Defining Productivity for the Knowledge Age

Productivity is a term you may hear on a daily basis but have you ever stopped to consider its meaning, especially within the context of knowledge work and knowledge workers?  It probably isn’t what you think it is.

Promises of productivity increases frequently come from technology vendors in the course of promoting their offerings.  Few, if any, appear to be able to explain exactly what they are promising, leaving one to wonder if one might therefore type faster, have more meetings, hold more efficient meetings, or write more memos and e-mail messages?  In a more serious vein, however, this is a very serious question: what exactly do we mean when we use the “p” word?

In an industrial setting, defining productivity is simple; it’s how many widgets go flying out the factory door in a given period.  The American Heritage Dictionary of the English Language, Fourth Edition, defines productivity as “the rate at which goods or services are produced, especially output per unit of labor.”  The Bureau of Labor Statistics uses the term “output per man-hour” to indicate productivity.  When applied to knowledge work however, it seems that all bets are off.  So how exactly can one measure knowledge worker productivity in a quantitative fashion?

It took 150 years from the dawn of the industrial age until the beginnings of a management science began to  develop.  Unfortunately, there is little applicability of the industrial age’s management science to a knowledge economy setting.  Indeed, today we are in the very early stages of developing a management science for the knowledge economy and it will probably be decades before we fully understand even what questions have to be asked.  The wide range of tasks that knowledge workers undertake, combined with the fact that there are different levels of knowledge workers, ranging from those with a single skill to highly skilled workers who exercise independent thought and action most of the time, makes both the task of defining productivity and developing a management science somewhat tricky, to say the least.

We’ll continue to examine this topic in the coming weeks and months.  In the meantime, if you have any thoughts, suggestions, or comments, please share them here.

Jonathan B. Spira is the CEO and Chief Analyst at Basex.

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