By Claire Rutkowski It's All About the Data Software + Technology
must be standard across the entire lifecycle. We use P&IDs to tie things together, but let’s go deeper. If we move data definitions further up the lifecycle and define what is needed through each phase, we can ensure that the right data is captured as projects progress. By using digital twin capabilities, infrastructure stakeholders can combine and amalgamate data from various sources, making a series of data silos into one cohesive bank of geospatially referenced data points about an asset, whether that is a carbon footprint, emissions, as-designed data, as-built data, maintenance information, or asset performance information. However, even digital twins can become siloed and stagnant if not done right. To truly be valuable across the infrastructure lifecycle, digital twin technologies need to have an open foundation to build upon with infrastructure schemas that have standards for data translation from one application to another. Only then can a digital twin be leveraged as a dynamic, comprehensive living data set. Only then can we light up all the dark data we currently lose throughout the infrastructure and asset lifecycle to gain true insights. Is the work worth the effort? Absolutely. Rich datasets drive actionable insights to improve project decision-making and operational performance. These insights can shed light on previously undetected trends, allowing an organization to proactively course correct, leading to better outcomes for all stakeholders – design firms, EPCs, constructors, asset owners and operators, and the public at large. Stakeholders can then leverage machine learning, artificial intelligence, and other tools, which thrive on rich data to glean insights into their data for carbon calculations, predictive maintenance recommendations, and better, more sustainable outcomes. But it all comes back to the data. Let us not settle for 4 percent data reuse. The opportunity for smarter infrastructure outcomes across the lifecycle is in the 96 percent. By using data as a foundation, we can collaborate, leverage, reuse, and become much more efficient and insightful. Given the increased demand for infrastructure projects, the growing backlogs, resource shortages, and the urgent need to reduce climate change, we must get the fundamentals right. We cannot afford not to.
Our world runs on data. The advent of BIM and the proliferation of IoT-sensing devices have driven a veritable deluge of data. We are drowning in it. But surprisingly, we are not using it. A report by FMI Corporation, a consultancy firm, stated that 96 percent of the data generated by infrastructure projects specifically is never reused. You could argue that a certain portion of that data should not be reused because it is project-specific, but certainly not 96 percent of it. One of the reasons we are unable to leverage data in the infrastructure sector is that every time we hand a deliverable off from one firm to another or from one phase of the asset lifecycle to another (e.g., the handoff from project design and delivery to construction or construction to commissioning), we lose data. Perhaps the tools or systems being used in each phase do not talk to one another, or the data being generated in one phase is incompatible with the structure of the data in the next phase. As a result, we lose a lot of the hard work performed in one phase and in many ways start over in the next phase–with less fidelity and detail. The same FMI study reported that 90 percent of the total data its accounts produce during engineering and construction is unstructured. Unstructured data can be difficult, if not impossible, to translate and migrate from one tool to another; it is one of the main drivers for information getting lost along the way. The result is a lack of visibility into data, leading to challenges in communication and collaboration because stakeholders are not looking at or talking about the same data sets. It also means that decision makers are making decisions based on incomplete data, because some of it did not transfer over. And siloed data gets left behind, driving obsolescence. For the infrastructure sector to take full advantage of tools like artificial intelligence and machine learning, stakeholders need robust data sets containing structured and unstructured data that can be mined for patterns and insights. AEC firms and asset operators need cohesive, complete data sets to foster communication and collaboration. Cohesive and complete data sets can also ensure that we are measuring the complete carbon footprint of an asset, from project delivery to construction to operations and potential decommissioning. This will help the sector drive sustainable outcomes. And robust and accurate data that can be leveraged by machine learning and artificial intelligence tools will also help ensure accuracy to design intent, greater efficiencies throughout the asset lifecycle, and provide insights not otherwise gleaned. How can the infrastructure sector achieve this? From a technology perspective, the creation and maintenance of rich data sets require open platforms that can work with multiple tools. Interoperability among those tools is also required, and the data must be able to be shared securely and appropriately throughout the entire supply chain. The data also needs to be captured and maintained. Data requirements
Claire Rutkowski joined Bentley in 2016, where she serves as the company’s CIO Champion, advocating for CxOs at engineering firms and serving as a bridge between Bentley and its engineering accounts. Previously, Claire led the global IT organization at Bentley, shaping and delivering a technology agenda across Bentley’s business. By collaborating with executive leadership, she ensured Bentley leverages the most advanced solutions to achieve the goals of the company and its users. Before joining Bentley she was CIO at MWH, responsible for delivering IT strategy, services, and support to 7,000 engineer - ing professionals globally. Claire is a PMP and has received numerous awards, most recently the Top 80 CIOs You Should Know, and was named to 2022’s Top 10 Most Inspiring Women Leaders.
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csengineermag.com
October 2023
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