In the world of trading stocks, a well known adage is
If you have a good trading system you trade your money, if it’s mediocre you trade other people’s money and if it’s lousy you write a book about it.
In inventing as in stocks, to make money, talent alone does not work and luck is an important factor. But to come up with ideas is certainly a learnable trait. I have met many people who teach how to invent. One would imagine that such teachers can generate ideas effortlessly, however the reality is that inventors need at least two aspects of knowledge to be prolific. The first is indeed systematic methods of inventing. The second, which in today’s lean and quick world is often forgotten, is a wide knowledge base. If we compare inventing to quick reading, than the methods of systematic inventing are methods of quick reading, but the knowledge is the books.
The biggest driver for knowledge is curiosity, which is why curious people make good inventors.
A few days ago I participated in a panel about “things developers overlook”. The panel consisted of a great group of people and many smart things were said such as
- listening to your customers, both internal as well as external
- the crucial importance of a system architect or system engineer
- the art of engineering communication through specifications, requirements and presentations
- having a structured process in place such as New Product Introduction (NPI)
After the panel I thought of the many examples where all these things existed, yet an engineering error (or decision) permeated through the development process and emerged as a product catastrophe and a major embarrassment to the relevant company. These occurrences are not rare and indicate that in the complex world we live in and develop for, even the best methods and plans fall short of expectations. Its well known that released software has bugs, either large or small, its also widely accepted that products may be recalled. yet we find it hard to accept that engineering is limited in its ability to execute without flaw in the development cycle.
I though of giving some examples from the best of companies to remind us to be wary of data, plans and to constructively question our development activities
In 2010 left handed people reported having a significant percentage of dropped calls when using their iphone 4. It seems the problem was related to a choice of antenna placement in the phone. In 2014 when Apple released the iphone 6 and 6+ users complained of bending phones. The problem was apparently related to engineering and design trade-offs made in the phones.
The Pentium FDIV bug is a bug in the Intel P5 Pentium floating point unit (FPU). Because of the bug, the processor can return incorrect decimal results, an issue troublesome for the precise calculations needed in fields like math and science. Discovered by Professor Thomas R. Nicely at Lynchburg College. Intel attributed the error to missing entries in the lookup table used by the floating-point division circuitry.
Most recently the Volkswagen Emission Scandal is an amazing lesson in realizing and managing the limitations of engineering.
From the dawn of mankind, ideas have pushed the boundaries of reality and expanded our knowledge and capabilities. The first person who realized how fire can be used to cook food, or the first person to invent the wheel had a huge challenge in reaping the rewards of their invention. The reduction to practice may have been simple, but the dissemination and protection of ideas had to wait a few thousand years to the era of patents and writing.
Today, inventors and idea originators have a whole system to protect their ideas, but the reduction to practice, and commercialization are often a daunting task.
The simple case is an idea which can become a company. In this case, the idea originator either forms a company, builds a team and raises money to make the idea happen or he should find an entrepreneur who has the drive to create a company around the idea.
Other ideas are challenged to become companies. These ideas typically exist within an ecosystem of constraints, or within established markets (e.g. toys, food etc) which require extensive capital to bring products to market. In these cases while the option of forming a company is possible alternatives such as open innovation are attractive. the following is a partial list of sites which offer challenges and are seeking ideas. These sites present a lower effort route than forming a company towards commercialization of ideas.
Quirky is a site mostly aimed at gadgets
NineSigma typically provides technical problems from large companies
Innocentive also offers less technical challenges
Kaggle is geared towards the data scientist
Intellectual Ventures focuses on building long term relationships with its inventors
just follow the link
“Some men fish all their lives without knowing it is not really the fish they are after.”
Henry David Thoreau
The problem most people have with statistics is acceptance. Most people understand probability, even it’s implication on potential outcomes and yet when emotion comes into play and our sense of control takes over statistics become something to beat.
That’s why it’s interesting to hear Bill Gross speak on TED on why startups fail
Bill Gross claims timing, more than the team, the idea and the execution is the most important element. But timing is something we don’t control ( or it would have been relegated to second place by team or execution).
So when people talk about growing unicorns ( legendary horned horse and companies worth over $1B ) they are like the person focusing really hard before throwing the dice. Unless the dice is rigged, the focus does not effect the outcome.
What people should talk about and preferably act upon stems not from fighting the probabilities but by embracing them. If we use the dice analogy then the rules can be summed as
- Create a conducive atmosphere to dice throwing
- Throw the dice as often as possible
In startup speak this means frugality in operations until the dice fall as you need.
I read with sadness “quirky bails on building not-so-useful products“. The sadness is that the initial quirky model was an inventors dream come true, scrabble something on a napkin, get it voted and presto quirky’s product machine will make it happen. Since I am always looking at new open innovation models, I registered and tried my luck at inventing a few things. My initial observations were that
– there were very few actual inventors inventing things on the site
– most of the inventions looked like not so useful products
The latest news from Quirky reaffirmed my conviction that open innovation is about two things
– the channel to customer
– and enough motivation for the inventors
Quirky finally has figured the first one out, now I wonder if they will find a better way to make the second thing happen