In the last 2/3 years, our market has been facing great changes. Not even the big firms are having a good time; rather, it is quite the opposite. Their payment times have become even longer than their decisional times. For them, not taking any action has become a sort of strategy, given how much they fear making a mistake.

It’s better to look for new markets as soon as possible. We will search for clients abroad, although keeping here our production. In the meanwhile, however, there has been a market which found us, without us actually looking for it. It’s the start-up market. If the former one didn’t take any decision at all, the latter does it too much, and too frequently. And as we all know, haste makes waste.
The outcome, is usually a solution that by now gets called, even in an euphemistic way, quick & dirty. The most mean ones do call it the spaghetti code, with reference to the whole software architecture.

Since long time ago, we had adapted to work in an Armageddon Team environment. We always privilege package contracts and this forces us to be strongly efficient in the management of any possible variation that might occur as we go. To be able to sustain the possibility that some start-up might succeed, and if they do, it will be on an international level only, we have to pre-think our sw (software) in terms of horizontal scalability, of which I know the actual meaning, but I like to extend it to the concept of sw.
Which sw does scale horizontally? The one that allows me to change or add components with simplicity and therefore with formal “neatness” at every level of the software architecture. Thus, here comes our asymptotic goal regarding the proceeding through successive approximations: quick & clean. We need to render clean what is usually dirty, while respecting an important commitment: quick

Startup time is a web-TV show dedicated to the start-up ecosystem – DTT 294 channel

The anchorman of this show has published on “Opinionage” this question, that directly concerns us: “Is it better to first create a business plan/society, or to first test on the market a functioning prototype?“ adding the following introductory comment: “In this simple question, two completely different approaches for the launch of a new venture are hidden. Obviously some activities are “capital-intensive” and thus might require a remarkable funding for the development of a prototype, but this is not always the case, leaning to use this model even for start-up that should be “lighter”. For example, in USA, they have been talking about “lean start-up”. But what do we think could be more useful for our market/context, here in Italy? A structured approach including a business plan and society incorporation, or a more “proof of concept” one, completely focused on the product/service? And in both cases, which are the major difficulties that we are going to face or fear the most? And why?”

Everyone can participate at the debate as well as the poll, by registering on “Opinionage.com”

Funding innovation initiatives coming out from public research early stage results by Claudio Mordà general manager at Rete Ventures

Positioning: in the last three years I’ve been in charge to develop and manage (Rete Ventures) a start-up promoted and owned by the largest italian public research body.

Operating on the market, our goal is to facilitate and enable new innovation initiatives, based on the exploitation of scientific research results and technologies coming out from research labs (licensing intellectual property rights, creating spin-off, …) including funding of those initiatives. The very early stage nature of scientific/technological results from public research represents a critical point for anyone intending to exploit those results. Prototyping may bridge the gap between a promising early stage invention and its industrial development and application. Funding the passage from Research to Development (seed capital, tech transfer project, …) it’s not so easy even if it would desirable.

Hereafter some of the issues to consider when addressing a prototyping objective in a public research environment.

• There are tens of research areas/topics to work with. They sweep from biotechnology, to nanotech, from medicine to agriculture, from molecules to software, …

Issue #1 – What a prototype is? Prototyping may have different meanings. In other words it is context sensitive. Different approaches are needed. Both to build prototype and to manage them.

• Some technologies are completely a-specific (from an application point of view) and cross-discliplinary.
  (real life) example: Special surface treatment/modification may enable a very effective hydrophobic behaviour. They can apply this surface modification technique to textiles, ceramics, glass, …

Issue #2 – A prototype of what? Who is the customer?

• The availability of a concrete running prototype is very valuable for any investor and for any researcher too. Due to the limited amount of resources available, achieving a concrete running prototype could be a very critical issue. In particular, every time they cannot somehow “virtualize” the prototype itself.

Issue #3 – Even if “concrete” doesn’t always mean physical, nevertheless in our case we need to manage also very physical systems, i.e. a very physical prototype. This increases the amount of resources they need.

