment and deliberate action So a decision is onlyregarded as such when it has been communicated someway andaccepted for implementation Basic elements of a decision processinclude information seeking ascription of meaning (interpreta-tion) applying a decision criteria and subsequent implementationaction (Thomas et al 1993)

Decision theory has its root in economic theory with the as-sumptions that people make decisions to maximize utility basedon self-interest and rationality (Skinner 1999 Mackie et al2007) the expected utility or normative decision theory Thishowever does not consider the possibilities or effects of moderat-ing or intervening factors that make decisions reference-dependent (Kahneman and Tversky 2004) Nonetheless expectedutility theory has been applied in the oil and gas industry withsome success (Mackie et al 2007) and has been the predominant model for normative decision making (Tversky and Kahneman1992) The theory is considered idealistic however because it fo-cuses on how people should make decisions (Mackie et al

2007) rather than how they actually make decisions (Skinner1999) Technical people in the oil industry have been observedto exhibit a tendency for normative approach to decision makingthereby weakening their ability to deal with uncertainty (Capen1976 Mackie et al 2007) Project management in the oil andgas industry is dominated by technical people and probablymore than a few are struggling with tendencies towards this nor-mative thinking phenomenon An alternative approach is the de-

scriptive decision theory Descriptive decision theory deals with how people actually

make decisions It postulates that people make decisions bychoosing ways to satisfy their most important needs even if they do not have all the required information and their choice

is not optimal (Mackie et al 2007) When people are facedwith making decisions under uncertainty they simplify the chal-lenge by relying on heuristics or rules of thumb (Kahnemannand Tversky 1979 Tversky and Kahneman 1992) that arelargely rooted in acquired knowledge and past experiencesThere are two relevant offshoots of descriptive theory

the theory of bounded rationality (Simon 1976 Kahneman2002)

prospect theory (Kahneman and Tversky 2004 1979)

Both recognize the ample limitation of human beings to be

rational most of the time and postulate that inductive thinkingis more natural (Arthur 1994 Kahneman 2002 Kahnemanand Tversky 2004)

Prospect theory explains decision making under risk(Kahneman and Tversky 2004 1979) which more realisticallyreflects megaprojects The theory distinguishes two phases in thedecision process framing and valuation Framing consists of a

preliminary analysis of the prospects offered (by the challenge)to the decision maker leading to a representative constructionof his or her perception of the challenge associated contingenciesand possible outcomes A heuristic simplification of perceivedrisks or challenges takes place such that the decision-maker canmake some meaning out of it During this phase the quantityquality and timeliness of information (information feed ) available

to the decision maker past experiences and knowledge about rel-evant subject matter will have huge effects on how he or shemodels the possible prospects which is the outcome of this pro-cess Information timelines have also been hypothesized as a fac-tor due to the time pressure that most project managers are underTime pressure affects decision-making (Hwang 1994) and infor-

mation suffers degradation when not delivered timely (Greer andKropp 1983) Valuation follows framing in which the decision-maker assesses the value of each prospect based on an ldquoopportu-nity-threat rdquo or a ldquogain-lossrdquo principle and then chooses accord-ingly (Thomas et al 1993 Kahneman and Tversky 2004)Prospects are consequently labeled for example as ldquoopportunityrdquo

or ldquothreat rdquoUltimately the aim of decision-making is to minimize sur-

prises which arise from mismatches between what actually hap- pens and what was expected to happen (Gharajedaghi 1999)Four reasons largely related to the management of informationto support decisions have been advanced for why mismatches

can occur following decisions (Gharajedaghi 1999)

1 wrong information or input datamdasha decision process problem2 wrong implementation of what was decided3 change in the assumed context after the decision was made

(such as business or social context around the project)This may be caused by poor awareness of the environment or by a chance event

4 the decision itself may be fundamentally flawed in qualitywhich would be a problem with the decision approach or

process

115 Information-feed in decisions

Various studies have established that the root cause of almost all project failure can be traced back to human error or misjudg-ment (Johnson 2006 Virine and Trumper 2008) and poor judg-ment can often be traced back to the way the decisions were made(Hammond et al 1998) As making decisions is considered themost important job of any executive (Hammond et al 1998)the ability to make right decisions on projects should be a principalindicator of project management professionalism Unfortunatelydespite the reported moderate-to-poor performance of megaproj-ects (Merrow 2003 Miller and Lessard 2000 Fayek et al2006) many project managers presume their decision-making ca-

pabilities are above average (Massey et al 2006) and conse-

quently care little about improving the quality (Capen 1976Goodwin and Wright 2004 Virine and Trumper 2008) This at-titude could influence the rigor of their approach to seeking infor-mation in support of decision-making and potentially result inmore wrong judgment than should have been otherwise

Information feed (or scanning) (Thomas et al 1993) in-volves searching external (Coulter 2000) and internal(Thomas et al 1993) environments to identify important issuesor events that could affect the organization and its objectives It is a key element of the decision process enabling managers toformulate expectations about the future (Greer and Kropp1983) As top decision-makers will usually have access to far more information than they can deal with (Mintzberg 1978Thomas et al 1993) they become selective in favor of

4




information they consider to be most useful It has been estab-lished that decision-makers who use more information tend to

be more comfortable in dealing with ambiguity and uncertaintyand consequently more positive with labeling their challenges(Thomas and McDaniel 1990) Externally-focusedinformation-feed in particular is considered more influential in

facilitating this (Thomas et al 1993 Coulter 2000) Thosewho are positive with labeling (as suggested by prospect theo-ry) tend to project positive outcomes with expectations of ldquogainrdquo or ldquoopportunityrdquo (Dutton and Jackson 1987) rather than ldquolossrdquo or ldquothreat rdquo They also tend to have a fair amount of control on organizational or project direction In contrastldquothreat rdquo labeling implies a negative situation in which a likelyloss is projected by the decision maker and over which he or she feels relatively little control (Dutton and Jackson 1987)

