The development of a strategic decision management model
an analytic induction research process based on the combination of project and value management
Michel Thiry, AIA, PMP, MAPM, CVS, CVM, PVM, Organizational Consultant, Associate Consultant PMGS, Associate Professor ISGI-UTS, External Lecturer Reading University
Over years of practice in a wide range of project environments, I have, like others (Frame 2002), witnessed a change of the role of project manager from a single person with specific technical skills to that of a team of individuals which exercise a wide “function” that spans from strategic to technical. Until recently project managers were typically working “for”clients and answering to the client’s representative, who was the true decision-maker. The project management function is now evolving towards a co-managed business-technical partnership (Frame 2002), which gives it authority over strategic level resources and therefore true decision-making power (Spradlin 1997). With this new role, comes the need to understand the making of decisions.
Gadeken (1999) argues that the project manager’s “emphasis must shift from that of project management professionals to leaders of organizational change.” Görög and Smith (1999), who advocate the use of project management in strategy implementation of organizations, suggest that project management needs to move towards a more strategic-oriented paradigm. They argue that this new paradigm involves:
1. A cycle that encompasses both strategic objectives and strategic benefits evaluation.
2. The development of a methodological background in addition to tools and techniques.
3. Taking into account of the interrelatedness of projects.
I have argued that project management, as it is defined by textbooks and by the tools and techniques that support it, is focused on “performance” (Thiry 2002a).“Learning,” which is key to decision-making, is not taken into account. On the other hand, decision-making textbooks and practice focus on the decision-making process itself, taking very little account of the implementation of decisions and the measure of actual results. This emphasizes the need to develop a strategic decision management framework effectively supporting the partnership between business and projects.
The basic assumption of this research is that most organizational decisions relate to a change process, which in essence is fluid. Within this view, the decision management process is constituted of a series of iterative loops, starting with the identification of a need to change and leading to the actual successful output of the change process. Each cycle should fulfill an expressed need, thus ensuring the strategic value of project outcomes, but also constitutes an evaluation of the need to further the change process. Theory-wise, this model relies on a broad range of literature: decision-making, organizational change, strategic management, project management, value management, goal motivation, and evaluation theories. Applications of those theories are presented to support the elaboration of a practical decision management model.
Although elaborated in the first half of the 20th Century, practical research applications of Analytic Induction (AI) have only recently been recognized. The dominance of deductive statistical research methods, which can produce fast conclusions, has not enabled AI to be accepted as a mainstream research methodology. AI is an ideal methodology to develop and verify theories concerning complex situations as it is based on the continual reformulation of hypotheses or redefinition of studied phenomenon in the light of new data, until the theory is strongly anchored in practice. This makes it difficult to use when quick results are the key to success, but it offers practicing researchers a golden opportunity to ground their theory in practice.
This study is set in a participatory (qualitative) research paradigm (Denzin and Lincoln 2000), which recognizes the coexistence of subjective and objective realities. Findings are developed through successive transactions and strongly grounded in practical and experiential context.
Exhibit 1. An integrated Design Management Process
The main element of validity in all research could be deemed as the isomorphism between what is being studied and what is being reported (Punch 1998). Traditional research is deductive and can only give a cross-sectional assessment of a situation, even with a longitudinal study. Thus, a number of authors have argued that they often miss the complexity and ambiguity that are the features of most organizational situations (Denzin and Lincoln 2000; Guba and Lincoln 1989; Rubin and Rubin 1995). In an environment as complex and changing as organizational decision-making, only a process like AI can lead to the necessary degree of validity. As a cyclic process, it can also seize the complexities that characterize the shift of value management and project management from technical to management methodologies and the emergence of program management.
AI is primarily a cyclic process; it goes through observation and an initial definition of the phenomenon,followed by a deductive hypothesis formulation, inductive case analysis, hypothesis reformulation, and so on until a degree of certainty about the hypothesis is achieved.
Structure of Paper
The paper’s structure is based on the AI process; it is divided into a number of loops that each represents an inductive-deductive cycle leading to the current theoretical framework. The first loop covers the initial definition of a phenomenon and the period from 1992 to 1996, which leads to the formulation of an integrated design management process in construction projects. The second loop covers the period from 1996 to 1998, which led to the integration of VM in both project and program management. The third loop explains how VM has been linked to a learning loop and project management to a performance loop and both combined into a change management cycle, prompting the development of a cyclic decision management process, and covers the period from 1998 to 2000. Finally, between 2000 and 2002, a full decision management model was developed, based on previous findings and organizational theory.
First Loop: 1992–1996
In more than twenty years of architectural and construction management practice I have witnessed the waste of efficiency and effectiveness caused by fragmentation of architecture, engineering, and construction and the difficulty to integrate practice, even within disciplines. These observations prompted me, between 1982 and 1992, to develop and apply a framework integrating briefing, design, and construction processes in a number of turnkey projects.
