No matter what industry you’re in, it’s likely that big data already plays a huge role or will in the near future. That includes the building, construction and manufacturing industries, which use data analytics to make various processes more efficient.
It’s inevitable that big data will only play a larger role in the building and manufacturing industries over the course of the next decade, but does that mean it’s a good thing? For the time being, it all depends on who you ask.
Here is a quick look at the role big data could have on manufacturing industries over the next 10 years, the pros and cons, and what it all may mean going forward.
Big Data — The Pros
There are many ways big data and advanced analytics could improve manufacturing in the near future.
One of the key metrics in manufacturing is yield, the output that’s produced compared to the input of materials and labor. Those who argue for big data say it could help improve yield because it can help workers diagnose and correct potential flaws in their processes.
With so much information available, it’s easy to go back and look at historical data and then optimize processes based on the patterns that are found.
In a more efficient industry fueled by big data, manufacturers could also save time, which could, in turn, lead to cost savings. In fact, big data can help reduce manufacturing costs on a number of fronts, including the cost of production, packaging expenses and the amount spent on transporting and storing products.
In theory, this could lead to lower inventory costs, which would, of course, help the bottom line.
Another opportunity presented by big data comes in the form of “green construction,” or building homes that conserve energy over the long run through elements such as energy efficient windows, light fixtures and appliances, as well as solar panels.
Finally, big data can contribute to making manufacturers more efficient all around, including the ability to increase collaboration between departments. If each department of a manufacturing outfit has access to the constant stream of data and analytics, it puts everyone on the same page and encourages improved quality control.
Big Data – The Cons
While big data and advanced analytics could undoubtedly benefit manufacturing industries, it could lead to a number of setbacks as well.
For example, some envision a world in the not-so-distant future in which machines and robots have the data and physical capabilities to eliminate the need for humans at construction sites in most cases. This would include things such as robotic cranes and digging machines along with automated builders.
If humans largely aren’t needed on construction sites, it could save manufacturers money, but it could also leave many without work. In this scenario, humans would still be needed, but mainly only as overseers of multiple construction projects at once.
What the Future Holds
Nobody knows exactly how this will all shake out, but it’s likely that the most positive outcome would be somewhere in the middle. Everybody wants manufacturing industries to become more efficient, and big data and analytics can help. At the same time, nobody wants to see massive losses in jobs or unhealthy levels of energy consumption, which could be consequences if said data becomes a bit too big.
There’s no denying that data is already big business. Revenue from the sales of big data will reach $187 billion in 2019, according to a forecast from IDC Research. That would be up 53 percent from $122 billion in 2015. It’s clear that big data is not going away.
The question is whether big data and automated processes will lead to massive job losses, and the answer isn’t easy. Yes, robots and machines that can build things more efficiently than humans could lead to fewer construction workers, for example. On the other hand, this shift would also lead to increased demand for data scientists and others on the analytics side, which could create a whole new set of jobs.
The solutions aren’t easy, of course, and only time will tell how the manufacturing industries react. The ideal situation would include the best of both worlds, but whether that is feasible is anybody’s guess at this point.