AI is already revolutionizing the industry. During our CEO's latest participation at the Technology Week in Barcelona, he discussed how AI for project planning and scheduling is changing the discipline for the better but, there is one aspect that is being overlooked: learning from past projects & using those learnings in new project plans.
A brief overview of a project schedule lifecycle
When creating a detailed schedule for a new construction project, a planner must manually input the specifics of every task to be completed. A typical construction project involves thousands of tasks, requiring planners to manage and provide extensive information, from task duration and sequence to resource type and quantity.
Planners usually depend on past productivity data collected by their company and their own expertise to estimate figures for the new project. This process is not only time-consuming and labor-intensive but also susceptible to judgment errors, leading to suboptimal schedules.
For example:
Inexperienced planners may lack the past exposure needed to reliably assist them in new situations.
The construction company’s productivity database may be imprecise, irrelevant, outdated, or more frequently than not, inexistent.
Extracting insights from large databases of past data is manual and challenging.
Due to these factors, planners often resort to guesswork when producing detailed schedules, which can lead to potential productivity losses, hidden costs, and risks associated with poor scheduling.
Once the baseline schedule is approved, this is the schedule that is followed for the project execution if all goes well. This schedule sees weekly or monthly progress updates based on the progress in the field. From these updates is where most if not all project analysis is done: S-curves, Earned-Value Management, Percent Plan Complete, etc.
The execution phase is the most important for the project's success. It is where the project meets its objectives, is delivered successfully or fails (often miserably), and produces the headlines we are all used to. This may be the reason why most software solutions are focused on this phase of the project. It’s the most complex, the most critical, and where the cameras are!
AI era of project planning
Artificial Intelligence (AI) powered solutions are no exception. There are many project management, scheduling, progress management, analysis, and reporting software out there that leverage AI to improve or automate part of the work required during the project execution phase.
These solutions deliver value to project teams and help them manage the enormous complexity of a construction project in execution. But, the main problem faced by teams in this phase is that there is no longer any room, time, and options to maneuver and make changes if things go wrong. The graph below illustrates this point:
Once in the production phase, the cost of changes increases dramatically for little added value. The value isn’t delivered here, the value needs to be identified and delivered early in the project lifecycle.
Using AI to “dig” project graves
What is not known by many (and hopefully shocking to the reader), is that most projects have significant parts of the scope where planners used some form of guesswork or “guesstimating” when producing the plan.
The main reason for this is simply a lack of past productivity data from the company in an easy-to-use, readable, and actionable way.
At Frontline we believed it should be as simple as:
I need to plan the Low Voltage Installation activities of an industrial warehouse facility in the UK.
Have, in 10-20 seconds, a list of all Low Voltage Installation activities on industrial warehouses from past projects that my company has done, with insights (duration, productivity, variance)
We set ourselves up to do it, and we have done it -at least the first step. The 1st version of Frontline Trender™ is ready. Check it out:
We are testing it with current and new clients who want to accelerate 2x the time they take to develop a new project schedule by increasing 10x the accuracy and confidence in the specific details of each task that makes the project.
If you want to be among the first users, reach out to us! Contact us or fill out the form below for a free demo.
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