Master Thesis
What is NPPM success and how can it be measured? A systematic literature
review
by Stefan Voskeuil
Master Thesis
MSc BA Strategic Innovation Management Faculty of Economics and Business
University of Groningen
Student: Stefan Voskeuil Student number: 2697769 Email: S.F.Voskeuil@student.rug.nl
Supervisor: Dr. J.D. van der Bij Co assessor: Dr. K.R.E. Huizingh
Word count: 14625 Date: 14-07-2020
Version: final
2 Abstract
3
Table of Contents
1. Introduction . . . 4 2. Methodology . . . 5 2.1 Data collection . . . 5 2.2 Data analysis . . . 6 2.3 Data synthesis . . . 8 3. Results . . . 83.1 Measurements and definitions of NPPM success . . . 8
3.2 Descriptive analysis . . . 10
4. Discussion . . . 17
4.1 Main findings and implications . . . 18
4.2 Limitations . . . . 20
4.3 Future research avenues . . . 20
5. Conclusion . . . 21
References . . . . 23
Appendix A . . . 27
4 1. Introduction
New product portfolio management (NPPM) and picking the right new product projects are vital for a firm to maintain its competitive position (Cooper, Edgett & Kleinschmidt, 1999). Portfolio management is all about resource allocation to achieve the business’s new product and technology objectives. It is a dynamic process, whereby a business’s list of active new product (and R&D) projects is constantly updated and revised (Cooper et al., 1999, Kester, Hultink & Griffin, 2014). It has gained a central position in project management, development research, and company management practice within firms (Martinsuo, 2013).
The most detailed research papers to date, conducted by Cooper et al. (1999, 2000, 2001, 2002) found three characteristics of NPPM success: strategic alignment, maximizing the portfolio value, and balance. Also, Kester has described three dimensions of decision-making in new product development (NPD) that are associated with the dimensions of Cooper on portfolio success, i.e. the dimensions Kester et al. (2014) identified should make sure NPD portfolio success is reached. These dimensions are portfolio mindset, focus, and agility.
Despite the seeming importance of managing NPD in the portfolio, firms still struggle to achieve success in their NPD efforts (Griffin, 1997). The question, however, arises: ‘What exactly is NPPM success?’ According to McNally, Durmuşoğlu & Calantone (2013), firms improve their abilities to generate multiple new product ideas that are consistent with current product strategy and select the projects with the highest likelihood of success, which should improve new product performance. Cooper et al. (1999) argue that portfolio management and the prioritization of new product projects are vital for successful business performance and they state several requirements. To gain NPPM success, managers have to understand that portfolio management is about making strategic choices, product choices that managements make today determine what their business will look like five years out, it entails resource allocation, and it deals with the critical issue of balancing resources available with the numbers of projects (Cooper, 1999). Nonetheless, it remains unclear what actually comprises NPPM’s success, and therefore the first part of this paper will reveal what is known in the extant literature about this subject by conducting a systematic literature review.
An impediment to this systematic analysis is the loose application of the term ‘portfolio management. Therefore it is, at first, important to make a distinction between (single) project management and portfolio management. Project management can be defined as the process of controlling the achievement of the project objectives (Munns & Bjeirmi, 1996). A project is a single undertaking: a series of tasks that aim to produce a specific product, service, or benefit within a defined timeline, while on the contrary, portfolios focus on a higher-level view of an organization's activities (Martinsuo & Lehtonen, 2007). Hence, this paper will not lay its focus on single project management but considers portfolio management in its entirety.
5 A definition of project portfolio management is presented by Blichfeldt and Eskerod (2008), who describe the ‘managerial activities that relate to the initial screening, selection, and prioritization of project proposals, the concurrent reprioritization of projects in the portfolio, and the allocation and reallocation of resources to projects according to priority’ (p. 358). This definition falls within the scope of this research and is, therefore, included and followed in this paper.
Another argument showing the inconclusiveness of the literature is clarified by the fact that the popular press has made some possible suggestions for solutions in the portfolio management (Benko and McFarlan, 2003; Brown and Eisenhardt, 1998), however, empirical research has not yet developed or adopted really feasible solutions to achieve new product portfolio management success that would sufficiently account for practice and context (Martinsuo, 2013). Above all, it appears unclear what actually comprises NPPM success in the first place.
Therefore, the above-mentioned leads to the following research question: ‘RQ: What is NPPM success and how can it be measured?’
By answering the research question, this paper aims to contribute to the portfolio/innovation management literature, by conducting a systematic analysis of determinants of NPPM success (in the rest of this paper also referred to as ‘portfolio success’). This process will lead to a comprehensive multidimensional framework of clusters on which to build measures of NPPM success determinants and outcomes. The purpose of this study is, therefore, to identify, review and organize empirical research on NPPM success and, nonetheless, to establish a research agenda by describing the areas where further research would create a more nuanced view.
In the following sections, first, the methodology of this study will be presented, discussing the data collection strategy and the method of data analysis. Second, the results will be presented. Here the measurements and definitions of NPPM success will be discussed, as well as the descriptive analysis will be provided. Finally, this paper concludes with a discussion of the key findings and implications, the study limitations will be addressed, and future research avenues will be identified.
2. Methodology
Although a significant number of articles have been published discussing various aspects of determinants of NPPM success, no commonly accepted body of knowledge synthesizes their findings. This paper follows the systematic literature review structure suggested by Crossan and Apaydin (2010), following the three steps of data collection, analysis, and synthesis. The data collection step involves a systematic search and selection process of literature to be reviewed. This step follows the methodology implemented by Meier (2011) and Wassmer (2010) regarding the selection of literature, which will be elaborated on later. The data analysis step involves reviewing the articles resulted from the search process and matching these to offer a comprehensive overview of the current literature. Lastly, the data synthesis step initiates the new knowledge that delivers the contribution of this systematic literature review.
2.1 Data collection
6 product portfolio performance, portfolio performance measures. The following filters had been selected during the search process: the document type was filtered into articles and chapters, the language selected was English. The keywords were used as a selection for the title, subject, abstract, or keywords.
The search process went as follows. Every keyword would have been searched for individually in every database. This resulted in 1924 articles. To further reduce the number of articles and eliminate the possible overlap between searching on different keywords, groupings were made which takes into account duplicates. The articles were filtered into three groups. Since the main goal of this study is to find insights into NPPM success and thus a broad overview was needed, the first group of interest is meta-analyses and reviews. The second group was obtained by citation-based selection criteria and thus filtering on highly-cited papers. And the third group were recent papers (2017-2020) since those articles could not get cited as much as older papers but could be useful for this study. 2.2 Data analysis
Group 1: Meta-analyses and Review Papers
Meta-analyses and review papers were found as follows. The above-stated keywords were searched for individually and the words “review” and “meta” were added to the search process. This resulted in a total of 275 papers. Papers were at first judged by their title, abstracts were only read if the paper had one of the keywords (partially) in the title. Titles that were for example focused on single project management were rejected since the focus of this study is the management of a whole portfolio. Resulting in 88 titles being good enough to read the abstract. After reading the abstracts, nine papers were being downloaded. Abstracts should be focused enough on NPPM, when NPPM, NPPM success, or portfolio performance/success was just mentioned but not really a part of the study, the paper would not have been downloaded. Resulting in only nine meta-analyses or review papers that were written in a proper analytical sense, with the remainder being purely and/or narrowly focused articles (e.g. on financial markets, architecture, accounting, law, etc.). Eventually, after carefully reading the nine meta-analyses/review papers, only two turned out to be useful and were integrated.