Early detection of system disturbances is enhanced throughgood and timely information-feed (Dutton and Duncan 1987)allowing for pro-activeness Less timely information is generally

considered inferior because the managers expectations will con-tain greater error (Greer and Kropp 1983) On the other hand de-cision makers tend to use less information when they believe theyare knowledgeable about their business environment or situationthan when they feel it is poorly understood (Thomas andMcDaniel 1990) Decision makers may sometimes not be right in this judgment however The quality and quantity of informationavailable to decision-makers in business organizations was foundto correlate with the quality of their decisions (Thomas et al1993 OReilly 1982) As project management is similarly under-

pinned by decisions one can expect that the information-feed tothe project manager (as a key decision-maker) will influence pro-

ject performance and derivable strategic value

The extent to which a business leader or project manager feels in control of strategic issues is an important influenceon how information gathering towards decision support andinterpretation will be approached (Thomas et al 1993Kahneman 2002 Muumlller 2003) Several studies have arguedthat most people see threats as uncontrollable and that oppor-tunities are characterized by a high degree of controllability(Thomas and McDaniel 1990) This study investigatedsense of controllability as a measure of the extent to whichthe project manager feels in charge of the project The levelof confidence of being in control would largely be influenced

by how the project manager perceives the quality and effec-

tiveness of risk management on the project Based on theworks of Morris and Hough (1987) Miller and Lessard(2000) and initial interviews of seven project managers(with a combined experience of 130 years) during the earlystages of this study ten areas of greatest challenges on mega-

projects were identified

1 contracting and procurement management2 government relations management (as McKenna et al

2006 noted the decision mechanisms of host govern-ments are often unclear and can lead to significant complications)

3 host community relations management4 joint venture interface management

5 health safety security and environmental (HSSE)6 multi-location management of fabrication and facilities

integration7 implementation of local content policies8 project governance9 managing the core project team (individual aspirations

job satisfaction etc) including attaining cohesion withinthe broader team and

10 impact of multi-cultural leadership within the project

These challenges are consistent with what Miller andLessard (2000) identified as the top failure factors in large pro-

jects Most of the challenges are political and social with poten-tial to affect decision-making Technical risks seem lesschallenging Overall governance remains a challenge onmany megaprojects (Miller and Lessard 2000) and factors re-lated to technical content and project-economics seem to have

less significant impactsThis discussion informed two hypotheses for the study

H1A The information-feed in support of the project managersdecision on oil and gas megaprojects will have a significant in-fluence on the level of derivable strategic value

H1B The magnitude of external focus within the informationfeed in support of the project managers decisions on oil andgas megaprojects will correlate positively with the long-termstrategic value realized

H2 The project managers perception of his or her level of controllability will significantly influence information feed on

the project

116 Contextual influences on project decisions

Organizational (Thomas et al 1993) personal and project characteristics (Muumlller et al 2009) are contextual factors andmay influence decision-making For example they could influ-ence the project managers approach to information feed andhow challenges may be classified as ldquothreats or opportunitiesrdquo

(Ford 1985)mdasha moderating influence In particular what a project manager perceives as important to senior management (an or-ganizational context) is expected to influence his or her management priorities hence decisions This also informs the

project managers perception of how he or she may be measuredhence his or her behavior Literature on organizational behavior and decision making also infer that experience plays an important role in decisions (Kahneman 2002) and has a positive relation-ship with decision outcomes (Dane 2008) So the project man-agers professional experience (a personal context) could beexpected to influence the information framework adopted onthe project hence potential impact on strategic outcomes Thisdiscussion informed the third hypothesis

H3A The project managers perception of senior management drivers (an organizational context) will moderate the relationship

between information-feed and strategic value from oil and gasmegaprojects

5




H3B The project managers professional experience (a personalcontext) will moderate the relationship between information-feedand strategic value from oil and gas megaprojects

117 Research model

Fig 2 illustrates the hypotheses and represents the research

model for the study

12 Methodology

The study perspective taken is the descriptive decision theo-ry school and the research questions demanded analyzing his-torical data from practitioner experiences on megaprojects Weadopt a positivist epistemology and test the three hypothesesusing a deductive research design applying a quantitative ap-

proach of probabilistic survey sample requiring minimal inter-ference with the research objects (Czaja and Blair 2005Cooper and Schindler 2006) The primary target population

was the managers of megaprojects employed by oil and gascompanies These are people with responsibility for entiremegaprojects or substantial parts of them The survey question-naire was pre-tested on five senior project managers and refined

based on pre-test results before the actual survey which wasweb-based Results analyzed did not include those from the

pilot All scaled responses were based on a 5-point Likert scale and reliability checks were done at sub-scale level(Field 2009) The main variables were summarized by takingmeans of their underlying sub-variables Data reliability and va-lidity is discussed within succeeding sections The hypotheseswere tested using results from bi-variate correlation analysis

ANOVA and multiple regressions including moderated hierar-chical regression (MHR) analysis

121 Independent variables

There are two independent variables in the research model

1211 Information feed (scanning) Elements measuredwere the quantity quality and timeliness of information gath-ered by project managers These were combined to form theconstruct variable Information-Feed Deriving from how the

questions were constructed these same sub-variables couldalso be segregated as internally or externally focused informa-tion as a means of further sensing where problems may be com-ing from The components of Information-Feed included

1 Performance information on corporate financial services

HR management and performances (Corporate Perfor-mance factor )

2 Information on ldquo pulserdquo of internal and external stakeholders(Stakeholder Pulse factor )

3 Information on project efficiency stakeholder management benchmarks etc ( Project Performance factor )

4 Timeliness of information to the project manager towardsdecision-making ( Information Timeliness factor )

Measurement items for this scale were adapted from litera-ture and previous research works (Thomas et al 1993 Gioia1986) This is also the dependent variable for Hypothesis H2

1212 Controllability (sense of control) This measurement was based on how threatened the project manger felt about the ten areas of greatest challenge derived from literature andthe qualitative interview of senior project managers discussedearlier in this paper (refer to the section on ldquoInformation-feedin decisionsrdquo) The perceived significance of the risks posed

by each challenge formed the basis of measuring how well incontrol project managers felt

