The manufacturing industry is no longer isolated from the change that has reshaped other industries. Big Data and big data analytics can be considered as a positive force that has enabled the manufacturing sector to address some of the many pressing issues and get back on track of economic recovery. According to a report by ResearchMoz called “Global Big Data in the Manufacturing Sector Market 2016-2020, the global Big Data market in manufacturing is all set to grow at a pace of a CAGR of 16.87%.
Manufacturing industries are continuously faced with the challenge of improving manufacturing quality, reduce support costs, and improve supply chain operations to improve the overall efficiency of their operations. Along with these operational improvements, manufacturing industries also want to improve customer experiences to improve market share and drive business success. Given the volume of data that is generated, manufacturing industries can leverage big data gathered from several data sources for improved insights, enhanced customer service, real-time decision making and identify patterns that could improve operational efficiency for better business performance. In this blog, we take a look at some functional areas that can benefit greatly from Big Data.
Improving Operational Efficiencies
Almost all, manufacturing organizations want to discover ways to optimize their operations to increase yield, improve quality, and reduce cost. Big Data tools can assist organizations with information hidden in data gathered from the granular level. By capturing machine level data, manufacturers can identify the time and effort required for meaningful output and identify the conditions required to lead to optimal outcomes. By real-time granular utilization of data and by processing the volume and velocity of data, organizations can locate quality and output inefficiencies in a proactive manner and improve operations.
Supply Chain Management
Big Data analytics can help manufacturing companies gain deep insights into their supply chain and help them identify ways to respond to volatile market demands and identify supply chain risks. Big Data provides more clarity to contextual intelligence that is shared across the supply chain that improves organizational performance. By plotting the data sources on the basis of volume, velocity and variety and the level of structured and unstructured data, Big Data can help organizations make the supply chain more organized. Big data analytics can help in supply chain risk management by providing greater visibility and increasing predictability across the supply chain by identifying likely problems like delivery accuracy and their potential impacts. Big Data also helps in improving traceability performance, gaining deeper vendor understanding, creating comprehensive supplier profiles, understanding customer journeys and optimizing inventory management – all of which make the supply chain function smoothly.
Asset Management and Maintenance
Big Data can play a big role in asset management for manufacturing companies. With the help of sensors on machinery, production center managers can gain immediate insights on machine performance. Advanced analytics can indicate performance, quality and training variables of each machine and also show its operational efficiency. This insight helps in streamlining workflows in the production center to increase efficiencies and productivity by limiting unplanned stoppages and downtime.
Organizations need deeper and clearer insights into the production and supply chain for enterprise planning. With Big Data, they can gain deeper insights into the elasticity of demand for better product demand and production forecasts and quantify the impact of daily production on financial performance. These insights help production planners and senior management with asset optimization – this helps in better enterprise planning and improved financial outcomes.
Big Data can also play a big role in product development. Usually, customized or built-to-order products cost exponentially higher and need well-defined production processes. Manufacturers also need to account for the product mix and the associated development costs keeping in mind the evolving product development landscape to stay competitive. Big Data can help manufacturers evaluate several product configurations that they can sell without impacting the existing production schedules and also provide agile responses to the product improvements that have been implemented.
Improving Customer Experience
With better information and insights, manufacturing companies can serve their customers better. By leveraging Big Data from partners, sales channels, and social media sources, they can gain greater visibility into customer preferences and needs and develop a better customer profile. With detailed information, organizations can draft better customer centric offerings and implement proactive and targeted programs for their customers. Big Data can also improve customer experience by improving the responsiveness of customer service with better support and proactive problem resolution and also help companies reduce support costs.
In order to leverage Big Data, manufacturing organizations have to have an architectural plan that encourages agile reporting and analysis. By integrating Big Data into the very information architecture of the data warehouses and aligning those with business needs and goals can help manufacturing industries implement well-scoped increments that can claim success.