Introduction
In the last decade, the world we had taken for granted has been shattered. More and more, organizations have to deal with a complex, turbulent environment. Misunderstanding of this environment has been the downfall of many projects, programs, and organizations in recent years because for as much as we have learned to deal with uncertainty and have developed the tools and techniques to do it, we do not understand how to deal with ambiguity.
The traditional project space is fraught with uncertainty, and project managers are well equipped to deal with it; but complex, turbulent environments are the domain of ambiguity. Ambiguity is not to be confused with uncertainty. Uncertainty concerns what is not clearly or precisely determined—what is not certain to occur, while ambiguity concerns the things that may have more than one meaning—things that can be understood in two or more possible ways.
Complex and turbulent environments generate ambiguity through the increased number of stakeholders, the quick evolution of technology, the changing markets, and a number of other factors that create interactions that can often not be predicted. This is what project managers, and managers in general, have been ill equipped to deal with.
This presentation will first examine how the current business environment fosters ambiguity and how ambiguity is different from uncertainty. It will show how organizations in general, and project-based organizations in particular, need to recognize ambiguous situations and how they can deal with them. Finally, it will show how individual project, program, portfolio, and project management office (PMO) managers can adapt their decision-making, behavior and management methods to each of the four uncertainty-ambiguity areas.
Uncertainty and Ambiguity
Uncertainty is associated with change; as the pace of change increases, uncertainty increases proportionally; the more turbulent the environment, the greater the uncertainty. Typically, ongoing operation or business as usual (BAU) generates little or no uncertainty whereas change has high uncertainty (see Exhibit 1).
Ongoing operations are repetitive and information is accurate because it is based on proven historical data that is unlikely to change; information is also readily available and generally comprehensive. On the other hand, when the pace of change increases, information may not be available in time and is often incomplete and inaccurate which creates a need for estimation. Estimation is a prediction; it is based on appraisal factors that are agreed, but can change, and approximation of outcomes, which is based on assumptions. Planning supported with breakdown structures, network diagrams, cost estimating and risk management help us reduce uncertainty in projects.
Exhibit 1. Uncertainty relationship with business portfolio of actions
Ambiguity is related to the number of choices you have when making decisions, the more complex the environment, the more there are possible interactions and the more choices are available. At technical level, it is usually possible to make rational decisions because although technical options may make the decision complicated, there are just so many possible combinations and typically, the decision makers can rely on accurate data. At the tactical level, decisions often concern processes, and there are more complexity and possible interactions that can complicate choices. Decision makers have to rely on a mix of rational and intuitive decision tools and often rely on group decisions to gain better information and buy-in to the decision.
When reaching the strategic level, complexity increases a lot because multiple interactors come into the equation, which multiplies the possible choices and often generates conflicting information. Information is often high level and cannot be evaluated accurately; subjective values are important and intuitive decision making is often the way forward. This is not something new. Mintzberg (1990) and others demonstrated that strategic managers make most of their decisions based on intuition. When complexity is reduced, rational decision making can be used because choices are more limited and cause-effect relationship can be more clearly identified, but when complexity is high, managers have to rely on intuitive decision making and accept that they may need to review their decisions as the situation evolves.
Exhibit 2. Relationship between ambiguity and business decision making
When compared over time, during a change process, for example, uncertainty and ambiguity behave in very different ways (see Exhibit 3).
Uncertainty is linear; it is high at the beginning of a change (project or program) when there is little accurate data available and the team has to make assumptions, and estimates. As the change process progresses and accurate data becomes available, uncertainty diminishes to the point where, at the end, there is no more uncertainty. Typically, project managers are well equipped to deal with uncertainty.
On the other hand, ambiguity is linked to complexity, the more choices, the higher the ambiguity. In a change process, ambiguity is cyclic; it will diminish every time decisions are made and will rise again as new issues appear and decisions have to be made to resolve them. Project managers are ill-equipped to deal with ambiguity because they are traditionally asked to make rational decisions and to focus on performance. Ambiguity requires intuitive decision making and a focus on learning (sensemaking).
