Construction companies today are overrun with data. To get the best uses from that data, many contractors are jumping on the data management train. However, enemies lurk there, waiting to turn your efforts into data mayhem.
It’s not just the volume of data that’s posing big problems for data management, but the velocity as well. Then there is the issue of managing multiple types of data while trying to integrate them so you can get the most value from their analysis. One of the first enemies of data management is poor or no classification.
1. Classification is absent
Most construction firms must control and protect sensitive and confidential data. That data is exposed to bad actors and data loss throughout its lifetime. It travels on mobile devices and winds its way through countless systems and communication pipes where it can be compromised or lost.
Unless you classify the data, you can’t even begin to protect it. By using data policies that control encryption, data access and who has the authority to change or delete data, you effectively identify and protect sensitive data.
2. Uncontrolled data diversity
You need a wide range of data types, from structured to semi-structured to unstructured because that’s the data that exists in construction. When integrating all that data though, you quickly face the problem of limitations in data management platforms and tools. Some data management solutions work best for streaming data, while others excel at handling static data. An SQL database covers your integrity and availability needs, but doesn’t handle your unstructured data effectively.
Still, you have to manage all the data. So, your best solution could be a hybrid approach, where you use the platform that covers most of your needs while adding in some tools that fill in the gaps. Diversity is needed, but you have to manage it.
3. Ignoring use cases
You’ve got data that has multiple uses across not only your project, but across your business. This data presents challenges in data quality and integration. Something as simple as a client name and contact information gets used many ways across your systems. The same information must also be recalled in multiple ways and used in multiple formats. For project data, you might need well-defined data points for labor analysis, but high- level data combinations for portfolio insights.
If you ignore use cases during classification, you don’t have to worry about integration. But, that defeats the whole concept of managing your data. So the enemies here are not identifying all the use cases, and then not using integration tools that appeal to the people who use the data.
4. Poor data management
Managing data without confirming your management efforts are working, is simply an effort in blind faith. You need to confirm the data gets to its use case.
More than that, you need to confirm if it got there on time; it had the structure the end user needed; it met the quality standards; and, you could trace its journey to its source.
When you confirm the data is getting to the use case, you are in effect making sure the data is visible; that there are no informational gaps and that it was delivered efficiently. Most importantly, you confirm it was fit for its purpose.
5. Failing to capture and manage streaming data
A stream of data has no beginning and no end. These are a sequence of recorded events. So they are difficult to integrate with other data. But, more and more construction firms are using streams.
Drones, light detection and ranging equipment, geographic information systems, surveillance tools, and sensors of all types, represent the current construction data streams. But, there are many more streams poised to come online as new devices and apps arrive at the jobsite.
Each team member on the job is producing a stream of data. Every decision they make, whether it is applying more pressure to a jack hammer, or making a second trowel pass over a drywall joint, is a data point holding potential new insights. For construction’s data to have the most usefulness, it should include the experience and know-how of the people doing the work.
In most instances, companies are capturing and integrating very little of this streaming data. But as sensors and other collection devices proliferate, you will need to capture and analyze those data points to reap the benefits.
6. Overlooking discoverability
Vast troves of data have limited usefulness if they aren’t discoverable. Cataloging the data or creating a discovery layer on top of your data tier helps users know what data is available. That knowledge alone can inspire all types of novel data inquiries leading to insights that improve business and project outcomes.
Your catalog should grow with your data and should constantly reconfigure to match changes in your data hierarchy. For example, at some point you might consolidate two separate streams of data so it’s more useful to users. You should then ensure your catalog reflects the new configuration.
As the volume and velocity of construction data grows, each contractor faces the very real possibility of becoming irrelevant if they don’t capture the data they create and squeeze the value from it.
Data management platforms and tools provide the keys needed to unlock all your data’s value once you deal with its enemies. A centralized project and documentation platform like Procore ensures all your data is available anywhere, any time, and securely.