The manufacturing industry, as a final example, has perhaps always been focused on data, as companies have strived for decades to optimize supply chains and speed time-to-market for the design, assembly and distribution of products. But even a sector as data-centric as manufacturing can benefit from a renewed focus on both the technologies and the analytics processes that stem from today’s Big Data evolution, such as developing an in-depth view of micro-segmented customer preferences to drive new product design and roll-out.
CSPs across the globe have been grappling with burgeoning network traffic for a while now, and the issues and implications are well understood, if not necessarily well managed, to date. But the opportunities from Big Data reach well beyond efficient management of network traffic. The analyst firm Analysys Mason recently wrote that they believe that mobile operators can derive the greatest opportunity from big data, because of three assets that they have in spades:
I would argue that any service provider – not only mobile operators but broadband operators, ISPs, international carriers, cable and satellite providers – can derive opportunities from big data. Big Data processes to capture information from as many sources as possible, aggregating data into comprehensive customer records, and applying analytical approaches to derive insight from this information, empower a CSP to better meet customers growing demand for content, portability of content across devices, and an enhanced experience that packages the collection of content and services tailored to each individual’s – or his extended social group’s – needs and tastes.
Within a CSP environment, there are numerous processes that are both critical to, and derive benefit from, better data analysis and understanding. Beyond increasing network record volumes, big data about operational processes related to customer service, billing, and customer financial management – including Days Sales Outstanding (DSO), treatment and churn – enables the CSP to expand automation and drive efficiencies into business-as-usual tasks.