2 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15project planning (Bart, 1993; Andersen, 1996). So, isproject planning that important? Our assumption wasthat good planning itself may not be a sufﬁcient pre-dictor of success. This assumption follows previousdoubts about project planning, such as Peters et al.(1988, p. 138), who wrote:Unfortunately, most innovation management prac-tice appears to be predicated on the implicit as-sumption that we can beat the sloppiness out ofthe process if only we’d get the plans tidier andthe teams better organized. The role of experimentsand skunkworks, the zeal of champions, the powergained from exploiting the innovative user as part-ner, is denigrated as an aid only ﬁt for those whoaren’t smart enough to plan wisely.This means planning is a necessary but not a sufﬁ-cient condition for project success. Planning is not aone-time task. Eisenhower’s historical dictum: “Plansare nothing, planning is everything” points out theimportance of the planning process itself. Most au-thors agree that projects are complex, time restricted,unique endeavors and special tasks that have not beendone before. Consequently, it is very difﬁcult or evenimpossible at the initial planning stage to know pre-cisely which activities have to be carried out in orderto complete the project, and what their cost and dura-tion parameters are (Andersen, 1996). Adding to thatthe high uncertainty associated with projects, the tradi-tional emphasis on project planning in the industry aswell as the unequivocal empirical results are even moresurprising. Hence, we interpret Eisenhower’s dictumto mean that in managing projects, original projectplans and project goals will have to be changed toaddress the dynamics caused by uncertainty, and tomaximize project success.On the other hand, changes in plans can cause hightransaction costs, which have a negative impact onproject results. Changes in plans may be introducedfor various reasons. They may come from a changerequired by the customer, from new and better ideassuggested by the project team, or even from the dic-tate of a new manager, who comes in at a later stageand wants to impose its own twist to the project.Quite often, projects undergo tremendous changes andwhen the project is ﬁnally completed it may no longerbe relevant: too much “tweaking” can result in lossof the original project focus. The original questionregarding project planning can thus be rephrased:“How do changes in either goals or plans impactproject success?” This question is hardly addressedby previous research, and we believe that a carefulempirical investigation is needed to better understandthe effect of change on project management success.Referring again to Eisenhower, the central questionof this article could be rephrased as: is it true that,plans are nothing, changing plans is everything?Our ﬁrst objective was to study empirically the im-pact of project planning, project goal changes, andproject plan-changes on project success, and to de-termine whether a high quality of project planningcould compensate for the possible negative effects ofchanges. When referring to the quality of project plan-ning we refer to the quality of the initial project plans.The second goal was to understand how project con-textual variables affect goal changes and how suchchanges, in turn, affect project success.The next section discusses the theoretical and em-pirical literature on the limitations of project plan-ning and speciﬁes hypotheses based on that review.In the third section, we derive and empirically testthe conceptual framework. The results are reported inthe fourth section. In the ﬁfth section, the implica-tions of the results are discussed. The ﬁnal section isan effort to discuss the practical implications of ourresults and to present some suggestions for furtherresearch.2. Current research on project planningPlanning is prevalent in project management and inthe strategic management literature. The discussionof formal strategic planning and its impact on thecorporate performance is somewhat parallel to the dis-cussion of project planning and its impact on projectsuccess. Therefore, the ﬁeld of strategic planningseems to be an important source of knowledge com-plementing the discussion of project management. Theliterature on strategic planning generally addressesthree different problem areas: the importance and im-pact of plans on performance, the planning process it-self, and contextual inﬂuences on the planning process(Armstrong, 1982). In the following discussion, werefer to these three issues within the context of projectplanning.
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 33. The impact of project plans on project successThe impact of strategic planning on corporateperformance has been addressed in several studies(Rhyne, 1986; Ramanujam and Venkatraman, 1986).Only 10 out of 15 empirical studies have reportedsigniﬁcant improvements resulting from formal plan-ning activities (Armstrong, 1982). In contrast, theresults pertaining to the impact of planning on projectsuccess are much less ambiguous. A review of 44empirical project management success factor studies(Lechler, 1997) identiﬁed 13 studies analyzing theeffect of project planning on project success. All ofthe analyzed studies have demonstrated signiﬁcantstrong or medium positive effects on project success.However, there are other authors in the ﬁeld of projectmanagement who claim that formal project planningis not necessarily helpful or even desirable (Bart,1993; Andersen, 1996). Bart (1993) indicates thatthe traditional approach to planning and controllingof R&D projects tends to fail because of excessivelyrestrictive formal control, which curtails creativity asa factor contributing to project success. Bart proposesto reduce formal planning and control to a minimumrequired level. Yet, even if this is done, there is noargument as to the contribution of complete and accu-rate capturing of end-user requirements to successfulproject completion (Chatzoglou and Macaulay, 1996).The main reason is that the output of the requirementsanalysis stage will most likely determine the outputof the entire development process. Posten (1985a,b)has found that 55% of all defects in R&D projectsoccur during requirement analysis and speciﬁcationwhereas 43% of all defects are not found until afterthe testing stage.The almost unanimous agreement in the projectmanagement literature in contrast to the strategic man-agement literature could derive from methodologicaland conceptual factors. One possible argument couldbe the choice of the dependent variable. The strategicmanagement literature indicates that the inﬂuence ofplanning differs over different performance measures(Armstrong, 1982; Ramanujam and Venkatraman,1986). The criteria for measuring project success mustreﬂect different views (Cooper and Kleinschmidt,1987; Pinto and Slevin, 1988; Freeman and Beale,1992). Nevertheless, the