The big data collected from consumer eCommerce shopping will provide valuable feedback to the retailers who in turn will be able to use this information to improve their product lifecycle and manufacturing. This is important to both the retail and manufacturing because it improves the raw material utilization and it also reduces the overstock inventory at the end of a product lifecycle. One of the greatest challenges of retailers is inventory management and replenishment and this is where big data can have the greatest impact in not only how much to manufacture but also a greater ability to focus the products for which the consumer is truly searching and not just the products for which the consumers settle.
The big data analysis can be much more valuable than information gleaned from surveys or even focus groups because the information collected from actual consumer shopping is honest in the respect that it is not influenced by the retailer’s assumptions. Another reason for the value of big data analysis is that the information is provided continuously on a near real time basis. This continuous update process allows for a continuous refinement of the analysis that can be utilized to refine the forecast and planning.
This continuous analysis refinement supports an ability to adjust as trends and changes in the shopping occur. This is important so that a more accurate view of the demand and sales can be developed throughout the sales cycle. Each offering has a life cycle where the sales begin to grow, they then level off and at the end of the sales cycle they decline. This sales life cycle is in addition to the product life cycle, in other words, each product will be offered in a series of sales cycles. These complimentary life cycles are found in fashion products along with home goods, appliances and even hardware such as tools.
Retail and manufacturing have always collected and analyzed demand planning and forecasting information to develop the product and sales lifecycles. Big data now provides the ability and the tools to expand the information collected for analysis and then to develop the complicated algorithms required to perform the demand planning and forecasting analysis on these large amounts of data. While demand planning and forecasting has been around and been improved along the way for a long time, the opportunities presented by the huge amounts of data that big data practices are able to effectively analyze will bring new knowledge to the process. The value that big data brings to the table in the manufacturing practices and life cycle is this new knowledge regarding consumer shopping habits and the continuous accuracy of sales trends revisions.
And now for the audience participation portion of the show…
ECommerce will have wide ranging impacts on both the retail and manufacturing sectors. How can you focus these abilities to improve the consumers’ experience? Improving the consumers experience will require a re-evaluation of the sales channels, the manufacturing channels and practices and the supply chain channels and practices from the raw materials to the consumers’ homes. In order to ensure and maintain success in this new reality you must harness the tools and capabilities in many new areas. How can you support these continuously changing requirements?