122 Moderating variables

There is one moderating variable in the research model

1221 Contextual The variable has two main componentsFirst was the project managers perception of what his or her se-nior management drivers were for example cost schedulestakeholder management safety quality economics etc Thesecond was information on the project managers professionaltenure obtained as a measure of experience (Garvey andReimers 1979 Crawford 2007) To further understand thecontext of responses some categorical and ordinal data on com-

pany type demographics role on project project cost and so onwere gathered

123 Dependent variable

There is one dependent variable in the model

1231 Strategic value Strategic value was measured fromthe viewpoint of the executing project managers Items mea-sured were those sustainable development goals found commonto the super-majors and they center around earning the admira-tion of key stakeholders and economic performance namely

Value to Partners how well project performance is alignedwith corporate objectives and aspirations of the host govern-ment and co-venturers on the project

HSSE Compliance health safety security and environmen-tal performance on the project towards ensuring that theasset delivered can be safely operatedFig 2 Research model

6




Profitable Asset Performance economic profitability fromoperating the asset delivered by the project

Value to Host Community making significant socio-economic contribution to the society

These variables have not been weighted in this study

13 Analysis

131 Data and sample characterization

A total of 107 responses were received out of which 69 wereused in the analysis Responses from non-oil and gas project managers (N=8) and low input responses (N=30) wereeliminated The sample size exceeds the minimum requirement of 5 cases per variable for regression (Tabachnick and Fidell1989) as over 12 cases per regression variable was achievedWhile all the projects are considered major due to reportedcomplexity about 15 of them cost less than $1 billion The

projects analyzed were spread across all regions of the worldMiddle East Far East Australasia Africa Europe NorthAmerica South America and RussiaCaspian The largest number of projects were in Africa (35) and the least in SouthAmerica (b5) Almost 90 of respondents said their project were joint ventures showing that most oil and gas companiesconsider megaprojects as too risky for single-company sponsor-ship Such relationships however could complicate project execu-tion due to challenges of obtaining consensus About 80 of the

projects analyzedwere completed within the last 6 years which isabout 25 of the typical life-span of deliverables from a mega-

project While longer-term value is of course not fully realizedwithin 25 of the assets operational life this should be enough

time to permit evaluation of the long-term strategic value indica-tors as proposed in this study

An analysis of variance (ANOVA) was done on the meanscores of industry types observed statistical modes of project costs and the roles of respondents on projects Results indicatedthat there were no significant differences in mean (pN01) henceall responses could and were analyzed as a single data set Datareduction was implemented using factor analysis For instancethe variables in the long-term strategic value construct was re-duced from 6 to 4 groups information feed construct increasedfrom 3 to 4 variables variables in ldquocontrollabilityrdquo and ldquosenior management driver rdquo constructs were reduced into 4 groups each

The construct variables as described above formed the input tothe regression analyses that tested the hypotheses Regression re-sults showing standardized beta values of all significantly influ-ential factors are presented in the appendix

2 Results and discussion

21 Information-feed in support of project manager decisions

( H1A and H1B )

All four subvariables that make up the information feed con-struct were regressed as a block and in a stepwise backwardentry mode with each of the strategic value subvariables Thisregression algorithm eliminates non-significant variables and

therefore does not present the beta values of such variablesThe block approach (rather than regression of each informationfeed variable) better simulates the reality of simultaneous oc-currence and interactive influences of the factors (subvariables)on each other Two of the four information feed factors infor-mation on stakeholder pulse and project performance signifi-

cantly influenced long-term strategic value indicators whilecorporate performance information and information timelinessdid not (see Table 1) The table shows the significant standard-ized Beta values All R 2 values are above the 002 trivialitythreshold (Cohen 1988 Muumlller 2003) In general the resultsshow that long-term strategic value is influenced by informa-tion feed during project execution hence supporting Hypothe-sis H1A Note that almost 40 of the variance on themeasure of how much the venture partners (strategically) val-ued the project is explained by information feed indicatingthe importance of adequate and quality information in securing

partner goodwill

The corporate performance information factor had the low-est score (mean=296) confirming that project managers areright to give it the least attention compared to other informationfeed factors Of all the information feed factors evaluated in thissample information timeliness received the greatest attentionfrom project managers (mean score of 368) despite its insignif-icance to long-term value This is likely to be achieved at someexpense of quality and adequacy While it is true that poor tim-ing of information can degrade information value (Greer andKropp 1983) and hinder proactiveness this problem howeverseems more salient with regard to short-term decisions whichare required to manage the tactical objectives on megaprojectsIt thus seems more information-gathering energy is put where it

is least needed information timelinessmdashan indication of the prevailing short-term focus in decision-making

Integrating project performance information into project man-ager decisions has a double-edged influence a positive influenceon promoting project value to direct investor partners whileexerting a negative influence on similar value to host communi-ties who have their interest mainly tied to the benefits they expect to receive from the project (and not the anticipated benefits to thecorporation) So when attention to host community relations is

poor good project performance will mean little to the communi-ties The mean score of 29 associated with how host communi-ties valued projects in the sample studied is below average and

the lowest of all long-term strategic value indicators (30 is neu-tral) indicative of predominant apathy to the projects by host communities So the negative correlation between project perfor-mance information and project value to host communities should

be expected In fact from our experience communities can be-come antagonistic as a way to express their perception that corpo-rate gains are being made at their expense

Information on stakeholder pulse had the greatest influenceacross all long-term strategic value indicators (see Table 1) The

pulse measured is of those stakeholders outside the project team(such as government joint venture partners host communitiesand asset operators) so it is an externally focused informationvariable The results show that project managers are more effec-tive in creating value when they are able to factor information

7




on current stakeholder pulse into their decisions This supportsHypothesis H1B and indicates that project managers level of

awareness of relevant events and trends in the external environ-ment surrounding their megaproject does significantly affect thequality of their decisions and consequently the long-term valueobtained from the megaproject It also underscores the strong in-teraction of megaprojects with society This result aligns withoutcomes of similar studies in organizational management (Thomas et al 1993) and with Coulters (2000) claim that exter-nal environment analysis is very important to successful strategicmanagement in business organizations