In 1992–93, as Head of the Professional Services Procurement Section, I had the opportunity to initiate the development of an integrated practice of value management and project management for the Construction Department of a major Canadian City. The Director of the Department had decided to champion the introduction of VM to try to control spiraling costs. Following applications of VM at the detailed estimate stage, it was concluded that integration from the project definition phase would be more effective to control costs and ensure quality of deliverables.
At that time, Architectural Practice Theory promoted the architect as the integrator of construction practices, but reality was quite different. Value Engineering and Value Analysis Theory, were primarily concerned with product improvement, and Project Management Theory, prior to publication of the 1996 version of A Guide to the Project Management Body of Knowledge (PMBOK® Guide) (Project Management Institute 1996) was fragmenting practice, and not recognized at management level.
Exhibit 2.VM Integration at Project Level
From 1994 to 1996, building on these observations, I took responsibility for the integration of all project processes on a number of complex fast track projects, concentrating especially on the application of VM. In 1995–96, I wrote a number of papers (Thiry 1996a, 1996b, 1996c) advocating the integration of VM in the management of projects, as a means to improve stakeholder needs management and product value.
Initial Definition of Phenomenon
Following those initial observations, the observed phenomenon we described as:
The lack of integration between the different disciplines in a project situation does not allow a clear understanding and management of stakeholders’ needs and expectations.
First Hypothesis Formulation
Combining the theory of the Architect as an integrator with VM and project management integration, I developed a Design Management process and led the application of this process on two extensions of the Montreal Casino. The fact that our firm led three consecutive phases of the development of the Montreal Casino over a number of years, combined with the application of this model, enabled me to formulate the following hypothesis:
The project management role should be extended to cover pre-initiation phases and post project feedback, in order to better understand and manage stakeholders’ needs and expectations. This will also trigger an active participation in strategic level decision-making.
Second Loop: 1996–1998
Inductive Case Analysis
In 1996, I accepted a position as Value Management Consultant for the Program Management Consultancy of a UK-based global construction organization. This gave me the opportunity to experiment first hand with the use of VM in the early stages of projects and apply the theoretical framework developed in 1994–96 in a wide range of industries, from water treatment and transportation to pharmaceutical. A number of interventions were implemented at program level and therefore at pre-initiation stage with numerous stakeholders and a complex web of relations.
Interventions at the program level required explicit differentiation between project management as a role and the individual project manager. Working with a large multinational water treatment organization, managing multiple projects simultaneously, prompted the need to distinguish program management from project management.Most of the large complex projects or programs I worked on also identified the need for group decision support methods,which VM was providing as a secondary benefit.
In parallel, I was tasked with the development of large pan-organizational training programs in VM for London Underground and a worldwide Self-Development Program in VM (part of a work-based MSc program) for my own firm. I participated actively in the development and implementation of a pan-organization project management training program for a large European Public Organization, including training needs analysis. This latter program was part of a wider organizational change program to bring the organization from functional to projectized. During these interventions, it became clear that early use of VM as a soft,rather than hard methodology was required at program level.
Inductive Theory Analysis
In those years, VM writers started developing the concept of “Soft” VM (Barton 2000; Green 1997) and Integrated VM (Thiry 1996b; Thiry 1996c; Thiry 1997) advocating the use of soft people-based methodologies like group decision-making (Vennix 1996), systems thinking (Waring 1989), and soft systems analysis (Checkland and Scholes 1994) as an integral part of VM.
Exhibit 3.VM Integration at Program Level
Group decision-making and strategic management literature provided the theoretical basis to shift VM theory from hard to soft and develop it as a management level methodology. At the same time, a group of VM practitioners was developing a European VM Standard, which eventually described VM as a “style of management”(CEN 2000).
Concurrently, the PMBOK® Guide, 1996 edition, confirmed project management as a performance-based methodology, clearly centered around the definition of clear objectives and parameters, as well as a process-based timeframe. Other standards (ISO 10006; BS-6079) aimed to expand the project management process to the product life cycle, but it was generally agreed that the project manager’s role was confined to the processes between initiation and closing.
In this loop, I developed two distinct frameworks combining VM and project management. The first describes the use of VM within the project management life cycle, mostly as a needs identification method and a project review methodology; the second considers the wider program process.Those frameworks reinforce VM as a soft, integrated methodology and reinforce its group decision focus; they acknowledge that an extension of the project management role can rely on the use of soft VM and confirm project management as a performance-based methodology.
Third Loop: 1998–2000
Inductive Case Analysis
In 1998, I had the opportunity to lead a complex VM intervention consisting of bringing together a number of soft and hard projects supporting considerable organizational growth and culture change, while minimizing the impact on a number of key ongoing new product development projects. VM was used to perform stakeholders’ analysis and to identify needs and expectations to formulate a program. It was followed by the development of alternatives and options on the program organization process, the grouping of existing project and the identification of the required support projects. One of the key learning points of this process was the importance of sensemaking in high ambiguity situations.
