Manufacturing continues to play a significant role in driving a company forward. However, the role it used to play earlier in advanced and developing economies has undergone a paradigm shift. The manufacturing sector in the developing countries has been delivering immense new employment opportunities that are transforming societies. Manufacturing also plays a crucial role in creating jobs in developed countries. In matured and bigger economies, manufacturers not only drive productivity but also efficiency gains and innovation.
Big Data enters the scene when a company strives to attain productivity and efficiency gains. It also fosters new insights that drive innovation. Manufacturers can adopt different ways to find new information and identity patterns that enable them to improve the production process, identify variables that affect production, and increase the supply chain efficiency.
A research found that 67 percent of manufacturing executives have planned to invest in Big Data analytics despite facing the pressure to reduce costs. A major chunk of the population knows that Big Data analytics is needed to compete in a data-driven economy successfully. This makes them invest in data integration and management of assets in order to attain digital transformation and have an upper hand in the competitive market.
With the increasingly interconnected environment globally, supply chains and manufacturing processes are becoming lengthy and complex. Efforts should be made to modernize these processes and optimize supply chains supported by the ability to analyze every process component in detail. Big Data analytics makes it possible for manufacturers.
Over the years, manufacturing has concentrated on production at scale and left product customization to enterprises that serve the niche markets. During the yesteryears, customizing was not necessary owing to the time and effort required to appeal to small customer groups.
Manufacturers today are using tools to successfully improve production processes, optimize asset performance, and facilitate product customization. Some of the vital Big Data analytics tools are: Data storage, Data Cleanup tools, Profiling Tools, Data Mining Tools, Data Mapping Tolls, Data Analysis, Data Visualization, and Data Monitoring.