Dealing with Uncertainty in Facility Management (FM) Contracts Through a Data-Driven Approach

Abstract

Nowadays, the FM scenario is undergoing a deep transformation due to the increasing adoption of information and communication technologies (ICTs). Real-time data, new storage possibilities and data analytics are changing the modalities of monitoring and control of service performances offered at the building scale. Data-driven approaches based on predictive analyses applied in FM are meeting a large consensus from FM operators which are perceiving the related achievable benefits. However, applications of ICTs in FM are still at an experimental stage and they can be subjected to a variable level of uncertainty due to the lack of knowledge about systems behaviors. This uncertainty can not only affect the calculation of the expected service performance (SLA) but also the deviation between expected and actual service performances. The uncertainty on expected performances gains a higher relevance when FM services are outsourced to an external provider (especially in performance-based contracts). The paper aims to propose a methodology to quantify and manage the deviation between expected and actual service performances within FM contracts, acting both in the contracting phase (SLAs definition) and during the service provision (deviation expected/actual performance). This methodology would support FM stakeholders in managing the level of uncertainty on expected service performances, mitigating related risks.