Emergence and Emergents in Entrepreneurship: Complexity Science Insights into New Venture Creation

1 Emergence is a Process that Creates an Emergent Outcome

The process has become well known through research in the Prigogine tradition, including Nonaka (1988), Chiles et al. (2004), Plowman et al. (2007), and others. Based on these inductive process studies, complexity researchers are virtually agreed around the five key dynamics of emergence – the five sequential phases in the process (Lichtenstein 2014). These are described in #4 below.

The outcome of emergence is emergent order – an emergent. An emergent is the tangible expression of what’s been created, whether an organization, a new system/innovation, a collaboration or shared value; it is a new social agent. Examples of emergents include teams, projects, innovations, ventures, organizations, companies, alliances, social innovations, community initiatives, and some institutions. They are constantly organizing themselves (Tsoukas and Chia 2002; Weick 1979), and as such they remain discernable in their economic/social environment.

This distinction between the process of emergence and the outcome, an emergent, is not often made by researchers. Nor is it easy to discern the difference, for in our multi-layered social world the latter is often fully embedded in the former. Still, by attempting to bring more clarity to the process vs. the outcome, we may be able to better integrate each other’s work.

2 Emergence is Sparked by Agency – Generative Emergence is Intentional

All social entities – all emergents – are created through agency: entrepreneurs use intention, aspiration and personal passion to create their ventures/projects. Often they combine their agency with others, to expand the potentiality of the venture.

Although this seems obvious to entrepreneurship scholars, it is anathema to most complexity science researchers, who argue that emergence happens “naturally” when agents follow simple rules of interaction. In this sense new order will simply self-organize, without any added intent or drive by its agents (Kauffman 1993, 2000). Generative emergence takes the opposite view: emergence is intentional. Agency, even if distributed, is the source of successful organizing.

At the same time, having intention does not mean having control. As all entrepreneurs know, there is nothing predictable about entrepreneurial outcomes, especially because they are often non-linear. Instead of trying to control, successful entrepreneurs learn how to be flexible in their organizing, to improvise (Sawyer 2003; Garud and Karnøe 2000), innovate (Garud and Karnøe 2003), use effectuation (Sarasvathy 2001; Dew et al. 2011), and so on (Garud, Kumaraswamy, and Sambamurthy 2006; Mullins and Komisar 2009). Further, they operate with this flexibility so as to continuously adapt to the dynamic social world (Arteaga and Hyland 2013). In these ways, agency is central to emergence.

3 Emergence Increases the Capacity of the System

The emergent reflects a new way of organizing that dramatically increases the capacity – effectiveness, efficiency, quality – of the system (Corning 2003). Perhaps the most remarkable example of this capacity increase is Margulis’ (1971, 1981) research on symbiogenesis. Within a cell, an internal micro-structure (semi-autonomous organism) emerges and envelopes the local mitochondria into itself. As a result, the cell can produce 2000 times more metabolic energy than the “normal” cell without the emergent (Corning 2002). Another example is Prigogine’s dissipative structure: Hexagonal “cells” (vortexes) of molecules emerge that increase by “orders of magnitude” the capacity of the container to dissipate heat (Swenson 2000).

Emergence researchers have identified increased capacity in a variety of ways. Plowman et al. (2007) describe how re-emergence at the church yielded more services to the residents, more space for expanding the programs, and increased meals served. Smith and Gemmill (1991) do an algorithmic calculation of the enhanced capabilities of groups that self-organized. Nonaka (1988) shows how innovations can totally re-create the companies they originate in. Chiles, Meyer, and Hench (2004) identify six key growth indicators for the dramatic expansion of the Branson theater sector, as the area emerged and re-emerged over time.

Entrepreneurs intuitively understand increased capacity, because the success of a new venture depends on generating more value than the cost of producing it. A classic example is Adam Smith’s pin factory which, when organized, was able to produce 100 times more pins than individuals doing all the tasks themselves.

Perhaps increased capacity should be framed as a proposition, i.e. an assertion to be further tested. This is because entrepreneurs rarely know at the outset how increased capacity will be generated, so tracking its emergence is extremely difficult. Second, some outcomes of emergence generate intangible outcomes, e.g. expanding a company’s mission or goals, remaking the boundaries of a project, integrating new learning into the firm. These important outcomes may dramatically increase capacity but in ways that are very hard to measure. Still, the overall proposition argues that new order creation leads to very positive effects for the system.

4 Emergents Arise in Cycles of Emergence

The fourth insight/claim is that the process of emergence is a progression of five sequential phases or dynamics, which together lead to new order creation. This is a cycle of emergence. Those five phases reflect a specific logic that explains why and how emergence happens in social systems (Lichtenstein 2014).

The cycle is initiated when an entrepreneur starts to pursue an idea for value creation, which enacts or takes advantage of an opportunity. The entrepreneur’s organizing – this intense activity and innovation – pushes the system into a state of disequilibrium. As this intensity of disequilibrium organizing continues, in phase 2 of the cycle the system will generate stress, tensions and experiments. Stress becomes more widespread due to the inability of current routines and relationships to manage the increased levels of activity, as well as the pressure to figure out the innovation and get it on the market. This also leads to experiments: new ideas and structures that aim to solve the disjunctions of intensity. More importantly, any experiment can become the seed of the needed solution, the new framework for increasing overall capacity.

