Facilio’s Prabhu Ramachandran on how you can extract even more value from building data
The US Department of Energy’s four-year Smart Energy Analytics Campaign recently presented findings that found analytics software had led to a median of 9% energy savings, in six and a half thousand buildings studied across the US. In the last few years, the consensus around the impact of operational analytics software for buildings – in predictive maintenance, energy management, commissioning etc – has become nearly universal in the commercial real estate industry.
Although this mainstream acceptance is a welcome first step, it is also becoming obvious that to truly optimise the power of analytics, the industry needs to become better at implementing the insights it unlocks. Let’s take a look at how improvements in software can enhance this leap from insights, to actionable outcomes.
Getting more from Analytics
Analytics are not a standalone ‘magic’ solution. For software to transform your operations to be more data-driven, you need to have a team that can drive the journey from insights to action, with empirically measurable results. So, one of the critical capabilities, which a great O&M software must have, is allowing all stakeholders and vendors to collaborate effectively.
But that’s just a start. Prescriptive insights either uncover physical or system level issues. The first kind – that is, physical issues – usually need active human involvement to be resolved. Human intervention in system-led control issues, on the other hand, is much more complicated. Any enhancement needed in the Three S’s – Sequences, Setpoints, and Schedules – requires the reprogramming of local automation software. This is far from straightforward, and even if a local control system is improved, the process will need to be repeated for all systems in your portfolio.
As emerging smart building technologies add to the solutions you employ, this process will only get more complex. Especially since greater automation, more sophisticated control sequences, and the ability to deliver ever more personalised occupant experiences, will continue to escalate.
The need for O&M teams to drive efficiency across every process, performance metric, and workflow, makes a strong case for cloud-based portfolio automation software. This portfolio-wide approach allows management software to be consolidated, and control sequences to be made more effective, at scale. Let’s consider the advantages of the approach:
• Ownership of portfolio optimisation process: For fully optimised operations, O&M teams need control over data, as well as sequences, setpoints, and schedules. Legacy control software is unable to provide this, because it was designed to be used by vendors. Cloud-enabled software platforms overcome these limitations, taking into account inputs from all stakeholders, including occupants, to achieve full spectrum enhancement that ticks every box.
• Portfolio scale consolidation of management software: Legacy building management software systems depend on separate applications for each function. The new generation of cloud-based software platforms enables portfolio-wide unification and eliminates redundancies. Challenges, such as the recent pandemic, or the introduction of new regulatory guidelines and standards, can be overcome far more easily by replacing obsolete control sequences through over-the-air upgrades.
• Cloud-enabled control sequences: Just like cloud computing enhances the power of analytics to crunch data, cloud-based machine learning unlocks the ability to constantly upgrade control sequences – predictively and proactively. The ability to take all real-time data and all sources across a portfolio into account results in much more comprehensive control sequences.
A New Benchmark
Analytics applications leverage advances in cloud computing, to crunch all the data created in local control systems, to generate insights. The next step in this evolution is to leverage the cloud for control sequences as well. A portfolio automation software will use cloud-based machine learning algorithms to create predictive and proactive control sequences, replacing the reactive control sequences of the past. They will be able to leverage data from any system, in the building or the cloud, instead of just the data available in the local controller, to improve the effectiveness of the control sequence.
For example, whereas the state of the art local control system needs occupancy sensors to tailor ventilation to actual occupancy, a cloud-based portfolio automation software will make use of the best available occupancy data, whether from an occupant app, WIFI access points, people counting device, or access control system.
To reach the benchmark, the cloud-based portfolio automation software needs to be paired with a secure and intelligent edge, to monitor for local connection issues and mitigate in real-time.
Next, the software needs to be capable of implementing supervisory control for all building systems: state of the art sequences, continuously updated, with self-service management and modifications of schedule and setpoint standards.
The new benchmark requires a strong roadmap focused on ML capabilities, to make predictive and grid-interactive enhancements, while enabling open integrations and workflow automation, to enable modern O&M use cases.