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A wide-ranging look at risk management Five proven steps to develop a risk management strategy for construction scheduling The engineering and construction industry has historically taken an informal and improvisational approach to risk management, often leading to risks being identified too late in the project lifecycle.
Frank Malangone Senior director for Product and Industry Strategy, Oracle Construction and Engineering
Results from the June 2020 quarter survey depicted that building projects throughout New Zealand were expected to see delays in completion times lasting between 20 and 60 working days, with the impact of COVID-19 regulations yet to be accounted for. Proper risk management will help project teams identify potential risks before they are encountered and give the teams time to develop strategies to reduce the issue’s impact. Some firms mistakenly only manage risks at the project level, which leads to an incomplete picture of exposure and performance. Results from a NZ questionnaire survey of consultants and contractors in the construction industry showed 21 risk factors which were segregated into six broad categories in diminishing significance levels: site conditions, main contractor, pricing, subcontractor, external and client related risk. It’s important to expand that focus, elevating that visibility to the program level. This will allow teams across projects to better synchronise resources and adjust plans to realise successful outcomes. Organisations managing construction projects (or portfolios) are increasingly looking for ways to incorporate more comprehensive risk management practices, but many in the industry are not sure where to begin. Here are five proven steps to help develop a thorough risk management strategy in construction scheduling:
in appropriate schedule, labor, and supply chain contingencies. 4) Disseminate for clarity 1) Recognise the risks The management team, at the beginning of a program or project, should try to identify potential risks.
to manage large, complex projects with thousands of data points that can change frequently, including calendars, resources, and the relationships between them.
Could poor weather or uncertain site conditions potentially delay construction? Is there a risk that material costs could significantly rise unexpectedly?
It is also not suited to conducting risk analysis across far-reaching programs. For these types of complex scenarios, it is best to use a true risk management application.
It is impossible to identify and manage every possible risk, but the team should agree on any events that are most likely to occur and have the greatest impact. These are the factors that they will monitor and manage.
In addition, new AI tools leverage machine learning to analyse project data – both past and present – to continually assess schedule accuracy and provide predictive intelligence into potential risks on projects.
2) Evaluate your exposure After identifying potential risks, the team should determine the likelihood of each risk occurring, as well as impacts to costs and schedules.
Such tools can empower teams across the organisation to sharpen decision-making and take action on emerging risks before they become showstoppers.
Risks should then be ranked on the probability that they are to occur, and the impact they may have. Teams should prioritise how they will manage specific risks with the help of Monte Carlo simulations and scenario planning tools. This will allow users to create and run various whatif scenarios by changing key variables. While Monte Carlo analysis can be conducted via a spreadsheet, this approach is not suited
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3) Establish a response strategy Teams should have a detailed plan of action on how they plan to mitigate high-impact risks.
The project team should communicate this information to the project owner after they have completed their risk assessment and defined mitigation strategies. This demonstrates an effort to take a proactive approach to reducing risk and allows contractors an opportunity to discuss the risks, mitigation strategies, and potential impact on the schedule and cost of the project with the project owner. 5) Track, adjust, and repeat As risks continue to develop, program managers must build in regular assessments to their mitigation strategies as conditions change. Again, machine learning provides key support here by helping to identify potential risks and inefficiencies early, helping organisations make more informed decisions about the best path forward. In conclusion
Scenario planning technology plays an important role here to assess what-if scenarios and determine costs and benefits of each mitigation strategy.
Good risk management strategies require the integration and analysis of diverse sets of information, including budget, cost, and schedule data.
While some risks ultimately can’t be avoided, such as building during unforeseen inclement weather conditions, this step can reduce the impact on the project by building
With this in mind, organizations managing construction projects will be well on their way to shoring up their risk management practices. CT
