BuildOps is excited to share this predictive analytics usage report. Our goal is to help construction industry professionals understand the best technology tools and platforms. Our team identified hundreds of platforms and tools and we invite you to explore, compare, and learn how they can benefit your business.
Some of the largest infrastructure projects produce an average of 130 million emails, 55 million documents, and 12 million workflows. With vast amounts of data being captured from many sources, many firms can’t manage and process this much information.
What We Discovered
71% of construction executives rated prioritizing digital skills and making data-driven decisions as a winning move for businesses in the future construction industry ecosystem (Source – McKinsey).
Companies, like Skanska, are using employee, equipment, and material tracking to optimize the location of tools and resources (without this type of optimization – workers would walk an average of 6 miles per day to get equipment and materials needed for work). It’s simple optimizations like these that create the most impact on revenue. The top 5 most used solutions: IBM SPSS, 6sense, Radius, IBM SPSS Statistics, and Appier.
There are over 40 predictive analytics platforms on the market today and over 29,000 companies around the world that are leveraging them including a multitude of construction companies.
What’s a Business Intelligence or a BI platform?
Predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what happened in the past to provide the best assessment of what will happen in the future.
Construction Competitive Advantage Application – One example of predictive analytics in construction is the ability to create budgets that consider all possible factors that could emerge during a project, including regional labor and material costs. Predictive analytics can help you forecast how much of a particular material you’ll need for a job or estimate seasonal cash flow needs based on historical data and more.
Top Findings
- IBM SPSS, 6sense, Radius, IBM SPSS Statistics, and Appier are the top 5 most used solutions.
- In the past 10 years, we are seeing low to midlevel interest from construction companies in predictive analytics. (Google Trends data)
- Interest in predictive analytics among construction companies is widespread with a significant level of interest around the country.
- Predictive analytics and big data are a winning combination. Companies that used big data analytics in construction reported an 8% average increase in revenue (Source – BARC).
Global Data
How popular are predictive analytics tools in the construction industry? This Google Trends chart highlights the popularity of the predictive analytics topic among construction companies with interest barely existing about 10 years ago. For the past 7 years, there is a steady interest in the subject, Google tracked popularity ranging from 10 to 50 on the popularity index (1 to 100 scale) over the past few years (the chart below highlights the beginning of the interest in these tools among construction companies).
Below are the global predictive analytics platform usages across 6 million-plus websites. Compare and see whether construction companies differ when it comes to web analytics tools. Here are the top 40 technologies across the top few million websites on the Internet.
Comments and Other Findings
- Consider companies, like Skanska, are using employee, equipment, and material tracking to optimize tools and resources locations (if not for this type of optimization – workers would walk an average of 6 miles per day to get equipment and materials needed for work).
- Predictive visualization systems used with analytics tools reduce project timelines for construction projects, especially during the pre-construction phase.
- 40% of construction companies mention that frequent changes in worker safety regulations have been the top labor challenge during the pandemic (According to SoftwareAdvice). Companies with predictive analytics and planning capabilities were able to gain an advantage vs. non-users.
