Construction companies are actively trying to thrive in the modern business environment. Their reliance on Business Analytics (BA) is getting more and more critical because the simplest construction plans can be very critical with a lot of effort on environmental impact studies and feasibility.
Predictive analytics tools assist you in fetching valuable data streams in real time. With the right body of know-how, experience and skills, you'd be able to optimize work schedules and find the right job-fit for your company from the data available. On the other hand, Business Intelligence (BI) only gives you visibility over information.
Here are 5 ways Business Analytics can benefit a construction business.
1) Leveraging Workforce
With Work Breakdown Structure (WBS) the delegation of work is simplified. It jots down tasks and adds or removes individuals by breaking down the quantity and the type of skill needed. With the tasks streamlined, expectations are clarified based on what needs to be done and who needs to do it. BA tells you a couple of things like the relevancy and the accuracy of skills deployed for the work carried out and the tasks that were time-consuming yet mission oriented.
2) Detecting Loopholes
To totally understand the information available, first, all the documents need to be digitized. From this, relevant information can be derived. A master sheet is created by descriptive analytics which comprises of all the failures encountered in the previous project, what triggered them and their extremity. Predictive analytics then analyzes the possibility of repetition of these failures on the ongoing projects. This can drastically reduce the bench-time.
3) Scanning Risks
No other sector roots for worker safety more than construction space. An injured worker can lower the productivity of the team and even lower their morale. With the help of predictive and prescriptive analysis, the workforce can majorly avoid site disasters. Predictive analysis can pinpoint disaster zones to the nth degree accuracy. The pedometer analytics can assist you in positioning tools and heavy-duty equipment strategically so that visibility is improved to avoid disasters. Faulty machinery can also be detected by predictive analysis and servicing can be scheduled so that outdated machines are not allotted to the crew. This ensures that the project's progress is not hindered.
4) Reducing Production Overheads
No organization wants downtime. Manual Monitoring is not only laborious but fails to predict or prevent downtime rising again in the future. The predictive route can reduce labor and production costs. As per GE's Kimberlite survey, a predictive and data-based approach can reduce downtime by 36 percent. Other than detecting faults, Big Data allows the company to optimize the performance and the quality of the equipment.
5) Compelling Insight
Big data prevents small fragments of data from being unanalyzed. Predictive analytics turns passive data into valuable insights. Multiple scenarios can be run based on the optimistic, likely and pessimistic estimates. Your reporting becomes highly detailed allowing the company to assess the readiness of the project by practically.