Group 2: Highly cited papers and Top and very good papers
7 This resulted in 106 articles published in top and very good journals. Three of those articles were already integrated into group 1.2 and thus already found through highly-cited methods. Consequently, those three articles were not further judged since they already were part of the other groups. 49 articles had titles where the search words were integrated and therefore 49 abstracts were being read. 23 of those abstracts did not have enough overlap with the subjects of this study while the other 26 did have enough overlap with the subject of this study, thus, 26 papers were downloaded and were fully read. Eventually, eight papers were being integrated into this research. The papers that were downloaded were published in the following journals from the SOM list: Journal of Product Innovation Management, Industrial Marketing Management, Management Science, the Academy of Management Journal, Research Policy, Journal of Business Research, Journal of Operations Management, and European Journal of Operational Research.
Papers that were excluded: book reviews; non-business, purely descriptive, narrowly focused, and difficult to generalize papers; those that focused on process innovation (instead of product innovation); and papers in which the term ‘portfolio’ was used to address (for this research) nonrelevant subjects such as ‘accountancy’, ‘financial outcomes’ or ‘stocks/bonds.’ An overview of the exclusion and inclusion criteria is stated below in Table 1.
Table 1: Exclusion and inclusion criteria (adapted from Meier, 2011)
Inclusion criteria Exclusion criteria
Theoretical papers
Mainly articles that provide the basis for summarizing and integrating the empirical evidence.
Quantitative and qualitative empirical papers Both types of studies have been included in the sample of reviewed articles.
All industries
The article provides a cross-industry overview of the literature.
All countries
The article provides a cross-country overview of the literature.
Pre-1997
The seminal paper of Cooper et al. (1997) is chosen as the reference point of this review. Previous papers have been excluded.
Publication type
Book reviews, non-business, purely descriptive, too narrowly focused, and difficult to generalize papers have been excluded.
Deviating subjects
Papers that focused on process innovation, project management, or the term ‘portfolio’ referred to (for this paper) nonrelevant subjects have been excluded.
Group 3: Recent papers
Since recent papers could have been discriminated against during the citation-based method, because of the short amount of time they could have been cited, the initial pool of search results was filtered for recent papers (2017-2020). This resulted in a total of 1372 search results for all search terms together. Eight results had overlap with other search terms or were already found in the two groups mentioned before. Only 149 titles had at least one of the search terms mentioned (partially) integrated and thus met the requirements. After reading the abstracts of the 149 papers, 54 articles were downloaded. Those articles were downloaded since they were focused on this paper subjects whereas the other 95 abstracts were too focused on NPD or projects. Eventually, this resulted in six recent papers being used for this study.
Reference papers
8 or contributes to- this study. Then the abstract was read and when they seemed useful the articles were fully read. This resulted in a total of 32 reference papers useful for this study.
2.3 Data synthesis
To analyze the pool of all 137found articles, data is collected from each paper found. To find insights on mutual relationships, as well as relationships on NPPM success, a descriptive analysis is conducted, within particular the data on year of publication (from 1997 to today), journal of publication (name of journal), data collection period, research method as well as details on sample size, definitions of NPPM success, hypotheses and correlations, prevalent theories, and constructs (Kohli & Melville, 2019). Moreover, the process is engaged through synthesizing the literature by contrasting and comparing the findings. The results of this process of analyzing the papers are stated in the (upcoming) path models (Figure 2 & 3) capturing different relationships, presented in the results section. Below, the study selection process is outlined in Figure 1 (‘based on Figure 2 of Dikert, Paasivaara & Lassenius, 2016’). Ultimately, (after subtracting the duplicates) 59 papers are used in this study.
Figure 1: The study selection process
3. Results
In this section, the measurements and definitions of NPPM success, a descriptive analysis of the initial sample, and a review of the selected articles will be provided. By scoping out the theoretical field the results will be analyzed, a preliminary path model (Figure 2), and the final path model (Figure 3) of the existing research will be displayed.
3.1 Measurements and definitions of NPPM success
9 the sake of clarity of this research, it is important to write out the measurements of these dimensions here. Firstly, value maximization is measured through financial returns such as long-term profitability or return on investment (Cooper et al, 1997). Secondly, balance is measured by evaluating projects based on the extent to which the mix of NPD projects is proportional across multiple considerations. Examples are long-term projects versus short-term ones, high-risk versus low-risk or across various markets, technologies, product categories, and project types (Cooper et al, 1997). In other words, a balanced portfolio has harmony concerning specific parameters (Kester et al., 2011). Thirdly, strategic fit assesses projects in terms of the extent to which they reflect the firm’s strategy (Cooper et al, 1997). Cooper et al. (1997) expands their definition by adding the importance of having the right number of projects (for the resources available) and having the right time to market (which is the time between idea generation and actually bringing a product to the market) to avoid gridlock. Besides, Kock, Heising, and Gemünden (2015) add the importance of preparing innovation portfolios for the future, which is seen as a measure for the quality of the strategy of the portfolio (Voss & Kock, 2013).
Over time measurements are added based on extended definitions of portfolio success. For instance, the measurements in the article of Jonas (2010), which are process effectiveness, portfolio success, and portfolio-related corporate success, intersect with those of Cooper. Furthermore, how NPPM's success is being measured depends on the objectives of the portfolio process. Jonas et al. (2012) for example states that the average project success and use of synergies are together the maximizations of value. In the article by Meskendahl (2010), this dimension of value maximization is subdivided into two dimensions, namely average project success, and synergies. Some deviating measurements are described in the paper of Kraiczy, Hack, and Kellermans (2014) which refer to the NPPM success measurements ‘degrees of product innovativeness’ (Miller & Friesen, 1982; Prajogo & Ahmed, 2006) and ‘patent counts’ or ‘citations’ (Hagedoorn & Cloodt, 2003). Nevertheless, at the end of the article, these authors use the dimensions of Cooper et al (1997) for their research also.
Altogether, the following measurements appear to be essential in literature for measuring NPPM success: 1) Value maximization. 1a) Average single project success. 1b) Synergies. 2) Balance; with in particular 2a) Having the right number of projects. 2b) Having the right time to market (avoiding gridlock). 3) Strategic fit 3a) Future preparedness. An overview of all the measurements is summarized in table 2 of Appendix A.
