This blog is by Claudio Frascoli at Nokia Networks.
There is no doubt that big data still is one of the hot topics in our industry with no shortage of discussion but also no easy way to gauge what real progress is being made. The tone of the conversation can help us a lot in this sense: What are operators currently saying? What are the key items on the agenda when we meet to talk about big data strategies? And, more importantly, has anything changed in the past 12 months?
When operators start evaluating how big data analytics could potentially improve their businesses, conversations typically become peppered with what I call the magic of big data. The focus turns to radical new business opportunities, or incredibly creative ways to mix and match data that would allow futuristic insight on customer behaviors. To borrow an analogy, it’s like talking about self-driving cars. They’re very appealing, but we’re not quite there yet.
The reality check usually comes when the conversation shifts from “What could be done in theory?” to “How are we going to do it in practice?” And I believe this is what’s happening right now in our industry. More and more operators have gone through the highs of the hype cycle and are now wrestling with all the practical implications associated with the introduction of big data analytics in a telecommunications environment.
How do I create a data-driven organization? How should the organization change to make better use of data? What skills do I need? Who is in charge of data? What data do I need and what is the best technology for my specific use cases?
To stick with the automotive theme, this is where the big data rubber hits the telecom road.
“External uses are not a priority because there are many hurdles for monetization. In our view, it is better to suffer the pain of implementation internally before being efficient enough for external monetization.” These are the words of Jean-Marie Culpin*, Group Marketing Director at Orange. I think he captures extremely well what has changed in the past 12 months.
Implementation first, monetization second?
Finding new revenue streams enabled by big data analytics is still a long-term priority and there are several operators that have been able to make substantial progress in this area. However, focusing first on use cases that more directly affect day-to-day operations is a great way to address some of the major challenges that big data analytics pose to telecom operators.
On the one hand, it simplifies the issue of finding the right business fit for big data analytics initiatives. For some, the starting point is customer experience management; for others, it is operational efficiency; and for others, it is marketing effectiveness. All of these areas are very tightly connected to the core business of mobile operators. This is where investments in data analytics are easier to justify to executive management and this is where they yield the most immediate returns.
On the other hand, this approach allows operators to focus on building capabilities that have the potential to really transform the way they operate and do business. I am referring to skills, tools, organization and processes that need to be in place to harness the value of data, and that must be in place when exploring the potential of external use cases.
Introducing CDO’s: Chief Data Officers
For instance, the issue of who owns data inside the organization is not a trivial one. According to European Communications*, operators are becoming increasingly aware of this and Chief Data Officers are starting to appear in the organizational charts of several telecom service providers. When you merge information from different parts of the organization, not only do you need to overcome technical obstacles, but you also need to ensure communication across company silos. And to ensure end-to-end ownership of data, you need proper processes in place for morphing data into business value through multiple use cases. This is all the more important when big data becomes a new business in itself, and clear ownership should be in place to ensure successful execution. It’s rather hard to sell a product if no one is responsible for it!
This is just one example of the many practical aspects or bumps in the big data road ahead. But, with a good (business) grip and a powerful (big data) engine, my only other advice is buckle up – it’s going to be a speedy ride!
Be sure to catch our recorded webinar that took place on Sept. 30, 2014: Big Data for dynamic experience management.
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* European Communications – Big data: External monetization takes back seat to internal use cases (Q2 2014)