AI Is Solving Construction’s Gray Work Issue

During this three-part series, we’ve talked about artificial intelligence (AI) in construction. The first article provided a reality check on what AI can and cannot do for construction project management. Next, we covered the risks of using AI and the impact of an overreliance on the technology. In this third and final installment, we take a closer look at how AI is solving the growing issue of gray work in construction, with a real-world example of how to tame it.

First, what is gray work, and should you be concerned? Gray work is what happens when employees lose valuable time doing work around the project instead of moving it forward. For example, if vital project information is located in multiple spreadsheets, PDFs or databases, employees may spend hours just tracking down the data they need to do their job. In fact, Quickbase recently conducted a survey of 1,000 workers and discovered they were spending 15-20 hours a week on this activity, losing valuable time and resources to gray work.  

Gray work is a growing issue in construction, given the project-based nature of the work. Additionally, since many construction companies are in various stages of digital transformation, they likely find themselves in a mix of technology tools and applications, along with paper-based processes, that are used in the office and on the jobsite. These technology solutions and outdated processes usually aren’t integrated, making it difficult for managers and business owners to see the big picture of each project’s productivity and profitability. By the time they can get their hands on relevant information, the project has entered its next phase. Or worse, it’s stalled.

AI can help construction companies eliminate gray work. Yet it requires more than introducing it into the workflow. For AI to be successful in automating processes, eliminating gray work and giving decision-makers accurate information in real time, it requires a solid foundation built on high-quality data and processes. 

At Quickbase, we call this a dynamic work management platform. This makes it easy to extract and integrate critical information from the various tools and apps that are used throughout the company, solving the gray work issue. Adding AI to the platform accelerates the time to deliver innovative solutions that automate processes and connect data, and if there is a shortcut or process specific to a project and not already on the platform, anybody can easily build an AI-driven app. Using AI prompts, employees are guided through the app building process, so that the final application both delivers what is needed and is connected to the rest of the company’s data.

Here is an example of how a solar company can tackle gray work and strategically introduce AI into its project workflows.

Solar Panel Company Shines With AI

A midsized solar panel company uses various databases, spreadsheets and apps to manage all the moving parts of their business. Along with managing people, vendors, prospects, customers and project installations, there are also inventory and supply chain challenges occurring regularly. Adding to this is the occasional building and/or grid infrastructure retrofit project. 

For each installation, the solar company must manage multiple subprojects. The details behind each subproject are often scattered across various tech tools. Other times, vital information lives in the project manager’s head or is handwritten on a clipboard by a site supervisor in the field. One rainstorm, shipment delay or failed building inspection can set the project back by days, if not longer. That unpredictability is, paradoxically, inevitable. Even as teams create “perfect workflows,” these situations can spawn gray work that knocks a project off schedule and leads to an erosion of productivity and profitability. 

Here’s how AI, as part of the solar panel company’s dynamic work management platform, can streamline processes and keep projects on track.

• Accurate cost estimates — Pulling in cost data from previous projects, the solar company can take it to the next level by creating an AI-powered app that includes the latest data on supplies and inventory. Now they have real-time supply costs aligned with previous project costs for more accurate bidding and budgeting. 
• Optimize scheduling and staffing — Based on the solar company’s historical project data, and the records of skills and certifications of employees and subcontractors, they can use AI to build project schedules that assign labor to align with each phase of the project.
• Connect the field and the office in real time — When teams are in the field for installations or maintenance, they now have all the information they need: delivery windows, alerts on delays, parts and tools, and a backup process to accommodate schedule disruptions. They can manage check-ins, roles and overall project progress. The information from this app flows directly into the company’s enterprise project management platform.  

For the solar company, streamlining processes and having confidence that decisions are being made based on current and accurate information enables them to:

• Improve the margins on every project
• Earn high customer satisfaction scores, resulting in more business
• Realize low employee turnover because staff are free to focus on more challenging assignments

The solar company example reflects the benefits of AI across most mid- and large-sized construction projects. It is one thing to have information; it is quite another to be able to use it proactively to get ahead of potential issues. AI-driven apps supported by a dynamic work management platform make it easier to manage and execute each project by automating routine tasks, eliminating reliance on paper-based forms, and spotting potential delays with enough time to make necessary changes to keep the project on track.