The IT
productivity paradox apparently does not show any signs of going away. Some of
the scientists who originally coined the term have just come up with more research. This new research is now linked to AI and shows that the deceleration
of productivity growth has become even worse that it was twenty-five years ago
when the discussion started. The average annual productivity growth in the US was
at 2,8 % in 1995 – 2004 and it dropped to just 1,3 % in 2005 – 2016.
Interestingly,
most of the presented explanations are still very much the same as they were in
1993 when the same author published his first famous paper on this subject.
The core of
the paradox twenty-five years ago was “mismeasurement”, which meant that the
productivity actually grows but we somehow do not see it. All right, we are now
in 2018, so you would think twenty-five years were enough to figure out how to
measure that invisible growth? Apparently the numbers are even worse now than
then, so there is no invisible growth. At that time, twenty-five years back, the
second possible explanation was seen in “implementation lags”. Now, as the “mismeasurement”
theory does not hold anymore, this implementation lag becomes “the biggest
contributor to the paradox”.
But this
also does not stand. Twenty-five years should have been enough to start seeing
at least minimal growth even given all the lags, and the only trend we see is
continuing deceleration.
So, I would
have a much simpler explanation for the paradox. If productivity keeps
decelerating during the twenty-five years of IT implementation across all
trades, shall we conclude that it is this exact factor, information technology,
that causes of the deceleration?
Here are
two specific examples why and how this happens.
Let us look
at AI and its flagship application, which is customer service through chatbots.
There is analysis of cost per call going down from $35 - $50 on the phone to $8
- $10 in a web chat. Looks good in the first place, but note a very
revealing phrase in the same paragraph about the increased handle time of the
web chat. This is not just the agent’s time; this is also customer’s time. As
it increases, the customer loses more time with the service and cannot dedicate
this time to own business. Among the customers of Hypersoft, we have seen
organizations where employees spend on average 15 or even 30 minutes in
electronic interactions with automated service and support applications. This
is as much as six percent of working time lost. In fact, some vendors of
chatbot software even consult their customers how to increase the average session
length! The balance is obvious: whatever is saved on the call center agent, is
lost by the customer having to spend their expensive time dealing with the bots
and automated response systems.
Another
example is the incredible easiness of pulling people into virtual meetings with
the modern conferencing software. I know one customer where the average count
of meeting participants went from 3 – 5 to 12 – 14 after they made a virtual conferencing
system available to all their employees. How does it help that those 14 persons
did not incur travel expenses, and is it possible to believe that an average
meeting in a large company needs 14 participants? I guess the answer is obvious
here.
There are
many more similar situations, which we encounter daily with our Productivity
Analytics. This is not proof of digital technology being always counterproductive
by its nature. However, this is proof that the technology does generate
substantial loss of time by keeping people busy with it, instead of doing their
work. And it is not just training people how to use it right, it is the very
nature of many modern productivity tools to replace work by “work-related
communication”.
We plan to
continue this research. There is a lot of discussion going on at business about
“technology adoption”, which is somehow presumed to always be a good thing. But
we need to identify all those cases when implementation of digital technology
results in an increase of the total time that all involved persons need to
produce the same output. We can do this quite well already with Omnicontext,
and we are improving these capabilities every day. Stay tuned, there will be
more insight coming from Hypersoft on this topic.