As earlier stated, the basepoint of this study concerning the definition of NPPM success is the definition introduced by Cooper et al. (1997). On top of that, Cooper et al (1997, 1999, 2001) also state six success criteria for portfolios: 1) Having the right number of projects in the portfolio for the resources available. 2) Voiding pipeline gridlock in the portfolio. 3) Having a portfolio of high-value projects. 4) Profitable high-return projects with solid commercial prospects. 5) Having a balanced portfolio. 6) Having a portfolio of projects that are aligned with the business strategy. Also, Kock et al. (2015) add the importance of preparing innovation portfolios for the future to gain success. This is also indicated by McNally et al (2013)., who argue that firms should select the projects with the highest likelihood for portfolio success and generate multiple new product ideas. Jonas, Gemünden and Kock (2012) divide the second dimension of maximizing value into two dimensions namely: 1) The average project success over all the projects in the portfolio in fulfilling time, budget, quality, and customer satisfaction objectives. 2) The exploitation of synergies between projects.
10 Synergies. 3) Balance; which includes 3a) Having the right numbers of projects and 3b) Having the right time to the market.
3.2 Descriptive analysis
There are multiple variables found in the literature that measure NPPM success. These variables are critically analyzed and each must have a clear direct relation – or a moderating/indirect effect (which is discussed later in this chapter) – with NPPM success. For the clarity of this research, it is important to acknowledge that the search process starts with portfolio success and studies this subject. What is meant with this is that this research stays very close to portfolio success itself; it sometimes encounters variables that define success and sometimes encounters variables that are close to it, but it never considers variables that predict success remotely. Therefore, a variable is not seen as a predictor of NPPM success here, but more as a determiner. Hence these term ‘determinant’ is used further on in this paper.
The cluster analysis is done by clustering the determinants found into groups so that the determinants in one group are similar to each other, and as dissimilar as possible from the determinants in the other groups (Hand, Mannila & Smyth, 2001). Using cluster variables to group the found determinants into clusters that share common characteristics allows reducing the number of variables for analysis, therefore aiming to make it less complex. Next to that, the preliminary- and final path models (Figure 2 & 3) are based on the determinants that fall within the method of New Product Portfolio Management or falls under Portfolio Success itself. These determinants are clustered, resulting in the cluster variables stated in table 3 of Appendix B. The cluster variables are created by combining the determinants that are similar in the subject to arrive at an overarching term. Furthermore, clusters were created from determinants similar in subject and therefore took place around the same moment in time during the portfolio process. Determinants that influence portfolio success but do not fall within the portfolio management or portfolio success approach were not included.
In Figure 2 below, a preliminary path model of the three main cluster variables and their relationship with NPPM success is displayed. Next, the for this paper used explanations of the main cluster variables will be provided, as well as the definitions of the associated determinants, and the relationships of the cluster variables on NPPM success are discussed.
11 Portfolio Information
The first main cluster variable in the above stated initial path model of Figure 2 is Portfolio Information. This cluster variable consists of eight in literature found determinants that affect NPPM success. Below, the description of this cluster variable, as well as the belonging determinants are discussed.
At first, it is important to demarcate Portfolio information for this paper. Although some attention in extant literature devoted to this subject is available, it is particularly focused on the project level (instead of the portfolio level) and descriptions vary. Therefore, portfolio information is considered in this paper as all the concerning information of projects, plus the associated risks, needed for a successful portfolio. Looking at the found within-cluster determinants; this cluster can be subdivided into two subcategories about ‘information itself’ and ‘information regarding risks.’
Information can work in two ways. At first, it is important to have high information quality to increase the chances of project portfolio success (Cooper et al., 2001). Information quality is concerned with the availability, comprehensiveness, and transparency of information (Teller, Unger, Kock & Gemunden, 2012). On the contrary, the lack of project information has been highlighted as a central barrier to the success of project portfolio (Cooper et al., 2001). This determinant needs explanation here since for this paper the way of looking is as follows: project information is all the information of the project for the portfolio. In the portfolio, this information can be uncertain and changing and is a characteristic of portfolio decision making which will be discussed later on. However, a similarity between these two is that they are both not (yet) have been tested in the literature. To channel information flows from the project to the portfolio level, successful organizations have a shared reporting approach, which is defined here as the determinant portfolio reporting (Müller, Martinsuo & Blomqist, 2008).
When there is, for example, information asymmetry (imbalance), risks, and information about risks come into play (Teller, 2013). This is illustrated by the overarching found determinant of project portfolio risk management quality, consisting of risk coping capacity, risk transparency, and risk management efficiency, and is positively related to project portfolio success. Portfolio risk management quality mediates the relationship between portfolio risk management and project portfolio success. This means that the integration of risk management into the project portfolio management process is positively related to project portfolio success (see for more explanation concerning mediators also ‘moderating clusters’). Teller & Kock (2013) found that in practice the relationship between risk management quality and project portfolio success increases with a higher degree of internal-, as well as external-dynamics. Risk management efficiency is not stated separately as a determinant in table 3 of Appendix B since this a qualitative proposition and therefore left out of further consideration. Moreover concerning risks; risk prevention has a significant positive effect on risk coping capacity as well as a direct positive impact on project portfolio success (Teller & Kock, 2013). According to Teller & Kock (2013) and Ropponen & Lyytinen (1997), risk prevention is needed to prevent the identified risks from materializing. It involves risk response measures, which need to be adopted ex-ante, to enhance the organization's capacity to cope with risks and increases the effectiveness of risk management. All of the above-stated forms of risk determinants are included in this cluster since they all entail information regarding risks.
12 expects that the quality of the information and the successful implementation of the information cluster affects the decision making and its results. Apart from that, some suggestions for the relationships of within-cluster determinants (of portfolio information) on the decision-making cluster variable are already made in the literature. For instance, high information quality over the project landscape forms the basis for good decision making and facilitates the prioritization of the right projects (Teller et al., 2012). Furthermore, Cooper et al. (2001) found that project information is a characteristic of the portfolio decision process. Nevertheless, there is still a gap here and therefore offers room for future research avenues.
Portfolio Decision Making
The second and biggest main cluster variable in this study concerns the portfolio decision-making and consists of ten determinants found in the literature.
Portfolio decision making is an integrated system of processes that considers project prioritization, selection, and project termination decisions (Kester et al., 2014). However, NPD portfolio decision making is much more complex than just selection and termination decisions. It also includes decisions to delay projects, or to continue them, but with reduced resources (Müller et al., 2008; Kester et al., 2014). Therefore, one can say that portfolio decisions must balance a multitude of conflicting goals of an organization (Müller et al, 2008).