difﬁculty of measuringproject success from several points of view havedriven project managers to use simplistic formulaesuch as meeting or coming close to budget, attainingscheduled goals and achieving acceptable levels ofperformance. These measures are partial and some-times misleading (Baker et al., 1988). Although themultidimensional approach for assessing project suc-cess is a common understanding today, most of theproject management literature does not differentiatebetween the impacts of success factors on the varioussuccess dimensions.Another methodological argument is that the suc-cess factor studies do not investigate the impact ofsuccess factors on the project performance over its lifecycle. An exception is Pinto and Prescott (1990) whoclaim that critical success factors of project manage-ment fall into two distinct sub-groups: those relatedto initial project planning and those concerned withsubsequent tactical operationalization. It was foundthat the relative importance of planning and tacti-cal factors varies across the project life cycle. When‘internal’ success measures are used (meeting budget,schedule and performance goals), planning factors areinitially perceived to be of high importance but areovertaken by tactical issues as the project progressesthrough its life cycle. When ‘external’ success mea-sures (perceived value of the project and client satis-faction) are employed, planning factors have dominantimportance over tactics throughout the project’s lifecycle.4. The inﬂuence of the planning process on thequality of project plansPlanning is a process with many different activitiesthat cover a variety of issues, using numerous planningtechniques and planning procedures such as analysis,design reviews, reports and interpersonal communi-cation. Bryson and Bromiley (1993) identiﬁed em-pirically two groups of planning activities having animpact on the project success: internal project commu-nication, with a positive inﬂuence on project success,and forced project goals, with a negative inﬂuence.The ﬁrst result is also supported by Lechler (1997).The importance of the initiation phase stands outrelative to other phases in the project life cycle (Kingand Cleland, 1988; Meyer and Utterback, 1995). Dviret al. (1999) indicated in a study of 110 development
4 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15projects that the origination and initiation phase, hasthe greatest inﬂuence on project success. During thatphase major decisions are made such as deciding theproject’s objectives and planning the project’s execu-tion. They also found that although the preparation offormal design and planning documents has a strongpositive effect on meeting time and budget objectives,it also contributes signiﬁcantly to customer beneﬁtsderiving from the end−product.In a follow-up study, Dvir et al. (2003) suggestedthat no effort should be spared in the initial stage of aproject to properly deﬁne the goals and the project’sdeliverable requirements. This task cannot be achievedwithout customer or end-user involvement in theprocess.The use of planning tools is an integral part of theproject planning process, especially the use of net-works. They are based on computational models orig-inating in large projects from the 1950’s onwards, andare used extensively predominantly in the aerospace,defense and construction industries (Kerzner, 1998).Project planning is mainly focused on detailed networkscheduling approaches (Tatikonda and Rosenthal,1999). Gutierrez and Kouvelis (1991) criticize the useof CPM as it systematically fails to predict the dura-tion of complex projects. Many truly excellent orga-nizations do not use the PERT approach to planningprojects. For instance, one of Hewlett-Packard’s UKplants uses whiteboards and Post-it notes for projectplanning at the top level, with individual sub-projectmanagers free to use computerized planning softwareat the task level (Maylor, 2001).Andersen and others propose replacing the standardplanning approach with milestone planning (Andersenet al., 1995; Turner, 1993), where a milestone is de-ﬁned as a result to be achieved. Since a milestone de-scribes what is to be done, but not the way it shouldbe done, milestone planning promotes result-orientedthinking rather than activity-oriented thinking.The criticism of planning tools derives from prob-lems associated with the implementation process,which is prone to frequent changes of project goalsand plans. The commonly used tools do not provideanswers to managing changes. As the strong negativeinﬂuences of frequent goal changes show (Murphyet al., 1974), project managers are not aware of theconsequences of frequent changes and are not pro-vided with the information necessary to deal withchanges efﬁciently. The efforts to develop alternativesolutions, such as the use of Post-it notes or milestoneapproaches, instead of using detailed networks, alsoreﬂect the severity of frequent goal or plan-changesduring project implementation.5. Project goal changes versus plan-changesThe discussion about project planning processesdoes not directly address the issue of goal changes orplan-changes. However, implicitly one can assert thatproject planning is an ongoing task and therefore it issubject to changes. Trade-offs are usually made be-tween the three traditional constraints: budget, sched-ule and scope, and are often made without taking intoaccount the impact of these changes on project suc-cess, or speciﬁcally on customer satisfaction.In order to analyze the inﬂuence of changes onprojects we have to distinguish ﬁrst between two types,changes that have an impact on the project plan but donot have an impact on the project goals or meeting cus-tomer requirements: we call these plan-changes. And,changes that reﬂect a change in the project goals: wecall them goal changes.Plan-changes are typically induced by the envi-ronment and prevent us from following the originalproject plan. Such changes can be a result of shortagein resources, delays, strikes, weather conditions, etc.Sometimes they are a result of poor planning requir-ing change in order to meet the requirements. Theproject manager has to make the necessary adjust-ments without changing the project scope and goals.Goal changes on the other hand, are typically a re-sult of a conscious decision by the stakeholders tochange the goals of the project. They could be due tochanges in requirements, lack of ability to meet exist-ing requirements within the available budget and time,or changes in circumstances that impact the necessityof the project end-product. Goal changes, when ap-proved, require a change in plans in order to meet theupdated requirements.Both types of changes are unavoidable, but in theﬁrst case all what that the project manager can do is toﬁnd the most efﬁcient way to deal with the situationwhile in the second case, the amount of change can becontrolled by collaboration between the project teamand the stakeholders.
