A Data Science Central Community
In the current context of fierce competition, in order to maintain their position, large companies must use a variety of means: service commitments, multichannel approach, extensive monitoring of the supply chain until the last kilometer, digital communication, shop connection, website, call center, customer loyalty program, community animation, products and prices personalization, etc.. But above all they must continually put the customer at the heart of their strategy, and make it as the first priority of all their employees, who have to make the smile as a key component of their business.
It is clear that many business do not live up to their customer good experiences: long waiting queues (which are virtual phone store or concrete), sellers more or less competent and sometimes unscrupulous, orders process by phone complicated and time consuming, internet opaque contractual clauses, unfulfilled commitments, customer service unreachable, claims not taken into account, at the slightest problem infernal spiral of unnecessary calls, no vision of the historical relations, etc..
Beyond the definition of a strategy focused on the customer, the adaptation of the organization, staff training and the development of effective information systems to manage operations, large companies which want to lead the race must invest heavily in their decision-making systems, and in particular use Big Data to better understand the markets, control their actions and ensuring their clients experience they expect. But beware there are no ready-made solutions, ready for use, that solves all the problems previously mentioned.
Although technologies of traditional BI systems continue to evolve, they are generally very mature and professionals know the effective implementation. It is quite different for technologies related to Big Data, which are for the most part a very recent release, poorly understood and poorly controlled by the small number of professionals who have some experience in the Big Data. Despite this unfavorable context, it is necessary for large companies to launch Proof of Concept project to begin to learn the Big Data processing which must be common use tomorrow.
If virtually all business functions can be affected by Big data, now it is mainly the Marketing / Sales functions which care the most. For these functions it is mainly to find new opportunities, through the tracking of usage and customer experiences, highlighting expectations, needs that can be met with innovative offers, exploit the relations, position the offer, push the offering to potential people at the best times of contact, optimize their marketing investments based on the results they have seen with previous programs.
But if the Marketing / Sales functions offer many possibilities, it is not always easy for a company already well equipped with decision-making information systems to find where to start with the Big Data. Indeed in some cases using Big Data merely bring a little more information to support analysis to improve the results of an existing model, and thus often the new Big Data application, although that it offers a significant contribution, could not bring a very interesting ROI. It is therefore preferable to seek to invest in new areas of analysis that are little or no coverage, and return to the improvement of existing practices in a second time.
To find the correct fields to invest, there may be a good approach to look at pioneers; some very large international companies are racing ahead. Teradata for example, has created a club of companies that have more than 1 P0 in their decision-making system and use new Big Data technologies. The club currently has about forty companies and representatives in almost all major industry sectors (eBay, Apple , Boeing, Wal Mart , Barclays, AT & T, Pfizer , Well Point Health, Intel , etc.). We can also learn from smaller companies that do not have one P0, but for which Big Data are vital as: LinkedIn, Gilt Groupe, Chegg.com, Zazzle, Eightfoldlogic, Razorfish, Insight Express, Machinima, Intuit, Full Tilt Poker, etc.