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Persuasion.  Many believe persuasion is the art of convincing others to see things their way. They’re partially correct. But what if we rethink it as a process of learning rather than influencing? This counter-intuitive notion requires us to listen rather than preach and to seek different conclusions rather than proselytize. In this paradigm, persuasion has more to do with establishing credibility, building trust, finding common ground, providing supportive evidence and connecting emotionally.
An effective persuader frames the argument to illuminate its benefits for the target audience. She must have the social radar to detect the nature of pushback and accurately sense, as well as respond to, the feelings of others. In the face of differences, this can be a painstaking process requiring sensitivity and the willingness to be vulnerable. Old school persuaders see these traits as weakness and that, I suggest, is why they fail as often as they do.
Credibility begets believability and that is the cornerstone of persuasion. Without it, we are rarely given the time of day by those we seek to influence. And that is deserved. Before they begin, successful persuaders consider their argument from every angle: Is my evidence weak? Are there different ways of looking at my point of view? In what ways might we already have common ground? Can I express my position in a more compelling manner? A masterful persuader matches the message with a fervor consistent with her opponent’s willingness to understand it.  [ If you’re interested, I’ve written extensively on this topic before. ]
The News.  Many, thinking they will be better informed, are addicted to the news. I confess I’m one of them (though highly selective in my choice of sources). The problem, more than ever before, is that “the news” is a huge source of misinformation. What we like to call news is quite transitory – it exists only at the moment we receive it. Then it changes. It’s old news once we hear or see it. And the sheer quantity of the news, much of which is irrelevant if not specious, has eroded its quality.
The news is skewed or distorted to meet the needs of those who pay for it and thus those who consume it. Advertisers or pundits, being human, are motivated to put their particular spin on it. The more controversy, the better – that’s part of the addiction. Most of what we’re fed by those who decide what should constitute the news is largely useless to the quality of our lives. It rarely helps us make better decisions or understand our increasingly uncertain, ambiguous, complex world. It invariably annoys, confuses and frustrates us. The news doesn’t make our opinions more rational; it only convinces us we’re right. Because, we are conditioned to ignore what we disagree with.
The news doesn’t instil greater purpose in our lives. It just keeps us wanting more. When we stop inhaling or imbibing it, we discover those who are injected with their daily dose are often misinformed. Our biases (particularly our availability and priming predispositions) make us want to believe there can’t be a “different side to the story.” So, we take it for what it is. Without the incessant daily “hit,” we might more often say “I really don’t know.” The antidote to the addiction is to diversify our information sources, consciously differentiate facts from opinions, and spend less time passively consuming and more time observing and thinking. The thoughts of others imprison us if we’re not thinking for ourselves. The search for truth requires effort. Seeking confirmation of what we already believe doesn’t.
Analytics.  This reflection relates to the above. With click technology, we amass more data than we ever thought possible. It too is part of the news. Virtually every commercial transaction or interaction is digitized and tracked in some way. Companies as well as the media are drowning in data, much of it superfluous to their raison d’etre. The question is whether they have the commonsense and statistical literacy skills to properly utilize it? How many decision makers have the requisite knowledge in probability theory, data extraction and information normalization to do a deep dive into the difference between consequential signals and utter nonsense. As artificial intelligence increasingly becomes a critical component of how business choices are made, there’s a greater need to test, challenge or invalidate the outputs of its algorithms. The objective should be to draw insightful conclusions from a mountain of data rather than assume it tells us the way it is.
Analytics are projected to be a $275B industry this year. Those who understand the value and the limitations of big data say much of that money will not be spent wisely. Gartner, a reputable research firm, estimates that almost 85% of big data projects are abject failures. The quality, care and statistical significance by which information is gathered, manipulated and reported varies widely. Our brain is innumerate – without mathematical training, it is incapable of dealing with numbers. Data takes on the power of certitude. So, it plays on our biases. We rarely ask where the numbers came from, how they were “spliced and diced” (e.g., what was left out) and whether they actually address the problems we’re trying to solve. And, invariably, the real issue is whether we’re asking the right questions.