When it comes to decision making, are projects different from programs?

Managing Partner, Valense, Ltd.


Typically, when presenting the justification for a new project (at the project level), the business case explores the necessary information needed to support the decisions to commit to achieving the outputs. At the program level, the business case needs to present the necessary information to support decisions that will, over time, increasingly commit an organization to the achievement of its outcomes or benefits. In order to do so, the business case resorts to a number of reasoning processes in logic and argument, such as deductive, inductive, abductive-inference, or analogy.

This paper presents the major differences between the decision-making processes in a time-limited project environment and the decision-making processes in the longer time-scale of the program environment. Often, it is too commonplace that the more classic decision-making theory and practice of breaking down big decisions into smaller decisions used in a project approach are exported to the program approach, with the underlying assumptions that the sum of many small decisions will lead to one good major decision and the conviction that people think and decide in a rational manner, using probabilistic facts in a constructive way.

This paper outlines the major differences between project and program business case construction and explores the more recent trends in decision making to help program managers when the volume and/or complexity-induced information overload limits or precludes the use of a traditional decision-making approach.

Decision Making

Mintzberg (Sambharya, 1994) considered decision making to be the most crucial part of managerial work and organizational functioning. Different definitions of what a decision is and involves abound in literature that spreads through the knowledge of many centuries and throughout all disciplines (Schull, Delbecq, & Cummings, 1970). Decision making is very important to most companies. Modern organizational definitions can be traced back to von Neuman and Morgenstein (1947), who developed a normative decision theory from the mathematical elaboration of the utility theory applied to economic decision making. Their approach was deeply rooted in sixteenth-century probability theory. This trend has continued until today and can be found relatively intact in present decision analysis models, such as those defined under the linear decision processes. This approach uses the probability theory to structure and quantify the process of making choices among alternatives. Issues are structured and decomposed to small decisional levels, and re-aggregated with the underlying assumption that many small good decisions will lead to a good big decision. Analysis involves putting each fact in consequent order and deciding on its respective weight and importance.

Most descriptive research in the area of decision making concludes that humans tend to use both an automatic non-conscious thought process as well as a more controlled one when making decisions (Hastie, & Dawes, 2001). This dual thought process is possible, because of the human mind's ability to create patterns from facts and experiences, store them in the registers of long-term memory, and re-access them in the course of assessing and choosing options. Many authors refer to this mechanism as “intuitive decision making,” a term that has not gained much credibility in the business environment and is still looked down on by many decision analysts; therefore, it is not surprising to find that a linear mechanistic approach to decision making permeates the literature of project management.

Throughout its development, the project context seems to have neglected the importance of the softer and/or more qualitative aspects of the management domain. These aspects are now being recognized as essential for good business to develop and, in the new context of projects and programs, quantitative aspects of the decision-making process are progressively becoming secondary issues to such qualitative issues as the meaningfulness of a decision for different stakeholders and the overall organization.

Project managers are repetitively expected to listen to different stakeholders' needs and account for the numerous quantitative variables when making decisions; however, both information overload and organizational constraints usually make this difficult to implement. Very little guidance can be found in the project literature when it comes to decision making. If anything, the overwhelming importance of the decision making issue seems rather accepted as common knowledge for project managers. It is not mentioned or explored in A Guide to the Project Management Body of Knowledge (PMBOK® Guide)— Fourth Edition (PMI, 2008a), despite the bulk of recent research and growing interest in this domain. In spite of the increasing importance placed on decision-making knowledge and skills, many project and program managers continue to struggle with the concept that can stand in the way of career progression and may be one of the primary factors preventing project and program success.

Project management practice is permeated with the thought that, in order to facilitate decision making in the project context, simple (linear) evaluation tools should be widely used and, depending on the context, some more advanced evaluation tools are regularly applied. However, it has long been documented that decision-support tools are no longer sufficient, because organizations are becoming flatter and increasingly projectized and project managers' roles have grown to accommodate the ever-changing complexity of the business environment. This situation has added considerably to the number of variables and the dimensions of an already complex web of relationships brought about by the stakeholder focus. With such changes as the implementation of project management offices, portfolio management, program management, and project-based organizations, project managers are now called on to interact with an ever-expanding pool of stakeholders and other tools, such as meetings, reports, and electronic networks are also important facilitators in managing strategic projects. Intuition, judgment, and vision have become essential complement tools for successful strategic project and program management.