13 synergy. The authors state that these managers' support and involvement activities in the portfolio management process will achieve portfolio success, however, this determinant has not been tested in the article of Yang & Xu (2016). Finally, project portfolio success is highly positively associated with information quality, cooperation quality, and allocation quality, which together compose the determinant project portfolio management quality (PPM quality). Jonas (2010) already suggested PPM quality as a predictor of project portfolio success. This is confirmed by the research of Teller et al. (2012) who explain that increased PPM quality promotes and generates better management decisions, thereby improving success. According to their research, PPM Quality has a positive (tested) effect on project portfolio success (Teller et al., 2012).
The last two within-cluster determinants are focus and agility. Kester et al. (2014) suggest that these dimensions of NPD portfolio decision-making effectiveness (i.e., portfolio mindset, focus, and agility) are associated with achieving the three dimensions of NPD portfolio success (i.e., strategic alignment, maximal NPD portfolio value, and portfolio balance). Both focus and agility have (in extant literature) a directly related and positively tested effect on NPPM success. Focus is defined as ‘the firm focuses development efforts on those projects that achieve their long-term goals’; and agility is defined as ‘the firm is agile in how they make and implement NPD portfolio decisions.’ Portfolio mindset is not considered here since this found determinant has a moderating effect on NPPM success and falls within the moderator cluster variable ‘organization mindset’ which will be discussed in that part of this paper.
Thus, the cluster portfolio decision-making refers to all the within-cluster variable determinants that are related to the decision-making process within portfolios and all have a positive direct effect on NPPM success.
Portfolio Methods / Approach
14 positive correlation, which is stronger than with traditional methods (Luiz, de Souza, Luiz, Jugend, Salgado & da Silva, 2019).
In Figure 3 below, the final path model is displayed. Next, the moderating clusters, the found determinants within, as well as the relationships, are discussed.
Figure 3: Final Path Model (The solid lines state in the literature discussed relations; the dotted lines are suggestions for future research.)
Moderating clusters
A moderator is a variable that alters the direction or strength of the relation between a predictor and an outcome (Baron & Kenny, 1986; Holmbeck, 1997; James & Brett, 1984). Thus, a moderator effect is nothing more than an interaction whereby the effect of one variable depends on the level of another. Whereas moderators address “when” or “for whom” a predictor is more strongly related to an outcome, mediators establish “how” or “why” one variable predicts or causes an outcome variable. More specifically, a mediator is defined as a variable that explains the relationship between a predictor and an outcome (Baron & Kenny, 1986; Holmbeck, 1997; James & Brett, 1984). In other words, a mediator is a mechanism through which a predictor influences an outcome variable (Baron & Kenny, 1986).
Moderating cluster: Organization Mindset
15 Harmancioglu, 2009). The latter positive effect is explained by the expectation that the higher the analytic cognitive style, the more detailed evaluation of criteria will be integrated into the balance dimension (McNally et al., 2009). This cluster is also about knowledge sharing; that is knowledge sharing within the project, knowledge sharing among projects, and knowledge sharing within the organization. What comes here into play is ambiguity tolerance which represents a person's capacity to accept the absence of information about the range and probabilities of possible outcomes (Sherman, 1974), and therefore should be taken into consideration when sharing knowledge. These last two determinants are positively related to NPPM success but are however both not tested. Considering the stated above, the organization’s mindset does have a direct relationship with NPPM success. On top of that, this study also suggests that the organization mindset will have a moderating effect on the relationship between the portfolio information cluster and the portfolio decision-making cluster, as well as the relationship between the Portfolio Information and NPPM success. This can be explained by looking at the mindset of the people within organizations concerning the management of the portfolio; there are indications that this mindset affects the decision to be made in the portfolio. An organization with a positive mindset, so a high degree of analytic cognitive style, portfolio mindset, tolerance for ambiguity, and open knowledge sharing will be better in processing information which results in better decision making and a higher degree of portfolio success.
Moderating cluster: Early Phase Management
The second cluster of moderators is named Early Phase Management. This cluster entails three in literature found determinants that all have an indirect effect on NPPM success.
The reason why these determinants are clustered together is that they all can be gathered in the early, initial stages of the portfolio management process. Take for instance the determinants portfolio management formalization and integration project portfolio risk management (PPRM). Formalization is defined here as the degree to which pre-established processes, procedures, work rules, and policies are clearly specified and followed (Jang & Lee, 1998), whereas a better integration signifies the ability to combine new knowledge into the new existing capabilities, or, in other words, contributes, collects, and combines individual inputs and also builds a shared understanding creating a common ground and new perceptual schema (Weick & Roberts, 1993). Now both determinants do not only have a direct positive effect on portfolio management success (Kock & Gemunden, 2016; Kock et al., 2014; Teller et al., 2012); (William & Rutta, 2017), but they can also improve project portfolio success by increasing relatively the PPM quality (decision making cluster variable), and the PPRM quality (portfolio information cluster variable).
16 The solid arrows in the final path diagram of Figure 3 indicate (the above substantiated) links of this moderating cluster on portfolio information as well as portfolio decision making. Furthermore, it is expected that early phase management moderates the relationship of portfolio information on decision making, the relationship of portfolio information on NPPM success, as well as the relationship of portfolio decision making on NPPM success. Nevertheless, these relationships have not been tested in literature yet and therefore provides scope for future research.
Moderating cluster: Portfolio Stakeholders
The third cluster consisting of moderating variables influencing NPPM success comprises (as the name already indicates) determinants dealing with Portfolio Stakeholders.
Stakeholder whole portfolio means that not stakeholders of single projects, but stakeholders of the portfolio as a whole affect the success of a portfolio. These stakeholders are either directly involved in the PPM process, can influence the success of the portfolio, or are affected by the portfolio (Beringer, Jonas & Kock, 2013). The stakeholders of the portfolio as a whole may affect the success of a portfolio or may be affected by line managers (stakeholders who are below senior management but not necessarily above and increasingly alongside), project managers (can be classed with middle management and have a positive influence on strategic fit and average project success), and increased engagement in the PPM process (which positively affects the success of their projects) (Beringer et al., 2013). Increased stakeholder engagement may positively contribute to a portfolio’s success only if the higher level of engagement is also invested in the appropriate process phase (Beringer, Jonas & Gemünden, 2012). Considering the above, determinants that can be distinguished here are stakeholder behavior and stakeholder management. A determinant that also takes part in this stakeholder process is top management involvement, which refers to a group of top managers who participate in portfolio decision activities (Felekoglu & Moultrie, 2014). According to Yang & Xu (2016), a well‐designed and well‐implemented portfolio management process can stimulate top managers' involvement in new product portfolio management so that sufficient resources can be assigned and portfolio management performance is enhanced (positive effect). In addition, top managers should select and evaluate projects based on their profitability to maximize the value of an R&D portfolio and gain portfolio success (Yang & Xu, 2016). This study suggests that top managers could affect the decisions being made, by giving their opinion and doing the above. Therefore, this within-cluster determinant is one example of why in future research there should be looked at the connection to the relationship of portfolio decision making on NPPM success (as displayed in the final path model of Figure 3).
