Wasp Barcode Technologies: The Barcode Solution People

Big Data and the Supply Chain

2014-Big-Data-Comp3 As companies continue to collect increasingly larger volumes of marketing and analytic data over time, something unexpected has occurred: data sets often become so incredibly large and unwieldy that they are difficult to manage, analyze, and even store. Nevertheless, these large data sets are incredibly important -- so important that new methods of interacting with them have been devised and companies are recognizing the overall usefulness of the data. Volume, Velocity & Variety In the early days of computing, the data collected was quite minimal. A consumer's name, address, and telephone number might be collected -- if that. As computer technology advanced, it became possible to capture almost every aspect of a client interaction or transaction.  The volume of big data is valuable only if it can be "mined" for meaning. To mine big data, you need to have the proper tools, and you need to know what you're looking for; traditional analytic procedures simply do not apply. According to Ginni Rometti, the CEO of IBM, "Big data will ... force the marketer to understand each customer as an individual within 18 months or risk being left in the dust." Collecting and analyzing big data may seem like a challenge only facing larger corporations; however, the evaluation of big data is essential for small businesses to remain competitive. While the concept of big data may seem intimidating, it's actually relatively easy to acquire and use. Additionally, the velocity with which big data speeds through a company means data collection tools must be equipped for the ever increasing amount of data transmitted and those same tools must allow a business to analyze the data quickly and efficiently. From employee productivity to consumer habits, big data collection encompasses a wide variety of information that needs to be analyzed appropriately to find trends and patterns. The ability to leverage the findings of big data analysis gives small businesses a competitive edge over their larger counterparts. Small businesses are typically more agile and can quickly adjust or modify strategies and procedures in response to the information gleaned from big data mining. Many small companies are doing so to tremendous effect. Big Data Prevents Bottlenecks Although most discussions of big data revolve around consumer information (personal details, purchasing trends, website traffic, etc.), there is incredible potential for extracting supply chain details: distribution & logistics, manufacturing, and sourcing/suppliers.  In fact, much of this data may already be accumulating as part of independent systems and only needs to be combined for analysis. Using large amounts of real-time data helps small businesses adapt by preventing bottlenecks throughout the supply chain. Systems that allow users to collect data at each stop along the supply chain give businesses the transparency needed to control inventory fluctuations: whether in the raw goods used to manufacture products or in the finished goods being sold and distributed to consumers.  An inventory management solution that records item data by scanning barcodes is an efficient and easy-to-use method for both big data collection and big data analysis; which increases the overall cost-effectiveness of the supply chain. The optimization of inventory management through big data analysis ensures inventory is stocked and replaced appropriately and that it is distributed throughout the supply chain in the most efficient way based on prior data. Thus, companies can use big data to resolve issues with order fulfillment or supplier management. Big Data Mining Any question regarding a pattern or trend can be discovered through a big data set as long as the data is available; using this type of data to make future decisions is called predictive analysis. Big data mining allows small businesses to predict the demand for inventory items; guaranteeing desirable items remain in stock and preventing the carrying of inventory items that do not move. According to the Harvard Business Review, 85 percent of organizations currently have big data initiatives or are planning to get into big data in the future. Thus, big data has become a necessity for those who want to remain competitive. Companies that move large amounts of inventory and supply chain management are likely already collecting volumes of data but are not using this data to improve business practices or procedures. Using the right technology to more accurately predict customer demand is the desire of any inventory manager.  Allowing analytic tools to draw that information out of data already collected by your small business will lower both your investment in inventory and the resulting carrying costs and will result in increased profit and competitiveness.