|
Productivity Review by a Georgia Tech economist named Peter G.
Sassone.
3
Between 1985 and 1991, Sassone studied twenty
departments at five major US corporations, paying particular
attention to the impact of the arrival of new office technologies such
as personal computers.
As Sassone documents, professionals paid to do highly
specialized work were spending more and more time doing
administrative work. “Intellectual non-specialization was the
dominant characteristic at most of the organizations in this study,”
he writes. The immediate cause of this imbalance, he notes, is a top-
heavy staffing structure that has a skewed ratio of skilled
professionals to support staff. In seeking explanations, he points to
“office automation,” noting that many firms paid for costly computer
systems by reducing support staff that used to perform the functions
computers could now “simplify.”
As Sassone argues, this trade-off can be lopsided. When you
eliminate support staff, the skilled professionals become less
intellectually specialized, as they have to spend more time on
administrative work that computers made just easy enough for them
to handle on their own. As a result, it now requires more of these
professionals to produce the same amount of valuable output for the
market, as they have fewer mental cycles free to conduct this
specialized work. Because the professionals have much higher
salaries than the support staff, replacing the latter with more of the
former can be expensive. Sassone crunches the numbers and argues
that the organizations he studied could immediately reduce their
staffing costs by 15 percent by hiring more support staff, allowing
their professionals to become more productive. To Sassone, this
analysis provides a compelling answer to the stagnating productivity
in the early personal computer age. “Indeed, in many instances firms
have used technology to decrease, rather than to increase,
intellectual specialization,” he writes.
In the intervening decades, the non-specialization issues
reported by Sassone have become even worse. Knowledge workers
with highly trained skills, and the ability to produce high-value
output with their brains, spend much of their time wrangling with
computer systems, scheduling meetings, filling out forms, fighting
with word processors, struggling with PowerPoint, and of course,
above all, sending and receiving digital messages from everyone
about everything at all times. We think we’ve advanced because we
no longer need secretaries or typing pools, but we don’t factor in how
much less bottom-line-boosting work we actually accomplish. I
became so frustrated with the loss of specialization in my own world
of academia that in 2019 I wrote an article for The Chronicle of
Higher Education’s magazine that detailed the many ways in which
professors’ potential intellectual output has been massively
decreased due in large part to increased demands enabled by
technological advances. My editor gave the piece a provocative title:
“Is Email Making Professors Stupid?”
4
It became one of the
magazine’s most read articles of the year.
Tenner notes that economics textbooks used to introduce the
idea of efficient labor markets by telling the story of the best lawyer
in town who also happens to be the best typist. The obvious
conclusion of the textbook story is that the lawyer would be foolish to
not hire a typist. If the lawyer bills $500 an hour and a typist costs
$50 an hour, then the lawyer will clearly end up better off
outsourcing the typing so she can spend more time on legal work.
The arrival of computers in the workplace, it seems, obscured this
once obvious reality. We’ve all become the lawyer spending hours at
the typewriter.
—
In this version of recent workplace history, the arrival of computer
technology led to a diminishment of specialization in knowledge
work. As the data cited above reinforces, this shift likely created
major economic ramifications for this sector. It concerns us here,
however, because it also has a significant impact on our journey to
move past the hyperactive hive mind workflow. The sheer quantity
and variety of tasks in a non-specialized work environment make the
hive mind workflow unavoidable. When you’re faced with an
overwhelming incoming stream of unrelated tasks, you don’t have
enough margin in your schedule to create smarter alternative
workflows—there’s just too much bombarding you to individually
tame everything with optimized processes. In other words, when
playing defense against an onslaught of unpredictable obligations, ad
hoc, unstructured messaging soon becomes the only reasonable
option to prevent yourself from drowning.
This reality creates a nasty, productivity-sapping circularity.
When you’re overloaded, you’re forced to fall back on the flexibility
of the hive mind. This workflow, however, leads to even more
fragmentation of your attention, making you even less efficient in
getting things done. The result: overload increases! As this spiral
continues, you’ll eventually end up in an overwhelmed state of
inefficient desperation, where the idea that you can somehow
carefully engineer smarter workflows seems impossible.
If we want to tame the hyperactive hive mind, therefore, we must
first tame the trend toward non-specialization. By reducing the
number of different obligations you’re required to tackle, you’ll gain
the breathing room needed to then optimize the workflows you
deploy to handle what remains—creating a one-two punch of
productivity gains that can completely transform your effectiveness
or that of your organization. This chapter asks you to embrace the
following principle as a crucial step toward moving past the hive
mind:
Do'stlaringiz bilan baham: |
