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Eight takeaways from prof Andy McAfee's second machine age discussion

Den Howlett Profile picture for user gonzodaddy September 17, 2015
The Second Machine Age is upon us. What matters now is our capacity to embrace what it means beyond the buzzwords that go with it.

andy mcafee
prof Andy McAfee

At Dreamforce 2015, prof Andrew (Andy) McAfee delivered an entertaining and absorbing session that talked to the topic of our needing to be more nerdy. It is worth picking apart because McAfee speaks to topics that are coming into view for many enterprise buyers.

These are my eight takeaways contextualized into the thrust of modern consulting engagements:

  1. Technology remains an aid to our decision making but it can be a powerful aid.
  2. Today's technology consulting is about the intersection with business. It is no longer about the preferred flavor of bits and bytes.
  3. Business leaders need to be far more technology aware, nerdy if you will, if they are to ask the right questions.
  4. Technologists needs to be far more aligned to an understanding of business outcomes than in the past.
  5. Asking the right questions is increasingly the most important key to getting the machines doing the right math.
  6. Asking the right questions requires much more by way of creativity and the ability to discern the real question that needs answering, not just the one that appears on the table.
  7. Whether we like it or not, success will be measured by our ability to pay attention to the data and not the HIPPOS in the room.
  8. The middle class jobs of tomorrow will be far more interesting than those of today.

How do I get there? I'll provide context and background.

Enterprise 2.0's failure

I first met McAfee at an enterprise 2.0 conference in Boston in 2008. He coined the term enterprise 2.0 in 2003 and published a book of the same moniker in 2006.

I was highly skeptical about the thinking behind enterprise 2.0 and was vocal in my critique. McAfee was gracious enough to offer a considered response. Most people who were devotees of enterprise 2.0 believed I was wrong. I said:

The world is NOT made up of knowledge driven businesses. It's made up of a myriad of design, make and buy people who - quite frankly - don't give a damn about the 'emergent nature' of enterprise.  To most of those people, the talk is mostly noise they don't need. They just want to get things done with whatever the best tech they can get their hands on at reasonable price. That doesn't mean some wiki, blog or whatnot. More likely they'll be investigating sensor tech.

By 'emergent' McAfee posited a technology led, collaborative knowledge sharing economy. History proved that I was largely correct, although my argument was not as well framed as it could have been. Today, I'd argue we're in the second half of figuring out what a knowledge business looks like and it ain't quite as was envisaged 12 years ago.

Most enthusiasts, including McAfee, talked in terms of the technology as a cure all and did not adequately address the problems people were trying to solve. Add in a dose of cultural inertia and enterprise 2.0 was always going to falter. Mine wasn't a popular view among the cognoscenti and other consulting hangers on.

Eight years on, considerable, practical difficulties remain. The good news is that practitioners who stuck with the problem solving element are now seeing tangible results, especially in the world of community building.

The Second Machine Age

Fast forward to last year when McAfee co-authored The Second Machine Age. I winced at the title and the premise upon which it was constructed. Bill Teuber said of the book:

If the first machine age was about the automation of manual labor and horsepower, the second machine age is about the automation of knowledge work, thanks to the proliferation of real time, predictive data analytics, machine learning and the Internet of Things...

In The Second Machine Age, the great software-defined businesses of tomorrow will be the ones that usher in breakthrough innovations that do new things entirely -- the kind of innovation that generates new value by opening up unforeseen market opportunities: new products, new services, new ways of servicing customers, and new jobs.

My difficulty, which in hindsight was misplaced, is that I could never imagine a world where the machines could be as inventive as humans. Nor could I imagine a world where machines dictate decision making. To me, McAfee's latest book was merely an extension of a theory I believed was wrong.

Machines v HIPPO

It turns out that mine is not (quite) the correct framework from which to approach some aspects of decision making and value creation in the 21st century. What has changed and why does any of this apparently cerebral topic matter?

Many business issues can be better understood when we apply technology. Today for example, there is an important debate about the value self driving cars bring. McAfee talks about the Google self driving cars and the fact they have only recorded 16 accidents, all of which were the fault of another party. McAfee attributes this to the fact that Google has taught these cars the rules of the road and as dumb processors, they follow the rules they've been given. Ergo safe and boring driving.

Warming to his theme, McAfee talks about how being nerdy provides superior predictive results than being a HIPPO (Highest Individually Paid Person's Opinion.)

McAfee gives the example of vintage wine rating which for many years was dominated by Robert Parker. In 1990 prof. Orley Ashenfelter, a labor economist, developed a formula that predicts wine quality at the time of harvest. When first published, Ashenfelter was ridiculed by the wine snobs. Ashenfelter's predictions are remarkably accurate. According to the FT:

While few wine experts have publicly acknowledged the power of Ashenfelter's predictions, their own forecasts now correspond much more closely to his simple equation results. Take that, Robert Parker.

At this point you might be forgiven for being slightly confused. McAfee is clearly demonstrating the power of applying algorithms and formulae to problem solving. But how the heck did Ashenfelter derive his predictive formula which says:

Wine quality = 12.145 + 0.00117 winter rainfall + 0.0614 average growing season temperature - 0.00386 harvest rainfall

Where the machines fail

McAfee doesn't address that topic but he does point up three areas where computers cannot match humans:

  1. Creativity - you're not going to get a prize winning novel out of a computer any time soon.
  2. Common sense - sometimes the results you see from machines are nonsense.
  3. Social skills - to quote McAfee, "I can't imagine the half time pep talk from a robot."

None of those traits gets any of us off the nerdy hook.

Are you ready?

As McAfee took questions, I noticed that those who asked focused on the human exceptions. It's not surprising. Any conversation that starts with: "We're going to let the data speak for itself and make decisions based upon that data" is bound to cause disruption. Just as Parker described Ashenfelter "ludicrous," anything that challenges our deeply held beliefs about our ability to make good, solid judgments is threatening. Humans don't respond well to threats.

McAfee is keen to point out that machine led problem solving and innovation will open up fresh opportunities and create new classes of work. He acknowledges that those in the middle, those whose work can be automated or passed over to a machine will be squeezed. I already see that in my chosen profession of accounting. Machines can write pretty decent, fact based stories. I receive some of those. There is ongoing and vigorous debate about the robotization of business processes. But we will need many more problem solvers and creative thinkers who can heft the technology than we have in the workplace today.

The only thing that stands in our way is the infinite human capacity for behaving like rabbits caught in the headlights of an oncoming car when presented with major disruptive trends.

Oh yes - I almost, but not quite, agree with McAfee. That makes me smile.

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