Top Posts of 2013
2013 was a big year. More precisely, it was a “big data” year, when a technology that nobody heard of and that nobody can actually see, became what everybody wanted to talk about. I can’t remember anything ever happening like that before.
It was also the year we began to see the limits of disruption. Massive political protests in both Egypt and Ukraine showed that taking to the streets is not enough. Unless you build a new order that is legitimate, it will soon be disrupted again.
It was also a big year for Digital Tonto. In 2013 I began publishing on Harvard Business Review, Forbes and Business Insider, swelling my total audience to over a million and a half readers. Even thinking about a number that big makes my head spin! Thanks to everyone for your support over the years. Here’s my top posts of 2013.
I was happy to see that this post was the most widely read this year, because I thought it was the most important one. It’s long been apparent that, strategic planning, at least in the traditional sense, has become untenable. Now, it’s becoming just as clear that failing “fast and cheap” is becoming too slow and expensive.
In the past, we left strategy to the “smart guys,” who would try to glean what the future would bring through spreadsheets and then spread the gospel in PowerPoint presentations for underlings to execute. Now, as Rita Gunther McGrath puts it, “Prediction and being ‘right’ will be less important than reacting quickly and taking corrective action.”
As we saw in the 2012 Presidential election, having the “smartest guys in the room” doesn’t do you much good if your competition is running thousands of simulations per night based on real time information and then changing course accordingly.
When we think about disruption, we tend to think about “Influentials,” a small group of special people who drive the zeitgeist and convince the rest of us to act. Yet for better or for worse, Influentials are a myth. In truth, everybody is an influencer and we create the change we want to see.
This post explains how that happens. In truth, it’s not individual influence that’s important, but group dynamics. So if you want an idea to spread, you’ll be much better off seeking out people who are passionate about your idea than trying to discern who is influential. It is the network, not the nodes, that drives disruption.
I can tell you from experience that starting a business is one of the hardest things you can do. Over one third fail within the first two years and even successful ones falter. The average life expectancy on the S&P 500 has fallen from 75 years to under 15.
While every business is different, every manager needs a clear idea for how they will create, deliver and capture value and understand that whatever their business model, one day—probably sooner than later—it will become obsolete.
Almost since its inception, marketers have followed a fairly simple model called the “sales funnel.” You would build awareness for your product, get people interested in its features, overcome objections, drive customers to make a decision and follow up after the sale.
For the most part, the more people you put in the top of the funnel by driving awareness, the more sales would come out the other end. But now that model is broken.
Today, creating awareness is much less likely to result in a trip to the store and much more likely to result in searching behavior on the Internet, which can be tracked by your competitors who will retarget those same customers with a competing offer. In effect, by creating awareness you are doing lead generation for the competition.
While the previous post mostly describes the problem, this post outlines a solution. It starts with a simple framework for forming objectives and then outlines six corresponding tactical approaches and offers compelling use cases for each.
I’ve used this framework in my own work and have found it very helpful and easy to use. Hopefully, you will to.
It’s become fashionable to say that we’re “data driven” and that we live by the numbers. The problem is that our numbers are always wrong. Sometimes they’re off by a little, sometimes they’re off by a lot, but they are always wrong.
While unsettling, this doesn’t have to be a problem if we are realistic and sensible about how we use numbers. This post explains how to do just that.
Technology moves so fast these days, it seems almost impossible to figure out what will happen next. However, although we can never know exactly what the future will bring, the broad strokes follow predictable principles. This post outlines what the basic rules are and what we can expect over the next decade.
Historically, computers have been elaborate calculating machines. They were great for rote tasks in which simple, repetitive steps were required, but couldn’t match humans for jobs that involved complex pattern recognition. That’s beginning to change as machines are taking over jobs we used to think of as innately human.
This post explains how computers learn to perform complex tasks such as legal discovery, medical diagnoses and even creative work.
Everybody in business knows how important it is to innovate and there is no shortage of experts, gurus and conferences that promise to show you how it’s done. But after sitting in an auditorium watching flashy case studies for a few days, you’ll probably end up feeling confused more than anything else.
This post sets forth clear principles that anyone can follow. Take a look and tell me what you think.
Big data is the unofficial buzzword of 2013. As one person said to me, it’s become the business equivalent of teenage sex, everybody says that they’re going it, but nobody really knows how. Unfortunately, all the hoopla makes it hard to take big data seriously.
Yet it’s become clear that there is a widening gap between organizations that are using data effectively and those that are not. Furthermore, performance seems to have little to do with company size or technology investment, but depends on how well an enterprise learns to use data as a performing asset, rather than just an analytical tool.
This post explains what big data is and points to how you can use it in your business.
Looking Ahead To 2014
2013 was a pivotal year. Technologies that have been in the lab for years, such as big data and machine learning, practically exploded onto the public consciousness. From IBM’s Watson to the NSA’s PRISM program, I don’t think I can ever remember a time when our conception of what technology is capable of changed so quickly or more completely.
I expect 2014 to be a much smaller year, with few dramatic new advances, but more pervasive effects. We’ll be less interested in specific technologies and more interested in how they come together to form ecosystems. The age of stand-alone brands is over, in the future, you’ll either be connected or you’ll be dead in the water.
Another issue coming to the fore is an increasing tension between disruption and legitimacy. We’ve already seen this in the political sphere, with the failed revolutions in Egypt and Ukraine giving way to a new round of protests. We’ve seen it in the commercial world as well, with Groupon being just one example. Going forward, we’ll have to figure out how to transform a disruptive model into a sustainable one.
I’ll expect to be writing quite a bit about these issues in the year to come and hopefully add some clarity where I can. But for now, I’d like to thank you all for the enormous support over past year and wish you a very happy and healthy 2014.