It is stale news that construction companies are using data to achieve their project goals. The industry has paved its way quite some time ago in data collection, storage, and analysis. The news is about the challenges they are facing in these processes and how leading organizations have overcome these challenges with effective planning and strategic use of technology.
As of now, construction companies have been focusing on the following types of organization data to increase operational efficiency and get decision support to ensure timely completion of the construction project:
1. Jobsite data
It is a gold mine of all the data. Data captured at the job sites helps in tracking every ongoing activity in a course of time. Most construction companies track the time of employee movements in the field, using wearable technologies, and asset data such as equipment specifications, location, quantity, and consumption patterns.
Based on the information, they can decide on new purchases, select or reject vendors, determine the time to complete a job for targets, and hire freelance contract workers for added support.
2. Employee Data
Employee data is about the skills, performance, and productivity of every employee. This sort of data is helpful in making hiring decisions, training and support, and scheduling and dispatch. For instance, most construction companies use scheduling and dispatch software, backed by AI and machine learning.
The schedulers match the location, skill, and availability of the field workers and recommend the best workers for the job. Similarly, by tracking the visit-in and visit-out times of the field workers, project managers can determine their most effective resources and track down workers who need guidance and training.
3. Asset Data
Most construction companies use a lease or rental model to acquire an asset, as it relieves them of the burden of capital cost and maintenance. However, tracking and management get complex when managers lack real-time visibility into asset location, quantity, and functional status.
In order to overcome these challenges, they seek help from digital tools to keep track of asset-specific information, which is generally recorded through proper serialization. Advanced construction management software may allow you to keep a record of all the documents associated with the assets, such as service history, service manuals, a team of service technicians who worked on them, and customer account details.
These are three varieties of data that are usually captured by construction companies. Often companies make the mistake of focusing too much on the volume of the data instead of variety. The result is a large volume of datasets that have not been collected to answer project-specific questions. It is essential for construction companies to focus on the following activities in their data collection practices.
1. Linking of data
Data in itself is not information. You need to add context to the data and that would need you to link one dataset to another to get a complete picture of your construction project.
Use tools that are powered with advanced data analytics capabilities to help you correlate the data and generate useful Insight. Although, it is only possible when you have a variety of data such as employee data, field activity data, and asset performance data.
Correlating data helps you delve deeper into the “what”, “why”, and “how” aspects of the projects. You could figure out patterns, spot anomalies, and detect changes in patterns to make informed decisions. Proper data linkage requires a focus on the accurate collection of data, data analytics capabilities, and integration and associated implementation procedures.
2. Data Cleansing
Even though your utmost focus is on variety, you can’t really escape from the volume. It is because even in one type of dataset, there is a multitude of variables. For instance, if you are collecting field data of your workers, the key variables could be visit-in and visit-out timings of field force at the site location, the number of breaks, time spent on a particular activity, an asset used, and so on.
Now considering that you have 30 workers, it won’t take too long for the volume to increase. Besides, now chances are that 2 workers resign each month and along with their replacements, you add one extra worker to ensure consistency in the project.
Secondly, there is a possibility of asset replacement, and inclusion of new tasks as the project escalates.
If you do not update the data on a regular basis, your master data may become inaccurate, inconsistent, and inconclusive in a short span of time. Data cleaning from time to time ensures that you have the right data in hand all the time that generates accurate insight.
A Call to Action
Do you collect and utilize data to get real-time visibility into your operations? If yes, setting standards, policies, and practices to create, manage, and utilize data would increase compliance and clarity within your team.