Big data enables rapid analysis of huge amounts of data at faster speeds than any individual can ever achieve before technological developments. So, here are some ways big data has helped many companies to excel in the important task of materials management.
Predicting the seasonal requirements
The retailers & manufacturers know various seasons bring a diverse range of consumer needs and demands. Before the big data platforms got widely accessible, companies totally relied on historical data & educated assumptions of deciding how they will accommodate the seasonal fluctuations. Big data can now reveal specific trends and optimize stock management. The big data will help the companies to plan for the seasonal periods and holidays, like Christmas & school periods. Top brands will have to look at the data from earlier years & calculate which factors can result in the higher or reduced need for some items or products.
Big Data & Master Data Management
It’s quite tempting to draw the comparison between big data and master data management as both the terms are a bit interconnected, however, they are different.
Despite the differences, big data & MDM benefit one another. The big data feeds their insights to master data management, and MDM feeds data with the master data definitions. Big data exists even in real-time as well as involves prompt access to alerts, data as well as inventory management or control metrics by cloud computing systems.
But, the volume and velocity of big data hinder companies to make the right & timely decisions without any use of data management solutions. In order, to overcome such challenges, the use of the MDM will create the logical point for the big data analysis. MDM manages important information that is a bit critical for the business processes.
Whereas MDM mainly involves combining the internal info from the different company sectors and bringing this together in one area, this is considered as the basic information, which involves the smaller data sets. The information will include the inventory levels, customer details, sales as well as other basic information that will be moved on a single file.
Reducing reach of the recalls
Whenever companies get product recalls, they need to act very fast to reduce any damage that is caused to the people, stores, and companies. The easiest way of doing this is using number-tracking software when any brands identify their problematic batches. The lot numbers will be assigned to the shipments of the products, like those produced at the plant on one specific day. After that, companies will see which stores have received these recalled products, and which maker produced them. One such example is Amazon that uses big data in order to decide if it has to stop shipping certain products because of food safety risks. Thus, it monitors 67 sites daily for any incidents of food safety warnings & potential recalls.
Perhaps another significant benefit that big data provides inventory management is to improve its efficiency. The warehouse operations will include several small and interconnected processes. Suppose one of them lags, then it will cause some issues throughout the whole process. With big data, the managers will have to address efficiency-related issues they don’t know existed. The information collected from different tools warehouses use will tell administrators in case machinery is not functioning at its best performance. In the same way, data collection will inform the supervisors of the employee performance & suggest different ways of increasing productivity.
The poor organization will lead to slowed and faulty operations, as the right organization will optimize this process.