Business management incorporates tasks of planning, organizing, actuating, and controlling. Technology is often used to manage specific duties on a daily basis within each of these tasks. Since managers have to use information during these processes and activities, they have to have a basic knowledge of technology.
In today’s modern world, next-gen technologies are being deployed by leading edge businesses. These include technologies like Artificial Intelligence (AI), Internet of Things (IoT), Machine Learning (ML), and Advanced Analytics. Let’s look at the differences and how they are being used in the Heavy Work Community.
Artificial Intelligence (AI) is an aggregative term for describing when a machine mimics human cognitive functions, like problem-solving, pattern recognition, and learning. Machine Learning is a field of AI that uses statistical techniques to give computer systems the ability to "learn" from data – the more data, the better the insights. In the construction industry, data generated from transactions such as enter/exit jobsite, change orders, purchase orders, shipping notices, etc. can be fed into AI and ML engines to enhance decision-making and generate more value to the company.
For example, AI is used in the 3D modeling application called Building Information Modeling which ensures that all systems – engineering, electrical, plumbing – don’t interfere with each other. Solutions exist that use AI and ML to prioritize risk on a jobsite, to plan projects, to create detailed timelines, to plan for labor resources, and more. Some firms are using virtual reality glasses to send autonomous robots into buildings under construction to track work in progress, to assist schedulers and dispatchers, and to enhance training.
The Internet of Things (IoT) is used in the construction industry to get real-time information from connected devices, such as truck telematics, smart shipping pallets, forklifts, construction equipment, and more. For example, you can monitor a bulldozer to see how efficient it is or when its last maintenance was. GPS tracking and telematics can keep track of truck and equipment locations to ensure they are on schedule and aren’t delayed in their arrival to a jobsite.
If you want to improve productivity by reducing wasted movement and time searching for tools, materials, and equipment at the jobsite, you can track the workers with IoT sensors as they move throughout their day. Once you collect the data, you can analyze worker movement and time, then reorganize the location of tools and materials to make them more accessible to workers to reduce time.
Advanced analytics encompasses predictive analytics, the process of using data to find patterns, trends and relationships, and prescriptive analytics, the process of using data to prescribe a solution to a problem. With advanced analytics, project managers will be able to more accurately forecast materials for projects, helping to eliminate the need for over-ordering. Analytics can also help to determine where the best place to place materials at any point in time, helping to decrease the cost of transportation. Advanced analytics can help you turn construction data into insights that lead to better bottom line results.