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What are the best ways to use data analytics in building performance evaluation?

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Data analytics is the process of collecting, processing, and analyzing data to generate insights and inform decisions. In the construction industry, data analytics can help improve the performance of buildings by measuring and optimizing various aspects such as energy efficiency, indoor environmental quality, occupant satisfaction, and maintenance costs. In this article, you will learn about some of the best ways to use data analytics in building performance evaluation and how they can benefit your projects.

本文章的要点总结

Implement smart tools:

Utilize sensors and smart meters to gather real-time data on energy use, air quality, etc. This allows for adjustments that can drastically improve building performance and occupant satisfaction.
Engage in detailed analysis:

When project figures like cost variance (CV) are off-target, investigate the specific causes. This helps your team correct issues, optimize operations, and ultimately enhances project outcomes.

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1 Data collection methods

The first step in using data analytics is to collect relevant and reliable data from various sources. Depending on your objectives and scope, you may use different methods such as sensors, smart meters, surveys, audits, or building information modeling (BIM). Sensors and smart meters can provide real-time and granular data on energy consumption, temperature, humidity, lighting, air quality, and other parameters. Surveys and audits can help you assess the occupant feedback, comfort, health, and behavior. BIM can help you integrate and visualize the data in a digital representation of the building.

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David Vogel

Solar Energy Mentor I Streamlining Federal Grant Approvals & Material Distribution for Commercial Solar Projects I Retired CEO Project SunRize I Pastor Church of Unity Society
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Ever wonder how your building is really performing, beyond just bricks and beams? Data analytics is your secret weapon. I've seen buildings transformed from energy guzzlers to efficiency exemplars just by the right use of sensors and smart meters. These tools provide real-time insights into energy consumption, air quality, and more, allowing for precise tweaks that lead to significant improvements. Add in occupant feedback from surveys, and you're not just optimizing a structure, you're enhancing lives. Data isn’t just numbers; it's the blueprint for smarter, more sustainable buildings. #divineintervention #gabenfreude

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2 Data analysis tools

The next step is to use appropriate tools to analyze the data and generate insights. There are many tools available in the market that can help you with data analysis, such as Excel, Tableau, Power BI, or MATLAB. These tools can help you perform various tasks such as data cleaning, filtering, aggregation, visualization, modeling, and reporting. You can use these tools to create dashboards, charts, graphs, maps, or tables that can help you understand the patterns, trends, correlations, and anomalies in the data.

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3 Data-driven optimization

The final step is to use the insights from data analysis to optimize the building performance. You can use data analytics to identify and implement improvement opportunities, such as retrofitting, commissioning, tuning, or controlling the building systems and components. You can also use data analytics to monitor and evaluate the impact of the optimization measures on the building performance indicators, such as energy savings, carbon emissions, occupant satisfaction, or productivity. You can use data analytics to compare the actual performance with the design or benchmark performance and adjust your strategies accordingly.

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4 Data analytics benefits

Data analytics can be a powerful tool for evaluating building performance, offering a range of benefits such as improved energy efficiency and environmental sustainability, enhanced indoor environmental quality and occupant well-being, reduced operational and maintenance costs and risks, increased value and competitiveness in the market, and support for the decision-making and communication processes of stakeholders.

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Hayden J. Peairs

Project Resourcing
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Stop looking at data as something to hide! From a performance standpoint, if PF, SPI, SV, CV, etc etc etc are outside of management's tolerance range, DIG DEEPER. Hopefully you've organized your WBS(es) to identify exactly what account codes within each discipline are adversely affecting your numbers. Was your initial estimate correct? Is your project team capturing expenditures and progress correctly? Help your team understand what you're seeing and guide them on how they can improve it so that everyone is pleased. The mantra of "dig deeper" can be applied to any metrics found on projects from P&Ls to safety scorecards. Time is often of the essence but creating a simple tracking system gives data value and gives project teams leverage

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5 Data analytics challenges

Using data analytics in building performance evaluation can come with some challenges, such as ensuring data quality, security, and privacy. It is also important to select the right data collection methods, analysis tools, and optimization techniques. Data complexity, volume, and variety must be considered, as well as integrating and aligning the data from different sources and systems. Additionally, managing the data ownership, access, and sharing is a key factor.

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6 Data analytics best practices

To ensure successful data analytics for building performance evaluation, you should clearly define objectives and scope, plan and design data collection methods and analysis tools, validate and verify data and results, interpret and communicate insights and recommendations effectively, and implement and monitor optimization measures. Validate accuracy, consistency, and relevance of the data and results. Support recommendations with evidence and examples. Evaluate performance and outcomes regularly and objectively.

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Cynda Jones, MBA

Doctoral Student | Behavioral Scientist | Blockchain Strategist | Public Speaker | On a mission to leverage psychology and blockchain for a safer and more secure Internet.
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I have found it helpful to assess the level of asymmetry within the team targeted to use the analytics as well as the organization. In my experience, the early stages of analytics building is fraught with people afraid to admit they don’t know how to use analytics and employees untrained to deliver meaningful analytics visualizations. Pretty pictures don’t always provide actionable insights. Don’t assume people will just get it. I have had to decommission poorly designed analytics and teach the core skills needed to ensure the analytics designers understood statistics, strategy, storytelling and presentation. It is also important to offer education to employees to help them understand and embrace the use of analytics.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the best ways to use data analytics in building performance evaluation?

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1 Data collection methods

2 Data analysis tools

3 Data-driven optimization

4 Data analytics benefits

5 Data analytics challenges

6 Data analytics best practices

7 Here’s what else to consider

Construction

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What are the best ways to use data analytics in building performance evaluation?

1

2

3

4

5

6

7

1 Data collection methods

2 Data analysis tools

3 Data-driven optimization

4 Data analytics benefits

5 Data analytics challenges

6 Data analytics best practices

7 Here’s what else to consider

Construction

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