As facilities management systems generate increasing volumes of operational data, the challenge is no longer collection but interpretation. Organisations are now moving beyond scattered information to integrated data ecosystems that convert raw inputs into actionable intelligence for efficiency, security and sustainability. Leaders across facilities management explore how integrated data ecosystems are transforming operations from manual oversight to strategic intelligence.
The Facilities Management sector is undergoing a seismic shift from traditional, manual oversight to a sophisticated digital format. At the Clean India Show 2025, industry leaders attended a panel discussion which was moderated by Mahesh Madgavkar, Head at Group Administration at ACG Worldwide, guiding the panel on how the transition from raw data to actionable intelligence is redefining operational efficiency, security and sustainability.
The session focussed on the fact that while data has always existed within buildings, the modern challenge lies in its integration and purposeful interpretation.
“That the real value of modern FM lies in integrating scattered data streams and using intelligent systems to convert information into actionable operational insights.” — Mahesh Madgavkar
There is a tremendous volume of data currently sitting in silos. In large-scale operations, such as manufacturing plants or expansive corporate portfolios, data often originates from diverse sources like visitor management systems, access control and manual logbooks.
Lt Col Ravindra Bhati, General Manager and Cluster Head-Security at Deepak Fertilisers and Petrochemicals Corp. Ltd, noted the difficulty of conducting manual headcounts across 90-acre plants during mock drills. By integrating scattered data from various software into a single point of access, the organisation achieved real-time visibility.
“We understood that data was available to us and made good use of the integration of that data which is important and we do not have to look out for expensive solutions,” he said.
Madgavkar reinforced this point by noting the evolution from manual logbooks to intelligent systems. “Leveraging AI for sensor-based cameras allows for recording only during movement, which optimises storage and utility,” he said.
“Integrating data from multiple systems enables real-time visibility across large facilities, improving emergency response and operational coordination.” — Lt Col Ravindra Bhati
For many organisations, the entry point for data intelligence is sustainability. The ability to monitor energy, water and carbon footprints provides a clear business case for digital transformation. Milind Patil, Head of Administration-India at Bureau Veritas, emphasised that starting with “low-hanging fruit” is more effective than requesting massive budgets for unproven AI tools.
By installing smart meters and IoT-based monitoring systems in a pilot project, Bureau Veritas achieved a cost optimisation of 22–25%.
“Work with what we have in hand and that will be a good start. Directly jumping to AI and then asking for budget while sitting idle is not helping,” he said.
“Starting digital transformation with simple, measurable initiatives such as smart meters and IoT monitoring before investing heavily in complex AI systems.” — Milind Patil
Madgavkar added that since HVAC systems often account for 70–75% of energy consumption, pulling data from these systems through IoT sensors is vital for any green revolution strategy.
Chetan Jadhav, Head of Infrastructure and Administration at Aditya Birla Capital, noted that as his portfolio grew by 20% over three years, data became the primary tool to ensure consistent stakeholder experiences across hundreds of branches.
“Data is always there, it is how you interpret the data that is vital and whether you are fully using the data that is available. You are collecting the data with a specific purpose and that makes a difference,” he said.
Jadhav emphasized that while technology evolves, the choice to use AI remains personal to the organisation. The focus must remain on whether the data helps a team understand where improvement is needed and how stakeholders rate their performance.
“The real impact of data lies in how organisations interpret and apply it to maintain consistent service standards across expanding facility networks.” — Chetan Jadhav
As FM managers transition into strategic business partners, the focus is shifting toward predictive and intuitive maintenance. Nilesh P Gokhale, Regional FM Lead-Central AMEA at Mondelez India Foods Private Limited, explained that AI serves as a tool to analyse data rather than a replacement for human judgment.
“AI is a machine, it is not human, it will give you outputs or throughputs, whichever guard rails you set to it… Today FM managers are strategic partners to business,” he said.
Gokhale envisioned a future where “intuitive AI” predicts equipment failure before it happens. Beyond maintenance, he described a seamless employee experience where smartphones sync with office infrastructure to reserve parking and desks.
Madgavkar noted that even small initiatives, such as AI-based coffee machines, provide data on employee preferences, helping leaders understand the health-consciousness and culture of the organisation.
“AI should support FM teams by analysing operational data and enabling predictive maintenance rather than replacing human decision-making.” — Nilesh P Gokhale
With the rise of data sharing comes concerns regarding privacy. Addressing audience questions on data safety, Gokhale pointed to the Digital Personal Data Protection (DPDP) Act in India as a critical framework. While some exposure exists today, the industry is moving toward a more regulated environment where data privacy is integral to the system architecture.
Key Takeaways: Data Intelligence in FM
- Start Small: Focus on “low-hanging fruit” such as smart meters and water sensors to prove ROI before investing in expensive AI platforms
- Purposeful Collection: Data should be collected with a specific outcome in mind, such as cost efficiency, employee satisfaction or carbon reduction
- Integration is Key: Transition from scattered software silos to a single-point access system to improve emergency response and resource management
- Predictive Shift: Move from reactive repairs to “intuitive maintenance” by setting clear parameters for AI to monitor equipment failure rates
- Culture and Experience: Use data from vending machines and workspace sensors to understand the evolving preferences of a modern workforce.