Scaling down our corporate incubator was right because we did not loose our innovation expertise
Updated: Feb 17
The title is provocative of course and relate more to a successful pivot of our organisation, initiated 18 months ago.
So, first let look back seven years ago, when I joined one the Europe's state of the art corporate incubator, internal venture builder, intrapreneur start-up studio, you name it... After two major reshaping of the activities, a third and recent wave got finally our model totally pivoted into a very different setting. This was not very well accepted by the collaborators who dedicated hard work to build up a strong pipeline of projects... but looking at it today, I am convinced that was definitively the right thing to do.
One of the reason behind my positive viewpoint is the drive from our new Chief Technology Officer who came initially from semi-conductor industry and was capable to perceived two inflections a bit ahead of our pharma and life science industry - the first one being the refocus of tech giant business model as B2B technology infrastructure to our industries (Microsoft Azure, AWS, Google Cloud...), the second being the combination of deep technologies such as biotech, electronics and computation to solve scientific and engineering bottleneck i.e. "predicting protein folding" mixing X-ray diffraction and cryo electron microscopy crystallography data with AI.
In the first part of the article, I'll explain the reason for scaling down our incubator and then in the second part, I'll focus on the risk to reshape our model without leveraging the real reasons that make a corporate incubator an impactful engine for the company's current and future growth.
Disruption danger with Innovation Sheriff gone!
No worries, new one will enter the saloon soon.
Ten years ago, back in 2013, the DAX 30 CEOs could read in the news
An interview of Larry Page, CEO of Google stating: "We ended 2013 with another great quarter of momentum and growth. Google's standalone revenue was up 22% year on year, at $15.7 billion"
An announcement that Airbnb reached 10 Million booking just 5 years incubated after being incubated at Y combinator
Almost suddenly, two companies ignored by the industry's elite, were generating better financial performances or growth than most of the DAX 30 companies. Even worst, those new entrants were challenging our own industries core business models with the risk to make them obsolete.
To face this paradigm change, many large companies CEOs had to react! Back in 2015, they have launched their innovation labs to identify internal ventures, rethink their business model from inside, learn from the surrounding start-up ecosystems and understand the adoption of digitalisation and its impact on their customers. The vision and objectives were correct and the innovation labs have started to source, generate and incubate concepts that they have further derisked into business projects. At that time, the expected return on investment from the top management was to have mechanisms to foresee business inflections and to get enough "time" to prepare options to survive external disruption.
It took five years to build an holistic engine, be part of internal key networks and external innovation ecosystems. We became this transverse organisation capable to identify before anyone a customer problem in one of our business units, a spectrum of solutions in the innovation ecosystem and combine proprietary buildings blocks in another part of the company to create a unique advantage. We were creating a significant impact in attracting the outside word "light" inside some business units... and in bridging the gap between R&D and commercial departments silos. We had a multiplicative effects, after running hundred programs with thousands of participants and key advisors, we could quickly assemble a coalition before an inflection point was unveiling to the majority of the industry and already have something prepared to react. We built a pipeline of over 100 internal venture candidates, invested more than 50 million euros in over 20 of them with several launched to the market generating significant revenue.
But, at the end, the digital giants and start-ups did not disrupt nor took over our good old industry. Our "defending unit" was obsolete. At the same time the financial return of our internal ventures engine had unnoticed effect on the core business top line, being quickly seen as a useless "attacking unit". Finally, the top executives who contracted us our mandate were gone and the rich context of international crisis created more urgent priorities for new management board.
When "defending" and "attacking" Innovation disruptors did not make sense anymore for the company's executives, it sent the signal that it was time to scale down our corporate incubator.
Defending unit against the disruption
First learning - digital disruptors got disrupted
Do you remember Verily, Calico, Onduo, Haven health, Galvani, ..? From 2015, we believed Google, Amazon, Tencent or Apple would revolutionise the pharma and life science and medical industries. We believed that a new entrant could build a new pharmaceutical giant in less than 5 years with a disruptive business model. This did not happen, those companies had to stay focus on their core and even failed so far in reinventing themselves. We see today how Facebook struggles in its Meta(verse) transformation and how Google's whole business model is challenged by ChatGPT's Microsoft.
What digital giants got possibly wrong, is that our industry companies owned their use cases and what problem to solve for their customers anf for themselves. It was just a matter of time to learn the digital technology part, therefore, instead of becoming competitors, the digital giants have become key partners. They have commoditised their core computational technology as B2B offering to strengthen leading industry companies. Within the last 10 years some industry players have built their knowledge and expertise on how to integrate digital technology at every level of their organisation, for streamlining their manufacturing, for forecasting their sales. It took some years, but today our industries have become data mature and data driven organisations. They have built significant competitive advantages at all layers of their company. The competition therefore is not between classical industry and digital giants but rather between industry giants themselves supported by their underlying digital technology partners.
Second learning - the next inflection is yet to come
The key of owning the use case and integrating digital technology is just the tip of the iceberg of the soon to come next markets disruptions. Below the water, in front of everyone, the convergence of technologies is happening. Here we are talking about deeptech, the interface of science, engineering and design. A topic far more difficult for a band of programmers to tackle from their garage. We talk about biotechnology, meeting material science, meeting advanced computational capabilities... sounds crazy...
