Organizing a System of 10 Billion People

Organizing a System of 10 Billion People

In this post, I will make some predictions on the nearer and farther end of the Quantified Self movement. Using McLuhan’s Tetrad, I will argue that Quantified Self will get huge incentives from enhancing healthcare, crowdsourcing science, and support a strong common ground, people will organize their life upon. Also, Quantified Self will weaken institutionalized medical care, and it might even obsolesce governmental surveillance by pushing moral control from institutions back to communities. By this, Quantified Self retrieves a form of communal life that could be called a bucolic, but also global village. Finally, Quantified Self, together with the web and social media, can become part of an adaptive, global operational system that make a population of 10 billion people sustainable. Organizing a System of 10 Billion People Quantified Self – this means tracking your life, analyzing the data, sharing intimate details, and changing behaviour. Self-tracking has become a huge thing recently. It is a complex built on three rather new technological pillars: wearable technology, hardware to measure your life, sensors that everyone can carry around, second ubiquitous mobile technology, thus the means to emit the data at once into the cloud, and finally social media everyone participates in and […]

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Datarella People – Helge F. Gruetjen, Boat Racer & Physicist

Cambridge PhD student Helge Gruetjen was a chain-smoker, weighting 120 kilograms, who started to row for the Cambridge University Boat Club in 2010 to become one of a team of five trying to beat the Oxford squad. He had set himself an „unrealistic goal“: to lose more than 25 kilograms while bulking up, simultaneously. In the last 2.5 years the 26-year-old managed to lose 0.5 kilograms per week, by stopping smoking, tracking his food intake, sleep patterns and more, using an Excel sheet, 4 hours of training per day…..and a lot of will power. „I knew I had to become very fit within 2.5 years. And I had to lose weight in a very soft and sustainable way.“ But how to motivate oneself to constantly lose weight during 2.5. years? For Helge, to be part of the Cambridge boat race team, was the biggest motivating factor. First, he analyzed his own behavior: which aspects of his life are obstacles to that goal and had to be changed. These were: smoking, exercise behavior, eating behavior, sleep patterns, etc. „We have to get up at 5:45am and start our day with the first round of training. Then I head to my office. […]

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Datarella – Lessons Learned: Hire Slow – Fire Fast

Datarella – Lessons Learned: Hire Slow – Fire Fast

A lot of entrepreneurs hire fast and fire slow. In particular when new coders are required to develop a software. A bias towards speed and quick growth drives many leaders to be quick to hire new personnel and strategic cooperation partners. Hiring fast is absolutely fine as long as everything works out well. The problem is, many people do not react quick enough when they figure out problems and significant quality issues with the people they cooperate with. Datarella decided to hire a German-based software development team for the programming of the prototype app including a backend system. The team had good references and offered us their service at an attractive price. The introductory meeting was very promising. It was clear to hire them quickly. Over the course of time, we figured out that the development team lost one of their key persons, who supported us on our project. As a result, they stopped hitting the pre-defined milestones and started to deliver poor quality. Firstly, we asked them to take care of the problems they obviously had within their team. Secondly, we put them under pressure to deliver in time. However, our development partner was not able to improve his […]

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Datarella People – Michael Ricks, Self-Tracker, Investment Banker, Inventor

Here’s the transcript of this Datarella (DR) interview with Michael Ricks, self-tracker, investment banker and inventor. DR Michael, you are an American living in Munich, Germany. Could you tell us a little about you? Michael Ok – so, what am I? A guy who is trying to get the most out of life. I’m a father of four kids who are pretty active. I work as an investment banker and inventor, and otherwise I’m just enjoying life. DR How do you track yourself? Michael Probably like everyone does. I get up in the morning and think about what my day is going to bring. Every day I do a thousand repetitions of something or a combination of those thousand things. So, most days I start with a hundred stit-ups in bed! And that’s the beginning of tracking what I’m doing there in the course of the day. Then I figure out how many hours I’ve slept, and then I decide how to spend my day: I look at my calendar, divide up my time, dibide up my activity… and start! DR What reason would there be to stop tracking yourself? Michael If tracking became something which consumed more time and […]

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Data Based Storytelling And The Real Customer Journey – or: What To Learn From Data Journalism

Data Based Storytelling And The Real Customer Journey – or: What To Learn From Data Journalism

Know your customers and build an ongoing relationship between them and your brands by looking beyond a on-time meet-up caused by a marketing campaign! Highly engaged users become loyal customers, have higher LTVs and contribute more to your bottom line than the casual customer. Yes to that. But how to to build a stronger relationship with your customers? Do you know enough about them to accompany them on their journeys? If you’re a reader of Nate Silver’s FiveThirtyEight, you’re aware of his disdain for opinion journalism (e.g. op-ed columns), which „[…] doesn’t seem to abide by the standards of either journalistic or scientific objectivity. Sometimes it doesn’t seem to abide by any standard at all.“ So, if a (well researched, if good) op-ed column does not fit to a journalistic or scientific standard – does a customer journey description, which (typically) ends when the customer actually starts his real life journey because she leaves her desktop, fit to any marketing research standard? Won’t the customer act and express herself in a different way when on the road, when actually being shopping, when passing by out-of-home advertisements in a hurry – compared with relaxing with her iPad in her living room? […]

