All signals point to growth opportunities in construction and manufacturing. The economy has added 670,000 construction jobs since January 2021, and 85% of middle-market manufacturers expect production increases over the next 12 months.

Construction and manufacturing are complex industries with challenging operations and low margins. Digital Trailblazers leading transformation initiatives in these industries can’t pursue hyped-up technologies and long-term AI experiments.

At a recent Coffee With Digital Trailblazers on Pragmatic Ways to Transform Work Management in Complex Industries, we discussed what makes these industries complex and how shifting to dynamic work management leads to pragmatic AI applications.

What makes the manufacturing and construction industries complex?

“When you talk about industry 5.0 in manufacturing and construction, they rely significantly on the choreography of people, equipment, and material with work in multiple locations including offices, shop floors, job sites, and job site trailers,” says Tim Douglas, GM of Construction at Quickbase. “There’s a lot of variability in how they deliver a product or a building and work that needs coordination – including the data to deliver their product or project on time, with high quality, and with safety for the people doing the work.”

Other factors also drive complexity in industries like manufacturing and construction.

• Many stakeholders. Owners, general contractors, architects, subcontractors, trades, equipment delivery companies, and building product manufacturers operate in construction projects. In manufacturing, there are OEMs, outsourced design, business process outsourcers, and supply chain partners.
• Employees, contractors, and robots. In construction, many people working at the job site are self-employed or work for different companies. In manufacturing, people on the shop floor work alongside robots and cobots. Construction companies and manufacturing must also follow union regulations.
• Worker safety. Businesses must adhere to the latest OSHA regulations and ensure workers are trained for the job they’re assigned and the equipment they’re using.
• Low margins. Construction projects are often awarded to the lowest bidder, and unit costs are a primary factor in manufacturing. Lawsuits, insurance claims, medical emergencies, malfunctioning equipment, and supply chain issues can easily make a job unprofitable.   
• Complex scheduling. Managing a multi-party workforce, scheduling downtime for equipment maintenance, working around weather issues, and timing deliveries require day-to-day management.
• Evolving regulations. Construction regulation changes in 2024 include enhanced building safety regulations, changes in contract law, and labor law updates, while manufacturers must consider the evolving global sustainability regulations.
• Shrinking talent pool. In construction, there are almost twice as many workers aged over 55 than under 25, and in manufacturing, those over 55 are almost three times greater, according to The Bureau of Labor Statistics’ 2023 data.
• Complex system integrations. While every company has its ERP, CRM, HCMS, and document management systems, manufacturers have systems for manufacturing execution (MES), supply chain (SCM), product lifecycle (PLM), quality (QMS), warehouse (WMS), and asset management that require integration. Construction companies may have multiple systems for CAD/BIM, project management, scheduling, estimating, bidding, safety, and field management to cover different types of projects and owner preferences.
• Rapidly evolving technologies. Industry 5.0, smart buildings, smart cities, and smart manufacturing are all in their early stages and will drive new technologies and operational changes.

Complex businesses can’t be managed with Gantt charts and spreadsheets

Complex industries like construction and manufacturing have systems of records that are often too rigid to support all the day-to-day variability that happens on shop floors and construction job sites.

“There’s no single system that will choreograph a manufacturing supply chain or a construction job site,” says Douglas. “Not only are they choreographing different resources, companies, and people, it’s the disconnected aspects of those systems supporting them that lead to a lot of this information falling through the cracks.”

The workflow, data, and communication that falls through the cracks is gray work, where 45% find their software solutions neutral or negative for productivity.

How have workers in construction and manufacturing addressed gray work in the past?

“The most widely deployed tool in construction technology today is Excel,” says Douglas. “When you have information from many different systems of record and the gaps are somehow being filled by uploads and downloads through Excel, it only exacerbates the problem.”

According to the Quickbase Research Report, 58% of people surveyed spend less than 20 hours per week on meaningful work that drives results for key projects. Creating spreadsheets to move data between systems, responding to long-running operational emails, and communicating schedule changes with Gantt charts is no way to manage work in complex industries.

Examples of dynamic work management and pragmatic AI

Scaling from gray work to dynamic work management and onto pragmatic AI requires defining a problem statement, stating a long-term vision, and starting with some practical first steps. During the Coffee Hour, we reviewed several opportunities to reduce the gray work and begin the transformation:

• Construction management solutions with configurable apps for prefab tracking, bid management, and site safety audits. “Over the years, companies have developed very sophisticated datasets around their historical estimating and bidding,  but they don’t have insight into their performance because the data is locked in 800,000 different spreadsheets in specific project bid packages,” says Douglas. “They drive consistency in their bids, so it’s  an area ripe for AI models to look into to better understand specialty contractor performance, material cost, and product performance after the fact.”
• Dynamic work examples in manufacturing include converting checklists to analytical workflows, optimizing equipment maintenance schedules, and shop floor management solutions.

In a previous article, I shared five steps to simplify the planning and adoption of dynamic work solutions in construction, manufacturing, and government. I also wrote about how committing to technologies that improve jobsite safety and purposeful career development helps construction companies attract top talent.

Growth opportunities are catalysts to drive operational changes. In complex industries like construction and manufacturing, the opportunity to transform to dynamic work management and pragmatic AI will create significant advantages for businesses to win jobs, improve safety, and attract top talent.  

This post is brought to you by Quickbase.

The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Quickbase.