True Analytics™ - Energy Savings, Comfort, and Operational Efficiency
|Data Driven Building Management
The real secret to success with this data was how we used it. We enabled teams to engage with one another towards a common goal and get more done.
starting an analytics company for buildings I lived another life in
the startup world. I had worked in many roles developer, analyst, and
product manager for companies that analyzed data to make operational
improvements and recommendations for companies. We analyzed the
operational logs from companies such as Google, Microsoft, and Walmart
telling them how to improve their sites and increase customer
In many ways that space is the future of where analytics in buildings can be. But though we could measure and analyze anything from what people clicked on to what they searched for the real secret to success with this data was how we used it. We enabled teams to engage with one another towards a common goal and get more done.
What Automation and Software Will do to the Industry (no robots will not take over)
While I write this article we have processes that are
automatically discovering data in Building Automation Systems. Once
identified the data is automatically standardized to a tagging schema
based on Haystack and ASHRAE standards. This automated process allows a
few people to connect hundreds of buildings a month to a modern
People’s first reaction to this is to worry about robots replacing them. It makes sense because they often think their value add is aligning data or shifting through a few controls to find ‘unique’ issues even though the issues in buildings are not new or unique. PNNL, ASHRAE and many others have documented these.
But what people are missing is that automation unlocks their time. Facility managers who want the most bang for their buck can focus teams on specific issues without having to dig through raw data. The GSA, who recently presented at NFMT’s High-Performance Buildings conference, estimated that data driven approach to facility management not only saved them 8-10% in energy but also recovered .20 -.30 a sqft in operations and management. One customer with 90 buildings had two full time techs digging through data to look at systems. Over the course of a year they verified operations in 40 of those buildings. An automated process can verify operations in all 90 buildings every 5 minutes. Freeing up that team to fix issues that appear.
Building Better Relationships Using Data
Modern analytics tools are a feedback loop that help
more than just facility teams. Commissioning agents and controls
contractors that once spent days trying to align data and setup basic
trends are now spending that time working with their customers on
fixing issues in their buildings. They have targeted reports that show
areas that schedules, set points, and sequences can be adjusted. They
are creating value add services, no longer spending their valuable time
just making sure the database is online or the data is correct.
Continuous monitoring has allowed them to make the transition from transactional to relational services. They are able to discover things such as issues that occur outside of occupied hours that are often not caught. For example weekend sequences that the Monday through Friday team would never catch.
The service providers use automated analytics as a diving off place for customer engagement. They check up on the low hanging issues that require no capital expense to follow up with larger improvements that fall into capital management.
Choose Your Key Performance Indicators
If you're bringing data and analytics into an
organization it is good to start with a conversation around goals.
Improving operations while maintaining comfort for tenants is
achievable but it requires visibility into both. Once these are
established matching the goals to KPIs (Key Performance Indicators)
will give you a guide to where you should gather data. We normally look
at comfort along with energy savings which we break into equipment
runtime and performance.
Your KPI’s should show you areas for improvement. They are not
dashboards that show graphs that are disconnected from the underlying issues. While
energy and EUI are good starting points, they can lead to a false sense
of completeness. We had one customer who had done a great job of
improving performance in their buildings. They had a number of
buildings with 90s in energy star ratings, after we installed there
were still roughly 10% savings in those buildings. All low hanging
Below is a common occurrence, equipment running 24/7 so if you were to attempt regression analysis on the kwh data you would miss it.
IOT is Short for a Lot More Data and More Systems to Maintain
The sheer amount of data and information coming from
systems can be daunting. A 100,000 sqft building can have tens of
thousands of data points. Summed over a portfolio of buildings keeping
track of and maintaining that data can be daunting.
In addition, more affordable hardware is enabling more of the building stock to come onto the market increasing the amount of data to shift through. Where once controls made economic sense in larger buildings smaller buildings are becoming more available.
While the number of sensors and controls being installed is increasing the size of most facility teams is not. To successfully mange these additional systems a clear plan needs to be in place. Sensors should be prioritized based on the impact they have on systems and a monitoring plan should be set to automatically check these sensors for variances or issues. For example the impact of an Outdoor Temperature sensor can be significant compared to an individual thermostat. Having an analytics service take care of monitoring and prioritization allows teams to increase time between manual service while reducing the impact of faulty sensors.
Analytics With a Purpose
There are large opportunities to leverage data and
analytics in building operations, but to be successful one has to
remember what automation and analytics are for. Modern analytics
services should reduce the amount of time teams spend looking for
issues or verifying things are running within expected bounds. They
should help teams improve their workflow and provide assistance in
Cause at the end of the day it’s the team that makes the impact.
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