Commerce 2.0 and the demands of continuously changing consumer shopping demands makes the data analysis both extremely important and very complicated at the same time.  The importance, I think, is clear because of the consumer shopping demands generate a great deal of information that retailers are very interested in analyzing to identify trends.  The complication lies in the spread of valuable data across many partners and platforms, including potentially the end consumer.  As in most complicated problems the solution is not impossible, however it requires careful planning to take into account complications and the limitations in order to deliver the solution.


The challenge is quite clear; how do you bring together data across platforms and networks to perform the analysis.  Even though the question may be simple there are many factors that must be taken into account to resolve.  Some of the key challenges are:

  • The definition of the data across partners to understand what is required.  Working across partners requires additional effort when evaluating what data to use in the analysis.  It is important to understand how the partners define and then collect the data in order to understand what to select for the analysis.  From the most simplistic example - one partner may use ‘part’ as the name of the item, while another may use ‘item’ and another might use ‘SKU’.  You can see by this example that it is important to understand the definition and not just the name of the element.
  • The communication network between the partners can cause delays or limitations in the volumes of data that is being passed.  This requires additional analysis to determine the most efficient means of moving data across the network.  In addition, this requires additional analysis to determine the most efficient location for the analysis.  In other words, maybe it would be better to perform a subset of the analysis on one partner’s network and share the results, or many it would be more effective to share the entire data group.
  • The location, or where, the analysis is performed can complicate the analysis exercise.  This would be a very common requirement to also determine the best method for partners to share information across the network. 
  • Finally the ‘ownership’ and use of the data must be clearly defined and practices understood and documented.  The data ownership remains with the partner collecting the data and the use and time frame for the use must be clearly understood and agreed prior to any analysis.


These challenges may seem overwhelming at first and will require planning and coordination in order to overcome them.  The point of the matter is that the data and analysis is more complicated with the more external partners involved.  This complication can be overcome though with planning, coordination and clear definitions and agreement going into the exercise.


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?