Lao Tzu.

Big Data is the new miracle tool in business and marketing to improve customer experience, used to drive more loyalty and sales – or even to predict future desires in product development. In reality though, Big Data is both promising (when used properly) and a curse (when used by naïve people). Any tool can be only as good as the professional using it, and there seems to be too much blind believing into what Big Data and “Data Analysts” – the new saviors everybody is calling for – can achieve.

Big Data a lucrative and fast-growing industry – the Financial Times calls it the “new oil” – is dominated by companies such as Alphabet (Google’s parent company), Amazon, Apple, Facebook and again Microsoft – also the five most valuable listed firms in the world.  Amazon grabs 50% of online spending in America. Google and Facebook dominate digital advertising in America. So far, they keep most customers happy. But as smartphones and the internet have made data abundant, ubiquitous and far more valuable, their control of data gives them excessive power, including buying a start-up for absurd looking amounts because it could become a new competitor. And machine learning has its pitfalls: even as algorithms can predict when a customer is ready to buy, the results often are Kafkaesque. Some examples:

1/ since booking a hotel for a vacation months ahead, I still am getting pestered with constant offers for other hotels at the same location as well as around the World whenever I open any website for general news or professional information. This feels like cooking in a Kitchen with somebody constantly trying to sell the ingredients for the meal in the making again and again.

2/ after I got my annual medical check-up, a pop-up in Skype offered me “a new treatment for your lung cancer”. Luckily, this was a false assumption, but certainly a bit too rough, I called back and Skype apologized. This intelligent-machine isn’t smart – and how did Microsoft get access to my medical check-ups?

3/ ever since we had a home security system installed, I still get pop-ups and spam-eMails from the same company – sometimes with enticing discounts, which we didn’t get in the first place.

BIG DATA OBSTRUCTS CREATIVITY.

The paramount effect isn’t just the privacy intrusion and eventual insult to one’s intelligence, but the never-ending hawking of a myriad of “other people bought this” bullshit offers. So far, AI and Big Data may have their place in science and academic research – with qualified and smart people handling algorithms and analysis – but in emotionally minded consumer business it seems to magnify the ineptitude of people who program it basically senseless and of those applying it blindly.

Big Data of this kind promotes a culture of noise over signal, more mediocrity and an ever-lower level of innovation, identity and quality in products, services and human-minded experiences. At this stage, Big Data is killing creative exploration and progress. And because it pretends “safe” predictions, it also is a major roadblock to business innovation. E.g. the market research industry’s addiction to big data, has become a roadblock to digital-interactive innovation, because they cling to outdated methods like the Habsburg-Austria monarchy once rejected Manchester’s weaving machines, because they would reduce cheap labor.

In fact, half of launched new products are not as successful as planned. Consumers aren’t acting as robots – they have a mind, feelings and desires. When I am buying pink Birkenstocks, this doesn’t mean that I also want to by young girls clothing seven days a week. Overall, market success by Big Data is shrinking, because products become more and more similar and comparable, incl. leading to money-losing price wars. Old-school 1 to 10 market research resulting in identical results for all competitors is a sure way for failure.

Here is an example how Motorola rejected frog’s smartphone concept on 2001 – designed with Nextel’s (today Sprint) support and request – because “research shows that the market wants proven technology in fashionable design”. For them this was hard data because back then Nokia dominated the wireless phone market with more than 100 different designs. And investing $ 30 million was out of Motorola’s executive management minds.

Big Data Victim: rejected frog-proposal for a touch-screen smartphone to Motorola (2001)

Then it was Steve Jobs at Apple who put the market on its head – a wireless media & communication computer in your hand – and he added a software-based user experience which made the Symbian OS look like a dinosaur, which it was.

DESIGN FOR REAL PEOPLE – NOT MARKETS.

How can Big Data become consumer smart?  The desired way would be to personalize offerings using signals of intent, so consumers get content that is relevant to what they are doing and wanting right at that moment. And when one realizes that the masses move into one direction: don’t just THINK DIFFERENT but also DESIGN DIFFERENT.

More effective will be the use of Smart Data in innovation, design and product development. However, this again will require a reverse analysis of users and product offerings: don’t do what all do, because you will face paramount competition of bland products hawked at lowest prices. Just think of the myriad of iPhone-copied smartphones: the only way to make some profit with these copies seems to be cutting some cost by a mediocre WiFi or a lower-tech battery.

Big Data already has started some very questionable trends in the process of designing: after the core of designing (creative conversion of technology, science, business and social aspects into human-minded physical and virtual products) already has been watered down by Design Thinking (the thesis is that execution has out-paced innovation, which is very visible), there is now talk of Computational Design (the thesis is to design in real-time for billions of individual consumers based upon experience over innovation). Frankly, we already see that Design Thinking is a mirage: to my knowledge there isn’t a single design success created by what I call corporate entertainment. And putting experience over innovation also could be called copy – don’t create. Actually, it already is reality with a few ODMs in China manufacturing near-identical smartphones, offered by a myriad of brands.

Financial results confirm my thesis (I may repeat myself): it pays to think and design different, and to copy isn’t just unethical but also mediocre business.

In Q3 2016, global smartphone profits were US$ 9.4 Billion (strategyanalytics.com). Apple’s profit was US$ 8.55 Billion (a share of 91%), whereas Huawei as most successful Android copy-cat generated just US$ 0.2 Billion profit (a share of 2%). And it is somehow similar in other industries such as in the automotive industry: Porsches profit per car is about US$ 17,600 whereas Volkswagen or Toyota have to sell dozens of cars to achieve the same profit.

Ask yourself: do you want to trust blindly Big Data Machine Intelligence and become a corporate lemming going over the cliff with confidence, or will you take the risk of a creative rebellion for true progress and accept the option of sustainable success – or brilliant failure?

Header image by: datacentervoice.com