Water utilities are battling compounding challenges never faced all at once: ageing infrastructure, growing populations, supply chain shocks, economic instability, cost-of-living pressures and climate extremes. As trusted asset management advisors, our role is to help water utilities allocate their limited resources as efficiently as possible while they face these challenges.
In response, significant effort has gone into improving delivery efficiency by modernising delivery models, adapting digital engineering and achieving construction efficiency.
However, for many water utilities, projects still take years to become delivery-ready, with significant time spent deciding on the right option to achieve strategic objectives. The greatest efficiencies are no longer occurring in delivery, but instead in how projects are planned, how information is used and how decisions are made.
Regulators have encouraged utilities to find ways to drive efficiencies in the planning and delivery of assets. Across the Australian infrastructure sector, modernised, integrated delivery models and digital engineering have been argued for as the solution to driving capital works momentum.
With years of effort to improve delivery productivity, many water utilities now find that projects can take just as long to become site-ready, in planning and approvals, as they do to deliver. These delays create cost, risk and customer impacts. So, with a hyper focus on planning efficiencies, what can actually help utilities?
Fortunately, Australia is not alone with these challenges. Through our work in a joint venture alliance, we worked with a major water utility in the United Kingdom on an ambitious vision: get its projects to site in half the time at 30 per cent less cost. The desired outcomes weren’t just about improving speed and cost, but also quality, and community and customer outcomes.
The focus was to shift away from squeezing more efficiency gains out of delivery teams and speed up the front end of projects: planning, options analysis, business cases and approvals.
Early projects with the U.K. utility are showing early benefits. Rather than accelerating every project equally, the shift is about making clearer, earlier calls on risk, complexity and delivery readiness.
The shift allows for repeatable work to move faster with tailored governance, while genuinely complex investments receive deeper integration and assurance up front. These gains come primarily from avoiding rework, late changes and duplicated effort rather than reducing scope or assurance.
Asset management and project delivery teams are often working from two different, fragmented digital systems, each with its own data:
At the handover point, information is re-entered and then maintained separately, and the two systems don’t always communicate with each other. As a project progresses, the data becomes increasingly disconnected, and teams are working from different numbers, definitions and assumptions about assets. This presents a core challenge if you bring these teams together in planning.
A critical shift needed for 50/30 to succeed is to deliberately connect asset information and project management systems into a single, shared source of truth, so views and conclusions can be driven from the same underlying data.
For U.K. water utilities, this has been addressed by deliberately connecting asset information and delivery data into shared digital environments, rather than joining systems at the handover point. Site data is captured digitally once and flows directly into asset systems, removing the need for traditional re‑entry, reconciliation and bespoke as‑built deliverables. This gives asset, planning and delivery teams a common, trusted view of cost, risk and readiness early enough to influence investment decisions.
The digital connectivity between teams across the water program enables them to take advantage of the rapid, transformative opportunities AI can offer.
Once data is joined, structured and trusted by teams, AI could be applied to tasks such as forecasting demand, prioritising investment options, assessing risk based on previous work and testing scenarios. Water-sector research is increasingly pointing to this same sequence: AI can support utility planning, but only when the underlying data foundation is strong enough to be trusted.
Without that shared data foundation and mature decision-making processes, AI will struggle to gain confidence or adoption. In other words, AI is not the starting point, it is the multiplier that becomes valuable after data, governance and ways of working are in place.
Project planning and project delivery teams, despite both being responsible for asset management, can be siloed, using disconnected systems and potentially holding preconceptions about each other's roles.
50/30 encourages teams to work together further upstream in the planning process, allowing delivery teams to better understand and inform project option decisions. Once they’re in shared forums together, looking at the same information and agreeing on commitments, trust can be built.
In the U.K., these changes only worked because utilities invested as much in how teams work together as they did in new processes or technology.
This is about a workforce uplift as much as it’s about a change of process. More collaborative behaviours, clearer ownership and less sense of “you’re on your own getting a project through approvals” or “we’ve gotten this through, you can now deliver it”. The behavioural shifts in planning and approvals can spill over into how the organisation works day to day.
When planning and delivery are finally looking at the same data, with data trusted by all parties, they can stop treating every project as if it deserves the same process and speed. They can see side‑by‑side which assets are in the worst condition, where the biggest service and regulatory risks lie, and what each option will cost in resources. That then lets them make clearer calls about which projects should move first.
The same information also helps with decisions about delivery pathways. Repeatable, lower‑risk jobs can follow a more automated, standardised, templated pathway with fewer steps and lighter governance, while genuinely complex or high-risk ones can follow a more bespoke route with greater design, engagement and integration between teams. The delivery model is matched to the real risk and complexity of the work, rather than forcing everything through a one‑size‑fits‑all process.
Some projects can safely be pushed into a ‘fast lane’ with compressed planning timeframes and earlier site starts, others need more time up front because the downside of getting them wrong is much higher. The win is that a meaningful slice of the program can still be accelerated (the typical ‘bread and butter’ projects teams have delivered for decades), but done so in a way that’s evidence‑based.
Bringing delivery teams earlier also helps deliver higher-quality projects by enabling them to identify and address quality concerns early, reducing potential rework in design. This contributes to the ambition of 30 per cent less cost.
Allan MacMaster is Technical Director - Advisory, Australia and New Zealand at AECOM. This article was first published by AECOM. You can find the original here.