Eight to Late

Introduction

The lack of a clear definition of project complexity has lead to much confusion amongst project management academics and practitioners regarding what makes a project complex to manage. A recent paper by Harvey Maylor, Richard Vidgen and Stephen Carver, entitled Managerial Complexity in Project-Based Operations: A Grounded Model and Its Implications for Practice, is a step towards changing this situation. In the paper Maylor and his co-workers  present a qualitative empirical model which captures both structural (static) and dynamic¹ elements of  managerial complexity in projects. I summarise and review the paper below.

Background and Objectives

The authors make the observation that project management methodologies (as codified in the various “bodies of knowledge”) contain what is deemed as accepted practice rather than best practice.  The point being that there is never any proof offered that the practice in question is indeed the best, or even better than others. Such proof is impossible because methodologies are highly prescriptive and  ignore context (i.e. the particular environment and quirks of individual projects).  This dogmatic, “our way is the best way” attitude is inconsistent with the diversity of situations and factors that make projects hard to manage. Hence the need to develop a understanding of what makes a project complex.

It may thus be helpful to consider projects as complex adaptive systems. As a first step, the authors discuss various characterstics of such systems, in particular those that might apply to projects. I have covered much of this material in an earlier post, so my coverage here will be brief. The main points the authors make are as follows:

1. The components of a complex system interact and produce outcomes that are unpredictable and nonlinear.
2. One cannot understand a complex system by studying the individual components that comprise it.
3. A complex system displays path dependence (i.e. dependence on history) and sensitivity to initial conditions.
4. Adaptive systems can change and “learn” from experience.

There have been several models of project complexity proposed by researchers. Each of these propose various dimensions (or factors) that capture complexity. Some of these factors are:

1. The number of physical elements of a project and their interdependencies. (Baccarini)
2. Organisational, technical and resource complexity.
3. Organisational and technical complexity, and structural and dynamic interactions between the two. (Xia and Lee)

Although earlier models have been useful, organisations have found that other factors (unaccounted for in existing models) contribute to managerial complexity in projects. With this in mind, the authors’ aim to develop a comprehensive empirical model of managerial complexity in projects and thus answer the question: What makes a project complex to manage?

The Model

The  model  was developed through workshops that involved a large number of practising project managers. I will not go into details of research methodology here; please see the original paper for details.  What is important to note is that the model includes input from a broad range of practitioners. With that said, I’ll move straight on to a description of the model.

The model describes both structural and dynamic elements of managerial complexity. The authors find that structural complexity in projects comprises of the following broad dimensions: Mission,  Organisation, Delivery, Stakeholders and Team. Following a distinctly academic penchant for acronymisation (to coin a term), the authors call their model MODeST, taking the first letter or two from each of the above dimensions.

The hierarchy below lists each of the above dimensions along with their sub-dimensions. Further, the lowest level of the hierarchy (sub-dimension level) lists representative questions that can be used to characterise each sub-dimension.  (Note: Please see the paper for full details).

• Mission
  • Objectives
    • Is there a clear vision?
    • Are the goals clear?
  • Scale
    • Long timescale?
    • Large number of resources?
  • Uncertainty
    • Are there interdependencies with other projects?
    • Are there interdependencies within the project?
    • Does it involve new technology?
    • Has the project been done before?
  • Constraints
    • Are there legislative or compliance constraints?
• Organisation
  • Time
    • Are there multiple timezones?
  • Space
    • Are team members colocated?
    • Is there face-to-face communication between team members?
  • Geography
    • Are there multiple languages?
  • Project / organisation fit
    • Is there a mismatch between project team structure and organisational structure?
  • Organisational change
    • Does the project involve organisational restructuring?
• Delivery
  • Administration
    • Is project reporting accurate, adequate and does information get to people who need it?
    • Is project data collection accurate, true and complete.
  • Decision Making
    • Is there effective governance of project decision making?
    • Are too many levels of management involved in decision making?
  • Change management
    • Is the change management process cost effective?
    • Is it flexible?
  • Project processes
    • Are project processes defined, standardised but not overly bureaucratic?
    • Is there a clear responsibility for tasks and deliverables?
  • Project management methodology
    • Is there a common methodology used throughout the project?
  • Resources – Human
    • Are human resources shared across projects?
    • Who controls human resources for the project?
    • Does the project manager have control over resource selection?
  • Resources –  Technology
    • Does the project have tool support?
  • Resources – Financial
    • How flexible is the project budget?
• Stakeholders
  • Stakeholder Identification
    • How many stakeholders are there?
    • Are there any unidentified stakeholders?
  • Support for project
    • Do stakeholder groups interfere with the project?
    • Do stakeholders have sufficient time for the project?
    • Do they respond to project needs in a timely manner?
  • Relationship basis
    • Is the relationship between the project and stakeholders contractual?
  • Experience
    • Do the stakeholders have realistic expectations of the project?
    • Do they have domain experience?
    • Do they have project management experience?
  • Power
    • Do the stakeholders have power to make decisions.
  • Key stakeholders
    • Is there senior management support?
  • Sociopolitical
    • Are there hidden agendas or unsurfaced assumptions?
    • Do stakeholders have conflicting priorities?
    • Are there any conflicts between requirements of different stakeholders?
  • Interdependencies
    • Are there interdependencies between stakeholders? (e.g. between suppliers)
• Team
  • Project staff
    • Do team members have sufficient prior experience?
      Does the project involve multiple technical disciplines and languages?
    • Are the team members knowledgeable and competent in all aspects of the project (business, technical and project management)?
    • Are the team members motivated?
  • Project manager
    • Is the project manager an effective communicator?
    • Does the project manager have authority?
  • Group
    • Are there cultural differences between team members?
    • Are there personality clashes or is there any rivalry within the team?
    • Does the team have a shared vision for the project?

