Consumer Chain Data

The greatest potential value proposition that will result from implementing a consumer chain and the technology integration architecture and framework is the potential of big data combined from across the consumer chain.  The big data potential though requires preparation, planning and expertise that may not be currently available to you.  There are specialized skills and experience required to implement a robust big data architecture and more importantly it is essential to develop the big data architecture and framework that will support the near future needs of your consumer chain.  The initial design should be supported with a high quality design from experts to build the flexible and robust framework to support the big data needs.

The skills required to design a robust and flexible big data architecture to support your needs are not common and cannot be effectively provided by your database management team.  Big data expertise and experience are specialized and you will gain the greatest value from investing in specialists to work with you to perform the analysis and design of the architecture.  Starting with a stable platform is important to the success of this initiative and skimping on the investment will end up costing you much more in costs to rework and lost opportunities for analysis.  This is very much like the old commercial ‘pay me now or pay me later’, if you skimp on the initial investment you will end up paying much more in the long run.

From a data collection and analysis perspective there are three areas producing the greatest volume of data and the greatest volume analysis requirements;

1. The online consumer community site supporting the interaction and retention of consumers.  This site provides a wealth of data related to the consumer interaction and participation in the community to identify product likes and dislikes and also potential combinations of products for cross selling opportunities.
2. The eCommerce site supporting the shopping and sales demands of the consumers.  This provides the finalization of the consumer shopping experience from the search and shopping patterns to the final sales to support analysis of site logistics, product offerings and combinations.
3. The supplier data supporting the procurement and supply of new and continuing products.  This is really a two way street and a point of value for your suppliers.  The retailer provides the early forecasts and sales statistics for the products while the supplier provides the procurement through shipment of the products to the retailer.  This is especially important to efficiently managing the inventory life cycle and especially managing the overstock inventory.  

The data repository and the data analysis are extremely important to the ability of the partners to derive value and inefficient data storage and analysis or missing data can have a dramatic impact on this value.  This is why it is important to invest in the early development to provide a solid and robust framework to build.  Remember, you can pay for it now or pay a much greater price later to develop this architecture and framework and it is better to pay up front because of the long term savings and value realized.      

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 consumer's experience?  Improving the consumer’s 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?