Why it’s the era of Data Science but not of the Data Scientist
By: Arjan Haring
Tags: Nerd, Big Data, Data Science

Intro Huig da Nerd alias @hugo_koopmans : uber-nerd/data-scientist > interested in data mining, (text) analytics, data visualization and how to make money with that. Managing partner at DIKW.

Data science is hot. Everybody is talking about it. Data scientists are being worshiped, and rightfully so. You have been working in data science for decades now (you look much younger).

Indeed I started out in the previous millennium with what we now call data science, back then be did “No cure, no pay” projects to proof we could predict customer behavior from data. Really? Really.

By the way, we never lost a challenge but still we had a hard time selling our product because it was so threatening to people. And actually that did not change…

Would you say the current Data Science hype is deserved? And what is the impact on business?

Well, “deserved” feels a bit awkward, I see it as an inevitable evolution of the human species (see Ray Kurzweill’s book “Spiritual Machines”, and yes I am a believer [Editor’s note: No.]) The impact on business is of course huge, even without the common public noticing.

For example the real-time auction of Google Adwords is still something that surprises a lot of nice looking ladies on the parties I attend (as hot (not so young) nerd you can imaging my party schedule…)

Did your projects change, (are they really getting cooler) if you compare with 10 years ago?

I must say “Yes” to this question, especially the possibilities with real-time, location based stuff is mind-blowing cool…

Let’s look at some of your guru’s. Davenport told us businesses have to compete on analytics. Do companies know there is a competition?

To be honest, no. Let me tell you a secret: Companies do not exist… a company is a collection of people… a brand is a concept to persuade consumers… but the people that work for companies most of the time are to busy to fight battles in their own little kingdoms and do not have the power to look over their own social network (max 50 people) and act on behalf of the company/organization (often more then 1000 people). But that is an evolutionary thing, as explained beautifully by Richard Dawkins (Blind Watchmaker, Selfish Gene | Meme).

So individuals understand very well there is a competition, as said, it is like playing Chess on to different boards at the same time.

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Thomke convinced us that Experimentation Matters, but do companies care? Which companies have adopted a culture of experimentation? Not very many and if they have they have a hard time keeping it(see last alinea for why). Siegel shows us organizations can predict who will click, buy, lie or die. But how many companies truly have precog capabilities?

Again, still very few companies are able to leverage the predictive power present in their data. I have seen examples of companies that fight their own size and inflexibility to the extend it hurts every day big-time. But the truth is that predictive capabilities are not (yet) the biggest challenges companies have. A lot of companies are still very very busy with their core processes.

And in the (database) marketing domain most people are just afraid that they cannot proof their added value, really… I have been in lot’s of places were I tried to spread the word, almost on a religious basis, to see marketing as a series of statistical science experiments. That is, to see a campaign as a statistical experiment. Yes, including control groups to examine results so we can proof the added value of floors full of marketing people. But I still fail miserably. O, so that could be me? Hmmm… let me think about that, next best question please.

With Data Science being the hottest topic around Data Scientist get a rockstar status, right? I can only imagine the VIP treatment they are getting. Boardroom influence, golden careers, pioneering the data revolution. It’s good to be a data scientist, right?

Well, I love my trade and yes I am pestered to work abroad more then once a week but I feel that the biggest mistake that is made right now is that there is no career path for young people in the organizations that look for a career in data science.

Statistical skills are maybe valued more then in the past, but the transparency these skills bring to organizations, to what works and what does not work are so threatening that data based decisions are still not wide spread and common practice.

Let me close off with my favorite quote from the book CoA: “In Gods we trust, all others have to prove their point.”

Amen.

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