• A concrete running prototye may be something different from a “simple” proof of concept. It wuold desirable to stay closer to the final user environment. In other words, “R&D” is a two sides context where “proof of concept” stay more into the “R” – research – and  “prototype” stay more into the “D” – development.
  (real life) example: an excellent nanostrucured sensor of combustion products, able to produce realtime feedback to an emission control system, may face serious acceptability problems if not easily interfaceable with the emission system itself and to the existing control device.

Issue #4 – It’s highly reccomended to make the investor understand the final application and the possible related business model you can build upon it and sustain.

• Any investor – even the inventor himself, in case of a resear-preneur – needs to consider how long and complex is the path leading from the invention to a feasible “industrial” application and to exploitation of that invention. Even considering only the dimension of time, the path can be very different. Drawing a diagram “technology risk vs time”, the resulting curve of a nanotech based new photovoltaic application, it is considerably different in respect of a biotech based molecule for a new drug.

Issue #5 – a running prototype rises the confidence in being able to better manage the risk intrinsic to any new technology, lowering that risk.

• Last but not least. Prototype comes from Greek: πρωτότυπον (prototypon) “primitive form” that results from πρῶτος (protos) “first” + τύπος (typos) “impression”.

Issue #6  – definitely prototypes improve the way we may communicate our technology, its application and, most of all, advantages and opportunities resulting from its adoption.

by Lorenzo Brenta advisor and partner at FastPrototypingLab

Over the last 500 years science has freed itself from a top-down cognitive process: Galileo and other prominent scientists introduced the bottom-up approach (scientific method), thereby accelerating progress exponentially. Over time, the same bottom-up principles also came to dominate the economic and political arena (think of democracy). The new approaches based on this method are largely responsible for the explosive growth in wealth and the demographic success that characterize our modern societies.

In science, a bottom-up approach entails experimenting, gathering data and building models to explain the data. Building models is very different from claiming absolute truth. It is a continuous process of discovery and refinement. Uncertainty is intrinsic to the process, and so is failure.

Uncertainty is the first source of our knowledge. Keeping the door open to doubt, to novel information or better arguments is the foundation of science. Uncertainty, by limiting the range in which a conclusion holds true, increases the reliability of our conclusions. Similarly, failure is not something to be avoided. You can learn as much from an experiment that does not work as from one that does, if you have the right attitude. Indeed, the process of pushing the concept or product to “the limit”, to the point it fails, has fostered numerous engineering accomplishments.

More recently, in the ’40s, with the development of games theory in mathematics, the scientific method was further enhanced by the emergence of collaboration. The increasing of scientific Nobel prizes awarded to more than one individual is there to testify how widespread collaboration has become. This approach, now recognized even as a fundamental principle of evolution (together with mutation and natural selection), was also quickly adopted by the business world in international trade, and by politicians in shaping international organizations. The dividend has been spectacular, not only in terms of economic growth but also in the decline of war and ethnic violence.

Most importantly, in the scientific process, decisions are based on evaluating what works better, not by claiming received wisdom. In other words, decisions are based on the concept of controlled experiment. Experiments are nothing new in our cognitive process. We experiment all the time in our most critical learning stages as babies, toddlers and adolescents. The approach, though, is contrary to the learned behavior of introspecting or “calling a meeting”, yet proven vastly superior: concepts like evolution by natural selection, or quantum mechanics are counter-intuitive.

In business, certain typically bottom-up approaches are now commonly used. We regularly build models and readily understand the value of collaboration. We are learning to deal with ever increasing uncertainty. Yet, other aspects still have to be fully understood and interiorized. The value of failure is neither well appreciated nor deemed acceptable in many business cultures, particularly the Asian ones. Consequently, fully experimental approaches are hardly ever put in place.

So, why not use experimental approaches in business in a systematic way? Experiments can be far more successful in determining superior results than commonly used approaches such as seniority or consensus. Additionally, the ever more important and pervading Web provides the ideal medium to perform experiments, with its rapid data acquisition, and the ease and limited cost of testing product changes.

Think bottom up! Act bottom up!

Prototyping the Future by Jaap Kalma Advisor and partner at Fastprototypinglab

Launching an innovative venture is no piece of cake. To tread where no one has gone before, with the odds heavily stacked against being successful, takes great vision, competence and character – or mindless overconfidence in one’s abilities and luck. Probably both. Our economy surely needs growth, but unfortunately there aren’t many of these “superman entrepreneurs” around. As a result, many promising new business ideas flounder because they lack such a driving force behind them.