17 Moderating cluster: Management Approach
The fourth moderating cluster consists of a concatenation of management approaches and this cluster entails how organizations deal with their portfolio management processes.
The dotted (and thus not yet substantiated) arrow (see Figure 3) on the portfolio methods/approach cluster on NPPM success works in two ways. On the one hand, a higher degree of certain management approaches will lead to more NPPM success. For example, a higher extent of the within-cluster determinant task execution indicates a maturity of project portfolio management that leads to higher process performance, portfolio success, and portfolio- related corporate success (Jonas, 2010). Task execution is defined here as the activity level to which project portfolio management is implemented and utilized (Jonas, 2010). Also, if the number of projects people are (parallel) working on does not exceed a given amount (which is situational dependent) then this determinant can be advantageous for success (McDonough & Spital, 2003).
On the other hand, the other determinants negatively affect portfolio success. Switching team leaders and members, stretching financial resources, as well as longer portfolio backlogs negatively affect portfolio success. Considering the latter, organizations that more successfully met their portfolio objectives had significantly shorter portfolio backlogs than did organizations that were less successful in meeting their objectives. The authors calculated portfolio backlogs as the number of projects in the portfolio 12 months before, divided by the number of projects commercialized, plus the number terminated over the prior year. Other suggested reasons for these harmful methods on portfolio success can be found in the overload of the portfolio. Taking too many projects in the portfolio at once which will lead to insufficient attention, switching team leaders and members will result in the loss of both tacit project-specific knowledge and unique dynamics, new leaders/members may not accept responsibility for recovering from prior schedule slippages and stretching people and financial resources can result in shortages of vital equipment on a portfolio project or an inability to construct as many prototypes as are necessary to run tests which, in turn, can lead to project delays, and therefore inadequate attention (McDonough & Spital, 2003). Furthermore, the determinant ‘number of project people are parallel working on’ works also the other way around. When there are too many people working on parallel projects this will be detrimental for portfolio success, again due to overload and insufficient attention (McDonough & Spital, 2003).
Apart from the direct effects of the determinants on portfolio success, it is also expected that this cluster will have a moderating effect on the relationship between portfolio methods/approach and NPPM success. Possible sense-making for this could be that by applying the positive determinants (such as a high extent of task execution and the right number of projects) and at the same time avoiding the negative determinants of this cluster, the portfolio method is strengthened and will be more successful.
4. Discussion
18 4.1 Main findings and implications
The research question (RQ) of this paper was: ‘what is NPPM success and how can it be measured?’ This paper aims to contribute to the portfolio/innovation management literature, by conducting a systematic analysis of how the determinants found influence NPPM success. This has resulted in both a (in the literature found) generally accepted way of measuring NPPM success as well as an embracing definition. Additionally, a final path model (Figure 3) was generated for demonstrating which determinants influence NPPM success.
Firstly, in the results section, an overview of the measurements and definitions of NPPM success in extant literature was sketched. Altogether, the following measurements appeared to be essential in literature for measuring NPPM success: 1) Value maximization. 1a) Average single project success. 1b) Synergies. 2) Balance; with in particular 2a) Having the right number of projects. 2b) Having the right time to market (no gridlock). 3) Strategic fit 3b) Future preparedness.
These terms are measured as follows. The first measurement of value maximization is measured through financial returns such as long-term profitability or return on investment (Cooper et al, 1997). This measurement can be split into the average single project success of the portfolio, which regards the fulfillment of time, budget, quality, and customer satisfaction objectives; and synergies, which covers the interdependencies between projects. The second found measurement, balance, is measured by evaluating projects based on the extent to which the mix of NPD projects is proportional across multiple considerations (Cooper et al., 1997). In other words, a balanced portfolio has harmony concerning specific parameters (Kester et al., 2011), such as high-risk versus low-risk or long-term versus short-term projects (Cooper et al., 1997). The literature has shown that this measurement can be divided into three important measurements. Having the right number of projects is measured by balancing the available resources and resources needed for ongoing projects (Ghasemi, Sari, Yousefi, Falsafi, & Tamošaitiene, 2018). Having the right time to market, which is defined as the time between idea generation and bringing a product to the market, ensures avoiding pipeline gridlock, which means undertaking projects on time and in a time-efficient manner (Cooper et al., 1999) The third measurement of strategic fit assesses portfolio projects in terms of the extent to which they reflect the firm’s strategy (Cooper et al, 1997; Teller & Kock, 2013). Beringer et al. (2013) measure the strategic fit of a portfolio as the degree to which the objectives and demands of a portfolio's projects are consistent with the objectives and demands of the overall organizational strategy. Future preparedness, which is the organizations' preparedness for the future in terms of technological assets and competencies (Kopmann, Kock & Killen, 2017), valuates the long-term benefits offered by a project portfolio (or in other words the creation of new markets and development of new technologies and capabilities) and by that is a measure for the quality of the strategy (Voss & Kock, 2013).
It was suggested that a real definition of NPPM success in the extant literature is scarce. However, this paper found several dimensions of the definition of NPPM which turned out to be useful. These were: 1) Strategic alignment. 2) Maximizing value; which is further divided into 2a) Average project success and 2b) Synergies. 3) Balance; which includes 3a) Having the right numbers of project 3b) Having the right time to the market.
19 Secondly, by conducting a descriptive analysis, determinants influencing NPPM success were clustered. The found three main clusters, form the basis of the final path diagram (Figure 3). Their significant importance is due to their direct relationships on NPPM success. The first main cluster, Portfolio Information, entails all the information of the project including the risks. It was founded that this cluster can have a positive effect on the decision-making cluster, which is further elaborated on in section 4.3 (future research avenues). The second main cluster, Portfolio Decision Making, balances a multitude of conflicting goals of an organization, whereas not only project prioritization, selection, and project termination decisions were taken into consideration, but also delaying projects with reduced resources. This has resulted in all within-cluster determinants found having a direct positive relationship with NPPM success. The third main cluster of Portfolio Methods/Approach showed that the portfolio method used can have various effects on portfolio success, with in particular employing CCPM concepts & tools being more effective for gaining success than traditional PPM practices. All in all, it can be stated that businesses that are aiming for portfolio success should first consider these three main clusters when organizing their portfolio process. This should be done by not only considering the effects of these main clusters on portfolio success but also by looking at the effects of the within-cluster determinants of these main clusters. Examples of this are considering the quality of information when making decisions or involving the opinion of top managers in order to enhance portfolio success.
Furthermore, the four found moderating clusters were integrated into this research. These moderators are more distant from NPPM success compared with the main clusters, however, it is expected that they have an indirect effect on portfolio success. These effects will be discussed in depth in section 4.3 future research avenues.On top of that, the clusters organization mindset, portfolio stakeholders, and management approach proved to have determinants with direct influences on portfolio success.
