Technology

Construction Intelligence on Tap

Contractors are modernizing and scaling operations to take advantage of untapped potential.
By Anne Hunt
August 31, 2021
Topics
Technology

Technological advances in construction go far beyond cordless power tools and long-lasting, quickly-recharging batteries—although, those are both awesome. Many of today’s high-tech construction “tools” allow teams to better collect, manage, analyze and share data in order to make smarter, more profitable decisions in the field, office and executive conference room.

With the invention of the internet and cloud-based, real-time computing power and processing, the face of how contractors handle virtually every aspect of business today across the globe is changing. Innovations such as machine learning and predictive data analytics can do in seconds what could typically take days, weeks, even months to do through manual processes or even legacy software programs. That’s why more and more contractors are implementing these technologies into their operations to streamline workflows, improve business processes and reduce profit fade.

A Look at How Machine Learning and Predictive Data Analytics Work

Machine learning is already integrated into everyday life. Think about how cloud-based shopping platforms like Amazon and eBay choose which ads to display. The ads are based upon buying and search habits. Facebook and Instagram use similar learning technologies to choose the “people you may know” or target the user with specific ads or content.

Machine learning consumes large quantities of complex data, identifies patterns in it and distributes reliable, effective and repeatable results. It sifts through loads of data to find the key pieces and share them at the right time, with the right users. This process, also known as Artificial Intelligence, involves computer algorithms utilizing grouped data to detect patterns and predict outcomes, and is used by the majority of today’s mobile apps. This technology allows businesses in nearly every industry to take raw information, create strategically segmented data cubes, transform related cubes or data sets into intelligence and even make smart decisions, automatically, based on that intelligence.

Today, machine learning and predictive data analytics are being applied to aid and inform project stakeholders in making smart, actionable decisions throughout the entire construction project lifecycle. For instance, industry research found that larger infrastructure projects create an average of 130 million emails, 55 million documents and 12 million workflows. Would anyone on the project team be able to handle that volume of data? Challenges such as this—the ability to access massive quantities of data—are often what moves companies to embrace technology.

Contractors See Value in Machine Learning and Predictive Analytics

For construction project teams, machine learning and intelligent data tools bring new power to the table for contractors, helping them to:

  • recommend actions to make projects more efficient and profitable;
  • quickly analyze complex project data;
  • make smarter, real-time decisions;
  • automate cumbersome workflows; and
  • make accurate predictions and forecasts for future work.

As the economy rebounds and contractors look to grow their businesses and profits, machine learning can play a lead role. Contractors are transforming their operations with modern technologies to take advantage of machine learning and predictive analytics. Working in the cloud, with connected solutions and data allows contractors to deploy analytics and machine learning tools that can process massive amounts of data, assess patterns and make intelligent decisions.

A Singular Source of Construction Intelligence

When there is a single set of connected data across different construction departments or disciplines, this is where machine learning and predictive data analytics can really shine. Think of standardized data as the fuel that machine learning and predictive analytic tools need for optimal performance.

When data can be pulled together and standardized, such as from wearable technologies, smartphones and mobile applications, back-office accounting and project management solutions and more, machine learning and analytic tools can be easily applied to:

  • easily analyze and forecast job costs;
  • quickly identify project risks;
  • better track worker productivity;
  • optimize workflows and processes; and
  • set and review benchmarks; and much more.

All of this can be done using historical data to train a machine learning model to predict job performance and other metrics.

Bid Smarter, Win More Work

Beyond the day-to-day management of projects, machine learning and predictive analytics can also help contractors win more profitable work. Project estimating teams can utilize relevant data culled together from previous projects to better inform how they assess future work. They can hand-pick the best possible opportunities and precisely bid them to maximize profit opportunities.

In a world where even a few hundred dollars can make or break winning a job or not being profitable, this is more important than ever. Especially as we begin to emerge from a global pandemic and more infrastructure and construction work becomes available, bidding is more competitive than ever.

Simplify Work, Empower Employees and Operate Safer Projects

Machine learning and artificial intelligence doesn’t just apply to job costs and progress or bid packages. Contractors are using intelligent workflows and automation across all aspects of their business. Some examples:

  • Business development teams utilize data analytics to identify new business opportunities and build stronger customer relationships.
  • Project managers are using machine learning and AI tools to better determine crew utilization and efficiency with normalized data metrics to improve behaviors and output.
  • Safety managers are reducing emergency situations and critical safety accidents on the job with real time monitoring of worker safety combined with hours worked to predict critical safety situations.
  • Both project managers and HR teams are using machine learning workflows to predict employee retention, forecast the number of employees needed for projects, place the right workers on the right jobs and much more.

Though there is still boundless untapped potential, machine learning, data analytics and AI are no longer in their infancy stage. More and more contractors are modernizing and scaling their operations today to take advantage of these applications and reap the rewards.

by Anne Hunt
Anne Hunt leads the incubation and innovation of new data first services to revolutionize Viewpoint’s customers and the construction industry at large. Previously, Anne worked in the Trimble Transportation vertical where she led analytics initiatives and applied statistical theories of collecting, analyzing and interpreting quantitative data using tools such as python and Tableau. Anne has a master’s degree in Analytics from Villanova University.

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