I also led a series of VM workshops for the large European Public organization, to develop a combined program-project process supporting organizational change and earlier training. It is an obvious example of a situation where an organizational change process confuses people and a sensemaking process is required to clarify the issue. A sensemaking approach was also used to facilitate a workshop aimed at gaining stakeholders agreement on the reporting process of a large automotive information technology (IT) support organization.
These interventions were all dealing with major, unsettling change and it became clear that those situations could not be dealt with solely with planning and project tools and techniques. This type of intervention needed to encompass a learning perspective.
Inductive Theory Analysis
In parallel of practical application of VM and project management, research in theories of decision-making and change management literature brought the following conclusions.
A key theoretical finding leading to the concept of decision management was the fact that most decision-making literature lacked:
1. An identification of expected results as part of the decision process, which VM could address.
2. An implementation process to carry through the decision and deliver the results, which project management could address.
Change management literature identified the fact that organizations were ill prepared to deal with what Minzberg and Westley (1992) called: emergent change, while Weick (1995) identified the need for sensemaking as a prerequisite to change. These concepts instigated my redefinition of Mile’s (1972) traditional VM process of: information-analysis-creativity-judgment-development into a more management adapted sense-making-seeking-evaluation-decision (Thiry 2001).
At strategic management level, Mintzberg and Waters (1985) have defined two types of strategy:
1. The “deliberate” strategy, which is based on a precise plan and is consistent with project management.
2. The “emergent”strategy, which is largely responsive and could be associated with VM.
Later, Mintzberg et al (1998) argued that both should be considered to achieve results and have named this approach the “configuration”school. Hurst (1995), reinforcing this argument, described organizational change as a cyclic “Change Eco-Cycle” composed of a renewal loop (emergent strategy), which follows a crisis (emergent input), and a conventional loop (deliberate strategy), which follows a choice (deliberate input).
The eco-cycle concept and those of Learning (Argyris and Schon 1978; Senge 1990) and Process Consultation (Schein 1996) were key to the development of a cyclic, stakeholder-oriented change management process. Learning focuses on the systemic perspective and iteration process; process consulting identifies the need to work with the clients in order to enable them to develop their own solution. These directly address the concepts of multiple, often conflicting, stake-holders’ needs, which the PMBOK® Guide identifies without offering a solution.
From 1998 to 2000, I wrote and presented a number of papers on decision-making in projects (Thiry 1998), the use of VM in support of organizational change and project management in support of strategic change (Thiry 1999; Thiry 2000a). In a paper presented at the International Business and Corporate Strategy and Planning Congress (Thiry 2000c), I argued that VM was ideally suited to carry out the learning loop required to address emergent change. A paper, written for the Project Management Institute (PMI®) 2000 Seminars & Symposium (Thiry 2000b) was the first to offer a combined view of value and project loops into a program framework destined to manage decisions. These papers focused on the concepts of sensemaking and that of a cyclic change management process combining a learning (emergent) and a performance (deliberate) loop.In particular, the importance of VM as a sensemaking process needs to be outlined.
VM and Sensemaking
VM is a group-based methodology that “… aims to reconcile multiple stakeholders’ differing needs and enable an organization to achieve the greatest progress towards its stated goals with the minimum use of resources” (CEN 2000).
Exhibit 4. Combining Learning and Performance Loops for Change Management
Exhibit 5. A Learning Loop for Program Management
The first step of the VM process is to make sense of the emergent input that justifies a change. Weick (1995) writes: “In the case of ambiguity, people engage in sensemaking because they are confused by too many interpretations, whereas in the case of uncertainty, they do so because they are ignorant of any interpretation.” In decision-making, “sensemaking can be seen as a system of interactions between different actors, building a collective understanding of a situation” (Thiry 1999).
The second step of the VM process, seeking (later labeled ideation), is based on creative thinking concepts (deBono 1990) and consists of identifying as many alternatives as possible.
The third step consists of evaluating options in regards of the critical success factors established through the sense-making process and to assess their feasibility and prioritize them, in regards of resource availability and capability. Since VM is mostly a group process where key stakeholders are heavily involved, decision makers will feel confident of their decisions and support the chosen options.
It has been demonstrated that organizational change requires a learning loop, associated to VM, to respond positively to emergent changes and that project management can efficiently deliver deliberate change, once choices had been made. It is now safe to say that any extension of the project management role, to support decision management, should be carried out through integration with VM as a learning loop to complete the project management performance loop.
The frameworks below represent this combined view. Exhibit 5 deliberately replicates by project management process groups displayed in the PMBOK® Guide to enable easy comparison.