The main contribution this study makes is presenting answers on the research question by providing overarching terms of measurements and definitions of NPPM success, as well as providing a comprehensive multidimensional framework of clusters on which to build measures of NPPM success determinants and outcomes. Several managerial implications can be conducted from this paper, in which managers can benefit from this empirical evidence that forms the essence of this study. At first, managers should consider the moderating roles of the four found moderating clusters when striving for NPPM success. Examples of this are taking into account their organization mindset when appraising portfolio information and making decisions, or reckon with all the stakeholders in the portfolio decision-making process.
20 4.2 Limitations
Although this systematic review was conducted in a disciplined manner, potential limitations must be acknowledged. First, the search process is limited to English-written articles embedded in portfolio management journals through consulting the Google Scholar and Business Source Premier databases. Thus, this review does not involve portfolio management literature that goes beyond this boundary or published in a different language than English. On top of that, given the rising interest in portfolio management research, future reviews could also include literature from other fields of study, such as marketing or supply chain management.
Furthermore, a significant number of extant literature takes the articles of Cooper et al. (1999, 2000, 2001, 2002) as a basis. Although these papers can undoubtedly be grouped under the renowned literature, there is possibly a bias here. When authors over-rely on the work of Cooper et al., other research areas and ideas can be treated underexposed, since every author holds opinions that affect his or her discussion of an issue. An example of such an underexposed area is the possible effect of portfolio information on portfolio decision making.
Finally, one difficulty of this study was finding relevant literature. Because of differences in the use of terminology collecting and consolidating relevant literature turned out to be a challenge. It appeared that terms concerning the portfolio management field are used interchangeably. For instance, the search terms ‘New Product Portfolio Management’ and ‘Portfolio success’ provided many useful results, whereas the search terms ‘product portfolio performance’ and ‘portfolio performance measures’ ultimately yielded considerably less (useful) results. Future research should, therefore, be cautious with using and integrating these concepts and terms in portfolio management literature.
4.3 Future research avenues
Seven future research directions are introduced resulted from the moderators of this research. One more future research direction is added; the relationship of the Portfolio Information cluster on the Portfolio Decision making cluster. These directions resulted from the descriptive analysis and are displayed in the final path model of Figure 3 through the dotted lines. The relationships to be researched in the future are discussed below.
The found moderating cluster organization mindset offers room for research on the relationships of portfolio information with portfolio decision making and portfolio information with NPPM success. This can be interpreted as follows; all within-cluster determinants found deal with information that influences decision making and portfolio success. This generally means that a positive portfolio mindset will enhance portfolio success and this is understated by the propagation of an analytic style, having a portfolio mindset, tolerance for ambiguity, and open knowledge sharing. It is expected that this cluster, apart from the direct connection to portfolio success, also impacts how organizations deal with portfolio information and how this information affects the decision-making. However, these relationships have not yet been studied in the current literature.
21 made and how these decisions in the portfolio management will have an impact on the NPPM itself and therefore its success. The expectation is that in a higher complex environment it is for the management more difficult to keep control, consequently harder to reach NPPM success, and therefore moderating the just mentioned relationship. Nevertheless, these relationships have not been tested in literature yet and therefore provides scope for future research.
Moreover, the overall moderating effect of portfolio stakeholders on the relationship between portfolio decision making and NPPM success has not been tested or mentioned in the literature yet. The following assumption can be made here: ‘if all stakeholders act to their best capabilities, then there is a positive effect on the relationship of portfolio decision making on NPPM success.’ This can be explained by looking at the (positive) within-cluster determinants. Stakeholder management and behavior are in the literature described as key success determinants, whereas literature suggested that top management involvement contributes 8.2% to portfolio success. The determinant ‘stakeholder whole portfolio’ was not tested, however, the research of Beringer et al. (2013) indicates that different kinds of managers have various positive effects on portfolio success. Considering this, it can be assumed that top managers may have different expectations regarding the success of NPPM compared with the stakeholders of the whole portfolio. Therefore, this resulting moderating effect is a suggestion for future research.
Also, the effect of the moderating cluster management approach on the relationship between the cluster Portfolio Methods / Approach and the dependent variable NPPM success has still to be researched. Possible sense-making for this could be that by applying the positive determinants (such as a high extent of task execution and the right number of projects people are parallel working on in the portfolio) and at the same time avoiding the negative determinants of this cluster (such as switching team members & leaders, stretching people & financial resources, too long portfolio backlogs and too much projects people are working on in the portfolio) the portfolio method is strengthened and will be more successful.
Finally, a positive relationship between portfolio information on portfolio decision making is expected. The in this paper stated within-cluster determinants of portfolio information, such as information- or PPRM quality, have a positive direct effect on NPPM success. Above on that, for making decisions, information is needed. It is expected that the higher the quality of the information or the quality of project portfolio risk management, the higher the details and risk insights, so the easier the process of decision-making. Thus, this study expects that the quality of the information and the successful implementation of the information cluster affects the decision making and its results. This relationship has not yet been researched though and therefore offers room for future research.
5. Conclusion
In this paper, the objective was to synthesize different research streams that focus on NPPM success to ‘sketch’ an overview of discussed research and provide propositions for future research.
22 within have a direct effect on NPPM success and are seen as the most important outcomes of this study. Finally, the four found moderating clusters also play a significant role. They do not only (partly) directly affect the relationships of the found main cluster variables on NPPM success, but also have various moderating effects on them.
23 References
1. Alexandrova, M. (2018). A principal component analysis of project portfolio management practices. Ekonomicko-manazerske spektrum, 12(2), 96-105.
2. Archer, N., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. International Journal of Project Management, 17, 207–216.
3. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.
4. Beringer, C., Jonas, D., & Gemünden, H. G. (2012). Establishing project portfolio management: An exploratory analysis of the influence of internal stakeholders’ interactions. Project Management Journal, 43(6), 16-32.
5. Beringer, C., Jonas, D., & Kock, A. (2013). Behavior of internal stakeholders in project portfolio management and its impact on success. International Journal of Project Management, 31(6), 830-846. 6. Blichfeldt, B.S & Eskerod, P. (2008). Project portfolio management—there's more to it than what management enacts. International Journal of Project Management, 26(4), 357–365.
7. Cooper, R., Edgett, S., Kleinschmidt, E., (1997). Portfolio management in new product development: lessons from the leaders I. Research Technology Management, 40(5), 16–28.
8. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (1999). New product portfolio management: practices and performance. Journal of Product Innovation Management, 16(4), 333-351.
9. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2000). New problems, new solutions: making portfolio management more effective. Research-Technology Management, 43(2), 18-33.
10. Cooper, R. G., S. Edgett, & Kleinschmidt, E. J. (2001) Portfolio management for new product development: Results of an industry practices study. R&D Management, 31, 361–80.
11. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2002). Portfolio management: fundamental to new product success. The PDMA ToolBook 1 for New Product Development, 9, 331-364.
12. Crossan, M. & Apaydin, M. (2010). A multi‐dimensional framework of organizational innovation: A systematic review of the literature. Journal of management studies, 47(6), 1154-1191.
13. Daft, R.L., (1992). Organization Theory and Design, 4th ed. West Publishing, St. Paul, MN.
14. Dickinson, M.W., Thornton, A.C., Graves, S. (2001). Technology portfolio management: optimizing interdependent projects over multiple time periods. IEEE Transactions on Engineering Management, 48(4), 518–527.
15. Dikert, K., Paasivaara, M., & Lassenius, C. (2016). Challenges and success factors for large-scale agile transformations: A systematic literature review. Journal of Systems and Software, 119, 87-108. 16. Felekoglu, B., & Moultrie, J. (2014). Top management involvement in new product development: a review and synthesis. Journal of Product Innovation Management, 31(1), 159–175.
24 18. Griffin, A. (1997). PDMA research on new product development practices: Updating trends and benchmarking best practices. Journal of Product Innovation Management: An International Publication of The Product Development & Management Association, 14(6), 429-458.
19. Goldratt, E.M. (1997), Critical Chain, 1st ed, North River Press, Great Barrington.
20. Hagedoorn, J., & Cloodt, M. (2003). Measuring innovative performance: Is there an advantage in using multiple indicators? Research Policy, 32(8), 1365–1379.
21. Hand, D. J., Mannila, H., & Smyth, P. (2001). Principles of data mining (adaptive computation and machine learning). MIT Press.
22. Holmbeck, G. N. (1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: Examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65, 599–610.
23. James, L. R., & Brett, J. M. (1984). Mediators, moderators, and tests for mediation. Journal of Applied Psychology, 69, 307–321.
24. Jang, Y. & Lee, J., (1998). Factors influencing the success of management consulting projects. International Journal of Project Management, 16(2), 67–72.
25. Jonas, D. (2010). Empowering project portfolio managers: How management involvement impacts project portfolio management performance. International Journal of Project Management, 28(8), 818-831.
26. Kester, L., Hultink, E. J., & Griffin, A. (2014). An empirical investigation of the antecedents and outcomes of NPD portfolio success. Journal of Product Innovation Management, 31(6), 1199-1213. 27. Kock, A., Heising, W., & Gemünden, H. G. (2015). How ideation portfolio management influences front‐end success. Journal of Product Innovation Management, 32(4), 539-555.
28. Kohli, R., & Melville, N. P. (2019). Digital innovation: A review and synthesis. Information Systems Journal, 29(1), 200-223.
29. Kopmann, J., Kock, A., Killen, C. P., & Gemünden, H. G. (2017). The role of project portfolio management in fostering both deliberate and emergent strategy. International Journal of Project Management, 35(4), 557-570.
30. Kraiczy, N.D., Hack, A., Kellermanns, F.W. (2014). Empowering project portfolio managers: How management involvement impacts project portfolio management performance. Journal of Business Research, 67(6), 1065-1073.
31. Luiz, O. R., de Souza, F. B., Luiz, J. V. R., Jugend, D., Salgado, M. H., & da Silva, S. L. (2019). Impact of critical chain project management and product portfolio management on new product development performance. Journal of Business & Industrial Marketing, 34(8), 1692-1705.
32. Matheson, J. E. & Menke, M. M. (1994). Using decision quality principles to balance your R&D portfolio. Research Technology Management, 37, 38-43.
33. Marris, P. (2011). La chaîne critique pour réduire le ‘time to market’ et accroître la productivité. STP Pharma Pratiques, 21( 5), 1-12.
25 35. McNally, R. C., Durmusoglu, S. S., Calantone, R. J., & Harmancioglu, N. (2009). Exploring new product portfolio management decisions: The role of managers' dispositional traits. Industrial Marketing Management, 38(1), 127-143.
36. McNally, R. C., Durmuşoğlu, S. S., & Calantone, R. J. (2013). New product portfolio management decisions: antecedents and consequences. Journal of Product Innovation Management, 30(2), 245-261.
37. McDonough III, E. F., & Spital, F. C. (2003). Managing project portfolios. Research-Technology Management, 46(3), 40-46.
38. Meier, M., (2011). Knowledge management in strategic alliances: a review of empirical evidence. International Journal of Management Reviews, 13(1), 1-23.
39. Meskendahl, S. (2010). The influence of business strategy on project portfolio management and its success—A conceptual framework. International Journal of Project Management, 28(8), 807-817. 40. Miller, D., & Friesen, P.H. (1982). Innovation in conservative and entrepreneurial firms: Two models of strategic momentum. Strategic Management Journal, 3(1), 1–25.
41. Müller, R., Martinsuo, M., & Blomquist, T. (2008). Project portfolio control and portfolio management performance in different contexts. Project management journal, 39(3), 28-42.
42. Munns, A. K., & Bjeirmi, B. F. (1996). The role of project management in achieving project success. International journal of project management, 14(2), 81-87.
43. Nidumolu, S.R., (1996). Standardization, requirements uncertainty and software project performance. Information Management, 31 (3), 135–150.
44. Nobeoka, K., Cusumano, M.A. (1994). Multi-Project Management: Inter-Project Interdependency and Organizational Coordination in New Product Development. Massachusetts Institute of Technology (MIT), Sloan School of Management, 1-25.
45. Oostuizen, C., Grobbelaar, S. S., & Bam, W. G. (2018). Project portfolio management best practice and implementation: A South African perspective. International Journal of Innovation and Technology Management, 15(04), 1850036.
46. Sherman, R. (1974). The psychological difference between ambiguity and risk. The Quarterly Journal of Economics, 88, 166−169.
47. Teller, J., Unger, B. N., Kock, A., & Gemünden, H. G. (2012). Formalization of project portfolio management: The moderating role of project portfolio complexity. International journal of project management, 30(5), 596-607.
48. Teller, J. (2013). Portfolio risk management and its contribution to project portfolio success: An investigation of organization, process, and culture. Project Management Journal, 44(2), 36-51. 49. Teller, J., Kock, A. (2013). An empirical investigation on how portfolio risk management influences project portfolio success. International journal of product management, 31(6), 817-829.
50. Thompson, J.D. (1967). Organizations in Action: Social Science Bases of Administrative Theory. McGraw-Hill, New York, NY.
26 52. Turner, R. (2016). Gower handbook of project management. Routledge.
53. Unger, B. N., Kock, A., Gemünden, H. G., & Jonas, D. (2012). Enforcing strategic fit of project portfolios by project termination: An empirical study on senior management involvement. International Journal of Project Management, 30(6), 675-685.
