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Data-driven decision making in EPC: Harnessing big data and analytics for project optimization

Data-driven decision-making plays a pivotal role in shaping strategic business decisions across companies of all sizes. It involves utilizing facts, metrics, and data to guide strategic business decisions aligned with objectives and initiatives. For engineering, procurement, and construction (EPC) firms, harnessing big data and analytics is essential for optimizing projects and achieving long-term sustainability and margin improvements effectively. Neglecting factual insights in an EPC company can significantly impact project execution and outcomes. Therefore, cultivating a skilled team to oversee data management and analytical processes is crucial for ensuring business competitiveness and client satisfaction. Drawing from 25 years of direct management experience at Nuberg EPC, I share valuable perspectives on integrating data into strategic business decisions.

The Importance of Data in EPC:
AK Tyagi
Founder, Chairman & MD
Nuberg Engineering Ltd.

Data remains pivotal for informed decision-making in today’s landscape. The surge of big data, along with advancing algorithms, has positioned it as a cornerstone across various EPC factors such as planning, finance, execution, supply chain management, etc. The practice of leveraging data for decision-making, known as “data- driven decision-making,” offers manifold benefits, although some may not immediately be evident.

According to a BARC survey, businesses that utilize big data reported an 8 percent increase in profits and a 10 percent reduction in overall costs.

Types of data utilized in EPC:
  • Design data includes blueprints, CAD models, and specifications.
  • Procurement data involves information on materials, suppliers, and logistics.
  • Construction data includes on-site activities, progress reports, and workforce management.

Technologies such as GIS (Geographic Information System), ERP (Enterprise Resource Planning), RFID (Radio Frequency Identification), and ECM (Enterprise Content Management) are also integral to managing these data sets.

Types of analytics utilized in EPC:
  • Descriptive analytics: understanding what happened.
  • Predictive analytics: forecasting what might happen.
  • Diagnostic analytics: identifying why something happened.
  • Prescriptive analytics: suggesting actions to optimize outcomes.
Challenges Addressed by Big Data and Analytics in EPC:

One of the major challenges in EPC data governance is managing the various types of data, such as project plans, design documents, financial information, construction schedules, procurement records, equipment logs, safety reports, and regulatory compliance documents.

Key Areas Where Big Data and Analytics Optimize EPC Projects:
  • Planning and Assessment: Data and analysis aid in the correct planning and implementation of upcoming and current projects. This includes the collection of previous data and project analysis, identifying needed changes, and making necessary additions. It helps mitigate future risks or problems. This encompasses budget estimation, future partnerships and collaborations, human resources, required machinery and materials, and scheduling.
  • Supply Chain Optimization: Data and analysis in the supply chain help to streamline the flow of goods and services from supplier to project. It aims to reduce costs, improve efficiency, and enhance overall supply chain performance by optimizing inventory levels, transportation routes, supplier relationships, and cash flow strategies.
  • Infrastructure Development and Management: Big data also assists in EPC in infrastructure development and management by enabling predictive analytics for better project planning, optimizing resource allocation, improving construction efficiency through real-time monitoring, and enhancing maintenance strategies and renovation through data-driven insights.
  • Risk Management: Predictive analytics assesses risks more accurately for Nuberg, allowing proactive mitigation strategies. Identify potential risks, assess their impact and likelihood, and implement strategies to mitigate them proactively throughout the project lifecycle, ensuring resilience and minimizing disruptions. These strategies played a crucial role during the pandemic, and we were able to take the proactive decision to charter flights for our engineers in the interest of employee health balanced with project completion timelines, earning Nuberg tremendous goodwill with both the talent and the client.
  • Environmental Impact Monitoring: This involves maintaining predictive forecasting reports for an area based on historical data and the current situation of the site. We gather extensive environmental data, such as air and water quality measurements, biodiversity surveys, and geographical data, facilitating a thorough understanding of potential impacts. It helps us control and prepare for any unforeseen situations and prepares us to handle them effectively.

Utilizing data-driven decision-making, we have delivered EPC and Lump Sum Turnkey (LSTK) projects in 32+ countries, working with esteemed clients across chemicals, fertilizers, steel, oil & gas, and nuclear & defense sectors. Our expertise includes chlor-alkali, sulfuric acid, and hydrogen peroxide plants for clients like Al Ghaith Industries (UAE) and Inovyn (Sweden), infrastructure projects for Rashtriya Ispat Nigam Limited (India) and SAIL, oil dispatch terminals and pipelines for IOCL and ONGC, and significant projects for the Heavy Water Board (India) and DRDO. Data-driven decision-making has enabled us to enhance project planning, execution, and delivery, ensuring optimal outcomes and client satisfaction.

The Engineering, Procurement, and Construction (EPC) industry has been essential in developing global infrastructure. Various contract execution models exist in the market, with the EPCM model currently being the most prevalent. Big data enhances synergy in estimating prices, scheduling project execution, considering global weather patterns, and other factors that impact project success. Many EPC companies are trying to develop capabilities in this space, and we believe we have a good balance of cost vs. efficiency vs. scalability.

Future trends in data-driven decision-making in EPC:

Looking ahead, the future will be shaped by transformative technologies such as AI, IoT, and blockchain, which promise to revolutionize predictive analytics, real-time monitoring, and transparency in procurement and contract management. Integrating these advanced analytics with real-time data will enhance project site responsiveness and adaptability. Sustainability will be a key focus, with data-driven insights optimizing resource use and energy efficiency. Enhanced communication and stakeholder engagement will be facilitated through collaborative platforms and improved data visualization tools. Predictive maintenance will mitigate downtime and costs, while stringent cybersecurity measures and regulatory compliance will safeguard data security and privacy. Human-machine collaboration using AR, VR, and robotics will further enhance capabilities, boosting safety and efficiency in construction operations. Although AI is already in use, many innovative features are yet to be fully realized.

The EPC industry plays a crucial role in global infrastructure development. Embracing data-driven decision-making is essential for achieving successful project outcomes amid competitive landscapes and evolving technologies.

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