John Turley shares his thoughts on how complexity requires organisations to transform. He posits that building a collaborative culture is not enough. Rather organisations must leverage collaboration in order to innovative, survive and thrive in our changing world. Therefore understanding what defines an innovative culture, and how to build innovation into both working practice and the very fabric of the organisation is key.
Organisations are responding to increasing complexity by enabling greater collaboration across organisational boundaries. As a result, new, better ways of doing things emerge from the daily interactions between teams and customers. The role of management changes from one of coordinating and directing people in their activities to one of creating the conditions in which emergence can flourish.
Collaboration on its own, however, is likely to result in improvements to traditional elements of business success (e.g. operational capability), which are not enough. Leaders must instead carefully orchestrate both operational & dynamic capabilities that allow evolution and innovation over time. Only by balancing these two capabilities, which often conflict with each other, can organisations thrive in the long term, particularly in disrupted markets3.
For example, in an operational environment, it’s a good idea to measure key metrics, such as how long it takes for a support analyst to provide a first response to a problem logged by a user. This metric can be monitored, and action is taken if the amount of time exceeds some pre-agreed boundaries defined in an SLA.
This works because the actions that need to be taken by the support analyst can be easily understood in terms of cause & effect. There is no need for initiative or deviation from standards in an operational environment in which the focus is on increasing efficiency.
However, the application of such measurement and control systems in an environment in which innovation is valued creates a conflict, because it suppresses initiative, deviation from standards, and innovation.
There have been many recent developments in our understanding of the importance of networks of informal or social working relationships between people and the functioning of our organisations. Social working relationships, the implications of complexity, and the benefits of leveraging new technology give us an opportunity to tap innovative potential that is currently unrealised.
In today’s increasingly volatile, unpredictable, and ambiguous environment innovation must happen more quickly than ever before to ensure our relevance persists as consumer expectations heighten. Innovation that is focused around the people that will use new services and products underpins growth in this future landscape.
In order to avoid spending time and money developing products or services that customers don’t want by the time they are launched, innovation, like collaboration, must emerge from the interactions between teams and customers. It is, however, a more complex social process than collaboration. New ideas must be recognised & experimented with in small-scale prototypes, but in order to become truly disruptive, they must then be scaled into the operational core of the business6.
Such rapid, human centred innovation can only come from the people involved in the day-to-day activities of the business, rather than from within the management hierarchy that is too removed from the creation of value. By recognising this truth, leaders are then responsible for creating the conditions and empowerment for innovation to flourish.
Stable environments, in which most things that need to be known are known, or at least knowable, are predictable, so leaders can plan. The “predict and plan” management paradigm that has dominated the last hundred years is breaking down as a result of increasing complexity1. Managers find it harder to keep abreast of the pace of change or make sense of what is really happening, so their ability to coordinate people around specific objectives is compromised.
Yet without top-down management control, many fear chaos, so continue to organise in a way that suppresses innovation. Emergence, which is a key contribution of complexity to organisational science4, is the idea that value arises as a result of interactions between people, processes, and tools and offers an alternative to top-down management.
Emergence is the reason why the whole can be greater than the sum of the parts. We know, for example, that putting eleven talented footballers on a pitch doesn’t always result in a great team, but sometimes it does. The difference is not in the players themselves but in their interactions. Anyone who has watched a team fall apart during a game after playing well for long periods will recognise that the value is in the interactions of the players, not just the individuals.
The dynamic is no different in teams off the pitch, which is why the discourse around various types of agility (business, organisational, team) invariably talks about the need for teams to be self-organising. The people doing the work are best placed to know how it should be done.
The reason to call out emergence as the specific mechanism that leads to self-organisation is that for innovation to follow leaders need to create the conditions in which value emerges in a coordinated way across large parts of an organisation. This means recognising the importance of relationships as well as the capabilities of the individual, because, despite the myth of the heroic lone inventor, innovation is a social undertaking5.
Relationships, as well as capabilities, shape whether an individual can be a successful part of a team producing complex products and services in a complex environment. But for innovation to emerge we need to think beyond the individual and the team, (i.e. the individual's relationships) and look at the network of social relationships across the entire organisation.
