Decision Making in
a Data-Driven World
Data is the new oil of our era.
It fuels our lives – but is no longer an inert thing. Rather data is something alive and changing, something that can tell us a lot about who we are as individuals and a society – and determine how we proceed in business.
Jennifer Erwitt and Rick Smolan
Human Face of Big Data
“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
To get in the Big Data game, a company needs three kinds of table stakes:
1. The data itself. Large quantities of information in a format allowing for easy access and analysis
2. Advanced analytical tools (Hadoop and NoSQL). Both proprietary and open-source tools and platforms are widely available these days
3. Expertise. Advanced analytics requires staff with state-of-the-art skills in everything from data science to worldwide privacy laws, along with an understanding of the business and the relevant sources of value.
Bain and Company
Older ways of thinking about Big Data leaves humans out of the equation. What actually matters is how the people are connected together by the machines and how, as a whole, they create a financial market, a government, a company, and other social structures.
Two facets to the myth of data and technique
If we fail, it is because we didn’t use the right technique
If we just knew more, we would be able to fix anything
A Failure of Nerve: Leadership in the Age of the Quick Fix
How do we understand and
make sense of this data?
“See that bird? What kind of bird is that?”
“I haven’t the slightest idea what kind of a bird it is.”
“It’s a brown-throated thrush. Your father doesn’t teach you anything!”
But it was the opposite. He had already taught me:
“See that bird? Well, in Italian, it’s a Chutto Lapittida. In Portuguese, it’s a Bom da Peida. In Chinese, it’s a Chung-long-tah, and in Japanese, it’s a Katano Tekeda.”
You can know the name of that bird in all the languages of the world, but when you’re finished, you’ll know absolutely nothing whatever about the bird.
I learned very early the difference between knowing the name of something and knowing something.
Can a machine ever be truly called intelligent?
Can it understand and make sense of our world?
John Searle’s "Chinese Room Experiment" famously challenged the concept of artificial intelligence and understanding.
According to Alan Turing, the father of computer science, if a computer can convince a human they're communicating with another human, it can be said to think.
The Chinese Room suggests that however well you program a computer, it doesn't understand Chinese, it only simulates that knowledge, which isn't really intelligence.
Chinese Room Experiment -- John Searle
Imagine yourself in a room with boxes of Chinese characters that you can't understand, and a book of instructions that you can.
If a Chinese speaker outside the room passes you messages under the door, you follow instructions from the book to come up with an appropriate response. The person outside the room will think they're chatting with a Chinese speaker.
In an equivocal, postmodern world, infused with the politics of interpretation and conflicting interests and inhabited by people with multiple shifting identities, an obsession with accuracy seems fruitless, and not of much practical help, either.
Karl Weick (1999)
Weick's Seven Properties
1. Identity and identification
4. Social Context
5. Ongoing events
6. Extracting Cues
7. Plausibility over accuracy
Do we prefer the plausible solution that big data can decisively predict flu trends, or the accurate one that may be more complex?
"After reliably providing a swift and accurate account of flu outbreaks for several winters, the theory-free, data-rich model had lost its nose for where flu was going.
Google's model pointed to a severe outbreak, but when the slow-and-steady data from the [US government center] arrived, they showed that Google's estimates of the spread of flu-like illnesses were overstated by almost a factor of two."
By claiming that computers will ever organize all our data, or provide us with a full understanding of the flu, or fitness, or social connections, or anything else for that matter, they radically reduce what data and understanding means.
Ikkel Krenchel and
Making Sense of Data
Ushahidi is a non-profit software company that develops free and open-source software for information collection, visualization, and interactive mapping.
Ushahidi serves as a prototype and a lesson for what can be done by combining crisis information from citizen generated reports, media and NGOs and mashing that data up with geographical mapping tools.
The platform has been used to monitor elections in India, Mexico, Lebanon and Afghanistan. It has been deployed in the DR Congo to track unrest, Zambia to monitor medicine stockouts and the Philippines to track the mobile phone companies.