Exhibit 3. Uncertainty and ambiguity variation over time
The Relationship Between Uncertainty and Ambiguity
We have now seen that uncertainty is linked to a lack of accurate information and can be resolved with rational decision making whereas ambiguity is the product of complexity, which increases the potential choices and can only be resolved with value-based decision making. We will now examine how the combination of uncertainty and ambiguity affects the behavior of the decision makers.
Many scholars have studied the relationship between uncertainty and ambiguity. In 1980, Earl and Hopwood studied the management of information systems and developed a model of IS decision-making approaches in different situations (see Exhibit 4).
Exhibit 4. Choice of approach to decision making (Adapted from Earl & Hopwood, 1980)
They contend that in a low uncertainty and low ambiguity (LU-LA) situation decision making should be rational and analytical whereas in a high uncertainty high ambiguity (HU-HA) situation decision making is subjective (based on the decision makers’ values) and inspirational. In a low uncertainty and high ambiguity (LU-HA) situation, where information is clear and available, but there is disagreement over objectives, negotiation and compromise are the way forward. This is a situation where there is often a display of political or power tactics. Finally, in a high uncertainty low ambiguity (HU-LA) situation, typical of clearly scoped projects, opinion, based on subject expertise, and assumption, based on risk management and estimating, are the way forward.
Similarly, in the early nineties, Mintzberg (1990) developed a model for strategic decisions under uncertainty (Exhibit 5) where he used complexity and rate of change as the two axes. I have shown earlier that complexity breeds ambiguity and a fast pace of change breeds uncertainty. In his study, Mintzberg explained that in a low complexity and slow rate of change (LU-LA), rational decision models can be used whereas when the rate of change is fast and complexity is high (HU-HA), rational decision models are not valid because data is not reliable and the situation changes too quickly. In a project environment, the rational model is typical of operational work or improvement projects where there is time to formulate decisions, plan and communicate them to the implementers. In complex fast paced environments, Mintzberg suggested the use of a radical model, which consists of doing what you can until the situation settles down. In the radical model, decisions are made without the capability to fully understand their consequences because complexity is too high. The situation requires an iterative process where knowledge and understanding are gained in retrospect and decisions are revised accordingly. This is typical of the sensemaking/decision aspect of agile management, at project level, and program/value management at strategic level.
Exhibit 5. Decisions under uncertainty (Adapted from Mintzberg, 1990)
When complexity is low, but the rate of change is high, the main pressure is time to deliver. Because the environment is not complex, you can easily see what the right decision is and implement it right away. In such a case, the formulator is also the implementer. This is typically the case for well-defined projects and programs where time, and often cost, are of the essence, and where the A Guide to the Project Management Body of Knowledge PMBOK® Guide—Second Edition (Project Management Institute [PMI], 2008) is the best management process. If you are in an environment that is stable, but complex, the situation requires expertise and negotiation to be able to choose the right path; this is a case where continuous interaction is required between implementers and formulators to make the right decisions. It is typical of a budget allocation situation or of portfolio management, where operational and project players submit demands to be selected by senior managers.
These two models are, in fact, saying very similar things and can be used to understand that relationship between decision-making behaviors and situation that occur in project organizations. I will now demonstrate how they can be related to, and used in, different organizational situations.
The Project Organization Space
Organizations are not consistent environment; in fact, different parts of the organization can display different levels of uncertainty and ambiguity at different times. Different combinations of uncertainty and ambiguity will require different management behaviors and decision approaches, or even organizational structures. However, many managers do not distinguish between uncertainty and ambiguity and will often display the wrong behavior at the wrong time. For example using rational decision making tools when information is not available or making a knee-jerk decision when they had enough time to analyze the situation.
I will use the “Eco-Cycle” model developed by Hurst (1995) (Exhibit 6) to show how organizations can be subjected to different levels of uncertainty and ambiguity in different contexts. I will then combine all the models together to show how a project organization can be subjected to different combinations of uncertainty and ambiguity and what kind of behavior managers should display in each situation. Hurst looked at the way behavior changes in organizations at different stages of its evolution. He assumed that organizations regularly go through crisis situations and that managers aim to reinstate a state of stability that is characterized by a conservation approach and represented it as an infinity loop.
