Project Management Institute

Discriminating contexts and project management best practices on innovative and non-innovative projects

University of Quebec at Montreal


Global competition put pressured developed countries to invest in product and technical innovation, which have become the backbone of the new knowledge economy. Product and technical innovation in the business world today is a recognized and well-developed field of research. In this field of research, the project management perspective is limited. Understanding project management of innovation projects requires adopting a perspective that is both broader and more detailed than that currently found in the innovation management literature.

Managing an innovative project—a project that produces a new product or that involves a new concept and a new technology—is hypothesized as being different from managing projects that produce a standard product with low innovative content using few innovative technologies. If true, different processes will be required and tools and techniques will be used differently to execute these processes.

This paper is a part of ongoing research exploring project management practices, research that is based on the observation of the use of project management tools and techniques. For this paper, 91 well-known tools representing what is specific to the profession and what project managers do everyday are used to measure project management practices. Previous research has shown that comparing project management practice between projects in different contexts or of different types reveals both similarities and differences (Besner & Hobbs, 2006, 2007). The similarities point to the generic component of project management practice. On this background of generic practice, many significant differences can be identified. This paper is based on this same approach of seeking to identify similarities and differences in project management practice in different contexts and on projects of different types. The focus here is on innovative and non-innovative projects. Both contextual differences and differences in practice between high- and low-performing organizations are investigated as a way to discriminate contexts and project management best practices for innovative and non-innovative projects.

Literature Review

Research on Project Management Practices

Several papers on project management practices have been published in recent years, many of them examining practices by means of the use of project management tools and techniques. These studies generally focused on a specific knowledge area or a specific aspect of the use of tools (such as risk, quality, and barriers to use or implementation). See Besner and Hobbs (2006, 2007) for a more detailed review of this literature. Only a limited amount of research examines a wide range of practices and tries to identify general use and usefulness of project management practices. Besner and Hobbs (2006, 2007), Milosevic and Iewwongcharoen (2004), White and Fortune (2002) and Loo (2002) presented research analyzing contextual differences in project management practice. This paper is a part of this stream of research.

The idea of organizational project management maturity is another thread of literature that discriminates between poor practice and good practice. This theme has been among the most popular in the project management literature in recent years (Ibbs & Reginato, 2002; Jugdev & Thomas, 2002; Pennypacker & Grant, 2003). Much of this literature is based on the premise that project performance is correlated with levels of organizational project management maturity. Research results are as yet unconvincing, but important research is currently underway to further explore this relationship (Thomas & Mullaly, 2007). Because project management maturity is one of the contextual variables in the present study, the results shed some light on this issue.

Research on the Contexts and Practices of Innovative Projects

Innovation generates new ideas or methods to compete in existing market or to create new ones. Innovation in the project management literature is occasionally associated with project performance. The literature on innovation also relates innovation to successful organizations. According to Cooper, Edgett, and Kleinschmidt (2004b, p. 50), “best-performing businesses undertake a higher proportion of more innovative NPD projects, while the worst performers have a timid NPD project portfolio.” One could argue that this general statement does not apply to all market segments. This paper explores this issue by comparing best practices on innovative and non-innovative projects.

The factors explaining success in innovative projects could be grouped in many ways. The literature has examined innovation from numerous perspectives, that is, from different organizational functions at strategic, tactical, and operational levels as well as from context, market, and environmental perspectives; all have been used by researchers to explore innovation.

Since innovation is an endeavor to produce a unique deliverable usually in the shortest time possible, it is by definition a project-oriented temporary enterprise. No surprise then, that project management has also been recognized as a crucial best practice for successful innovation (Miller & Floricel, 2004; Thieme, Song, & Shin, 2003). Nevertheless, few researchers have explored the specific project management practices and context that support successful innovation projects.

Krishnan and Ulrich (2001) reviewed the literature on product development. They focused on business process decisions often supported by knowledge and tools. They distinguished product development itself (research about concept and product design) from staging the organizational context to develop the project. The project management processes deployed in setting up the development project are considered part of the academic field of operations management and as such exclude more strategic organizational perspectives. Krishnan and Ulrich (2001) further decomposed project management processes into decisions about prioritization, task sequencing, communication, tracking, and control. While providing more detail than general statements about project management, this breakdown does not provide the level of detail needed to understand project management as it is practiced on innovative and non-innovative projects and to provide guidelines for practice.