Maybe not, if I talk about genetic tested driven AI for RNA sequence synthesis and encapsulated into nano-objects injected a billion times in human beings. Having been involved in the framing a very similar deeptech convergence topic, I can ensure that you can't succed by only assembling a bunch of innovation projects. You have to think in term of platform of interconnected building blocks and some unique proprietary elements that allows you to capture massive value along the way.
I personally initiated a technology radar initiative at the company level, a year ago, to identify deeptech convergence. This was successfully taken over and operationalized by our scout department. This is a sign that industry companies are nowadays doubling down their effort in preparing for this next disruption wave and this explains why some industries are making strategic moves today to build a new kind of deeptech innovation labs.
Attacking unit becoming the disruptor
Third learning - innovation projects financial metrics will kill your incubator
Your unique value proposition is to understand inflections before they become disruption, and help your current business to adapt. This can not be turned easily into a metric. Therefore, when you think about it, having a scouting department, a start-up partnership program and an internal venture incubator, overall creates a lot of overheads and spendings. The strategy department, we belonged to, had explained well that over a 10 years period, for 50Bn€ invested in M&A, 10Bn€ dedicated to R&D, there was only 100Mn€ spent for the forefront disruption overwatch.
But no corporation would accept sunk costs for too long. With no disruption happening, the lengthy Return On Investment metrics soon got hacked by the finance department. Our business cases were strong, clear with calculated risks and estimated significant upside. However, pure financial KPIs created a distortion for our promising internal ventures on two of their potential exits:
The first type of exit is the transfer to an existing Business Unit. For every candidates in this exercise, they would rarely survive the comparison with other capex investments or small targeted M&A. Since most of those innovation projects were carrying too much uncertainty, to meet the return expectations in the short to mid term, they were therefore in most of the cases deprioritized.
The second type of exit consist in creating a spin-off or a joint-venture with an initial investment form our corporate venture capital arm. In the current case, our innovation projects would compete with hundreds of mature start-ups to invest in, again many good reasons not to invest.
Of course among our 20 ventures incubated, two or three would still make the headline of our intranet and communicate as a success story and see few colleagues promoted. But for the other one, such financial measuring bias was the "coup de grace" that killed our incubator model.
Fourth learning - your job is to widen a portfolio of options for current business units
While venture capital can rely on a relevant deal flow model, corporate incubators have only a limited number of concepts to explore that will dry very soon when explored as a pipeline. The model that I witness having successful impact is the platform one. Behind platform you have the necessary critical mass of bundling projects or uses cases with some economy of scale.
A platform is more specific than a megatrend field. un a top-down logic, you can easily define quantify its business potential in term of total addressable market and build a strategic roadmap around it, you would secure budget along this roadmap and report overall progress to senior management and avoid the pitfall of single projects valuation
A platform is less detailed than a single project. In a bottom-up approach, it usually consist in learning concrete facts from a bundle of 3 to 5 projects that combined can't be judged on the financial metrics. Kill one of its underlying projects and 3 new ones will take place, with an easy repositioning of the talented contributors... this is called a reverse pipeline
A platform plays a specific role in a portfolio and provide optionality to your current business units. The overall strategy of a platform for understanding future markets would help your business units to adapt their preferred path in case of inflection. The several underneath projects at the bottom, would help to understand in real time how your customers and ecosystem reacts. In a transverse manner, a platform would be finally an occasion to bind a strategic industry partner to promote the adoption of new standards and share some risks
You just need a few platforms very well positioned in a portfolio. Their value in creating options should be clear for the business units heads:
contribute to learn new customer behaviors
derisk deep technolgies
maximise novel business model value capture
...
To conclude
Maybe one of our mistake 7 years ago was to innitiate our deeptech innovation lab too early with much more expensive learning cycles than the usual digital ones while underestimating the acceleration in Data & Analytics. Sometime first mover advantage doesn't pay off: see innovation copilots blog.
Fortunately, with our most recent transformation we strengthen both our defense and attack. We moved away from the "explore exploit" fallacy, we have dropped the inefficient projects pipeline logic and replaced it by a portfolio of platforms having each one a clear ROI in generating optionality for the current business units.
First, we have a very well staffed Data Office and first class infrastructure with key technology partners associated in order to tackle an endless amount of uses cases and build an advantage against direct industry competitors
Second, we focus on initiating 3 to 5 wider platforms that are providing regular technology and market insights to the current business unit's heads as a well perceived return on investment and additional options to create future revenue streams when next inflection wave will come
Even if this logic is now in place and has been shared to many internal stakeholders and decision makers, I still see several risk for this effort to be vain:
The logic/vision behind the last organization pivot hasn't been communicated as such nor explained to the innovation organisation's employees
The recently hired managers may not be familiar with those innovation management logics and still seem stuck in daily operations or lengthly business plan write-up
Most of ongoing platforms adopt only a top-down logic, incapable of learning from individual projects nor capable in attracting strategic partners. Even worse, the few successful platform owners have not been approached to share their key learnings and best practices.
It is just a matter of time before we loose our momentum, our pivot was necessary and the organisation is now on track.
However, by not mastering our platform portfolio logic we will put current business at risk of being disrupted by the soon to come deeptech inflection wave.
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For more general explanation on those logics, I recommend the Innovation Copilots podcast