As engineers and construction professionals, we love numbers. They are at the heart of everything that we do and let’s face it, the most difficult calculation we could do is try and calculate how many calculations we have done across our careers. It is also true to say that as an industry, we are creating, capturing, analysing and utilising more numbers than ever before. We are awash with data, and while that’s great, data is nothing without insights.
The classic example that I am sure we have all seen is the analysis of bomber damage during WWII. After each mission, the damage taken to returning bombers was analysed to help try and find areas where the aircraft could be strengthened.
From the data, the solution is obvious, strengthen the wings and fuselage.
Enter Hungarian-Jewish statistician named Abraham Wald, who reviewed the data and pointed out a critical flaw; the lack of data on aircraft that never returned.
Therefore efforts were made to reinforce the areas not identified by the original analysis, the cockpit, engines and tail. In other words, the most vulnerable parts of the aircraft. The outcome, fewer fatalities and greater mission success.
So while data is valuable, insight is more so.
The challenge that we all face is taking data and creating insights, communicating those insights, and using them to beneficial outcomes. So, where do we start? In the beginning, would make sense.
The proliferation of data is linked to the tools that we use, tools that are more commonplace in construction than ever before and collect numbers like never before. BIM data, project analytics, collaboration tool, drone information, remote station data, site records, material records, performance analytics, are all creating what we refer to as big data.
Big data is defined by Oracle[1] as:
The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity.
Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.
And there is the rub; what are the problems that we need to solve? In our next few blogs, we are going to look at how we can create a cycle of improved performance across the lifecycle of a project. From design through delivery to post-handover and future learning, there are opportunities for all of us to improve collaboration, understanding, performance and planning.
But like Abraham Wald, we have to find the insights from the terabytes of data that every project generates.
At Civil Project Partners, we have started to utilise data to create insights for our team and therefore for our clients. A good example is how we have used readily available data to map infrastructure investment in Queensland.
Notes
The data show QTRIP information by district and level of investment. A fairly simple analysis, but invaluable for major contractors, supply chain members and more for resource planning, investment planning and more.
[1] https://www.oracle.com/au/big-data/what-is-big-data/