The new frontier of work: Hyperspecialization

For the past five years, our work at MIT’s Center for Collective Intelligence has looked at how new communication technologies—particularly the Internet— enable large numbers of people all over the planet to work together in new and different ways. Last year my colleagues and I unveiled our first attempt at
“mapping the genome” of collective intelligence* by identifying the building blocks of how companies can construct productive and efficient collective intelligence systems.

Our newest addition to the genome is  hyperspecialization. The idea, which we have written about in the latest edition of Harvard Business Review,** refers to the way in which work that was previously done by one person is now being broken into more-specialized pieces done by several people.

Hyperspecialization is not the same as outsourcing or offshoring, though it is enabled by the same technologies. Here’s a way to wrap your brain around the idea:

Imagine for a moment that physical goods could be transported just as easily, quickly, and cheaply as information. Suppose, for instance, that you could order an egg for breakfast that was prepared all over the world: perhaps the egg was laid in Shanghai, cracked in Stockholm, scrambled in Singapore, heated in Seoul, salted in Santiago, and served to you in San Francisco. This, essentially, is what hyperspecialization is, but
instead of making breakfast, workers all over the world can do pieces of knowledge work jobs that are today done by one person in a single place.

To grasp just how much hyperspecialization could potentially benefit the global
workforce, consider how much time you personally spend on small tasks during
your workday that don’t draw on your expertise and that you may not be particularly good at. This could be anything from creating a PowerPoint presentation, to analyzing a foreign accounting document.

Enter a service that could offer instant entrée to a network of individuals around
the world who can do those tasks faster and cheaper than you. The service would
give you access to, say, a group of slide-making specialists: software designers, graphic design artists, proofreaders, and maybe even content experts with particular industry knowledge. (Some, for instance, might specialize in sales presentations for office supply products, and others in internal project review meetings for the pharmaceutical industry.) By using a service like this you could free up your time to concentrate on bigger projects that draw on your own unique expertise.

In our article, we highlight several such services. TopCoder, a start-up software
firm based in Connecticut, slices its clients’ IT projects into small chunks and offers them up to its worldwide community of freelance developers as competitive challenges. On platforms such as Mechanical Turk and Samasource, workers take on tiny tasks that often involve piecemeal work, such as organizing photos, editing text, and basic data entry in exchange for payment.

Meanwhile, InnoCentive stages competitions in which scientists and technologists all over the world solve difficult problems posted by companies who can’t or don’t want to solve the problems internally.

The point is: there are already huge opportunities for companies to engage hyper-specialist knowledge workers, and for these highly specialized workers to make money. The potential quality, speed, and cost advantages virtually guarantee that this model will become more prevalent.

But what could hamper its widespread adoption?

One challenge is the difficulty of recruiting hyperspecialists. Platforms such as TopCoder and Mechanical Turk greatly simplify the process for organizations that want to engage hyperspecialists because they can simply use the pool that has already been assembled. But these platforms are still less than a decade old, and are few and far between. In the coming years, we predict there will be many more platform providers of this sort and that some will reach very large scale.

Another obstacle is the complicated laws and regulations that surround cross-border
knowledge work. There’s a need for simplification and rationalization of tax laws and labor regulations country-to-country and even state-to-state in order for hyperspecialization to really take off.

The third and perhaps biggest barrier has to do with our mental model of work. Often,
it simply doesn’t occur to us to organize work this way. We need to get much better at what you might call “micro-delegation” – that is, assigning other people to do small pieces of work that we need done. (Micro-delegation is the opposite of micro-management, in which one intervenes in and monitors much too closely work one has delegated to others.)

In our article, we also talk about some of the potential downsides of hyperspecialization, and I think it is important to consider these carefully and reduce them as much as possible. Overall, though, I think the benefits of hyperspecialization are likely to far outweigh the costs. Few of us would voluntarily give up the benefits that have come from the industrialization of physical work over the last two centuries, and I suspect our descendants will feel the same way about the hyperspecialization of knowledge work a few decades from now.

Thomas Malone is the Patrick J. McGovern Professor of Management at the MIT Sloan School of Management and the founding director of the MIT Center for Collective Intelligence. 

*http://sloanreview.mit.edu/the-magazine/2010-spring/51303/the-collective-intelligence-genome/

**The Big Idea [TM1]: The Age of Hyperspecialization; Harvard Business Review, July/August 2011: http://hbr.org/2011/07/the-big-idea-the-age-of-hyperspecialization/ar/1 (Co-written with colleagues Robert Laubacher, associate director of the MIT Center for Collective Intelligence, and Tammy Johns, senior vice president of innovation and workforce solutions for ManpowerGroup)

 


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