Capital project excellence (part 4): Why effective performance insight and reporting demands the right balance of human and artificial intelligence

Start adding items to your reading lists:
or
Save this item to:
This item has been saved to your reading list.
In this seven-part series of blogs, Daryl Walcroft discusses PwC’s “Project Excellence System” – beginning by providing an overview of the framework as whole, and then drilling down into each of its six capabilities in turn. With US capital projects poised to experience a renewed infusion of spending, Daryl says the framework can play a crucial role in keeping projects on track, and help ensure they deliver successful outcomes.

So far in this series of blogs on PwC’s Project Excellence System, I’ve looked at system’s overall objectives, capabilities and benefits, and examined the advantages of integrated project technology; described why capital project controls and governance must evolve for a data-rich world. In this fourth blog, I turn the spotlight onto performance insight & reporting, a capability whose critical importance is all too often underestimated – sometimes with catastrophic results.

I ended my last blog, on capital project controls and governance, by setting out my vision of the future: one in which we’ll be able to gather a mass data of relevant data from myriad sources and sensors, and use analytics and machine learning algorithms to predict what’ll happen on any project. If this vision is anywhere near reality, then traditional performance insight & reporting tools and methodologies are on borrowed time.

So, what will replace them? The answer is already emerging – and, like so many of the changes happening elsewhere in the Project Excellence System, it relates to the mass of data available for decision-making on projects. To make the most of this data, we’re seeing project investors, owners and contractors turn to emerging technologies and analytics to help them make sound decisions around the selection of the right investments, the successful delivery of projects and the maintenance of assets.

To meet this growing need, there are numerous tools being offered in the marketplace to support decision-making. In my view, the ones that will produce the best outcomes and ultimately stand the test of time are those with the ability to rationalize the huge volumes of available data, and synthesize it in ways that are useful, relevant, and adaptable to specific requirements.

But the developments underway go much further than the advent of a new generation of decision support tools. Across the major projects industry and beyond, we’re all in a period of rapid and pervasive change, as more data migrates to the cloud, more systems integrate seamlessly, AI becomes not just mainstream but prevalent and near-ubiquitous, and data gathering systems become ever more accessible. These advances are bringing us the ability to provide meaningful, real-time insight into progress, risk, performance, safety and countless other key areas. Crucially, systems are able to consider the lessons from the past and help predict future outcome – a particularly interesting capability for anyone delivering a major capital project.

Why is all this technology so compelling for projects? To visualize the answer, imagine a situation where the owner of a large capital program to deliver a new hospital can use technology to inform them of the best time to start the project, the best contracts, the best materials based on global commodity trends, and the best sequence to deliver the project. What’s more, the system can also predict risks before they arise. The impacts would be profound – and would likely include significant cost savings, together with reduced reserves and contingency levels in recognition of the greater certainty around the outcome.

If this sounds like a wonderful new world – and many ways it is – the fact remains that we need to be cautious. AI and related technologies don’t represent a panacea. And while they do provide a useful set of tools and techniques that can be applied to many project situations, it is vital to weave in the human element carefully and consistently. The best decisions are informed by a balance of human and artificial intelligence – and this isn’t going to change any time soon.

In my next blog in this series, I’ll look at a Project Excellence capability at the sharp – and highly operational – end of project delivery: project and team organizational effectiveness.

 

{{filterContent.facetedTitle}}

Contact us

Daryl Walcroft

Principal, US Capital Projects & Infrastructure Leader, PwC US

Follow us