Data analytics and business intelligence (BI) have been getting a lot of press recently due to their increased use in the construction industry. "Number crunching has always been a big part of construction — a commonly heard phrase is that construction companies are accounting companies which happen to erect buildings," says Bernard Marr, How Big Data And Analytics Are Transforming The Construction Industry. The most significant change recently has been the abundance of data available to analyze.
Construction has traditionally been an under-digitized industry with only accounting data being structured and somewhat available. Now companies are leveraging many data sources and multiple data types — and not just accounting data anymore. The industry is no longer restricted to what is found in a SQL database. Data can now be automatically extracted from unstructured sources such as documents and photos which was previously problematic. This data can then be accompanied by more structured sources from project management solutions such as Procore, Autodesk, Plangrid and ERP solutions such as Sage, Viewpoint, and CMIC. There are also emerging data sources from IoT devices and sensors that can be leveraged as well. The ability to pull data from multiple sources into leading business intelligence tools such as DOMO, Tableau, and PowerBI have made it easier for companies to begin evaluating their data.
"Although data analytics may appear to be the magic bullet, the technology doesn't come without challenges." Stated Edward A. Sutton III, Principal Consultant and Systems Manager for Black & Veatch in his ENR article Data Analytics: Enabling Next Gen Construction
Challenges in harnessing data
With all of this "new" data, it is crucial to have a plan of attack on how you are going to handle it. Data is coming from different systems in various formats and needs to be somehow connected. An easy way to get started aggregating and understanding your data is to utilize a business intelligence software product such as PowerBI. PowerBI has a vast array of connectors that have been developed by both Microsoft and by partners to tie into many of the popular ERP and PM solutions utilized in construction today. However, these out of the box solutions may not solve all your problems and additional mapping, clean up, and normalization is usually required to leverage the data entirely.
Genuinely leveraging your data requires a much larger roadmap which many GC's have not even scratched the surface of. Conversations about data warehousing, custom connectors, and refresh rates should happen in order to develop a comprehensive data strategy for your organization. Business processes, too, may need to be harmonized across projects to enable meaningful data collection, comparisons, and analysis. However, that should not stop you from getting started.
Image courtesy of ENR
Start with the data you already have
Identifying how to align your data with your corporate goals can be a tremendous task. For this reason, many GC's have been hiring data scientists. Within the last year we have seen McCarthy, Suffolk, XL, and others hire these experts to define a data strategy and begin to mine their large datasets. "We needed someone to help us focus on being more proactive with our data," according to DJ Phipps at XL Construction. XL is a long-time customer of Procore, so they have years of data available.
Since much of the AEC industry is focused on productivity and safety, many companies are applying their data and analysis investments in these areas. Measuring and predicting key performance indicators (KPIs) based around production requires data from several sources. Data from timecards, schedules, quantity take-offs, and accounting are all needed to determine valuable insights on worker productivity. Safety analytics is another hot area for tracking, measurement, and prediction. Smartvid.io is helping to make jobsites safer by automatically identifying safety hazards in jobsite photos that already exist in systems like Procore, Autodesk, and Oxblue. Smartvid.io also recently partnered with Suffolk to analyze nearly ten years of data across 360 projects. Suffolk's Chief Data Scientist, Jit Kee Chin, presented the results of the collaboration at ENR Futuretech — a statistical algorithm that accurately predicts when safety incidents will happen simply by analyzing jobsite photos. Tools like these are estimated to help Suffolk increase productivity from 14 to 20 percent in a few years.
While at first glance all of this may seem daunting, data analysis represents a massive opportunity to improve operational efficiency, reduce risk, and create a real competitive advantage for GCs who establish expertise in this area. As with any new initiative, it is normal to start small and begin digesting the data you have from ongoing as well as previously completed projects (like photos!) Find out what tools already exist to analyze your data and begin finding answers to approaches to improve your business results today.