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 56. The contextual inﬂuences on planningprocessThe main purpose of planning is to reduce uncer-tainty (Shenhar, 1993; Laufer et al., 1997) and hencethe function of planning is dependent on the context inwhich it is undertaken. Several authors recognize theimportance of contextual inﬂuences on strategic plan-ning. Formal planning systems can contribute highlyto risky and important decisions (Sinha, 1990). Tech-nological uncertainty has been shown to have a nega-tive impact on the success of projects (Murphy et al.,1974; Rubenstein et al., 1976; Souder and Chakrabarti,1978; Baker et al., 1988; Might, 1984; Ashley et al.,1986; Pinto, 1986; Larson and Gobeli, 1988) and theplanning process itself (Grinyer et al., 1986). As thesuccess factor studies show technical uncertainty iscaused by external inﬂuences like a technical break-through of a competitor or technological risks inher-ent to the project task. Dawson and Dawson (1998)have shown that current planning techniques are inade-quate for projects involving uncertainty and risk. Theysuggest that projects should use probability distribu-tions to assess task durations and generalized activitynetworks with probabilities associated to each path.The ﬁndings of Turner and Cochrane (1993) suggestthat contextual variables are one of the main causesfor changes over the project lifecycle; among them,technological uncertainty is a typical variable whichmoderates the effect of project planning on projectsuccess by causing plan and goal changes (see alsoBalachandra and Friar, 1997).Bryson and Bromiley (1993) show that technolog-ical uncertainty has a signiﬁcant negative impact onGoal Changes EfficiencyCustomerSatisfactionContext----++++Quality ofPlanningPlan Changes+- -+-+++Fig. 1. Hypothesized relations between the planning variables and success.project success and that stability has a positive in-ﬂuence. They identify eight different contextual vari-ables affecting the planning process of organizationalchange projects. Some of these variables, like tech-nological uncertainty and economic stability, also de-scribe the context of projects.The empirical literature has shown some evidencefor the impact of contextual settings on the successof projects. Yet, their impact on planning is not an-alyzed, which is surprising because planning shouldreﬂect and anticipate contextual inﬂuences. From thatdiscussion, we can conclude that the interactions ofproject planning with other process-related variablesand their combined effects on project success, havenot been studied in-depth. Therefore, only a modelthat describes the various interactions between plan-ning variables and several success dimensions can re-veal the ‘true’ effect of planning on project success.In conclusion, it seems that project plans and theplanning process are an important part of projectmanagement, but the question remains whether theirinﬂuence on project success is correctly assessed oroverestimated. In essence, most of the literature seesthe project plan primarily as a static and stable entity,and the question of how plan and goal changes affectproject success is still relatively unanswered.7. The conceptual framework of the studyThe deﬁnition and operationalization of the vari-ables and their interrelationships are discussed in thissection. The hypothesized relationships between themodel variables are graphically represented in Fig. 1.