The project management practices observed in the present study extend beyond these basic project management operational level processes. The field of project management encompasses a broader view of the product development process and, therefore, a wider view of what Kristhnan and Ulrich referred to as staging the organizational context, including planning at a strategic level, project selection, project organizational structure, and so forth.

Much research has been directed at identifying key innovation success factors. The variables identified in this literature include strategic alignment and shared vision, communication and collaboration (Shum & Lin, 2007), cross-functional and multi-disciplinary teams (Terziovski, Sohal & Howell, 2002), project selection, portfolio management, better phase gates processes, resource allocation and availability of resources (Cooper, Edgett & Kleinschmidt, 2002, 2004b), and the “people side”: the organizational culture and climate, the engagement and commitment of senior management (Cooper, Edgett & Kleinschmidt, 2004a).

Shenhar (2001) proposed a theoretical framework based on a contingent approach to project management; he insisted that one size does not fit all. He linked innovation in projects with managing technological uncertainty and looked at the interplay of uncertainty with project complexity. More resources are necessary to manage larger and more complex projects. Shenhar showed that higher uncertainty is significantly linked to better planning and control procedures and tools in high-technology projects.

Innovation requires efficient planning and control, but it needs at the same time flexibility and empowerment (Khazanchi, Lewis, & Boyer; 2007). Badir, Buchel, and Tucci (2005) confirmed that team empowerment along with hierarchical levels, centralization, and formalization contribute to project performance, while Gebert, Boerner, and Lanwehr (2004) pointed out that the literature in general recommends more decentralization as one dimension of empowerment.

Models to structure the innovation process in its different phases are presented in the literature. Koskinen (2005) opposed the exploration phase in which the process is cluttered by ill-defined problems and ideas with the exploitation phase in which a well-defined process exploits specific knowledge, clear goals, and problem definition. “Despite the fact that front-end concept definition and selection are central to a firm's innovation capability, these activities are ill-structured and typically the most poorly managed in the entire innovation process” (Massey, Montoya-Weiss & O'Driscoll, 2002, p. 37). The results presented in this paper confirm many of those findings and give more specific insights into the contribution of project management by detailing project management best practices for innovative projects.


An investigation of project management practice may lead to the identification of best practices and inductively suggest new conceptualizations. The approach taken in this paper is to construct an empirical description of project management practice and then to interrogate that description to support theory building and validation. Project management practices are not entirely homogeneous. In this paper, we investigate both contextual differences and differences in practice between high- and low-performing organizations as a way of identifying those practices that indicate the existence of patterns and frames of reference.

This paper presents results from the second phase of an ongoing research program. Results from Phase 1 were published in Besner and Hobbs (2006, 2007). The program is based on empirical data provided by practitioners collected using Web-based surveys. The survey instrument is divided into two major sections. One section collects information on practitioner informants and the characteristics of both their projects and their organizational context (Crawford, 2000). The second section collects data on the actual use of project management tools and techniques. An extensive list of well-know tools and techniques is investigated. The respondents answer questions for each of these. After analysis of the results of Phase 1, small changes were made to the questionnaire. Some tools were added to the list and some tools that are used only very rarely were removed. In addition, several questions were added to the section on organizational context and project characteristics. The additions included the identification of innovative projects and high- and low-performing organizations. These additions are exploited during the analysis that follows.

The lists of tools and techniques used in the surveys were drawn from the PMBOK® Guide (PMI, 2004), the relevant literature, and other sources. The tools and techniques that have been selected are those that are identified with the practice of project management. The research reported above in the literature review most often includes both very general concepts and processes (such as training programs and performance measurement) and very specific tools (such as WBS and project charter), but does not make an explicit distinction between tools and processes. The present research investigates only tools and techniques that are project-specific and well known. It does not investigate general processes. Restricting the investigation to well-known tools and techniques specific to project management ensures that the questionnaire will be well understood by practitioners and that the results can be interpreted reliably. This paper is based on the examination of 91 well-known project management tools and techniques. These are presented in alphabetical order in Table 1.