Fourth Loop: 2000–2002
In summary, at this stage, a phenomenon had been defined:
The lack of integration between the different disciplines of in a project situation does not allow a clear understanding and management of stakeholders’ needs and expectations.
Through three major loops of inductive case analyses and practical application of reformulated theoretical hypotheses, a degree of certainty had been achieved concerning the understanding of this phenomenon:
1. The project management role should be extended to better understand and manage stakeholders’ needs and expectations. This will also trigger an active participation in strategic level decision-making.
2. It must rely on the use of soft VM and confirm project management as a performance-based methodology.
3. It should be carried out through integration with VM as a learning loop.
Following previous analyses of decision-making and change management theories and conclusions thereof, the development of a theoretical framework representing the big picture of strategic decision management can now be attempted.
Inductive Case Analysis
The period 2000–2002 enabled me to test an integrated decision management framework in a number of pan-organizational training programs and people-oriented organizational change.
Participation in Project Management Training Programs
As a trainer and researcher, I was directly involved in major training programs for two large public organizations, one in the United Kingdom (UK) and the other in Belgium. These organizations were preparing to undertake the next phase of a pan-organization training program that had spanned over 3–4 years and was a key element in a major organizational change.
Within a research project, investigating the ways in which organizations evaluate decision results, I interviewed two key stakeholders in each organization. The main conclusions were that, in both cases, the decisions had been driven from the top and supported a major organizational change to move the organization form functional to projectized. In each case there was a learning loop, including a form of sensemaking, before the decision to undertake the program was confirmed.
At the time of the interview, these organizations were in a learning loop that was part of the program appraisal process. The interviews established the need to make sense of the program outputs, generate alternative courses of action, and evaluate them in regards of the current critical success factors, before a decision to undertake a subsequent phase could be made.
Development of Project Management Training Programs
On five other pan-organizational training programs, I developed the program in collaboration with the client. In two cases, VM was used to structure and perform the training needs analysis (TNA); in another case a systematic TNA had been carried out prior to my involvement. In these cases, clear program objectives linked to organizational effectiveness were identified and critical success factors were set to measure the program results. In the two other cases, where triggers for the program were set at performance level,man-agers had predefined the requirements and I met with key stakeholders, strictly to validate requirements, the objectives were mostly limited to the number of people to be trained.
In all the above cases, including the two large programs of the previous section; when an unambiguous (deliberate) decision had been made that project management training was the requirement and objectives were preset, project (performance) methodology was used to run the program, which meant a planning-execution control approach. When the objectives were not as clearly defined (emergent) from the start as to what the organization, or management unit, required to improve its performance, the managers of the program went through a learning process, including sense-making, in order to define those requirements more clearly, before any attempt was made at generating alternatives or evaluate options.
Project Management Methodology Development
In another interesting case, very similar to the one described in the 1998–2000 loop for the European Public Organization, a small, highly specialized organization invited me to discuss project management training. I quickly realized that pure training was not the answer, but that the problem lay mostly in the fact that there was no consistency in the application of project management methodology and therefore no integration of the planning and reporting processes, making the manager’s job unmanageable.
Through a series of interviews and VM-based workshops, we identified the issues to be addressed and, applying a process consultation approach, managed to introduce planning, risk management, reporting, forecasting, and earned-value analysis into the group’s project management processes. Acceptance was high and the group now meets regularly, without the help of an external facilitator, to update their methodology and processes.
The lessons from this consultancy process are that sense-making and a learning-based approach are effective in the successful resolution of confusing, ambiguous situations where multiple stakeholders have diverse and often conflicting interests, whereas a performance-based approach would, most probably, have deepened differences and exacerbated existing conflicts.
Inductive Theory Analysis
From Decision-Making to Decision Management
Traditional judgment and decision-making (JDM) literature bases the evaluation of decisions on two central variables established by Maier (1965) and later confirmed by Vroom and Yetton (1973):
1. Quality dominant;focusing on the “efficiency” of the decision-making process and based on decision theories (Kahneman and Tversky 1979; von Neuman and Morgen-stern 1944). Quality dominant authors argue for more detailed and accurate data to increase the quality of decisions.
2. Acceptance dominant, focusing on the “satisfaction” of the decision-maker with the decision and based on judgment theories (Bunn 1984; Hammond 1955). Acceptance dominant authors base decision-making on probabilistic concepts and their research is almost exclusively based on laboratory experiments or controlled studies. Satisfaction is based on motivation factors, which are mostly subjective and related to perception.
Following a thorough review of JDM literature, I identified four areas of concern for strategic applications:
1. JDM, as defined in the literature, is difficult to apply in complex settings.
2. The implementation process is mostly limited to the decision task.
3. The task environment is considered as generic, not taking into account the context.
4. Decisions are viewed as stand alone events.
I will examine those issues in turn to identify how they can be addressed.
