Andy Steele, chief strategy officer of Buildots, looks at how AI progress management is a powerful partner for lean construction principles, bringing more projects in on time and on budget by helping project teams to work smarter, not harder
Over 75% of construction projects are delivered late. Contrary to popular belief, over half of these delays are caused by (preventable) operational inefficiencies, not external factors like weather or design changes.
Lean construction is a project management methodology that emphasises collaboration and continuous improvement rather than hierarchical decision-making and fixed workflows.
It has been around since the 1990s, but its popularity is growing steadily as the industry realises that ‘working harder’ isn’t a viable way to solve systemic inefficiencies.
However, most project teams still rely on subjective reporting and rough estimates to track progress, which prevents them from maximising the value of the six lean tenets.
Teams need objective data to get the most out of lean construction. This is where AI comes in, unlocking accuracy, detail and insights that can’t be captured with the human eye.
Here’s how AI progress management enhances each of the six lean construction tenets.
Generating value
Generating value – prioritising clients’ needs and eliminating anything that doesn’t contribute to them – sits at the heart of lean construction.
However, figuring out how to do this can be tricky. After all, clients typically view the construction process from a distance, while project teams live and breathe every minute detail. It can be hard for those not immersed in construction day in and day out to understand how their actions affect what happens onsite.
AI progress management bridges the gap between clients and project teams. By analysing vast amounts of data, AI can turn complex information into accessible insights so all stakeholders can see how their decisions impact overall value delivery.
Eliminating waste
In lean construction, the “Eight Deadly Wastes” – defects, overproduction, waiting, non-utilised talent, transportation, inventory, motion and excess – represent areas where inefficiencies can creep in, leading to rework and delays.
AI progress management addresses these wastes by tracking each trade’s progress, so project teams can catch and correct errors early before they lead to costly rework.
AI can also inform resource allocation decisions by accurately forecasting potential delays and recommending the pace needed to meet planned completion dates.
Focusing on flow
Flow is a lean construction cornerstone. But to get this right, you need a clear idea of when and where each trade is working, which can be hard on large, complex projects. Even with daily huddles, miscommunications happen.
AI progress management improves communication by providing accurate data on progress down to every last plug socket, pipe and piece of ductwork. This allows for dynamic schedule adjustments and, over time, improves weekly lookahead plans.
Kyle Nitchen, senior project manager at leading US contractor Layton Construction, notes: “I often compare complex construction projects to rolling a snowball down a mountain. You can make adjustments quite easily when you’re at the top of a mountain with a small snowball. That’s almost impossible when you get closer to the bottom of the mountain – ie the end of the project.
“When you have a steady stream of data at your fingertips, you can spot problems early and make those smaller adjustments further up the mountain before they escalate.”
Continuous improvement
Addressing constraints and consistently implementing what you learn is the foundation of continuous improvement. But to do this, you need to find the root cause of problems, ideally before they spiral out of control. This is tough without accurate data.
Consider this example. A trade might tell you they’re around 75% done, putting them bang on schedule. Usually, you’d have to take this at face value. But with AI progress management, you can look closer and find that this trade is working across multiple floors without completing them, preventing others from starting their work. Now, you’ve spotted an issue and can take steps to get back on track.
Optimising the whole
This means prioritising overall project success over individual targets and can require a mindset shift for teams used to focusing solely on their own performance.
Chris Vine, project superintendent at Hensel Phelps – ranked in ENR’s top 20 contractors by revenue – explains: “Years ago, we still thought, ‘as long as I do what I need to get done, that’s good’. Eventually, you learn that your sole success doesn’t necessarily translate to project success.”
AI progress management supports optimising the whole by giving an accurate big picture view of projects, ensuring activities align with overall goals rather than being driven by individual trades’ competing needs.
Respect for people
Respect for people is about creating a work environment that values wellbeing. This is difficult in an industry known for demanding schedules, overtime and burnout.
By streamlining processes and minimising errors, AI can help the industry return to sensible working hours.
Moreover, it can defuse conflicts by providing a shared source of truth. After all, accurate data removes the guesswork and finger-pointing from project meetings, fostering a less adversarial environment.
AI and lean construction are powerful partners
Integrating AI progress management with lean construction isn’t just a tech upgrade. It’s a strategic move toward a modern, efficient industry. That’s because AI offers lean practitioners the means to truly apply all six tenets in the field. We’ve compiled more of our thoughts on this topic in this white paper.
