It’s safe to say Big Data is here to stay. Since its introduction in the manufacturing landscape in the early 1990’s, Big Data has demonstrated its value proposition in the capacity for grouping, sorting, and analyzing large and complex data sets into executable actions, provides planners and managers the capability to apply predictive analytics and other forward-looking logistic strategies to increase the efficacy, efficiency, and cost-effectiveness of planning and production programs.
Big Data has since found a home working in tandem with other supply and manufacturing movements such as Industry 4.0, Advanced Analytics, and The Internet of Things (IoT). Alongside these technological developments and platforms, Big Data has helped companies gain increased insight and visibility into a number of critical planning and production functions such as forecasting, modeling, data analysis, and the implementation of integrated sales and manufacturing principles for a more streamlined production cycle.
However, even with all these attributes in its favor, questions still abound for manufacturing companies as to how implement Big Data into a planning and production scheme to leverage the benefits Big Data has to offer. Questions like: How should manufacturing companies leverage the information, data, analytics, and predictive insights created via Big Data into a competitive advantage? Or, what benefits does Big Data provide planners and managers in terms of reducing supply chain management risks? Lastly, how does Big Data impact the entire production cycle from planning and procurement to transport management and customer relations?
With these questions in mind, let’s examine how exactly Big Data drives manufacturing efficiency and how companies can turn these efficiencies into opportunities for growth and expansion.
Integration with intelligent planning systems
Because Big Data operates via a cloud-based memory and data storage platform, it allows for a seamless integration with existing intelligent planning and reporting systems. With Big Data’s ability to function alongside a centralized database that helps eliminate planning and communication silos, planners and managers can deploy a Big Data-driven operational structure with little to no disruption in existing workflows. If we conceive of a lean supply stream with a front-end of the cycle driven by such enhanced planning platforms as Industry 4.0, demand capacity planning, job and resource allocation, then it makes sense the back-end of the production cycle (or the analysis side of the cycle) would benefit from a detailed, specific, and powerful analytics structure like Big Data. Essentially, integrating Big Data into an existing planning and analysis relationship allows one hand to wash the other, which pushes for greater end-to-end visibility (E2E) and agility across the entire value chain.
Increased planning accuracy and precision
Increased accuracy of forecasting and modeling is a critical element of operation for today’s manufacturing companies. According to a recent article in Forbes, Big Data can help companies increase the efficacy of their demand planning strategies by more than 40 percent. This means Big Data not only helps companies procure materials, manage inventory, and allocate jobs and resources more effectively, but it also helps companies reduce the costs associated with shortages, overages, and replanning programs. Additionally, as we just discussed, Big Data has and is continuing to increase the adoption of other industry-leading movements such as Industry 4.0, Advanced Analytics, and The Internet of Things. Essentially, if we view these three components of modern manufacturing as the car, Big Data is the fuel that allows the car to drive down the road. Because Big Data is largely built on Cloud technology and provides companies with easy information sharing and the ability to break down communication and planning silos, industry analysts believe it’s impact and staying power cannot be understated.
Holistic insights into supply situations
One of the biggest value propositions of Big Data for today’s manufacturing companies is the ability to view, in the moment, the holistic strengths and weaknesses of a company’s supply chain, production cycle, and overall supply network situation. Because Big Data provides such detailed insights into very specific data fields, it’s easier for planners and managers to understand on a large scale the health of their planning, production, and transport processes. On a network partner level, Big Data gives manufacturing companies greater insight into supplier quantity levels and enhanced capability to predicting supplier productivity over a given span of time. Because Big Data works in conjunction with Advanced Analytics, companies can view product condition and quantity in real-time to help manage trade-offs. This means companies can provide more accurate production timetables and more precise delivery windows to bolster customer satisfaction.