The Shape of Productivity to Come

As I've stated in my earlier pieces in this series, we want to make IT more important in the future. However, just linking IT spending to worker productivity doesn't fully address our goal.

We can find as many productivity futures as we can workers, or at least classes of workers. Today, for example, only about a quarter of workers have any significant information content in their jobs, and only about 15% of workers "collaborate" to any significant degree. The people who study how workers actually do their jobs have suggested that at least two thirds of workers could be empowered by IT, and that collaboration could extend to about a third of all workers. That means that we can really chart two courses for productivity evolution -- one that targets broader empowerment and the other that induces broader and more efficient collaboration.

The broader collaboration path seems to lead through the integration of social media concepts with team and project management activity. Nearly every worker today has some experience with social media, and this has created a new kind of skill set, like skill in writing or verbal communication, ready for exploiting in productivity projects. If everyone collaborates socially via social media, why not collaborate likewise in business? But that's not enough; social media should be applied to goal, like deepening or broadening collaboration.

The "deepen" model seems to be the goal of Cisco's Spark, as well as earlier initiatives like Basecamp or Google Wave. A social media site can be a point of information exchange, the place where everyone comes to contribute and access information either in store-and-retain or interactive form. Companies have had success with this approach, but typically with fewer than half of the target workers. The number of interactions you miss is far greater than the number of workers missed, and so the "deep" approach never seems to reach critical mass. More breadth is needed.

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This seems to be what Microsoft has in mind with its acquisition of LinkedIn. Very few people use LinkedIn for team collaboration; arguably it doesn't even have the necessary capabilities. What it does have is scope; most professionals are on it. That means that collaborative relationships inside a company or between companies will often be between current LinkedIn users. The community is in place, awaiting only the tools.

It would be easy to make the Group facility of LinkedIn into a "Team" facility, providing a message-board element of collaboration. Adding in real-time IM and calling (through Skype for Business) would be fairly easy since you can already record contact data in LinkedIn. Note that sans the features of a Spark or Basecamp, the "Skype Teams" team messaging app Microsoft reportedly is developing wouldn't be enough. If a Team could be given cloud storage for files, with version management, you'd have a social-based platform with all the tools of Spark, Basecamp, or Wave, but with a huge in-place community.

But if two thirds of workers could be empowered by IT, even getting all of the one third that could be made collaborative still leaves a third of all workers out in the information darkness. What do you need to do to bring them on board? Remember, they're not collaboration candidates.

Work practice studies show, not surprisingly, that the big problem with empowering the additional third of workers is that their jobs aren't done through computers and networks today. You could argue that a worker who's putting tires on a car or cooking burgers could be empowered, but the problem is that the worker would be burdened just with the task of keeping the IT applications up to date on what they were doing. This is where "contextual" support comes in, and the Internet of Things (IoT).

If IoT is about sensors and controllers everywhere, then IoT processes could be made to do a lot of work without human supervision. That alone would increase productivity, but it seems unlikely that complete automation of tire installation or burger-flipping is in the cards, near term. The impact of IoT is more likely to come from learning things about the worker, which reduces what the worker has to tell an application to get meaningful support.

If a worker's position, whether detected by near-field communications (NFC) or GPS, is proximate to a broken pipe and the worker is a plumbing expert, a reasonable inference is that the worker is there to fix the pipe. Furthermore, if there's a work order in the system to that effect, then you have enough information to "tell" the worker how to find the break. You'd also know whether the pipe was leaking water or some noxious chemical, and advise accordingly. Most important, all of this could be done without the worker having to take time to input information -- time that would have to be made up by any productivity application before you'd even break even.

We can imagine a future where workers equipped with mobile broadband and NFC moves through a fabric of sensors and controllers that tell the workers things and do things on their behalves -- things more profound than automatically opening doors. The problem lies in getting that fabric in place.

Fortunately, one attribute of our un-empowered third of workers is that they tend to stay within facility boundaries, so companies could address IoT goals on an intra-company scale rather than waiting for the whole world to advance to IoT, if it does. Factory processes seem particularly promising, and companies like GE Digital are addressing this space with its cloud-based Predix IoT platform.

None of this is going to be easy, and we shouldn't expect it to be. Radical improvements come only from radical changes, and businesses themselves will have to marshal the political support needed to bring revolutionary solutions into play. The best technology strategy, absent adoption, will always fall short, and the industry can't afford to leave productivity gains on the table if it wants to continue to grow.

Read the earlier posts in this series:

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