6 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–157.1. Project successPinto and Mantel (1990) identiﬁed three distinctaspects of project performance: the implementa-tion process; the perceived value of the project; andclient satisfaction with the delivered project outcome.Shenhar et al. (1997) have used in their research threecriteria for the assessment of project success: Meetingdesign goals; beneﬁts to customers; and commercialsuccess and future potential. Since each stakeholderassesses the project’s outcome from a different pointof view, it is conceivable that the relative importanceassigned to each dimension will vary with the stake-holder assessing the project success. Lipovetsky et al.(1997) who have used four dimensions for measuringproject success have found that customer satisfactionis by far the most important criteria, almost twice asimportant as efﬁciency. The importance of the othertwo criteria, commercial success and future poten-tial was almost negligible. Therefore, in this study,we measure project success with the two successcriteria: project efﬁciency and customer satisfaction.Several empirical studies show a strong correlationbetween project efﬁciency and customer satisfac-tion (Lipovetsky et al., 1997; Pinto, 1986). Thus wepropose:Hypothesis 1. Project efﬁciency positively impactscustomer satisfaction.7.2. Planning variablesThe planning variables used in our study are: thequality of project planning (schedule, budget andscope), the frequency of plan-changes, and the extentof goal changes. Many empirical studies show thepositive impact of project planning on project success(Murphy et al., 1974; Rothwell et al., 1974; Pinto,1986 and many others). It is hypothesized therefore,that the quality of project planning positively affectsproject efﬁciency as well as customer satisfaction.Hypothesis 2a. Project success (both efﬁciency andcustomer satisfaction) is positively affected by thequality of project planning.This means implicitly that the deﬁnition of projectgoals as part of the project planning process willreduce the extent of project goal changes. We pro-pose also a reducing effect of the quality of projectplanning on the frequency of plan-changes althoughthis effect might be less strong. Nevertheless, poorplanning quality will cause many plan changes evenif there are many other reasons for plan changes.Hypothesis 2b. High quality of project planning re-duces the extent of goal changes and the frequency ofplan changes.Only a few empirical studies have analyzed the di-rect effects of goal changes (Murphy et al., 1974;Lechler, 1997) on project success. These studies showstrong and signiﬁcant negative effects of goal changeson project success. Thus, we can assume that the posi-tive effects of the quality of project planning on projectsuccess are counter balanced by negative effects ofgoal changes and plan changes.Hypothesis 3a. Goal changes have a strong negativeeffect on project success (both efﬁciency and customersatisfaction).The distinction between goal and plan changes al-lows for the assumption that the changes in plans willoccur even when the project plan was carefully pre-pared and no goal changes are introduced. Therefore,it is not clear how plan changes will inﬂuence projectsuccess. We assume that a high frequency of planchanges will have a negative effect on project success.Hypothesis 3b. Plan changes have a strong negativeeffect on project success (both efﬁciency and customersatisfaction).Goal changes always lead to plan changes while theopposite is not true. Thus, we propose:Hypothesis 3c. Project goal changes lead to planchanges.7.3. Contextual variablesThe third group of variables describes the contextof planning. Technical risks are the one contextualvariable analyzed and discussed most often in the lit-erature. Another major contextual inﬂuence on project
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 7success and the planning process are the availableresources which negatively impact project success(Balachandra, 1984). Variation in the resource struc-ture during the project implementation is a signiﬁcantfactor for failure and is caused by insufﬁcient man-power and too many parallel projects done at the sametime. Yet, it is not clear how the quality of projectplanning is impacted. The importance of a projectfrom the perspective of the company has a positiveimpact on project success (Pinto, 1986).In an exploratory approach several contextual vari-ables, describing the contextual inﬂuences on theresource structure, competitive internal and externalenvironment, were assumed to inﬂuence the quality ofproject planning and stimulate goal changes and as aresult, plan changes. We thus propose our exploratoryhypothesis:Hypothesis 4. Contextual variables impact goal andplan changes and the quality of project planning.The core model is derived from our literature anal-ysis and theoretical ideas and therefore, the test of thispart of the framework is conﬁrmatory. On the otherhand, the last hypothesis is an exploratory statementsince only few studies analyzed contextual inﬂuenceson project success. There are some indications that thecontext might inﬂuence the project planning and ex-ecution but how and which variable has an effect onproject planning was not analyzed in detail yet.8. Methodology8.1. Research design and data collectionData collection was performed in Germany andresulted in a sample of 448 projects. A detailedquestionnaire, which was designed to measure theimpact of success factors of project management, wasdistributed to the members of the German ProjectManagement Society (Gesellschaft für Projektman-agement, GPM)). Each respondent was asked to ﬁllout two questionnaires gathering data on a pair ofcompleted projects—a successful and a failed project.This concept of pair wise comparison was ﬁrst intro-duced by Rothwell et al. (1974) and has the advantageof reducing the personal bias of the key informants.The questionnaire included 199 single items andsome quantitative information about each project. Outof these, 67 items were directly taken from Pinto’s(1986) questionnaire, with permission of the author,and translated into German. The remaining items weredeveloped with the help of several experienced projectmanagers. Two versions of the questionnaire werepre-tested and modiﬁed after in-depth interviews andresponses by a group of experienced project managers.The variables in the questionnaire that are rele-vant to this study are listed in Table 6: the extentand the frequency of goal-changes, the frequency ofplan-changes, the quality of project planning, projectefﬁciency and customer satisfaction and six contex-tual variables. Each item was assessed on a 7-pointscale; from strongly agree to strongly disagree. Dueto their exploratory nature ﬁve of the six contextualvariables were measured