- What is selling – and where: With POS data available daily waiting once a week to adjust store inventory is over. Immediate shelf adjustments puts the right product in the right place.
- Customer buying patterns: Patterns emerge from data about customer behavior and CPG companies can meet consumer needs before the consumer is aware of those needs.
- Is your data clean?: Pulling in structured data into rigidly structured DSR data warehouses is fairly straight forward. The retailer and CPG firm share and use the same definition for key retail elements. But as CPG adopts big data technology that allows ad hoc, sometimes unstructured data to become part of the analytics pool, CPG may find that the category managers and home office are using different definitions for sale, customer, etc. With flexibility comes responsibility – the responsibility of creating a single definition for common retail elements. Big data allows CPG the flexibility to do this.
To summarize – many nuggets can be mined from the transactional data received from the retailer. But it is increasingly critical that this data is brought in and analyzed much faster than before. Big, rigid data warehouses bog down loading increasing volumes of data making it more difficult for CPG category managers, supply chain and manufacturing to respond quickly to changing consumer buying behavior. Big data, by design, can reduce this process from many hours to mere minutes.
To understand how fast analytical insights can help you gain that competitive advantage for your brand contact us today for a complementary consultation. (We won’t tell your IT director if you don’t.)