Without an appropriate framework, some authors have suggested that managers do not characteristically solve problems but only apply rules and copy solutions from others (March, 1991). Managers do not seem to use new decision-support tools that address the potential all-encompassing sector-based elements, such as flexibility, organizational impact, communication, and adaptability, nor technological and employee developments (e.g. intellectual capital). There is, therefore, a potential for the managerial application of new, value creation decision-support tools that could develop within new decision-making frameworks. Because these are no mature tools, the first time they might be introduced in a more qualitative way, “a way of thinking,” as suggested by Amram and Kulatilaka (1999), to reduce the managerial skepticism. Recent decision-support tools may be successfully combined with traditional tools to address critical elements and systematize strategic project management.

It is now a well-accepted fact that traditional problem-solving techniques are no longer sufficient because they lead to restrictive, linear Cartesian conclusions on which decisions were usually based in the past. Instead, practitioners need to be able to construct and reconstruct the body of knowledge according to the demands and needs of their ongoing practice (Schon, 1987). Reflecting, questioning, and creating processes must gain formal status in the workplace (Bredillet, 2004).

In the 1950s, Cyert, Simon, and Trow (1956) already implied that management is a series of decision making processes and asserted that decision making is at the heart of executive activity in the business world. In the new business world, decisions need to be made fast and most often will need to evolve over time. However, most of the research is based on a traditional linear understanding of the decision making process. In this linear model, predictions are made about a known future: decisions are made at the start of a project, taking for granted that the future will remain an extension of the past.

Decision Making in the Project Management Context

The commonly accepted definition of a project as “a unique interrelated set of tasks with a beginning, an end, and a well-defined outcome” assumes that everyone can identify the tasks at the onset, provide contingency alternatives, and maintain a consistent project vision throughout the course of the project (De Meyer, Loch, & Pich, 2002). The “performance paradigm” (Thiry, 2002a, 2002b) used to guide project management holds true only under stable conditions or in a time-limited, change-limited, context (Standish Group International, 1994). This is acceptable as long as, by definition, the project is a time-limited activity, and for the sake of theoretical integrity, is restricted to the foreseeable future.

In this context, the traditional decision-making model has provided project managers with a logical step-by-step sequence for making a decision. This is typical of models proposed in the decision-making literature of past corporate planning and management science. It describes how decisions “should be” made, rather than how they “are” made. The ability of this process to deliver “best” decisions rests on the activities that make up the process and the order in which they are attended to. In this framework, the process of defining a problem is similar to making a medical diagnosis; the performance gap becomes a symptom of problems in the organization's health, and identification of the problem is followed by a search for alternative solutions. The purpose of this phase of the decision-making process is to seek “the best solution” (Jennings, &Wattam, 1998, Ch 1). Several authors have identified a basic structure, or shared logic, underlying how organizations and decision makers handle decisions. Three main decision-making phases can be defined: Identification, by which situations that require a decision-making response come to be recognized; development, involving two basic routines (a search routine for locating ready-made solutions and a design routine to modify or develop custom-made solutions); and selection, with its three routines (screening, evaluation-choice, and authorization) (Mintzberg, Raisinghani, & Theoret, 1976).

Decision Making in the Program Management Context

More recently, many organizations have felt a need to further develop a fully “projectized” structure, which goes beyond a simple portfolio approach and involves the management of strategic decisions through programs (Moore, 2000; Richards, 2001; Thiry, 2004b). This move has somewhat shifted the responsibilities and decision-making roles of project and program managers. It is well documented that, in most organizations, project managers work within a paradox. They have an official role in a legitimate control system, facilitating an integrated transactional change process, and simultaneously participate in a shadow system in which no one is in control (Shaw, 1997).

