Scaling Open Innovation

Partnering up to solve grand challenges is the only way to go. You spread the risk, access new perspectives, open up new resourcing models, and tap into scalable R&D. It is not easy, but it is becoming easier thanks to new types of European and national funding instruments combined with more acceptance across ecosystems of organisations. Siloed approaches to creativity of new products and services tether the imagination to the organisation chart and short-term measurements.

Open Innovation also does more than solve the particular challenge for which the consortium was formed. It also opens up new value chains between consortium partners which were unimagined before the collaboration kicked off. It creates multiple “App Store” moments. At Spinverse, we see this on a daily basis where our European partners from corporates, SMEs, startups, RTOs and universities discover new combinations of technologies and unleash creative business models across multiple markets.

How to accelerate value creation beyond the original concept

But this blog is not about creating new technologies. It is about scaling. It is about how we can accelerate the value creation beyond even the original concept for the consortium. Scaling is not only a factor of how cool and innovative the new technology is. Its potential value has to be understood by early adopters, who will “take some risk” and help to commercialise these new capabilities. It could also be a set of non-profit or societal benefits that are to be accrued. Either way, someone has to take the risk to get behind it. Risk, of course, is relative. We should also understand that it may require additional catalysts for it to really scale as a service. It may require a platform which allows new, unidentified players to come in and build on the new capabilities. No one has a monopoly on business model insights.

Aside from the spreadsheets and Business Model Canvases (BMC) needed to figure out how to scale something new, the organisation (or value chain) needs some special characteristics. Examples of tools that come in handy in scaling can include imagination, grasping, seeing, feeling…and the underappreciated skill of situational awareness and the “adjacent possible”. Not all of these characteristics may be available in a single organisation. This is where the open organisational approach to scaling comes in.

Obvious new business models are just waiting to be discovered

Let’s dive into a couple of “obvious” new business models waiting for the right combination of organisations to bring to the market at scale technologies that already exist.

Exhibit A: Agricultural data. In many countries farmers and their suppliers are learning the value of digitising their businesses. They are using combinations of land and air robotics (drones) for inspections, harvesting, planting and other tasks. They are able to get real-time data from these machines, combine that with weather and satellite imagery and make faster decisions to improve the efficiencies and yields of their crops. Adding AR/VR into the mix affords a new layer of control and simulation.

Many of these initiatives are being deployed in a fragmented way. But what if all of this agricultural data could somehow be scaled at a national level? What if we took the same approach to agricultural data that the Finns have taken to Healthcare data?

Farming is a risk-intensive industry. Technology, if deployed effectively and in a cost-effective way, can offset some risk but not all of it.

Enter the Bank. In some countries, banks lend a significant amount of money to farms that helps them manage their harvesting cycles and operational models. Banks, especially at a regional level, know a lot about their customers’ needs. Banks are also searching for new service lines to create. A bank that provides funding to farms could also choose to provide agricultural data services back to the farms and supply chains.

The economic value of all the agricultural data in a region or country is enormous (and probably not yet fully appreciated). If the bank had access to agricultural data, then it would be able to manage its risk and offer insights back to the farms to improve yields. Naturally, the bank would require an ecosystem of partners to gather, store, analyse and offer the data. This scalable ecosystem could encompass drone service providers, IT companies, universities and research, and specialist agricultural organisations. The bank could be a catalyst that could help to monetise vast sums of agriculture data at a national level for economic, societal and climate-related benefits.

There is no real magic involved in building this. Other than “grasping”.

Exhibit B: Sea Port digitisation. Sea ports are complex environments which feed into the arteries of a national economy. They fuel the movement of people and goods into and out of a country. They are perfect locations for digitisation and automation, and many sea ports and organisations are accelerating projects to solve economic and climate-related challenges.

What if an ecosystem of organisations had access to all of the sea port data (appropriately secured and access-controlled)? How could logistical supply chains, port operators, cities and government institutions benefit from such a vast treasure trove? What economic modelling could be run in near real-time speeding up decisions at multiple levels?

An open innovation approach to scaling (or deploying) multiple streams of rapidly emerging technologies is one of the most exciting opportunities available.

At Spinverse we help ecosystems figure out how to grasp it.