Seth Godin has
once again come up with provocative post complete with calculations. The post
(available here)
is on laggards. He terms it the opportunity of laggards and suggests the only
solution to deal with laggards would be to bring them up rather than bring up
the averages. It is normal to find people obsessed with averages. Averages are
pulled down by laggards. Eugenics might suggest an extreme step to eliminate
laggards. There are many others who advocate laggards being brought up to the
standard of the average. The bell curve does exist, yet it’s skewness needs to
be smoothened at its lower tail. Increasing the upper bounds will not seemingly
solve the problem, the only mechanism as Godin seems to put forth is bringing
up the laggards.
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His examples are
very interesting. He uses the example of the road, party laden with dirt, the
rest a smooth highway. His argument as his calculations suggest is not about
building a vehicle that drives faster on the highway but developing a vehicle
that drives faster on the dirt road. In other words, the effectiveness of the
vehicle lies not in it speeding on the highways but its ability to handle the
dirt roads. In fact, it makes quite bit of sense in the Indian context. Given the
complexities, it is rather usual to find road differences in significant
quantum. The Indian automobile industry is not about producing faster cars but
cars that can navigate the roads in the hinterland with efficiency. The road
development in India is of course haphazard. Large number of villages are still
connected by dirt roads. The vehicles that need to navigate these roads need to
be sturdy. This is what the blog attempts to point out in the larger context.
This naturally
has significance for product development and going beyond that product
packaging. There is an anecdote in CK Prahlad’s works wherein he points out
that packaging of a Western MNC entering into India in the early 1990s suffered
quite a bit of damage given the road conditions. The package was suitable for
US conditions. They had to adapt to the changing conditions in India to
survive. This exactly would hold good for the logistics and supply chain who
have to plan their operations not keeping the highways in mind but the dirt
roads that exist off radar. The products designed are not for the best case scenario
but to prove their worth or utility in the laggard scenario. In fact, in the
Indian railways, the speed of the train is determined by the weakest hand, the
slowest maximum permissible speed of the coaches or the wagons in the consist.
Innovation too
is dependent on the laggard phases. To borrow from chemistry, it is the
rate-limiter step that determines the pace of progress. The rate-limiter is
nothing but the slowest step in the process. Development of innovation would
entail building up the slowest hands in the process thus speeding the entire
process rather than focusing on expanding the strongest hands. As in sports, it
is the slowest hand that often acts as a chink in the armour for the
professional teams. This is something that can translated into human resources
at any organization.
Organizations
seek to pursue a goal towards which all their resources are directed. The organization
expects the resources to operate at a certain pace in order to achieve the
goal. The hindrance would obviously be the rate limiting steps or the laggards.
There are some human resources which might perform above average, yet there
would be few who would perform below average. They lag behind the moving
average. The easiest answer would be to fire those laggards so that the
averages pick up. This might sound nice in theory and is the bedrock for the
relative evaluation that happens at multiple levels both in education and
professions. The relative evaluation system would obviously focusing on
identifying the laggards and sending a signal for them to move out. Yet rather
than moving out they could be better harnessed into improving themselves. In any
relative evaluation model, there would be laggards. Just that the average picks
up, does not mean the laggards are eliminated. The point then would be to keep
eliminating the resources whenever they fall below average or not at least are
seen as weak hands pulling down the averages. This is something existential at
any point of time. Therefore, as Godin points out, the increasing averages
would not really translate into good practice on the ground.
Thus the firm
strategy on human resources and its evaluation will have to be viewed in a
different way if Godin were to go by. In the context of economics, there is something
called stated preference and something revealed preference. A manager practising
in the human resources domain would wax eloquently on how he or she strives to
bring the laggards onto the mainstream at par with those at the average or
slightly above average. Yet in practice for all the stated preference they have
been talking about, disappears with the focus being on the creating the exit
strategy for the laggards. As Godin’s short provocative blogs puts out, this is
far from ideal. His calculations demonstrate that increasing the average on the
higher side would not really improve things unless the averages on the laggard
dimensions improve. Digital transactions are not going to be the norm unless
the weakest hand accepts it. In other words, the bottom of the pyramid must
adopt to digital payments if it has to find success. The same holds good for
many an innovation or concepts which necessitate acceptance from those at the
bottom end rather than the top end.
Through the
examples Godin points out the different view of the laggard. A laggard might be
seen an undesirable, yet they would exist. An analysis of the laggard would be
more relative in nature than absolute. The frames of reference change from era
to era. Five miles an hour would have been extraordinary some centuries before.
Maybe a few centuries down the line 500 miles per hour might be sluggish. The point
is not to discard the laggard but to bring them up to a level wherein they
reduce the sluggishness. They contribute to the progress through their own
learnings. These learnings will have to be enhanced rather than a discard.
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