22 Sense of controllability and information-feed system ( H2 )

All controllability factors mean scores were less than 30

(Table 2) By these low ratings megaproject managers confirmedthey felt exposed to key execution risks Based on prospect theo-ry cases like this where project managers feel inadequately incontrol imply that they will have higher tendency of negative(threat) valuations of prospects presented by challenges on their

projects and therefore frequently prone to expecting poor perfor-mance than success This is not a good psychological state to bein frequently especially for megaproject managers that influencesuch significant amount of corporate resources A noteworthy ob-servation is that the significant risk factors have to do with

relationships that are largely external to the project teammdashfor ex-ample government contractor and project governance This is ev-

idence of the strong external interest in and the influence of governance issues on megaprojects as compared to traditional projects This supports findings from earlier studies (Miller andLessard 2000 Jaafari 2004) Miller and Lessard (2000) conclud-ed that the quality of relationships with human institutions is amajor success factor on large projects These external influenceson megaprojects which are by nature volatile and dynamic cannot

be wished away They tend to wrestle control from project man-agers and can affect the core business if not well managed(Cattaneo 2009)

Except for mitigations against risks from team characteristics(pb01) all the controllability factors were significantly influen-tial on information feed at the pb005 level It follows that in de-

signing the information feed framework for megaprojects the project manager should ensure that controllability concerns areadequately factored in for example in securing quality datathat enable status monitoring in the identified risk exposure areas

Interestingly the quality of mitigation against risks from con-tractor relations has a negativeinfluence on two factors corporate

performance information (beta=minus419) and information timeli-ness (beta=minus239) This suggests that project managers tend togive less emphasis to securing corporate information and pursu-ing timeliness of information as the project teams relationship

Table 1Regression result of information-feed (IV) and strategic value (DV)

Dependent variables

Value to partners HSSE compliance Pro1047297table asset Value to host com

Independent variables Information on Mean 396 323 352 290Corporate performance 296

Stakeholder pulse 312 484 374 340 538

Project performance 365 277 minus193

Information timeliness 368R 2 385 140 116 289Regression F 2062 1091 876 1217

pb01 pb005 pb001 pb 001

Table 2Regression result of controllability factors (IV) and information feed (DV)

Dependent variables information on

Corporate performance Stakeholder pulse Project performance Timelines

Independent variables Mitigation of risks from Mean 296 312 365 368Team characteristics 232 258

Govt relations 276 316

Contractor relations 214 minus419 minus239

Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8




with contractors gets better The storyline implied here is that ascontractor relationships improve on the project information shar-ing becomes more qualitative and proactive hence the relevanceof corporate performance information and information timelinesscould become lower to the project manager The reverse may be

painfully untrue though when contractor relations are suboptimal

as getting more timely information orand quality corporate per-formance information cannot substitute for the cultivation of good relationships between contractors and the project teams

Three underlying elements of the controllability factorswhere project managers said they experienced most vulnerabil-ity with risks were multi-location execution (mean=197) andHSSE management (mean=203) both associated to the pro-

ject team also contracting and procurement (mean= 206) anelement associated with contractor relations risks (Table 3)

Of the three only the contracting and procurement risk mitiga-tion element that underlies the controllability factor identified ascontractor relations has a significant relationship with

information-feed hence should receive the greater attentionThe few project managers who felt more in control (those withrisk mitigation capabilityge40) were clearly differentiated bytheir approach to information feed They used better-quality in-formation more consistently Their mean scores on a scale of 5were 30 or higher or 10 to 30 higher than those of lower-

performing megaprojects

23 Contextual influences ( H3A and H3B )

This hypothesis was tested by moderated hierarchical regres-sions based on recommendations by Sharma et al (1981) for identifying and analyzing moderator variables All subvariables

of ldquoinformation feedrdquo and ldquosenior management priorityrdquo con-structs were centered and cross-product terms were createdthereafter (Jaccard et al 1990 Eweje 2010) The interactiveinfluences from the regressions results is summarized belowin Tables 1 and 2 while Tables 4 to 8 contain the detailsThree of the four senior management drivers have significant moderating influences on how the megaproject managers deci-sions create long-term value These three drivers are

ldquoachieving profitable operationsrdquo which purely moderatesthe impact of Project Performance information feed on

Strategic Value to Partners (Tables 4 and 5) and quasi mod-erates the impact of Corporate Performance information feedon Strategic Value from Profitable Asset Performance(Tables 4 and 6)

ldquostakeholder support rdquo is a pure moderator of the impact of Project Performance information feed on Strategic Value to

Partners (Tables 4 and 5) and a pure moderator of the impact of Corporate Performance information feed on StrategicValue to Host Communities (Tables 4 and 7)

ldquo project schedulerdquo is a pure moderator for the impact of Information-feed on Stakeholder Pulse on Strategic Valueto Host Community (Tables 4 and 8)

This result indicates that project managers are allowing their awareness of senior managements drivers to influence their value-creating decisions Consequently Hypothesis H3A issupported

The results though show that the HSSE-Quality variable as aldquosenior management driver rdquo was not significant in influencing

project managers decisions toward long-term value as wasexpected (see Table 4) Similarly no significant moderating ef-fect was established on the strategic value indicator ldquoHSSE com-

pliant operationrdquo In essence despite acclamation of HSSE as ahigh priority and core value in the annual reports of oil and gasindustry companies megaproject teams attentiveness to HSSEappears to lag behind senior management rhetoric This was asurprising finding indeed as the logical expectation is that suchstrong management emphasis on this driver should influence de-cisions Another study extending this one did show that the high

preference for efficiency (for example schedule and cost) among

company executives during the execution phase of megaprojectsis counterproductive and did lessen project managers focus onHSSE and quality issues (that is a negative correlation) makingthe company rhetoric less influential (Eweje 2010) As suggested

by Irwin and Baron (2001) circumstances or context issues cansometimes provoke decision makers to override or inconsistentlyapply their corporately stated values In the case of this study theorganizational context of intense pressure for high project

Table 3Scores for underlying variables of controllability

Underlying variables controllability Mean

Risk mitigation capabilityContracts and procurement 206Government relations 255Host community 300Joint venture 248HSSE 203Multi-location 197Local content 272Project governance 265Project team 243Cultural diversity 287

Team cohesion 425

Table 4Summary of the moderating effect of the relationships between ldquoInformation

Feed Variablesrdquo

and ldquo

Strategic Value Variablesrdquo

by ldquo

Senior Management Driversrdquo

Independent variableinformation feed

Dependent variable strategic value

Value to partners

HSSEcompliance

Pro1047297tableasset

Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS

Project perform P SS POInformation

timeliness

Legend P=pure moderator Q=quasi moderator

Significant senior management drivers PO= profitable operations SS= stakeholder support PS=project schedule