Table 1. List of Tools by Alphabetical Order

Assigned project sponsor Fixed-price contract Program master plan
Assignment of risk ownership Gain-share contract Progress report
Baseline plan Gantt chart Project charter
Bid documents Graphic presentation of portfolio Project closure documents
Bid/seller evaluation Graphic presentation of risk information Project mission statement
Business case Kick-off meeting Project portfolio analysis
Business problem definition Lesson learned/post-mortem Project priority ranking
Change control board Management reserve Project procedures manual
Change request Medium-term post evaluation of success Project scorecard/dashboard
Client acceptance form Milestone planning Project war room
Communication plan Monitoring critical success factors Project website
Concurrent engineering Multi-criteria project selection Quality plan
Configuration review Needs analysis Ranking of risks
Contingency plans Network diagram Re-baselining
Contract documents Non-financial business benefits metrics Recovery schedule
Contract penalties Organizational capacity analysis Requirements analysis
Contractual commitment data Project management community of practice Responsibility assignment matrix
Cost/benefit analysis Project management software for issue management Risk management documents
Cost-plus contract Project management software for monitoring of cost ROI, VAN, IRR, payback
Critical chain method and analysis Project management software for monitoring schedule Scope statement
Critical path method and analysis Project software for multi-project resource management Self-directed work teams
Customer satisfaction surveys Project software for multi-project scheduling Stage gate reviews
Database for cost estimating Project software for project portfolio analysis Stakeholder analysis
Database of historical data Project management software for resource leveling Team building event
Database of lessons learned Project management software for resource scheduling Team development plan
Database of risks Project management software for scenario analysis Timesheets linked to activities
Earned value Project management software for task scheduling Trend report
Fast tracking / rapid implementation Project management software Internet access Updated business case at gates
Feasibility study Project management software linked with ERP Value analysis
Financial business benefits metrics Probabilistic duration estimate(PERT Analysis) Work authorization
Work breakdown structure

The Sample

Phase 1 of this research program was based on a sample of 753 responses (Besner & Hobbs, 2006, 2007). The results presented here are based on the analysis of 734 responses from a new sample. Approximately two-thirds of the sample examined here is composed of North American practitioners. The other third is spread across the globe:

Canada 36%
United States 30%
Other 34% (from 70 different countries)

The support of PMI's Research Department in soliciting Project Management Professionals accounts for the high proportion of respondents from the United States. The higher proportion of Canadians can be explained by the nationality of the authors, who solicited more widely their fellow Canadians and the support provided by both the Montreal and Southern Ontario chapters of PMI.

The sample is drawn from practitioners working on several types of projects, as shown below:

Information Technology 45%
Business and Financial Services 18%
Engineering and Construction 12%
Telecommunications 6%
Industrial Processes 2%
Others 17%

This distribution by project types is not out of line with the distribution of project management practitioners in general and with the distribution of PMI membership.

Respondents reported working in different organizational roles and also reported having significant experience in project management, as shown below:

Program director 29% with an average of 5.7 years of experience
Project managers 47 % with an average of 7.9 years of experience
Team members 8 % with an average of 8.7 years of experience
Other 16 % with an average of 7.3 years of experience

It is important that respondents be experienced in project management because they are reporting on project management as it is actually practiced. The sample is well distributed across many variables describing both organizational contexts and project characteristics, which greatly facilitates the comparative analysis upon which the results are based.

Measurement of Innovation

This paper focuses on differences between innovative and non-innovative projects. For the purposes of this paper, projects involving a high level of product or technical innovation are considered innovative projects.

Measurement of Performance

High- and low-performing organizations are identified from the respondents perceived rate of project success of their organizations when compared with their direct competitors, organizations from the same sector of activity. This measure was revealed to be one of the most robust by Cooper, Edgett and Kleinschmidt (2004a). Following a survey of 105 large organizations, they concluded that overall success measured against competitors was “particularly robust” (p. 35).

High performing organizations develop specific project management capabilities and adjust their practices to become efficient innovative leaders. Practices that discriminate high- and low-performing organizations can be used to provide guidance to other organizations seeking to improve their performance.

Measures of Project Management Practices

For each of the 91 tools and techniques respondents were asked to identify the actual extent of use on a 5-point Likert scale from no use to very extensive use.

Statistical Analysis

Pearson correlations were use to measure correlation between contextual variables. Anova procedures were applied to measure significant differences between the usage levels of tools in sub-groups. Crosstabs were analyzed to interpret significant relationships between contexts based on likelihood ratio chi-square statistics. The same level of significance, p < 0.01, was used throughout.

