Charting a course through complexity
Brooke Co-founder Brett Nan Tie explains how understanding complexity can help you solve your most complex problems.
We live in a complex world, and much of that complexity is of our own making.
We have choices that previous generations could not even conceive of. Not so long ago there were no mobile phones, let alone smart phones or mobile devices. Now there are dozens to choose from and we can use them just about anywhere. We can buy fresh food from almost anywhere on the globe from our local supermarket. We can purchase almost anything we need (and a whole lot we don’t) online, usually from a plethora of vendors and with a choice of models, substitutes and imitations.
We live in an increasingly connected, “always on” world, where data and information are the new currencies. In the past we had to make decisions knowing we didn’t have enough information. Now we have to make decisions in the face of mountains of information, some of which may be relevant, most of which is not and an increasing amount of which is erroneous.
The pace of change continues to pick up and if the World Economic Forum is right then we are on the cusp of a fourth industrial revolution. The convergence of data, artificial intelligence and other technologies is creating cyber-physical systems that have the potential to radically change the nature of work, and perhaps even what it means to be human. All of this adds to the complexity we face as individuals and as organisations.
Whether you rail against this change, or applaud it, the trend shows no signs of slowing. The question you need to ask is, how can you make complexity work for you?
This is the question Brooke answers when we help organisations solve their most difficult problems.
We work together to chart a course through the complexity they face to achieve the outcomes they need to be successful.
Pinpointing the drivers of complexity
Once the required outcomes are clear, the next step is to understand the complexity that must be navigated. This means identifying the underlying drivers of complexity, the things that make the achievement of the outcomes difficult.
While the individual drivers may be defined in many ways (Brooke has its own complexity framework, measurement system and database) it’s useful to divide them into two categories – inherent and contextual.
Inherent complexity drivers are those that arise specifically from the nature of the outcome you are trying to achieve. For example, the more systems that need to be integrated to achieve an outcome, the greater the complexity. By definition, inherent complexity drivers are difficult to change and impose much the same level of difficulty regardless of the organisation.
This brings us to contextual complexity drivers, which depend on the context in which the outcomes need to be achieved and hence tend to be organisation or situation specific. For example, the more stakeholders involved in decision-making, the greater the complexity. Contextual complexity drivers not only affect overall complexity in their own right, but can also act to attenuate or amplify the inherent complexity drivers.
It is possible to change contextual complexity drivers, to improve decision making processes for example. Sometimes this can be in the form of one-off changes (e.g. exemption from a particular approval process), but contextual complexity drivers also often represent opportunities for systemic improvements.
The complexity that needs to be navigated therefore comprises the overall effect of the inherent and contextual complexity drivers.
Illustrating the importance of complexity analysis
Projects often start with a narrow technical focus around deliverables, which puts the attainment of the intended outcome at risk and creates blind spots in terms of understanding the complexities they face. Completing a complexity analysis at the start of a project helps set it up for success by providing its design team with a broader and deeper understanding of the challenges ahead.
Let me give you an example of where this approach could have saved time, money and reputational damage to an organisation. This particular organisation had deemed one of its projects to be low risk due to its relatively small scale and budget. With few controls and little oversight the project inadvertently, but emphatically breached a sensitive condition of its environmental permit. While the direct impact was a relatively small fine, related costs were substantial. The breach occurred at a time when the organisation was negotiating with the environmental regulator for a blanket exemption from having to obtain individual permits for minor projects, which in turn would have saved it a considerable amount of time, money and effort. Instead, the organisation had to spend additional time and effort proving to the regulator that it had adequate systems of control in place for its minor projects.
Consideration of contextual factors related to risk could have saved this organisation from considerable cost and damage to its reputation.
Where to next?
So, you have defined the outcomes you need to be successful. You have identified the complexity drivers in relation to these outcomes and categorised them into inherent and contextual drivers. You have reduced the overall complexity challenge by addressing the contextual drivers as far as possible.
We believe that the key to success is to then match the competencies and controls that you apply to the level of complexity, as we will further explain in our next two blogs.
To learn more about Brooke’s approach speak to us today.