A mechanistic style of management, which warrants a more rational and linear approach to decision making is appropriate when goals are clear and little uncertainty exists in the prevailing environment (De Meyer, Loch, & Pich, 2002; PMCC, 2002). Program management practice is not meant to replace this management focus; rather, it encompasses it in a larger context. Here, project managers cannot control their organization to the degree that the mechanistic perspective implies, but they can see the direction of its evolution. When several variables are added to a system or when the environment is changed, the relationships quickly lose any resemblance to linearity (Begun, 1994).

These issues have been raised by authors (Gorog & Smith, 1999; Grundy, 2000; Lycett, et. al., 2004; Thiry, 2004b) in reference to strategic issues such as the organization's competitive position, the achievement of the program's benefits, and the effects of changes on the program business case. These same issues have traditionally been processed through a project view of change control rather than a strategic view of change management. One of the main drawbacks is that these standard approaches focus on a linear program life cycle (Lycett, et. al., 2004; Thiry, 2004a). According to these authors, the focus on early definition and control of scope severely restricts flexibility, thus negating the value of having a program. Furthermore, insistence on a rigid life cycle intrinsically limits the ability of the program to adapt in response to an evolving business strategy (Lycett, et. al., 2004).

In his work on decision making during the implementation of strategic projects, Grundy (2000) found that cognitive, emotional, and territorial aspects were so intrinsically interwoven into the decision-making process that he employed the concept of “muddling through,” originally introduced by Lindblom in 1959. Similarly, unsatisfied with the rational model of decision making at upper management levels, Isenberg (1984) stated that managers rely too heavily on a mix of intuition and disciplined analysis and might improve their thinking by combining rational analysis with intuition, imagination, and basic rules of operation.

Project Management Decision-Making Framework

The literature shows that project managers seem to have a natural predisposition to using a more traditional and structured approach to decision making. This observation can be accounted for in more than one way. The difference could be caused by the nature of their roles and responsibilities, or that people who have personal affinities for this type of decision-making approach tend to be attracted to this type of work. Further psychological testing would be necessary to establish this second type of relationship; nevertheless, the project management literature still describes a logical step-by-step approach, such as those described by Jennings in the 1990s and by Mintzberg in the 1970s. Although critics of this approach have outlined the fact that the ability of this process to deliver “best” decisions rests on the activities that make up the process and the order in which they are attended to, project managers seem to be comfortable with, and skilled at, using this method to resolve problems.

Within this decision-making model, a process of deductive reasoning is more often used than in the program management context, in which inductive reasoning is more often described as a preferential thought process when engaged in decision-making activities. The concept of deductive reasoning was first developed by Aristotle, Thales, Pythagoras, and other Greek philosophers of the Classical Period (600 to 300 B.C.). This is the type of reasoning that proceeds from general principles or premises to deriving particular information. This type of reasoning is quite characteristic of most linear decision making tools used in the context of “high certainty.” These tools are aimed at achieving an optimal solution to a problem that has been modeled, with two essential requirements:

  1. that each of the variables involved in the decision-making process behaves in a linear fashion (of the decisional range), and;
  2. that the number of feasible solutions is limited by constraints on the solution.

These techniques rely almost entirely on the logic and basic underlying assumptions of statistical analysis, regression analysis, past examples, and the linear expectations and predictions they stimulate. A good example of this is the story that Aristotle is said to have told of how Thales used predictive logic to deduct, from accumulated historical data, that the next season's olive crop would be a very large one and he then bought all the olive presses, making a fortune in the process. However, given that deductive reasoning is dependent on its premises, a false premise can possibly lead to a false result. In the best circumstances, results from deductive reasoning are typically qualified as non-false conclusions, which can best be explained in the following simple example:

All humans are mortal. Paul is a human Paul is mortal.

