Many people extol the arrival of a new era of mindsharing where social networks enable us to consult with the wisdom of the crowd. Experiments such as the famous cow weighing experiments demonstrate that a crowd can sometimes arrive at conclusions better than any individual contributor. Referring to , one of the books who started discussing this topic we find that most crowds don’t really bother reading the basic requirements for effective wisdom generation as laid out in this book; In some cases, groups are remarkably intelligent and are often smarter than the smartest people in them. The three conditions for a group to be intelligent are diversity, independence, and decentralization. The best decisions are a product of disagreement and contest. Too much communication can make the group as a whole less intelligent. So it seems that by their very nature, social networks are not a good medium for mindsharing. Networks for mindsharing should actually separate the questions from the answers. People who are answering should not see other answers, and most probably should not see who is asking the question, but if this is the case, why would people participate ? This answer should probably be answered by startups trying to build networks for mindsharing. My interest is the relation of the motivation problem to open innovation. In many cases open innovation is a contest based, non information sharing platform, so it meets the basic requirements. However, as anyone who has dabbled in open innovation quickly finds out, the return on invested time is abysmally low. In fact many times you compete with hundreds of teams for an illusive target. The chances of winning are low, even if you are an expert at the particular field. The solution adopted in some platforms is publicity for winners. However this solution does not scale well, as there is always only one first place. People fare better by writing articles and publishing their work. Digging deeper into most platforms actually reveals an interesting fact; very few people actually participate in these platforms. After all platforms which aim to tap the knowledge of humanity, only attract a few thousand experts of which most don’t actually participate in the different competitions. So while crowds can be wise, its an open game to find ways to motivate the individuals to make this happen.
Lets say I start a kickstarter campaign to fund the development of a time machine. The team which is composed of a cadre of leading Physicists has been hard at work for two years and with the funding we will have a working prototype by the end the year. We are offering the customary T shirts, mugs as well as various levels of souvenirs from the past and future. To fend of the skeptics we are even offering three trips to the future as part of our testing program.
Would you participate ? What would you think of kickstarter if this project succeeds in its funding goal ?
All this is not to condone kickstarter or time travel. Just to share my amazement at the ability of some projects to raise money.
My previous discussion on input devices, brings to mind another topic. As we consider the role of connected devices and electronic helpers the prevailing concept is of an imaginary helper. Something that takes care of the boring chores and fills our life with fun and creativity. We tend to think of the helper much in terms that we have thought about calculators many eons ago. They can do the math but always fall short of being a human. Scifi has of course explored what happens when robots develop feelings and become humans. Yet, no one has yet suggested the unfathomable and perhaps most important electronic aide we need; a rational co processor.
In fact, people always would argue against it, after all Spock from Star Trek was above all rational but lacked feeling. But I am not advocating loss or relegation of feeling. The rational co processor would provide that missing element in any comparative shopping application- the option of not buying. After all, from soft drinks to politicians our world is filled with means to manipulate our irrational part and induce us to buy, vote, or act in certain ways. Its really amazing to consider how much of the GDP is actually stuff which we don’t need but are induced to buy. So if the rational co processor was to take hold, would that bring the economy to a grinding halt ?
From the Microsoft Kinect, Apple’s Siri to Intel’s PerC, organizations are looking for the next thing after touch screens, mice and keyboards.
The quest overshadows the fact that new input devices take a long time to mature. If one examines the history of the computer mouse, its clear that time to mass adoption was more than 20 years. A similar view of the touch screen can trace its origins to the 80’s and mass adoption occurring twenty years later with the touch screen smart phone.
New input devices typically attempt to provide a ‘natural’ user interface, and yet the combination of technology under performance as well as misdirection of the role of the user interface result in a long time to mass adoption.
Stepping back for a moment we can ask ourselves, what is the role of a input device. The answer can encompass a wide range of options from gaming to content creation, and more often than not communication person to person or person to machine. An interesting observation is that while our thoughts are often multifaceted and parallel, our input device interaction, wether typing, speech or gesture is slow and serial.
