Digitalisation, Major Projects & Infrastructure

PMO evolution: Using data to improve delivery

With technology developing at a rapid pace, PMOs are the new intelligence centre, writes Jason Cooper Asia Pacific director PMO at SNC-Lavalin’s Atkins business.

In an age when we’re more informed than ever before, it’s extremely frustrating to see that the rail construction industry is still beset by familiar problems in terms of on time, on budget, high quality project delivery, especially with complex major infrastructure programmes which are being executed by Programme Management Offices (PMOs).

Despite all the technological progress of the past 40 years, infrastructure delivery authorities are still crying out for increased transparency, improved predictability and smarter decision making to avoid costly overruns and searching questions. Today, a digitally-enhanced PMO is taking the next step to improve decision-making on complex rail projects.

The basic premise of having a single team within an organisation focused on defining and maintaining programme management standards to improve delivery is not new and the benefits are well established. Fundamentally, governance and assurance over an entire programme ensures that the information driving delivery is consistent, accurate and transparent, which, in turn, leads to more informed decision making.

As such PMOs have long driven efficiencies in design, delivery and operational management, but there is room to do more.

As we are now in the middle of the fourth industrial revolution – the convergence of cyber and physical systems – it’s at this juncture that we should expect more from PMOs, given the rich data which is now widely available.

When collected, managed and analysed in the right way by the PMOs, data can have a significant impact.

If structured and planned properly in the set-up phase of programmes, the data becomes a real-time resource that supports greater surety around time, cost and quality outcomes during construction and in the future asset operation and maintenance phases.

Pushing this further still, data can enable the use of predictive analytics, via artificial intelligence, that replaces reactive decision making with earlier, more proactive decisions; while prescriptive analytics sees programme controls technology automatically make recommendations based on the data to hand.

So, what’s stopping us from reaching these heady heights of cutting-edge data-driven delivery?

We can’t deny that the infrastructure industry sometimes lacks the appetite for change. It’s well documented that we lag behind other industries such as automotive and manufacturing when it comes to the adoption of digital technology and the harvesting of data. Perhaps we’re constrained by the risk and rewards mechanisms of contracting models? Perhaps procurement routes need to better incentivise innovation? Or perhaps we’re just stuck in our ways?

Jason Cooper, director PMO at SNC Lavalin Atkins.

Whatever is holding us back, the reality is that we don’t handle data in a consistent way across the industry – we don’t always re-use it, store it or make it available for future analysis and benchmarks. Such disparate, unconnected systems make it difficult to ingest, use, and re-use, data effectively, as we’re simply not singing from the same hymn sheet.

The lack of harmonisation means that when data is presented to support decision making on major infrastructure programs, CEOs and program directors have to wade through a flood of data to find the information that supports a decision.

For me, two immediate areas require attention if we’re going evolve into an industry that fully understands and utilises the incredible data we have at our fingertips.

It’s well documented that there are skill shortages within engineering and construction, and this is being exacerbated as the industry continues to negotiate a wave of technological disruption. The Australasian Railway Association (ARA) estimates that by 2024, there will be a 36.4 per cent skills gap in civil engineering professionals in the rail industry. The need to upskill is apparent, as is the importance of training and education that evolves alongside digital trends.

While digital skills are clearly a priority, this needs to be supplemented by data skills if we’re going to unlock the power of AI, digital twins and the like. We need more data analysts, data scientists and data savvy professionals if we’re going to turn information into actionable intelligence.

A second area – and one which may be even a tougher nut to crack – is the accessibility and analysis of data. Without clean, consistently organised data, our analytics platforms are useless. And it’s here we perhaps need to view data differently for the good of the industry, as well as the next complex infrastructure programme.

Data needs to be shared – it can’t be locked away or kept out of reach behind restrictive and archaic contracting models. We must allow data to flow more freely if we’re going to learn and improve. To have data from completed projects stored away is sacrilege – a wasted opportunity to mine invaluable knowledge.

That said, we can’t pretend that granting access to data isn’t without risk, which is why we must ensure that it is shared securely, ethically and responsibly. If we have the right systems, protocols and laws in place, there’s no reason why the international construction community – and their clients – can’t share data for the greater good of major programme delivery and the continued evolution of PMOs.

With these principles in place, the next step is using the resource of data to improve decision making. To this end, SNC-Lavalin Atkins is investing in advanced analytics capabilities that will organise and analyse data across programmes globally for the benefit of infrastructure delivery. Using these new capabilities to match real- time data with delivery schedules create the possibility of automated early warning systems that prevent delays and reduce risk. Accurate reporting will mean that decisions can be made based on the realities of the project’s status, with data-based evidence to back that up.

Right now, finding the right data to support a decision is like looking for a needle in a haystack, but with powerful digital tools, PMOs can start harnessing the potential of data to make decisions, earlier, faster, and with more surety, improving time, cost, and accountability outcomes.

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