The recently published report on Data Analytics and AI in Government Project Implementation provides a framework to strengthen project delivery and capability building through advances in data science and AI. It focuses on developing the use of project data analytics and AI to support project delivery, placing the UK at the forefront of this emerging discipline. Our work supporting public infrastructure projects focuses on the opportunity to improve outcomes and value for taxpayers through data-driven insights and automation. We see first-hand the challenges industry faces in using data effectively and advise on how to overcome them. In this article, we reflect on the overarching themes of the report: the importance of high quality dataA innovation culture within a data literate society WorkforceAnd Partnerships For better project results.
- Best data and availability: To leverage data and AI, you need good quality data. In infrastructure projects, we’ve found that data diversity and format across different systems and contractors can limit visibility. To improve both availability and quality, projects need to consider future data needs from the beginning.
- Experiment together: The government pilots proposed in the report will help identify the best opportunities early on, but must be accompanied by a culture change to ensure success. We have advised projects on how best to focus on new opportunities, including providing a list of common and high-impact use cases via The Generative AI FileAs technology continues to develop, project teams will need to quickly explore and understand its potential to enable effective outcomes.
- Big Data Skills and Capabilities: The industry needs to embark on a skills development agenda to build capacity and build capabilities. To overcome the skills shortage, the industry must look to maximise productivity by adding non-traditional digital and data roles. Traditional project roles, such as risk managers, will also need to increase their data literacy as this role evolves.
- Data Partnerships: Average productivity levels in the construction sector have remained consistently below the UK average (1). To overcome this situation, the public and private sectors must work together. The sector must be willing to exchange knowledge and build partnerships to ensure relevant skills are developed and best practice is shared.
- Evidence-based decision making: Identifying underperforming projects and implementing early intervention leads to improved project outcomes. In a recent study conversation With nPlan Founder Dev Amratia, we discussed using nPlan’s machine learning to accurately predict project outcomes. Using these technologies on infrastructure projects can improve the accuracy of forecast assessments, risk management, and real-time monitoring.
Every infrastructure project is unique and there is no one-size-fits-all approach to using data analytics and AI. To achieve better outcomes, the infrastructure sector must build on this framework and share its expertise to deliver long-term value for the public. For more perspectives on generative AI in infrastructure and real estate, check out our blogs on bridging the gap, transform real estate, Overcoming implementation challenges and kissing a human-centered approach and listen to the Future prospects on this publication.
The references
(1) Office for National Statistics, “Productivity in the construction sector, UK”, ONS, 2021.
