Is Big Data Really Here to Stay?

Posted by Nick Ostdick on Apr 25, 2017 9:00:00 AM

Arguments persist about whether Big Data will last in the manufacturing industry. Fact or fiction. Trend or mindset. Fad or fixture. While Big Data has certainly permeated nearly every aspect of today’s manufacturing and supply pipeline, some industry analysts still question the validity, value proposition, and staying power of Big Data for companies as they strive to streamline their operational platforms and leverage lean manufacturing principles for optimal productivity and profitability.

First introduced to the manufacturing and supply chain landscape in the early 1990’s as a method of grouping, sorting, and analyzing large and complex data sets into executable actions. The sorting of these large, unstructured datasets gives manufacturing companies 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.

Yet, even so, some questions still remain as to the longevity of Big Data particularly in variant-rich industries where change and evolution happens in the blink of an eye. To shed some light on this issue, we’ll compare and contrast those who believe Big Data is a passing trend with those who believe Big Data isn’t going anywhere to answer the question: Is Big Data really here

The Big Data non-believers

For those who cast Big Data aside as a non-essential element in today’s supply and manufacturing industries, their argument stems in large part from the viewpoint that Big Data complicates rather simplifies, creates additional layers of undue complexity instead of creating increased levels of visibility and transparency. The basis for this outlook is comprised of several key points including:

1). Big Data is well-suited for identifying correlations or patterns within unstructured data sets, however, Big Data lacks the capability or insight to provide planners and managers with the connection, links, and larger meanings behind these correlations. Essentially, Big Data can connect a handful of dots to create a certain outline or image, but deciphering what that image means on a larger scale is where Big Data fails to meet expectations and needs. 

2). On a related note, because Big Data is so adept at showcasing patterns or correlations, some industry analysts worry a reliance on Big Data can result in too many correlations, some of which may be false or invalid. This can lead planners and managers to execute planning and production decisions based on data and reporting which have built-in deficiencies due to the ease of correlation and pattern recognition.

3). Big Data excels at analyzing data and reporting which contain common variables - or, in other words, when data is similar in structure and nature, Big Data provides an important value proposition in sorting and structuring information. But as we know, the manufacturing and supply industry is variant-rich with a number of shifting variables and elements. Those who oppose Big Data charge is lacks the functionality to address outlying data and information, or instances where input varies from the norm. 


The Big Data believers

On the other hand, those who purport Big Data to be a truly disruptive and lasting force within the manufacturing and supply industry point to a number of key components of its functionality and capacity to help companies increase the efficiency of planning and production and streamline back-office or operational processes. Those on the side of Big Data argue from the standpoint that:

1). 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. 

2). 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 help companies reduce the costs associated with shortages, overages, and replanning programs. 

3). 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. 

4). Big Data also makes it easier for companies to examine their planning and production processes on a more microscopic level. Gone are the days when planners and managers waited until the end of the month or quarter to review data and adjust planning and production cycles based on outdated information. Big Data provides the link between daily production metrics and mid to long-term production goals. This allows companies to make critical adjustments in real-time based on shifting constraints, rules, or variables in production programs. 


Is Big Data worth the hype?

As you can see from our comparing and contrasting, one side of the argument clearly has more weight than the other - and more distinct points of fact to support it. While some within the manufacturing industry may still discount Big Data as a needlessly complex tool without any real value, companies who embrace Big Data have the evidence on their side that Big Data is a key value proposition in refining a company’s value chain, promoting organizational-wide growth, and giving companies a competitive advantage in an increasingly global market.  

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Topics: Manufacturing, Automotive Industry, Advanced Analytics, Supply Chain Management