ANALYTICS
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CLOCKING OFF!<br />
Data analysts need to take<br />
a look at themselves<br />
As data analysts and scientists become among the most in-demand experts, Nick Booth<br />
wonders what would happen if they analysed their own use of data analytics<br />
O<br />
ne of the joys of reporting on the telecoms<br />
industry was that it was full of<br />
uncomplicated, no nonsense characters who<br />
didn’t feel the need to invent their own<br />
special secret language – unlike the IT world.<br />
Communications service providers (CSPs) were happy<br />
to connect people and let them get on with their lives.<br />
No dodgy software contracts packed with hidden<br />
licensing trojans. No built in obsolescence. No<br />
grandiose claims about saving the world,<br />
revolutionising business and bringing democracy to<br />
society. Granted, the CSPs and their dealers did<br />
charge huge amounts for managing moves and<br />
changes for their clients. But even that was a good<br />
discipline, as it stopped people moving about and<br />
over-complicating things.<br />
The modern incarnation of the telecoms operator, the<br />
CSP, is mobile and data driven so, inevitably, they’re<br />
becoming more like IT companies. But, I’m relieved to<br />
say, they’re not quite the full Amazon, although many<br />
shareholders and equity holders won’t be pleased<br />
about that. They want their CSP investments to be<br />
omnipotent and ruthless.<br />
Still, it’s obvious that data could save the life of the<br />
CSP by creating new opportunities, but then ruin it all<br />
over again by over-complicating things. The modern<br />
CSP has far too much complication to deal with, but<br />
they like to make life even more difficult for themselves<br />
by constantly moving their own goalposts.<br />
The rapid growth by acquisition means that there<br />
seems to be a massive disconnect between the<br />
various departments of a modern CSP. The people in<br />
the call centre rarely have any connection with the<br />
intelligence available in their own data centres. John<br />
and Jane call centre operators only seem to be<br />
interested in two things. Getting you off the phone as<br />
soon as possible or selling you something you never<br />
knew you wanted.<br />
There is a certain logic to this. According to David<br />
Zakkam, relationship head for data sciences company<br />
Mu Sigma, the average CSP could save a million<br />
dollars a year if it could shave a second off every<br />
support call. Zaikai advises 140 of the Fortune 500<br />
companies on how to use data analytics to make each<br />
call more efficient and productive by giving call centre<br />
staff a better idea of who you are. However, having<br />
worked in a call centre myself, I suspect that many of<br />
the managers at shop floor level will take a much less<br />
sophisticated tactic. They’ll instruct their ‘here today,<br />
gone tomorrow’ minions to say anything to get the<br />
customer off the phone, once it’s obvious that they’re<br />
not going to buy anything.<br />
Which brings us to the second option, up selling.<br />
Again, I will rely on the testimony on an expert witness<br />
from the telecoms industry, Eliano Marques, head of<br />
data science at the Think Big Partnership. CSPs<br />
constantly offer things to clients that they have no use<br />
for at all. “I often try to understand the logic of the<br />
sales people at service providers. Why do they offer<br />
me 200 channels when it must be clear from their data<br />
that I only use ten. And why would they keep shoving<br />
a Samsung offer on me, when it must be obvious from<br />
their data that I’m an Apple fan,” says Marques.<br />
It would seem there is a massive schism between the<br />
people who think for the company, the data scientists,<br />
and the people who act for it, in the call centres and<br />
the support teams. They seem to have completely<br />
different and counter productive targets.<br />
Every CSP aims to progress with use cases that have<br />
an instant pay off, says Marques. Data scientists,<br />
whether internal or external, are hired to identify the<br />
best action for increasing profitability for the company,<br />
either through cutting costs or boosting the revenue.<br />
But the gap between potential value and the<br />
achievable value is often massive. For example, the<br />
best way to cut costs would be to create a predictive<br />
maintenance model that would identify where<br />
problems will occur and nip them in the bud. But it’s<br />
also the hardest. Partly because the people who are<br />
sent to do the fixing jobs have their own agendas,<br />
which don’t align with the company’s. The fastest way<br />
to meet your targets, I discovered, was to pass the<br />
buck, tick your box and re-assign. The thoughtful few<br />
who actually tackled the hard jobs would get no<br />
reward.<br />
If only there was some way those people-centric<br />
problems could be analysed!<br />
The author,<br />
Nick Booth,<br />
is a contributor to<br />
VanillaPlus and a<br />
technology journalist<br />
The rapid growth by<br />
acquisition means<br />
that there seems to be<br />
a massive disconnect<br />
between the various<br />
departments of a<br />
modern CSP<br />
VANILLAPLUS MAGAZINE I SEPTEMBER / OCTOBER 2016<br />
57