Hello, and welcome to this special Insights edition of Futureproofed. I'm Eoin O Murchu, and today I'm joined by Alex Marx, Head of Data Insights for Infrastructure & Real Estate's team. Today's Insights is in response to the recent Data Analytics and AI Report published here in the UK by a coalition of industry project bodies and the UK Government.
Alex, for listeners who missed this publication, could you explain what the Government Report is about and some of the key observations within it?
Absolutely. So this report sets out a framework in which the Government, together with professional bodies, want to improve the way we leverage data to drive better outcomes in Government projects. There are five key aspects that they talk through.
There's building data skills, which is equipping project teams with the skills to analyse and interpret data effectively. There's improving data quality and availability, which is making sure that the data they have available to them can drive as much value as possible because it's accurate, accessible and usable. The third element is about enabling evidence-based decision-making, using data and insights to inform project decisions and improve the outcomes of projects.
And the fourth piece is about promoting experimentation, encouraging pilot projects and testing to understand the potential of new data analytics and AI tooling. And finally, it's about partnership, building collaboration between government departments and external partners to share data expertise. Now, these principles are fantastic and very ambitious, but I think one of the themes that I really enjoyed in this report was about the emphasis on people and the emphasis on access, giving people the comfort and confidence to leverage data where they can, and then equipping them with the data itself to make sure that they can apply it to project outcomes.
Yes, thanks, Alex. And I think there are some really relevant themes that you just pointed out there. Something that struck me was the importance of data, data quality and potentially data availability.
Is that fair to say in terms of driving value across the wider project and delivery life cycle?
Absolutely. Data quality sits at the foundation of driving better outcomes and ensuring that you build value and also create trust within the organization. A lot of project organizations are not used to a level of change and actually reliability on the information they're seeing is essential to then inform the way they make decisions and set strategies.
There's a holistic view of this, and they talk about the fair framework within the report, which is very important to ensure that when there is data, it's easy to find, it's used for multiple purposes, and therefore it can drive decisions across the business. And where this comes into play is two big areas. So it's about reliability.
If you're going to make data-driven decisions, you need to ensure that the data informing them has a level of quality, that it is fit for purpose. And quality can be in the eye of the beholder as well. It's worth noting that quality doesn't have to be affection, it just has to be good enough for the task that it's being used to set.
And then there's a holistic viewpoint aspect of quality, which is making sure that it's reflective of every different element of a given project so that you know that decisions around costs in a construction project, what that will mean for the handover and the operations of that project at a later point in the programme.
And finally, you've highlighted some really interesting observations there. From your perspective, what are some of the tangible next steps that people listening in to this insight can take away to drive value from some of the observations and opportunities that are outlined in this report?
So I think there's a couple of different elements. Firstly, there's the people aspect. Data is going to become part of all of our business and all of our roles, and it's no longer going to be a separate siloed activity within projects.
And we've already seen that over the last 10 years. But I think what's more important is as we move at faster pace, people need to get more comfortable with data and the easiest quick win way of doing that is just to get your hands on data person into your role, see what you can understand from it, see how it can inform and change the way you do work. And that word change is the other important part of this.
And I think that's the more long-term aspect, which is changing our mindsets. The report talks about promoting experimentation, the idea of fail fast, the idea of learning how to test quickly what could be done before investing overly in new tech, new process, new ways of doing work. And that idea that there is no failed experiment and becoming more comfortable with change is something that is really essential to projects and that we see can be a bit of a barrier in some of the industries that we work in.
Thanks, Alex. That's some really interesting observations. And thank you all for listening to the shorter edition of Futureproofed Insights.
If you want to know more about some of the topics we've discussed today, please do check out our accompanying blog. Or alternatively, check out our recent Deep Dive podcast on the power of AI and capital projects, which we did with colleagues from nPlan. So until next time, thank you all for listening.
