Optimizing Cost Estimation Capabilities: A Key to Successful Project Outcomes for EPCs
Globally, the economic turmoil is causing executive management at EPC companies to rethink over their capital expenditure plans to stay profitable and viable. While there is a need to trim the existing staff, it is also equally important to preserve the engineering talent and experience, in order to maintain the identity and competitive advantage of the company. Today, most EPC companies are focusing on shifting key talent to business development and bidding areas to win more projects, which is further leading to brain drain, and is one of the big concerns for leaders at these companies.
The challenge is then to focus on cost estimation process, as it remains a key to win more projects, select the ones that ensure maximum return on invested capital (ROIC) and deliver them on schedule and within the budget. The reality today however is poles apart. The EY research survey reveals that $22.4T USD of investments in oil & gas megaprojects is bankrolled worldwide. Out of these 365 megaprojects, 64% are facing cost overruns while 73% reported scheduled delays.
Some of the root causes of cost overruns and delays, as identified by E&Y, are overly aggressive forecasting and estimates leading to ineffective project management. It is thus the right time for EPC and owner companies to evaluate their existing cost estimation methods and optimize it to ensure better project outcomes and compete better in the market. This requires leaders at EPC companies to take necessary proactive initiatives, some of which include automating knowledge work & engineering workflows and leveraging historical data from past projects. Let’s look at them in detail.
Automating Knowledge & Engineering Workflows
Manual data transfer occurring between engineering teams leads to chances of errors, and with loss of experienced engineers, the complexity is even more. It’s significant in such cases to automate the manual data handover and reduce the estimation time. Leaders must identify data that can be transferred electronically and can be used in developing estimates. Automating the transfer of quantities from P&ID, 3D models and detailed plant design directly to estimation software helps in quickly generating detailed estimates with reduced chances of errors.
Software technology can play a strategic role here to counter the loss of brain drain. With advanced modeling and simulation tools, engineering knowledge across multiple design disciplines can be leveraged to generate accurate estimates faster.
Design automation is one such approach, which allows easy configuration and estimation of components that are identical but different. For example, equipment like heat exchangers, pressure vessels, storage tanks and valves are although designed for specific applications, they all have design profiles that require only minor changes in the geometrical dimensions. Automating the design process for these components enables the engineer to simply enter input parameters and the design is configured accordingly.
DriveWorks is one such leading design automation tool that uses rule based approach to alter the designs developed in SolidWorks. The tool also allows configuring sales documents based on the rules specified, and makes it easier to generate estimates. SolidWorks also has in-built cost estimation and quoting tool that easily monitors manufacturing costs while designing, making easier for manufacturers to automate their quoting process.
Leveraging Historical Data from Past Projects
Historical data helps companies to make strategic decisions, as it provides better insights into actual costs. Apart from estimating, leveraging historical data also enables better scheduling and strategic planning. However, this requires companies to create a well-maintained database for historical costs for all procured items and create a template for projects that are repetitive in nature to serve as a starting point for estimators. The template should be developed such that it captures all the details such as wage rates, soil types, wind loading, pipe specs and equipment design standards such as ASME, BS, etc.
Based on the template, the models, methods and cost data used in estimating can be standardized to improve consistency within groups of estimators. The template can be further calibrated to better comprehend the complex relationships between cost drivers such as location, construction materials, standards and costs. With this approach, companies are in a position to define and develop customized templates for different projects and generate estimates that are closer to actual values.
Conclusion
It is the right time for EPCs as well as other industries with large capital investments to consider estimating as a strategic element rather than just another business function to improve project performance. Companies need to continually examine their existing estimating methods and optimize them through automating workflows wherever possible and improve the accuracy of estimates by leveraging historical data. Whether it is about reducing project costs or cost of bidding or making informed decisions quickly, optimizing cost estimation capabilities remains a key to success.
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