9




efficiency performance provoked an inconsistent response of megaproject managers to the core value of HSSE

The project management experience variable surprisinglyalso did not produce any significant interaction in the regressionswith each of the information feed subvariables Hence Hypothe-sis H3B is not supported Dane (2008) explained this phenome-non by contending that ldquo procedural experiencerdquo ldquotacticalexperiencerdquo and ldquolocalized experiencerdquo rather than simply ldquo pro-fessional tenurerdquo (that is number of years practicing a profession)

explain decision effectiveness Procedural experience is the capa- bility to adhere to the rules and procedures that govern a profes-sion tactical experience is that derived from historicalencounters with similar situations and localized experience is fa-miliarity with the techniques strategies and likely positions of other professional players and business leaders within the areaof operation Other studies have established that a professionalsability to make accurate judgments does not necessarily improveover time (Dawes et al 1989 Camerer and Johnson 1991) Thisnon-improvement in quality of judgment despite increasing ten-ure on the job has been attributed to professionals not doingenough to recognize or overcome their cognitive biases hencelimiting their opportunity to learn from their experiences despiteincreasing professional tenure (Dane 2008)

3 Conclusions and recommendations

We proposed two research questions

which factors of information-feed supporting a project man-agers decision impact the strategic value delivered bymegaprojects for the sponsoring organization the most


We haveestablished there is a significant relationship betweeninformation-feed during the execution phase of oil and gas mega-

projects and the long-term strategic value of the project withexternally-focused information types having the greatest influ-ence The four components of information feed studied have asignificant impact on the four components of strategic value weidentified from the literature search Information on stakeholder

pulse however has the greatest impact When relationship withhost communities is not so good information about project per-formance has an adverse impact on value to the host communitywith improvements to one leading to lower performance in theother We saw that the quality of the project managers decisionswill be influenced by their perception of the desires of senior management but surprisingly not by their tenure practicing the

project management profession If project managers can better understand how the quality of information feed influences their

Table 5Moderation of relationship between ldquoProject Performance informationrdquo andldquoStrategic Value to Partnersrdquo by ldquoSenior Management Driversrdquo

Variable entered Dependent variable strategicvaluemdashvalued by partners

(Govt and JV )

Strategic value (N= 69)Step 1 Step 2 Step 3

Information on project performance 411 403 392

Perception of SNR MGT (SM) driver mdashSTKHOLDER SUPPT

minus017 121

Perception of SNR MGT (SM) driver mdash profitable asset operation (OPS)

156 097

Perception of SNR MGT (SM) driver mdashHSSEQ

061 051

Perception of SNR MGT (SM) driver mdash project schedule

018 minus015

Info on project performancetimes SM driver (stakeholder support)

295

Info on project performancetimes SM driver

(profitable asset ops)

275

Info on project performancetimes SM driver (HSSEQ)

minus204

Info on project performancetimes SM driver (schedule)

minus210

F for regression 1358 323 383

F for change 1358 070 017

R-square 0169 0204 0369

Main table contains standardized coefficient betasVIFb5 ple010 ple005 ple001 ple0001

Table 6Moderation of relationship between ldquoCorporate Performance informationrdquo andldquoStrategic Value from Profitable Asset Performancerdquo by ldquoSenior Management Driversrdquo

Variable entered Dependent variablestrategic valuemdash

profitable asset

performance

Strategic value (N= 69)

Step 1 Step 2 Step 3

Info on corporate performance 147 178 144Perception of SNR MGT (SM)

driver mdashSTKHOLDER SUPPTminus050 minus122

Perception of SNR MGT (SM)driver mdash profitable asset operation (OPS)

287 278

Perception of SNR MGT (SM) driver mdashHSSEQ minus119 minus078Perception of SNR MGT (SM)

driver mdash project scheduleminus053 minus111

Info on Corp PerftimesSM driver (stakeholder support)

minus012

Info on Corp PerftimesSM driver (profitable asset ops) 414

Info on Corp Perf timesSM driver (HSSEQ) 042Info on Corp PerftimesSM driver (schedule) minus061



R-square 0022 0090 0258


10




decisions they would be positioned to take better decisions andimprove the performance of the megaprojects they are managing

The results also suggested that most managers of megaproj-ects felt exposed to key execution risks It was also found that the quality of risk mitigation on megaprojects does significantlyinfluence information feed to the project Hence the design of information-feed systems for megaprojects should be risk-

based The level of clarity on information requirements for project decision support and how the desired information can bequalitatively obtained and managed can be seen as critical indica-tors of how well a megaproject is positioned for success A fram-ing session to address decision support is recommended very

early in the execution phase Suggested issues to address includeidentification of key decision areas critical to project success andwho the responsible parties are what the major exposures for the

project are what information is needed to support quality deci-sions sources of data acquisition and how to secure data of ade-quate quality and establishing a decision framework

This study shows that a superior risk management systemenhances a project managers sense of control over the project and better positions the manager to make value-creating deci-sions Recognizing the major areas of risk exposure and factor-ing them into the information feed framework was found toultimately improve the quality of decisions The informationfeed system should especially keep the project manager ap-

prised of performance in risk areas particularly areas with

weak mitigation in place so as to foster proactive interventionsThis makes investing in a qualitative project risk coordinator akey resource in support of decisions The stronger the project managers sense of control is over risk exposures the morelikely his or her project information feed system will create bet-ter long-term strategic value Most important aspects to focuson towards achieving a good sense of control on megaprojectsare managing risks from contracting and procurement relationsin addition to paying good attention to other soft issues such as

project governance government relations and managing the

challenges that social diversity and geographic dispersion pose to the project team

People tend to uphold values more strongly in contexts wherethey are buying or have something to gain whereas they tend tocompromise values when selling giving up or losing something(Irwin 1994) Consequently the behavior of most project man-agers within this study sample in ascribing inadequate signifi-cance to HSSE as a core value is indicative of a fear of loss It is likely they have greater fear of defaulting on cost and schedulethan on HSSE In almost all probability senior management or the project decision board by their actions are giving the impres-sion that project efficiency such as cost and schedule should takehigher priority contrary to their rhetoric on core values for exam-

ple HSSE Senior managers need to be aware of their conscious

Table 7Moderation of relationship between ldquoCorporate Performance informationrdquo andldquoStrategic Value to Host Communitiesrdquo by ldquoSenior Management Driversrdquo

