Sunday, January 29, 2023

Data and Analytics for Improved Construction Performance

Construction industry indicators are often a measure of economic progress. In US alone, the construction industry accounted for about 4% percent of the GDP in 2021 i.e., $800 billion. Hence analysts and investors pay good attention to leading or lagging indicators such as construction spending, Bid and Take-Off Performance, employment rates, NAHB (National Association of Home Builders) housing market index, and more. However, the construction industry is typically a low margin industry that is prone with inefficiencies. Large capital construction projects are often late, over budget, and poorly executed. The average profit margin in the construction sector is below 6 percent. This is very low when compared to other industry sectors like Banking, Oil/Gas, Retail, Telecom, and more. Also, while labor productivity in the global economy has increased by an average of 2.8 percent a year over the past two decades, the construction sector has registered a mere 1 percent annual improvement [1].

So, what can the construction or AECO (Architecture, Engineering, Construction and Operation) companies do to increase the productivity and profit margins in today’s business environment where it is more complexity, speed, ambiguity, and volatility? While there are many solutions to increase the profit margin, one key solution that is available to the construction companies is to invest in data and analytics (D&A) related capabilities. D&A today are considered the key enabler of innovation and productivity in every business function and in every industry sector. A Mckinsey report says D&A can provide EBITDA (Earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [2]. According to Boston Consulting, nine of the top ten innovative companies in the world are data firms. A report from MIT says, digitally mature firms are 26% more profitable than their peers [3].

Fortunately, the construction industry today has enormous amounts of data needed for D&A. This data often comes from the BIM/CAD (Building Information Modeling/ Computer Aided Design) data from the projects, jobsite data collected by IoT (Internet of Things)devices, accounting, procurement, and project management data, and much more. But many construction companies don’t have the right tools, skills, and capabilities to capture and analyze the data. Research by Mckinsey Consulting found that, construction industry has the lowest D&A [4].  In this backdrop, how can the construction industry leverage D&A and improve business performance?

Before we go specifically to the technical matters related to D&A, let us look at some of the construction business use cases pertaining to D&A. Specifically how does D&A help construction firms improve their business performance.Fundamentally, D&A helps organizations derive insights by asking the “right” questionsat the “right” time and improve business performance. With D&A, construction companies can streamline workflows, automate tasks, reduce costs, and more. For example, by analyzing worder movements with GPS tracking from IoT wearables and smartphones, construction companies can assess the level ofunnecessary and dangerous movements that happenin the work facilities. This can help and eliminate lot of unproductive work and improve worker safety.Also, D&A can help closely track job costs, change orders, material and equipment usage, worker productivity and more toget a better status of tasks for productivity improvements and work forecasting. Last, but not the least analyzing data from past projects will ensure that the submission in theproject bids is accurate and competitive, therebyhelping the companies to land on more projects.

In this regard, D&A can source data by integrating data from systems such as Procore, BIM/CAD tools from Autodesk Revit, Dassault CATIA, SAP ERP, SharePoint ECM and other data sources into a canonical system such as the data warehouse or data mart.  The data in the data warehouse or data mart can be used in the D&A workspace for deriving insights at the project, program, and portfolio level. The D&A workspace is a flexible SaaS (Software As A Service) based interface that allows GCs (General Contractors), Construction Managers, and other analysts to quickly derive insights and share the results with other team members [5]. Using the drag-and-drop interface, one can craft the analysis, add powerful visualizations, curate a dataset, share and schedule projects with anyone in the organization, and more. Overall, the data and insights can be presented in configurable dashboards and customizable BI reports from the D&A Workspace and help one to make right decisions in real time.

While technology brings speed, scale, and security, technology itself will not help the construction companies unlock the true and full value of data. Overall, there are five key components construction or AECO companies needs to leverage D&A for improved business performance. They are data culture, data literacy, quality data, technology, and data governance. Implementing these five components will increase the odds of successfully transforming D&A solutions into tangible business results namely increased revenues, reduced costs, and mitigated business risks.

Reference

  1. https://www.mckinsey.com/capabilities/operations/our-insights/how-analytics-can-drive-smarter-engineering-and-construction-decisions
  2. Southekal, Prashanth, “Analytics Best Practices”, Technics, 2020
  3. MIT, “Digitally Mature Firms are 26% More Profitable Than Their Peers”, https://bit.ly/2xBTPNe, Aug 2013.
  4. https://www.mckinsey.com/~/media/McKinsey/Industries/Consumer%20Packaged%20Goods/Our%20Insights/Solving%20the%20digital%20and%20analytics%20scale%20up%20challenge%20in%20consumer%20goods/Solving-the-digital-and-analytics-scale-up-challenge-in-consumer-goods-vF.pdf
  5. https://www.toric.com/

About the Author

Dr. Prashanth Southekal is a Consultant, Author, and Professor. He has consulted for over 80 organizations including P&G, GE, Shell, Apple, FedEx, and SAP. Dr. Southekal is the author of three books — “Data for Business Performance”, “Analytics Best Practices”, and “Data Quality” — and writes regularly on data, analytics, and machine learning in Forbes and CFO University. His second book, ANALYTICS BEST PRACTICES was ranked #1 analytics books of all time in May 2022 by BookAuthority. He serves on the Editorial Board of MIT CDOIQ Symposium, Advisory board member at BGV (Benhamou Global Ventures), Grihasoft (IN), and Astral Insights (US). Apart from his consulting and advisory pursuits, he has trained over 3,500 professionals worldwide in Data and Analytics. Dr. Southekal is also an Adjunct Professor of Data and Analytics at IE Business School (Madrid, Spain) and CDO Magazine included him in the top 75 global academic data leaders of 2022. He holds a Ph.D. from ESC Lille (FR) and an MBA from Kellogg School of Management (US). Outside work, he loves juggling, golf, and cricket.

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