by single items. Three itemsmeasure the sixth contextual variable, strategic impor-tance. All constructs that were measured with multipleitems were tested with Cronbach’s Alpha for scale re-liability and with conﬁrmatory factor analysis for uni-dimensionality. All scales achieve a Cronbach’s Alpha>0.8 and communalities of >0.6. All variables werealso tested for normality. In preparation for the SEMestimations, a covariance matrix was calculated usingthe variables’ z-scores. The resulting covariance ma-trix is based on 448 responses.8.2. Sample characteristicsThe data collection effort achieved an overall re-sponse rate of 43%, resulting in a sample size of 448projects. The sample for the present investigation con-tains data on 257 successful and 191 unsuccessfulprojects (Table 1).About 50% of the respondents were project man-agers. In cases where the project managers could notbe reached, team members were approached. TheTable 1Distribution of the respondents’ functionsFunction Frequency Frequency in percentProject manager 207 46.2Team member (technical) 85 19.0Team member (business) 36 8.0Others 120 26.8448 100.0
8 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15Table 2Distribution of project typesType of project Frequency Frequency in percentMachine tool manufacturing 25 5.6Plant construction 61 13.6Building construction 30 6.7Product development 116 25.9Reorganization 52 11.6Software 109 24.3Others 55 12.3448 100group ‘others’ includes respondents who were exter-nal consultants or specialists with intimate knowl-edge of the project. This homogeneity of respondentsparticipating actively in the project implementationenhances the validity and reliability of the measures.The sample is relatively balanced concerning thedifferent types of projects (see Table 2). Around 26%of the projects in the sample are machine tool, plantconstruction or building construction projects. Prod-uct development projects account for another 26%,including projects for product modiﬁcations, productenhancements, and completely new products. Around24% are software projects. The group ‘others’ includesmainly projects dealing with creating new technicalconcepts as well as technical feasibility studies.The sample provides a fairly representativecross-sectional distribution of projects carried out inthe German industry. For further detailed informationon the sample see Lechler (1997).8.3. Data analysisThe contextual variables of our model wereidentiﬁed using an exploratory correlation analysis(Table 3). Out of an initial list of twelve different con-textual variables six have been found to signiﬁcantlyaffect the planning process: strategic importance ofthe project, level of experience of the project team,personnel constraints within the organization under-taking the project, parallel projects undertaken at thesame time, occurrence of technological breakthroughwhich affects the project results, and the technologicalrisk associated with the project.The interaction hypotheses were tested using astructural equation model. For the model estimationTable 3Pearson’s correlations between six contextual variables quality ofplanning, goal changes and plan changesContextual variables Planning variablesQuality ofplanningGoalchangesPlanchangesPersonnel constraints n.s. 0.226∗∗ 0.226∗∗Parallel projects n.s. 0.202∗∗ 0.174∗∗Occurrence of breakthrough n.s. 0.247∗∗ 0.127∗∗Technological risk n.s. 0.175∗∗ 0.165∗∗Importance 0.204∗∗ n.s. n.s.Level of experience 0.170∗∗ n.s. n.s.n.s.: not signiﬁcant.∗∗ P ≤ 0.01.linear structural relationships (LISREL) version 8.51was used. LISREL is a statistical method that allowssimultaneous analysis of hypothesized causal relation-ships for multiple variables (Jöreskog and Sörbom,1993), e.g. the direct effects of goal changes on thetwo different project success variables and simultane-ously the indirect effects by taking into account theeffects on the variable plan changes and its effects onthe success variables.The evaluation of a structural equation model isquite complex since no single test offers sufﬁcientevidence to accept or reject a model. Recognizingthe problems associated with the evaluation of linearstructural equation models (Bagozzi, 1980; Andersonand Gerbing, 1988; Bollen, 1989; Fritz, 1992; Soniet al., 1993; Baumgartner and Homburg, 1996), acomprehensive set of tests was employed to assess thegoodness of ﬁt. To accept the model, the followingcriteria have to be satisﬁed: a chi-square (P > 0.05),which tests the null hypothesis that the estimatedvariance–covariance matrix deviates from the samplevariance–covariance matrix only because of samplingerrors. The chi-square test is limited to the extentthat it is dependent on the sample size. Browne andCudeck (1993) showed that with an increase of thesample size any model could be rejected. Because ofthese weaknesses of the chi-square test, Jöreskog andSörbom suggested the two global ﬁt indices, goodnessof ﬁt index (GFI) and adjusted goodness of ﬁt index(AGFI). To evaluate the ﬁt of our structural equationmodels we used the AGFI, since its calculation isbased on the GFI and because it accounts for the de-grees of freedom. Values below 0.90 indicate that the
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 9model should be rejected (Baumgartner and Homburg,1996). The root mean square error of approximation(RMSEA) is a measurement of non-centrality andestimates how well the ﬁtted model approximates thepopulation covariance matrix per degree of freedom.Browne and Cudeck (1993) suggest that a RMSEA ≤0.05 indicates a close ﬁt and that the model shouldbe accepted. The comparative ﬁt index (CFI) assessesthe relative reduction in lack of ﬁt as estimated by thechi-square of a target model versus a baseline modelin which all of the observed variables are uncorrelated(Bentler, 1990). Models with a CFI below the 0.85should be rejected (see Bentler and Bonett, 1980).9. ResultsTable 3 provides the correlations between thesix contextual variables having signiﬁcant correla-tions with goal-changes, plan-changes, and quality ofproject planning. Only two variables are correlatedwith the quality of project planning (strategic impor-tance and level of experience) and the other four arecorrelated with goal changes and plan changes.In the next step of the data analysis, the interactionof the model variables were estimated simultaneously.We started the LISREL analysis with the conﬁrma-tory part of the model only, e.g. the contextual vari-ables were not included in the estimation. Based onthe results of the correlation analysis we introducedthe contextual variables into the model. According tothe pattern of correlations (Table 3) the paths fromR2= .19Goal ChangesR2= .26EfficiencyR2= .55CustomerSatisfactionImp.+.61R2= .26Plan Changes +.14-.16-.23 +.27-.21+.50-.27Expr.+.20 +.16Pconst.+.11+.16PProj. Trisk. Break.