In this post we’re exploring this key question within our ‘Importance of Data in Facilities Management’ Report.
As industries across the board become increasingly data-driven, FM as we know is no exception. Data has evolved beyond a support function and now drives core operations and client relationships.
However, handling data presents various challenges, as evidenced in the context of Facilities Management and other industries. These challenges are multi-faceted, involving governance, infrastructure, quality and security.
Data Governance and Quality
One of the most significant challenges is maintaining accurate, consistent and reliable data. Poor governance leads to fragmented systems, inconsistent data and difficulties in ensuring data quality. Regular cleansing and standardisation processes are essential to combat these issues but are resource-intensive.
Data Fragmentation and Siloed Systems
The use of disparate systems in FM often results in fragmented data, where each system holds its own “version of truth.” This siloing inhibits the centralisation of data, reducing operational efficiency and complicating integration efforts. API integration and unified platforms are potential solutions, but require investment and technical expertise.
Technical Infrastructure and Integration
Integrating multiple systems into a cohesive infrastructure poses a technical challenge. The complexity and cost of managing APIs, ensuring data transfer compatibility, and maintaining a centralised system often discourage organisations from pursuing comprehensive integration.
Cybersecurity Risks
As data becomes increasingly digitised, protecting sensitive information from breaches and complying with evolving regulations are critical, yet challenging. The inability to securely connect Building Management Systems (BMS) to networks without exposing vulnerabilities illustrates the tension between functionality and security.
Data Overload and Processing
The sheer volume of data generated in modern operations can overwhelm Facilities Managers and Analysts. Identifying relevant information amidst the noise and processing real-time data efficiently are ongoing struggles. This challenge necessitates advanced filtering tools and effective data visualisation.
Ownership and Transparency
Defining clear ownership of data between service providers and clients remains contentious. Without transparency, collaboration and trust erode, reducing the value data can deliver. Establishing agreements and shared access protocols is vital for productive partnerships.
Resistance to Change
Organisational resistance to adopting new technologies limits the potential of data analytics. Older systems, lack of digital fluency among staff and a hesitance to allocate resources for upskilling exacerbate the issues.
Cost Constraints
Financial limitations hinder widespread adoption of advanced data systems. High costs for infrastructure, integration and training often place these solutions out of reach for many organisations, forcing them to continue with inefficient legacy systems.
Balancing Innovation and Privacy
Striking the right balance between leveraging innovative technologies and adhering to privacy standards can be challenging. This tension often results in risk-averse approaches that hinder technological progress.
Skills Gap
There is a growing need for professionals skilled in interpreting, managing and communicating data insights. Bridging this gap requires continuous upskilling and fostering collaboration between technical specialists and operations teams.
Overcoming these challenges demands a multi-pronged approach: investing in technology and training, fostering a data-driven culture and building robust governance frameworks. By addressing these barriers, organisations can unlock the full potential of data for improved decision-making and operational efficiency.
To access a free, full copy of the 64-page Report, please email us at research@wma-consultancy.co.uk and please keep an eye out for more Report extracts in the weeks ahead.