Last week’s 5G Asia Summit attracted a diverse audience from across the region, including the likes of SK Telecom, Etisalat and NTT Docomo. The 3-day event covered subjects such as security, signalling, virtualisation and of course the road to 5G. Proving to be one of the most interactive sessions at the event, SysMech’s Mark Slinger joined Virat Patel and Ahmed Saady Yaamin on the panel entitled; ‘5G Analytics: What role will data analytics play in the connected device ecosystem?’
The technology challenges
Virat Patel, Managing Director of Pioneer Consulting Asia chaired the session, kicking things off with a discussion on the problems created for the central technology platforms managing the massive volumes of data associated with the connected device ecosystem.
Mark Slinger, Head of Product and Development at SysMech shared his experiences on working with the diverse mixture of data sources and use cases within the telecoms ecosystem. He explained how the underlying technology needs to cater to multiple use cases from several operational departments within a CSP. The functionality to put data into the hands of many users to investigate connections, automate activities and predict future outcomes is key.
Mark also discussed the need to process and store data more efficiently as volumes increase. CSPs can no longer treat all data in the same way, instead they need to understand the requirements of each use case. CSPs are now asking the question, ‘do I need this data now, do I need it in semi-real time or do I even need it in real time at all?’ The underlying technology needs a combination of datastores suited to the needs of both steaming analytics and long term data storage to successfully process the influx of data in the most efficient manner.
How to maximise value of data analytics in the connected device ecosystem
When the underlying technology can manage the data associated with a connected device ecosystem, the next logical question to ask is what critical areas should a CSP focus on to actually get value from big data analytics?
Ahmed Saady Yaamin, Vice President of Business Intelligence at Robi Axiata Limited explained that CSPs need to focus on the business problem top down, working down their data sources and identifying how to access what is needed. What is important is to actually get started – it’s OK to start small and then build on each use case to expand it.
Mark Slinger suggested that a bottom up approach can also be used; reviewing what data sources already exist and what correlation and connections can be found. This can help to identify unknown connections and uncover potential new value. The combination of both a top down and bottom up approach can prove productive agreed the panel.
One area the panel agreed on was the need to quickly act upon insight. In order to maximise value, CSPs must not only visulise their data, but also introduce processes that allow them to quickly act upon what they see. This should, ideally, be driven through automation, allowing CSPs to test big data outcomes quickly, fail fast, and adapt until a valuable result is achieved.
CSPs vs. big internet players
Progressing the discussions, Virat tackled the subject of why the big internet companies such as Google and Facebook can capitalise on their big data but CSPs seem to continue to struggle?
Both the panel and the audience were unanimous that CSPs need to get better at capitalising their big data analytics. CSPs have the right data, and have done for a number of years, but are just not making head roads when it comes to monetising that data in the same way as the internet giants. Of course we must remember that a direct comparison is not entirely straightforward as traditional CSPs have had to prioritise resource and investment in the network and handset subsidies from day one.
It was also agreed that there needs to be a fundamental shift in mind-set from the traditional ‘telco-approach’ to a more ‘internet-approach’ way of thinking. The internet companies all share common facets such as transparency, open access and freemium models. One member of the audience even suggested that CSPs introduce a freemium model, in which revenue was driven by targeted advertising based on insights from CSPs highly valuable data sets. This transition in mind set need to be driven from the top, and with the right resource structure in place.
At the end of the session, it was clear to see that big data analytics plays a major role in the connected device ecosystem. For this to prove profitable, CSPs not only need the right technology, but they also need the right culture.