Is it just me or has ‘big data’ become passé for others, too? It wasn’t so long ago that there was a conference on the subject being held every second week somewhere in the world. We became besotted with terms like Hadoop and were introduced to a new breed called data scientists.
As if data stored in Oracle, SQL and Teradata systems wasn’t big enough we convinced ourselves that we needed bigger data to be able to determine the very smallest trend or fad and be able to ‘profile’ customers at a ‘personal’ level to give them a better customer ‘experience.’
Telcos were told that this is what the new digital players were doing and that was one of the reasons they were able to become so popular and grow at astonishing rates – the antithesis of the general trend for themselves.
No one seemed to pay much attention to the fact that they were newer entities without the burden of legacy systems and that most actually made their money by crunching data and selling the results to others. Telcos, after all, were simply designed to provide connectivity and some once unique services – like voice and messaging.
Google may have started as a search engine but its founders soon discovered the power of data as a source of income, particularly in advertising. Amazon learnt very early in the piece that to sell customers ‘up’ they had to know more about them and be able to suggest linked products on the fly. Booking.com and Trip Advisor worked out that people were the best source of rankings for properties and used this to become powerhouses in their field.
All had a unique reason for analyzing data and all make money out of it, but I’m not sure how many telcos can boast increased revenues, let alone improved bottom lines, as a result of ‘big data’ initiatives – even though many have been practicing the fundamentals for some time, but maybe didn’t realize it.
Revenue assurance and fraud management stand out as examples where telcos have excelled at extracting data from multiple sources, and some incredibly complex systems. They have become experts at normalizing that data, storing it in ‘big’ data repositories and processing it, often in real-time, to minimize leakage and risk. Anything recovered was reflected straight on the bottom line because it was previously accounted for at cost levels but not as collected revenue.
That may seem a relatively simple example, but that very same data is now being used to monitor customers that may be churning, determine profitability of tariff plans, products and services, and even to determine if a customer is even worth keeping! And all without impacting the performance of systems that provide the data in the first place. Pretty clever stuff, when you think of it.
But what makes all this interesting is that they don’t need a team of data experts and scientists to make use of their big data. Their existing vendors of network equipment and back office systems have developed apps that allow them to use the data any number of ways and by using visual aid like ‘drag and drop’ with results popping up on ‘dashboards’ that give management a quick and easy to understand visual that makes running the business that much easier.
Of course, these apps will not replace the really complex data analysis that some businesses think they need, but it is a lot cheaper and the return on investment is quick and tangible. As we so often see, the lure of something new and exciting, sold with brilliant marketing, may distract management from using what they already have more effectively. In the case of data, the grass may not necessarily be greener than that in your own backyard, and bigger may not necessarily be better.
This article first appeared in TelcoAnalytics Asia, May 2015.
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