Rob Bryant, EVP of APJ at InEight

Project health is constantly buffeted by risk events from all sides. And projects in Australia are being crippled by a trifecta of weather, supply chain disruption and increasing input costs.

Working through another La Niña season, the wet weather will loom over the construction sector as projects will once again be delayed and subsequently run over budget because of persistent and unusual weather. Hence, it is no surprise the latest InEight Global Capital Projects Outlook reveals there is a 11% higher concern over climate change from 2021 to 2022.

Managing risk, improving efficiency, and determining more predicable outcomes are all strategies to help reign in those factors and bring about a sense of wellbeing in a project landscape that is littered with chaos mines.

Developments in digital technologies enable solutions such as artificial intelligence (AI) and enhancements to Critical Path Method (CPM) provide timely forecasts, reliable predictions, and effective risk management in the face of changing factors, whatever the weather.

How can AI support risk management

Although AI is not some magic tool whereby a contractor pushes a button and generates a schedule, it can be leveraged and manipulated to provide more realistic, dependable suggestions. In effect, it improves the planning process by enabling a computer to mimic the way a human makes decisions.

An inference engine is a component of the AI system that applies logical rules to the knowledge base to deduce new information. When a project owner asks for a suggestion, the inference engine requests inputs in order to understand the context, such as the type of project, location, quantities and other variables. It then uses those variables to understand context, interrogate the knowledge library and provide suggestions.

To fully capitalise from the benefits of AI, project leaders are provided a list of suggested risks from the company’s knowledge library repository. Rather than project leaders having to brainstorm from a blank sheet of paper, they can consider previously realised risks and opportunities from similar historical projects.

Not only that, but as new risks are identified, they can be published to the enterprise risk register ready for subsequent consumption the next time around. This self-perpetuating risk management loop is an entirely new and more effective way for an organisation to become more risk mature.

How CPM helps provide data insights

Traditional risk reports have tended to be statistical in nature referring to the likes of probabilities and correlations — all very interesting but in reality, how useful are they?

When it comes to risk reports, project owners and contractors should be looking to solve the risk exposure on a certain project, why on-site workers are exposed and how can contractors mitigate such risk.

One of the biggest drawbacks of traditional project risk management has been that risk analysis has been conducted not only as a separate exercise to the planning process, but worse, it is conducted in a separate software tool. Instead, the processes of building a CPM schedule and risk analysis should be combined into one.

By accounting for risk and uncertainty during the schedule development itself, we start to move toward true risk adjusted forecasting — where we can make more informed decisions by having an up-front understanding of risk hot spots. And by being able to toggle the risk events on and off, see the impact of them in the schedule.

There are now more meaningful ways to report risk than what has previously been possible. The new ways include smarter risk reporting, focusing on required contingency to overcome risk exposure as well as highlighting whether specific risk events or areas of schedule aggressiveness are driving on-time completion exposure.

Putting an end to “from-scratch” planning

Data is the key to project certainty, but it can only be relied upon if construction utilises past data when structuring present day projects. As such, this is where having a benchmark plan plays into tracking project progression.  Benchmark plans enable contractors to better understand if there is a need for further alignment.

Task durations can also be established using historical data. In the process, the AI-enhanced program asks a series of questions (e.g., scope of work, number of units, and so forth) and then uses historical productivity rates to determine the duration. This provides a more defendable, realistic estimate that is based upon past performance.

Project quality and the health of the project is paramount to even starting to think about scheduled risk analysis. Without it, the results are going to be flawed. With the incorporation of AI planning capabilities and CPM, the entire planning process has become more of a collaborative partnership It can now draw on past project performance to guide the planner and allow collaborators to be invited to endorse or suggest alternatives, whilst also seeing in real time the impact of their suggestions.

By continuing to apply this agile and insightful approach the health of construction project is sustained throughout the timeline. These new digital technologies are offering a quantifiable leap forward in the world of project planning and scheduling. Whilst weather can still present a wildcard, these new digital developments provide a quantifiable leap forward in the world of project planning and scheduling. To ensure project health, why not apply the tools and insight at your disposal?