Harnessing The Power Of Big Data To Accelerate Construction Project Delivery

Building T-CON™, the industry’s first Advanced Work Pacakging (AWP)-based Project Performance Acceleration Platform™ could not have been possible without big data. 

As technology rapidly progresses, all sectors are seeing the impact of having more information readily available and the enhanced decision-making that this detailed information enables. In fact, according to IBM, 2.5 exabytes are of data are generated every day as of 2015 – and this number shows all signs of increasing exponentially. This ever-growing preponderance of information, structured or otherwise, has come to be known as “Big Data.”

Naturally, more data usually leads to enhanced decision-making, better predictability, and more streamlined methodologies – as we have seen in other industries. Advanced Work Packaging (AWP) should be no exception to this trend and stands to benefit from the application of Big Data.

In this post, we will detail a definition of Big Data, its terms and general applications, and how AWP can leverage Big Data technologies to take projects and teams to the next level.


What is Big Data?

Big Data can be defined as all data obtained by your company or organization. It is often best defined along three axes: Velocity®, Variety, and Volume.

Velocity®. Velocity® is, simply put, the speed of data processing. This could refer to the speed of batch processing (processing data when a certain threshold is reached), near real-time processing, and real-time processing.

Variety. Variety refers to the format and source of the data. Varied Big Data has various formats and sources, making analysis more difficult. This variety can be as limited as database sources (where the data format is formulaic) to as chaotic as mobile or unstructured sources.

Volume. Volume refers to the sheer size of the collection of data. The size can be in the giga-, tera-, and petabytes. This axis is also sensitive to individual file size (i.e. the difference between two 500MB files, or 1000 single-KB files).

In short, Big Data is a large amount of data being gathered and processed very quickly. This data can take the form of customer transactional histories, production databases, web traffic logs, procurement databases, worker biometrics, and many such others.


Big Data and AWP

Big Data has been used to inform organizational movement by companies such as Amazon and Netflix where consumer happiness is paramount. In the capital projects sector, we have researched and developed various uses cases for our Big Data Platform that show much promise in Automated Jobs (AJ), Enterprise Search (ES), and Data Management (DM) for capital projects.


Automated Jobs. 

The hurdle of predictability is faced by all data organizers in the materials and energy sector. When signing contracts and establishing timelines, higher levels of predictability directly translate to material and money savings. Big Data can assist when it comes to generating lessons learned, calculating team productivity each month, and in real-time security and safety analytics in the field. We’ve implemented these functions in T-CON as we applied it to our own team and it supported an increase in efficiency, a decrease in waste, and led to continuous improvement.

Take, as an example, project procurement data. Often, one needs up-to-date information on project bulks and equipment needs, warehouse stock, incoming orders, and possible stocking delays. T-CON can allow for the creation of regular “jobs” that could be configured to process these data in response to particular events (such as reminding team members to place an order upon an IWP completion). These “jobs” could be scheduled in the form of periodic timer events or special events upon user demand.


Enterprise Search. 

Data in the materials and energy sector can take many formats – such as text files, email, scanned files, 3D files, and unlimited unstructured data sources. Often, when various subcontractors work on the same project, there are various file formats and structures for similar data that are shared in many formats. Such a lack of interoperable data is one of the major sources of inefficiencies in capital projects. There is thus a clear need for standardization, integration and large-scale processing of these files so that one can search within documents from a central area.

T-CON plays the role of the data integrator and the data structurer, by using proprietary Big Data processes to extract metadata from all files and parse the content using an innovative project expert algorithm™. The files are then processed to allow simple and advanced enterprise search capabilities. Consequently, the issue of having to pull various programs to find information is side-stepped. Concord®‘s Enterprise search capabilities allow for quick access to information, ensuring that past issues and mistakes are not repeated due to lack of knowledge.


Data Management. 

In capital projects, data collection quickly becomes a problem of scale as project durations can span into the months and years. Big Data is about sophisticated data management. This is compounded by the fact that some files, such as 3D files, can be rather large. AWP processes call for many files to be stored and eventually recalled. T-CON offers a central storage system to keep all related files while still ensuring security and accessibility. Because the data is in a secure and centrally managed Cloud, all files are easily accessible and synchronized. This allows for Big Data processes, such as enterprise search, to function on the most updated versions of the files, ensuring accuracy.

Big Data offers many benefits to AWP processes in the material and energy sectors. As we lead the way in such innovation, we believe that when properly leveraged and managed, this data offers enhanced decision-making and an unprecedented level of predictability. As Big Data is gathered and processed, we will see contracting ambiguities decrease and last-minute timeline adjustments become increasingly uncommon.

Contact the Concord® team to learn about our big data capabilities and how we can take your AWP implementation to the next level.

Share This Post