Identifying Innovation Opportunities

Identifying innovation opportunities

9 min read

In our previous article, Understanding Innovation, we learnt about innovation and disruption theory and how to differentiate between sustaining technologies and disruptive technologies. This article, which forms part two of our digital transformation series, continues the narrative by discussing how organisations can identify innovation opportunities and make an informed decision without biases. With resources traditionally focused on project-based work, how and where Architecture, Engineering and Construction (AEC) companies direct their efforts is critical.

”I suppose it is tempting, if the only tool you have is a hammer, to treat every problem as if it were a nail.”

– Abraham Maslow 1


You would be hard-pressed to find any AEC organisations which don’t claim to be innovative. But how does one decide which innovation to pursue and which to avoid? And more importantly, how can we bring evidence-based research into our decision making process to ensure we avoid common pitfalls?

Approaches to Innovation

Approaches to innovation

Through our dealings with clients, our experiences tell us that most AEC companies approach innovation in one of two ways. The first is what we call the fear of missing out (FOMO) approach. This is frequently seen in larger companies through the exploration of every shiny, new technology, currently in vogue. Unfortunately, the consequence of this approach is often a lot of quick exploratory studies which fail to deliver any significant, long-term advantages.

The second approach to innovation we commonly see is where initiatives are pursued based on ‘heuristics’, that is, through the use of their intuition to guide them in which initiatives to pursue and which to avoid. But heuristics leave us prone to numerous cognitive biases that skew our thinking in ways that are well-documented and predictable. This leads to poor decision making from even the most well-managed organisation. Very rarely, on the other hand, do we see companies which have an innovation strategy which guides how initiatives are discussed and decided.

The science of decision-making

The psychologist and economist Daniel Kahneman is most notable for his work on the psychology of judgment and decision-making, as well as behavioural economics, for which he was awarded the 2002 Nobel Prize in Economic Sciences. In his book, ‘Thinking, fast and slow’, he argues that there are distinctive patterns in the errors people make. Systematic errors are known as biases, and they recur predictably in particular circumstances.2

Systems 1 & 2 of the brain

In analysing how people make decisions, Kahneman describes two systems in the mind: System 1, which operates automatically and quickly; and System 2, which allocates attention to the effortful mental activities. System 2 articulates judgements and makes choices, but it often endorses or rationalises ideas and feelings that were generated by System 1. And it is here, in System 1, that cognitive biases occur.

System 1 limitations

One example that Kahneman gives to illustrate the limitations of System 1 is the bat-and-ball problem. Do not try and solve the problem, but listen to your intuition:

A bat and ball cost $1.10

The bat costs one dollar more than the ball.

How much does the ball cost?

This exercise was tested on university students, and more than 80% gave the incorrect answer. If you were like the majority, you answered 10c. But this is wrong. The correct answer is 5c (5c for the ball and $1.05 for the bat). This demonstrates just one of the well known cognitive biases – that many people are overconfident and prone to place too much faith in their intuitions.

To explain overconfidence, Kahneman explains that when the mind makes decisions, it deals primarily with ‘Known Knowns’, phenomena it has already observed. It rarely considers ‘Known Unknowns’, phenomena that it knows to be relevant but about which it has no information. Finally, it appears oblivious to the possibility of ‘Unknown Unknowns’, unknown phenomena of unknown relevance.3

Cognitive biases

Other cognitive biases which are well documented and that can lead to poor decision making include:

Anchor Bias

Anchoring bias

The tendency to rely too heavily on, or anchor to, a past reference or one piece of information when making a decision.

Bandwagon Bias

Bandwagon effect

The tendency to increase the conformity of one’s behaviour as the number of other people exhibiting similar behaviour rises.

Confirmation Bias

Confirmation bias

The tendency to seek or emphasise information that confirms an existing conclusion or hypothesis.

Hindsight Bias

Hindsight bias

A tendency to see beneficial past events as predictable and bad events as not predictable.

Information Bias

Information bias

The tendency to evaluate information even when it is useless in understanding a problem or issue.

Loss Aversion Bias

Loss aversion

The tendency for people to strongly prefer avoiding losses than obtaining gains.

Oversimplification Bias


In seeking to understand complex matters, humans tend to want clear and simple explanations.

Restraint Bias

Restraint bias

The tendency to overestimate one’s ability to show restraint in the face of temptation.

Status Quo Bias

Status quo bias

A preference for continuing to do things as they are done today.

It doesn’t take much effort to see cognitive biases in action in the AEC industry. While many organisation promote the notion of agility and innovation, when it comes to changing deeply ingrained ways of working, many resist (status quo bias). After all, if it ain’t broke, why fix it? When new technology comes to market promising better and faster ways of working, organisations frequently focus on minimising costs instead of the potential gain (loss aversion). When attending design technology conferences, very rarely do delegates challenge the notion of industry-accepted norms, such as Building Information Modelling (bandwagon effect).