Group decision-making—an acceptance dominant concept, based on participation—(Forrester 1958; Vennix 1996) is probably the theory that best applies to complex situations. Group models are based on simulation, but because of their complexity and the number of variables, they are difficult to use in “real-life” settings. As already seen above, learning models have aimed to counter this difficulty by developing a concept of feedback and iteration, which will enhance the group’s decision capabilities (Argyris and Schon 1978, Checkland and Scholes 1990; Senge 1990).
As demonstrated above through case analyses, a learning-based group decision process is effective in complex settings.
A vast amount of decision-making research has concentrated on decision-making itself, but it is recognized that the implementation of decisions is often not a research issue (Morgenson and Hoffmann 1999). On the other hand, Armenakis and Bedeian (1999) advocate that implementation processes and actions are key to the success of change efforts. Hatch (1997), Neal (1995), and others argue that strategy cannot be implemented successfully if both the goals and the strategy are not supported and that both must be continually readjusted to fit emergent inputs as the implementation progresses. The implementation process is key to the successful delivery of organizational decisions.
An analysis of Goal Motivation Theories (e.g., Frese and Sabrini 1985; or Hacker et al 1982) will suggest elements of response concerning the successful implementation of decisions. People are motivated to achieve goals that they have participated in setting and which are valued and achievable. VM uses a cross-functional team process to identify needs and build their shared value; it also establishes what can be achieved with the available resources, therefore fostering participation, value, and achievability. Success in project management is particularly influenced by the concept of a hierarchical model of motivation (Emmons 1989), which structures goals into levels to guide achievement behavior and discrepancy reduction models (Carver and Scheier 1990), which link motivation to the perceived rate of goal achievement.
I suggest that a VM-based learning loop is required to make sure that goals are linked to needs and expectations and to regularly measure the rate of achievement and project-based performance loop is required to define the scope of goals and the means to achieve them.
Uncertainty and ambiguity are two key organizational decision contexts and they are often confused. Thiry (2001) and Weick (1995) have made a clear distinction between uncertainty and ambiguity. Uncertainty is defined by the difference between the data required and the data already possessed; it is a “lack of information.” Ambiguity, on the other hand, consists of multiple and conflicting interpretations, typically found in complex situations. Whereas uncertainty requires acquisition of objective information, ambiguity requires sensemaking, exchange of views and clarification of situations/problems.
Quality dominant JDM authors argue that additional data will contribute to a reduction of uncertainty but Weick (1995) warns against the fact that complex situations can increase perceived uncertainty and the risk of increasing ambiguity by adding data. Additionally, in complex situations, there must be an understanding that goals evolve and change during action and both the existing and desired state are fluid, again increasing ambiguity. There is a danger to using uncertainty-reduction processes in ambiguous situations. In strategic management, an iterative ambiguity-reduction process is required to counteract cyclic ambiguity increases and clarify goals and expected results on an ongoing basis.
Exhibit 6.The Decision Management Cycle
Görög and Smith (1999), argue that strategic management is based on the continuous re-formulation and is a form of continuous adjustment, whereas projects concentrate on achieving one single particular result within set time and cost constraints. The performance-based project management approach is embedded in an “uncertainty-reduction” process (Winch et al 1998). In complex or emergent situations there needs to be an “ambiguity-reduction” process provided by a learning-based VM approach (Thiry 2002a) before any attempt is made at uncertainty reduction.
Research into JDM literature and practice has led me to the conclusion that strategic decisions should be redefined as “a continuum, based on a series of deterministic choices, leading to the delivery of an outcome which impacts effectiveness of the organization.” Decision tools and techniques have to be developed in view of their applicability and “usability” by decision-makers and implementation and control of outcomes must be part of the framework.
In his 1997 PMI Seminars & Symposium paper, Tsuchiya wrote, “Traditional organization style designed to thrive on mass production, stability and growth cannot be fixed to succeed in the current world where customers, competition and change demand flexibility and quick response.” He further added: “an unaligned organization is a waste of energy, whereas commonality of direction develops resonance and synergy” (Tsuchiya 1997).
In a paper presented at the Jerusalem PMI Europe Conference in 2000, I have written:
Project management gives organizations the means to implement strategies quickly and effectively, as long as they are part of a consistent vision. … Following an analysis of the situation using the learning loop concept, the organization will commit limited resources to a decisive reaction to the emergent input. (Thiry 2000a)
Projects are typically associated with deliberate strategies; most projects and project’s outcomes can be considered as a “deliberate change.” Accordingly, projects are an effective vehicle for delivering deliberate or planned change within an organization, once a choice has been made. Emergent change requires a reactive, adaptive strategy, which can be provided by a VM framework.The implementation of a cyclic VM-project management decision management framework will support the view of strategic decisions as a continuum,allowing constant evaluation of the results (deterministic choices), in regards of the objectives and the necessary flexibility to readjust the decision, if needed, to achieve organizational benefits.
