Revolutionizing Supply Chain Management
with Big Data Analytics
Revolutionizing Supply Chain Management with Big Data Analytics
Big Data and Big Data Analytics (BDA) are providing landmark changes to the Supply Chain Management industry. With access to new metrics, and often with assistance from third party logistics (3PL), customer service and business efficiency can both be improved. This is in addition to being able to identify and react to your brand’s reputation and make more informed business decisions.
Big data is defined as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”
This is all true, but it’s more than this. Big Data is all of the data taken from digital and traditional sources both inside and outside of your company that represents a consistent and accurate source for ongoing analysis of business to track progress and provide situational awareness.
Big Data Analytics
The cut and dry definition of Big Data Analytics is “the process of examining large and varied data sets -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.”
Let’s break that down. Big Data Analytics is the active process of taking large sets of data, organizing, and analyzing it to find useful patterns. This is useful to organizations in working to better understand what information they have collected, and in identifying what aspects of this information should inform their future business decisions.
The Effect on Supply Chain Management
Big data is characterized by the three V’s;
- Volume: Data comes in massive data streams from different sources including social media, business transactions, machine-to-machine information transfer, or sensor data.
- Variety: Data comes in all shapes and formats. This includes documents, video, audio, email, and more.
- Velocity: Big data analytics work fast. Having such a high data stream means it must be processed at a remarkable speed.
Having direct access to this volume of information and it readily analyzed provides several direct benefits.
- Time Efficiency: With tools like Snowflake available, in-memory analytics are able to identify what sources of information are and will continue to be helpful for making quick, but informed, business decisions.
- Product Development: In understanding popular customer trends you can design your development efforts around what you already have identified as a need.
- Understanding the Market: Analyzing big data allows you to better understand the current situation of the market. With a better understand of what is valued and what is not, you can customize your offers to the more popular needs of your clients, creating more value in your services.
- Reputation Control: Every company has an online reputation to some extent to another. Whether that reputation is good or bad can elevate your business to the next level or leave you seen as a plague to be avoided. With big data analytics you can see what is being said about your company; Reinforce the good points, and work to correct what is seen badly.
This information lends itself to countless opportunities to improve processes.
- Traceability: The ability to pinpoint exactly where a product is on the supply chain. Using barcode scanners and attaching a radio frequency identification device to a product a supply chain manager can create this easily.
- Forecasting: Big data sets are particularly useful in predicting what customers want and when they want it. Having accurate forecasting based on prior transactions throughout the supply chain allows companies to improve their profitability in predicting consumer demand.
- Relationship Management: Big data is profoundly powerful in helping improve customer service across the board. If every single stop in the supply chain has access to the correct customer information, there is a far higher chance of fixing any problems that occur during fulfillment, warehousing, or distribution and accurately fulfill the order.