Challenge 2:
Spiralling costs

“Time and budget are usually the main constraints on building projects, but here both counted for nothing.”
Rowan Moore, architecture critic, the Observer

Exactly how much has been spent on La Sagrada Familia over the years is unknown but it’s estimated the project has cost between $1.6 billion and $2 billion, since 1882. Funded by private donations and tourism, the current estimate for building costs per year is €25 million.

The construction of La Sagrada Familia has seen costs spiral due to several factors, including fluctuations in funding and inflation over more than a century, expensive high-precision practices and handcraftsmanship, and the cost of international expertise to complete a World Heritage site.

La Sagrada Familia operated without a building permit for 137 years, until 2018. As a penalty for this oversight, it will pay £31 million to Barcelona authorities in instalments over the next decade.

La Sagrada Familia has now received a seven-year licence at a cost of €4.6 million, making it the most expensive building permit in Barcelona’s modern history (and that’s with a 65% discount for being a public, not-for-profit building.)

A planner’s 21st century perspective

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Preventing cost overrun with generative AI

Unlike La Sagrada Familia, most projects do have a total budget. It’s vital for the financial health of a project to stay within its means if profit margins are to be protected and cash flow maintained. Project managers must manage and reverse overruns quickly before scope and stakeholder confidence becomes compromised.

Did you know?

Builders of La Sagrada Familia are immortalised in stone in the Nativity facade’s Portal of Mercy. Cast from their death masks, the faces of deceased carpenters, stonemasons and sculptors are captured in eternal memory for their tireless work.

Generative AI makes this possible with...

Earned Value Management (EVM)

With generative AI, EVM can integrate real-time information to predict costs and schedules, identify risks and optimise resources. The result is faster, data-driven decisions and more precise control over the project’s finances.

By combining measurements of scope, schedule and cost in a unified framework and automating their analysis, planners can measure performance and progress in terms of money for an accurate picture of project health.

Hypothetical Use Case

Sourcing sandstone from quarries across Europe means fluctuating costs in its price and transportation. EVM can assess the current and predicted future cost variance, and the overall impact the spending trend will have on total costs. Planners are then armed with actionable insights to work to minimise any expected budget variance at project completion.

Dispute protection

Generative AI helps protect construction projects from costly claims by exposing the root of the problem. Through inspecting the specified activity and tracking through predecessors, the start delay—and its impact on future activities—is revealed.

Project managers can filter activities and identify which supplier, activity or contractor is the most significant contributor to the timeline’s delays. Data can then be collected manually for assessment or calculated using algorithms to help reach a resolution.

Hypothetical Use Case

The tallest part of La Sagrada Familia, when completed, is also the most delayed. The tower of Jesus Christ is the church’s central spire, and multiple dependencies must be met for progress to be made. This includes sourcing of materials that can satisfy structural integrity, efficient engineering techniques and the timely installation of sculptures, stained glass and mosaic. Generative AI can help to pinpoint who and what is holding up each stage, supporting any delay claims against contractors or clients.

Acceleration opportunity generation

Generative AI can assess current project performance and make realistic predictions on when a project will finish.

By uncovering delayed activities and showing the impact of remedying them with test mitigation scenarios, incoming delays can be absorbed, and delivery accelerated.

Hypothetical Use Case

Architect Francesc de Paula Quintana i Vidal faced the task of sourcing copies of destroyed plans and reconstructing the vandalised plaster models after the Spanish civil war. He could have used generative AI to get a clear view of the project’s new end date and assessed potential acceleration opportunities to reignite La Sagrada Familia’s progress.

Find out more about the other struggles La Sagrada Familia has had.

Choose which Challenge to learn more about.

Learn how to use Al to avoid delays, prevent cost overrun and accelerate capital projects.