54. van Bruggen, G. H., Smidts, A., & Wierenga, B. (1998). Improving decision making by means of a marketing decision support system. Management Science, 44(5), 645−658.
55. Voss, M., & Kock, A. (2013). Impact of relationship value on project portfolio success—Investigating the moderating effects of portfolio characteristics and external turbulence. International Journal of Project Management, 31(6), 847-861.
56. Wassmer, U., (2010). Alliance portfolios: A review and research agenda. Journal of Management, 36(1), 141-171.
57. Weick, K. E., & Roberts, K. H. (1993). Collective mind in organizations: Heedful interrelating on flight decks. Administrative Science Quarterly, 38(3), 357- 381.
27 Appendix A
Table 2. Overview of NPPM measurements in the articles
Author Year Measurements
Cooper, R.G., Edgett, S.J. & Kleinschmidt, E.J.
1997 Managers use three broad dimensions to evaluate the firm’s portfolio of new product projects:
1. Value maximization, measured through financial returns such as long-term profitability or return on investment.
2. Balance, evaluate projects based on the extent to which they ensure that the mix of NPD projects is proportional across multiple concerns (project completion date, technical risk, return on investment, etc).
3. Strategic fit, assess projects in terms of the extent to which they reflect the firm’s strategy.
Cooper, R.G., Edgett,
S.J. & Kleinschmidt, E.J.
1999 Portfolio performance was measured on six metrics:
1. Having the right number of projects in the portfolio for the resources available.
2. Voiding pipeline gridlock in the portfolio—undertaking projects on time and in a time-efficient manner.
3. Having a portfolio of high-value projects
4. Profitable, high- return projects with solid commercial prospects, 5. Having a balanced portfolio (long vs short, high vs low risk) 6. Having a portfolio of projects that are aligned with the business’s strategy
Yang, Y. & Xu, D, L. 2017 1. Strategic fit
2. Average project success 3. Synergy
Tiwari, P. & Panicker, S.
(Not shown)
1. Long term strategic context of portfolio strategic fit (The amount of the intentions and needs related to portfolio’s projects are aligned with the entire organization).
2. Short term operational context of average project success (The three restrictions to deliver project as per specifications within budget and on time)
Kopmann, J. 2013 Project portfolio success comprising four sub-constructs. 1. Average project success
28 Kopmann, J., Kock,
A., Killen, C. P. & Gemünden, H. G.
2017
Project portfolio success as a second-order construct with five sub-dimensions:
1. Strategy implementation (successful project portfolio management)
2. Future preparedness (the organizations preparedness for the future in terms of technological assets and competences)
3. Portfolio balance (the equilibrium of risks, long- and short-term opportunities and the steady utilization of resources within the project portfolio’s execution)
4. Average project outcome (the respective indicators for average project success should not refer to the adherence to cost, time and scope but rather to quality of the project’s outcome and the satisfaction of the project customer)
5. Synergy exploitation (the added value that emerges from dedicated portfolio management in addition to the single projects‟ contribution through the capitalization of interdependencies and the avoidance of redundancies)
Teller, J. & Kock, A. 2013
Project portfolio success comprising six sub-constructs:
1. Average project success (Budget, schedule, quality adherence, customer satisfaction of all projects in the portfolio)
2. Average product success (commercial effects such as goal-achievement regarding market success, Return-on-Investment, break-even, or profit of all projects in the portfolio)
3. Strategic fit (the extent to which all projects reflect the corporate business strategy)
4. Portfolio balance (the balance of the project port- folio concerning risks and expected benefits)
5. Preparing for the future (deals with the long-term aspects and considers the ability to seize opportunities that arise after the projects have been brought to an end)
6. Economic success (the short-term economic effects at the corporate level, including overall market success and commercial success of the organization or business unit)
Kock, A., Heising, W. & Gemünden, H,G.
2015
A second-order construct that consists of five dimensions: 1. Business success (the impact of the portfolio on the firm’s business performance)
2. Average economic success of products and project results (The impact of the portfolio on the individual product level)
29 4. Portfolio balance (the strategic perspective of balancing existing and new technologies and application areas—in addition to risk— within the project portfolio)
5. Preparing for the future (the benefits and long-term
opportunities for the organization that are rooted in the project portfolio and even before that in the ideation phase)
Ghasemi, F., Sari, M,H,M., Yousefi, V., Falsafi, R. &
Tamošaitiene, J.
2018
The main portfolio management objectives are: 1. Portfolio value maximization;
2. Strategic alignment; 3. Portfolio balance; and 4. Right number of projects
Oosthuizen, C., Grobbelaar, S.S. & Bam, W.G.
2017
Maximizing value can be divided into two separate dimensions: 1. Average single project success (time, quality, budget, and customer satisfaction. And 2. The use of synergies between projects.
The top six success criteria found in the literature are the following in ranking order:
1. Projects linked to strategy 2. Portfolio balance.
3. Average single project success. 4. Use of synergies.
5. Future preparedness. 6. Maximizing value.
But how the success should be measured depends on the choice, project, and interpretation of the researcher or practitioner.
Beringer, C., Jonas, D. & Kock, A.
2013
1. Operative short-term perspective: The cumulative success of all projects in a portfolio.
Therefore, average project success is defined along the three familiar dimensions of the project management triangle: cost, schedule and quality.
2. Strategic long-term perspective Strategic fit of a portfolio,
In the context of project portfolio management, we define strategic fit as the degree to which the objectives and demands of a
portfolio's projects are consistent with the objectives and demands of the overall organizational strategy
Meskendahl, S. 2010
Divided value maximization into two separate dimensions:
30 fulfilment of time, budget, quality, and customer satisfaction objectives
2. The use of synergies between projects within the portfolio, which covers the interdependences between projects.
3. The portfolio's overall fit with the firm's business strategy and 4. The portfolio's balance are the third and fourth dimensions on project portfolio success as suggested by Cooper et al (2002).
Voss, M. & Kock, A. 2013
Defined project portfolio success as a multi-dimensional second-order construct with six sub-constructs:
1. Overall business success
2. Economic success of products and project results 3. Strategic fit
4. Use of synergies 5. Portfolio balance 6. Future preparedness
Jonas, D. 2010
The success of a project portfolio management system is multidimensional consisting of the three dimensions of
1. Process effectiveness (Information quality, allocation quality, cooperation quality)
2. Portfolio success (Average project success, use of synergies, strategic fit, portfolio balance)
3. Portfolio-related corporate success, (business success, preparing for the future) which will be affected by changes in the PPM system consecutively.
Kraiczy, N.D., Hack, H. & Kellermans, F.W.
2014
New product portfolio performance:
- Patent counts or citations (Hagedoorn & Cloodt, 2003) - Degrees of product innovativeness (Miller & Friesen, 1982; Prajogo & Ahmed, 2006).
31 Kester, L., Griffin, A.,
Hultink, E. J. & Lauche, K.
2011
32 Appendix B
