June 2016
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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.

Jason Burt
VP Product
Buildpulse

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Before 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 engagement.

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 analytics service.

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.

Discharge

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.

Weekly Report

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 fruit.

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.

Farway Heights

IOT is Short for a Lot More Data and More Systems to Maintain

Reliable Controls 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 prioritizing issues.

Cause at the end of the day it’s the team that makes the impact.



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