At first glance one would think, “We’ve always had real-time customers, haven’t we?” The short answer is a conditional "yes". We make and receive calls, surf the web, open applications and perform tasks when we need to. This level of activity has historically been relatively easy for operators to forecast, build capacity to support, and most importantly, monetize.
So why is the concept of real-time important now, especially within the context of transforming networks and business models to support this? It is because the profile of a customer is no longer what it traditionally was. Customer behaviors illustrate massive drops in traditional services, while consuming data-driven services at rates that no longer financially support the standard practice of overbuilding the network.
How is the customer profile evolving? With the rapid rise of IoT, device applications have exploded onto the market, with literally no end in sight as we “digitize” our lives. The definition of a customer is no longer bounded by a handset, or even a group of handsets (families, business customers, and so on). Today, a customer is a more complex entity, where handsets are just the beginning. A customer is now further profiled to include Smart Home systems (alarms, appliances, climate controls, lighting, landscape watering); Smart Vehicle systems (maintenance, navigation and traffic, streaming and WiFi access, autonomous driving, mobile commerce, etc.); Medical Health platforms (sensors to track health, inform loved ones, inform health care providers); Smart Cities (municipal traffic, air pollution, energy and sustainability monitoring); and many other potential device and access variables.
What further complicates the view of a given customer is the concept of "access". When customers had a single device in hand, an operator could know where a customer was on the network, and could manage and forecast necessary bandwidth and capacity to support that. The onslaught of IoT and the cloud has complicated it so that a customer can appear (to the network) to be in many places at once. Wireless and wired devices attached to that customer or their account may initiate activity, albeit large or small in consumption, through any of these devices, at any time.
Profiling and Predicting in a multi-dimensional world. Network forecasting and planning has evolved to become sophisticated over time. Predicting behaviors of different demographics of customers has helped operators effectively augment planning and budgeting. However, in the past, relationship of a customer to his or her access was a linear conversation: operators knew that behavior was predominantly driven through a single point of access — the mobile handset. With the advent of multiple devices generating data that is driven by a customer, group of customers, or an event (e.g., weather event), this is also changing.
Imagine if a digitally enabled car that is streaming videos to occupants, while autonomously driving those occupants for 20 miles. In this vehicle, there may be many connected devices, such as handsets occupying spectrum in CDMA/GSM and the vehicle platform itself as with LTE-connectivity, not to mention perhaps a passive GSM connectivity for roadside assistance services.