Illustrating how opening up the R&D machinery is different and beneficial

The implementation of open innovation as a way to interact with external research is of growing interest as more and more realize that innovation is too complex to be mastered by your own. However, the level of openness vary to a great extent and also depends on the intention by the one opening up. This post illustrates four different stages of opening up research in the pharmaceutical industry, but can be applied in any research-heavy industry.
The perspective is from pharmaceutical R&D looking to improve how external innovation is achieved using the fairly new model of open innovation. The factory (figures) illustrates the pharma R&D engine and the person outside is a biotech, start-up, other pharma company, academic researcher, patients or even a citizen scientist — any external party.
The purpose of this post is to provide easily understood pictures of what open innovation actually could and should mean for R&D-heavy industries such as pharma.

First stage — Protective and Closed

The initial stage is exemplified by a traditionally closed company not actively seeking engagement from external partners. The first choice is using internal competences and the attitude is usually “we know best and don’t really need external input”. In some cases this might very well be true, especially for larger corporations that can still manage to hire the absolute top people, but when it comes to the rapidly evolving new technologies it is going to be really difficult to internalize and master edge science and new technologies. At this stage the external world is difficult to relate to and the current business operation model is protected. It is also very difficult for an external party to interact and provide valuable opportunities.

Second stage — Restrictive and Cautions

Atthis stage of implementation the innovation seeker (often the corporate R&D unit) is exploring how to engage with external partners. Traditionally specific needs are outsources, but great care is taken in order to minimize disclosure of internal knowledge and maintain full control of the process. New solutions can be acquired this way, but usually only solutions that are similar to those already existing internally. It is still rather difficult for an external partner to understand what will be relevant and the result is often a decline of interest. The innovation seeker have to spend significant amount of resources understanding who to invite in, all while making an effort of not disclosing too much.

Third stage — Opportunistic and Hopeful

The third stage is when the true powers of open innovation are starting to get unleashed. The internal R&D unit has recognized the value of interacting with external parties as means to explore and evaluate completely new opportunities. By utilizing a transparent interface the external party can identify ways to create value for the innovation seeker. The R&D factory discloses interests, needs or challenges in addition to providing some kind of value for the external participant. This could be a reward (usually the case in crowd sourcing), but also tools, models for scientific exploration and data. The key is transparency and providing mutual benefits to the participants, but there is usually still a concern of disclosing information that can be utilized by competitors. The ‘door is open’ so that external parties can get an idea of what is going on and how to connect.

Fourth stage — Participatory and Integrated

Byknocking down the wall, this R&D factory embraces external participation by active design. Being transparent and disclosing (at least part of) the internal research machinery and reducing barriers of engagement is a way to actively increase the chances of having relevant parties engaging and creating vale. As illustrated by the ‘conveyor belt’ machinery new opportunities can easily flow into the R&D factory, but only if they fit the predefined criteria which is why it is important to be transparent about what is desired and sought for. This level of integration with the external world can provide innovation you didn’t even know you could ask for. The ‘cost’ is to accept loss of control in the way that there are no business terms that will limit external participants in any way, in addition to providing mutual benefits and disclosing e.g. needs, science and/or intentions — information that could potentially be used by competitors.
This models relies on open source and open science in order to achieve open innovation where external parties can identify ways to create value for someone else and get rewarded for it. The mindset is ecosystem thinking where you as an R&D-heavy organisation has realized that successful innovation requires external collaboration and unconditional feeding into the ecosystem is critical in order to get something out of it.

Turning science into innovation is too complex to be mastered by your own and in an exponential world of new technologies and information it is critical to adapt a model where external collaborations happen per default. But the actual implementation of open innovation requires critical change in how we conduct science business and rethinking legal conditions, business terms, intellectual ownership and the general rules of engagement is now a must for success.

The author has designed and implemented open innovation in the pharmaceutical R&D industry and is personally convinced that strong disruptive forces are nearing the pharma industry that will greatly improve how we translate research into patient solutions.

Source : https://medium.com/@endnilsson/evolutionary-steps-of-open-innovation-2aaa0ee2454b