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Innovation Process and Change Facilitation Promoting Innovation Systems revised Technology and innovation management

Instigating Innovation: Accelerating Experimentation in industry

Originally published Feb 2016, revised March 2018

When innovation centres, technology transfer centres, applied research platforms and other similar organisations wish to help industry with innovation, one way could be to assist companies to experiment with new ideas. I will simply refer to these centres from now on as innovation and technology support centres. In most of the places where I work these centres are often hosted by or associated with universities, applied research organisations or technology transfer organisations.

One way to support industry to experiment is through various technology demonstration-like activities, allowing enterprises access to scarce and sophisticated equipment where they can try out new ideas. In its simplest form, a facility allows a company to order samples to a certain specification so that the company can see whether a particular process will be able to meet a particular specification or performance criterion. A slightly more intensive form of technology demonstration allows visitors in and a technology and its application is demonstrated (eyes only, no touching!). Very often equipment suppliers play this role, but in many developing countries equipment suppliers act more as agents and cannot really demonstrate equipment.

In Germany I saw demonstration facilities where the pro’s showed the enterprises how things work, and then they stood back to allow teams from companies to try things out themselves.

A critical role of innovation support centres is to provide industry with comparative studies of different process equipment. For instance, an innovation centre supporting metal-based manufacturers, providing the industry with a comparison of the costs and uses of different kinds of CAD systems could be extremely valuable to the industry.

Maker labs, Fablabs and similar centres all make it easier for teams that want to create or tinker with an idea to have access to diverse technologies, reducing the costs of experimenting. However, the equipment in these labs is often not so advanced, but it can often be very diversified. In my experience these centres are very helpful when it comes to refining early idea formation and prototyping. However, helping manufacturers to experiment with different process technologies, different kinds of materials, substitute technologies, etc. is a binding constraint in many developing countries. The costs of gaining new knowledge is high, and the high costs of failure make companies wary of experimenting.

Innovation support centres must be very intentional about reducing the costs of various kinds of experiment if they want manufacturers, emerging enterprises and inventors to try new ideas. These innovation centres can play a role by:

a) assisting companies to organize themselves better for experimentation internally

b) assisting many companies to organize themselves better for experimentation collaboratively

c) conducting transparent experiments on behalf of industry collectives.

In my experience, graduates from science disciplines often understand how to conduct experiments because their course work often involves time in a lab. They know basics such as isolating variables, managing samples, measuring results, etc. However, engineering graduates often do not have this experience (at least in the countries where I have mostly been working). The closest many engineering graduates will ever get to an experiment is a CAD design or perhaps a 3D printed prototype.

Therefore it is necessary for a range of these innovation and technology support centres to assist companies at various hierarchical levels to experiment.

At the functional or operational level, organising for experimentation involves:

  • creating teams from different operational backgrounds
  • creating multiple teams working on the same problem
  • getting different teams to pursue different approaches
  • failing in parallel and then regularly comparing results
  • failing faster by using iterations, physical prototypes and mock-ups.

According to Thomke, results should be anticipated and exploited – even before the results are confirmed.

At a higher management level, organising for experimentation involves:

  • Changing measurement systems not only to reward success, but to encourage the trying of new things (thus encouraging learning and not discouraging failure).
  • Moving from expert opinion to allow naivety and creativity.
  • Preparing for ideas and results that may point to management failures or inefficiencies elsewhere in the firm (e.g. improving a process may be hampered by a company policy from the finance department).

Getting multiple companies and supporting organisations to experiment together is of course a little more difficult. Management of different organisations have many reasons to conceal failures, thus undermining collective learning. One way around this could be to use a panel or collective of companies to identify a range of experiments, and then to have these experiments conducted at the supporting institution in a transparent way. All the results (successes, failures and variable results) are carefully documented and shared with the companies. However, to get the manufacturers to use these new ideas may require some incentives. In my experience, this works much better in a competitive environment, where companies are under pressure to use new ideas to gain an advantage. In industries with poor dynamism and low competition, new ideas are often not leveraged because it simply takes too much effort to be different.

Promising ideas from experiments can be combined and integrated after several iterations to create working prototypes. Here the challenge is to help industries to think small. First get the prototype process to work on a small scale and at lower cost before going to large scale of testing several variables simultaneously. An important heuristic is to prototype on as small a scale as possible while keeping the key mechanical or scientific properties consistent. More about this in a later post. (Or perhaps some of the people I have helped recently would not mind sharing their experience in the comments section?)

I know that this is already a long post, but I should like to add that Dave Snowden promotes Safe2fail probes, where teams are forced to design a range of experiments going in a variety of directions even if failure is certain in some instances. In my experience this really works well. It breaks the linear thinking that often dominates the technical and manufacturing industries by acknowledging that, while there may be preferred solutions, alternatives and especially naive experiments should be included in the overall portfolio. To make this work it is really important that the teams report back regularly on their learning and results, and that all the teams together decide which solutions worked best within the context.

 

Source:

THOMKE, S.H. 2003.  Experimentation matters: Unlocking the potential of new technologies for innovation. Harvard Business Press.