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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

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