Hurst’s model represents different organizational states or conditions that could occur over time, as the firm evolves, or simultaneously at different levels or in different areas of the firm and are based on actions (activities) that managers will undertake under these different circumstances. They specifically outline context and behavior as two main structuring points of management actions.
Exhibit 6. Adapted Hurst's eco-cycle (1995, p.103)
In this paper, I have deliberately omitted the constrained actions from Hurst’s eco-cycle since constrained actions more specifically concern the area of crisis management and stable conditions that do not directly concern project organizations and conscious decision making.
I will assume that the journey starts with a crisis that breeds confusion following this reasoning:
– Leadership behavior is typical of a low uncertainty and high ambiguity (LU-HA) domain; because turbulence is low, data is generally available in time to make a decision. It is the area where managers manage “the organization’s ability to change […] rather than change itself’ (Hurst, 1995, p.136). In this highly political area of ongoing conversations, “leadership […] develops loosely connected creative networks from which new activities can emerge” (p.104). This is typical behavior of portfolio management and governance activities.
– Creative networking behavior is representative of an area where both uncertainty and ambiguity are high (HA-HU). Decisions have to be made on a regular basis without the access to reliable data, which requires a sense-making and value-based approach. It is an area where “groups of individuals will begin to gel around a variety of opportunities and projects and start to take entrepreneurial action” (Hurst, 1995, p. 114). This behavior is congruent with business strategy, value management, and program management.
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• Once a choice has been confirmed on a course of action:
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– Entrepreneurship behavior is likely to be observed in a high uncertainty and low ambiguity (HU-LA) (clear scope and parameters) setting where requirements revolve around risk analysis and problem-solving. In this context, “more regular pattern of interactions begin to emerge as the contacts and events become linked into coherent flows and better articulated routines.” (Hurst, 1995, p.114). It is consistent with projects and innovation activities.
– Management behavior is the typical approach in low uncertainty and low ambiguity (LU-LA) area, where the purpose is to “restrict activities to those that have proved to work [and where] considerable effort and capital will be invested in describing these activities and embedding them in technology and formal organizational procedures to perpetuate their performance.” (Hurst, 1995, p.104). It is characteristic of operations (maintenance, updating and incremental improvements).
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• Following this, the goal of management will be to “conserve” the status quo and maintain the same situation until the next crisis hits. This is again a situation imposed by the environment.
If we combine the three models shown in Exhibits 4 through 6 and apply them to a project-based organization, we could say that low uncertainty (LU - slow rate of change) is typical of ongoing processes, whereas high uncertainty (HU) is typical of change processes like projects and programs. On the other hand, high ambiguity (HA -Disagreement over objectives) is typical of decision-making situations, whereas low ambiguity (LA) is typical of execution processes, where objectives have been agreed and need to be delivered. In Exhibit 7, I have shown that low uncertainty and low ambiguity (LU-LA) are the domain of operations management, an ongoing decision-free environment; low uncertainty and high ambiguity (LU-HA) are the domain of portfolio management, which is an ongoing process where information is available but offers many possible choices; high uncertainty and high ambiguity (HU-HA) is a situation where value management (agile and program approaches) is the best methodology to resolve difficult choices with little available data; and finally high uncertainty and low ambiguity (HU-LA), when objectives have been well defined and successful execution is subjected to the availability of data is the domain of project management.
In Exhibit 7, the lower left-hand corner (LU-LA) shows that managers use analytical decision-making processes typical of general management; this is the domain of business-as-usual (BAU) and day-to-day operations. The lower right-hand corner (HU-LA) indicates the need for an assumption approach, in which planning, estimating and risk management are the methods of choice, and behavior is entrepreneurial like in project management. In this case, the objectives have been agreed and decisions concern mostly the execution processes. The top left-hand corner (LU-HA) displays a need to negotiate and exercise leadership; this is typical of a decision-making process where information is known, data is available and accurate, but there is disagreement over objectives. Negotiation between players and leadership to achieve choices are the behaviors displayed by managers in those situations. Portfolio management, where multiple projects and programs have to be selected against diverse, often divergent, objectives and set budgets is typical of this situation. Finally, the upper right-hand corner (HU-HA) represents a situation that is at the same time complex and turbulent, preventing rational decision making and pre-planned change. Value management through sense making and networking is probably the best approach in such a situation. Value management can be considered as the initial step of program management where the program is not clearly defined from the start or subject to change; it is also the type of approach required in agile management where the whole team needs to make decisions iteratively as the situation evolves.