The above dimensions and sub-dimensions characterise the structure of managerial complexity in projects. However, that isn’t all: the authors mention that many workshop respondents emphasised that elements (i.e dimensions) that make up the model interact thereby “multiplying” managerial complexity. This is one aspect of dynamic complexity. The authors also note that interactions can occur within a single element – for example, within interdependencies between suppliers and stakeholders. Analysis of the data showed that there is a dynamic element corresponding to every structural element of the model. Further still, dynamics of an individual structural element can be affected by interactions with other structural and dynamic elements. That is, the dynamics of one part of the system can be altered by other changes in other parts. The model thus captures structural, dynamic and interactive aspects of managerial complexity in projects.

The authors report that workshop participants also recognised their own role in adding to managerial complexity. For example, a project manager who fails to recognise task dependencies in early stages of a project contributes to complexity down the line. Project managers are thus, ” key actors embedded within the conceptualisation of the complexity of their projects rather than external observers.” The authors suggest that this indicates that many elements of managerial complexity can in fact be tamed by proper management. That, arguably, is what a project manager’s job is all about.

Implications and Discussion

The authors observe that projects are ubiquitous within organisations. Yet, current project management practices as codified in well-known methodologies fail to account for variations in context between projects. Managerial complexity varies with (and is defined by) a particular project’s context – for instance, a project may have several stakeholders with conflicting requirements whereas another may have only one stakeholder. The model developed by the authors describes managerial complexity using five dimensions and several sub-dimensions. These structural elements can change in time and also interact with each other, so the model is also capable of describing dynamic complexity in projects.

To illustrate expand on the last point of the previous paragraph, consider stakeholders – the “S” in the MoDest acronym. The authors point out that, “from an organisational theory perspective, a project can be seen as being constituted from the entire set of relationships it has with itself and with its stakeholders.” Project managers need to understand not only the power and legitimacy of each of the stakeholders, but also the relationships or interactions between them.  Moreover, the relationships between stakeholders evolve in time – i.e they are dynamic. Similarly, the other four dimensions of the model also display dynamic behaviour.

This dynamic behaviour is merely a restatement of the obvious:  in projects things change, sometimes rather quickly and unexpectedly. Standard project management practice offers techniques such as risk management, configuration management and change control to manage these. However, the authors suggest their data shows that,  “the nature of change considered by existing approaches is limited and that such programmatic responses may be inappropriate.” They go on to state, “Such dissatisfaction with traditional requirements engineering and command-and-control project management strategies has lead to an interest in agile project management approaches.” These statements will ring true for  those who have been burned by  the limitations of traditional project management methodologies.  Agile techniques embrace change; traditional methodologies seek to control it (and do so unsuccessfully, one might add).  The implicit acceptance of change in agile methodologies make it consistent with the dynamic model of managerial complexity proposed by the authors.

Conclusion

The paper describes an empirical model of managerial complexity in projects. From my (admittedly incomplete) reading of the literature, the model is more comprehensive than those that have been proposed heretofore. Further, it captures structural, dynamic and interactive aspects of elements that make a project complex and hard to manage. The model challenges current practice as embodied in traditional, “big-bang” approaches to running projects, but is consistent with Iterative/Incremental methodologies which form the basis of agile techniques.

The authors end with a brief description of some areas for further research. Some of these include:

• Refining the dimensions of complexity and finding the key drivers of each.
• Determining whether compexity can be quantified.
• Exploring the possibility of managing complexity.

We are still a long way off answering these questions, and thus developing a quantitative, controllable understanding of project complexity. Yet, the model presented provides at least a partial answer to the question: What makes a project complex to manage?

References:

Maylor, Harvey.,  Vidgen, Richard, & Carver, Stephen., Managerial Complexity in Project-Based Operations: A Grounded Model and Its Implications for Practice, Project Management Journal, 39 (Supplement), S15-S26. (2008).

Footnotes:

¹ See this post for more on structural and dynamic complexity.