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The Need for Actor and Strategy Models

1.1 Actors and Decision-Making

Actors matter for decision-making. Realizing organizational goals and objectives, successfully implementing a large project, or achieving policy impact is only possible with the support of others. Decision-makers cannot pretend to operate in a command and control environment where their decisions are readily agreed to and taken forward by others. Governments and businesses alike need to navigate and manage their network environment (De Bruijn & Ten Heuvelhof, 2008). A fundamental part of this is knowing who the important actors are, how to activate partners and accommodate critics, when to adapt to your network environment, and when to try to influence it (Van Schendelen, 2005). Moreover, mapping the actors in a network that could offer support in case of different uncertain developments is key for adaptive management, enabling decision-makers to quickly change gears in response to emerging challenges and opportunities.

For a long time, rational planning was considered part of one realm, and understanding networks and social decision processes part of another. In one realm, decision analysts, policy analysts, economists, and engineers would support decision-makers to find smart, efficient, optimal, or robust alternatives that combine multiple objectives, taking into account various types of uncertainties. In another realm, social scientists, organizational scientist, political scientists, and the like would focus on the processes, people, and politics involved, pointing out fundamental drivers and associated dilemmas inherent in multi-actor decision-making. One only needs to think of the writings and influence of Machiavelli about power and politics in decision-making in the early sixteenth century to recognize the importance of this tradition.

These two realms offer useful pillars or poles on a continuum because there are also many fruitful crossovers that combine insights from both realms into new approaches. These approaches have grown in number and maturity in the past few decades. A very visible result is the use of methods and techniques traditionally used more in systems science and engineering to analyze the political and social processes of decision-making. Examples are game theory, social network analysis, and cognitive mapping (Hermans, 2005; Hermans & Thissen, 2009). These approaches represent multi-actor decision-making processes, for instance as games, transactions, debates, or information flows in networks. Essentially, they all use models to capture and explain important features of the actor interactions that drive multi-actor decision-making. Therefore, we refer to these approaches as actor and strategy models.

1.2 Applications of Actor and Strategy Models

The importance of, and interest in, actor and strategy models has grown over the past years. It is now widely recognized that decision-makers cannot be effective if they do not manage their actor environment. These actor environments themselves are undeniably complex. Decisions are made and implemented in decision arenas that lack clearly defined boundaries and participants. Multiple decision arenas are linked, across sectors and across multiple levels of governance. Local decisions and global networks are linked through social media and geopolitics, through globalized production networks and value chains, and for instance local cities are seen as key responders for shared global challenges (Barber, 2013). There are numerous cross-sectoral, interconnected, and hybrid networks of organizations in various forms-public, private, firms, and foundations-and information and capital readily flows across national and regulatory boundaries (Castells, 2010). Moreover, the networks and decision arenas are constantly changing, both within and outside organizations (Freeman, 2010).

As connections among people, organizations, and countries continue to grow and as traditional boundaries among groups, sectors, and segments continue to be redefined, the need for a proper understanding of the actor dimension continues to grow in importance. Actor and strategy models help to gain such understanding. Examples of past applications give an impression of the benefits to be gained from their use.

1.2.1 Flood Protection

The Houston Galveston Bay Area in Texas is highly prone to hurricane-induced disaster. The area has seen a longstanding debate about ways to improve flood protection, and around 2014, this debate was growing increasingly sour. Scientists could not offer a way out because the key experts and research institutes also appeared to be diametrically opposed in their positions. The debate had become so intense and bitter that a productive communication between the two opposing sides was virtually impossible. A process structured around actor models was used to organize a workshop where stakeholders from across the divide jointly explored the complexity of the problems as well as pathways for alternative solutions. The workshop did not deny the irreconcilable differences between actor groups, but still enabled actors to eliminate outcomes that would be bad for all and rather focus on future scenarios with potential wins for at least one of the groups. Two weeks after the workshop, a platform for joint action was formed and the workshop was widely acknowledged as an important contributing factor (Cunningham et al., 2015).

1.2.2 Internet Innovations

In the early days of Internet video services, the late 1990s and early 2000s, Dutch actors played a key role as pioneers. By 2013, the market was dominated by US-based firms such as YouTube, Google, Apple, and Netflix. How could this happen? A social network analysis of the relations among the Dutch key actors over time provided important insights. It showed that the early innovations of the pioneers in Internet video services in the Netherlands were financially supported by the government. However, this financial support stopped when the innovation system was still in its formative phase and had not yet entered its growth phase. With hindsight, this was too early, and was an important reason why early pioneering Dutch actors could not retain their central position in this innovation network. This held important lessons for future Dutch innovation policies (Poel, 2013).

1.2.3 Enterprise Planning

Modern manufacturing companies spend a lot of time and resources to smoothen their workflows and planning processes, integrating various decision support systems and procedures. However, it often turns out that actual integration of operations remains very difficult. Integrated and coupled enterprise planning and control systems cannot prevent continued hick-ups in planning, delays, and cost overruns. Actor models applied to different manufacturing companies showed how different units and departments in these companies, each with their own objectives and responsibilities, were still able to mess up production schedules. Production planners and operations units have to deal with units for product quality control, procurement, sales, and marketing. Their demands and sometimes strict procedures are not very efficient from a short-term operational perspective, but are sometimes critical for the longer-term success of the company. These insights could be used to improve the design of procedures and management information systems (Osorio, 2012).

1.2.4 Pollution Control

Environmental pollution of land, air, and water bodies often stems from various smaller sources that together have a significant impact. In the Netherlands, a group of policy makers from different organizations, levels, and sectors established a platform to reduce such diffuse pollution. As a first step to get going and achieve some early results, they had identified areas where they expected an easy start with some early successes. Among those was the use of chemical herbicides in maintaining public spaces: chemical substances used for weed control in public parks, streets, squares, and pavements. An actor model helped to clarify the different perceptions on this issue held by the key actors involved. This showed that, in practice, a reduction of use of these chemical herbicides might be more difficult than expected. The companies using herbicides and the government agencies that contracted their services were not convinced that good alternatives would be feasible or would be less damaging. This helped government organizations to update their expectations about the chances of easy and early results, but also showed them specific areas where further research and communication would need to focus on (Hermans, 2005).

1.2.5 More Examples of Applications

The use and usefulness of actor and strategy models is illustrated further in Table 1.1. The table shows examples where actor and strategy models have been applied and have made a difference for several cases in the past. Although the table shows many applications in the Netherlands, a bias due to the affiliations of the authors of this book, it also shows examples from various other parts of the world. These indicate that the use of actor and strategy models is not confined to any specific country or region.

Table 1.1 Applications of actor and strategy models