The final element of the continuum concerns evaluation paradigms.According to Guba and Lincoln (1989), evaluations can be both: “summative” (to assess) or “formative” (to improve). Quinn (1996) argues that, in complex situations, each stakeholder will construct different evaluation criteria and evaluation measures will therefore need to be negotiated. Guba and Lincoln (1989) and Stake (1975) talk about “responsive” evaluation, where parameters and boundaries are determined through an interactive negotiated process.
Most proponents of the combined learning/performance program management paradigm (Wijnen and Kor 2000; Görög and Smith 1999; Murray-Webster and Thiry 2000) argue for a continuous re-evaluation or “reformulation” of the program, in regards of the achievement of organizational benefits, an inductive (based on emergent inputs) and formative type of evaluation/control. On the other hand, proponents of the performance paradigm (Bartlett 1998; CCTA 1999; Reiss 1996) argue for a deductive (based on set parameters) and summative type of control, based on performance parameters such as time, cost, resources, risks, and so on.
In the context of complex strategic situations, a valid decision model must offer both a summative evaluation at the project level and a formative evaluation at the strategy-program level, allowing for negotiated evaluation as program objectives are redefined. I have called this type of evaluation ‘mastery’ to distinguish it from control.
Exhibit 7. Strategic Decision Management Model
Strategic Decision Management Model
The following model is the latest representation of the concept described in the previous section.
It is only through the iteration of a number of cycles that this model can effectively represent strategic decision management as a continuum. The following model allows regular evaluation of project outcomes, in regards of organizational benefits; as well as the flexibility to readjust the expectations, as required by emergent inputs, or to readjust the expected outcomes to fit the circumstances.
Program Management as a Decision Management Tool
Wijnen and Kor (2000) write that a program strives for the achievement of a number of, sometimes conflicting, aims and has a broader corporate goal than projects, which aim to achieve single predetermined results. Partington (2000) argues that programs require integration across strategic levels, controlled flexibility, team-based structures, and especially, an organizational learning perspective, which is able to accept paradox and uncertainty. Murray-Webster and Thiry (2000) advocate a vision of programs, which includes mechanisms to identify and manage emergent change; they promote the concept of a “learning loop,” which completes the project management “performance loop.”
In the last year, I have argued that program management could be the methodology of choice for decision management if it can distance itself from the performance paradigm it is currently in (Thiry 2002a). A number of authors have suggested program “phases” which, albeit their different names are, in most instances, just transpositions of the project paradigm into program management. Görög and Smith (1999), as well as Thomas et al (2000), have argued for a management discourse when project management is applied at strategic level. Recently I have presented a program life cycle process aimed at supporting strategic decisions and that reflects this management discourse (Thiry 2002b). The process is as follows:
Formulation is the stage where purpose is defined, stake-holders, their needs, and expectations are identified; it is also the stage where program benefits are determined. Contrarily to project initiation, it is a complex process, where ambiguity is high. It is the initial learning cycle of programs where sensemaking, ideation and evaluation of alternatives take place and which ends with the decision to undertake a program.
Organization is the process of selecting and prioritizing projects and other actions required to deliver benefits and setting up the program team and structures. It includes the installation of operational procedures that will enable project interdependencies and interrelationships to be managed, as well as pacing the program and ensuring ongoing benefits delivery. Deployment involves the actual initiation of projects; interdependencies, and resources management; sponsor-level control, including scope verification and closeout, and benefits delivery. It is made up of review, pacing, and approval of project outputs and change/configuration control, including realignment and reprioritizing. Appraisal essentially concerns the program level assessment of benefits; it is a process that requires constant re-evaluation of the program’s circumstances and critical success factors. It is a formative mastery process, which typically corresponds to a period of stability, enabling benefits to impact the organization. Dissolution happens when the rationale for the program no longer exists; uncompleted work, projects, and resources are re-allocated to other programs, which are reformulated as needed; a post-program feedback is carried out and knowledge is recycled. It is a phasing down process, much more extensive than project closing.
This program management life cycle is iterative in nature and reflects the extended and evolving nature of strategic decisions. It is the logical extension of the AI process into practical applications of the Strategic Decision Management Model and will be a subject for development in the next few years.
Exhibit 8.The Program Management Life Cycle
Conclusion and Theory Formulation
Starting with the observation that:“The lack of integration between the different disciplines in a project situation does not allow a clear understanding and management of stakeholders’ needs and expectations,” I have used Analytic Induction to formulate a theory of Strategic Decision Management which states that:
1. Strategic Decision Management requires the combination of a learning-based group decision-making process and a performance-based decision-implementation process.