Variable entered Dependent variablestrategic valuemdashvalued

by host communities


Info on corporate performance 194 249 298

Perception of SNR MGT (SM)driver mdashSTKHOLDER SUPPT

minus264 minus123


408 302



Info on Corp Perftimes SM driver (stakeholder support)

435

Info on Corp Perftimes SM driver (profitable asset ops)

minus092

Info on Corp PerftimesSM driver (HSSEQ) minus

185Info on Corp Perf timesSM driver (schedule) 078



R-square 0038 0204 0350


Table 8Moderation of relationship between ldquoInformation on Stakeholder Pulserdquo andldquoStrategic Value to Host Communityrdquo by ldquoSenior Management Driversrdquo

Variable entered Dependent variable strategicvaluemdashvalued by host

communities


Information on stakeholder pulse 485 420 350


minus149 minus230


218 107


minus045 046


minus036 104

Info on Stakeholder Pulsetimes SM driver (stakeholder support)

108

Info on Stakeholder Pulsetimes SM driver


minus092

Info on Stakeholder Pulsetimes SM driver (HSSEQ)

110

Info on Stakeholder Pulsetimes SM driver (schedule)

330



R-square 0235 0282 0406


11




and subconscious practices for rewarding performance as it would influence project team behaviors

The inconclusive judgment on the influence of project manag-er experience on information-feed can be corrected by future re-search that would consider the influence of procedural tacticaland localized aspects of professional experience as suggested

by Dane (2008)The limitations of the study are in the relatively small sam-

ple size and low R 2 values Sixty-nine responses to the ques-tionnaire limit the generalizability of the results Larger variations by country and project size and type do seem likelydue to relatively few responses spread globally This is also in-dicated by the relatively low levels of practical significance(R 2) shown in Table 2 Careful application of the results in

practical settings is advised and should be preceded by a com- parison of the settings at hand with the settings described How-ever the value of this study may extend well beyond the oil andgas industry to the extractive and energy industries in general

and perhaps to other industries that execute megaprojects Care-ful application may be necessary where characteristics of the business environment differ significantly from those of the oiland gas industry for instance in space and aviation So an ex-tension of the study to other industries or to social or govern-ment organizations where megaprojects are instruments of strategy realization will be useful as a validation While thisstudy has established that there are significant links betweeninformation-feed in support of decision-making by project managers and strategic value derivable from megaprojects it has not come up with what a viable information management system directly supporting the project manager in his or her de-cision could be A research that could come up with a simple

and easy-to-use information management system primarily fo-cusing on supporting the megaproject managers decision-making would be a good complement to this study It wouldalso be an important aspect of enhancing the decision frame-work for these project managers that could potentially havehuge influences on corporate strategic direction

References

Arthur WB 1994 Inductive reasoning and bounded rationality The AmericanEconomic Review 84 (2) 406ndash411

Asrilhant B Dyson RG Meadows M 2007 On the strategic project man-

agement process in the UK upstream oil and gas sector Omega 35 89ndash103

BP 2007 Our key priorities safety people performance Annual Review BPLondon

BP 2008 Sustainability Review BP LondonBrower J Gilbert C 2007 How managers everyday decisions create mdash or de-

stroy mdash your companys strategy Harvard Business Review 85 (February)72ndash79

Camerer CF Johnson EJ 1991 The processndash performance paradox in expert judgment how can experts know so much and predict so badly In EricssonKA Smith J (Eds) Towards a General Theory of Expertise Prospects andLimits Cambridge Press New York pp 195ndash217

Capen EC 1976 TheDifficulty with Assessing Uncertainty Society of PetroleumEngineers SPE 5579

Cattaneo B 2009 The New Politics of Natural Resources Time for ExtractiveIndustries to Address Above-ground Performance ERM Consulting Services

Worldwide London UK

Chu PC Spires EE 2001 Does time constraint on users negate the efficacy of decision systems Organizational Behaviour and Human Decision Processes85 (2) 226ndash249

Cohen J 1988 Statistical Analysis for Behavioural Science 2nd editionHillsdale NJ ErlbaumCooke-Davies T 2002 Establishing the Link Be-tween Project Management Practices and Project Success in Proceedings of the 2nd PMI Research Conference Project Management Institute Seattle

July Newtown Square PACooper DR Schindler PS 2006 Business Research Methods 9th edition

McGraw-Hill Irwin NYCoulter M 2000 Strategic Management in Action 2nd edition Prentice Hall

New YorkCrawford LH 2007 Developing individual competence In Turner JR

(Ed) The Gower Handbook of Project Management Aldershott Gower pp 677ndash694

Czaja R Blair J 2005 Designing Surveys mdash A Guide to Decisions and Pro-cedure 2nd edition Sage London

Dane E 2008 Examining experience and its role in dynamic versus staticdecision-making effectiveness among professionals In Solomon G(Ed) Best Paper Proceedings of the Annual Meeting of the Academy of Management Anaheim August Academy of Management New York

Dawes RM Faust D Meehl PE 1989 Clinical versus actuarial judgment

Science 31 1668ndash1674Dutton JE Duncan RB 1987 The creation of momentum for change

through the process of strategic issue diagnosis Strategic Management Journal 8 279ndash295

Dutton JE Jackson SE 1987 Categorising strategic issues link to organi-zational actions Academy of Management Review 12 76ndash90

ExxonMobil 2007 Annual Summary Report 2007 ExxonMobil CorporationEweje J A 2010 Investigating factors that affect project manager decisions

on oil and gas megaprojects and how they impact the realisation of strategicvalue PhD thesis Lille SKEMA Business School

Fayek AR Revay SO Rowan D Mousseau D 2006 Assessing perfor-mance trends on industrial construction mega projects Cost Engineering 48(10) 16ndash21

Field A 2009 Discovering Statistics Using SPSS 3rd edition Sage LondonFlyvbjerg B Bruzelius N Rothengatter W 2003 Megaprojects and Risk

