To heck with SnapChat. Gads, it became a fad
as young women stood in front of their
bathroom mirror and used their
smart phone to take imprudent pictures
of themselves. No one knew that this
would be a fad, but anyone could guess
that the fad had a lot wrong with it,
would get a lot of push back, and
would not last very long.

Instead of all that nonsense, to get
around the 'product/market fit' risk,
here is how: Pick a problem where the
first good or a much better solution
will be a must have for a sufficiently
good, large, dedicated, whatever audience
of users/customers to make a business
worth $10+ billion.

The classic would be a safe, effective,
cheap one pill taken once cure for
any cancer. So, have a problem, cancer,
and the first good solution, the one
pill, and it is a must have for a lot
of people -- ballpark half of the
population will die of cancer before
anything else.

So, with that pill, have product/market
fit so strong that just on a rumor
the front doors of the company will be
mobbed by people desperate for the pill.

That situation is what you want to aim for.

Well, everyone can see the problem of
cancer, but so far no one knows how
to make that pill. If making the
pill were easy, then that problem would
have been solved by now.

In information technology, can do
much the same thing: The problem
is already out there and fairly
easy to see.

But, there is
no free lunch here, no royal road,
no ten easy steps. Instead, if lots
of people know how to solve the problem,
then it would have been solved by now.

So, need to attack a problem where
not many people know how to solve it.
In particular, need a problem that just
routine software is not nearly sufficient
for a good solution.

Next, when have the problem and the solution,
the risk is already way, way down,
but have yet to cover ANY of the risk
reduction techniques in the OP.

So, the real key to risk reduction and
high ROI for startup projects is to have
good solutions that nearly no one else
knows how to do.

For now, for information
technology, the best approach to such
solutions is original research in applied
math, typically based on advanced
prerequisites. An advantage is that
such work can
be reviewed reliably. And passing such
review, now have a low risk project
where the rest of the work to high ROI
is routine. That's the goal, right?
I just gave you the magic, golden,
secret sauce, right?

THAT'S, for now, how to do
information technology startups with
high ROI and low risk, right from the
beginning, that is, based on, say, a
project proposal on paper
with the math included.

The ante in that game is to be able
to read, review, check, at least direct
such work, in the math.

I doubt that
there is a single VC firm in the
US that can do that. The NSF can.
So can ONR, and DARPA. So can high
end journals in applied math. So can
the applied math departments of
leading research universities.
But VCs? Nope. With at most
a tiny number of exceptions:
History majors from
Williams College? Nope. Computer science
chaired profs at leading
research universities? Nope. Silicon
Valley entrepreneurs? Nope.

So, we're talking something rare
and exceptional. Well, we know that
except for luck that is a necessary
condition for $10+ billion. So,
we have to be able to work effectively
with things that are exceptional.