From the project manager's perspective, the project's basic assumptions and constraints are the starting premises for all further decisional processes. In fact, these initial conditions of the project environment act as limits or boundaries, necessary for this type of decision-making process to be effective. With this said, project managers seem to describe a pattern in which large decisions are actually made during the first phases of the project and before and during the planning stage. Project management typically delivers outputs in the forms of products and services, and most project decisions are made to commit to the achievement of these specific outputs (PMI, 2008b). This perspective infers that a series of small decisions, which amount to the project plan, are made during the planning phase and finally add up to what is referred to as a large decision: the approved project plan. All these decisions that shape the project are made at the onset of the project. All later decisions are considered less important, more specific, and aimed at problem solving, often limited to one domain of knowledge at a time (i.e. technical, human relations, procurement). Because most large decisions have been made at the onset, once the scope is defined, it limits the number of possible dependent variables in the decision-making process. The number of significant stakeholders involved is also limited, and the overall situation is described as limited to the project's immediate environment. Much of the decision making follows a relatively traditional structured model to which the deductive thought process seems to adapt readily. Exhibit 1 illustrates this decision-making model in projects.

Decision-Making Model in Projects

Exhibit 1 – Decision-Making Model in Projects

Program Management Framework

A particularly interesting finding is the fact that deductive reasoning does not seem quite as popular or as universally called for in the decision-making processes of the program management literature. Although the process of deductive reasoning is described sporadically in the program management literature, the process of inductive reasoning seems more popular. Deductive reasoning applies general principles to reaching specific conclusions, whereas inductive reasoning examines specific information, perhaps many pieces of specific information, to derive a general principle.

A well-known example of this type of thought process is found in the story of Sir Isaac Newton. Through observation and thinking about phenomena such as how apples fall and how the planets move, he deduced the theory of gravity. Program managers relate stories about having to collect information through observation, questions, and numerous exchanges in order to put the pieces together into a cohesive story to manage the program. The use of analogy (plausible conclusion) is often apparent. This process uses comparisons such as those between the atom and the solar system, and the decision-making process is then based on the solutions of similar past problems or what is often referred to as experience. Contrary to project management, in which most decisions are taken to commit to the achievement of specific outputs, program management typically delivers outcomes in the form of benefits, and business case decisions are taken over longer periods of time, depending on the number of projects that are integrated and to the timing scales of these different projects (PMI, 2008b).

These concepts increasingly commit an organization to the achievement of the outcomes or benefits and the decision-making period, although important at the beginning, continues progressively as the situation evolves to accommodate the changes in this larger environment. Program managers tend to converge toward an ongoing series of large decisions (affecting the totality of entire projects) as the program evolves over time. This can be compared with the project level discourse that described large decisions at the onset and smaller ones (not affecting the overall business case of the project) as the project evolved. This is in keeping with the fact that, because programs deliver benefits as opposed to specific products or services, the limits of the program environment are not as specific or as clearly defined as those for the project. Organizational benefits are inherently linked to organizational strategy, value systems, culture, vision, and mission. This creates an unbounded environment and basic assumptions are not as clear as for the project environment. This could account for the fact that deductive thought processes are less suited than inductive ones in the decision-making processes of program managers. (Exhibit 2)

Model Decision Making in Programs

Exhibit 2 – Model Decision Making in Programs


Decision-making processes for projects and programs differ significantly in the timing, pacing, and number of major decisions, as well as the nature of the decision-making processes employed. Most large or important project decisions are bound by the project's basic assumptions, and project managers tend to have a preference for deductive mental processes when making decisions. The occurrence of large or important program decisions seems to persist throughout the program life cycle because they are prompted by setting the assumptions for each project when these programs kick off. Because the program delivers benefits, which cannot be as clearly defined as products or services, its environment is not as clearly defined or bound by set basic assumptions; hence, inductive reasoning seems more suited to meeting the decision-making needs of program managers.


Amram, M., & Kulatilaka, N. (1999). Real options: Managing strategic investment in an uncertain world (1st ed.). Massachusetts: Harvard Business School Press.

Begun, J. W. (1994, December). Chaos and complexity frontiers of organization science. Journal of Management Inquiry, 3(4), 329-335.

