However, the tools alone are not sufficient. Analytics relies on asking questions of the data to generate insight and, given that CSP data is useful to many different teams and departments within the organisation, there is a real risk that non-expert users will find the analysis process difficult.
The need to obtain insight and capture value will grow more pressing with the increased focus on customer experience, the advent of VoLTE and the surge of data that this will create. Moreover, the ability to assure the experience the customer has when using the CSP’s services and networks is crucial in order to minimise churn.
Robert Eriksson, director of customer experience management at Polystar, gives the example of a CSP
that is deploying VoLTE: “CSPs have an edge on OTT voice services when it comes to the quality of the
service. When deploying VoLTE it is important to be able to monitor and assure that the quality of the voice service maintains the high level expected by users. At the same time, VoLTE is a complex technology that needs to work in some complicated scenarios,” he explains. “The CSP has to pay particular attention to how all of those can work together. They must have the information they need to be able to assess network performance, service quality, predictive tasks, and have early visibility into any problems that may affect the perceived quality of the service.”
The problem, though, is that one size does not fit all. It is not possible to have a single set of big data, and common dashboards to visualise it: such an approach would not suite the needs of all users within a CSP. Different teams have different needs for data – and different ways in which they need to visualise it. What is required is a way to adapt the data and the way in which it is visualised, so that different teams will be able to extract the maximum value from it.
In other words, CSPs need a means to short-circuit the analytical process to make function-specific data available to the different types of user within a CSP.
“What Polystar is talking about is how the information that exists with CSPs’ big data can be directed to the people who actually need it,” adds Eriksson. “We are collecting huge amounts of data, we’re addressing how we can choose sub-sets of that data and then deliver it to the people and places where it will have an impact. We need to make this accessible, so that CSPs can assure their customer experiences and deliver new services securely and profitably.”
Polystar has developed a proposition that takes care of the capture, sorting and the storage of data from networks and services, so that it can be accessed and utilised by the different teams and departments within a CSP. “It has got to be made easy for each user to interpret the data,” says Eriksson. “We have to convert it into something that is relevant to them.”
That means a technology product on its own is not sufficient because it can’t know the operational priorities of a CSP business unit. For that reason, the Polystar proposition involves working with the CSP to understand what is relevant to it. “Which key performance indicators are required and how they
should be presented can only be identified by understanding the underlying needs of the users. In
turn, this can only be understood by working closely with the CSP,” says Eriksson. “It’s not about us giving you what we think you need or giving you everything we think you might want. Instead, it’s about us gaining an understanding of each customer’s priorities and tailoring the proposition for their specific situation. You can focus on doing your job, while we will interpret your needs and deliver the appropriate technical details.”
Polystar acknowledges that CSPs typically have similar key goals, which is useful when identifying
areas in which to make data available to CSP teams. However, he points out that CSPs are not all the same.
“A greenfield LTE operator will be different from a CSP that has 2G and 3G and a new group of LTE customers to serve,” explains Eriksson. “What we offer is designed to support not just what we think matters but also what matches the needs of our customers.”
Polystar’s approach is to create solutions aimed at specific stakeholders within CSPs. The solutions
provide the data that is relevant to different functions, and is visualised in a way that supports the workflow of the users.
The solutions already cover the majority of daily needs, but for queries that demand a very high level of detail, Polystar’s system also provides drill-down capabilities to enable insight from the lowest level of signalling events.
Within that context, operations could be a specific user group that needs specific data to assure
continuous network performance and consistent customer experience. To achieve this, they need powerful analytics tools adapted to their needs. Other groups can then use the same sources of data, but
filtered and adapted to support their needs, such as customer care, marketing, and other functions. It’s inefficient to have each group analysing the complete set of data to obtain the insights required.
“Having the single platform that we offer enables the needs of different groups to be met in group-specific solutions without duplicating effort or the resources used,” says Eriksson.
It remains early days. “We’re only beginning to scratch the surface of the practical application of big data analytics but we have identified clear use cases and needs,” Eriksson adds. “This process will be iterative and we fully anticipate the use, to which CSPs put the data we present them with, will evolve dramatically.”
Use cases Eriksson identifies include:
• Analysis of near real-time data when introducing new services like LTE and VoLTE to provide insight
into trends and provide predictive information to support network engineering and service operation
centres (SOCs);
• Improving first-call-resolution and customer experience in customer care by providing information on the likelihood of specific types of problems;
• Supplying product management and marketing with actionable customer insights to identify user
behaviour that could help in designing a new service, bundle or marketing campaign.
Those examples are only the tip of the iceberg when it comes to data analytics and Eriksson anticipates
increased usage of data insights stimulating further demand. Use cases will proliferate and the number of groups needing data presented to them in a way that is readily accessible and understandable will increase exponentially as a result.
“As a telecoms supplier, we intend to support CSPs through the CSP’s entire LTE and VoLTE journeys to
ensure they achieve significant returns on their investments in data analytics,” Eriksson concludes.