An Anatomy of Ambition Cambridge University Press Cambridge UKFlyvbjerg B 2007 Truth and lies about megaprojects Faculty of Tech-

nology Policy and Management Delft University of Technology Sep-tember 2007

Ford JD 1985 Theeffect of casual attributions on decision makers responsesto performance downturns Academy of Management Review 10 (4) 770ndash786

Garvey N Reimers CW 1979 Toward a better measure of work experienceWorking Paper No 499 Princeton University Department of EconomicsIndustrial Relations Section

Gharajedaghi J 1999 Systems Thinking Managing Chaos and ComplexityButterworth Heinemann London

Gioia DA 1986 Symbols script and sensemaking creating meaning in theorganizational experience In Sims HP Gioia DA (Eds) The ThinkingOrganization Jossey-Bass San Francisco CA pp 49ndash74

Goodwin P Wright G 2004 Decision Analysis for Management Judgment

3rd edition Wiley Chichester UKGreer WR Kropp DH 1983 The incremental benefits of changes in the

timeliness of information Information Management 6 (6) 329ndash336

Grun O 2004 Taming Giant Projects mdash Management of Multi-organizationalEnterprises Springer Verlar Berlin

Halman JIM Braks BFM 1999 Project alliancing in the offshore industryInternational Journal of Project Management 17 (2) 71ndash76

Hammond JS Keeney RL Howard R 1998 The Hidden Traps inDecision-Making Havard Business Review January 1ndash11

Hwang MI 1994 Decision making under time pressure a model for informa-tion systems research Information Management 27 (4) 197ndash203

Irwin J 1994 Buyingselling price preference reversals preference for envi-ronmental changes in buying versus selling modes Organizational Behav-iour and Human Decision Processes 60 431ndash457

Irwin J Baron J 2001 Values and decisions In Hoch SJ Kunreuther HC

Gunther RE (Eds) Wharton on Making Decisions Wiley New York

12




Jaafari A 2004 Modelling of large projects In Morris PWG Pinto JK(Eds) The Wiley Guide to Managing Projects Wiley New York

JaccardJ Turrisi R Wan CK 1990 Interaction Effects in Multiple RegressionSage Newbury Park CA

Johnson J 2006 My Life Is Failure The Standish Group International West Yarmouth MA

Kahneman D 2002 Maps of Bounded Rationality A Perspective on Intuitive

Judgement and Choice Nobel Prize lecture December 8Kahnemann D Tversky A 1979 Prospect Theory An Analysis of Decision

Under Risk Econometrica 47 263ndash291

Kahneman D Tversky A 2004 Prospect theory an analysis of decisionunder risk In Shafir E (Ed) Preference Belief and Similarity SelectedWritings Massachusetts Institute of Technology Cambridge MA

Kaplan RS Norton DP 1996 The Balanced Scorecard Harvard BusinessSchool Press Cambridge MA

Klein RL 1989 Mega projects views of a Fluor Project manager In KimmonsRL Loweree JH (Eds) Project Management mdash A Reference for Profes-sionals Marcel Dekker New York and Berlin

Mackie SI Begg SH Smith C Welsh MB 2007 Decision type mdash a keyto realising the potential of decision making under uncertainty APPEAJournal 2007 (1) 309ndash319

Massey C Robinson D Kaniel R 2006 Cant wait to look in the mirror the

impact of experience on better-than-average effect Proceedings of the An-nual INFORM Meeting Pittsburgh PA November 5ndash8

McKenna GM Wilczynski H Van der Schee D 2006 Capital Project Ex-ecution in the Oil and Gas Industry Increased Challenges Increased Oppor-tunities Booz Allen Hamilton

Merrow EW 1988 Understanding the Outcomes of Megaprojects A quanti-tative Analysis of Very Large Civilian Projects The RAND CorporationSanta Monica CA

Merrow EW 2003 Mega-field developments require special tactics riskmanagement Offshore 63 (6) 90ndash92

Miller GA 2009 Wordnet mdashAbout us WordNet Princeton University http wordnetprincetonedu

Miller R Lessard DR 2000 The Strategic Management of Large Engineer-ing Projects mdash Shaping Institutions Risks and Governance MIT PressCambridge MA

Mintzberg H 1978 Patterns in strategy formulation Management Science 24(9) 934ndash948

Morris PWG Jamieson A 2004 Translating Corporate Strategy into Pro- ject Strategy Realising Corporate Strategy Through Project ManagementProject Management Institute Newtown Square PA

Morris PWG Hough GH 1987 The Anatomy of Major Projects A Studyof the Reality of Project Management Wiley Chichester UK

Muumlller R 2003 Communication of information technology project sponsorsand sellers in buyer-seller relationships DBA Thesis Henley Management College Henley-on-Thames UK

Muumlller R Spang K Oumlzcan S 2009 Cultural differences in decision making in project teams International Journal of Managing Projects in Business 2 (1)70ndash93

Murray-Webster R Thiry M 2000 Managing programmes of projects InTurner JR Simister SJ (Eds) Gower Handbook of Project Manage-

ment Aldershott Gower pp 47ndash63

Office of Government Commerce 2007 Managing Successful Programmes2nd edition The Stationery Office London

OReilly CA 1982 Variations in decision makers use of informationsources the impact of quality and accessibility of information The Acade-my of Management Journal 25 (4) 756ndash771

Project Management Institute 2006 Standard for Program Management Pro- ject Management Institute Newtown Square PA

Project Management Institute 2008 A Guide to the Project Management Body of Knowledge 4th edition Project Management Institute Newtown Square PA

Reinhard RF 1989 Mega projects views of a Bechtel project manager InKimmons RL Loweree JH (Eds) Project Management mdash A Referencefor Professionals New York and Berlin Marcel Dekkerl

Royal Dutch Shell 2008 Annual Review and Summary Financial Statements2007 Royal Dutch Shell The Hangue and London

Shao J 2010 Impact of program managers leadership competences on programsuccess and its moderation through program context PhD thesis LilleSKEMA Business School

Shao J Muumlller R Turner JR 2011 A measurement construct for programsuccess Project Management Journal to appear