Recent technological advances including collaborative platforms & data analysis tools have made this easier than it used to be. Organisational Network Analysis (ONA), pioneered by people like Rob Cross (Babson Business College & Connected Commons), is a technique that has been used to map social networks to uncover what is going on informally within organisations. The structure of these networks can be understood through the work of sociologists like Mark Granovetter and Ronald Burt.
In an ONA study recently undertaken in a part of a large public company it quickly became apparent that whilst IT teams were likely to be very good at solving problems quickly in the event of an incident, they were also less likely to be open to change.
This is because dense areas of the network (i.e. where each person in a group has a strong relationship with all of the other people in the group) are efficient in situations they have met before. People in dense networks tend to reinforce the status quo (this effect is known as homophily by sociologists) and therefore be less good at learning how to deal with new situations.
Managers later confirmed that their teams were good at responding to incidents, but that they were struggling to find better ways to work.
To increase the likelihood of new ideas emerging, becoming established in small-scale working proto-types before being scaled and launched (research shows innovation happens in stages2 - idea generation, idea elaboration, championing/amplifying & implementation/adoption) the structure of the social networks needed to change.
Ideas tend to be generated by individuals that span multiple networks, partly because being a member of different groups gives these ‘brokers’ a different perspective, but also because people who like to move between different groups tend to do so naturally. ONA can identify these people so that they can be encouraged to do play this valuable role more often.
These people are less effective at developing new ideas into working prototypes, however, because this activity requires a different set of social network connections. Once identified ideas are more effectively developed into working proto-types by people with dense networks, providing somebody with sufficient social capital can land the idea.
Once a small working prototype has been developed, ‘connectors’ need to champion the idea with leaders in the operational core of the business before they’ll adopt it. Connectors are people with large amounts of energy and social capital at a senior level of the operational business.
As organisations get older many of the characteristics that underpin innovation, such as willingness to experiment, decentralised decision making, and reward for solving problems, reduces. Some areas on the social network become more densely connected, and those ‘clusters’ become isolated from each other. Silo’s form. The structure of the social networks leans toward operational efficiency and away from the dynamic capabilities needed to unlock emergent innovation.
Once visible re-orientating network structure towards one more likely to yield innovation can be achieved relatively easily by encouraging patterns of activity leaders would like to see more of. For example, encourage those that already function on the boundaries of networks to share their observations. These people are already acting as ‘brokers’ of new ideas.
Support ‘connectors’ that can land new ideas into well-connected teams for development of prototypes and reward their experiments. Take advantage of the ‘weak ties’  that connect otherwise disparate parts of the network, so that information flows more efficiently around larger parts of the network. Then use Organisational Network Analysis to confirm whether the steps you’ve taken are having the desired effect. If not, try something else.
Recognising that innovation is a social function that emerges in a complex environment helps leaders make sense of innovation and act in a way that is likely to lead to a successful outcome. Applying knowledge, tools, and techniques that have so far been largely overlooked provides leaders embedded in the traditional management paradigm with the tools they need to develop themselves and their teams toward a brighter, more innovative future.
|Complexity Rising: From Human Beings to Human Civilisation, A Complexity Profile. New England Complexity Science Institute. Bar-Yam, Y. (1997)|
|Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organizations: Effects of environment, organization and top managers. British Journal of Management, 17(3), 215–236. http://dx.doi.org/10.1111/j.1467-8551.2006.00498.x.|
|Leadership for organisational adaptability: A theoretical synthesis and integrative framework. Arena, M. & Uhl-Bien, M., (2017). Page 94 – Summary of Dynamic Capabilities.|
|Generative emergence: A new science of organisational, entrepreneurial and social creation. Lichtenstein, B. (2014).|
|A. Hargadon, “How Breakthroughs Happen: The Surprising Truth About How Companies Innovate,” (Harvard Business Press, 2003). A. Hargadon and R. Sutton, “Technology Brokering and Innovation in a Product Development Firm,” Administrative Science Quarterly 42, no. 4 (1997): 716- 749. J Singh and L. Fleming, “Lone Inventors as Sources of Breakthroughs: Myth or Reality?,” Management Science 56, no. 1 (2010): 41-56.|
Groundswell: Tapping employee networks to fuel emergent innovation. Arena, M., Cross, R., Uhl-Bien, M., & Simms, J. (2017). Page 5 – The Social Nature of Innovation.