2. Complex strategic situations involve both ambiguity and uncertainty; uncertainty cannot be reduced before ambiguity is reduced.
3. VM is a learning-based, ambiguity-reduction process aimed at identifying and managing multiple stakeholders’ needs and expectations.
4. Project management is a performance-based, uncertainty-reduction process aimed at delivering solutions to clearly expressed needs and expectations.
5. The combination of VM and project management into a decision management cycle can provide the necessary learning and performance processes to effectively manage strategic decisions.
6. The iteration of a series of learning-performing cycles is required to achieve successful delivery of organizational benefits linked to organizational effectiveness and effective response to emergent inputs.
7. Program management could provide the structure for strategic decision delivery if grounded in a management paradigm.
Strategic decision-making is deeply lacking good “practical” research on implementation; project management and VM can provide the needed support to a theory of strategic decision management, which needs to be strengthened with more research.
Argyris, C., and D. A. Schon. (1978). Organizational Learning: A Theory of Action Perspective.Wokingham: Addison-Wesley.
Armenakis, A. A., and A. G. Bedeian. (1999). Organizational change: A review of theory and research in the 1990s. Journal of Management 25: 293–315.
Bartlett, J. (1998). Managing Programmes of Business Change. Wokingham: Project Manager Today Publications.
Barton, R. (2000). Soft value management methodology for use in project initiation—A learning journey. Journal of Construction Research 1 (1): 109–122.
Bunn, D. W. (1984). Applied Decision Analysis.New York:McGraw-Hill.
Carver, C. S., and M. F. Scheier. (1990). Origins and functions of positive and negative affect: A control process view. Psychological Review 97: 19–35.
CEN. (2000). Value Management, BS EN 12973:2000. European Committee for Standardization (CEN) Technical Committee CEN/TC 279—British Standards Institute (BSI) Technical Committee DS/1.
Central Computer and Telecommunications Agency (CCTA). (1999). Guide to Programme Management ‘HMSO Publications.’
Checkland, P., and J. Scholes. (1994). Soft Systems Methodology in Action.Chichester: John Wiley & Sons.
de Bono, E. (1990). Lateral Thinking: A Textbook of Creativity,3rd ed. London: Penguin Books.
Denzin, N. K., and Y. S. Lincoln. (2000). Handbook of Qualitative Research,2nd ed. Thousand Oaks, CA: Sage Publications.
Emmons, R. A. (1986). Personal strivings: An approach to personality and subjective well-being. Journal of Personality and Social Psychology 51: 1058–1068.
Forrester, J. W. (1958, Jul/Aug). Industrial dynamics: A major breakthrough for decision-makers. Harvard Business Review: 37–66.
Frame, J. D. (2002). How PMI is keeping up with rapid change in the profession. PMI Today. Newtown Square, PA: Project Management Institute Publications.
Frese, M., and J. Sabini. (1985). Goal Directed Behavior: The Concept of Action in Psychology. NJ: Lawrence Erlbaum.
Gadeken, O. C. (1999). Third wave project leadership. PM Network: 43–46.
Green, S. D. A. (1997). Kuhnian crisis in value management? Value World 20 (3): 19–24.
Görög, M., and N. Smith. (1999). Project Management for Managers. Newtown Square, PA: Project Management Institute.
Guba, E. G., and Y. S. Lincoln. (1989). Fourth Generation Evaluation. Newbury Park, CA: Sage Publications.
Hacker, W., W. Volpert, and M. von Cranach, eds. (1982). Cognitive and Emotional Aspects of Action.Amsterdam: North Holland.
Hammond, K. R. (1955). Probabilistic functioning and the clinical method. Psychological Review 62: 255–262.
Hatch, M. (1997). Strategy and goals. In Organization Theory: Modern Symbolic and Postmodern Perspectives (pp. 101–119). Oxford: Oxford University Press.
Hurst, D. K. (1995). Crisis and Renewal: Meeting the Challenge of Organizational Change.Boston: Harvard Business School Press.
Kahneman, D., and A. Tversky. (1979). Prospect theory: A analysis of decision under risk. Econometrica 47: 263–291.
Maier, N. R. F. (1965). Psychology in Industry. Boston: Houghton Mifflin.
Miles, L. D. (1972). Techniques of Value Analysis and Engineering,3rd ed. New York: McGraw-Hill Book Company.
Mintzberg, H., B. Ahlstrand, and J. Lampel. (1998). Strategy Safary. London: Prentice Hall.
Mintzberg, H., and J. A. Waters. (1985). Of strategies, deliberate and emergent. Strategic Management Journal 6 (3): 257–272.
Mintzberg, H, and F. Westley. (1992). Cycles of organizational change. Strategic Management Journal 13: 39–59.