Gesture recognition is garnering significant attention as people envision electronic devices reading our gestures to enable a sleeker human interface. The early success of the Nintendo Wii and Microsoft Kinect have prompted huge investments and R&D efforts. Yet two years after introduction, the Kinect is not the game changer Microsoft had hoped for. Looking at gesture recognition with a view to past adoption curves, and with a view to its actual usability, it’s clear that the companies adopting an aggressive path have forgotten the lessens from books like the innovators dilemma or crossing the chasm. While they are diligently developing the technology they should be looking for a killer app, something that goes beyond cool. The app doesn’t need a huge market, but it should be critical enough to make a paradigm shift. In its absence, the adoption curve would sway between the wind of cool, and overhyped expectations.
In US patent law, one of the key requirements to grant a patent is that the patented idea is non obvious. The legal meaning and implications of non obviousness have attracted considerable discussion and research. Obviousness puts a threshold for invention and differentiates normal problem solving skills from the qualities required of an invention.
This raises an important question regarding the use of structured thinking tools such as TRIZ to create patents. If we take the extreme case and imagine a patent machine. A machine which takes as input the current state of art and comes up with new ideas based on a set of manipulations and predefined criteria. The question is whether the output of this machine is patent-able, or are the obtained patents obvious because anyone skilled in the art following the same instructions would have found them ?
It would seem that the invention requires something beyond the predefined instruction set, an expected stroke of genius, to convince the USPTO, the idea is worthy of a patent. This also highlights one of the differences between problem solving and inventing; which is framing.
When you solve problems, the goal is to find a solution. This solution can be tested and verified and the problem resolved. However not every solution is patentable or an invention. Putting aside issues of novelty, and focusing on the obviousness, the question is one of context. TRIZ for example offers structure for solving problems, but not of wording or defining the problem. Hence in the case of TRIZ, the obvious part may be the solution, but framing the problem is non obvious and yet since it leads to a solution, it is at the heart of the invention. In cases where the creative process creates many options to choose from, the question is whether the choice is obvious or not.
The situation is somewhat analogous to photography. After all, a photograph is a representation of the world. Something that everyone sees. However,the photograph frames reality. It focuses on some elements while relegating others to the background or outside the frame. By doing so, we can now see things we had not seen previously. The frame has created a new context. Similarly in inventing, the act of framing, putting boundaries, changing view point, focus, or even colors brings to light things that were not obvious.
On a practical note, to invent we need to go beyond problem solving. A problem is a good starting point, as is a solution. But we then need to go beyond that, looking at it from different angles, uses, aspects. In framing the problem or solution in several ways we have a unique view, which sometimes leads to inventions.
For example we can start with a problem of the phone of the future. Some envision that Glasses would be the way we communicate. They provide vision, hearing, situation awareness. But they seem to lack user input methods. So this is a good place to think about. What kind of input do we need to provide and how do the glasses use this input. we can imagine 3D image capture and the use of hands and gestures. This by itself is obvious. Yet what kind of gestures make sense and which do not. Can or should we overlay the commands on the hands or surface, and how can we provide tactile feedback. All these questions can find solutions. Some obvious and some not. But even a simple question like gesture recognition can be challenging in the context of eye glasses as they contend with challenging angles, weight and dimension limitations and user modalities. We need to focus on one aspect and drill it down to enablement. But at this stage its clear, that no route is obvious. Hence the outcomes might be patentable.
The best products and services address an unmet need. Startups which identify such opportunities in large markets, grow quickly to become successful companies. When the solution to the unmet need requires a yet to be developed technology, the risk associated with the venture increases dramatically. Just to clarify, a yet to be developed technology is not an integration of several available technologies but something which has a probability of not succeeding.