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Datarella People – Florian Schumacher, QS Evangelist

Here’s the transcript of this Datarella (DR) interview with Florian Schumacher, Founder QS Meetups, Germany. DR Florian Schumacher, you started the first Quantified Self QS Meetup in Germany. Could you introduce yourself and tell us about your QS approach? Florian When I learned about Quantified Self in 2011, I immediately felt attracted by its very positive culture. Consequently, I started the QS meetups in Berlin and Munich in 2012 which is a lot of fun. Besides, I am a trendscout of Wearable Technologies AG. Here, I’m dealing with all devices you can wear and the sensors which collect behavioral data. DR What do you track yourself and how do you do that? Florian I regularly and passively track my weight, my body fat, my physical activities and my sleep – all those data are collected automatically, so that’s completely effortless. Then, I manually collect sample data on my blood pressure, blood sugar, my girth, and I try to keep an eye on my haemogram. This, I do on a weekly basis. Then I track other data as time, which is quite sophisticated, since it’s not automated at all and I track everything: every project, every lunch, every activity finds its […]

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How Big Data Changes Marketing

About 0.5% of big data collected is actually being analyzed and monetized. The „rest“ ends up unused. 90% of all data ever created has been generated in the years 2012-2013, and 30% of it contains valuable information. During the last years, the amount of data has been increasing exponentially. Enterprises around the world are beginning to put Big Data on the top list of their operations. Big Data comes with a paradigm shift not only in research: here, the industry is shifting from finding and asking the right questions to letting the data speak for themselves, enabled by smart algorithms doing their analysis automatically. In marketing, the same paradigm shift is taking place: CMOs are provided with factbased, individualized answers in realtime, rather than with intuitive, retroactive perspectives of traditional market research. While it’s not the data in Big Data which is important. Rather, it’s the insights derived from it, the quality of decisions you make and the actions you take that transform big data into smart data, or “affinity data”, if you drill the data funnel down to the individual: the more information marketers have on their user’s likes, preferences and interests, the better they can target the individual […]

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Quantified Self or Quantified Us – A Social Responsibility

Quantified Self or Quantified Us – A Social Responsibility

Life logging, tracking, the Quantified Self, the Quantified Life – and now the Quantified Us? Do we need more or better expressions for this global trend which motivates people to change their behavior? Matthew Jordan and Nikki Pfarr from Artefact make their case for changing the Quantified Self into Quantified Us. The first degree of meaning, that is to know your personal data, is the first step for all life loggers: by collecting data about their behavior they can compare their subjective perception of movements, food intake etc. with the reality. And get meaning from that, such as: „Ah, I see – I don’t run 10 kilometers every second day but I run 7.5 kilometers twice a week – on average.“ After having learned about oneself, the user takes action – the second degree of meaning: she buys new running shoes to please herself and then she extends her weekly parcours to 10 kilometers, completed every second day. Lesson learned, quality of life of the individual improved. The third degree of meaning would be added, when people get advice to make better use of their – and other people’s – data in the moments when decisions are actually made. A […]

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Crowdsourced environmental monitoring

Many parameters a smartphone accidentially measures are useful in monitoring the environment. We have recently discussed, how air pollution with particulate dust can be monitored with an easy ad on to the phone’s camera. But there are even more subtle ways by which users can help to research and monitor environmental conditions. Another example is given by A. Overeem et.al. who track urban temperature over time in various metropole regions arround the globe. The approach is as simple as powerful: a regression over the battery temperature (that is measured by every smartphone anyway). The microphone, too, can give valuable data on local environmental conditions for an unlimited mass of individual users that participate. Sound level show noise emmission that can be located in space and time. Noise is regarded as a prime source of stress, but rather little is known about the changes that occur in different microgeographic regions. Apps like Weather Signal use thus a combination of the phone’s sensors to contribute to a richer model for weather conditions. Appart from just passivly deploying the phones as sensor boards themselves, it is of course also possible to collect data from other local sources and just transmit the results via […]

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Big Data helping people to understand real-time pollution risks

Big Data helping people to understand real-time pollution risks

From rapid urbanization in China to dung-fired stoves in New Delhi, air pollution claimed 7 million lives around the world in 2012, according to the World Health Organization. Globally, one out of every eight deaths is tied to dirty air – which makes air pollution the world’s single biggest environmental health risk. And, in areas with very bad air pollution, people live an average of 5 fewer years than those in other areas.  Not only in Chinese megacities or indian agricultural areas, people are trying hard to keep air pollution at bay. In Portland, Oregon, a local initiative called Neighbors for Clean Air is using Big Data to make bad air visible. The group is part of an experiment in initiated by Intel Labs, that uses 17 common, low-cost sensors, each weighing less than a pound to gather air quality data. This data feeds to websites that analyze and present comprehensible visualizations of the data. The sensors itself are built using an Arduino controller. They measure carbon and nitrogen dioxide emissions, temperature and humidity. By making the air pollution problem visible, the experiment not only made people recognize the importance of technology in understanding air quality, but Neighbors for Clean […]

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