Morgenson, F. P., and D. A. Hofmann. (1999). The structure and function of collective constructs: implications for multilevel research and theory development. Academy of Management Review 24: 249–275.
Murray-Webster, R., and M. Thiry. (2000). Managing programmes of projects. In R. Turner and S. Simister (Eds.), Gower Handbook of Project Management,3rd edition (pp. 47–64) Aldershot, UK: Gower Publishing.
Neal, R. A. (1995). Project definition: The soft systems approach. International Journal of Project Management 13 (1: 5–9.
Partington, D. (2000). Implementing strategy through programmes of projects. In Turner and Simister (Eds.), Gower Handbook of Project Management,3rd edition. Aldershot, UK: Gower Publishing.
Punch, K. F. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches.London: Sage Publications.
Project Management Institute Standards Committee. (1996). A Guide to the Project Management Body of Knowledge (PMBOK® Guide).Upper Darby, PA: Project Management Institute.
Quinn, J. J. (1996). The role of “good conversation” in strategic control. Journal of Management Studies 33 (3): 381–394. Oxford: Blackwell Publishers Ltd.
Reiss, G. (1996). Programme Management Demystified.Spon Press.
Rubin, H. J., and I. S. Rubin. (1995). Qualitative Interviewing: The Art of Hearing Data.Thousand Oaks, CA: Sage Publications.
Schein, E. H. (1988). Process Consultation: Its Role in Organization Development,vol. 1, 2nd ed. Reading, MA: Addison-Wesley.
Senge, P. M. (1990). The Fifth Discipline—The Art and Practice of The Learning Organization.New York: Currency Doubleday.
Spradlin, T. (1997). A Lexicon of Decision Making. Decision Analysis Society Website. Accessed at http://faculty.fuqua.duke.edu/daweb/lexicon.htm.
Stake, R. E. (1975). Evaluating the Arts in Education. Columbus, OH: Merrill.
Thiry, M. (1996a). Value Analysis Techniques applied to Project Concept and Development. Value World,SAVE (Society of American Value Engineers) XX.
———. (1996b). Added-value project management. Proceedings of the IPMA (International Project Management Association) Congress in Paris.
———. (1996c). Value: THE integration concept. Proceedings of the 1996 PMI Seminars and Symposium.
———. (1997). Value Management Practice.Newtown Square, PA: Project Management Institute.
———. (1998). Decision-making in projects: An integrated framework. Proceedings of the Project-World Conference (London, June 1998) and PMI-Europe Conference (Munich, July 1998).
———. (1999). Would you tell me please which way I ought to go from here? Is change a threat or an opportunity? Proceedings of the 30th PMI Seminars and Symposium.
———. (2000a). The emergent organisation. Proceedings of the 3rd PMI Europe Conference in Jerusalem.
———. (2000b). A learning loop for successful program management. Proceedings of the 31st PMI Seminars and Symposium.
———. (2000c). Successfully integrating value and project management into a complete strategic decision making–implementing cycle. Proceedings of the International Business and Corporate Strategy and Planning Congress in Amsterdam.
———. (2001). Sensemaking in value management practice. International Journal of Project Management.Oxford: Elseveir Science.
———. (2002a). Combining value and project management into an effective programme management model. International Journal of Project Management.Oxford: Elseveir Science and (2001) Proceedings of the 4th Annual PMI-Europe Conference in London.
———. (2002b). For DAD: A program management life-cycle process. Proceedings of the 5th Annual PMI-Europe Conference in Cannes.
Thomas, J., C. Delisle, K. Jugdev, and P. Buckle, P. (2000). Selling project management to senior executives: What’s the hook? Project Management Institute 1st Research Conference Proceedings.Drexel Hill, PA: PMI Communications.
Tsuchiya, S. (1997). Simulation/Gaming, an effective tool for project management. Project Management Institute 28th Annual Seminars and Symposium Proceedings. Drexel Hill, PA: PMI Communications.
Vennix, J. A. M. (1996). Group Model Building, Facilitating Team Learning Using System Dynamics.Chichester, West Sussex: John Wiley & Sons Ltd.
von Neuman, J., and O. Morgenstern. (1944). Theory of Games and Economic Behavior.Princeton, NJ: Princeton University Press.
Vroom , V. H., and P. Yetton P. (1973). Leadership and Decision-Making. Pittsburgh, PA: University of Pittsburgh Press.
Waring, A. (1989). Systems Methods for Managers: A Practical Guide.Oxford: Blackwell Scientific.
Wijen, G., and R. Kor. (2000). Managing Unique Assignments. Gower Publishing.
Winch, G., A. Usmani, and A. Edkins. (1998). Towards total project quality: A gap analysis approach. Construction Management and Economics 16: 193–207.
Weick. K. E. (1995). Sensemaking in Organizations. London: Sage Publications.
Proceedings of PMI Research Conference 2002