+.15 +.14 +.18n.s.Quality ofPlanningn.s.Fig. 2. Results of the structural equation model. Fit statistics: χ2 = 40.93, df = 25, P < 0.023, RMSEA = 0.038, AGFI = 0.94,CFI = 0.98. Parameter estimates are from the completely standardized solution and are signiﬁcant at P < 0.05 or better.importance and experience variables to the qualityof planning variable were added to the conﬁrmatorymodel. Paths from the other four contextual variableswere added to both goal-changes and plan-changesvariables. The ﬁnal model presented in Fig. 2 does notdiffer from the conﬁrmatory model of step one, there-fore we do not present that structural equation model.Except for the chi-square index, all test criteria aremet in assessing the model ﬁt. As mentioned, thechi-square index depends on the sample size. The sam-ple used in this analysis exceeds 400 cases and thatmake it nearly impossible to achieve P-values above0.05. Since all other tests achieve or exceed the re-quired ﬁt criteria, the ﬁnal structural equation modelshould be accepted. The results for the hypothesestests are shown in Table 4.The high positive impact of efﬁciency on customersatisfaction fully supports our ﬁrst hypothesis H1. Asthe signiﬁcant path coefﬁcients show project efﬁciencyis directly affected by all three planning variables.Customer satisfaction is directly affected only by thequality of planning and goal-changes and not directlyaffected by plan-changes. The signs of the path coef-ﬁcients indicate positive effects of quality of planningand negative effects of plan-changes and goal-changeson project success. Thus the hypotheses H2a and H3aare fully supported. On the other hand, hypothesis H3bis only partially supported since there is no signiﬁcantpath between plan-changes and customer satisfaction.Hypothesis H2b is also partially supported since thepath between quality of planning and plan-changesis not signiﬁcant but the path to goal-changes is
10 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15Table 4Hypotheses testing resultsHypothesis ResultH1 Project efﬁciency positively impacts customer satisfaction SupportedH2a Project success is positively affected by the quality of planning SupportedH2b High quality of project planning reduces the level of goal and plan changes Partially supportedH3a Goal changes have a strong negative effect on project success SupportedH3b Plan changes have a strong negative effect on project success Partially supportedH3c Project goal changes lead to plan changes SupportedH4 Contextual variables impact goal and plan changes and the quality of project planning Supportedconsiderably high and signiﬁcant (−0.27). Hypoth-esis H3c describing the effect of goal-changes onplan-changes is fully supported by the high andsigniﬁcant path coefﬁcient (0.50). The exploratoryhypothesis H4, proposing effects of contextual vari-ables on the three planning variables is supportedby the signiﬁcant path coefﬁcients in the LISRELmodel, which takes simultaneously into account thedirect and indirect effects of all variables and variablegroups on project success.10. DiscussionThe main purpose of this study was to providean in-depth investigation of the interactions betweenplanning variables on two different dimensions ofproject success. A secondary research issue was to es-timate the impact of contextual variables on the plan-ning process, especially how goal and plan changesare affected by the project context. The most impor-tant results of this study are the interactions betweenthe planning variables and their inﬂuences on projectsuccess. Only by investigating the three planning vari-ables separately using structural equation modelinginstead of multivariate regression analysis can we gaininsight into the complex indirect relationships amongthem and explore phenomena that would be otherwiseTable 5Total effects of the planning factors on successPlanning variables Effects on efﬁciency Effects on customer satisfactionDirect Indirect Total Direct Indirect TotalQuality of planning +0.27 +0.08 +0.35 +0.14 +0.25 +0.39Goal changes −0.21 −0.10 −0.31 −0.15 −0.19 −0.34Plan changes −0.23 – −0.23 – −0.14 −0.14unobservable. The total effects (direct and indirecteffects) of the planning variables on project successare summarized in Table 5. The results clearly showthat the positive total effect of the variable qualityof planning is almost completely overridden by thenegative effect of goal changes. If we add the totaleffects of the two variables, goal changes and planchanges on project success, their combined effectis considerably stronger than that of the quality ofplanning.The signiﬁcant but clearly differing inﬂuences of theplanning variables on the project success variables in-dicate the importance of differentiating between thesetwo success dimensions. While the quality of plan-ning positively affects both efﬁciency and customersatisfaction, changes are acting in the opposite direc-tion; namely, changes are compromising the projectresults. The magnitudes of these inﬂuences are of spe-cial interest. The quality of planning has the highestpositive direct effect (+0.27) on efﬁciency, while goalchanges have the highest negative direct effect (−0.16)on customer satisfaction. These results reﬂect the na-ture of traditional planning, which is focused mainlyon project schedule and budget, while project goals aremore focused on the project substance, which repre-sents the value for the customer. The differences in thetotal effects of the planning variables show that highquality planning cannot compensate for the negative
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 11Table 6Operationalization of the constructsConstruct Scale MeasuresSuccess Efﬁciency (Alpha:0.86) 1. The project had come in on schedule (Pinto).2. The project had come in on budget (Pinto).Customer satisfaction (Alpha:0.81) 1. The clients were satisﬁed with the process by which this project wascompleted.2. The clients are satisﬁed with the results of the project (Pinto).Planning Plan changes The project plans (schedule, personnel, budget) were often changed.Goal changes (Alpha:0.83) 1. Project goals were often changed.2. At least one major project goal was changed considerably.Planning quality (Alpha:0.85) 1. The entire project task (scope) was structured in work packages.2. Every work package was allocated with a speciﬁc time allowance.3. We knew which activities contained slack time or slack resources.4. All work packages had a predecessor and a successor work package (exceptthe ﬁrst and the last).5. There was a detailed budget plan for the project.6. The precise demand for key personnel (who, when) was speciﬁed in theproject plan.Context Technical risks (Alpha:0.79) 1. The task was technically demanding.2. The completion of the business goals included high risks.Importance (Alpha:0.78) 1. It was important that the