As a senior executive with responsibility for a geographically spread building portfolio of sites, the absence of relative performance data makes it difficult to take anything but a tactical approach to energy management.

Senior executives with responsibility for extensive portfolios of small to medium sites are under constant pressure to reduce operating costs, meet emissions reduction goals and deliver efficiency gains. They know there are opportunities for improvement, but they have no way of comparing their buildings, understanding where to focus to achieve the best ROI or knowing how to determine the size of the prize.

Understand where to focus to deliver ROI

Senior executives need to understand the savings potential across their portfolio and where to focus time, resources, OPEX or CAPEX to achieve the best return on investment before performing expensive audits and deploying operational tools. Otherwise, significant time and money can be wasted chasing diminishing returns.

There’s no question that advances in data capture and analysis technologies have facilitated more modern fault detection techniques and tools that help pinpoint actions required in single buildings. But these tools typically rely on BMS data, which is not available for the average small to medium site. The solution for this type of building portfolio lies in making use of underutilized but valuable meter data and taking a top-down approach.

Software to drive portfolio benchmarking

IBM Envizi extracts insights from meter data to deliver Portfolio Benchmarking Analytics, a software-driven solution to support a strategic approach to managing your building portfolio. In a single dashboard, the tool compares the energy intensity (both electricity and gas) of all buildings in your portfolio and ranks them by energy, cost and emissions savings potential so you can prioritize action based on ROI.

Historically companies with portfolios of small to medium sites have either avoided benchmarking all together or have conducted labor intensive analysis of invoice data. At best, this delivers a crude, one-dimensional view of portfolio-level energy analysis as it’s unable to take into account the many variables that impact energy consumption and energy intensity, such as weather and energy time of use.

IBM Envizi calculates intensity metrics using granular data to assess building performance, bringing together time series interval meter data with dynamic variables such as floor area, operating hours, weather conditions and even rates of production (where appropriate).

The software processes groups of like buildings into cohorts in order to calculate benchmark intensities for each cohort. IBM Envizi then applies automated regression models across each cohort to identify buildings demonstrating intensity outside the group norm. Once the outliers have been identified the software calculates the savings potential by monetizing the difference between these outliers and the benchmark and what impact bringing them in line with the norm would have in terms of potential cost, emissions and consumption savings.

This software will be of most use to senior managers with portfolio responsibility for energy or sustainability. IBM Envizi decarbonization solutions are best suited to organizations that operate large portfolios of small to medium-sized commercial buildings that have utility interval meters (or sub-meters) installed.

Envizi’s portfolio benchmarking analytics compared to the conventional approach to energy benchmarking

Envizi method

• Dynamic analysis, real-time access to interval data
• Software does the heavy lifting to capture and analyze a range of data that impacts energy intensity and costs.
• Buildings with similar attributes are grouped into cohorts for accurate analysis, allowing the system to account for the unique characteristics of the building being analyzed.
• Factor in the different attributes of large buildings and retail type properties (e.g., bank HQ building vs. shop fronts)
• Not only benchmarks buildings against each other, but also monetizes cost savings potential in underperforming buildings and breaks down the results to individual time of use bands. Any changes made to the equipment or meters also have an audit trail.

Conventional method

• Static analysis, based on one moment in time while energy consumption changes on monthly, seasonal and yearly basis.
• Labor intensive analysis, based on invoice data, crude and one-dimensional view of portfolio level energy analysis, unable to incorporate the many variables that impact energy intensity such as weather, floor area, building purpose, and time of energy use.
• Only focus on large complex buildings with BMS installed.
• Does not differentiate small to medium buildings from large buildings.
• Not intuitive for non-engineering people to assess the “size of the prize.” Not as accurate and rigorous.

Build your sustainability data foundation, streamline reporting and accelerate decarbonization with the IBM Envizi ESG Suite