Example Tweet at Ushahidi
@Ushahidi 2-car acc at State & Lake, both drivers injred
Human observer can tell the tweet refers to an auto accident, a medical emergency, and a street intersection in Chicago, but a computer would likely have a hard time recognizing that State and Lake are streets in Chicago, that “acc” is short for accident, or that “injred” is a typo for “injured.”.
Ushahidi is working at the intersection of human sensemaking and improved statistical classification tools.
Do we value intuition and tacit
knowledge in a data-driven world?
Most of the advocates understand data is a tool, not a worldview. My worries mostly concentrate on the cultural impact of the big data vogue. If you adopt a mind-set that replaces the narrative with the empirical, you have problems thinking about personal responsibility and morality, which are based on causation. You wind up with a demoralized society.
New York Times
What Big Data Lacks:
Data struggles with the social.
Data struggles with context
Data creates bigger haystacks.
Big data has trouble with big problems.
Data favors memes over masterpieces.
Data obscures values.
In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes.
A wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.
Designing Organizations for an
In some ways the technology is transforming us into brilliant fools.
In the riot of words and numbers in which we live so smartly and so articulately, in the comprehensively quantified existence in which we presume to believe that eventually we will know everything, in the expanding universe of prediction in which hope and longing will come to seem obsolete and merely ignorant, we are renouncing some of the primary human experiences. We are certainly renouncing the inexpressible.
How we make sense of the world cannot be fully captured by data, summed up well by Michael Polyani's famous statement about tacit knowledge, “we can know more than we can tell.”
Central to Polanyi’s thinking was the belief that creative acts (especially acts of discovery) are shot-through or charged with strong personal feelings and commitments.
The classic example of tacit knowledge is the bicycle – it doesn’t help if you only have an intellectual understanding of how to ride.
Similarly, the most successful parents are rarely those with the most knowledge of the latest ‘data’ and ‘techniques’ of child-rearing.
Phronesis... involves not only the ability to decide how to achieve a certain end, but also the ability to reflect upon and determine good ends consistent with the aim of living well overall.
The Greeks termed our practical knowledge and understanding as "phronesis", concerning values and interests that go beyond analytical, scientific knowledge (episteme) and technical knowledge or know how (techne).
The primary purpose of phronetic social science is not to develop theory, but to contribute to society's practical rationality in elucidating where we are, where we want to go, and what is desirable according to diverse sets of values and interests.
Engineering, medicine, business, architecture and painting are concerned not with the necessary but with the contingent - not with how things are but with how they might be - in short, with design.”
Phronesis and the Star vs. Heart
Airbnb can leverage data on specific cities, guest and host demographics, and other rental metadata to personalize search results. Can this data also factor into business and design decisions?
Despite their intentions to be data-driven, one of Airbnb’s most successful features, Wish Lists, was born out of a simple decision that had nothing to do with data and everything to do with human perception and iconography.
The company recognized that its “star” icon hearkened to generic, utility-driven experiences, whereas a “heart” anchored itself to the aspirational nature of Airbnb.
After switching from the star to heart, engagement went up by a remarkable 30%, reinforcing the importance of human understanding in launching new features.
We want to apply data to every decision.
We want to be a very data-driven company.
VP of Engineering
How does expert intuition fit into
a data-driven business strategy?
Intuition versus analytics is not a binary choice. I think expert intuition is the major missing component of all the chatter out there about analytics and being data-driven.
Chief Analytics Officer for New York City
under form Mayor Michael Bloomberg
Dreyfus Model of Skill Acquisition
- Transcend "reliance on rules, guidelines, and maxims"
- Have an "intuitive grasp of situations based on deep, tacit understanding"
- Use "analytical approaches in new situations or in case of problems"
Any renaissance, anywhere, whether in a marriage or a business, depends primarily not only on new data and techniques, but on the capacity of leaders to separate themselves from the surrounding emotional climate so that they can break through the barriers that are keeping everyone from “going the other way."
A Failure of Nerve: Leadership in
the Age of the Quick Fix
Expert intuition in often found in the choice of the business area where analytical initiatives are undertaken.
Few companies undertake a rigorous analytical study of what areas need analytics the most! For better or worse, the choice of a target domain is typically based on the gut feelings of executives.
