UI/UX Designer & Brand Strategist

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Why More Data is Not The Answer

 

Many years ago, when we just started using the buzzword “big data”, a lot of people thought it’s the magic pill for all of their product or comapny failures, problems and future success. Most people still believe that vast amounts of data can provide better solutions than a person who doesn’t have it but knows human behaviour. But somehow we again don’t hit the sweet spot, why’s that?

If it were a logical answer, we would already have found the answer — Rory Sutherland

What’s interesting to me is that we believe that logic is one of the critical elements in making good decisions. And by using logic, you think that data collected from the past is a good indicator of what will happen in the future. And in case you did not notice it, I wrote: “we collect data from the past to predict the future”.

And the problem here is not only the fact that we can’t read or don’t know what to do with all of the data we have but also the fact that it grows our ego and makes us biased to things. So this way we miss real opportunities.

Quantification bias — the unconcious belief of valuing the measureable over the immeasurable.

People become so fixated on numbers or on quantifying things, that they can’t see anything outside of it. Even when you show them clear evidence. So quantifying is addictive, and when we don’t have something to keep that in check, it’s easy to fall into a trap. Meanwhile, you are searching for future you are trying to predict in a haystack, you don’t feel or see the tornado that is coming behind your back.

 
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The calculation from the picture may be correct in math, but it’s never true in disciplines such as marketing, economics or even design. Everything around is more unpredictable. Even Nature itself doesn’t use logic to create everything that surrounds us.

Because something looks logical, it does not mean it’s true. And also, just because something is portrayed in a mathematical form does not mean it is useful information. You may have destryoed the usefulness of it when trying to calculate it — Rory Sutherland

 
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The environment affects our behaviour

We should not assume that when we look at consumer behaviour that it’s a product of preference. It can also be a product the way you design choice. Restaurants want you to drink wine because they can price it whatever they want. You can’t just price a glass of Johnie Walker for $30 and expect people to be happy because they know how much it costs. But you can buy a case of 20 bottles of Chateaux de Burgundy (fictional name) for $10 a box and price one bottle for $100. And people won’t even complain.

Again, past data is not an indicator of future innovation, progress, success or failure. If you know how to design habits, then you know how to create the future. And what’s interesting to me, is that we are social beings, and everything revolves around that — products we make, choices we make in life, how we choose to live and so on.

 
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Netflix and binge-watching

For those who don’t know Binge-watching, also called binge-viewing or marathon-viewing, is the practice of watching television for a long time span, usually a single television show. In a survey conducted by Netflix in February 2014, 73% of people define binge-watching as “watching between 2–6 episodes or more of the same TV show in one sitting.”

Before launching the feature, Netflix had a significant amount of data that they needed to make use of and see what can be done. And those who use Netflix, know that they have a good recommendation model based on your interest and watching history. They even had a $1 mil prize for those who can improve the algorithm, and there were winners, but the end result was only incremental progress.

One day, they hired an ethnographer (ethnography is the systematic study of people and cultures) who studied the data and found out that people love binge-watching. In fact, people didn’t even feel guilty about that. Netflix, together with their data science team, has been able to scale and validate this data, so they decided to do something simple but impactful. So instead of offering the same show from different genres, or provide more shows from similar users, they decided to offer more of the same show. So they did redesign the entire viewing experience to encourage binge-watching. That’s why people sometimes disappear for weeks or weekends — catching up.

We constantly pretend our perception of the present day will not seem ludicrous in retrospect, simply because there doesn’t appear to be any other option. Yet there is another option, and the option is this: We must start from the premise that — in all likelihood — we are already wrong. And not wrong in the sense that we are coming to the wrong solutions, because most of our conclusions are reasoned and coherent. The problem is with the questions themselves — Chuck Klosterman, But What If We’re Wrong?

 
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How Nokia believed in bigger data

Tricia Wang, tech ethnographer, in one of her Ted Talks, demystified big data and identified its pitfalls, suggesting that we should focus instead on “thick data” — valuable, unquantifiable insights from actual people — to make the right business decisions and thrive in the unknown.

It was about 2009 when iPhone just came out, and Android was gaining traction. Tricia lived among the Chinese people for many years and conducted ethnographic work. And by living with migrants to working as a street vendor and living in internet cafés, she gathered lots of indicators that led her to conclude that even low-income consumers were ready to pay only to have an expensive smartphone.

But, at that time, a lot of smart and realistic people thought that smartphones were a fad, and they will disappear. “Who will want to carry a big clunky phone who’s battery dies in a couple of hours. And also breaks all the time you drop them.

After presenting all of her data to Nokia, she recommended they switch to making smartphones. Meanwhile, people at Nokia haven’t been impressed because it wasn’t big data. They already had data that did not show any sign of that. Tricia’s data was based on a sample size of 100 people. Meanwhile, Nokia’s data was based on a million people sample size.

For you to see the picture, their data was based on the surveys they have been sending out and asking people if they would love to have or buy a smartphone. And of course people didn’t know what a smartphone is and most replied with a no. The rest is history. Nokia was bought in 2013 by Microsoft.

Some companies tend to believe that data from larger samples is more valuable than the ones from a small sample — Tricia Wang

We have better tools nowadays, that’s true. Now all we need is to learn to use them in a better way. By combining human behaviour with data is how we can discover new stuff, improve current lives or create new things.

 
Eugen Esanu