CGE Blog
January 29, 2014

The (Dis)assembly Line: Lessons From the Past on Collaborative Productivity

I recently read Matt Charlet’s blog post(1) in which he writes that collaborative productivity is increasingly important. Charlet explains that “ten years ago, 78 percent of an employee’s impact on functional or business unit performance came from their individual task performance and only 22 percent came from network performance. Today, the breakdown is 51 percent task performance, 49 percent network performance.” Charlet goes on to argue that IT employees “are asked to act more like anthropologists than engineers” when assessing collaborative teams in their “natural habitat.”

This reference piqued my curiosity to dig further. Could the recent explosion in collaborative productivity simply be a reflection of learning how to capitalize on the natural tendency of humans to collaborate when dealing with problems?(2) Then I wandered a little further off and thought: Is the enterprise collaboration tool nothing more than a 21st-century equivalent of the assembly line? This led me to explore the origins of the assembly line and, inevitably, to Henry Ford.

Ford found a way to make the bulk of his workforce more productive. The story goes that William Klann returned to Ford after visiting a slaughterhouse where the “disassembly line” saw “[meat] butchered as [it] moved along a conveyor. The efficiency of one person removing the same piece over and over caught his attention.”(3) As pretty much everyone knows, the resulting increase in productivity from the adoption of the assembly line established Ford in the annals of industrialist history. I then thought, enterprise collaboration tools are the equivalent of a (dis)assembly line for knowledge workers, who assemble and disassemble ideas. After a quick Google search, I found that I am not the only one to have this idea, as John Wink pointed this out in his blog under a learning context(4), although I had problems finding anyone who had fully explored the concept.

Does knowledge work align to this model? Knowledge work can involve straight line processes that fit the traditional assembly line model but it also includes iterative analytical approaches and free form creative scrums. Of course, the precursor to successful automation is process definition. I believe if the straight line and iterative processes are defined and automated, then keeping those open to more eyes, as modern collaboration tools do, could result in productivity increases in all three via the one percent rule.(5) The 99 percent of lurkers must engage on the defined processes they are actively tagged on, and all three process types will gain from the one percent active contributors that float between processes and add value. Sounds simple, but then why doesn’t every implementation bring instant value?

I returned to Ford’s experience for more information. You see, the craftsmen who used to build parts in their separate workshops and then assemble them piecemeal did not always like this assembly line idea. Ford countered by giving the best craftsmen motivation when he “astonished the world in 1914 by offering a $5 per day wage [$120 today], which more than doubled the rate… [and] instead of constant turnover of employees, the best mechanics in Detroit flocked to Ford, bringing their human capital and expertise, raising productivity, and lowering training costs… [Ford] also set a new, reduced workweek [48 hours, then 40 hours per week], although the details vary.”(6) However, Ford also made it possible for a non-craftsman to work and build things that the craftsmen previously had a monopoly over. I am sure not everyone was happy, even with more money and free time.

Modern day knowledge workers push back on the assembly line concept as part of the cultural shift necessary for collaborative productivity to succeed. After all, why did knowledge workers invest in school to work on an assembly line? Business leaders – not just IT leaders – must recognize and engage with this, before they can realize the benefits. But modern day knowledge workers are not only motivated by money and shortened work weeks. This is where we go to Daniel Pink’s concept of modern day motivation – autonomy, mastery and purpose.(7) Leaders today have to reward and reinforce the culture that leads to successful adoption of collaborative productivity, using concepts such as work from anywhere (autonomy), training (mastery) and, of course, a relatable vision of the big picture (purpose). Certainly it can work, as described by Mary K. Montgomery in her lecture explaining that in her assembly line biology research model “each student is respected for his/her contribution and everyone is invested in analyzing the results. Eventually, the students learn many of the other techniques as well, mostly from looking over the shoulders of each other during the inevitable laboratory ‘down time’… Students learn about shared responsibility and the true nature of collaboration.”(8)

Finally, I looked at the potential upper limit of collaborative productivity and found Richard Janow’s paper on “collaborative entropy”(9), or the cost of coordinating a collaborative work environment in large organizations. Mathematical models aside, Janow explains: “The productivity impact of collaborative entropy is large enough to strongly affect competitive advantage. Impact is maximized when the ratio of collaborative to individual effort is large. Large organizations may thus be inherently disadvantaged versus small ones wherever fast decision-making or high knowledge worker productivity are key drivers. Even a modest amount of collaboration significantly decreases the productivity of actors functioning primarily as individual contributors.”

So back to Charlet’s marvellous post which started us off. Leaders should encourage culture conducive to adoption of the (dis)assembly line of enterprise collaboration tools, but they must also ensure that the role of personal productivity, with its own mastery, autonomy and contribution, is still respected. Lastly, the knowledge work processes that can be defined must be defined before automation. A hammer cannot pound nails unless the human arm shows it what angle and amount of force to employ. This is a delicate balance, but one that could spark the greatest increase in productivity since the early 1900s.

Now its your turn. Together we can (dis)assemble this idea. Let me know what you think.

 —

References

1. Matt Charlet. “The Curiously Unsolved Case of Enterprise Collaboration” CEB’s IT Blog (29 August 2013)
2. Yvonne Rekers, Daniel B.M. Haun, Michael Tomasello “Children, but Not Chimpanzees, Prefer to Collaborate” Current Biology – 25 October 2011 (Vol. 21, Issue 20, pp. 1756-1758)
3. Wikipedia. “Assembly line” http://en.wikipedia.org/wiki/Assembly_line
4. John Wink. “Collaboration like an Assembly Line” LeadLearning blog (4 August 2013)
5. Wikipedia. “1% rule” http://en.wikipedia.org/wiki/1%25_rule_(Internet_culture)
6. Wikipedia. “Henry Ford” http://en.wikipedia.org/wiki/Henry_Ford
7. Daniel Pink. “Drive: The Surprising Truth About What Motivates Us” (2009) Penguin Group.
8. Mary K. Montgomery. “Collaborative research with undergraduate students: An assembly line model” Developmental Biology 247.2 (2002): 13
9. Richard Janow. “A Fundamental Limit on Productivity in Organizations: Collaborative Entropy Costs” (31 May 2008). New Jersey Institute of Technology


Craig Sellars
Craig Sellars is a passionate Canadian public servant and biologist. Connect with Craig on Twitter @CraigSellars.

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