In today’s world of high technology, we are increasingly getting access to all kinds of real time and historical data. Much of this is from building automation systems that control HVAC, lighting, security, fire alarm, shading, water management, and energy management. But also data from external sources like utility providers, financial performance, production results, employee retention and satisfaction, and many other relevant sources.
Making the Best Out of Building Data
The question is how can we make the best use of all of this data to reduce costs, increase profitability, increase production, improve employee morale, create a smarter greener building, or whatever our goals may be toward enhancing our business operation. Data analytics can help achieve those goals but in order for data analytics to work the investment in the process cannot stop with the initial implementation.
Detecting Building Problems with Data
Data Analytics “software” providers along with the organizations that “implement” the data analytics, like MACC, will provide intelligent algorithms that find, and sometimes automatically correct, specific problems that the system is programmed to detect. They will also provide the capability to look for and analyze other issues outside the programmed intelligent algorithms as well, but this needs to be done by people trained to do it. And these people need to do this on a regular basis. Additionally, any problems that the analytics system detects need to be reviewed and acted upon by someone specifically assigned to correct these issues. Detecting problems is only part of the process.
Consider Return on Investment for Each Corrective Building Improvement
The person or organization in charge of the decision making must stay involved so that proper actions can be determined relating to each issue. Detecting a problem that costs $300.00 to fix but only saves $50.00 a year might not fall within the expected return on investment objective. However, should it cost $50.00 to correct and save $300.00 per year then the right decision is easy.
Smart Building Algorithms
As a result of the continual review of data, new issues can be uncovered and new specific smart building algorithms can be added to the analytics engine that would then continually monitor the connected building(s) for that new condition and alarm the operators when it is detected as well. However, the detection, reaction, refinement, and related data analytics process cannot stop or most of the benefits will stop along with it.
Capturing Data Analtyics in a Building Isn’t a One-Time Investment
Data Analytics can produce some very impressive results and continue to produce those results year after year. But it is not a one-time investment and continual maintenance should be associated with it or the results will eventually diminish. As the right algorithms are developed, the level of maintenance can be reduced over time; however, someone needs to always remain assigned to act on the information generated from the data analytics.
Tridium and Sky Foundry Data Analytics Software
The two most prominent Data Analytics software providers are Tridium (Niagara Analytics) and Sky Foundry (Sky Spark Analytics). There are others as well and they all have their strengths as well as weaknesses. These two providers, and most of the others, do not provide the actual implementation though. Data Analytics is actually implemented through professional organizations like MACC, Siemens, Trane, or Invensys and the related regular maintenance is also provided through these organizations.
To Learn more, download this Niagara Analytics Framework Brochure or watch this brief video:
Picking the Right Building Data Analytics Software Provider
The software provider you choose is important but the implementation provider is even more important. The organization that implements Data Analytics makes the greatest difference in creating the Smart Building system that is the goal of all Data Analytics implementations. MACC can provide an honest evaluation of the Data Analytics programs and which one is best for your particular application. Contact us and let us how to best implement and maintain your Smart Building Data Analytics program.