Exhibit 7. Ambiguity-uncertainty relationship in project organizations (POs)
Exhibit 7 also illustrates the fact that, in considering uncertainty management at the exclusion of ambiguity, project management is doomed to remain a strictly executing process. More and more project managers are assuming a decision and business role; through this demonstration, I hope to have shown that, in order to succeed, they need to consider both uncertainty and ambiguity. In doing so, we will influence our project organization space and demonstrate that, when considered as a holistic approach, project management can be an organizational capability, not just a change execution process.
In the next section, I will examine how the current organizational context has created a need for project organizations to become more dynamic and use both uncertainty and ambiguity reduction methods to succeed.
Complexity and Turbulence
Anshoff (1979) was the first to use “turbulence” in the organizational context; he referred to it as the pace and nature of external change that a firm is subjected to. Bourgeois and Eisenhardt (1988), stated that these are contexts in which “information is often inaccurate, unavailable, or obsolete” (p. 816). Any change, and turbulence in particular, breeds uncertainty, which is the state of things that are not clearly or precisely determined, subject to change, dependent on chance or unpredictable factors. Karl Weick (1979), the well-known management author, links uncertainty to a lack of information or the ratio of assumptions versus facts: the higher this ratio, the greater the uncertainty. In a turbulent environment because accurate information is more difficult to obtain, uncertainty is typically higher.
Complexity as an aspect of organization theory has its roots in the study of ecosystems; it is a feature of complex adaptive systems (CAS) or, more specifically, non-linear processes. Organizational theorists associate organizational complexity to:
– multiple perspectives or approaches (Burrell & Morgan, 1979; Martin, 1992);
– the fact that organizational decisions are highly interdependent (Siggelkow & Rivkin, 2005); or
– “the number and diversity of the elements in an environment” (Hatch, 1997, p. 89).
Complex environments breed ambiguity, which refers to things that are open to or have several possible meanings or interpretations. Ambiguity is based on the ratio of expectations (undefined requirements) versus defined requirements, which requires clarification, high interdependency or conflicting aims, which require clarification and negotiation. Ambiguity-reduction is directly linked to the capability to make decisions. In a complex environment, a demand for additional information, which, in a simple environment would lead to a better understanding of the problem, could lead to added complexity by confusing the issue and making it more ambiguous (Weick, 1979). Therefore, methods that are typically used to reduce uncertainty like work breakdown structure, planning, and risk analysis cannot be used to reduce ambiguity.
Siggelkow and Rivkin (2005) defined three specific contexts for firms operating in turbulent and complex environments:
- Turbulence, in which “firms need designs that allow them to improve performance speedily to attain a decent outcome before conditions change” (p.102), which is typical of project management.
- Complexity, in which “firms need designs that permit them to search a diverse array of operational configurations before locking in on a set of choices” (p.102), which is typical of portfolio management.
- Combined turbulence and complexity, in which firms must balance speed and search, which is typical of program management.
These three organizational contexts are also typical of project-based organizations. In fact, in a study on “The Role of Human Resource Management in Project-oriented Organizations,” Huemann, Turner, and Keegan (2004) confirmed that the environment in a project-based organization is more dynamic and discontinuous.
Because the essence of projects is to manage change, project organizations (PO), which conduct a significant part of their activities as projects, are turbulent environments except in very specific circumstances where either the industry or the firm sits in a very stable context or manages only a few large and long-term projects. POs are also complex because of the number of stakeholders involved and the number of projects with diverse or even conflicting objectives.
If, as explained previously, POs are both turbulent and complex, it is important to understand how the relationship between uncertainty and ambiguity affects management domains like projects, programs, portfolios, and operations. We need to look at the organization as a whole, not only in static function terms as in the previous section, but as a dynamic, synergetic concept. I will now aim to show how well integrated project-based organizations can become more agile and responsive by dealing effectively with both ambiguity and uncertainty.
