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The Portfolio Management and Influence in Projects of Decisions
Abstract
One of the main objectives of portfolio management is related to the strategic alignment of the projects with the organizational strategy, through decision making. From this premise the present article aims to demonstrate how the portfolio management influences the decision making process in the projects of a financial organization. To achieve this goal, the project portfolio management processes and their relationships with decision making were studied. The methodological option chosen was a unique case study. The collected data were treated and analysed using the technique of qualitative data analysis through five phases of analysis and their interpretations. The results confirmed that use of the project identification process in portfolio management influence decision-making and as consequence, adding value to the business. It was also possible to demonstrate moderately that the use of criteria for project selection influences the consequences of decision making, to assist in the strategic management of the organization.
The new product process by which firms drive new product projects from inception through to commercialization, and the methods, practices and tactics embedded within that process, are the focus of this final of three articles reporting the results of the recent American Productivity and Quality Center study on performance and best practices in new product development. Many of the decisive activities that were identified turn out to be poorly executed, while a handful of tasks emerge as pivotal to NPD performance. Most firms now employ a systematic, formal, new product process, but the nature of the process and the way it is implemented are the true keys to success. For instance, delivering a differentiated, superior product is one practice that strongly separates the Best and Worst Performers. Market information, up-front homework, stable product definition, and voice-of-customer research are found to be relatively weak practices in businesses' new product efforts, but all strongly discriminate between the Best and Worst Performers.
The need to align organizations' objectives and strategies with the implementation of portfolios, programs, and projects is not a trivial task. Frequently, IT projects are based on revolutionary technology although not in full compliance with the business needs. Business model (BM) can be seen as an essential conceptual tool to capture, share, and create a common vision of an organization model. The present study aimed to identify the level of the alignment maturity of information technology projects with the organizations' business models in Brazil. For this purpose, an exploratory descriptive research was carried out using a survey questionnaire that was answered by 327 professionals involved with IT projects from February to April 2012. Descriptive statistics as well as univariate statistical analysis, such as frequency distribution percentage, and multivariate analysis, specifically the exploratory technique Categorical Principal Components Analysis (CATPCA) with optimal scaling, were applied. Based on the main goal of the present study, the score of 3.42 was obtained, and it indicates a maturity level '3-stablished/focused', which means the beginning of strategic use of IT in business. The analysis of the results also demonstrated that the formalization of IT project management in organizations has grown; the functional organizational structure is still the most commonly used although the projectized structure has gained popularity, and it is at the second position. The project management office (PMO) leads as the area that selects, prioritizes, and monitors projects. Based on hypothesis tests, it was verified that PMO and the projectized organizational structure are positive and significant aspects in the alignment of IT projects with business models.
Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible options to enhance the decision-making outcomes in organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.
A study of portfolio management practices in industry reveals three goals: maximizing the value of the portfolio, achieving the right balance and mix of projects, and linking the portfolio to the business s strategy. This first of two articles provides examples of portfolio methods used to achieve the first two goals. Maximizing the portfolio's value is achieved by means of various financial models, including the Expected Commercial Value method and the Productivity index, which are outlined and critiqued. Scoring models are also used to maximize the value of the portfolio. Achieving a balanced portfolio is quite a different issue, involving the use of bubble diagrams and other visual models.
Some of the findings of an extensive investigation into how businesses manage their research and development and new product portfolios are presented, including how satisfied management is with their portfolio management practices, and the portfolio results achieved in these businesses. An exploratory study was undertaken to gain insights into industry's use of portfolio models. Leading firms were identified and in-depth interviews were conducted with management to better define what portfolio management is, to identify the types of portfolio management in use, to understand the principal goals that businesses are trying to achieve via portfolio management, and to determine how managers perceived these models and methods.
Part I. Tackles the processes involved in the discovery stage of managing technological innovations. Details of how an idea capture and handling scheme works; Significance of customers to the management of technological innovations; Importance of developing alternative future scenarios to industrial research.
This first of three articles reports the results of the most recent American Productivity and Quality Center study on performance and best practices in new product development. Performance results achieved on a number of NPD metrics are reported first, followed by a set of Best Performing businesses, wha t these businesses ha ve in common and—most important—what differentiates them from the rest. This first article focuses on the " people side" of NPD—on how project teams are organized and on other winning characteristics of teams. The climate and culture for innovation within the business proves to be one of the strongest drivers of NPD performance, and the specifics of what the Best Performers have done to achieve this positive climate are outlined. Finally the role of senior management in setting the stage for the business's NPD effort is examined.
Innovation is one of the most important issues in business research today. It has been studied in many independent research traditions. Our understanding and study of innovation can benefit from an integrative review of these research traditions. In so doing, we identify 16 topics relevant to marketing science, which we classify under five research fields:
Consumer response to innovation, including attempts to measure consumer innovativeness, models of new product growth, and recent ideas on network externalities; Organizations and innovation, which are increasingly important as product development becomes more complex and tools more effective but demanding;. Market entry strategies, which includes recent research on technology revolution, extensive marketing science research on strategies for entry, and issues of portfolio management; Prescriptive techniques for product development processes, which have been transformed through global pressures, increasingly accurate customer input, Web-based communication for dispersed and global product design, and new tools for dealing with complexity over time and across product lines; Defending against market entry and capturing the rewards of innovating, which includes extensive marketing science research on strategies of defense, managing through metrics, and rewards to entrants.
