Digital Migrants And A Stark Economic Future
Why we'll see a very tough transient labor market for a couple of decades, with slowing or declining economic growth.
The only digital native Enterprise 2.0 businesses around today are those founded around 2000 to 2003 and that possessed the ability to build their own tools. This narrows the field significantly, to companies like Facebook and LinkedIn.
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The problem with these examples is that they're all in the consumer social media business. They went down the 2.0 path because they were forced to eat their own dog food to make financial equations balance. But they're hardly representative of the economic landscape. They don't make paint or shoes or refine oil.
The first generation of digital-native companies is still young--about four years old, in fact, since you really couldn't build a 2.0 company from the ground up, based on commercial off-the-shelf tools, before 2008. Of course, not all successful four-year-old businesses will go on to become large. Most will either fail or stabilize at medium size. But a few will grow big.
Transitional E2.0 Economics
This means that this transition-era Enterprise 2.0 conversation we're all so excited about today is going to be largely irrelevant by about 2018, when the first generation of digital-migrant Enterprise 2.0 businesses grows up. There's still plenty of action left in the old economy, but the emerging new management science will have to be based on companies founded after 2008.
[ Why is gamification a big deal? See Enterprise Gamification Ready To Make The Collaborative Dream Real.]
What's more, only a fraction (perhaps a third) of today's transitioning companies will actually make it. The rest will succumb to one of what I call the four horsemen of the enterprisocalypse: dissolution, disruption, disaggregation, and de-engineering. Their stories will at best teach us how not to fail. Not how to succeed.
Which transitioning companies will make it? Companies that own a valuable data flow are well positioned. If your competitive advantage is based on privileged access to some river of data, there's a good chance you'll make it. If not, there's a good chance somebody will eat your lunch.
Where The Future Is Emerging
A couple of recent consulting assignments afforded me a privileged view of the emerging digital native landscape.
The main players are in sectors you'd expect: media, gaming, entertainment, design, biotech, and consumer retail. These sectors are starting to transform at their very core.
Other sectors are transforming from the edges--previously weak parts of the supply chain are becoming strong. Such sectors include finance (innovative banking services), specialty manufacturing, education, contract labor, outsourced customer support, small business logistics, and event management.
What do digital native companies look like today, and what are they likely to look like when they grow up?
We're used to thinking of big companies based on three dimensions: revenue, staff size, and value addition. So typically, hedge funds aren't considered big companies. Despite producing a lot of revenue, they have small staffs and don't add much value to the real economy.
Likewise, digital native companies look small on the staff and value-addition dimensions. It's possible for them to get to multiple billions of dollars in revenue with only thousands of employees and very little direct value addition. To tell them apart from businesses like hedge funds, you must look at how the staff strength and in-house value addition are amplified via leverage.
So in the case of the large consumer Web E2.0 businesses of today, user-generated content adds both de facto staff and a lot of the value that's being booked as revenue. Or to take a non-consumer-Web example, the transformation of retail through self-checkout, social commerce, and other innovations has created a leveraged labor force. Customers are now checkout clerks and baggers, as well as part of the marketing staff, since they spend more of their time looking into and reviewing businesses and selling to others by feeding recommendation algorithms and participating in online word-of-mouth.