The Results of the Analysis

The Basic Toolbox

As previous research has shown, the most widely used project management tools and techniques are nearly the same across all contexts and all types of projects (Besner & Hobbs, 2006, 2007). The eight most widely used tools in Phase 2 are exactly the same as those identified in Phase 1, three years ago. This result is therefore extremely robust. Robustness is also verified against context, since the top 10 are almost identical in each subsample considered here: innovative and non-innovative; high and low performers. The identification of the same basic set of tools and techniques and the practices associated with these tools validates the idea of a generic project management field of practice as embodied by the bodies of knowledge, including the PMBOK® Guide (PMI, 2004). The content of the basic project management toolbox has thus been confirmed.

The last two tools of the list completing the top 10 of Table 2 are tools that were not part of the Phase 1 questionnaire, namely, contract documents and assigned project sponsor.

Table 2. The Basic Toolbox

1. Progress report 6. Requirements analysis
2. Kick-off meeting 7. Milestone planning
3. Gantt chart 8. Scope statement
4. Project management software for task scheduling 9. Contract documents
5. Change request 10. Assigned project sponsor

These results provide confidence that Phase 2 results are valid and coherent with Phase 1 for which face validity was thoroughly verified.

The following analysis involves comparisons between different subsamples to identify the presence or the absence of statistically significant differences and the discussion and interpretation of the differences or lack thereof. In order to make the results easier to follow, they have been broken down into sections, each presenting one set of comparisons. The comparisons have been further broken down, presenting first the comparisons of contextual variables, followed by comparisons of the use of project management tools and techniques and the associated practices. The expression “contextual variables” refers to a wide range of variables. It includes the characteristics of the organization, the respondents and the project. Some of these are very difficult or impossible to change, while others are amenable to influence by management.

Concerning the following sections, which discuss the differences in project management practices, the reader should remember that the most used tools in each case are the ones listed in Table 2. Each of the following sections present the tools that have the greatest differences in use for the specific context identified. Identifying the tools that are more used in a certain context is a way of identifying what discriminates practices in such a context. The practices and their context will be first compared between respondents who work on innovation projects and those who work on low-innovation projects. This is followed by comparisons between high- and low-performing organizations.

Differences Between Innovative and Non-Innovative Projects: Contextual Variables

The project environment surrounding respondents working on projects involving a high level of product or technical innovation was compared with the context of those working on standard products and technologies involving a low level of innovation.

The sample is well distributed (almost equally) across public and private organizations, large and small organizations (more than and less than 1000 employees), organizations highly mature and less mature in their project management processes. The sample is also split almost equally between external and internal, large and small, as well as long- and short-duration projects (using one year and $1 million project values as cutoff points). On all those dimensions, no statistically significant differences in the level of innovation were found between sub-groups, except for the very small projects (less than $50K), for which significantly fewer innovative projects were found. Also, no significant correlation was found between innovation and the different organizational structures, the sample being almost evenly distributed among functional, weak and strong matrices, and project-based structures. No significant correlation was found in relation with ill-defined or well-defined projects, nor with the existence of programs of projects versus individual projects. From this it can be concluded that innovation projects are found in many different contexts.

On other dimensions, statistically significant differences were identified, linking innovation to specific contexts. Looking at the application area of the projects, the level of innovative projects is significantly lower among the engineering and construction projects: 36% of participants work on innovative projects in engineering and construction, compared to 55% for the entire sample.

Significant positive relations were identified between innovation and complexity measures. This result confirms previous findings identified in the related literature. The relation with complexity was confirmed for the following two measures of complexity:

  1. Innovative projects involve a larger range of disciplines.
  2. Innovative projects have more interfaces with other systems/projects.

More innovative projects are also associated with: (1) a greater availability of competent human resources; (2) managers with more authority; (3) program directors more often than project managers. The associations with qualified and empowered personnel will be explored further in the following section.

Differences Between Innovative and Non-Innovative Projects: Project Management Practices

Project management practices in innovative projects are clearly characterized by a more extensive use of project management tools. Higher levels of usage are found for 78 of the 91 tools investigated. None are used significantly less. Seven out of the 13 tools for which levels of use are not significantly higher are related to contract management, indicating the contracts are as common in innovative projects as in the non-innovative. Table 3 presents the tools with the greatest differences in usage. Caution should be exercised in interpreting the lists showing the greatest differences, because the cutoff for selecting just the top 10 tools for presentation is arbitrary. Limiting to the top 10 can help identify the most important patterns within these differences by not letting too many details eclipse the essential.