Clearly, a mechanism which enables to quickly and cheaply check the market validity of a new business idea would be highly valuable. Market research had this pretense at some point, with ever greater sophistication (and cost) in simulating test market conditions. Unfortunately, research is limited and artificial by nature, and while important, it is notoriously difficult to use well. For this reason entrepreneurs tend to make little use of it, and simply launch their venture on the market – costly, time-consuming, and risky to their reputation (in Italy) as it may be. While many other great, promising ideas remain unexplored.

Apart from the economic opportunity for new ventures they present, new digital technologies now also allow for a third route between a full-out launch and market research: Prototyping. By developing a ‘façade’ front-end product that tests market validity, without investing in the expensive but more predictable back-end automation that would make it economically feasible, one can quickly test an idea’s potential on the market. This applies to services, but to ever more segments of manufacturing as well thanks to the rapid progress in 3D printing. Quick feedback allows quick adjustments to find the key for success, properly what successful entrepreneurs do best. This doesn’t mean it’s easy, or that old-fashioned quality in strategy and execution doesn’t count anymore. Rather, it requires an additional, complex skill-set. Treading where no one has gone before hasn’t become easier for those that master it, only faster, more economic, and less risky.

by Piero Formica, Senior Research Fellow, Innovation Value Institute, National University of Ireland (www.ivi.ie)

The physical economy gradually gives way to the digital economy. This puts entrepreneurial start-ups under the pressure of a changing landscape. From incubators to accelerators and experimental labs, a broad range of start-up nurseries work to lower the pressure. Even though seed and early stage funds are slipping, multiple and cheaper digital technologies trim down start-up costs and make more options available for budding entrepreneurs. Vigilant observation of the facts under the realism of assumptions – what we call ‘entrepreneurship through experimentation’ –helps knock down barriers that prevent potential entrepreneurs from exercising novel ideas and thereby increase the chances for an increasing number of young innovative companies to get off the ground.
New business ideas are brought to entrepreneurial execution through people, process, organization and delivery. However, being subject to a high degree of uncertainty, novelty makes people uncomfortable as to the launch of an entrepreneurial initiative. Stepping outside the bounds of safety means the recognition and acceptance of a culture of how to handle uncertain expectations that, all other things equal, interfere with the ability to recognize a novel idea.

References:
“Laboratory experiments as a tool in the empirical economic analysis of high-expectation entrepreneurship (with Martin Curley), Industry & Higher Education, Vol 22, No 6, December 2008
“Accelerating venture creation and building on mutual strengths in experimental business labs” (with Martin Curley), INDUSTRY & HIGHER EDUCATION, Vol 24, No 1, February 2010, pp 7–10
“From Entrepreneurial Fission to Entrepreneurial Fusion: Achieving interaction resonance in a micro innovation ecology” (with Martin Curley and Vincenzo Nicolò), INDUSTRY & HIGHER EDUCATION, February 2011
“Experiencing Experiments: A multiplayer game to build upon one another’s ideas – Crusoe gives way to Gulliver”, Industry & Higher Education, February 2012
The Experimental Nature of New Venture Creation (forthcoming, Springer, Fall 2012)

Personally I don’t believe in the existence of prefabricated formulas, algorithms, processes, that if applied can lead someone to create a successful company. Starting a company or business is certainly risky and nothing can assure us that the venture will be successful.

I believe, however, that if you  have the ability to learn  quickly and inexpensively from your mistakes, then the chances of being able to create a financially sustainable company grow considerably.

Learning quickly from one’s own mistakes requires essentially a personal attitude that not everybody has (admitting of being wrong, thinking critically over the mistakes made and learning from this experience) and a way forward that allows to check quickly and inexpensively the value of one’s own work.

The latter aspect passes through the ability to prototype efficiently the basic elements of one’s own offer. It could be taken for granted, but knowing what to prototype is a difficult art that requires, besides the necessary technical means, market insight. Even this, though, can be refined with the proper process of  prototyping, which is definitely one of the most fascinating aspect of the matter.