Firm foundations

Nadeem Ashraf, Head of Asset Management & Systems, Integral UK warns of the hidden dangers of bad data and siloed software and how it’s important to build foundations for AI-driven FM

The FM sector talks a lot about smart buildings, predictive analytics and the transformative potential of AI; and with good reason, the potential is enormous. Yet many organisations are eager to leap into advanced technologies before they address the fundamentals. Without high-quality, integrated data, even the most sophisticated AI and analytics tools will fail to deliver value. Poor asset registers, fragmented systems and inconsistent reporting not only undermine efficiency and compliance but also erode client trust and inflate operational costs.

THE TRUE COST OF BAD DATA

The adage “garbage in, garbage out” remains as relevant as ever. It’s a challenge every facilities manager is familiar with. Incomplete or inaccurate asset records often lead to a cascade of operational issues. Common ones include servicing equipment that no longer exists, missing critical checks, and relying on flawed maintenance histories. This can result in duplicated work orders, wasted engineer time, big gaps in compliance and lifecycle decisions made in the dark or on complete guesswork. While these costs may be invisible in the short term, over time they manifest as poor forecasting, higher reactive spend and, eventually, a broken relationship between client and provider. When compliance reports are untrustworthy or asset registers don’t reflect reality, the FM team’s credibility suffers.

COMPLEXITY WITHOUT VALUE

Many FM providers operate with dozens, or even hundreds, of disparate systems and portals, often developed in isolation. This fragmented ecosystem adds complexity without delivering any clear value. Data lives in silos, reporting standards differ, and there’s no single version of the truth. AI and analytics are only as effective as the data that feeds them. When information is inconsistent or unconnected, systems can amplify errors rather than deliver insight. The impulse might be to rush the deployment of new platforms on top of the fragmented environment, but this risks further wasted investments and operational slowdowns.

BUILDING A ROBUST DATA FOUNDATION

The solution cannot be technology for its own sake, but a disciplined approach to data. Facilities managers must treat data as a strategic asset. This means:

• Clear governance and ownership of asset registers.
• Defined processes for updates and regular audits to confirm accuracy.
• Consistent naming conventions and data standards to reduce confusion and duplication.

The next step is to connect systems so data can move across the organisation. Facilities managers can begin by linking maintenance, finance, procurement and helpdesk functions, which enables information to flow seamlessly. Even small integrations, like automatically updating a finance system when a work order is closed can save time and prevent errors. The goal is moving towards a coherent dataset that supports all operational decisions.

Maintaining quality is as important as building it, and here it’s useful to understand the foundation as built on four pillars: accuracy, completeness, consistency and timeliness. These must be upheld through validation routines, mandatory fields and a culture where engineers are empowered to report discrepancies. When teams see themselves as custodians of data as well as assets, reliability improves.

SMARTER, DATA-DRIVEN MAINTENANCE

With accurate, integrated data, predictive maintenance becomes practical. Managers can anticipate failures, optimise resources and analyse energy use and lifecycle costs with confidence. FM teams can also model different strategies, such as full SFG20 guidance, statutory-only regimes or fixed-on-failure models, then project the resources each requires. This allows providers to present clients with clear trade-offs and support value-driven decisions.

AI is beginning to improve data quality as well as analytics. Emerging tools capture equipment details more efficiently, using digital recognition to log make, model and location with minimal manual input. As it gets smarter, AI is also getting better at facilitating system integrations, cutting delivery times and costs. As these tools mature, FM teams will be able to survey large estates in days and connect platforms far more quickly. AI-powered assistants are also providing 24/7 support, automating routine queries and aiding technicians in the field.

While AI attracts attention, business intelligence tools remain essential. Platforms like JLL Azara provide real-time portfolio insights, cost analysis and scenario modelling, helping FM teams make data-driven decisions.

REMEMBERING THE HUMAN FACTOR

Technology adoption is only successful when paired with effective change management and workforce upskilling. FM teams must be trained to use new platforms, interpret analytics and act on insights. Embedding a culture of continuous learning and improvement ensures that technology investments translate into operational excellence.

The FM industry is right to be excited about AI, but technology cannot fix a broken foundation. Organisations that invest in governance, integration, and quality build a stable base for innovation. However, it’s possible, and advisable, to pursue parallel tracks, improving data quality while piloting targeted AI and business intelligence use cases that deliver immediate value and build momentum for broader transformation.

Ultimately, FM teams must learn to walk before they run but should not stand still. Clean up the data, simplify the systems and work towards creating a single source of truth. Only then can AI and analytics deliver on their promise to transform asset management and maintenance.