For each topic, we summarize key concepts and highlight research challenges. For prescriptive research topics, we also review current thinking and applications. For descriptive topics, we review key findings.
This paper reviews the strategic decision-making process literature with respect to the synoptic formalism/political incrementalism debate. Procedural rationality is chosen as a representative of the synoptic formalism perspective; and both intuitive synthesis and political behaviour are employed as representatives of the political-incrementalism perspective. In this paper, the author discusses the theoretical underpinnings of these three process dimensions, as well as the key research efforts gathered together under each perspective. In conducting this review, a number of areas have been identified which could profitably be examined further, and a number of implications for managers will be highlighted and discussed.
Portfolio management for product innovation – picking the right set of development projects – is critical to new product success. This article reports on the new product portfolio practices and performance of a large sample of firms in North America. Reasons why portfolio management is important are identified, followed by the relative popularity of the different portfolio techniques: financial methods are first, followed by business strategy methods, bubble diagrams and scoring models. Next, how the various portfolio methods fare in terms of six performance metrics is probed. Financial methods, although the most popular and rigorous, yield the worst results overall, while top performing firms rely more on non-financial approaches – strategic and scoring methods. The details of how some of these more popular methods are employed by firms to rate and rank development projects are also provided. Finally, managerial implications, including suggestions for making portfolio management more effective in industry, are outlined.
This study examined whether strategic decision-making processes arerelated to decision effectiveness, using a longitudinal field study design.We studied 52 decisions in 24 companies to determine if proceduralrationality and political behavior influence decision success, controllingfor the favorability of the environment and decision implementation.Our results indicate that decision-making processes are indeed relatedto decision success. Results are discussed in terms of the importanceof strategic choice in organizations.
The importance of new product development (NPD) for a company's growth and prosperity is emphasized and a number of methods have been suggested to help decision-making for NPD project portfolio management. In spite of their utilities, however, little attention was paid to develop a supporting system for portfolio management that can help quick but careful decision-makings under uncertainties. Therefore, this research proposes a decision-making framework that uses a fuzzy expert system in portfolio management for dealing with the uncertainty of the fuzzy front-end of product development. For the purpose of developing the framework, we adopted the three tools - strategic bucket for strategic resource allocation, scoring models for evaluating projects and portfolio matrixes for balancing projects - to find an optimal set of projects in the portfolio. In particular, this research established fuzzy inference-based models for evaluation criteria which are too ambiguous to be numerically described. Also, based on the evaluation results, the final selection of projects is made by an expert system, which can encompass the operational knowledge and company strategy in the rule-based system. The suggested framework was applied to the portfolio analysis in an electronics firm in Korea and verified its feasibility.
Effective management of single projects is no longer sufficient. In today's business market, proactive management of the whole project portfolio has become increasingly important for achieving long-term success and competitive advantage. At the front end of projects, opportunities are discovered, ideas are created, and the foundation for later project, portfolio, and, eventually, corporate success is laid. This paper contributes to the project management body of knowledge by combining the front end view on projects with the holistic view of managing project portfolio landscapes. It focuses on establishing a framework for conceptualization of the relationship between ideation and project portfolio management in product development environment by relating ideation portfolio management, front end success, and project portfolio success, and lays the groundwork for further empirical research. The overarching topic I address is the conceptualization of how ideation can facilitate and sustainably improve portfolio success in the product development environment in the long-term.
Business units in six Fortune 500 companies were studied to develop better understanding regarding drivers of product portfolio complexity and the means to manage them. Our research focuses on identifying important competencies for managing product portfolio complexity and on the development of appropriate theoretical explanations. We found three important competencies: product/technology portfolio strategy, organization and governance regarding complexity decisions, and product design and decision support systems. We explicate these competencies using a socio-technical systems theoretical perspective. Our findings provide the basis for a model describing the impact of complexity and complexity management on business unit profitability.