Concurrent engineering can be related with the establishment of cross-functional, multi-disciplinary teams that distinguish, as previously mentioned, innovative from non-innovative projects. It is identified here as a practice that differentiates innovative projects from non-innovative ones. The next three tools listed refer to scope management; identifying and defining the deliverables is at the heart of the innovation process. The last tool in this list—updating business cases at gates—could also be related to scope management; the results of early phases of innovation projects often redefine the project, which requires more frequent redefinition of the business case. This highlights the especially difficult problem of defining both scope and business purpose in innovative projects.

Table 3. Tools with the Greatest Differences in Level of Use Between Innovative and Non-Innovative Projects

1. Concurrent engineering 6. Team development plan
2. Requirements analysis 7. Stakeholder analysis
3. Configuration review 8. Monitoring critical success factors
4. Work breakdown structure 9. Quality plan
5. Database for cost estimating 10. Updated business case at gates

Five tools of this list will be shown to discriminate better-performing organizations from worse-performing; they will be discussed in greater detail in the following sections. The examination of project management practices has identified significant differences in the way innovative and non-innovative projects are managed. Among organizations that conduct more innovative projects, some perform better than others. The following sections introduce differences associated with varying levels of performance.

Innovation and Success

The context and practices identified above distinguish innovative from non innovative projects without considering the level of performance. The analysis shows that a higher level of innovation is, in general, positively related to a higher rate of project success. This does not mean that all innovators are high performers. There are better and worse performers doing innovative projects, as well as better and worse performers carrying out non-innovative projects.

The general positive measure of success related to achieving more innovation could be perceived as an indication that all organizations should systematically become more innovative. However, some organizations may not need to be more innovative to fulfill their mission. The goal should not be to become more innovative per se. If a specific market is requiring efficiency and no innovation, the goal should be to become the best performer carrying out the required non-innovative projects. If innovation is necessary, which is more and more often the case in our new knowledge economy, innovative best performer organizations should be the model to follow. The following sections examine the differences in project management context and practices between the high and low performers for innovative and non-innovative projects.

Differences Between High and Low Performers Common to Innovative and Non-Innovative Projects: Contextual Variables

The sample was split almost evenly between respondents from high- and low-performing organizations. As mentioned previously, respondents were asked to rate their organization's performance on projects as compared to other organizations in their sector of activity. Four contextual variables were shown to discriminate between high-and low-performing organizations both for innovative and less innovative projects. The four contextual variables are level of project management maturity, level of authority given to the project managers, level of precision of the project definition, and availability of competent personnel. Each one of these factors is positively but weakly correlated with the three others, the Pearson coefficient varying from 0.14 to .34. The strongest relations are between the level of maturity and the level of project definition (0.34) and between the level of maturity and the available competent personnel (0.31). These non-specific factors are examined first; factors specific to innovative projects will then be presented.

A higher level of project management maturity within the organization is the most significant difference between high and low performers. The level of project management maturity of organizations was measured on a scale of 1 to 5, similar to the Software Engineering Institute's Capability Maturity Model (CMM). This result is consistent with results found in the literature. The result is interesting, but the measures are not robust enough to claim that the issue has been put to rest. The correlations among this group of four variables that are all associated with project success may point to a possible constellation of good practices. More research is required on this important issue. A possible avenue of research would be to investigate the relationships between project management maturity, project management practices, and project success. This, however, is beyond the scope of this paper.

The second most important factor is the level of authority given to the project managers. A high rate of project success is related to project managers having full authority to achieve project outcomes compared to those who have limited authority to make key decisions. Project manager empowerment is shown to have an effective impact on success. This result is consistent with results presented by Lechler (2000).

The third factor is related to the level of project definition. Respondents working in high-performing organizations perceived their projects as being better defined. There are at least two possible interpretations of this result. The difficulty inherent in managing ill-defined projects may explain the lower success rate associated with this type of project. Defining a project is uncovering what needs to be done; ill-defined projects are harder to manage, since the project goal is a moving target. Success is therefore harder to achieve. It is also possible that more successful organizations do a better job at defining their projects and that the association between good definition and success is a product of good project management. The correlation between project management maturity and project definition would seem to support this second interpretation. However, both may be partial explanations working in tandem in many situations.

The fourth factor that differentiates high- and low-performing organizations is related to the availability of competent personnel. Lechler (2000) identified that the project manager's authority is a determinant of the competency of the project team. In other words, more powerful project managers are able to procure better resources, which in turn contribute to better project performance. Gadeken (1997) also presented similar results. The methodologies used by these two researchers allow them to confirm the direction of the causal relationships.