results of the project could be used as soon aspossible (Pinto).2. The implementation of the project was important for the organization’spolicy (Pinto).3. The implementation of the project was important for the success of theorganization (Pinto).Experience The projecting company had experience with the solution of similar problems.Manpower The project team did not experience any signiﬁcant personnel losses or transferduring the project’s development.Parallel projects The completion of the project depended on other projects, undertaken at thesame time.Break through The project was not subject to any recent technological breakthrough, whichcould have rendered it obsolete.All items are measured on 7-point rating scales, Cronbach’s Alpha in brakets.effects of changes. Although the total effect of thequality of planning (+0.39) is higher than the indi-vidual total effects of plan changes (−0.14) and goalchanges (−0.34), their combined total effect is con-siderably larger (−0.48).The interactions between the planning variables arenot straightforward and self-evident. While the qualityof planning reduces the level of goal changes (−0.27),it does not affect plan changes at all. Changing projectgoals leads to changes of project plans as shown in themodel by a strong direct effect (0.50). The percent-age of explained variance of the plan changes indi-cates that there are other inﬂuences causing changes inthe project plan. These results indicate that high qual-ity project planning, although very important, cannotcompletely compensate for plan changes during theproject life cycle.The third question this analysis addresses is howthe context inﬂuences the project planning activi-ties. This part of the study is more exploratory. Incontrast to our initial hypothesis, not all contextualvariables have a signiﬁcant impact on the planningand change variables. Regarding their inﬂuence, theyfall into two groups. Strategic importance and thelevel of experience of the project team are affect-ing only the quality of planning, as the exploratory
12 D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15correlations indicate (Table 3). Whereas the secondgroup of contextual variables, personnel constraints,parallel projects, occurrence of breakthrough, andtechnological risk exclusively inﬂuence goal changesand plan changes. Out of the latter variable grouponly the manpower constraints variable directly af-fects plan changes. This result stands in contrast tothe correlation analysis (Table 3) that shows signiﬁ-cant correlations with four contextual variables. Onlyby simultaneously estimating the inﬂuences of thecontext variables on goal-changes and the impact ofgoal-changes on plan-changes can we build a moreaccurate model. The main source for plan changes,besides goal changes according to these results, isshortage in manpower to execute the project.Two counter intuitive results come out of our anal-ysis. First, the quality of planning has no signiﬁcantimpact on plan-changes and second, plan-changeshave no signiﬁcant direct effect on customer satisfac-tion. These two ﬁndings have important theoreticaland practical implications. As of today, the projectmanagement literature discusses project planningas a single entity. From that perspective, it is onlynatural to assume that a higher quality of projectplanning will reduce the number of plan changes.However, our study does not support this view. Thecauses for changing project plans are obviouslycontextual-related or driven by goal changes.Addressing the second ﬁnding requires goingback to the differences between goal-changes andplan-changes. While goal changes are mostly the re-sult of a common agreement between the customer andthe project manager, there are many internal reasonsfor plan changes that do not interest the customer. Theresults also indicate that plan changes are basicallyefﬁciency-oriented. They reﬂect changes in a projectplan but do not necessarily impact the end-product.That may be one explanation for the non-signiﬁcantrelation between plan-changes and customer satisfac-tion. These results suggest further investigations byusing a more precise deﬁnition of the two types ofchanges and measuring the impact of these differentaspects on the two criteria of project success.10.1. Implications and outlookIn contrast to the general understanding, this studysheds a different light on project planning. Projectsare temporary, unique and ongoing tasks. It is unimag-inable that such tasks can be performed without anychanges at all. The results of this study support thisview but it seems that the essence of changes is evenstronger than that of planning, and indeed, while plansare not nothing, “changing plans is everything.”By analyzing the interactions between the threeplanning variables, project success and contextual in-ﬂuences this study contributes to theory building inthree aspects. First, it explores the prominent negativeimpact of changes, especially goal changes, on projectsuccess. Second, it reveals the interaction structurebetween the planning variables themselves and theirinteraction with the two dimensions of project suc-cess. And third, it identiﬁes several contextual vari-ables, which affect the quality of project planningand stimulate goal and plan changes. The most im-portant result is that the amount of changes duringa project’s implementation clearly distinguishes be-tween successful and failed projects. These resultspoint to several managerial implications.The quality of project planning affects the projectsuccess, but the major lesson is: while it is impossibleto prevent project changes at all, they should be keptto a minimum. The analyzed interactions between theplanning variables indicate a very high and positiveconnection between goal changes and plan changes;the number of plan changes is strongly affected bygoal changes. It is therefore in the hands of the PMto control the negative effect of plan changes by care-fully screening out from all proposed goal changesonly those which are really essential to the success-ful implementation of the project. Eventually projectgoal changes will negatively impact project success.Other measures to avoid the strongly negative effectsof goal changes are to freeze the requirements andthe design at earliest possible stage. Shenhar andDvir (1996) however have shown that the appropri-ateness of design freeze points in a project dependsupon its level of technological uncertainty. The higherthe uncertainty, the later will be the point of designfreeze. For prevention of changes in later projectphases—project managers should invest in upfrontactivities to capture the ‘real’ requirements of thecustomer (Dvir, et. al., 2002). A true reﬂection of cus-tomer requirements at the initial phase of the projectcan signiﬁcantly reduce the amount of changes in laterphases.
