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14th Dec 2021
Author: Laith Adel, principal consultant and general manager of pmo365
Though there are varying definitions, it’s summarised as consideration of the following aspects, in a transparent, fair and ethical way, during the project lifecycle (of resources, processes, deliverables, effects):
For a long time, implementing a fully sustainable project management process seemed like a puff dream that could not feasible weigh itself against the prevalence of the traditional ‘iron triangle’ of project management – time, cost, and scope.
Furthermore, the brunt of sustainability efforts in the project management space are often simply handed off to project managers by increasing the breadth of their responsibilities and adding new sustainable tracking benchmarks. This has inevitably turned sustainability into a matter of checks and compliances rather than a genuine strategic focus on projects.
How are project managers expected to handle this sudden overloading of benchmarks, criteria and scope without the proper tools that enable them to use their data effectively? This is exactly the gap artificial intelligence (AI) can help bridge and it will hopefully allow sustainable project development to be more than a puff dream for the lucky few.
The AI debate is nothing new in the project management sphere. However, discussions about AI often engenders one of two feelings:
While the fear of AI taking over our jobs is valid, with reports from the World Economic Forum suggesting AI will displace 75 million jobs by 2022, AI is also set to create more than 133 million new jobs in the same timeframe. When we begin to step away from the apocalyptic and fear-inducing narrative of AI, we can begin to truly embrace the opportunities it affords us, especially in regard to sustainability.
Data analysis predicts that by 2025 AI will take over a wide range of traditional project management activities, such as:
With these capabilities, AI will bring a whole range of benefits, particularly for the progression of sustainable project management practices.
By automating and streamlining extensive calculations and when paired with effective software and systems, AI will enable more efficient processes throughout the project lifecycle process. Efficient processes mean less resources used within the project development phase and an overall reduced environmental impact.
Logging data into systems takes time, energy and resources, and should not be overlooked as a potential space for greater efficiency both economically and environmentally.
However, the efficiencies are not limited to processes alone as AI can directly improve efficiencies with resource procurement and usage. For example, in the energy sector the predictive capabilities of AI have been used to monitor weather patterns that allows for the grid to actively pre-empt and respond to changing demands whilst optimising their production to ensure no excess carbon pollution is generated. This has not only significantly reduced harmful environmental impacts but has brought about extensive economic benefits.
The world is becoming more unpredictable than ever, and everything is moving at a pace never seen before. Humans can only calculate and pre-empt so far and so fast before they have become completely outstripped by the sheer speed the economic environment is demanding of them.
The predictive capabilities of AI built on extensive data analysis helps organisations easily identify and evaluate risks based on historical data. This removes the element of human optimism, which though helpful at times, does not always facilitate the most accurate risk evaluation. Reduced risks lead to reduced waste and maximum optimisation of resources available, bringing both environmental and economic benefits to an organisation.
AI is not almighty and there are still many limitations to its historic data based approach that will need to be solved. As a result, human input is still very much necessary. However, humans are bound to make errors when conducting manual tasks that often leads to resources wasted in reviews and revisions. AI will be able to address a large proportion of avoidable human errors in a wide range of tasks.
The overall resource and cost savings achieved by the risk and error reduction from AI will not only positively affect the sustainable agenda, but will also allow for the expansive considerations and apprehensions of a fully sustainable project management process to be addressed.
As mentioned before, the ever changing world is unpredictable and unexpected events like COVID-19 have shown us the importance of agility and adaptability for long-term resilience. AI’s machine-learning capabilities, predictive analysis and digital automation ensures organisations can promptly respond to the changes happening in the world as they happen.
Additionally, climate change is actively contributed to by our practices, and without any change our processes and businesses will constantly be at the whims of a more drastically evolving environment.
Project management approaches and processes can do more than simply react and adapt to these changes. Rather, with the power of AI and sustainable project management philosophies, we can ensure our activities are contributing positively to a sustainable future and make our businesses more resilient and future-proof.
Sustainability is an inherently complex human problem, but shying away from the bountiful benefits AI can offer us in making an effective solution is not going to help. Though there are plenty of reservations in regard to AI, the project management sphere must be willing to embrace and enlist its capabilities if we are to make a sustainable future, where sustainable project management is the mainstream, a reality.
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