Harvard Business Review
How do we choose which problems to solve?
Ralph Stacy's Complexity Matrix suggests that leaders must balance levels of certainty/uncertainty and agreement/disagreement in choosing which problems to address.
Intuition is nothing more or less than recognition.
A situation has provided a cue, this cue has given the expert access to information stored in memory, and that information provides the answer.
What is an "Explanation" of Behavior
Can we trust expert intuition?
Paul Meehl's analysis in Clinical vs. Statistical Prediction showed that in numerous studies statistical algorithms outperformed industry experts 60% of the time.
These results expanded the notion that humans are incorrigibly inconsistent in making summary judgments of complex information, especially in low-validity environments.
Thinking Fast and Slow
In the 1980s, Princeton economist and wine lover Orley Ashenfelter created a formula to predict the future prices of vintage Bordeaux wine.
The coorelation between his predictions and actual prices is above .90, demonstrating the power of simple statistics to outdo world-renowned experts.
His studies have also shown that in complex environments, algorithms can detect weakly valid cues more often human intuition.
Predicting the Quality and Prices of Bordeaux Wines
∆ price = -12.15 + (β1 * Winter rainfall) + (β2 * Average summer temperature) + (β3 * Harvest rainfall) + (β4 * Age of Vintage)
Are big data and advanced
Alorithims have proven to be important tools in decision making, but do they leave room for creative insight?
Kierkegaard argued that anxiety and uncertainty are necessary in the creative process.
Because it is possible to create — creating one’s self, willing to be one’s self — one has anxiety. Anxiety and uncertainty have always been necessary aspects of experiencing and actualizing possibility; they are essential for creativity.
The Concept of Anxiety
Life is lived forwards but understood backwards.
Kano Model of product
development and customer satisfaction
Data can serve as an great predictive tool, but will it provide the means to create delightful experiences?
Leveraging Human Data
Zara has grown into the world’s largest fashion retailer by moving beyond sales data to behavioral data.
Store managers and employees are trained to talk to customers and find out what they like and don’t like about a design. Each day, store managers report this information to headquarters, where it is then transmitted to a vast team of in-house designers who quickly develop new designs for production.
By constantly assessing customers attitudes, Zara is able to capture fashion trends from design to to production to store in two to three weeks.
Behavioral data from in-store customers has given Zara a unique perspective on how attitudes vary geographically, and have noticed that trends correlate closely between specific neighborhoods of various cities.
For example, the Fifth Avenue store in Midtown Manhattan is more similar to the store in Ginza, Tokyo, which is in an elegant, touristy area. Customers in SoHo align more closely to Shibuya, with attitudes that are young and trendy.
We do not know what we will know. Invention and creativity is always a surprise. If we could prophesy the invention of the wheel, we’d already know what a wheel looks like, and thus we could invent it."
The Black Swan
Even as Big Data gets bigger and quantitative analytic techniques become ever more powerful, they will never supplant the need for human intuition and creativity.
In a survey of 600 companies in the U.S. and U.K., Accenture Analytics found that data and intuition, when used in concert, correlate with higher returns on investment.
Jeanne G. Harris
Accenture Institute for High Performance
“The human element of intuition, our ability to understand context and ask the right questions is essential in making the best decisions possible. Putting Big Data in context is a step that moves us closer to the wonderful vision of enhanced human thinking built on advanced machine intelligence, combining data-driven recommendations with very human characteristics of intuition, creativity and imagination.”
President of Teradata Labs
Data will help us remember, but will it let us forget?
It will help politicians get elected, but will it help them lead?
It will help soldiers kill enemies remotely with drones, but will it help us see war as more than a game?
It will help police triangulate the location of gunshots, but will it help us address the underlying causes of violence?
It will help educators make excellent standardized tests, but will it help us embrace different standards of excellence?
It will help geneticists sequence our genome, but will it help us understand who we are?
It will help us feel connected, but will it help us feel loved?
It will help us see the world at it is, but will it help us see the world as it could be?
Data Will Help Us
By: Ryan Murphy