Differences Between High and Low Performers Specific to Innovative Projects: Contextual Variables

Focusing now on projects with a high level of innovation, only one additional factor related to context has been shown to differentiate high performers on innovative projects. The involvement of the project manager or program director during the initial phase of the project proved to be a discriminating factor. The initial phase is the one during which the project is initiated and the general concept developed. The involvement of the project/program manager provides added value for three reasons. First, the project/program manager brings a needed perspective and information to the development of the project during this phase. Second, at the start of the next phase the project/program manager is already well informed on the project, which facilitates a more seamless transition. Third, a project/program manager who was involved in the front end is more aware of the project rational behind the project, including the expected benefits, and is also more aware of the project context. All of these factors contribute to better decision making during the project life cycle on innovation projects where a clear vision of the project objectives and context are particularly critical.

Although participant involvement in the initiation phase is high for the entire sample, it is the program managers/directors who are particularly active during this phase. Besner and Hobbs (2006) also found a higher level of authority of the practitioners participating in the initiation phase and confirmed the phase's more strategic nature. The participation in the initiation phase of the project is not significantly related to the other general success factors described above.

During the fuzzy front end, an initial project definition is sought and the strategic scheme underlying the development of the innovation is established. A false start in the wrong direction is more likely to lead to failure (Morris, 1998). Participation in this phase is therefore an important role of the project manager and a vital part of project management practice. Almost all project managers participate to the planning/development, execution, and implementation phases, which is the traditional role of project managers. The discriminating impact on success of participating in the early phase of innovative projects is a strong argument for the official inclusion in this phase of the project management. This phase is presently neglected by the project management literature in general, and the PMBOK® Guide (PMI, 2004) in particular.

Differences Between High and Low Performers Specific to Non-Innovative Projects: Contextual Variables

Considering now non-innovative projects, the type of project organization adopted to manage the projects has a significant influence on the rate of success. A greater number of high performers are project-based structures, as opposed to functional or weak matrix structures. The type of project organization is weakly correlated to the general success factors described above. Organizations more mature in project management adopt a project-based structure more frequently and more fully. Projectized structures lead to better-defined projects and more authority given to project managers. Competent personnel are also more available to the projects in projectized structures.

The second specific contextual factor related to more successful non-innovative projects is the type of customer: internal or external. The results indicate different best practices for internal and external customers. For external customers, a higher proportion of high performers undertake non-innovative projects. This suggests that projects do not necessarily need to be innovative to be efficient and effective for these customers who are not seeking innovative products or services. Besner and Hobbs (2007) showed that projects for internal customers are managed quite differently from those for external customers. Organizations with external customers tend to be more mature, as well. As would be expected, they also have better-defined projects.

Differences Between High and Low Performers: Project Management Practices

In both of the sub-samples of innovative and non-innovative projects, many tools and techniques are used more in high-performing organizations. In the sub-sample of innovative projects, 67 of the 91 tools are used significantly more in high-performing organizations. While on low-innovation projects, only 37 are used significantly more in high-performing organizations. Moreover, the tools that show the greatest differences in level of use are quite different in each sub-sample. For this reason, they are presented and discussed separately. Table 4 presents the 10 tools with the most important differences in level of use between high and low performers for both the innovative and the non-innovative sub-samples.

Two tools are common to both lists: database for cost estimating and team development plan. Cost is an important success criterion, and estimation of cost is crucial to success. Measures of cost performance against the project budget are both very visible and often readily available measures of performance. In addition, cost performance is directly related to return on investment, which is a primary concern of senior management. It is therefore easy to understand why cost estimates based on reliable data differentiate so well between high- and low-performing organizations. The established association of databases for cost estimating with innovation is in part due to the fact that innovation is itself related to better performers. Considering the high uncertainty about the cost of innovation, organizations invest in a cost estimating tool to better approximate project demands on their scarce resources.

