Big data is here: The tools, technologies and the opportunities for gathering and analyzing large-scale data have finally evolved where most technology-savvy businesses can think of leveraging such data for competitive advantages. While retailers are focusing more on understanding the customer preferences to better manage their merchandise and enhance the business profitability, there is a definite play on leveraging the big data in supply chain functions as well to enhance operational efficiencies and reduce costs.
McKinsey Quarterly recently published several articles on this emerging technology. They profile AstraZeneca which recognized the power that real-world data (such as medical claims) gave the pharmaceutical companyâ€™s customers in evaluating the cost effectiveness of its products, and a retailer who found themselves perplexed by the sales reports showing that a major competitor was steadily gaining market share across a range of profitable segments. It explains that this â€œ...competitor had made massive investments in its ability to collect, integrate, and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments. At the same time, it had linked this information to suppliersâ€™ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing, and making information instantly available across the organizationâ€”from the store floor to the CFOâ€™s officeâ€”the rival company had become a different, far nimbler type of business.â€
While such focus on collecting the sales data to analyze the customer behavior is getting quite commonplace with retailers pioneering the space (think of Amazon and Nexflixâ€™s â€œyou might also likeâ€ lists, based on your buying behavior and reviews), there is plenty of big data streaming from the supply chain operations that can be leveraged for optimizing processes, automate decision making, and increasing overall efficiencies. Part of this big-data wave is being driven by the RFID tags that are slowly becoming embedded in all parts of supply chain and have moved from pallet-level tagging to item-level tagging and the other big part is the ability to capture, analyze and use the real-time POS data from the stores and other selling-channels. Together, these two data streams can be leveraged to better understand demand and manage inventory, supplies and resources.
The real-time POS data from the stores holds a treasure-trove of data for managing demand. It helps identify what is moving and how fast it is moving; it also holds information on quantity, price, discounts, and coupons being used; and enriched with the geo information! All this can help manage demand better by evaluating and optimally deploying inventory in the chain to prevent stock-outs at the most profitable stores. This data can also be used for continuously evaluating price and other incentives to enhance overall profitability, manage seasonal ramp-downs, and reduce the need for clearance events. It can drive the open-to-buy decisions and automate such decision-making to a large extent. Changing demand patterns across channels can drive the channel-inventories and can provide critical information for merchants.
As item-level RFID tags become ubiquitous, the retail shelf can also assume the role the inventory analyst at the store! It can send alerts for restocking the shelves when the presentation quantities fall below the threshold, but it can also order store replenishments when the store supplies fall below inventory thresholds. Connect this consumption data to real-time demand and you can think of intelligent automated inventory ordering and replenishment systems in the store that can respond to the real-time consumption in the store to ensure almost zero stock-outs. Now that is service we can all live with!
The RFID tags can also greatly help associates to restock inventory in its correct place so you would never have to find the teabags in the spice shelf.
The warehouses can become intelligent as well by sending replenishment order requests for themselves by continuously monitoring stocks and doing so well before the service level maintenance is jeopardized.
The same tags can track the inventory-in-transit in real-time: Such visibility can help in making intelligent inventory deployment decisions. This is especially true for managing the seasonal/fashion items where the orders are placed well in advance of knowing how the actual demand may play out.
As the ability to collect, analyze, and use real-time demand and inventory data becomes more accessible, it will open up another cycle of optimizing the supply chain operations and provide competitive cost-advantage to those who can leverage the technology for enabling their business processes.
Originally posted by Vivek Sehgal at http://feedproxy.google.com/~r/SupplyChainMusingsstrategyVisionOperationalExcellence/~3/v57ZhYVaEFg/big-data-bigger-opportunities.html