Sharma S Durand RM Gur-arie O 1981 Identification and Analysis of Moderator Variable Journal of Marketing Research XVIII(Aug) 291ndash300

Shenhar AJ Dvir D 2007 Reinventing Project Management The Diamond

Approach to Successful Growth amp Innovation Harvard Business SchoolPress Cambridge MA

Simon H 1976 Administrative Behaviour 3 rd edition TheFree PressNew YorkSkinner CD 1999 Introduction to Decision Analysis 2nd edition Probabilis-

tic Publishers Maiami FLSull DN 2007 Closing the gap between strategy and execution Sloan Man-

agement Review 48 (4) 30ndash38

Tabachnick amp Fidell 1989 Using Multivariate Statistics 2nd edition Harper-Collins New York

Thiry M 2004 Program management a strategic decision management pro-cess In Morris PWG Pinto JK (Eds) The Wiley Guide to ManagingProjects Wiley New York

Thomas JB McDaniel RR 1990 Interpreting strategic issues effects of strategy and the information-processing structure of top management teams Academy of Management Journal 33 286ndash306

Thomas JB Shawn M Clark D Gioia A 1993 Strategic sensemakingand organizational performance linkages among scanning interpretationaction and outcomes Academy of Management Journal 36 (2) 239ndash270

Turner JR Zolin R Remington K 2009 Modelling success on complex projects multiple perspectives over multiple time frames In Gemuumlnden H-G(Ed) Proceeding of IRNOP IX the Ninth Conference of the International Re-search Network for Organizing by Projects Berlin October Technical Univer-sity of Berlin

Turner JR Xue Y Anbari F 2010 Achieving results from major infra-structure projects in China using a results-based monitoring and evaluationsystem Proceedings of EURAM 2010 Rome June European Centre for Advanced Studies in Management Brussels

Tversky A Kahneman D 1992 Advances in prospect theory cumulativerepresentation of uncertainty Journal of Risk and Uncertainty 5 297ndash323

VirineL Trumper M2008 ProjectDecisionsTheArt andScience Management

Concepts

13



literature on this phase of megaprojects (Miller and Lessard2000 Grun 2004)

Organizational behavior theory suggests that the ability of a person within an organization to influence its strategic directionis a function of the amount of resource allocation he or she con-trols (Brower and Gilbert 2007) and not necessarily his or her

seniority The managers of megaprojects can be responsible for the allocation of between $03 billion to $20 billion The abilityof these senior project managers to influence corporate strategicdirection should not be underestimated Failure of just one pro-

ject can potentially wipe out the entire annual profit of an oiland gas conglomerate The strategic performances of busi-nesses are underpinned by decisions and the cost of poor deci-sions can be high This study aims to draw attention to how thedecision-making of project managers during project executioncan impact on the long-term strategic goals of corporationsTwo research questions are addressed

which factors of information-feed supporting project man-agers decision impact the strategic value delivered bymegaprojects for the sponsoring organization the most


Information is critical as an input into the decision process A positive correlation has been established between business per-formance and decision-making practice (Thomas et al 1993Mackie et al 2007) and since a program is a temporary organi-zation a correlation between program performance and decision

practices should be expected (Thiry 2004) Flyvbjerg (2007) has

observed that the main challenges of megaprojects is inadequateunreliable or misleading information and conflicts between deci-sion making policy and planning

The perspective of this research is from the view point of the project manager with focus on how decisions made by the project manager during execution impact on the strategic value deliv-ered by the megaproject to the sponsoring organization Fig 1illustrates the typical project delivery process followed by most oil and gas corporations The process is decision-based but

heavily biased towards the project front-end where the most value is created The execution phase activities and deliverablesenable the realization of value and is where projects managerstake the lead

In the next section we consider the nature of megaprojects andthen decision-making on megaprojects and we introduce the hy-

potheses We then describe the research methodology and resultsof the study We conclude by discussing the implications of thestudy

11 Theoretical framework and hypotheses

111 Megaprojects and the program management paradigm

A megaprojects is a special case of a program and as such is aset of multiple but relatedprojects directed towards commonstra-tegic and business objectives which generates benefits beyondthose that would have been generated had the projects beendone individually (Office of Government Commerce 2007Project Management Institute 2006 2008) This is the nature of oil and gas megaprojects which are essentially programs that in-tegrate strategically aligned commercially viable and logisticallycombinable projects under a single management umbrella Theyusually cost over $1 billion involve high uncertainty compriseintangible benefits and promise attractive long-term outcomes

(Miller and Lessard 2000 Flyvbjerg et al 2003) Compared totraditional projects they have long project and product life-cycles are significantly less predictable in terms of time and

Fig 1 Opportunity and project realization process in the oil and gas industry

2




























projects







3
























process






4




























the project







5





117 Research model


model for the study

12 Methodology




























6







13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13



























projects







3
























process






4




























the project







5





117 Research model


model for the study

12 Methodology




























6







13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13























process






4




























the project







5





117 Research model


model for the study

12 Methodology




























6







13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13



























the project







5





117 Research model


model for the study

12 Methodology




























6







13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13




117 Research model


model for the study

12 Methodology




























6







13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13






13 Analysis











( H1A and H1B )




partner goodwill









7


















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13

















Dependent variables






pb01 pb005 pb001 pb 001







Governance 265 275

R 2 112 100 076 057Regression F 418 743 547 407

pb01 pb005

pb

001 pb 001

8






























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13





























Team cohesion 425


Feed Variablesrdquo

and ldquo


by ldquo




Value to partners

HSSEcompliance


Value to host com

Corporate perform

Q PO P SS

Stakeholder pulse

P PS


timeliness



9

















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13
















(Govt and JV )




minus017 121


156 097


061 051


018 minus015


295



275


minus204


minus210



R-square 0169 0204 0369




profitable asset

performance






287 278




minus012





R-square 0022 0090 0258


10


















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13

















by host communities




minus264 minus123


408 302




435


minus092





R-square 0038 0204 0350




communities




minus149 minus230


218 107


minus045 046


minus036 104


108



minus092


110


330



R-square 0235 0282 0406


11











References










Worldwide London UK

































12


















































Concepts

13










References










Worldwide London UK

































12


















































Concepts

13

















































Concepts

13

mega projects - maximizing strategic value -info decision making

Documents