Project Success: A Multidimensional Strategic Concept

No project is an island: linking projects to history and context

This article develops a model of a project as a payoff function that depends on the state of the world and the choice of a sequence of actions. A causal mapping, which may be incompletely known by the project team, represents the impact of possible actions on the states of the world. An underlying probability space represents available information about the state of the world. Interactions among actions and states of the world determine the complexity of the payoff function. Activities are endogenous, in that they are the result of a policy that maximizes the expected project payoff.A key concept is theadequacy of the available information about states of the world and action effects. We express uncertainty, ambiguity, and complexity in terms of information adequacy. We identify three fundamental project management strategies: instructionism, learning, and selectionism. We show that classic project management methods emphasize adequate information and instructionism, and demonstrate how modern methods fit into the three fundamental strategies. The appropriate strategy is contingent on the type of uncertainty present and the complexity of the project payoff function. Our model establishes a rigorous language that allows the project manager to judge the adequacy of the available project information at the outset, choose an appropriate combination of strategies, and set a supporting project infrastructure--that is, systems for planning, coordination and incentives, and monitoring.

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On Uncertainty, Ambiguity, and Complexity in Project Management

Not many authors have attempted to classify projects according to any specific scheme, and those who have tried rarely offered extensive empirical evidence. From a theoretical perspective, a traditional distinction between radical and incremental innovation has often been used in the literature of innovation, and has created the basis for many classical contingency studies. Similar concepts, however, did not become standard in the literature of projects, and it seems that theory development in project management is still in its early years. As a result, most project management literature still assumes that all projects are fundamentally similar and that "one size fits all." The purpose of this exploratory research is to show how different types of projects are managed in different ways, and to explore the domain of traditional contingency theory in the more modern world of projects. This two-step research is using a combination of qualitative and quantitative methods and two data sets to suggest a conceptual, two-dimensional construct model for the classification of technical projects and for the investigation of project contingencies. Within this framework, projects are classified into four levels of technological uncertainty, and into three levels of system complexity, according to a hierarchy of systems and subsystems. The study provides two types of implications. For project leadership it shows why and how management should adapt a more project-specific style. For theory development, it offers a collection of insights that seem relevant to the world of projects as temporary organizations, but are, at times, different from classical structural contingency theory paradigms in enduring organizations. While still exploratory in nature, this study attempts to suggest new inroads to the future study of modern project domains.

One Size Does Not Fit All Projects: Exploring Classical Contingency Domains

Revolutionizing product development

http://www.reinventingprojectmanagement.com/material/other/11.%20In%20search%20of%20classification.pdf

In search of project classification: a non-universal approach to project success factors

Studies on project success factors were typically based on subjective lists for respondents to check, or on a limited number of managerial variables and success criteria. This comprehensive study uses multidimensional criteria for assessing project success, and employs multivariate statistical analyses for identifying the common managerial factors affecting almost all types of projects. Altogether, we used 13 success measures and 360 project management variables for our assessment. The use of a very detailed data set and multivariate methods enables us to address several perspectives which have not been adequately analysed by previous research. The main results of this study are: (i) A well-designed initiation phase is the most important factor in project success; (ii) organisational setup and project structure are not good predictors of project success; (iii) formal design and planning documents are instrumental in meeting project time and budget constraints, as well as in ensuring customer satisfaction from the end-product; (iv) design changes during the execution of the project are usually detrimental to the customer's satisfaction, and contribute little to the improvement of the end-products.

Stanislav Lipovetsky

Papers

In search of project classification: a non-universal approach to project success factors

What is really important for project success? A refined, multivariate, comprehensive analysis