As these continue, in phase 3 the system can become amplified to a critical event. According to the logic of emergence, positive feedbacks within the system accumulate, whereby a single further event can push the system into an entirely new regime of organizing. After this tipping point the system will either reorganize with increased capacity, or fall apart, unable to find a sustaining state. This reorganization is captured in phase 4, new order through re-combinations. Here, the newly organized entity is based on resources and capital that are already in the system, re-combined with new components; together these generate the next dynamic state of the entity. Alternatively, the critical event pushes the venture over the edge into failure, ending the organizing effort.

Finally, the cycle concludes with stabilizing feedback, whereby the system seeks to anchor the change, slow down the non-linear drivers, and find the parameters that maximize its efficiency and sustainability in the social ecology. The logic of emergence is oriented around the idea that ventures will remain in a dynamic state until the next opportunity tension arises, leading to a new round of disequilibrium organizing, and so on (Lichtenstein, 2014).

5 In New Venture Start-Ups (Using PSED Data), Process is More Important than Content in New Venture Creation

Another insight from complexity science is based on an analysis of longitudinal data from 1000+ entrepreneurs who were in the process of starting up their own companies – the PSED data ^[2] (Lichtenstein et al. 2007). We applied longstanding complexity hypotheses to examine these entrepreneurs’ organizing efforts, looking at the dynamics that distinguished those businesses that started up successfully vs. those that failed. It turned out that the key causal factor was not what these entrepreneurs did, but the pacing of their behaviors over time. That is, the activities of successful entrepreneurs were more evenly spaced, but with more activities occurring later rather than earlier in the process. This held true regardless of what the actual behaviors were, i.e. it didn’t matter whether they were writing a business plan, getting a phone number for the business, arranging child care, talking with clients, developing financials etc. Instead, their success was correlated to the pattern of entrepreneurial activity. This insight might be extremely beneficial to new ventures in start-up mode; these findings have not yet been tried in practice.

6 Emergence has Power Law Outcomes

A final insight from complexity science to entrepreneurship is stated by Crawford et al. (2015), in a study of the actual distributions of entrepreneurial factors and outcomes. The key question is whether these factors of entrepreneurship are normally distributed on a Gaussian curve, or if the data are better described through a Pareto curve, i.e. the 80/20 rule, where a small percentage of data is causing most of the effect in the overall system. The study mathematically analyzed 46 variables on resources, cognition, action and environments. Our findings showed that 95% of these common factors are not arrayed on a normal curve, but on a Pareto curve. That is, the assumption of normality is proven inaccurate for virtually all of these common variables; instead, the underlying distributions are explained through a power law.

These findings matters for at least two reasons. First, virtually all extant research in entrepreneurship and management is based on methods that assume the underlying distribution is normal, including all research using regression analysis, ANOVA, averages, etc. All of this research may be inaccurate due to missing key dynamics that exist in the margins of the system. Although the advice in many statistics classes is to carefully “throw out the outliers,” those so-called outliers are actually driving system outcomes.

A second key impact is best explained by how the Pareto curve’s 20/80 rule operates in society. For example, 80% of sales are made by 20% of salespeople; 80% of deposits are made by 20% of customers, 80% of calls are made by 20% of individuals. And as we now appreciate, 99% of the wealth is held by 1% of the people. As an entrepreneur, these findings mean that a very small portion of all activities or resources may have a disproportionate effect in the outcomes. Although it may be impossible to know ahead of time which activities have the most leverage, the entire framework may offer unique innovations into entrepreneurial organizing and action.

7 Discussion

How do these insights change how we think about entrepreneurship and entrepreneurial behavior? To begin, they derive from a broad framework that contrasts with the linear, economics-based explanation of new business growth. The emergence\emergents framework assumes a highly dynamic world of social agents. Agents are constantly organizing themselves and continuously learning and adapting; new agents emerge and re-emerge over time. Emergence is driven by entrepreneurial behavior: someone sees a potential, an opportunity, a chance to generate value, and they put their passionate agency into making it real in the world. Ultimately the goal of our entrepreneurial behavior is to generate emergence, by creating new value, solving a problem, capitalizing on an opportunity, improving a situation, generating more capacity. Emergence, rather than competition and profits, is really the driver of economic activity.

For those engaging in entrepreneurship, this view of the world also offers insight into how an emergent is generated, namely through a cycle of emergence – the five dynamics described above. Thus, agency and organizing can be directed in ways that parallel the cycle, starting with the initial drive the entrepreneur pursues, and continuing through the other four phases in turn. The outcome would be the creation of a new emergent, which brings higher capacity. This proposed methodology is ripe for application.

These insights also offer suggestions to entrepreneurs in the start-up mode. If success is more dependent on the temporal pattern of activities, as compared to what activity the entrepreneur does, the focus of start-up organizing should incorporate a different kind of balance over time – namely, not doing too much too soon. Likewise, if outcomes accrue according to a power law, entrepreneurs might be able to identify and leverage a few key elements of their efforts, which could have a non-linear effect in the system.

My hope is that these ideas can support entrepreneurial scholars and practicing entrepreneurs, to help understand and generate the emergence of new ventures, new projects, new collaborations, and new social entities.