Turning data into competitive advantage
Engineering and construction (E&C) firms are under pressure to meet increasing client demands to deliver more complex projects in less time, at lower cost, and with tech-driven efficiency.
Data analytics is a key innovation that can help meet those demands. And certainly, there’s no shortage of valuable E&C project and industry data. However, many firms don’t have an advanced data analytics program capable of turning that data into insights, and it’s hard to know where to start.
In our three-part series, we reveal an approach E&C leaders should consider to get a data analytics program off the ground, as well as case studies of industry-leading E&C companies that have enjoyed quick wins and demonstrated the value of data analytics for their organizations.
See below for series highlights and links to information designed to support E&C firms as they explore data analytics for better decision making, with results leaders can trust.
Getting started with data analytics
Construction companies are sitting on a tremendous valuable asset, and that asset is their data. Their data in the form of project field labor, safety reports, contractor bids and schedules. Engineering and construction executives can look the other industries and realize that expanding their data and analytic capabilities can help fight off new entrants and actually help drive their business in overall performance.Construction companies can get started - and it’s a simple three step approach. The first step is understanding data and data environment. A lot of organizations that we work with do not have a secure data structure such as a cloud environment with which they can set up an actual data analytic programs to run their analytics. Second, it’s really important to understand data capabilities within your organization. The actual capabilities of your team to be able to run these programs can sometimes be very sophisticated organization need to look outside in order to find the right resources. And third, it’s really important to set up a road map. Really trying to balance out quick wins, medium system enhancements, and long-term, what I would consider kind of transformational upgrades to the data and analytic programs.