Table 4. Tools with the Greatest Differences in Level of Use Between High and Low Performers

Innovative sub-sample Non-innovative sub-sample
1. Database for cost estimating 1. Quality plan
2. Stakeholder analysis 2. Database for cost estimating
3. Database of historical data 3. Team development plan
4. Database of lessons learned 4. Monitoring critical success factors
5. Database of risks 5. Earned value
6. Team development plan 6. Client acceptance form
7. Work authorization 7. Change request
8. Value analysis 8. Customer satisfaction surveys
9. Medium-term post evaluation of success 9. Responsibility assignment matrix
10. Project mission statement 10. Milestone planning

The importance of the team development plan highlights the importance of project teams to both innovative and noninnovative project success. The present research program focuses on project management tools and techniques, few of which are related to the human side of project management. The team development plan is an exception in that it is directly related to human resources development. The presence of this tool on the list of the tools that discriminate the most between high and low project performance may be just the tip of the iceberg. The human side of project management is a critically important dimension, but is not covered well by traditional project management tools. This may be to a large extent because the methods that lead to high-performing teams may not be specific to project management. This tool was also among the ones differentiating innovative from non-innovative projects; the presence of more multi-disciplinary teams and more competent personnel in innovative projects may explain why.

Differences Between High and Low Performers Specific on Innovative Projects: Project Management Practices

Databases are generally used less than most tools. The reason identified by Besner and Hobbs (2006) is related to the fact that individuals cannot use databases without the support of their organizations. However, four databases are among the tools that discriminate the most between high and low performance on innovative projects (left side of Table 4). Besner and Hobbs (2006) identified these same databases as the tools having the most potential to contribute to better project performance through a greater or better use. The use of databases could also be related to the greater rate of success of well-defined projects. Databases are organizational learning tools. They are ways to capture knowledge, and the use of this knowledge would certainly help better define future projects. Their presence in the list above means that their level of usage is much higher in organizations that successfully manage innovative projects. Developing such tools could therefore be considered an investment opportunity for organizations that want to support their innovation process.

Project mission could also be related to the necessity of better defining the project to reach success. This concise expression of the high-level project goal defines the project at an early stage. It can help focus attention or re-center it on the essence of the project. Focusing on the main purpose of the customer, on the business value, and critical parameters helps the team better define scope at lower-level project deliverables, particularly in highly uncertain and hard-to-define innovative projects.

The stakeholder analysis may be used in each phase, but Besner and Hobbs (2006) showed its more significant role in the initiation phase. This analysis is most useful during the fuzzy front end to clarify and manage expectations. There is then a double correspondence with the necessity to better define the project and a greater involvement in the initiation or concept phase as discussed above.

Value analysis is also a determinant decision-making tool used during the front end of the project. Value analysis is more closely related to product design than staging and managing the project itself. Nevertheless, value analysis is very relevant to innovative projects.

It is often not possible to ascertain the success of innovation projects at the time of their completion. Innovation projects are evaluated at a later stage after the innovation has been put into service or the market has had time to respond to the innovative product or service. The project can, at that time, really prove its effectiveness. High performers distinguish themselves from low performers with medium-term post evaluations of success. This measure of performance aligns the project goal to the longer-term success of the product rather than the shorter life of project development. Medium-term post evaluations of success focus greater attention and accountability of the project manager and other stakeholders on project benefits, more on effectiveness than on efficiency. This result is linked with the notion of empowerment that was identified as a central success factor.

Work authorization is an interface between the plan and its execution. A work authorization system is a formal procedure to authorize work before it is performed on the project. It is a traditional view of project coordination and more research would be necessary to better explain its presence in this list.

Differences Between High and Low Performers Specific to Non-Innovative Projects: Project Management Practices

The list of the 10 tools with the most important differences in use between high- and low-performing organizations is on the right section of Table 4.

The second and third tools in this list, database for cost estimating and team development plan, as previously discussed, are used significantly more in high-performing organizations, for both innovative and non innovative projects.

The quality plan is the tool with the greatest difference in use between high and low performers on non-innovative projects. The quality plan is a set of activities planned at the beginning of the project to achieve customer's quality expectations. It specifies quality criteria for each deliverable, referring to standards and norms that the final product must meet. Such criteria and customer expectation are more easily defined for standard products with low levels of innovation and are more extensively used in high-performing organizations producing standard products. The customer satisfaction survey can also be related to quality management. The use of surveys to measure customer satisfaction is often required of organizations that obtained ISO certification as part of the quality management system requirement. Emphasis on quality planning and control is thus strongly linked to success, especially in the context of standard production or low-innovative projects.

