When asset decisions are fragmented, portfolios underperform

A model built for a different reality

Most organisations do not have a maintenance problem first. They have a decision-making problem. Real estate and technical assets are still often managed through models built around individual buildings, local budgets and separate functions, even though the risks and trade-offs organisations now face sit across the portfolio. What appears structured at site level can therefore become misaligned with the realities leaders are trying to manage.

For decades, most organisations have managed real estate and technical assets one building at a time. Maintenance budgets are allocated site by site. Asset replacements are triggered by failures. Capital plans are developed locally rather than strategically. On the surface, that can look sensible and disciplined. In practice, it often leads to what Evrim Veli Ay, Global Technical Services Lead at ISS, calls local optimisation – fixing a problem in one building without understanding whether it is the right priority across the wider estate.

That is where current approaches begin to fail. Buildings are not equally critical. Lease events, asset condition, operational priorities, financial exposure and carbon targets do not sit neatly within the boundaries of one site. Yet many decisions are still made as if they do. The result is that capital often flows to the most immediate or visible problem, rather than the issue that matters most across the portfolio.

A building-by-building model can create the illusion of control while steadily destroying value. A local team may make a perfectly reasonable decision for its own site, but if that decision is disconnected from wider portfolio priorities, the organisation may still be overspending, sequencing investments badly or leaving higher-risk assets untouched. What looks efficient in one location can be inefficient across the estate as a whole.

“There are more applications in the market than there are ideas.”
Evrim Veli Ay, Global Technical Services Lead, ISS  

When fragmentation becomes the real problem

This gap becomes even more pronounced when responsibilities are split across functions. In many organisations, asset replacement, capital allocation and decarbonisation sequencing are handled by separate teams, on separate timescales and with different measures of success. One team is managing reliability, another is planning CapEx and another is focused on sustainability or compliance. Each may be acting logically within its own remit, but the organisation still lacks a joined-up view of where risk is building and where investment will create the greatest value.

That is why the problem is not simply poor maintenance, and it is not simply a lack of data. It is fragmented decision-making. The data may exist. The decisions may exist. What is often missing is the framework that connects them. In Ay’s words, this is not just a strategy failure. It is an intelligence architecture failure.

Why technology alone does not solve it

That distinction matters because it helps explain why so many digital investments fail to deliver the expected returns. In a market obsessed with digital transformation, the instinct is often to reach for the next dashboard, platform or IoT integration. But technology without a clear decision model rarely creates much value. More visibility within one system does not remove fragmentation across the wider organisation. More data does not automatically improve prioritisation. And a dashboard can make problems easier to see without making decisions any easier to take.

This is the trap of the shiny tool. Organisations invest in applications because they appear modern, measurable and easy to justify. But surface-level technology cannot solve a deeper structural problem. It can improve reporting within one workflow or one site, while leaving the broader logic of capital planning, decarbonisation sequencing and estate strategy untouched. The result is often more information, but not more clarity.

Ay captures the point sharply: “There are more applications in the market than there are ideas.” The line is provocative, but the problem it describes is practical. Sensors may be installed without a clear decision model for the data they generate. AI tools may be asked to predict failures against incomplete asset registers. Dashboards may present performance issues without linking them to lease strategy, capital timing, risk exposure or carbon implications. In each case, the technology is active, but not necessarily useful in the decisions that matter most.

Data is not the same as decisions

This is why data is not the same as intelligence, and intelligence is not the same as action. Many organisations do not suffer from a total absence of information. They suffer from information that is inconsistent, incomplete, poorly governed or disconnected from decision rights. Asset condition data may sit in one place, lease information in another and financial planning somewhere else again. Sustainability targets may be tracked centrally while maintenance plans remain local. The issue is not that nothing is known. It is that too little is connected.

When that happens, organisations struggle to answer questions that should be relatively straightforward. Which assets should be replaced first? Where is capital risk increasing fastest? Which planned investments no longer make sense because the site strategy has changed? Which carbon-related interventions will create measurable operational and financial value over time? Without a portfolio-level view, these questions become harder than they should be, and decisions become slower, more fragmented and more vulnerable to poor timing.

One example from ISS’ work illustrates the point. A customer with a highly distributed estate was reviewing capital needs asset by asset, and every request looked expensive and difficult to justify in isolation. But when ISS mapped those needs across the full portfolio, a different picture emerged: years of unfunded, high-risk work that had been hiding in plain sight. Priorities became clearer once the organisation stopped looking at each site individually and started understanding the estate as a whole.

“This is not just a strategy failure. It is an intelligence architecture failure.”
Evrim Veli Ay, Global Technical Services Lead, ISS

Why a new approach is needed

This is the fundamental weakness of many current models. They were designed to manage buildings. Increasingly, organisations need models that help them manage risk, capital, resilience and carbon across portfolios that are more dynamic, more scrutinised and more financially consequential than before. A site-level approach can still resolve immediate operational issues, but it is no longer enough to guide long-term investment and performance decisions well.

The organisations that move ahead will not be those that simply layer more advanced systems and technologies on top of fragmented structures. They will be those that rethink how asset decisions are made in the first place – shifting from local optimisation to portfolio-level visibility, from disconnected data to usable intelligence and from reactive interventions to more deliberate capital planning.

In other words, the issue is not whether organisations care about their assets. It is whether the model they are using still matches the reality they are trying to manage. For many, it no longer does. That is the real reason current approaches fail.

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