Portfolio management is the set of activities that allows a firm to select, develop, and commercialize a pipeline of new products aligned with the firm's strategy that will enable it to continue to grow profitably over the long term. To appropriately manage the firm's new product portfolio, decisions must be made about which projects to fund, to what levels, at what point in time. Previous research has investigated portfolio management decisions as individually discrete decisions. Significant streams of research have investigated both project selection and project termination decisions. This research project shows, however, that portfolio decision making may be better understood if it is considered as an integrated system of processes that considers these decisions simultaneously, along with other decisions such as those to continue a project with reduced funding. Using in-depth data from four diverse case studies, we use a grounded theory approach to develop a general model of how firms make new product portfolio decisions. According to the findings from these cases, effective portfolio decision-making processes produce a portfolio mindset, focus effort on the right projects, and allow agile decision making across the portfolio's set of projects. Effective portfolio decision making is the result of the interaction between three types of decision-making processes that managers use in making decisions: evidence-, power-, and opinion-based. Being able to use each of these types of processes to make decisions depends upon having the data inputs that they require. Three domain-based decision input-generating processes (i.e., cross-functional collaboration, practices of critical thinking, and practices of market immersion) are associated with making evidence-based portfolio decisions. In addition, organizational politics produces the inputs that are associated with power-based portfolio decision making, while managerial intuition is associated with opinion-based portfolio decision making. Firm cultural factors, including trust, collective ambition, and leadership style, are associated with how these evidence-, power- and opinion-based processes are combined into an overall portfolio decision making process, and whether the firm's processes are more rational and objectively made, or more politically and intuitively made. The article presents propositions for how the decision-making processes interact in their associations with decision-making effectiveness.
Companies frequently implement formalization to improve success. Previous research has found supporting evidence for the performance-enhancing effects of formalization in both single project management and project portfolio management. However, there is no research on how formalization at the project level interacts with formalization at the portfolio level, or on how this interaction may impact success. This study investigates the interaction of formalization at both levels and examines the moderating effect of project portfolio complexity on formalization. Using a sample of 134 firms, this study shows that single project management formalization and, likewise, portfolio management formalization are directly connected to portfolio success. Simultaneous formalization at these two levels delivers a complementary effect, resulting in an increase in success that is more than additive. A contingency analysis confirms that the proposed positive effects become more prominent if complexity is high. Complexity measured as project interdependency has a stronger moderating effect than complexity measured as portfolio size.
Highly regulated industries such as pharmaceuticals and agrochemicals face the challenge of maintaining a 0continuous stream of new products. This is difficult because of low probabilities of technical success, high development costs, uncertain market impact, a scarcity of good new product ideas, and limited human and capital resources available to develop them. The problem of evaluating and selecting which new products to develop and then of sequencing or of scheduling them is complicated further by the presence of dependencies between products both in the market place and in the development process itself.
Technology centered organisations must be able to identify promising new products or process improvements at an early stage so that the necessary resources can be allocated to those activities. It is essential to invest in targeted R&D projects as opposed to a wide range of ideas so that resources can be focused on successful outcomes. Typically, a number of options and tradeoffs are encountered; the selection of the most appropriate projects is the aim of R&D selection models. Although capital budgeting and financial portfolio management offer a similar style approach, the techniques used for the solution of those is different to that used for R&D project selection. The reasons for this are that project selection is complicated by many factors, such as uncertainty, interrelationships between projects, changes over time and success factors that are difficult to measure. Thus, a mathematical optimisation approach in isolation is not practical. Project selection models not only have to consider these problems but also that there are different types of R&D. The spectrum of R&D ranges from low budget exploratory research to large budget product development. This paper reviews the development of a project selection and evaluation tool that can be applied to a wide range of research, technology and investment decisions. Firstly, the background on project selection models is given. This is followed by the introduction of the model and its application to a sample group of projects. Finally, some conclusions are discussed as to the applicability of such models.
Globalization of markets and new business practices are prompting high-tech firms to reconsider their competitive strategy. The increasing complexity of technologies in addition to shorter product life cycles are also forcing firms to rely on R&D as a source of strategy. More importantly, firms are inclined to evaluate their technologies from a portfolio's perspective in which a set or a sub-set of R&D projects is evaluated together, in relation to each other. Portfolio techniques can help strategic managers in evaluating whether a portfolio of products is adequate from the perspective of long-term corporate growth and profitability. Obviously, when R&D projects are evaluated relative to one another, technical capability management of such projects must be carried out concurrently. In this paper, R&D Project Portfolio Matrix is used as a tool for analyzing a portfolio of R&D projects by linking competitive advantages of a firm to benefits these projects may provide to customers. Examples of batteries for electric vehicles (EV) and hybrid electric vehicles (HEV) are provided to illustrate how such a matrix is used, and some of the implications for innovation management of such projects.
Making R&D portfolio decision is difficult, because long lead times of R&D and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. The objective of this research is to develop a fuzzy R&D portfolio selection model to hedge against the R&D uncertainty. Fuzzy set theory is applied to model uncertain and flexible project information. Since traditional project valuation methods often underestimate the risky project, a fuzzy compound-options model is used to evaluate the value of each R&D project. The R&D portfolio selection problem is formulated as a fuzzy zero-one integer programming model that can handle both uncertain and flexible parameters to determine the optimal project portfolio. A new transformation method based on qualitative possibility theory is developed to convert the fuzzy portfolio selection model into a crisp mathematical model from the risk-averse perspective. The transformed model can be solved by an optimization technique. An example is used to illustrate the proposed approach. We conclude that the proposed approach can assist decision makers in selecting suitable R&D portfolios, while there is a lack of reliable project information.
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