Distorting Reality With Digital Analytics

Under cover of the night, sharing a bottle of tequila and a pack of cigarettes, two small-time criminals are debating how to strike riches and disappear to some random country without extradition laws. One would go for a strategy that seems to grab the headlines, while the other rebukes him for lacking vision. He argues that a bold plan leaves everybody hoodwinked because the police lack a well-honed strategy to thwart his plans. Although the less imaginative criminal admits that there could be some truth to this, and some do get caught executing the same idea he has, the guys who got caught were amateurs. He firmly believes he has what it takes to win against the odds.

His thinking shows signs of outcome bias, where he judges the mistakes of others with perfect insight as if that knowledge was available from the start and throughout the execution of the criminal plan. And this thinking also neglects probability, i.e. the odds are slim, but he is sure he will prevail. Criminals of any calibre, pun intended, have no monopoly on these biases. Many law-abiding people can also have them without harbouring any dastardly plan in their minds.

Many people have written about the late Steve Jobs' reality distortion field. Jobs was able to deliver what most thought was impossible. While researching this topic, I read a story of how Jobs challenged one of his engineers to shave off ten seconds of the Macintosh boot time. At first, the engineer told him no, but a few weeks later, he managed to reduce it by 28 seconds. What did Jobs tell him? Ten seconds could make the difference between letting someone die or saving their life.

"The people who are crazy enough to think they can change the world are the ones who do." 1997 Think Different Apple campaign

When trying to hire John Sculley away from Pepsi to become the future CEO of Apple, Jobs asked him whether he saw himself selling "sugar water" for the rest of his life. Sculley joined Apple and fired Jobs in 1985. By 1997, Apple was nearly bankrupt. Their last option was buying NeXT, a small computer maker company with a very niche market. NeXT's CEO was Steve Jobs. Apple's first "Think Different" campaign was for the Apple Macintosh computer. In 1997, Jobs rebooted that slogan for the launch of the iMac and said: "The people who are crazy enough to think they can change the world are the ones who do."

When I embarked on my career as a Web Analyst in 2009, the allure of changing not the world but how companies should build their website by analysing data held colossal appeal. I worked as a junior database developer, web developer, and conversion rate optimisation specialist before Web Analytics. When I discovered Javascript in 1998, I immediately saw how I would want to collect data on how people use a website and analyse it with a User Experience (UX) lens, or Human Computer Interface (HCI), as it was called back then. This youthful optimism faced challenges and resistance. What do you do when your desire for change meets someone else's?

As a Digital Analyst, you have facts and data to support your recommendations. But the stakeholders and clients you must persuade may have their own reality distortion field. They are likely to consider our facts and data as constraints, and challenging constraints is one of the very traits of that reality distortion field. A visionary leader may see the purest form of their work as not too dissimilar to what an artist does. Many creative people believe that facts and data undermine creativity. By extension, this visionary leader may feel the same way towards Digital Analytics: a straight-jacket for creativity.

"If you give yourself 30 days to clean your home, it will take 30 days. But if you give yourself 3 hours, it will take you 3 hours." Elon Musk

Self-fulfilling prophecies are also a concept I discovered early on in my career. I found that, given the choice, most people would rather be right than successful or happy. Whatever people believe, if they are directly involved in the outcome, things will turn out how they thought, good or bad. Therefore, people are responsible for their beliefs and should avoid catastrophising. But perhaps overoptimism should be equally undesirable. While researching for this article, I rediscovered this quote by Elon Musk: "If you give yourself 30 days to clean your home, it will take 30 days. But if you give yourself 3 hours, it will take you 3 hours." I fail to see universal application potential, however.

Sometimes, it can feel as if people believe that bold targets will always result in success, as if self-fulfilling prophecies were bi-directional. A project was successful and had an aggressive target; therefore, aggressive targets guarantee success. But people are far more interested in reading about successes than failures. Although post-mortem analyses of losses can be hugely insightful, publication bias, or how only the winners get to tell their stories, can result in the false belief that setting aggressive goals always works because that sort of story is far more frequent.

A grey area lies just beyond what facts and data think is possible. Would Steve Jobs use facts and data, and if yes, how? Instead of going for a reasonable set of recommendations, can we use Digital Analytics data to propose aggressive recommendations? After all, we can always unleash the plan on a control group rather than all the customers, increasing the control group's size over time and attempting to distort reality.

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