Identifying innovation opportunities

Given the way our brain works, we need a deliberate, structured way to identify innovation opportunities and to make decisions about which to pursue. We call this an innovation strategy and believe it is fundamental to any organisation. It allows organisations to harness the science surrounding innovation and decision making to give them the best chance of success. While avoiding biases can be as simple as involving someone else in the decision-making process – someone who has no inappropriate attachments or self-interest – identifying where to focus your effort is a difficult proposition for many organisations.

In our previous article, Understanding Innovation, we discussed how innovation could be classified as either a ‘sustaining’ or ‘disruptive’ technology. Sustaining technologies foster improved product performance, whereas disruptive technologies bring to a market a very different value proposition than had been available previously.4 But before deciding which type of innovation to pursue, it is worth considering the role of innovation within the broader spectrum of the profession.

“…the least likely future of all is that nothing much will change. Yet this is frequently the assumption of practitioners.”

– Richard & Daniel Susskind 5

The future of the professions

In ‘The future of the professions’, Richard and Daniel Susskind outline how technology will transform the work of human experts.6 They suggest that there are two possible futures for the profession. The first is a more efficient version of what we already have today. In this way, professionals continue working much as they have done since the middle of the nineteenth century, but they heavily standardise and systematise their routine activities (sustaining technologies).7 The second future involves transforming the way that expertise of professionals is made available to societies through lower costs, higher quality, and more convenient methods, than in the past (disruptive technologies).

They suggest that in the short and medium terms, these two futures will be realised in parallel. In the long run, however, the second future will dominate, and our professions will be steadily dismantled. While this might be alarming to professionals, “the least likely future of all is that nothing much will change. Yet this is frequently the assumption of practitioners.”

Do better things

Like the Susskinds, we believe that over time, technology will replace professional services and that AEC organisations are massively under-exploiting technology. It is one of the reasons why our vision is centred on improving the way that buildings are designed, built and operated through the use of digital design tools. But more importantly, we are fixated on the notion of doing better things.

For too long now, organisations have been overly focused on efficiency, which is the enemy of innovation. Efficiency optimises what already exists. In focusing on what already exists and improving on it, you miss opportunities to create something better. It’s “like a truck slowly moving along a pot-holed street fixing the holes as they see them one by one – it’s a terribly inefficient way to rebuild a road…”.9

Like any profession, most knowledge within the AEC resides in the heads of professionals, in the books and filing cabinets, and in their standards and systems.10 But so much of this knowledge can be encoded and embedded into digital technologies. In their book, the Susskinds present how this is currently under-way in many professions, including medicine, law, accounting, and journalism. For the AEC industry, the hardest challenge for most organisations is to shift away from the “this project is different” mindset. At first glance, this can be a difficult concept to grasp. But if we were to break down professional work into more basic tasks, it becomes apparent that much that goes on today under the umbrella of bespoke professional service is, in fact, routine and repetitive.11 By transforming the medium by which we develop, preserve, and communicate knowledge, organisations can achieve true digital transformation.


When identifying innovation opportunities, we see two paths for organisations. The first is that they ignore the warning signs of the digital evolution that is upon us and continue the status quo through the pursuit of efficiency. The other is one where organisations are proactive in embedding their knowledge into technology that is scalable and efficient, and which will ultimately assist their survival. It should come as no surprise that when we work with our clients, we challenge them to question their firmly held beliefs and practices and encourage a new mindset that embraces emerging technology.

While organisations may fear the unknown and consider much of this outside of their domain, consider Netflix. Netflix shifted from a DVD postal service to a DVD and Blu-ray rental business to a streaming business, and finally a content creation company. So next time, instead of identifying and addressing innovation in accordance within the structural boundaries of your profession, consider the bigger issue you are trying to solve. It may just make all the difference.

In our next article on digital transformation, we’ll discuss the concept of marginal gains and continuous improvements. Interested in finding out more about how Parametric Monkey can help define your digital transformation strategy? Contact us via our website.


1 Maslow, A. (1966). The psychology of science. Harper & Row, Madison, p.15.

2 Kahneman, D. (2011). Thinking, fast and slow. Penguin Books, Great Britain, pp.3-4.

3 Kahneman, D. (2011). Thinking, fast and slow. Penguin Books, Great Britain, p.248.

4 Christensen, C. (2016). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business Review Press, Boston, p.X.

5 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford, p.45.

6 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford.

7 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford, p.9.

8 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford, p.45.

9 Ferrier, A. & Flemming, J. (2020). Stop listening to the customer: Try hearing your brand instead. John Wiley & Sons, Brisbane, p.41.

10 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford, p.34.

11 Susskind, R. & Susskind, D. (2017). The future of the professions: How technology will transform the work of human experts. Oxford University Press, Oxford, p.32.

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