The quality plan is also one of the ten most used tools in innovative projects compared to non-innovative (see Table 3). Besner and Hobbs (2007) showed that some types of projects are clearly time-driven and others more cost-oriented. The project managements tools specific to innovation identified here are first and foremost connected to scope and content definition; quality expectations is related to these aspects. Quality plan is more difficult to define in high innovative projects and is not the most discriminating tools of high performers in innovative projects. Its absolute level of use by high performers is very high on well defined innovative projects.

Besner and Hobbs (2007) reported that earned value tools are used significantly more in engineering and construction projects, which have been identify in this paper as less innovative on the average. Earned value cannot exist without a well defined overall baseline plan, which is easier to develop a priori with standard products and well-known technologies. The same logic could be applied to explain the presence of the change request on this list because change is in reference of a pre-specified deliverable and a pre-defined plan. In addition, poorly tracked changes are a root cause of budget overrun in predefined and budgeted projects. The efficient use of change procedures is a well-established best practice in such projects.

Milestone planning is a summary-level schedule that identifies the major milestones, which are significant events in the project, usually completion of a major deliverable. It is related to the capacity to define and plan the project in advance. Milestone planning could be opposed to a detailed planning in bringing focus to the essential (not losing the view of the forest while taking care of the trees). This mindset combined to emphasis on team responsibility and commitment describe below could be ingredients of a recipe for success.

The responsibility assignment matrix relates all project stakeholders of the project organization to the work breakdown structure which define the exact scope of the project. This ensures that responsibility is assigned for each element of the project's scope of work. Koskela and Howell (2002) developed a theoretical framework in which they underline the importance of management-as-organizing, as opposed to management-as-planning and the importance of stakeholder commitment in a language/action perspective. Discussing and assigning responsibility have an impact on the short term commitment of project participants as oppose to longer term commitments discussed in the previous section. It is here showed to have an impact on success particularly for low-innovation projects.

The client acceptance form is usually used with external clients, and success was shown to be linked with external customers in low-innovation projects. Finally, it is not surprising to see that a more extensive use of critical success factor monitoring is linked to a higher rate of success, particularly in the more stable environment of low-innovation projects. At the same time, we saw that monitoring success factors plays an important role in innovation, as it was also identified in Table 3 as being among the tools that differentiate the most innovative from non-innovative projects.

Discussion and Conclusion

Implementation of proper project management processes is a recognized key success factor in the innovation literature. Few researches have explored more precisely which good project management practices lead to success. This paper identifies specific project management practices and contextual variables related to innovative project success. Moreover, the results suggest that innovation is not an inevitable path to success; there are enterprises that do not necessarily need to be innovative to fill customer needs. It could also be argued that not all phases or components of an innovative project are equally innovative; an innovative program can incorporate non-innovative projects. This paper therefore also identifies some of what is specific to non-innovative projects. The results are complementary and largely consistent with the existing literature.

High performers use project management tools and techniques more extensively, and do so all the more when they carry out innovative projects. Investigating the use of project management tools and techniques revealed the nature of the processes and best practices adopted by high-performing organizations. The context related to this usage together with the patterns of identified practices suggest different sets of success factors for innovative and less-innovative projects, and some factors common to both. A higher level of project management maturity within the organization is the most significant difference between high and low performers. This paper is one of the few that show the strong relationship between successful organizations and the maturity of their project management processes. Three other success factors weakly related to maturity are the authority/empowerment of the project manager, the availability of competent personnel, and a better-defined project at the outset.

Specific project management practices related to innovative or non-innovative high performing organizations are often directly associated with the contextual success factors that were identified. The higher level of use of databases, for example, can be related to the level of project definition. The level of authority of the project managers and the level of competency of the project personnel emphasize the human resource factor, while the responsibility matrix and medium term post evaluation of success tools underline the role of accountability and commitment of these crucial resources. Participation in the initiation phase also discriminates better performers of innovative projects. The point of view of the project manager practitioner is traditionally linked to efficiency and associated with operations management. The reality of the project manager role, particularly on innovation projects, is shown to be much larger. Participation in the initiation phase and the use of medium-term post-evaluations demonstrate both involvement throughout the project life cycle and responsibility for business benefits. The project manager role is therefore focused not just on efficiency, but on effectiveness as well.

A greater number of innovative projects are found to be led by better-performing organizations. Project/program managers with a higher level of authority and a greater availability of competent personnel are found to be contexts that discriminate between innovative and non-innovative projects. These factors are also success factors; in this way innovation is related to success.


The authors wish to thank Harry Stefanou and Ed Andrews, previous managers of PMI's Research Department, for their support in data collection.


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