Retailers must take into account the vast amounts of data required to maintain the social collaboration network across the consumer to the suppliers. This data will become the determining factor for the success of the network, including raw material suppliers, manufacturers, retailers, transport and consumers. All of these services and players must participate in the social collaboration network in order for the entire network to be successful and the data collected and shared across the network is one of the key factors that will produce the value for each of the partners.
The challenge of the data is determining what to collect and fortunately for all partners involved the big data technology makes both collecting and analyzing huge amounts of information possible. The challenge in the social collaboration network now is not so much the collection or analysis of the data, it is the data sharing and collaboration that must be used in order to analyze problems across the entire network of partners. Each partner, except of course the consumer, collects information they have deemed pertinent to their own environment and requirements. Now these partners must share this information across the network as necessary to perform extended analysis across the entire network.
The value of the data increases as the amount and the variety of data increases. This is a key baseline assumption. As a result of this baseline assumption the value of the potential data available across the entire extended network can be quite large. The size and diversity of the extended network provides the means to analyze questions quickly and the diversity of the information supports the accuracy of the results of the analysis. In other words, because of the data available from the very beginning of the supply chain, to the end, these analysis can quickly provide very accurate answers to the questions.
Due to the changing nature of the network, including the partners and available data, there are inherent difficulties in both developing and maintaining the data and the analysis. Every partner in the network owns their data and would share their data with the partners based on analysis requirements. This basis of data changes though based on partners leaving the network and then partners joining the network. This aspect makes some types of historical long term trend analysis a little difficult and must be taken into account when performing this type of analysis. A mitigating factor in this risk is the number of partners leaving the network would be relatively low and therefore the potential impact relatively low.
On the positive side, there will also be partners joining the network, including customer growth. These factors bring additional information and therefore additional value to the ability of the analysis. These factors would more than compensate for any partners that may leave the network and in fact I think it would also be a discouraging factor to leaving the network.
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 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?
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