D. Dvir, T. Lechler / Research Policy 33 (2004) 1–15 13Besides the interactions between different planningvariables, this study shows how contextual variablesaffect project planning. Such variables can be dividedinto two groups: those over which project managershave almost no control and those over which projectmanagers have some level of control. The negative in-ﬂuence of the second group of contextual inﬂuencescan be mitigated by a high quality of project planning.The quality of project planning is to a large extent inthe hands of the PM, and since the inﬂuence of plan-ning quality on goal changes is much stronger thanthe contextual variables, the PM can limit their im-pact. One contextual variable affecting both plan andgoal changes is the manpower constraints variable.Therefore, in order to reduce the number of goal andplan changes at the same time it is the PM’s primeresponsibility to assure that the required human re-sources for proper execution of the project are ﬁrmlysecured.Although our basic model is mainly conﬁrmatory,it has some limitations. One limitation is linked tothe static treatment of the data. The measurements areall ex-post and therefore do not allow analysing theimpact of changes over time. It is quite probable thatthe impact of goal and plan changes could vary overthe life cycle of the project.Another limitation is the common method varianceproblem associated with such designs. This is relatedto the choice of the key informants (George and Torger,1982), where the same person is asked about his/heractivities and their outcomes. This approach is crit-icized by several authors who question the validityof the results (Allen et al., 1988; Cooper, 1979;Campbell, 1982; Bedeian, 1988). Crampton andWagner’s (1994) meta-analysis does not support thiscriticism. Investigating 581 ﬁeld studies and analyz-ing 42,934 correlations, they conclude that the risk ofdistorted results through the use of key informants’self-ratings is relatively small. Another aspect inreducing the risk of a response bias caused is theexclusive selection of pairs of clearly ‘successful’and ‘not successful’ projects. The comparison of ex-treme examples, which the respondents in this studyare asked to draw, reduces the possibility of biasedinformation. According to Duffy et al. (1998), thegoal of such a study is to analyze higher order inter-actions between factors. They argue that it is unlikelythat the respondents take into account the interactionsbetween the factors and manipulate their answers ina speciﬁc pattern.Our study opens opportunities for further research.The low percentage of explained variance of the twochange variables indicates an important research di-rection: the search for explaining variables. The causesof goal changes are not fully explored.A more accurate deﬁnition of change variables isrequired too. Such a deﬁnition may enable further in-vestigation into the interactions between the contex-tual variables and the change variables and how goalchanges could be managed appropriately. Finally, wepropose further research, focused on the life cycle ofprojects to deepen the understanding of the interac-tions between plan and goal changes as well as theirimpact on project success.AcknowledgementsThe Authors are thankful for the important and valu-able remarks of their colleague Prof. Aaron Shenharwho reviewed our ﬁrst draft and helped to create aclear and more focused paper.ReferencesAllen, T., Katz, R., Grady, J.J., Slavin, N., 1988. Project TeamAging and Performance: The Roles of Project and FunctionalManagers. R & D Management 18 (4), 295–309.Andersen, E.S., 1996. Warning: activity planning is hazardousto your project’s health!. International Journal of ProjectManagement 14 (2), 89–94.Andersen, E.S., Grude, K.V., Haug, T., 1995. The Goal DirectedProject Management, second ed. Kogan Page, London.Anderson, J., Gerbing, D., 1988. Structural equation modelingin practice: a review and recommended two-step approach.Psychological Bulletin 3, 411–423.Armstrong, S.J., 1982. The value of formal planning for strategicdecisions: review of empirical research. Strategic ManagementJournal 3, 197–211.Bagozzi, R., 1980. Causal Models in Marketing. Wiley, New York.Balachandra, R., 1984. Critical signals for making Go/NoGodecisions in new product development. Journal of ProductInnovation Management 2, 92–100.Balachandra, R., Friar, J.H., 1997. Factors for success in R&Dprojects and new product innovation: a contextual framework.IEEE Transactions on Engineering Management 44 (3), 276–287.Baker, N., Murphy, D., Fisher, D., 1988. Factors affecting projectsuccess. In: Cleland, D.I., King, W.R. (Eds.), Handbook ofProject Management. Van Nostrand Reinhold, New York.
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