Project Organizations in a Complex and Turbulent Environment
In alignment with Hurst’s (1995) and Porter’s (2004 [1985]) views, I argue that organizations are continually subjected to internal and external pressures to change and that therefore, they need to be based on an integrated, mutually reinforcing set of activities that form a coherent whole. An activity-based approach enables organizations to adapt to changing circumstances and respond to both turbulence and complexity as they use different types of activities to respond to different situations. In Exhibit 8, I modified Exhibit 7 to add the ongoing dimension of Hurst’s model. I have replaced Hurst’s “crisis” by “pressure to change” and “choice” by “decision to implement” to better reflect the PO environment.
Exhibit 8. Contextualization of the project organization
In Exhibit 8, I identified a simple high-level interaction in the form of arrows that represent a typical organizational cycle.
In the low uncertainty-low ambiguity area, internal demands to maintain or improve capabilities are generated by the operational areas of the business. These demands create ambiguity, and they are assessed against the corporate objectives and the current portfolio of actions. Other demands are triggered by external sources and typically conveyed by account managers, research and development or sales and marketing.
All these demands create confusion, and they must be analyzed against the organization’s investment portfolio. Finance and portfolio management activities are then defined to secure or increase the organization’s market share. This is an area of rational actions and learning behavior where decision makers have to understand issues involved with each alternative.
Once the big decisions have been made, they will be further assessed against increasing uncertainty as the context of the organization evolves. The objective, in this strategic area of the business is to positively differentiate it from its competitors through emergent actions and change. It is in this area of the business that value management is used to define stakeholders’ needs and expectations and to address them in the most resource effective manner. Because value management is a group-decision process based on individual and collective values, it is ideal to respond to the issues identified by Earl and Hopwood (1980), Mintzberg (1990), and Hurst (1995), as well as issues identified in agile and program management.
As decisions are made to respond to a complex environment, ambiguity is reduced and actions are broken down into low ambiguity-high uncertainty innovation activities that can be defined in terms of scope, quality, time, and cost. These activities focus on performance to produce tangible results that can be transformed into new capabilities only at operational level. As they become organizational capabilities, they will improve the organization’s ability to respond to external pressures and maintain its market position.
Such integrated project organizations would be highly agile and responsive, able to deal with both uncertainty and ambiguity, therefore maintaining their competitive advantage over long periods. However, to achieve this way, project management needs to be truly integrated with strategic and operational activities.
Conclusions
Political and competitive issues between the different associations put aside; project management standards, certifications and maturity models provide a good example of the current stance in project management literature and practice where project management is seen as independent from its context. Most practitioners focus on generic activities -“good practices on projects most of the time” (PMI, 2008, p.3) and the project management community in general adopts a control-driven approach to the management of project disciplines (project, program, portfolio & PMO). At the recent PMI Research Conference held in Washington, project management researchers Crawford and Cooke-Davies (2010) stated that:
Project management as a field of practice initially focused on the standalone project and on development of generic standards, largely ignoring context. […] Recognition of project management as an organizational capability has been a more recent development, but models and standards for organizational project management have been subject to a similar one size fits all approach.” (p.1) They further argue that: “The discourse of project management [.] developed and promulgated through standards, is good for professional formation but reinforces the insularity of practitioners and separation from the rest of the management community.” (p. 2)
The broadening of project management practice, paired with the added turbulence and complexity of the current business context, requires a better integration of project, program, and portfolio within the organization and synergy between them to create value.
I have clearly established that project practitioners in particular and the project community in general should be aware that by focusing only on performance and on the management of uncertainty, they will encourage project management to remain a method for executing change and never become a management capability.
Currently project managers are perceived as “doers,” incapable of making the “important” decisions. My suggestion is that a broader and more dynamic project approach would create synergy between project, portfolio, and program management as well as with operational activities and become an organizational capability.
This “project approach” would include learning methods like value management to deal with high ambiguity that is a characteristic of the executive levels of organizations. It would require an open view of project practice that goes beyond good execution and includes good decisions under different circumstances and a good business sense.