An example for such a situation is identifying the unmet need for a zero emission low cost fuel source. If we have identified an algae which can efficiently produce emission free bio diesel, than we have a technology path to addressing the need. But if for commercial viability we need to boost the algae production level a hundred fold and experience has shown such development requires ten years, then we don’t have a technology path to walk by.
It is at this juncture that ventures make a dramatic, and usually unconscious decision among several choices. The first is recognizing the prohibitive risk, they seek a different opportunity. The second option is to explore the solution space for alternatives to the yet to be developed technology. The third is to discount the risk and develop the technology.
Ten fold improvement
For ventures pursuing the third option the prevailing benchmark is a 10X improvement in performance over state of art. But this approach actually creates the dreaded technology push. The reason for 10X may be attributed to the semiconductor industry and Moore’s law, which originally charted a two fold reduction in transistor size every two years. Hence if the development of a technology requires 5 years to become a product, than unless it is targeted at 10X, it will be obsolete by the the time it reaches the market.
So the transition from market need to technology push occurs when development times are long and the focus is on future performance. Aggressive targets are chosen to resolve the marketing risks five years into the future. The combination of all these create a spiral feeding itself of aggressive targets, development delays, market risk and even more aggressive targets. In software, you can release a semi featured, partially bugged product, and call it a beta. In other fields you use many terms, but in all cases the revenues remain in a distant horizon.
Its all about the timeline
The only solution to the technology push spiral is to acknowledge the risk associated with time. The project focus, should always be on shortening the schedule. Often the best way to start is by realizing short schedules enable less aggressive product specifications.
A Level Playfield
Apps are a great example of reducing the required resources to take a software idea to revenue. The critical question is what is the Return On Investment for the App market. This question has two aspects. The first relates to any investment decision in apps. The second is more general and holds lessons for any idea market.
App stores publish general statistics on downloads, and overall income, but refrain from publishing detailed statistics. Running through the published numbers reveals that apps in general do not provide a return on investment. The simple calculation is dividing the announced income from apps by the number of apps in the App Store resulting in an income of less than $10,000 per app. Since the required development cost of an app is estimated at around $50,000, it’s clear the ROI is difficult to justify. This also explains the absence of detailed statistics and a focus on success stories. After all success stories, as the lottery industry well knows, are a strong sales driver for app developers.
So the problem with lowering the barrier to revenue is that it promotes a gambling approach, where the thrill of participation offsets the low potential of winning. Another advantage of apps is the fact revenue is often not the primary success driver and downloads often count as the critical parameter. This works well for app developers as it provides short term measures of success.
Between Apps and Ideas
While apps create a thrill, and provide short term measures for success, many other idea markets lack these characteristics. Patents for example, have an ROI of several years, and there is little measure of intermediate success. One way to resolve these problems is creating idea competitions. Most of the crowd sourcing and open innovation sites use competitions to create the required thrill and induce idea submission. The problem with this approach is the ROI for the inventor. If there are hundreds of participants and only one or two winning solutions it’s clear the ROI doesn’t justify investment of time or resources. This also highlights the scalability challenge of open innovation sites.
A possible solution is to create an inventor network. After all in inventing, like in anything else, it’s all about the people. The network through peer review and mentorship creates a community spirit which addresses the time to ROI. The network should include an active buyer community which helps direct the invention process, provides feedback and even some short term monetary motivation. Intellectual Ventures is a great example of an early innovator in this space. It is actively building a worldwide inventor network. Inventors in the network are exposed to request for inventions as well as other inventors and collaboration opportunities. The inventors can submit their ideas to IV, and IV partners with inventors on bringing the best of these ideas to market. Future inventor networks may be fashioned as a social network where ideas are developed between network members and directed by other members towards buyers. But this already is the start of the pitch of my next startup.
To sum, I am a strong believer in idea markets and open innovation and their potential to accelerate innovation and create a better world. Drawing on lessons from the current activities in this field, I think the key elements to enable a sustainable idea market are