Bredillet, C. (2004). Knowledge management and organizational learning. In P.W.G. Morris & J.K. Pinto (Eds.), The Wiley project management resource book. New York, NY: John Wiley and Sons.

Cyert, R.M., Simon, H.A., & Trow, D. B. (1956). Observations of a business decision. The Journal of Business, 29(4), 237-248.

De Meyer, A., Loch, C. H., & Pich, M.T. (2002, Winter). Managing project uncertainty: From variation to chaos. MIT Sloan Management Review 43 (2) p60-67.

Görög, M., & Smith, N. (1999). Project management for managers, Newtown Square, PA: Project Management Institute.

Grundy, T. (2000). Strategic project management and strategic behaviour. International Journal of Project Management, 18, 93-103.

Hastie, R., & Dawes, M. (2001). Rational choice in an uncertain world. Thousand Oaks, CA: Sage Publications, Inc.

Isenberg, D. J. (1984). How senior managers think. Harvard Business Review, Nov/Dec, 80.

Jennings, D. (1998). Strategic DM. In D. Jennings, & S. Wattam (Eds.), DM: An integrated approach (2nd ed, pp. 251-282). Harlow, UK: Prentice Hall Pearson.

Lindblom, C. E. (1959). The science of muddling through. Public Administration Review, 19, 79-88.

Lycett, M., Rassau, A., & Danson, J. (2004). Programme management: A critical review. International Journal of Project Management, 22, 289-299.

March, J. G. (1991). How decisions happen in organizations. Human-Computer Interaction 6(2), 95–117.

Mintzberg, H., Rasinghani, D., & Theoret, A. (1976, June). The structure of “unstructured” decision processes. Administrative Science Quarterly 21 (2) 246-275.

Moore, T. J. (2000). An evolving program management maturity model: Integrating program and project management. Proceedings of the Project Management Institute's 31st Annual Seminars & Symposium Proceedings [CD-ROM].

PMCC (2002). A guidebook of project and program management for enterprise innovation (P2M)-summary translation, Revised Edition. Project Management Professionals Certification Center, Japan.

Project Management Institute (PMI). (2008a). A guide to the project management body of knowledge (PMBOK® Guide)—Fourth Edition. Newtown Square, PA: Author.

Project Management Institute (PMI). (2008b). The standard for program management—Second Edition. Newtown Square, PA: Author.

Richards, D. (2001). Implementing a corporate programme office. Proceedings of the 4th Project Management Institute-Europe Conference [CD-ROM].

Sambharya, R. B. (1994). Organizational decisions in multinational corporations: An empirical study. International Journal of Management, 11, 827-838.

Schön, D.A. (1987). Educating the reflective practitioner. London: Jossey-Bass.

Shaw, P. (1997). Intervening in the shadow systems of organizations: Consulting from a complexity perspective. Journal of Organizational Change Management, 10(3), 235-250.

Shull, F.A., Delbecq, A.L., & Cummings, L.L. (1970). Organizational DM. New York: McGraw-Hill

Standish Group International (1994). The CHAOS Report. Retrieved 25 February 2000 from http://www.standishgroup.com/sample_research/chaos_1994_1.php.

Thiry, M. (2002a/2001). Combining value and project management into an effective programme management model. International Journal of Project Management, (Special issue April 2002; 20-3, 221-228, and Proceedings of the 4th Annual Project Management Institute-Europe Conference [CD ROM].

Thiry, M. (2002b). The development of a strategic decision management model: An analytic induction research process based on the combination of project and value management. Proceedings of the 2nd Project Management Institute Research Conference, 482-492.

Thiry, M. (2004b) Program management: A strategic decision management process. Ch. 12. In P.W.G. Morris & J.K. Pinto (Eds.), The Wiley guide for managing projects. New York, NY: John Wiley and Sons.

von Neuman, J., & Morgenstein, O. (1947). Theory of games and economic behavior. Princeton, NJ: Princeton University Press

©2010 Manon Deguire
Originally published as a part of 2011 APMI Global Congress Proceedings – North America



Related Content