The Unstructured Data Structure

There are numerous analytics platforms available in the market. However, where traditionally there would be a need for a data scientist or information engineer to develop models and manipulate data, solutions are coming to market from companies like cVidya, LavaStorm, Comptel, and WeDo Technologies that embed analytics applications in OSS/BSS to target specific operational needs like revenue management, determining churn propensity, and service assurance.

When it comes to analytics applied to the structured data required for revenue management, cost does not appear to be a primary issue. The need is so great and the return is so positive when analytics are applied to fraud management, revenue assurance, and settlements that service providers rarely question the cost of the solution. However, when asked to provide funding for analytics efforts that include unstructured data used for product and offer management, the returns are less visible and the risk to customer experience is greater. As a result, service providers are approaching those efforts more cautiously.

And lest we forget, the application of analytics to data of any kind is not just a technical challenge that can be thrown over the wall to IT. Every service provider has access to the same technology. To deliver value, business and executive leadership must be engaged to ensure that the tools are solving business problems and delivering business results. That requires more than budget; it requires time and resource commitment from subject matter experts, executives and managers across the business. Those individuals must stay involved to ensure that the resultant deployment of analytics and big data meets their needs.