From data silos to actionable insights: Innovating within legacy constraints for the digital enterprise
Market View
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Interview with
Pedro Rente Lourenço
FORMER GROUP HEAD OF DATA & ANALYTICS, LAING O'ROURKE
about
Pedro Rente
Lourenço
Pedro Rente Lourenço is formerly the Group Head of Data & Analytics at Laing O'Rourke, where he drives enterprise-wide data strategy and delivers value-focused analytics solutions. With extensive experience in Data Science and Machine Learning, Pedro has successfully led major digital transformation initiatives and implemented innovative data strategies across both large enterprises and startups. He is particularly passionate about fostering data literacy and delivering measurable business outcomes through advanced analytics.
How has your organisation approached the challenge of extracting more value from data while working with legacy systems?
Four years ago, we recognised our significant dependency on legacy on-premises data warehouses was creating limitations. This prompted us to initiate a major cloud transformation program, taking a strategic approach that balanced maintaining necessary legacy systems while progressively migrating to the cloud.
We prioritised high-value use cases agreed upon with the business, starting with data migration, creating ETLs, and building our cloud platforms. Today, we're reporting more from the cloud than from legacy warehouses. This transformation has freed up space for specific systems, particularly financial ones, that need to remain on-premises due to specific requirements. These legacy systems can now operate more effectively without being impacted by the increasing reporting demands we face.
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Our cloud transformation has freed up space for specific systems that need to remain on-premises, while allowing us to handle increasing reporting demands effectively.
What do you see as the primary challenges when innovating with established technology stacks?
The most significant obstacle with on-premises resources and legacy systems is the cost of maintenance and hardware. Innovation becomes challenging because you don't have easy access to new tools on a pay-as-you-go basis. The investment required for new systems often prevents exploration and experimentation.
Consider this example: with our cloud platform in Microsoft Azure, when we want to explore new architectures or tools, we can quickly launch a proof of concept. We simply engage with vendors, access their services, and complete an exploration within two weeks. The same process with on-premises systems would require significantly more time and investment. While owning hardware might seem cost-effective over several years, the rapid pace of technological evolution makes cloud solutions more practical, allowing us to stay current with modern systems.
Can you share a successful example of innovation using existing systems and data?
One of our most successful innovations came from leveraging cloud capabilities rather than legacy systems. When OpenAI released their GPT models on Microsoft Azure, we quickly identified an opportunity with our bid writing team, who needed to summarise text within specific character limits for bid submissions.
We developed a Python web app proof-of-concept using GPT models that helped summarise approximately 5,000 text excerpts, significantly reducing the time required for bid preparation. What's particularly noteworthy is that we accomplished this within two weeks. A few weeks later at a Gartner event, I was surprised to see we were the only company in the room that had already deployed such AI tools. This surprised many, as construction isn't typically associated with data innovation. Our success stemmed from having readily available access to cloud services, a clear use case, and the ability to move quickly.
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We developed and deployed an AI-powered text summarization tool within two weeks, demonstrating that construction companies can be at the forefront of data innovation.
How do you balance data integration needs with the risks of changing established processes?
Our approach has been to separate our analytics platforms from our integration platforms. We maintain a global data platform for analytics and a distinct global integration platform for handling internal systems and external APIs. This separation helps protect both analytics and integrations while enabling targeted improvements.
The real challenge lies in changing business processes, particularly in our project-based environment where projects can run for years. We've found success by demonstrating value in specific areas and taking a pragmatic approach to change. For instance, we recently standardised our activity coding structure across projects. This standardisation allows teams to compare performance across different projects and better understand risks and cost patterns associated with specific activities.
Instead of forcing immediate wholesale changes, we created mappings between old and new coding structures and minimised rework requirements. This pragmatic approach, focused on delivering business value, has been key to successful adoption. As I often remind my team, it's not about whether change needs to happen - most people agree it does - but about how to implement it in a way that delivers net benefits rather than just creating additional work for us and our customers in other business functions.
How are you leveraging location-based data to enhance your existing information assets?
Location-based data plays a crucial role in our operations, particularly in linear infrastructure projects like railways and roads. We maintain dedicated GIS teams on these projects and utilise telematics for our fleet of trucks. One particularly impactful application has been in sustainability reporting. Instead of making broad assumptions about staff travel distances and associated carbon emissions, we now use approximate location data to track actual travel patterns and frequencies.
This more accurate approach has not only improved our emissions estimates but has actually revealed lower carbon numbers than our previous estimation methods suggested. We're also applying location intelligence to optimise material delivery and placement on construction sites, though integrating this data with legacy systems can be challenging since much of it resides within individual project sites rather than our central warehouses.
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The Data Academy has made our business more self-sufficient, with staff now building sophisticated reports, dashboards, and even initial machine learning models.
How are you addressing data literacy and upskilling across your organisation?
We've implemented a Data Academy program that has already trained upwards of 300 people through apprenticeships. This initiative helps employees who handle large amounts of data develop better data skills, making our business more self-sufficient. Projects can now self-serve from both legacy and modern systems, and we've seen impressive results with staff building sophisticated reports, dashboards, and even initial machine learning models.
The program has had several unexpected benefits beyond just technical capability. As people become more data-literate, they're better equipped to identify and address data quality issues. This increased awareness has led to improved risk management, better site information management, and enhanced commercial management – all driven by employees using their new skills with existing data.
The success of this program demonstrates that with the right training and tools, teams can extract significant value from both legacy and modern systems. It's created a culture of data-driven decision making that's transforming how we operate at all levels of the organisation.
about
Laing
O'Rourke
Laing O'Rourke is a leading international engineering and construction company known for its innovative approach to construction and digital engineering. As one of the UK's largest privately-owned construction firms, it operates across Europe, Australia, and beyond, delivering complex infrastructure, building, and energy projects. The company is at the forefront of digital transformation in construction, pioneering modern methods and sustainable practices to reshape how the built environment is designed, manufactured, and operated.
We are the global market leader in geographic information system (GIS) software, location intelligence, and mapping.
Esri UK is the exclusive provider of Esri solutions in the UK. We take a geographic approach to problem-solving, brought to life by modern GIS technology. We are committed to using science and technology to build a sustainable world.
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