The British Institute of Facilities Management (BIFM), has launched a Good Practice Guide to Asset Management Surveying Practice.
Aimed at FM professionals working within SME’s and large organisations, the guide provides information on producing meaningful asset data that meets increasing expectations of clients, adds value to FM operations and supports business decision making.
It highlights the most important aspects for planning, designing, managing and maintaining asset data information, and aims to support FM professionals in delivering added value by reflecting on their organisation’s strategy in their Asset Management policy.
Peter Brogan, research and information manager at BIFM explained:
“Asset Management is of major importance to FM professionals. At the most basic level better use of data enables FM to demonstrate its value across all business disciplines. However, its potential is not limited to day-to-day operations as utilisation of asset management data is recognised as a catalyst to both BIM and soft landings. The asset management opportunities now available to FMs are a complex and sophisticated area of expertise and stretch across a wide range of professional disciplines and activities.”
Written by Mark Spilling, director of Asssets55 Ltd, BIFM’s Asset Management Good Practice Guide includes specific guidance on:
- Applying key built environment industry standard models and principles to improve quality and quantity of asset data information. This includes Building Information Modelling (BIM), the Industry Foundation Classes (IFC) and COBie, to implement robust survey disciplines.
- Determining key survey goals and objectives.
- Identifying customer expectations and stakeholder needs and defining project scope to the ensure these are met.
- Producing detailed specifications for the required asset surveys.
- Setting up a mobilisation process to ensure asset data capture surveys are carried out in a professional, coordinated way.
- Auditing, reporting and management of data asset files to ensure consistency and accuracy for data standards and compliance.
- Maintaining and enhancing quantified and qualified data through analytics and information assessment.